University of Windsor

Essex Hall Study

Final Report

Eric Mintz, PhD

September, 2008

Table of Contents

Executive Summary...................................................................................................................i 1. Background and Pilot Study...............................................................................................i 2. Methods .............................................................................................................................i 3. Results and Discussion..................................................................................................... ii 4. Conclusions .....................................................................................................................v

Main Report ............................................................................................................................. 1 A. Background ......................................................................................................................... 1

a. Introduction ................................................................................................................... 1 b. Pilot Study........................................................................................................................ 1 c. Possible Exposures.......................................................................................................... 1

d. Rationale for Further Study .......................................................................................... 2 B. Literature Overview ............................................................................................................. 4

a. Definitions and Descriptive Epidemiology..................................................................... 4 b. Etiology ......................................................................................................................... 5

C. Methods ............................................................................................................................. 7 a. Study Population.............................................................................................................. 8

D. Limitations......................................................................................................................... 10 a. General .......................................................................................................................... 10 b. Study Specific ................................................................................................................ 11

1. Power considerations ................................................................................................ 11 2. Data base irregularities .............................................................................................. 12 3. Limited exposure data ................................................................................................ 13

E. Sources of Bias ................................................................................................................. 14 a. Misclassification by disease........................................................................................... 14 b. Misclassification by exposure ........................................................................................ 14 c. Migration ........................................................................................................................ 14 d. standard rates ................................................................................................................ 14 e. Healthy Worker Effect .................................................................................................... 15

F. Burden of Proof ................................................................................................................. 16 G. Results – Background....................................................................................................... 18

a. Characteristics of the study cohort................................................................................. 18 i. Starting date............................................................................................................ 18 ii. Person-Years............................................................................................................. 18

b. Standard populations – some considerations ................................................................ 18 H. Results .............................................................................................................................. 20

a. Interpretive Caution .................................................................................................... 20 b. Entire Cohort .................................................................................................................. 20

i. All cancers combined (total cancer) ............................................................................ 20 ii. Individual Cancers of interest (males only) ................................................................. 21

c. Analyses by workplace................................................................................................... 23 d. Analyses by start date - pre-post 1990 ....................................................................... 25 e. Analyses by start date - pre-post 1985 .......................................................................... 26

I. Discussion .......................................................................................................................... 28 J. Conclusions ....................................................................................................................... 35 References ............................................................................................................................ 37

Executive Summary

1. Background and Pilot Study An apparent occupational cancer cluster is a perceived excess of cancer that appears in a work population or subgroup over a given time period. Often an investigation is initiated, as in this case, by a belief among workers that all or some of their coworkers are experiencing more than the normal amount of cancer. In 2003, the University of Windsor expressed concern about an apparently unusual number of cancers that had occurred in workers from South Essex Hall. A preliminary, pilot study, verified the initial cancers of concern by running the six involved names through the Cancer Care Ontario (CCO) Registry. The presence of cases of multiple myeloma, Waldenstrom's macroglobulemia and chronic myeloid leukemia (CML) warranted an epidemiological study. All three are uncommon disorders of blood cells originating in the bone marrow. While no general, pertinent occupational exposures can be verified, workers described the air quality as being very poor before the ventilation improvements were done in the 1990s, during an initial meeting with union representatives, and University of Windsor stakeholders. The building is located very close to the on ramp of the Ambassador Bridge. Due to heavy truck and auto traffic and slow speeds, exposure to exhaust, both diesel and gasoline, was thought by some workers to be very heavy, particularly in South Essex Hall. As well, there were several tool and die workers employed in South Essex Hall before 1990. Tool and die workers are exposed to metalworking fluids (MWFs) for which there is evidence linking them to several cancers (26).

2. Methods This is a historical cohort study where workers were identified by past employment records and followed forward in time, to trace cancer development. Standardized Incidence Ratios (SIRs) were calculated on the historical cohort of workers who started work in Essex Hall at any time between 1955 and 2005. Standardized Incidence Ratios (SIRs) were constructed for total cancers and individual cancers (or related groups of cancers) where numbers permitted. The person-years of exposure partitioned by age and sex were calculated using the human resource data base of workers in Essex Hall. Analyses were done using both Windsor-Essex 1986/1996 and Ontario age-specific cancer incident rates from 1986/1996 to calculate the expected number of cancers.

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The observed cancers were compared to the expected cancers using the SIR as follows:

SIR = observed/expected where: observed - the number of cases of the cancer of interest that developed in the work cohort as ascertained from linkage with CCO records expected - the number of cancers that would have occurred in the worker population if they were getting cancer at the same rate as the standard population

Therefore an SIR of 1 means that the worker population is getting cancer at the same rate as the standard population (Windsor-Essex or province of Ontario). We say that they are getting cancer at the “expected” rate. An SIR of 2 means that the worker population is getting cancer at twice the expected rate. They developed two cancers for every one expected. This signifies, of course, that there may be a problem. Analyses were done separately for those who worked in North Essex Hall and South Essex Hall. Similarly, SIRs were computed separately for those who started before 1990 (and 1985) and those that started work after those dates. Ninety percent approximate confidence intervals were calculated and presented for all SIRs (6).

Study Population The study population was to comprise all of those who started work in Essex Hall during the time period of 1955 to 2005. The work roster was incomplete however, as those who began work before 1985 were included in the roster only if they were still actively working during 1985 or thereafter. These problems arose because only current workers were transferred to an updated human resources database in 1985.

3. Results and Discussion Total Cancer Workers in the entire Essex Hall work cohort experienced cancer at only about 60% of the expected rates, based on either standard. These results were statistically significant at the 5% level, meaning we are quite sure that the SIRs are truly less than one. This

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result held for both males and females, although the female results were not statistically significant, since they were based on much smaller numbers. Partitioning the data by starting date or work location in Essex Hall (for males only) produced similar results even though those who started work before 1985 or 1990 had higher SIRs than those who started work after those dates. Comparison of the early start group SIRs to the later start groups SIRs is dubious because the later groups were younger. Differences noted in the SIRs may be due to differences in the worker age-distribution or due to differing cancer risk of a combination of both. Workers in South Essex Hall showed slightly higher SIRs than those calculated for workers in North Essex Hall. An important question is why would the total cancer rates be so low? It is possible that there has been incomplete ascertainment of cancer cases for some reason, including high post retirement migration rates. Also, especially in the very recent past, CCOs records may not be complete. .A major reason for the very low overall cancer rate is the large deficit of lung cancer from the expected rate. Workers in Essex Hall developed lung cancer at only about 20 percent of the standard rates. Stated differently, only about one lung cancer case developed for every five expected. This statistically significant finding is quite dramatic. Since we know that the large majority of lung cancers are attributable to smoking (16), it follows that smoking rates were probably very low in this cohort. If true, this low smoking rate could explain much of the departure from expected cancer rates, since smoking is a risk factor for several cancers besides lung cancer.

Multiple Myeloma Only two cases of multiple myeloma occurred in this cohort However, since this is a relatively rare disease, even two cases constitute an somewhat unusual event statistically (p<.10) overall. Furthermore, one of the cases was actually Waldenstrom’s which is an even rarer variant. This case occurred in a 37 year old man, while the vast majority of Waldenstrom’s occurs in men over 60. Multiple myeloma is also a disease of older people having a similar, very steep risk curve with increasing age (13). Both myeloma cases occurred in South Essex Hall workers who started work before 1985. This is what we would expect if myeloma was associated with alleged exposures that were more marked before the late 1990s in South Essex Hall. The results of the study are consistent with an increased rate of multiple myeloma that is concordant with a relationship to work related exposures.

It should be noted that the knowledge of the causes of multiple myeloma and Waldenstrom’s are limited. But two suspected causes for multiple myeloma are radiation and diesel fume exposures, for which the evidence is more conclusive in support of radiation. Although some South Essex Hall workers related radiation exposures, the most pertinent, general exposure, although speculative, here is probably diesel fumes.

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Ecological studies, such as this one, may establish associations between exposures and subsequent development of disease. Causal links are rarely established, because by definition no information is available regarding previous occupational exposures, lifestyle risk factors (e.g. smoking), family history, and other risk factors for disease. Only occasionally if there is good occupational hygiene history of a “smoking gun” (a well established exposure to a known cause of the disease being studied) and the results are very strong and consistent, a probable causal link may be inferred. The causal inference would require other causal criteria such as dose-response to be satisfied as well. But in this study there is no occupational hygiene data from the historical period in question. As well, diesel fumes are a suspected, but not an established causal factor for multiple myeloma. Furthermore, the data is very limited. The results of this study fall far short of being sufficient to establish a causative relationship between working in South Essex Hall and the development of multiple myeloma and Waldenstrom’s. This study shows a statistical excess of multiple myeloma in South Essex Hall. If Waldenstrom’s was analysed separately then Waldenstrom’s showed a strong statistical excess. No matter how these cases were divided, the development of these two cases in this work cohort was a somewhat uncommon event statistically. The evidence is far too limited, however, to infer a causal link, although one may exist. There are three possible explanations for the statistical excess of multiple myeloma. 1. The results occurred by chance, even though they are statistically significant. The

precise probability of getting this result by chance is not possible to determine for the reasons outlined in this report.

2. There is a true excess, but it is not related to exposures in Essex Hall. One or

both of the workers in question may have been exposed in prior occupational or medical settings or as part of their lifestyles. They may also have a predisposition to develop these cancers.

3. There is a true excess and it is related to occupational exposures in South Essex

Hall. These exposures may be general, experienced by most or all workers in South Essex Hall or they may be more limited, for example, to tool and die workers.

Since we lack historical occupational hygiene data, etiological research for multiple myeloma has not strongly pointed to specific causes and we have very limited data, which is insufficient to further investigate causation, it is not possible to determine which of these scenarios is most likely. Chronic Myeloid Leukemia (CML) Only one case of CML developed in this cohort, however, it is a somewhat unusual statistical event, as well, particularly when the more stable Ontario standard rates were used. Although CML is a distinct condition, Waldenstrom’s and multiple myeloma are

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similar in that they are all disorders of blood cells originating in the bone marrow. The development of these three rare cancers, that share important characteristics, taken together, is suggestive of pertinent exposures. Furthermore, all three cancers occurred in men who started work in South Essex Hall workers who started before 1985. The evidence is not nearly sufficient, however, to infer a causal link to exposures in South Essex Hall, for reasons discussed earlier.

Pattern The pattern of cancer development in this cohort differed from the expected pattern. Only about 2.5% of all cancers that developed were expected to be either myeloma or CML, using the expected values computed from the Windsor-Essex standard (Table 3). These rarer cancers, however, actually accounted for 11.1% (3/27) of the cancers that developed in the work cohort. The common cancers, lung and colon cancer, were expected to account for 29.4% of total cancers. However, they also accounted for only 11.1% (3/27) of the observed cancers. There was a marked excess of the three rarer cancers over the expected and a clear deficit of these two common cancers. Although, these proportions are not independent, the pattern is unusual, for these rare and related cancers to have the same incidence as the two common cancers. Tool and Die Work

There were 10 confirmed tool and die workers who started work in South Essex Hall before 1990. Two of the three rare cancers of interest occurred in this small group. While this result may have been a chance event, it may also be due to exposures to metalworking fluids (MWFs) encountered by these workers. While some MWFs are established carcinogens, the evidence for a link to the rare cancers encountered here is presently equivocal (26). Along with the very small number of these workers and the lack of knowledge regarding specific exposures that these workers encountered, it is not possible to determine if the excess of these rare cancers was due primary to MWF exposures.

4. Conclusions 1. The total (all cancers combined) cancer rates experienced by Essex Hall workers who

began work between 1955 and 2005, was dramatically lower than the cancer rates of the general population of Windsor-Essex (p<.05). In fact, these workers developed cancer at only ½ to 2/3 the rate of the Windsor-Essex standard population.

2. Male total cancer rates held at two thirds of the standard rates or less, regardless of

whether they worked in South or North Essex Hall.

3. Male total cancer rates held at two thirds of the standard rates or less, regardless of whether they started work before or after 1990.

4. It follows from 1. to 3. above that the results of this study do not support any excess

of total cancer in this work group. In fact, they point more to a deficit of total cancer.

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5. It is very unlikely that the Healthy Worker Effect (HWE) explains a large portion of the

low cancer rates described in 1. to 3. above. 6. Male lung cancer rates, for the entire cohort, were found to be only about 20 percent

of expected rates (p<.05). Stated differently, Essex Hall male workers developed only 1 lung cancer for every 5 lung cancers that occurred in similar males in Windsor-Essex.

7. Since smoking is a dominant cause of lung cancer, it is a reasonable implication that

this cohort of workers had low smoking rates. The reason for these low rates is not known but may be due to ethno-cultural factors or socioeconomic or other factors.

8. Since smoking is also causally related to many other cancers, low smoking rates likely contribute to most of the deficit of cancer that developed in the cohort.

9. Ecological studies, such as this one, are blunt tools and therefore do not generally provide strong evidence for a causative relationship between an exposure and disease. This is particularly true, since there is no “smoking gun” in this study. A smoking gun is a well-established causal factor for a disease that workers were known to be exposed.

10. Although SIRs for prostate cancer generally showed a slight elevation, none was statistically significant. Those who started working in Essex Hall before 1985 had the highest SIR. There were not many person-years in the highest risk age groups for prostate cancer in the post 1985 start date group making comparisons to the earlier start date group somewhat tenuous.

11. The small number of recorded workers who started work before 1985 hamper somewhat the ability of the study to evaluate exposures in Essex Hall. It is also evident that since some cancers can take up to 25 years to develop, that follow-up time may not be sufficient to identify many work related cancers in workers who started after 1985 and particularly after 1990.

12. The records of many workers who started work before 1985 were unavailable for analyses which added additional uncertainty to interpretation of study results.

13. It is difficult to decide how best to classify the Waldenstrom’s case given the circumstances outlined in the report. The development of even one Waldenstrom’s in a group this size is unexpected, as it is an extremely rare condition. When analysed separately, the Waldenstrom’s SIR was very high at more than 23 (p<.05). This high SIR is due to the rareness of Waldenstrom’s.

14. This study shows a statistical significant excess of multiple myeloma (when the Waldenstrom’s was counted as a myeloma) in South Essex Hall that was consistent with a causal link to exposures in South Essex Hall. The sum of the statistical and exposure data is too weak to differentiate between the possibilities that the excess of multiple myeloma was a chance finding, was a true finding but not due to Essex Hall exposures, or a true finding due to Essex Hall exposures.

15. Whether the Waldenstrom’s was analysed separately or as a myeloma, the occurrence of these two rare cancers was a somewhat unusual statistical event.

16. Although only one case of CML developed in this cohort, it is a somewhat unusual statistical event, as well, particularly when the more stable Ontario standard rates

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were used. Although CML is a distinct condition, Waldenstrom’s and multiple myeloma are similar in that they are all disorders of blood cells originating in the bone marrow. The development of these three rare cancers, that share important characteristics, taken together, is suggestive of pertinent exposures. Furthermore, all three cancers occurred in men who started work in South Essex Hall workers who started before 1985. The evidence is not nearly sufficient, however, to infer a causal link to exposures in South Essex Hall.

17. The pattern of cancer development was unusual in this cohort as the number of the three rarer tumours originating in the bone marrow was equal to the number of the much more common lung and colon cancers. Although they are not independent, the proportion of total cancers that were due to the three rarer tumours was much greater than expected while the proportion of the common cancers was far smaller.

18. The study results suggest that MWF exposures experienced by tool and die workers, may have been largely responsible for the excess of rare cancers noted. The evidence supporting a causal link between tool and die work and the rare cancers, however, is weak and circumstantial. Conclusions are limited by the small number of relevant tool and die workers, and the limited knowledge about the relationship between MWF exposures from this time period and the rare cancers found in this study. Additionally, none of the tool and die workers developed a cancer that is strongly linked to MWFs in the scientific literature.

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Main Report

A. Background

a. Introduction An apparent occupational cancer cluster is a perceived excess of cancer that appears in a work population or subgroup over a given time period. Often an investigation is initiated, as in this case, by a belief among workers that all or some of their coworkers are experiencing more than the normal amount of cancer. In 2003, the University of Windsor expressed concern about an apparently unusual number of cancers that had occurred in workers from South Essex Hall. In an initial meeting in late 2003 (where Dillon Consulting and University of Windsor representatives met), there was a particular concern expressed that two workers with similar job titles and closely located workstations had developed Waldenstrom's and multiple myeloma, respectively. The six cancers presented that gave rise to the initial concern are described below.

b. Pilot Study Date of diagnosis Age at diagnosis Diagnosis Feb 01 50 chronic myeloid leukemia Dec 03 41 adenosarcoma lung large cell Nov 98 52 pancreatic cancer Jul 04 67 multiple myeloma May 96 37 Waldenstrom's macroglobulinemia Jul 01 46 Carcinoid

In a preliminary, pilot study, we have verified the initial cancers of concern by running the six involved names through the Cancer Care Ontario (CCO) Registry. The Registry records all cancers that were diagnosed to residents of Ontario. Consent forms were designed and mailed to the potential study participants. All were signed and returned by the patient or surrogates. Of particular note are cases of multiple myeloma, Waldenstrom's macroglobulemia and chronic myeloid leukemia (CML). All three are disorders of blood cells originating in the bone marrow (see Literature Overview).

c. Possible Exposures There had been concern for some time about ventilation and air quality in South Essex Hall. The University of Windsor first looked at the issue of air quality in the Essex Hall building (particularly the South wing) in 2001. The concerns centred on air quality and specifically a

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concern regarding diesel particulates and metallic dust and mercury, as well as other dust exposures. There were no discussions at that time about a cancer study. In September of 2001, the University contacted Pinchin Environmental to perform the hygiene testing. The air monitoring was completed in February 2002. The results of the air monitoring showed levels below the set limits. There were however, some PCB and mercury present and, in fact, loose mercury found on the floor in one area (1). While diesel particulates were shown to be low, it should be pointed out that testing was done on only 3 days in February 2002. We would expect seasonal variability in diesel particulates. During smoggy periods of the heavy summer driving season one would expect to find, higher readings. More recent testing by Pinchin done in 2007 in mid summer, however, showed diesel particulates to be well below set limits (8). There is concern that the air quality may have been substantially poorer in the past, before some improvements were instituted. In the late 1990s, there were upgrades or additions of several fumehoods in South Essex Hall. Four labs had new exhaust systems installed. New HVAC units were also installed in two labs. While no general, pertinent occupational exposures can be verified, workers described the air quality as being very poor before the ventilation improvements were done in the 1990s, during an initial meeting with union representatives, and University of Windsor stakeholders. The building is located very close to the on ramp of the Ambassador Bridge. Due to heavy truck and auto traffic and slow speeds, exposure to exhaust, both diesel and gasoline, was thought by some workers to be very heavy, particularly in South Essex Hall. As well, there were several tool and die workers employed in South Essex Hall before 1990. Tool and die workers are exposed to metalworking fluids (MWFs) for which there is evidence linking them to several cancers (26).

d. Rationale for Further Study Based on the pilot study, we thought there was sufficient cause to do further study. Our position was based on the following factors: 1. The pattern of recent cancers is suggestive. Particularly the fact that two rare cancers

that may well be causally related occurred in two workers whose work stations were close together in similar job titles. Additionally, one of these cancers occurred in a 37 year old individual, an age at which this disease is exceedingly rare.

2. There is the possibility that before ventilation improvements were made in South Essex

Hall, exposures may have been high due to poor ventilation and proximity to high levels of diesel and gasoline fumes as well as metal dust.

3. Some studies have found associations between diesel fumes and possibly gasoline

fumes exposures and the development of multiple myeloma (3).

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4. The concern that the University of Windsor has expressed and its resolve to clarify the matter. Given the probable exposures and their noted associations with some of the rare cancers, this concern is not unreasonable.

5. The non-invasive nature of the study that poses no risk to the health and little risk to

privacy of the workforce.

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B. Literature Overview

a. Definitions and Descriptive Epidemiology

Three rather uncommon cancers are of particular interest in this study. Multiple myeloma is a tumour of plasma cells, which are a particular type of white blood cell. These cells, that contain no haemoglobin, are made by bone marrow and help the body fight infection and other diseases (12). Normal plasma cells are derived from B-lymphocytes and are typically found within the bone marrow (12). B-lymphocytes are a type of white blood cell that secrete large amount of antibodies (immunoglobulin proteins) that circulate in the blood. Each plasma cell produces only one kind of antibody (monoclonal immunoglobulin) but groups of different plasma cells secrete many kinds of antibodies (polyclonal immunoglobulin) (12). Foreign invaders, normally viruses or bacteria stimulate lymphocytes to become a type of plasma cell that secretes polyclonal antibodies. The antibodies can then attack and neutralize foreign bodies. The term multiple myeloma denotes the condition where tumour cells are found in multiple sites within the bone marrow (12). Monoclonal multiple myeloma cells are overproduced so that they comprise 10 to 80 percent of the cells in the bone marrow in contrast to the 1 percent that these cells comprise of normal bone marrow (12). The result is localized bone destruction, anemia, reduced immunity to infection and kidney damage as well as other effects and symptoms. Waldenstrom's is very similar to multiple myeloma except that it does not produce the bone damage typical of multiple myeloma. Waldenstrom's arises when plasma cells and/or abnormal lymphocytes produce an excess amount of certain large antibodies called immunoglobulin M (20). Chronic myeloid leukemia (CML) is a cancer of the blood producing cells of the bone marrow (21). CML is also sometimes called chronic granulocytic, chronic myelocytic or chronic myelogenous leukemia. Leukemia cells do not function normally and cannot do what normal blood cells do, such as fight infection, thus making leukemia patients more prone to infection. Platelet problems result in leukemia patients being more likely to have unexpected bleeding and to bruise easily (21).

CML is usually associated with a specific gene mutation in a chromosome called the Philadelphia chromosome (21). This mutation is not inherited however. It is acquired due to lifetime exposures. Ionizing radiation is the only established cause of the mutation, although it accounts for the minority of cases (21).

Multiple myeloma is an uncommon cancer but CML is quite rare while Waldenstrom's is extremely rare. Recent Waldenstrom’s incidence rates found in participating cancer registries in the United States were found to average approximately 4.9/1,000,000/year (1000000 person-years) in white men (4). Only about one case is diagnosed per year for every 200,000 white men in the United States.

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It is even rarer in younger people as most cases occur in those 60 or older. The case that developed in a South Essex Hall employee was notable for the young age at diagnosis of 37. The age–specific rate for those under 45 was estimated to be less than .5/1,000,000 per year. Only about one case of Waldenstrom’s was diagnosed for every two million white men per year in the United States under 45. Clearly, Waldenstrom’s is extremely rare in younger men. Both Waldenstrom’s and multiple myeloma show a similar, very steep increasing incidence with increasing age (13).

In 2001, for every 100,000 white males there were only about 6 cases of multiple myeloma diagnosed in the USA and 1.9 cases of CML (24). Note that although it is uncommon, multiple myeloma occurs, in white men, at more than 10 times the rate of Waldenstrom's (13). Windsor-Essex CML crude incident rates (from 1986/1996 combined) were very high (calculated from CCO statistics). The CML rate was 6.38/100,000/year. Notice that this is more than 3 times the United States national rate of 2000-2004. The Ontario crude CML rate was similar to the United States rate at 2.20/100,000/year. The 1986/1996 crude incidence rate of multiple myeloma in Ontario men was 6.35/100,000/year. This is just slightly higher than the recent United States rate. The corresponding rate for Windsor-Essex 1986/1996 was found to be 6.38/100,000/year. While multiple myeloma incidence rates were very similar in Ontario and Windsor, the CML rates were very different. The Windsor-Essex CML rates, however, were very volatile, as expected, being about three times higher in 1996 than in 1986. Therefore, the Windsor-Essex rates are not statistically stable for this cancer. Age-adjusted Waldenstrom’s incidence rates in the United States over a 7 year period from 1988 to 1994 were found to be higher for whites than for blacks in contrast to the racial pattern found in multiple myeloma where blacks have about double the rate of whites (13). Since both multiple myeloma and Waldenstrom's are thought to be derived from B cells at a late state of maturation, the racial pattern disparity is interesting (13). Specifically, if multiple myeloma and Waldenstrom’s have similar causation we would expect similar racial risk patterns for both diseases. The apparent contrasting racial patterns between myeloma and Waldenstrom’s could be due to surveillance bias. Since Waldenstrom’s is very rare and not fully understood, it is prone to under-ascertainment and diagnostic errors. The ascertainment may be lower for blacks who generally have access to poorer medical care in the United States.

b. Etiology

Comparatively little is known about either the risk factors or the incidence of Waldenstrom's (13). It was only discovered in 1944 and was not a reportable disease in the United States until 1988 (13). The only readily available incidence data comes from two American studies that look at overlapping data (13, 4). The more comprehensive study, referred to earlier, compiled reported Waldenstrom's incidence data gathered from 11 population

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based Cancer Registries in the United States. They found a total of 624 cases between 1988 to 1994 inclusive (13).

Since myeloma and Waldenstrom’s are closely related conditions, it is reasonable to assume that they probably share, at least some causal factors. Supportive evidence at this point is limited, because our knowledge is mostly inconclusive about the etiology of these diseases, particularly Waldenstrom’s. Although, the causes of multiple myeloma and Waldenstrom’s are for the most part, not clear, ionizing radiation exposure has been found to be a risk factor for multiple myeloma in follow-up studies of atomic bomb survivors (17) and the only known risk factor for CML (21).

CML is clearly distinct from the other two diseases. The main common factor is that like Waldenstrom’s and myeloma, CML arises in blood cells in the bone marrow. As mentioned earlier, however, in contrast to the other two conditions, CML has a specific and significant genetic component Railroad workers have shown higher incident rates of multiple myeloma in several studies (5, 18). Amongst the suspected exposures are diesel fumes. Other suspects are benzene and creosote. Flodin et al. found elevated rate ratios for occupational exposures to engine exhausts, creosote and fresh wood (19). Diesel fumes have been implicated in several other studies including Lee et al. (3). When adjusted for other factors, Lee found an RR of 1.3 (30% increased risk) that was statistically significant at the 95% level. However, there was no dose-response found in this study, which limits the establishment of firm conclusions. Bezabeh et al. reviewed several studies that investigated the possible relation of engine exhaust exposure to multiple myeloma and concluded that they suggest that there is an association. Of the seven studies that they reviewed, all but one found an Odds Ratio of more than one (suggests association) although only one was statistically significant at the 5% level (22). The literature suggests that diesel fumes are a probable cause of multiple myeloma, but the relationship is not firmly established. An American case-control study found increased multiple myeloma rates in men previously employed as painters (solvent exposure) or in agriculture. Agricultural workers who were known to be exposed to pesticides were at particularly high risk (14). Their study lends support to previous studies that have found similar associations (14).

There is biological plausibility for benzene being causally related to the rare cancers of interest here. Benzene metabolites are destructive to the bone marrow (11). A meta-analysis found a statistically significantly increased risk of multiple myeloma in those exposed to benzene (25).

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C. Methods This is a historical cohort study. This means that a group of workers were identified by past records and followed forward in time, to trace cancer development. Standardized Incidence Ratios (SIRs) were calculated on the historical cohort of workers who started work in Essex Hall at any time between 1955 and 2005. Standardized Incidence Ratios (SIRs) were constructed for total cancers and individual cancers (or related groups of cancers) where numbers permitted. Analyses was done for both males and females, although the small numbers of females necessitates that both the analyses and interpretation concentrate on the male workers. The numbers were too small to allow meaningful analyses of individual cancers in females. Only five female cancers developed, each in different sites. The person-years partitioned by age and sex were calculated using the human resource data base of workers in Essex Hall. Analyses were done using both Windsor-Essex 1986/1996 and Ontario age-specific cancer incident rates from 19861996 to calculate the expected number of cancers. The observed cancers were compared to the expected cancers using the SIR as follows:

SIR = observed/expected where: observed - the number of cases of the cancer of interest that developed in the work cohort found by linking the Essex Hall cohort with the CCO Cancer Registry expected - the number of cancers that would have occurred in the worker population if they were getting cancer at the same rate as the standard population

Therefore an SIR of 1 means that the worker population is getting cancer at the same rate as the standard population (Windsor-Essex or province of Ontario). We say that they are getting cancer at the “expected” rate. An SIR of 2 means that the worker population is getting cancer at twice the expected rate. They developed two cancers for every one expected. This signifies, of course, that there may be a problem. An SIR of ½, on the other hand, means that they worker population is developing cancer at only ½ the rate of the standard population. A SIR of less than one generally, but not always, signifies a favourable situation. Sometimes the expected number of the disease in question should be less than the standard population number, in the absence of an occupational

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exposure. This occurs when the workforce is at lower risk than the general population with respect to the disease of interest. (see Healthy Worker Effect). The SIR is referred to as “standardized” because it indirectly adjusts (takes into account) for the age distribution of the worker population in the calculation of the expected rates. Ninety percent approximate confidence intervals were calculated and presented for all SIRs (6). All analyses were done separately for those who worked in South Essex Hall and those who worked in the rest of Essex Hall. If South Essex Hall had poorer ventilation in the past with resultant greater exposures then we may expect South Essex Hall workers to have high cancer rates. Similarly, analyses were done separately for those who started well before the fume hoods were updated (started before 1985 or 1990) and for those who started work in 1985 or 1990 or after. If there were significant ventilation problems and they caused significant exposures then we would expect (other factors being equal) more cancer to occur in the earlier start date group than in the standard population. For many in the post 1985 start group date and most in the post 1990 start date group, insufficient time has elapsed for many work related cancers to be diagnosed. That is, if work related cancers were a problem for this group there may not have been sufficient elapsed time for many of the cancers to manifest. This is particularly true for solid tumours. Solid tumours, such as lung cancer may take up to 25 years to be diagnosed after initial exposure to the carcinogen. Statistical significance at the 5% and 10% levels will be used as a rough guide only to determine if an unusual cancer experience occurred in this population (see Burden of Proof). Statistical significance is most relevant when one is testing one question with one statistical test. When several tests are performed in one study, it is referred to as multiple comparisons. Multiple comparisons increase the probability of chance findings (false positives) beyond the stated risk (p-value). Even if a result is statistically significant, there is still a real probability that the finding was a false one. On the other hand, false negatives may occur because of the low statistical power. As well, there are several possible biases that will generally bias the results towards the null (finding no effect). The patterns of any elevated cancer rates as well as the purely statistical aspects of the results can be used to separate results likely due to chance from those that are more suggestive of problems.

a. Study Population The study population was to comprise all of those who started work in Essex Hall during the time period of 1955 to 2005. Preliminary data analyses showed that the work roster was incomplete. Those who began work before 1985 were included in the roster only if they were still actively working during 1985 or thereafter. These problems arose because only

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current workers were transferred to an updated human resources database in 1985. Those who had begun work before 1985 but were not on the current payroll at that time, were not available for study. Clearly, the incomplete roster for those starting work before 1985 is biased in favour of inclusion of long-term workers. For example, if a worker started work in Essex Hall during 1968 and ended employment (in that area or the University) before 1985, they would not be included in the study cohort. If, however, they started work in 1968 and were still working in Essex Hall in 1985, they would be included. The roster was provided to us by the University of Windsor.

Total person-years of exposure were calculated by subtracting the starting working date in Essex Hall from January 1, 2007. This date was chosen because CCO's registry was current, although not necessarily complete, up to the end of 2006. Person years were partitioned by age for each worker. The approximate breakdown of person years is displayed in Table 2. Exclusions from the study population Students were not included in the study if their role at Essex Hall of the University of Windsor was solely as a student. If a student subsequently became a part-time or full-time employee in Essex Hall, they would be enrolled in the study on their employment start date in Essex Hall. Students were not included because it was judged that student record limitations would make it extremely difficult to track exposure to Essex Hall. As is common with studies of this kind, this study has generated considerable publicity and interest. As a result, several people have called the University of Windsor wishing to be included in the study, who were eligible for the study but whose record was missing. As mentioned earlier, many records are not available for those who did work in Essex Hall during the study period. These people were not included because those who called to be included in the study may differ in relevant ways from eligible, but not included people (or their surrogates) who heard about the study but did not contact the University. More specifically, it is very possible that those who developed cancer may be more motivated to be included in the study than those who did not. Therefore, these people were excluded to limit the possible serious bias that their inclusion would cause. Cancers were only counted if they were diagnosed after the work start date. Several cancers were not counted because they were diagnosed before the work start date in Essex Hall. Of these, one was a myeloma. Records showed that this individual was a student years earlier and that the myeloma occurred after his student starting date. Although this myeloma did not count, because it did not meet the set criteria and to count it would have introduced bias, nevertheless it is a case that could possibly be related to exposures in South Essex Hall. The student records are not precise enough to document exposure in Essex Hall.

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D. Limitations

a. General 1. This study utilizes occupational epidemiology, a field that investigates whether occupational exposures are associated with subsequent excess rates of disease. SIR studies, such as this one, are referred to as ecological because we have no information on non-occupational risk factors in individuals, such as smoking, family history, etc. Occupational ecological studies are, therefore, blunt tools. As is usually the case in these situations an investigation was initiated by a belief among workers that their colleagues in some worker subgroup were experiencing more than the normal amount of cancer. A cancer cluster is an excess rate of cancer or of a cancer type (types) over what would normally be expected in the worker population. It may be due to an occupational exposure to a carcinogen, characteristics of the workers (genetic or lifestyle), other common environmental exposures or to chance. Traditional epidemiologic and statistical methods are not readily applicable to the investigation of clusters because of the unique problems associated with their analysis and interpretation Part of the problem is the bias associated with the choice of the particular work group to study. For example, assume that there are no workplace carcinogens and additionally that all workers have the same chance of getting cancer. Then if there were 100 workplaces in Canada of the same size, we would expect, on average, 5 to develop a statistically significant excess of cancer. This follows from statistical probability theory. More attention would presumably be given to the workplaces with high cancer rates. Looked at in isolation, these workplaces would appear to be problem areas. However, we know, in this example, that the high cancer rates found were due to chance or natural variation. Some workplaces will have higher cancer rates and some lower cancer rates, in the absence of any carcinogens. When we study a workplace that has a high cancer rate(s), it is important to consider these statistical issues. The problem lies in separating high cancer rates that are likely due to chance or other factors from those with workplace related causation. It should be clear that a statistically elevated cancer rate, in itself, is not cause for alarm. Working in Essex Hall, was used as an inexact surrogate measure for any occupational exposures that may have occurred there. Since there is no information on individual exposures, there is no way to control for confounding for individuals because we do not know what other factors besides occupational ones may have caused cancers. Certainly many other common causes are acting besides the one(s) of interest in this study. For these reasons, firm conclusions regarding cause and effect for such studies are generally not possible. Even determining whether a disease is associated with an occupational group may be difficult due to many biases and limitations, some of which are described in this section.

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Statistical results can only be used as a guidepost. Since a number of independent SIRs were calculated, more than 10% (at the 90% confidence level) would be expected to be statistically significant even if Essex Hall workers were getting cancer at exactly the expected rate. Stated differently, even if there were no cancer problems in Essex Hall, some of the results would be expected to be statistically significant if a number of SIRs were calculated. On the other hand, small numbers result in very low statistical power (ability to detect SIRs as statistically significant that are truly elevated). Therefore, elevated but non statistically significant results may not provide reason for comfort. On interpretation of this pattern, reasonable people may disagree. The calculation of SIRs is an exact science. The interpretation of the pattern of a number of SIRs in a population is, however, more of an art. We are dealing with cancer, which for the most part involves very long periods from exposure to diagnosis. This period between initial exposure and diagnosis will vary by cancer. It is difficult to assign causation for a cancer to an exposure that may have occurred 25 years ago. These problems are less important for some of the cancers such as leukemia that have a shorter induction period.

It becomes obvious that one will not uncover excesses if one is looking in the wrong time window. Many leukemias may have short latency periods of less than 10 years. However, if an employee started work at Essex Hall and developed lung cancer 4 years later, it is almost certain that Essex Hall exposures did not cause the lung cancer. We know this because the minimum time needed for lung cancer to develop after initial exposure is much greater than 4 years. The expected pattern of excess rates in time is one of the tools we can employ to separate perhaps spuriously elevated rates from ones that require further scrutiny.

b. Study Specific 1. Power considerations

Power refers to the ability to detect a true excess of cancer of a specific amount. A limitation of the study will be the small population size. There were 799 workers in the study cohort of workers. The nearly 600 males who serve as the focus of the study, however, provide a more substantial total of over 9000 person-years of exposure. This number should be adequate for meaningful analyses, since SIRs are efficient statistically for small population studies. The efficiency of SIR studies is exemplified in the results where only two cases of multiple myeloma were sufficient to produce statistically significance results at the 90% confidence level. Epidemiology utilizes person-years as the denominators when calculating rates, in order to take into the amount of time that a person was followed. For example, one person followed for 5 years would provide 5 person-years of observation. Two people followed for 10 years would provide 20 person-years of observation. Ann employee who started work at the beginning of 1980 would provide 27 person-years of observation, since the study observation ended after 2006.

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No account was made for induction periods in the analyses. That is, all cancers that were diagnosed after the starting date of work in Essex Hall were counted. Most of these cancers occurred long after the starting date in any case. For example, both multiple myelomas were diagnosed after more than 10 years of employment in Essex Hall. The power in this study will generally be very low for rare cancers and for sub-analyses involving more common cancers. Power can be thought of as related to the quality and quantity of the evidence available, similar to evidence in a criminal legal trial. If there is not a large quantity of evidence and/or the evidence is unreliable, (bias) then the defendant is likely to be found “not guilty”. That does not at all imply that he/she is innocent. Similarly, when there are small numbers and little scientific information available in epidemiological studies, the results are often found to be “not statistically significant”. That means that we did not find that there was an excess of cancer beyond “a reasonable scientific doubt”. Reasonable doubt in science is quantified (and chosen) by the significance level. If the significance level is 5% (confidence level of 95%) then there is a 5% chance we will be wrong when we say that there is an excess of cancer. Note that results may not be statistically significant because there is truly no real increase in cancer or because there was not enough evidence (low statistical power). 2. Data base irregularities Probably more important than the lack of statistical power are the data base irregularities that were briefly discussed earlier. A sizable portion, most likely, the majority of the cohort that started worked in Essex Hall between 1955 and 1985 have not been transferred to the present database. There are two problems with this. The more obvious problem is that a lot of important information is not available for study. If the workers, for which we have no data, differ in pertinent ways from the early Essex Hall workers for whom we have information, then the problem is much more serious. This situation may result in study bias. For example, imagine that workers who had some health related problems caused by or aggravated by exposures in South Essex Hall, may have been more likely to leave work sooner than those who did not react adversely. If these workers were also more likely to develop cancer due to Essex Hall exposures, then our study would underestimate cancer risks. That is because those most likely to develop cancer would be missing from our database, since they would not continue working in Essex Hall until 1985. This scenario is very unlikely because any exposures in Essex Hall were not described as noxious to the point as to cause immediate symptoms. Most likely, the early workers included in the database would not differ markedly in regards to cancer risk than those excluded. In that case, there is not bias in the study, although the statistical power would be reduced due to the smaller number of workers followed and evaluated. The database was constructed for Human Resources purposes without regard for possible scientific analyses. By definition, one would expect it to be lacking, somewhat for a study of this kind.

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Additionally there were anomalies in the database in addition to the missing data discussed above. Although we think that we have data for all of the workers who started work in 1985 or later, this has been difficult to confirm. There were irregularities found in the work start date field that were described in the preliminary report. Painstaking work by Rita LaCivita, Leigh Harold and their staffs have largely removed this problem by verifying the start dates against the original human resource file records, for most workers.

Although the study team did verify the original work start dates in Essex Hall, many workers did several work stints during the time period of this study. For example, many worked as teaching assistants for only one term in successive years. Some problems suspected with the accuracy of the successive start dates were not corrected. As a result of concerns about the accuracy of the data for successive work terms, we did not present the results of cancer risk by the total time worked in Essex Hall in this report. 3. Limited exposure data Epidemiology assesses possible links between exposures and subsequent development of disease. Good quality occupational hygiene data is desirable, although often lacking. For Essex Hall, there was no occupational hygiene information available before 2001. Studies were done in 2001, 2006 and 2007. Most of our information about historical (before 2001) conditions in Essex Hall is based on anecdotal information from workers. As mentioned earlier, workers have alleged that the ventilation was very poor before the late 1990s. They complained of generally poor air quality and exposures to diesel fumes from the proximal Ambassador ramp as well as a variety of other exposures. It is difficult to assess the validity of these claims. However, it is reasonable to believe that there may have been, at least, historical exposure to diesel fumes. This belief is based on ventilation that most likely was not efficient along with quite plausible exposures to high ambient outdoor fume levels. The fact that several improvements were made to improve air quality in the 1990s give some credence to the claim that air quality was, at best, less than optimal. In this study we have used Essex Hall (particularly South Essex Hall) as an inexact surrogate of possible exposures. For example, if there were exposures to carcinogens in South Essex Hall we would expect the cancer rates there to be higher than in North Essex Hall. Those working in the earlier periods in Essex Hall may be expected to develop cancer at higher than the standard rates. Indirectly, then, we are able to assess the effects of possible exposures, although, of course, good historical occupational hygiene data would be highly advantageous.

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E. Sources of Bias

a. Misclassification by disease There is considerable misdiagnosis of cancer. The diagnosed cancer may not represent the primary site (where the cancer originated). The degree of misdiagnoses depends on the tumour type as well as other factors. There will also inevitably, be some death certificate coding errors of the tumour type.

Although misclassification by disease occurs, it is usually not as important as misclassification by exposure and other biases. However, for multiple myeloma and Waldenstrom’s, misclassification by disease may be significant (7, 23).

b. Misclassification by exposure Misclassification by exposure is usually more important than misclassification by disease. Here the exposure is simply working in Essex Hall. Clearly, working in Essex Hall is only an inexact, surrogate measure of exposure. If there were exposures to carcinogens in Essex Hall, they may or may not vary widely by location and time.

c. Migration People who develop cancer will only appear in CCO's registry if they were living in and treated in Ontario at the time of diagnosis. For example, if a significant portion of the retired employees moved to Florida, they would most likely be treated there and not show up as cancer cases in CCO’s registry. This is only a problem if the work cohort has migrated out of Ontario at greater or lesser rates than the general population. Although this is hard to ascertain, we have no reason to believe that the migration rates of the Essex Hall cohort would differ markedly from the migration rates for other residents of Windsor-Essex.

d. standard rates The standard rates used to determine the expected numbers of cancers are based on Windsor-Essex rates and provincial rates. The Windsor-Essex rates include an urban area where many people may have multiple exposures to various environmental and occupational contaminants. Therefore, the standard itself may have elevated rates. In that case we would be comparing Essex Hall cancer rates to standard rates that may be elevated for reasons that may not be relevant for Essex Hall workers. This may cause us to underestimate the risk in the Essex Hall cohort. Ontario rates also include areas with high cancer rates due to environmental, occupational and lifestyle exposures. As well, there is a healthy worker effect factor that may come into play when using standard rates (discussed below).

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Note that the two standards used are not independent. Cancers from Windsor-Essex are included in the incident cancers used to calculate provincial rates.

e. Healthy Worker Effect The healthy worker effect (HWE) refers to the phenomenon that people who enter the labour force are generally healthier than the general population. The general population contains people who are unwilling or unable to work. They may be unwell, unfit or even institutionalized. Workers demonstrate that they have better health in lower morbidity and mortality rates. The noted HWE authority McMichael (9) defines HWE as 'the consistent tendency for actively employed people to have a more favourable mortality (or morbidity) experience than the population at large". People must also remain in relatively good health to remain employed (10). Although employment introduces a selection bias that naturally screens against illnesses of younger ages that may hinder one doing work, it does not necessarily introduce a bias against hiring people who may eventually develop chronic diseases such as cancer. This is assuming that screening for smoking status does not take place. Therefore, the healthy worker effect is thought to be quite small for cancer. Cardiovascular disease (CVD) is a different story. Since CVD has such well known and recognizable risk factors, it is possible to screen for diabetes, blood pressure, obesity, blood cholesterol levels and lack of physical fitness at a young age. All may be predictors of CVD developing later on. Since rigid pre-employment screening occurs in professions such as firefighting, one would expect lower CVD morbidity and mortality to occur in firefighters. As well, the physical demands of the job should ensure that firefighters need to remain relatively healthy and fit. Additionally those in poor physical condition, who are likely at greater risk of CVD, would self-screen by not applying for physically demanding jobs such as firefighting. Clearly, the HWE may be quite large for firefighters, police officers, and other professions that have physical demands. Therefore, in the absence of workplace exposures we would expect their SIRs for CVD to be considerably less than one. The HWE has to be taken account when interpreting these situations. Summary Most of the biases discussed above serve as white noise, masking any real effect between exposure and disease. Along with the limitations inherent in such studies, the result is that most ecological occupational epidemiological studies are biased towards producing “negative” results. The low quality of the evidence (data) being evaluated often guarantees such findings. This should be taken into account when interpreting the findings.

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F. Burden of Proof The statistical burden of proof is very high. Traditionally we have to be 95% or at least 90% certain (confidence level) that differences are not due to chance before we state they are "likely not chance findings" or statistically significant. That leaves the area of high but less than 90% confidence as a gray zone where results are likely real, but not statistically significant. The arguments for using a 95% confidence level (5% significance level) centre on it being the historical standard for the burden of proof. There is, however, no logical basis for choosing the 95% level of confidence. In fact, in was originally arrived at based on the cost-benefit associated with agricultural decision making. It is arbitrary. Most people use it simply because others have, not because of its appropriateness. It was not designed with the limitations of occupational epidemiology in mind. The 95% level would appear unrealistically stringent here for a number of reasons including the following: 1. The confidence level assumes that the data is of high quality. Misclassification by

exposure (people are placed in the incorrect exposure categories) and some misclassification by disease (people are incorrectly classified as either being free from or having a given cancer) will usually decrease the chance of finding significant differences between groups. This sets the burden of proof much higher than the stated level. We are dealing with highly inexact data here. Most of the biases are non-directional errors that would increase the burden of proof by adding noise to the data.

2. The ramifications of incorrectly finding a particular significant relationship (false positive)

between an exposure and a cancer is not great since conclusions in a study of this type will be based mainly on patterns rather than individual associations.

3. The ability to detect true excesses (statistical power) is very low for many cancers in this

study. Using a high confidence level (e.g., 95%) decreases the power. For these reasons, I advocate a less stringent burden of proof of 90% if one is to be chosen at all. In any case, the choosing of a significance level is largely a red herring. Significance levels are most valid when one major question is asked and one statistical test performed. Statistical significance is used as a basis for decision making, such as whether a new drug cures a particular disease better than the existing drug. The statistical results of this study, alone, would not be sufficient for decision-making. We are looking at a number of SIRs, which brings in the issue of multiple comparisons. It is, therefore, not useful to rely on a stringent, strict statistical cut-off as a standard of proof. In so doing, we would be imagining that the quality of evidence is far superior to the reality and not taking into account serious issues affecting the true statistical significance of each finding.

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The 95% confidence level, or any other, is not magical. For example, a study comparing leukemia rates in children living around the Pickering nuclear plant to lower risk children found approximately a doubling of the risk for children living near the plant. The probability of this finding being due to chance (p-value) was about 5.5%. Therefore the study was interpreted as being “negative” because the results were not statistical significant at the 5% level. If the p-value had been 4.9%, the study would have been seen as “positive”. Clearly, these divisions are arbitrary. The above examples show that statistical significance (at any level) should be used only as a guidepost or screen for diseases that require further scrutiny. There will be statistically significant results that are due to chance, which increases with the number of independent SIRs calculated. On the other hand, because of low statistical power, non-significant elevations may be important, particularly if they are part of a pattern of excess rates.

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G. Results – Background

a. Characteristics of the study cohort i. Starting date As mentioned earlier, many earlier workers are not in the database. Table 1 shows that in our recorded cohort, that less than 11 percent of males and about 2 percent of females started work before 1970. Dramatically, only about 15 percent of males and less than 8 percent of females started work before 1980. We know that a large number of early start-date workers were not available for study. These workers would be the ones who would provide the greatest opportunity to study cancer risk, since for them the time for work related tumour development would be adequate. ii. Person-Years Table 2a shows that the total male person-years up to January 1st, 2007 was 9082. The female population was much smaller and amounted to just 2902 person years. Person-years peaked in the middle age range. These tables display the distribution of person-years, partitioned by age and sex. Note that in the entire cohort, women are slightly younger than the males, as they contribute a larger percentage or their person-years to the youngest two age groups and a slightly smaller percentage to the oldest age groups. Table 2b shows that the age distributions of workers in South Essex Hall and North Essex Hall were quite similar.

Table 2c shows that, as would be expected, workers who started before 1990 are much older than those who started after that time.

b. Standard populations – some considerations Two different standard populations were used for the analyses. The 1986/1996 Ontario standard has the advantage of having stable rates for rare cancers since it is based on a large population. Windsor-Essex was used as the other standard population to calculate SIRs. Using Windsor-Essex as a standard has the advantage for the more common cancers since the local rates should, presumably, more closely represent the exposures in the population from which Essex Hall workers are drawn. However, for rarer cancers, there will be instability in the Windsor-Essex Kent age-specific rates from year to year that will make the results less reliable. For example, CML rates were unusually low in Windsor-Essex in 1986, which resulted in the SIR being very high when using that standard. To lessen the instability issue, 1986 and 1996 Windsor-Essex rates were combined for use as the second standard population.

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Since there are significant temporal trends for some cancers, combined Ontario 1986 and 1996 incidence rates were used to comprise the second standard to match the dates of the Windsor-Essex standard and facilitate comparisons. This was only an important issue for prostate cancer, since age-adjusted prostate cancer incidence rates were rising during the period of 1986 to 1996. This increase may have been real due to an increase of risk factors. Alternatively, it may have been due, at least in part, to advances in detection due to increasing use of the PSA diagnostic test (15). The increases could also be partly due to real increases and partly due to increased detection.

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H. Results

a. Interpretive Caution It is tempting to compare SIRs to one another and it is commonly done. However, to do so is not generally valid. This is because the standard for SIRs actually comes from the worker cohort, not from the so called “standard” population. The standard provides the rates but not the age-distribution. Therefore, SIRs calculated on two different worker groups use two different standards. This is referred to as the “shifting standard” problem. Generally, SIRs should be compared to the standard, only. For example, if the SIR for overall cancer is 2.0 for those starting work before 1985, then the interpretation is that these workers developed cancer at double the standard rate. If those who started work after 1985 had a corresponding SIR of one, then the interpretation would be that they developed cancer at the same rate as the standard population. However, it would not be valid to say that the earlier start date workers developed cancer at double the rate of the later start date workers. In the special case where the two worker groups have a similar age-distribution, however, the SIRs may be cautiously compared. For example, the age-distributions of workers in North Essex Hall and South Essex Hall are reasonably similar, so SIRs calculated on these two groups may be validly compared.

b. Entire Cohort i. All cancers combined (total cancer) The SIRs for total cancers were low (Table 3). They were 0.59 and 0.62 using Windsor-Essex and Ontario standards respectively. This means that males working in Essex Hall developed cancers at less than 2/3 the rate than did men in Windsor-Essex and the entire province. These results were statistically significant at the 5% level (p<.05). A p-value of <.05 means that we are at least 95% sure that (in this case) the SIRs are truly less than one (and not due to chance variability). There is less than a 5% chance (p<.05) that the SIRs are not truly less than one. In other words, this is unlikely to be a chance finding. The situation was similar for females as the SIRs were 0.58 and 0.57 using Windsor-Essex and Ontario standards, respectively. These results were not statistically significant, however, as they were based on much smaller numbers. Only five cancers developed in women and there was no more than one cancer in any site. Twenty-seven cancers were observed in male workers that were diagnosed after the employees started work in Essex Hall. The 27 male cancers developed in 25 males. Two workers developed malignancies in two sites that were judged as independent cancers by Cancer Care Ontario. Therefore, they would be counted as two different cancers by Cancer

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Care Ontario and as two separate cancers when calculating provincial cancer incidence rates. Therefore we counted both cancers in these individuals to make our calculations correspond to Cancer Care Ontario data. If Essex Hall workers were experiencing cancer at the same rate as males in the province as a whole (Ontario standard), just over 43 cancers would be expected to have occurred in this group. About 46 cancers would have been expected to develop in the Essex Hall cohort if they developed cancer at the same rate as Windsor-Essex males (Table 3). Since Windsor-Essex total cancer rates are generally slightly higher than provincial ones, the expected number of cancers is generally higher than the corresponding expected values using the Ontario standard. This results in the corresponding SIRs being slightly lower when using the 1986/1996 Windsor–Essex standard. These differences did not generally affect the results, markedly. For this reason, the remainder of this report will refer to Windsor-Essex standard results, unless stated otherwise.

ii. Individual Cancers of interest (males only) The amount of male follow-up (person-years) allowed us to compute meaningful SIRs for major cancers and those of particular interest. Lung cancer: The incidence of lung cancer was extremely low in Essex Hall workers. The SIR was .20(p<.05). Remarkably, males who worked in Essex Hall developed only about 20 percent of the lung cancer than did comparable residents of Windsor-Essex. Only one lung cancer developed for every five expected. Colon Cancer: This major cancer also developed at low rates in this cohort. The SIR of .29 (p>.1) showed just over one case developing for every four expected. The SIR using the Ontario standard was even lower at .25. Note that both results are not statistically significant at the 10 % level while the lung cancer results were highly significant (5% level). These differences have occurred because lung cancer is more common than colon cancer and therefore the lung cancer calculations are based on more information and the confidence intervals are therefore more precise (Table 3). This means that the low colon cancer rates found are more likely to be chance findings than the lung cancer findings. Prostate cancer: This was the only major cancer where SIRs were found to be greater than one, although they were not statistically significant at the 10% level. Essex Hall males developed this cancer at slightly higher than the regional rates (SIR = 1.19, p>.1). However, prostate

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cancer rates in Windsor-Essex males were marginally higher than rates in the entire province. This results in the SIR being a slightly higher 1.30 (p>.1) using the Ontario standard.

Chronic Myeloid Leukemia (CML): Essex Hall employees developed more CML than expected, even though there was only one case. The SIR was much larger using the Ontario standard (4.35 (p<.1) vs. 1.72 (p>.1)). This SIR is statistically volatile, however, being based on only one case. Note that the excess is not statistically significant using the Windsor-Essex standard but is using the Ontario standard. Multiple Myeloma Waldenstrom’s was included with myeloma as they are very closely related and Cancer Care Ontario classified our Waldenstrom’s case as a multiple myeloma. Note: CCO does not apparently classify all Waldenstrom’s as multiple myelomas (7). According to CCO, it depends on the clinical aspects of the case. Classification of cancer cases is automated. Given this information, it is not a clear-cut decision as to whether we should include our Waldenstrom’s case as a multiple myeloma. The crucial question is what percentage of Waldenstrom’s are classified as multiple myelomas by CCO and therefore included as multiple myeloma when calculating the standard rates. This is important because we are comparing our observed cancers to the expected numbers based on a standard. If we did not combine the Waldenstrom’s case with myeloma case, then we would need provincial rates of Waldenstrom’s to use as a standard. From my discussion with CCO, it appears that meaningful Waldenstrom’s rates are not routinely available, since some Waldenstrom’s are apparently combined with myeloma while others are combined with “other sites” (7). An important consideration is etiology (causation). If the etiology of multiple myeloma and Waldenstrom’s is similar, which is not proven but is a reasonable assumption, then combining them for the analyses is logical. A completely appropriate standard rate is not available for the combined analyses.

These two cancers were the ones that elicited much of the initial concern amongst workers as two workers with similar jobs; working in close proximity developed these rare cancers. Whatever the case, even one case of Waldenstrom’s in a group this size would be unexpected, as it is an extremely rare condition. If the Waldenstrom’s case was analyzed separately, the SIR would be much higher than for myeloma analyzed by itself (see analyses below). That is evident because Waldenstrom’s is much rarer than is myeloma.

Although there were only two cases, this corresponds to a high rate of multiple myeloma in this work cohort. Essex Hall males had over three times the expected rate of multiple myeloma (SIR – 3.27, p<.1). Even with the very small number, the result would not often

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occur in a group such as this one (statistically significant at 10 percent level). Again, the statistical significance should be used only as a guide here, especially with all of the issues considering the Waldenstrom’s classification. However, it is quite clear, that whatever the case, it is somewhat unusual statistically to get both 1 case of multiple myeloma and 1 case of Waldenstrom’s in this cohort of workers, even though it may not be possible to be precise about the rareness (p-value). This is true regardless of where the Waldenstrom’s case is classified.

An alternative approximate analysis was done treating Waldenstrom’s as a separate entity (Table 7). Since reliable Waldenstrom’s Ontario incidence data was not available, incidence data was used from the Groves study (13) described earlier. Approximate age-specific incidence rates were extrapolated from the figure in that study in order to calculate estimates of the expected rates. The assumption is that Ontario rates would be similar to the average American rates from several state cancer registries. The results were dramatic. The SIR was 23.4. (90% confidence interval [8.31, 108.8]), which was also statistically significant at the 5% level (p<.05). The disease is so rare that we are 90% sure that the Waldenstrom’s incidence rate is at least 8.31 times the expected rate, even though there was only one case. The SIR takes into account the age distribution of the population at risk (the Essex Hall cohort) but it does not take into account the age at diagnosis of the case. Therefore the SIR is conservative, since the case here was extremely young, being diagnosed at age 37. Remember that the risk for Waldenstrom’s increases very steeply with advancing age. Additionally, there was a case of CML, which is also quite rare. Although it is clearly distinct from the other two rare cancers, CML originates primarily in cells in the bone marrow as does Waldenstrom’s and multiple myeloma. Three rare cancers, that might be reasonably expected to share, at least some causal factors occurred in this cohort. Furthermore, all three cases occurred in workers from South Essex Hall who started work before 1985. The pattern then is consistent with exposures in South Essex Hall. The development of these three cancers, taken together, suggests that there may have been pertinent exposures in South Essex Hall. The nature and limitations of this study do not, however, allow us to conclude that the pattern is strong evidence of causation between an exposure in South Essex Hall and these cancers.

c. Analyses by workplace

The study was initiated mainly because there was concern amongst South Essex Hall workers. These concerns centred on perceived ventilation problems in the past along with the belief that there was an unusual pattern of cancers that developed in South Essex Hall workers. To gain insight into this issue, male SIRS were calculated by place of work in Essex Hall.

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Total Cancer SIRs were low for both North and South Essex Hall workers (Table 4). SIRs were slightly higher, though, for South Essex Hall workers. The SIRs were .64 (p<.1) for South Essex Hall workers versus .53 (p<.05) for those who worked in North Essex Hall. North Essex Hall workers developed cancer at only about one-half the rate of the general Windsor-Essex population while workers in South Essex Hall developed about 6 cancers for every 10 expected. The corresponding SIRs were similar, albeit, slightly higher, using the Ontario standard (Table 4). The SIR was not statistically significantly less than one at the 10% level, however, using the Ontario standard.

Lung cancer The incidence of lung cancer was low in both groups, but both SIRs were not significantly different from one at the 10% level. The SIR was .37 (p>.10) for South Essex Hall while no lung cancers developed in North Essex Hall workers. Males who worked anywhere in Essex Hall experienced less than 40% of the lung cancer than did Windsor-Essex residents.

Colon Cancer Colon cancer SIRs was lower than expected, although not statistically different from one. The only colon cancer case occurred in a South Essex Hall worker. The SIR, however, was only .53 (p>.10) even in South Essex Hall.

Prostate cancer This was the only cancer where the SIR was higher in North Essex Hall, as the SIR was 1.39 (p>.10) compared to 1.02 found for South Essex Hall workers. The corresponding SIRs for Ontario were slightly higher, at 1.50 and 1.12, respectively. These rates are also not statistically significantly elevated however, at the 10% level. Chronic Myeloid Leukemia (CML) The only case of CML developed in a South Essex Hall worker. The SIRs were elevated for South Essex and were highly dependent on the standard chosen. The SIR was 3.13 (p<.10) using the Windsor-Essex standard and 7.82 (p<.10) using the Ontario standard. The sharp difference is due to the CML rates being much higher in Windsor-Essex than in the province. Multiple Myeloma Both multiple myeloma cases occurred in South Essex workers. The resultant SIR of 5.88 was statistically significant at the 10% level (p<.10). South Essex Hall workers developed multiple myeloma at nearly 6 times the rate than did Windsor-Essex residents. The result was similar using the Ontario standard although the SIR was slightly higher at 6.44 (p<.10).

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d. Analyses by start date - pre-post 1990 Many of the workers believe that working conditions were worse and exposures greater in the past, particularly prior to limited ventilation improvements that were done in the late 1990s. If there were more significant exposures in the past, then we would expect high cancer rates in the workers who started work earlier. Additionally, if there were any elevated risks due to working in Essex Hall, there would be time for most of these cancers to manifest themselves in the workers who started work before 1990. Many cancers would not be expected to have had sufficient time to be manifest in the post 1990-start date workers. This is true because many cancers may take up to 20 to 25 years to develop to the point of diagnoses from the time of initial exposure. Therefore, low SIRs in this group could be due to an absence of occupational exposures but could also be due to inadequate time of follow-up. Clearly, the earlier start date groups were of the greatest interest. To investigate, the cohort was divided by start date. Those who started work in Essex Hall before 1990 were analysed separately from those who started work after that date. The start date division is somewhat arbitrary. Dividing the workers by an earlier start date, such as 1985, has the advantage of ensuring a greater follow-up time in the earlier group as well as the disadvantage of having fewer workers in the earlier start date group. Analyses using a 1985 start date were also performed. The major difference in the results between the 1985 division analyses and the 1990 division analyses is that there was a greater differential between the total cancer SIR and the prostate cancer SIR in the earlier group compared to the later start date group using the 1985 division date. Again, as mentioned earlier, one has to be careful when comparing SIRs to each other.

Total Cancer Both SIRs showed cancer rates were between 1/2 and 2/3 the rate of the general Windsor-Essex population. The SIR was .60 (p<.10) for pre-1990 starting date workers compared to .56 (p>.10) for post 1990 workers (Table 5). Note that the SIR was not quite statistically significant for post-1990 workers. This result is due to the lower statistical precision in the post-1990 group due to smaller person-year of follow-up.

Lung cancer The SIR was only .12 in the post 1990 workers being highly statistically significant in that group (p<.05). The SIR was .62 (p>.1) the post 1990 group. Both statistics are based, however, on only one cancer. The pattern was similar, but the SIRs were slightly higher using the Ontario standard at .14 for the pre-1990 start group and .81 for the post-1990 start group. Colon Cancer The only colon cancer case occurred in a pre-1990 worker. The SIR, however, was only .33 (p>.10) even in the pre-1990 start date group.

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Prostate cancer Prostate cancer was slightly elevated in the pre-1990 group (SIR = 1.22, p>.1), and nearly as expected (SIR = .98) in the post-1990 start date group. The SIRs were similar and only slightly higher using the Ontario standard. Chronic Myeloid Leukemia (CML) There was only one case of CML although that was enough to elevate the pre 1990 SIR to 2.17 (p>.10). The SIR was 5.50 (p<.10) using the Ontario standard. The large gap in the two SIRs is due to the Windsor-Essex CML rates being much higher than the province’s. Multiple Myeloma Both multiple myeloma cases occurred in the pre-1990 cohort. The resultant pre-1990 cohort SIR was high at 4.08 (p<.10]. Males who started work in Essex Hall before 1990 developed 4 myeloma cases for every one expected case.

e. Analyses by start date - pre-post 1985 Total Cancer The SIR was .71 (p>.10) for pre-1985 starting date workers compared to .30 (p<.05) for post 1985 workers (Table 6). Note that the pre-1985 SIR is not significantly less than one, while the post-1985 is statistically less than one. Lung cancer The SIR was only .14 and highly statistically significant in the pre-1985 start date group (p<.05). The SIR was .35 (p>.1) in the post 1985 group. Both statistics are based, however, on only one cancer. The pattern was similar, but the SIRs were slightly higher using the Ontario standard at .17 for the pre-1985 start group and .45 for the post-1985 start group. Colon Cancer The only colon cancer case occurred in a pre-1985 worker. The SIR, however, was only .38 (p>.10) even in the pre-1985 start date group.

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Prostate cancer Prostate cancer was slightly elevated, but not significantly, in the pre-1985 group (SIR = 1.38, p>.1), and much lower than expected (SIR = .51, p>.10) in the post-1985 start date group. Neither of the SIRs was significantly different from one, however. The SIRs were similar and only slightly higher using the Ontario standard. Chronic Myeloid Leukemia (CML) There was only one case of CML although that was enough to elevate the pre 1985 SIR to 2.63 (p>.10). The SIR was 6.71 (p<.10) using the Ontario standard. The large gap in the two SIRs is due to the Windsor-Essex CML rates being much higher than the province’s. Multiple Myeloma Both multiple myeloma cases occurred in the pre-1985 cohort. The resultant pre-1985 cohort SIR was high at 5.00 (p<.10]. Males who started work in Essex Hall before 1985 developed 5 myeloma cases for every one expected case. Generally, although the 1985 cut-off dates were similar in pattern to the 1990 cut-off date results, the differentials between the SIR groups were generally larger using the 1985 cut-off date. This occurred because there were no cancers diagnosed in workers who started between 1985 and 1990. Therefore, in the pre-1985 start group, the number of cancers was equal to the pre-1990 start group but there were less person-years of follow-up. Therefore, the SIRs in the 1985 start date group were higher than in the 1990 start date group.

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I. Discussion

Total Cancer Workers in the entire Essex Hall work cohort experienced cancer at only about 60% of the expected rates, based on either standard. These results were statistically significant at the 5% level, meaning we are quite sure that the SIRs are truly less than one. This result held for both males and females, although the female results were not statistically significant, since they were based on much smaller numbers. Partitioning the data by starting date or work location in Essex Hall (for males only) produced similar results. Those starting work before 1990 had slightly higher SIRs than those who started work after 1990. This trend was similar, but sharper, for those who started work before 1985. Those starting work before 1985 had the highest SIRs; however, it was still only about three quarters of the expected rate. Workers in South Essex Hall developed cancer at slightly higher rates than did workers in North Essex Hall. Again, comparison of the early start group SIRs to the later start groups SIRs is dubious because the later groups were younger. Differences noted in the SIRs may be due to differences in the worker age-distribution or due to differing cancer risk of a combination of both. An important question is why would the total cancer rates be so low? The HWE is not generally a major factor for cancer. We would not expect cancer prone employees either to self-screen out of working in Essex Hall or to be screened out by the employer. It is possible that those with health problems that may be predictors of cancer left work disproportionately in Essex Hall because of poor air quality. This does not seem to be a likely scenario based on the probability that the quality of air in South Essex Hall was not poor enough to generate a large exodus of workers. It is possible that there has been incomplete ascertainment of cancer cases for some reason, including high post retirement migration rates (discussed earlier). Also, especially in the very recent past, CCOs records may not be complete. A major reason for the very low overall cancer rate is the large deficit of lung cancer from the expected rate. Workers in Essex Hall developed lung cancer at only about 20 percent the standard rates. This statistically significant finding is quite dramatic. Stated differently, only about one lung cancer case developed for every five expected. Studies have consistently shown that the great majority of lung cancer is due to smoking. Most studies have shown heavy smokers to have over 20 times the lung cancer risk of a non-smoker and that the vast majority of lung cancer cases are attributable to smoking (16). It follows that smoking rates were probably very low in this cohort. If true, this low smoking rate could explain much of the departure from expected cancer rates, since smoking is a risk factor for several cancers besides lung cancer. Windsor-Essex was used as the primary standard population in this study. It is comprised of both a rural and urban area. The city of Windsor, presumably, has higher cancer rates, generally, than the surrounding suburban and rural areas. If the workers in Essex Hall lived disproportionately in the rural areas of the region, that could help explain the low cancer rates. We have no information, however, on this issue.

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Prostate Cancer Prostate cancer was slightly elevated in most of the analyses. There were no dramatic differences dependent on the 1990 start date or on location worked in Essex Hall. The rates were all slightly higher using the Ontario standard, since Windsor-Essex has prostate cancer rates that are marginally higher than the provincial ones. None of the SIRs, however, were statistically significantly different from one at the 10% level Overall, there is only weak evidence in this data that prostate cancers are elevated. Although there were only slight differences between South Essex Hall and North Essex Hall SIRs, those starting before 1985 had a much higher SIR than those starting in 1985. However, the post 1985 group has very small expected numbers and so the amount of evidence is small. The expected number of cancers in this group is small because it is a younger group and prostate cancer occurs mainly in the older age groups. Stated differently, there were not many person-years in the highest risk age groups for prostate cancer in the post 1985 start date group. This results in comparisons to the earlier start date group being somewhat tenuous. In fact, as discussed earlier, comparison of SIRs to each other is not recommended, principally for the reason of disparate age distributions in the worker groups. Genetic or lifestyle factors may be responsible for the slightly higher rates. There are large racial and ethnic differences in prostate cancer risk. Black men have much higher rates of prostate cancer than do white men in the United States (15). Asians have lower rates than whites do. The racial composition of our cohort is not known.

Lung Cancer The most surprising finding in this study was the dramatically low lung cancer rates (discussed above). In addition, one of the two lung cancers occurred in a reported non-smoker. Colon Cancer This common cancer occurred at low rates, although the findings are not as dramatic as they are for lung cancer. The overall effect on the number of cancers is less with colon cancer than lung cancer since lung cancer is considerably more common. Multiple Myeloma Only two cases of multiple myeloma occurred in this cohort (see discussion in results section). However, since this is a relatively rare disease, even two cases constitute a somewhat unusual event statistically (p<.10) overall. Furthermore, one of the cases was actually Waldenstrom’s, which is an even rarer variant. This case occurred in a 37 year old man. The vast majority of Waldenstrom’s occurs in men over 60. Multiple myeloma is also a disease of older people having a similar, very steep risk curve with increasing age (13).

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Both myeloma cases occurred in South Essex Hall workers who started work before 1985. This is what we would expect if myeloma was associated with alleged exposures that were more marked before the late 1990s in South Essex Hall. The results of the study, although based on very limited data, are consistent with an increased rate of multiple myeloma that is concordant with a relationship to occupation exposures. It should be noted that the knowledge of the causes multiple myeloma and Waldenstrom’s are limited. However, two suspected causes for multiple myeloma are radiation and diesel fume exposures, for which the evidence is more conclusive in support of radiation. Although some South Essex Hall workers relate radiation exposures (32), the most pertinent exposure here is probably diesel fumes. While exposures are always possible, there is no evidence of radiation exposure to workers in South Essex Hall (33). There may be some radiation exposure via use of radioisotopes in biochemistry and chemistry in North Essex Hall (33). Workers allege that the ventilation and resultant air quality was poor in much of South Essex Hall before improvements were made in the late 1990s. If there were significant ventilation problems, then exposures to high level of diesel fumes is quite plausible. This is due to the very high truck and auto traffic proximal to Essex Hall because of its location near to the Ambassador Bridge onramp. However, this is speculative, since occupational hygiene studies were not done in Essex Hall, until recently. These recent occupational hygiene studies showed exposure to diesel fumes did not exceed guidelines (1, 8). Ecological studies, such as this one, may establish links between exposures and subsequent development of disease. Causal links are rarely established, because by definition no information is available regarding previous occupational exposures, lifestyle risk factors (e.g. smoking), family history, and other risk factors for disease. Only occasionally if there is good occupational hygiene history of exposure to a “smoking gun” (a well-established cause of the disease being studied) and the results are very strong and consistent, a probable causal link may be inferred. The causal inference would require other causal criteria such as dose-response to be satisfied as well. However, in this study there is no occupational hygiene data from the historical period in question. As well, diesel fumes are a suspected, but not an established causal factor for multiple myeloma. This study shows a statistical excess of multiple myeloma in South Essex Hall. When Waldenstrom’s was analysed separately it showed a statistical excess. No matter how these cases were divided, the development of these two cases in this work cohort was an uncommon event statistically. Statistical excesses by themselves are not very meaningful for many reasons outlined earlier in this report. The evidence here is far too limited to infer a causal link, although one may exist. There are three possible explanations for the observed statistical excess of multiple myeloma. 1. The results occurred by chance, even though they are statistically significant. The

precise probability of getting this result by chance is not possible to determine for the reasons outlined earlier in this report

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2. There is a true excess, but it is not related to exposures in Essex Hall. One or both of

the workers in question may have been exposed in prior occupational or medical settings or as part of their lifestyles. They may also have a predisposition to develop these cancers.

3. There is a true excess and it is related to occupational exposures in South Essex Hall.

These exposures may be general, experienced by most or all workers in South Essex Hall or they may be more limited, for example, to tool and die workers.

Since we lack historical occupational hygiene data, etiological research for multiple myeloma has not strongly pointed to specific causes and we have very limited data, it is difficult to determine which of these scenarios is most likely.

CML Although only one case of CML developed in this cohort, it is a somewhat unusual statistical event, as well, particularly when the more stable Ontario standard rates were used. CML, Waldenstrom’s and multiple myeloma are similar in that they are all disorders of blood cells originating in the bone marrow. The development of these three rare cancers, that share important characteristics, taken together, is suggestive of pertinent exposures. Furthermore, all three cancers occurred in men who started work in South Essex Hall workers who started before 1985. The evidence is not nearly sufficient, however, to infer a causal link to exposures in South Essex Hall.

Pattern The pattern of cancer development in this cohort differed from the expected pattern. Only about 2.5% of all cancers that developed were expected to be either myeloma or CML, using the expected values computed from the Windsor-Essex standard (Table 3). These rarer cancers, however, actually accounted for 11.1% (3/27) of the cancers that developed in the work cohort. The common cancers, lung and colon cancer, were expected to account for 29.4% of total cancers. However, they also accounted for only 11.1% (3/27) of the observed cancers. There was a marked excess of the three rarer cancers over the expected and a clear deficit of these two common cancers. Although, these proportions are not independent, the pattern is unusual, for these rare and related cancers to have the same incidence as the two common cancers.

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Tool and Die Work Two of the three rarer cancers of concern occurred in tool and die workers. The CML and Waldenstrom’s cases occurred in tool and die workers who worked at this trade for at least part of their work-time in Essex Hall. These two employees also worked in close proximity to one another. Although not all records have very specific job title information, for 10 of the 120 who started work in South Essex Hall before 1990, tool and die duties constituted, at least part, of their work. There are also 5 workers who may have done tool and die work, who were hired during this period, but their records are not specific enough to determine this definitively. Tool and die work was not limited to South Essex Hall. There were also 5 tool and die workers who were hired during this period who worked in North Essex Hall. Tool and die workers are exposed to a variety of chemicals in the workplace, including a group of substances routinely referred to as metalworking fluids. Metalworking fluids (MWFs) are commonly used in a number of industrial machining and grinding operations, which includes tool, and die work (28). Metalworking fluids (MWFs) are used to reduce heat and friction and to improve product quality in industrial machining and grinding operations (28). There is wide exposure to these fluids, approximately 1.2 million workers, in the United States, who are involved in machine finishing, machine tooling and other metalworking and metal-forming operations are potentially exposed (28). Exposure can occur through skin contact when equipment is handled that is covered with the fluids or by breathing aerosols generated in the machining process (28). The National Institute for Occupational Safety and Health (NIOSH) conducted a systematic review of the epidemiologic studies that examined the association between MWF exposure and cancer (26). The strongest evidence was found for an increased risk of cancer at several sites (larynx, rectum, pancreas, skin, scrotum, and bladder) associated with at least some MWFs used prior to the mid-1970s. But they also found much more limited evidence supportive of links with other cancers, including those in the hematopoietic system (26). Most of the few studies that have looked at exposure to MWFs and the rare cancers that we are particularly interested in have grouped cancer types together. For example, Park and Mirer (30) grouped non-Hodgkin's lymphoma and multiple myeloma together in their analyses. Others (29) grouped all lymphopoetic cancers together, which includes myeloma, some lymphomas and leukemia. Clearly, this clouds the results of the research for our purposes, since we are interested primarily in multiple myeloma and CML. Heinemen (27), however, in a very large study found a modest 40 percent increase in myeloma in Danish precision metal workers that was just statistically significant at the 5% level (Odds Ratio = 1.4 (1.0,2.1)). For every 10 cases expected, they found 14 cases. Precision metal work and tool and die work are very closely related. The tasks involved are very similar. The primary distinction is that tool and die workers require greater skill in order to qualify for their title. Since the trades are very closely related, we may reasonably assume that the exposures that the two trades would experience would be very similar. Park found that a small subset of his study group who had ever worked in grinding with soluble oils had an increased risk for myeloma and Non Hodgkin’s Lymphoma (they were

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combined in the analyses) (30). This proportionate mortality study found the PMR for this group to be 4.1 (p<.05) (30). A small standardized mortality study found that workers who had spent time in the tool and die area of an automotive plant (at least one month) had a high rate (SMR = 5.38, p<.05) of lymphopoetic cancer deaths (34). This SMR was based on only 3 lymphopoetic cancer deaths. It should be noted that many of the studies were Proportionate Mortality Studies (PMR) that generally provide weaker evidence than SIR or SMR studies. While the evidence is limited and most is not directly applicable, there are some indications of increased cancer rates in this broad group of lymphopoetic cancers. The evidence is weak, particularly considering that there were several negative studies as well. For example, two of the three cohort studies looking at hematopoietic or lymphopoietic cancers did not find significantly increased risk of these cancers in workers exposed to MWFs (26). It is important to note that there was little literature that looked specifically at myeloma and CML. As mentioned earlier, the term MWFs is a general term that refers to a wide range of substances. The exposures may differ considerably for different workers exposed during a particular point in time and have certainly changed over time. Risks may vary, then, for tool and die makers depending on which fluids they are exposed to and under what conditions, and of course depending on what proportion of the time that they were actually performing tool and die work. The risks associated with this type of work have almost certainly decreased in time as preventive measures have been taken in the past few decades to reduce exposures (31). Since we have no situation-specific industrial hygiene for workers exposed to MWFs in South Essex Hall and the employee records do not specify the particulars of the work done by employees classified as tool and die workers, we are left to speculate about specific exposures. Since changes in MWF composition that have occurred over the last several decades may not be sufficient to eliminate associated cancer risks, NIOSH recommends reductions in airborne MWFs (31). While tool and die work and metal work have been associated with increased risk of several cancers (26) there is very limited evidence of association with multiple myeloma and CML. It should be noted however that the studies in this area are limited, in terms of both quality and quantity, and the lack of strong evidence may be due to this limitation rather than a true lack of any effects. A possible interpretation of the rare cancer findings in this study is that the excess in these cancers were due, entirely or in part to exposures specifically associated with tool and die work. There is some supporting evidence for this interpretation. It is interesting that 2 of the 3 rare cancers occurred in tool and die workers who started before 1990, since only 10 of the 120 (8.3%) workers hired before 1990 were known to work in this trade. Four of the 13 (31 percent) total cancers (counting a second cancer that developed in one individual) that developed in male workers who started work in South Essex Hall before 1990, occurred

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in tool and die workers. There is some limited, evidence, then, that tool and die workers were generally at higher cancer risk. However, the evidence for an association between myeloma and CML and exposure to MWFs is limited and, at this point, equivocal. Little is known about Waldenstrom’s. Perhaps, more importantly, in South Essex Hall, we did not see any evidence at all of an excess of any of the cancers for which there is a strong link with MWFs exposures. Of the 4 cancers that developed in tool and die workers who started work in South Essex Hall before 1990, none occurred in a site strongly linked, in the literature, to MWF exposure. Moreover, of the 6 cancers, in the total cohort, that occurred in tool and die workers, none developed in a site for which there is strong evidence for a link to MWF exposure. In summary, the study results suggest that MWF exposures may have been largely responsible for the excess of rare cancers noted. The evidence supporting this contention, is however weak and circumstantial. Conclusions are limited by the very small number of relevant tool and die workers, and the limited knowledge about the relationship between MWF exposures from this time period and the rare cancers found in this study.

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J. Conclusions

1. The total (all cancers combined) cancer rates experienced by Essex Hall workers

who began work between 1955 and 2005, was dramatically lower than the cancer rates of the general population of Windsor-Essex (p<.05). In fact, these workers developed cancer at only ½ to 2/3 the rate of the Windsor-Essex standard population.

2. Male total cancer rates held at two thirds of the standard rates or less, regardless of

whether they worked in South or North Essex Hall.

3. Male total cancer rates held at two thirds of the standard rates or less, regardless of whether they started work before or after 1990.

4. It follows from 1. to 3. above that the results of this study do not support any excess

of total cancer in this work group. In fact, they point more to a deficit of total cancer.

5. It is very unlikely that the Healthy Worker Effect (HWE) explains a large portion of the low cancer rates described in 1. to 3. above.

6. Male lung cancer rates, for the entire cohort, were found to be only about 20 percent

of expected rates (p<.05). Stated differently, Essex Hall male workers developed only 1 lung cancer for every 5 lung cancers that occurred in similar males in Windsor-Essex.

7. Since smoking is a dominant cause of lung cancer, it is a reasonable implication that

this cohort of workers had low smoking rates. The reason for these low rates is not known but may be due to ethno-cultural factors or socioeconomic or other factors.

8. Since smoking is also causally related to many other cancers, low smoking rates

likely contribute to most of the deficit of cancer that developed in the cohort.

9. Ecological studies, such as this one, are blunt tools and therefore do not generally provide strong evidence for a causative relationship between an exposure and disease. This is particularly true, since there is no “smoking gun” in this study. A smoking gun is a well-established causal factor for a disease that workers were known to be exposed.

10. Although SIRs for prostate cancer generally showed a slight elevation, none was

statistically significant. Those who started working in Essex Hall before 1985 had the highest SIR. There were not many person-years in the highest risk age groups for prostate cancer in the post 1985 start date group making comparisons to the earlier start date group somewhat tenuous.

11. The small number of recorded workers who started work before 1985 hamper

somewhat the ability of the study to evaluate exposures in Essex Hall. It is also evident that since some cancers can take up to 25 years to develop, that follow-up

35

time may not be sufficient to identify many work related cancers in workers who started after 1985 and particularly after 1990.

12. The fact that the records of many workers who started work before 1985 were not

transferred to the current employee data base adds additional uncertainty to interpretation of study results.

13. It is difficult to decide how best to classify the Waldenstrom’s case given the

circumstances outlined earlier. The development of even one Waldenstrom’s in a group this size is unexpected, as it is an extremely rare condition. When analysed separately, the Waldenstrom’s SIR was very high at more than 23 (p<.05). This high SIR is due to the rareness of Waldenstrom’s.

14. This study shows a statistical significant excess of multiple myeloma (when the

Waldenstrom’s was counted as a myeloma) in South Essex Hall that was consistent with a causal link to exposures in South Essex Hall. The sum of the statistical and exposure data is too weak to differentiate between the possibilities that the excess of multiple myeloma was a chance finding, was a true finding but not due to Essex Hall exposures, or a true finding due to Essex Hall exposures.

15. Whether the Waldenstrom’s was analysed separately or as a myeloma, the

occurrence of these two rare cancers was a somewhat unusual statistical event.

16. Although only one case of CML developed in this cohort, it is a somewhat unusual statistical event, as well, particularly when the more stable Ontario standard rates were used. CML, Waldenstrom’s and multiple myeloma are similar in that they are all disorders of blood cells originating in the bone marrow. The development of these three rare cancers, that share important characteristics, taken together, is suggestive of pertinent exposures. Furthermore, all three cancers occurred in men who started work in South Essex Hall workers who started before 1985. The evidence is not nearly sufficient, however, to infer a causal link to exposures in South Essex Hall.

17. The pattern of cancer development was unusual in this cohort as the number of the

three rarer tumours originating in the bone marrow was equal to the number of the much more common lung and colon cancers. Although they are not independent, the proportion of total cancers that were due to the three rarer tumours was much greater than expected while the proportion of the common cancers was far smaller.

18. The study results suggest that MWF exposures experienced by tool and die workers,

may have been largely responsible for the excess of rare cancers noted. The evidence supporting a causal link between tool and die work and the rare cancers, however, is weak and circumstantial. Conclusions are limited by the small number of relevant tool and die workers, and the limited knowledge about the relationship between MWF exposures from this time period and the rare cancers found in this study. Additionally, none of the tool and die workers developed a cancer that is strongly linked to MWFs in the scientific literature.

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References

1. Essex Hall, University of Windsor; February 2002. Report I-017083. May 2002. 2. Pinchin Occupational Ltd. Health Hazard Investigation of the South Wing of National

Program of Cancer Registries Cancer Incidence and Mortality Report (USA) 2001. 3. Lee WJ, Baris D, Jarvholm B, Silverman DT, Bergdahl IA, Blair A. Multiple Myeloma

and Diesel and Other Occupational Exposures in Swedish Construction Workers. Int J Cancer. 2003 Oct 20;107(1):134-8.

4. Herrinton LJ, Weiss NS. Incidence of Waldenstrom's macroglobulinemia. Blood. 1993 Nov 15;82(10):3148-50.

5. Heineman EF, Olsen JH, Pottern LM, Gomez M, Raffn E, Blair A. Occupational risk factors for multiple myeloma among Danish men. Cancer Causes Control. 1992 Nov (6):555-68.

6. Ulm K. A Simple Method to Calculate The Confidence Interval Of a Standardized Mortality Ratio (SMR). American Journal of Epidemiology. 1990; 131(2):373-375.

7. Sagoe, Charles. Cancer Care Ontario. Personal Communication. January, 2008. 8. Pinchin Occupational Ltd. Health Hazard Investigation and Indoor Air Quality

Investigation of Essex Hall, University of Windsor. Report 41758. October, 2007. 9. IDSP. Report to the Workers’ Compensation Board on The Health Worker Effect. IDSP

Report No. 3, page 5, June 1988. 10. Sterling, TD, Weinkam JJ. Observations on Possible Sources, Extent, Persistence,

Constancy, and Corrections for the Healthy Worker Effect. In Report to the Workers’ Compensation Board on The Health Worker Effect. IDSP Report No. 3, page 111, June 1988. Grouse L. National Cancer Institute. Multiple Myeloma. Benchmarks. 5(3) June 25, 2005.

11. Joshi SC, Pant I, Shukla AN. Benzene Exposure and Its Relation to Multiple Myeloma. JCDR 1(4), August 2007, 325-329.

12. Grouse L. National Cancer Institute. Multiple Myeloma. June 22, 2005. 13. Groves FD, Travis LB, Devesa SS, Lynn A. G. Ries LAG, Joseph F. Fraumeni, Jr.

Waldenstrom’s Macroglobulinemia. Incidence Patterns in the United States, 1988–1994 14. Demers PA, Vaughan TL, Koepsell TD, Lyon JL, Swanson GM, Greenberg RS, Weiss

NS. A case-control study of multiple myeloma and occupation. Am J Ind Med. 1993 Apr;23(4):629-39.

15. MMWR Weekly. Trends in Prostate Cancer – United States 1980-1988, 41(23):401-404, June 12, 1992

16. Doll R, Hill Ab. Lung cancer and other causes of death in relation to smoking; a second report on the mortality of British doctors. Br Med J. 1956 Nov 10;2(5001):1071-81

17. Kyle RA, Rajkumar SV. Epidemiology of the plasma-cell disorders. Best Practice & Research Clinical Haematology. 20(4):637-664,2007.

18. Boffeta P, Stellman SD, Garfunkel L. A case-control study of multiple myeloma nested in the American Cancer Society prospective study. Int J Cancer (43):554-559, 1989.

37

19. Flodin U, Fredriksson M, Persson B. Multiple Myeloma and engine exhausts, fresh wood, and creosote: a case-referent study. Am J Ind Med. 12(5):519-529. 1987.

20. National Cancer Institute. Fact Sheet. Waldenstrom Macoglobulinemia: Questions and Answers.

21. UPMC. Health A-Z. CML. January 2008. 22. Bezabeh S, Engel A, Morris CB and Lamm SH. Does Benzene Cause Multiple

Myeloma? An Analyses of the Published Case-Control Literature. Environmental Health Perspectives. (104) (Supp. 6), December 1996.

23. King Mary Jane. Cancer Care Ontario. Personal Communication. January, 2008. 24. CDC NPCR. United States Cancer Statistics. By cancer type and race. 2001. 25. Infante PF. Benzene Exposure and Multiple Myeloma. A Detailed Meta-analysis of

Benzene Cohort Studies. 1076(90-109), September, 2006. 26. Calvert GM, Ward E, Schnorr TM, Fine LJ. Cancer risks among workers exposed to

metalworking fluids: a systematic review. Am J Ind Med. 33(3):282-92, 1998. 27. Heineman EF, Olsen JH, Pottern LM, Gomez M, Raffn E, Blair A. Occupational risk

factors for multiple myeloma among Danish Men. Cancer Causes Control. 1992 Nov;3(6):555-68.

28. NIOSH Health and Safety Topic. Metalworking fluids. 29. Silverstein M, Park R, Marmor M, Maizlish N, Mirer F. Mortality among bearing plant

workers exposed to metalworking fluids and abrasives. J Occup Med 30(9):706-14, 1988.

30. Park RM, Mirer FE. A Survey of Mortality at Two Automotive Engine Manufacturing Plants. A J Ind Med 30(6):664-673, 1996.

31. Criteria for a Recommended Standard: Occupational Exposure to Metalworking Fluids. NIOSH Publication No. 98-102: January 1998.

32. Forums held with Essex Hall workers. August 2006. 33. Harold, Leigh. University of Windsor. Personal Communication. 2008. 34. Park R, Krebs J, Mirer F. Mortality at an automotive stamping and assembly complex.

Am J Ind Med. 1994 Oct;26(4):449-63.

38

Tables

Table 1

Starting work dates by decade

By Starting date in Essex Hall

Numbers PercentagesDecade males females males females

1950s 5 0 0.9 0.01960s 57 4 9.7 1.91970s 28 12 4.8 5.61980s 120 50 20.5 23.51990s 203 87 34.6 40.82000s 173 60 29.5 28.2

Totals 586 213 100 100

Table 2Partitioned Person‐Years

Table 2aEntire Cohort

person‐years percentages in age groupAge grouping Males Females Males Females15‐24 years 189.6 182.5 2.1 6.325‐34 years 1812.5 859.9 20.0 29.635‐44 years 2902.5 910.9 32.0 31.445‐54 years 2060.6 581.7 22.7 20.055‐64 years 1285.5 267.4 14.2 9.265‐74 years 611.6 59.7 6.7 2.175‐84 years 181.4 29.1 2.0 1.085+ years 37.9 11.1 0.4 0.4

Total 9081.6 2902.3 100.0 100.0

Table 2bBy work location in Essex Hall

Males Onlyperson‐years percentages in age group

Age grouping South North South  North15‐24 years 114.4 75.2 2.2 2.025‐34 years 1021.6 791.0 19.5 20.635‐44 years 1711.3 1191.2 32.7 31.045‐54 years 1228.6 831.9 23.5 21.655‐64 years 743.6 541.9 14.2 14.165‐74 years 304.2 307.4 5.8 8.075‐84 years 100.0 81.4 1.9 2.185+ years 13.0 24.9 0.2 0.6

Total 5236.7 3844.9 100.0 100.0Grand Total 9081.6

Table 2cBy Starting date in Essex Hall

males onlyperson‐years percentages in age group

Age grouping pre 1990 post 1990 pre‐1990 post‐199015‐24 years 87.8 101.9 1.5 3.325‐34 years 894.2 918.3 15.0 29.535‐44 years 1675.2 1227.3 28.0 39.545‐54 years 1507.7 552.8 25.2 17.855‐64 years 1027.7 257.7 17.2 8.365‐74 years 565.4 46.2 9.5 1.575‐84 years 177.0 4.4 3.0 0.185+ years 37.9 0.0 0.6 0.0

Total 5972.9 3108.6 100.0 100.0Grand total 9081.5

Table 3

SIRs: Males Summary Analyses – Entire Work Cohort

Cancer Type  Observed 

Windsor‐Essex 

expected Ontario Expected 

SIR Windsor‐Essex 

90% CI Windsor‐Essex 

SIR Ontario 

90% CI Ontario 

Total  27  45.86  43.20  0.59  [.42,.82]**  0.62  [.45,.87]** multiple myeloma  2  0.6  0.57  3.33  [1.1,10.5]*  3.51  [1.2,11.1]* 

Prostate  11  9.24  8.49  1.19  [.71,2.0]  1.30  [0.77,2.2] 

Lung  2  10  8.26  0.20  [.07,.63]**  0.24  [.08,.77]** 

Colon  1  3.5  4.05  0.29  [.10,1.3]  0.25  [.09,1.2] 

CML  1  0.58  0.23  1.72  [.60,8.0]  4.35  [1.5,20.2]* 

Ontario - using 1986/1996 Ontario standard Windsor-Essex - using 1986/1996 combined Windsor-Essex standard * statistically significant at the 10% level ** statistically significant at the 5% level

Table 4

SIRs: Males by location in Essex Hall

 

- Ontario 1986/1996 Standard -

Cancer Type South 

Observed North 

Observed South 

Expected North 

Expected Total 

Expected  SIR South  90% CI SIR 

North 90% CI 

Total  16  11  23.61  19.59  43.20  0.68  [0.44, 1.0]  0.56 [.33,.94]**multiple melanoma  2  0  0.31  0.26  0.57  6.44  [2.2,20.4]  0.00   Prostate  5  6  4.48  4.01  8.49  1.12  [0.52,2.4]  1.50 [0.74,3.0] Lung  2  0  4.50  3.76  8.26  0.44  [0.15,1.4]  0.00   Colon  1  0  2.20  1.85  4.05  0.45  [0.16,2.1]  0.00   myeloid leukemia  1  0  0.13  0.10  0.23  7.82  [2.8,36.3]  0.00   

- Windsor-Essex 1986/1996 Standard -

Cancer Type South 

Observed North 

Observed South 

Expected North 

Expected Total 

Expected  SIR South  90% CI SIR 

North  90% CI Total  16  11  25.12  20.74  45.86  0.64  [.41,.98]*  0.53  [.31,.87]**multiple myeloma  2  0  0.34  0.26  0.6  5.88  [1.98,18.6]*  0.00    Prostate  6  5  4.91  4.33  9.24  1.02  [..47,2.17]  1.39  [.53,2.43] Lung  2  0  5.42  4.57  9.99  0.37  [.12,1.2]  0.00    Colon  1  0  1.87  1.63  3.5  0.53  [.19,2.5]  0.00    myeloid leukemia  1  0  0.32  0.26  0.58  3.13  [1.1,14.5]*  0.00     Ontario - using 1986/1996 Ontario standard Windsor-Essex - using 1986/1996 combined Windsor-Essex standard * statistically significant at the 10% level ** statistically significant at the 5% level

Table 5

SIRs: Males by Start date in Essex Hall

Pre 1990/1990 and later

Cancer Type  Time started  Observed 

Windsor‐Essex 

expected Ontario expected 

SIR Windsor‐Essex 

90 CI Windsor‐Essex 

SIR Ontario  90% CI Ontario

Total   pre 1990  23  38.06  35.94  0.60  [0.42,.86]**  0.64     [0.45,.91]**   1990 or later  4    7.79   7.21  0.51  [0.22,1.2]  0.55     [0.24,1.3] Multiple myeloma  pre 1990  2  0.49  0.48  4.08  [1.4,12.9]*  4.15    [1.4,13.1]*    1990 or later  0  0.11  0.08  0.00    0.00    Prostate  pre 1990  10  8.22  5.59  1.22  [0.7,2.1]  1.32      [0.77,2.3]    1990 or later  1  1.02      0.57  0.98  [0.35,4.6]  1.08      [0.38,5.0] Colon  pre 1990  1  3.06  3.60  0.33   [0.12,1.5]  0.29      [0.10,1.4]    1990 or later  0  0.44  0.67  0.00    0.00   Lung  pre 1990  1  8.38  7.78  0.12   [0.04,.55]**  0.14   [.05,.66]**    1990 or later  1  1.61  1.41  0.62  [0.22,2.9]  0.81     [.29,3.8] CML  pre 1990  1  0.46  0.16  2.17  [0.77,10.1]  5.50   [2.0,25.6]*    1990 or later  0  0.12  0.04  0.00    0.00    

Ontario = using 1986/1996 Ontario standard Windsor-Essex = using 1986/1996 combined Windsor-Essex standard * statistically significant at the 10% level ** statistically significant at the 5% level

Table 6

Started Work at Essex Hall Pre and Post 1985

(males only)

Cancer Type  Time started  Observed

Windsor‐Essex 

expected Ontario expected 

SIR Windsor‐Essex 

90% CI Windsor‐Essex 

SIR Ontario

90% CI Ontario 

Total   pre 1985  23  32.31  30.58  0.71  [.50,1.02]  0.75   [.53,1.1]    1985 or later  4  13.55  12.62  0.30    [.13,  .69]** 0.32   [.14,.74]**Multiple myeloma  pre 1985  2  0.4  0.4 ,   6,15.3]*1  5.00    [1.7 15.8]* 4.84   [1.   1985 or later  0  0.2  0.1 0.00    0.0   6  0 Prostate  pre 1985  10  7.27  6.68  1.38    [.80,2.4]  1.50   [.87,2.6]    1985 or later  1  1.97  1.81  0.51    [.18,2.4]  0.55   [.20,2.6] Colon  pre 1985  1  6  3.0 3,. 6] 2.6 8  0.38    [.1 1.8]  0.34   [.12,1.   1985 or later  0  4  1.1 0.00    0.00.8 9  0   Lung  pre 1985  1  7.17  6.04  0.14    [.05,.  65]** 0.17   [.06,.77]**   1985 or later  1  2.83  2.22  0.35    [.13,1.6]  0.45   [.16,2.1] CML  pre 1985  1  8  0..1 3. 4,31.2]*0.3 5  2.63  [.9 12.2]  6.71   [2.   1985 or later  0  0.2  0.0 0.00    0.0   8    0 

Ontario = using 1986/1986 Ontario standard Windsor-Essex = using 1986/1996 combined Windsor-Essex standard * statistically significant at the 10% level ** statistically significant at the 5% level

Table 7

SIRs: Males Summary Analyses – Entire Work Cohort

Waldenstrom’s/Myeloma Alternative Analyses

Cancer Type  Observed 

Windsor‐Essex 

expected Ontario Expected

SIR Windsor‐Essex 

90% CI Windsor‐Essex

SIR Ontario  90% CI Ontario

Total  27  45.86  43.20  0.59  [.42,.82]**  0.62  [.45,.87]** 

multiple myeloma  2  0.6  0.57  3.33  [1.1,10.5]*  3.51  [1.2,11.1]* 

Analysed Separately               

multiple myeloma  1  0.6  0.57  1.67  [.59.7.7]  1.77  [0.63,,8.2] 

Waldenstrom’s  1  0.03  0.03  23.4  [8.31,109]** 23.4  [8.31,109]**  Ontario - using 1986/1996 Ontario standard Windsor-Essex - using 1986/1996 combined Windsor-Essex standard Waldenstrom’s – based on United States rates estimated from (13) * statistically significant at the 10% level ** statistically significant at the 5% level