Post on 20-Jul-2020
transcript
IMPACT OF CANCER ON HEALTH RELATED QUALITY OF LIFE: EVIDENCE USING THE EQ-5D
A. Simon Pickard1,2
Caitlyn Wilke1,2
Hsiang-Wen Lin1,2
Andrew Lloyd3
1Center for Pharmacoeconomic Research & Dept Pharmacy Practice, College of Pharmacy,Room 164, 833 S. Wood St (MC886), University of Illinois at Chicago, Chicago, IL, 60612
USA;2 Department of Pharmacy Administration, College of Pharmacy.
3Health Care Analytics Group, United BioSource Corporation, 20 Bloomsbury Square,London, UK
370
AddressesA. Simon Pickard, PhD (Corresponding Author)College of PharmacyRm 164, MC 886 833 South Wood StreetUniversity of Illinois At ChicagoChicago, Illinois, 60612Ph: (312) 413-3357fax: (312) 996-0397 Email: pickard1@uic.edu
Key Words: HRQL, cancer, EQ-5D
In-Text Abbreviations:CHOP- cyclophosphamide, doxorubicin, vincristine, prednisone; CUA- cost utility analysis; HUI-health utilities index; HRQL- health related quality of life; IPI- International Prognostic Index; IQR-Inter-quartile range; nr- not reported; SD- standard deviation; SEER- Surveillance Epidemiology andEnd Results; QALY- quality adjusted life year; VAS- Visual analog scale; WHO- World HealthOrganization
Acknowledgements:The authors acknowledge funding support from the EuroQol Group Foundation.
••• ABSTRACT
••• BACKGROUND AND PURPOSE:
Cancer is one of the most frequent disease-specific applications of the EQ-5D. The objective of this study is to describe the burden of illness associatedwith various cancer types measured by the EQ-5D and to provide guidance forfuture studies to increase uniformity and comparability of EQ-5D results.
••• METHODS:
A structured literature search was conducted on EMBASE and MEDLINE toidentify papers using keywords related to cancer and the EQ-5D. Original rese-arch studies of patients with cancer that reported EQ-5D results or psychome-tric properties were included for the review.
Results: Of 57 identified articles, 31 studies were selected for inclusion. EQ-5D scores were reported in multiple studies of prostate cancer (n= 4), breastcancer (n= 4), cancers of the digestive system (n= 7), and Hodgkin and/or non-Hodgkin lymphoma (n= 3). Mean index-based scores ranged from 0.33 (SD 0.4)to 0.93 (SD 0.12) and VAS scores ranged from 43 (SD 13.3) to 84 (SD 12.0) acrosssubtypes of cancer.
••• CONCLUSIONS:
A substantial body of literature supports the use of the EQ-5D in cancer.EQ-5D index and VAS scores ranged widely due to heterogeneity of treatmentprotocols, cancer stage, and subtype of cancer. This summary of the availableliterature on utility-based estimates of HRQL in cancer using the EQ-5D is inten-ded as a resource for outcomes research and economic evaluations in this area.
371
372
••• INTRODUCTION
In 2000, there were 22.4 million individuals living with cancer, 10.1million new cases diagnosed annually, and 6.2 million deaths worldwide1. Thelifetime probability of developing cancer in the United States is 46% for menand 38% for women2. According to the World Health Organization (WHO),“the average five-year survival rate for cancer patients is 50% in developedcountries, 30% in developing countries”1. In addition to the uncertainty ofsurvival time, cancer patients must attempt to strike a balance between thephysiological benefits of treatment and the negative impact of these thera-pies on daily life1. Assessment of health-related quality of life (HRQL) can helpto better understand the physical, mental, and emotional implications of thecancer itself as well as effects of treatments such as chemotherapy, radiothe-rapy, and/or surgery.
Measurement of HRQL in cancer may be assessed using cancer specific ins-truments such as the EORTC QLQ-C303,4 and the FACIT measurement system5.Alternatively, generic HRQL preference-based measures such as the HealthUtilities Index (HUI)6 and EQ-5D7 may be used. Preference-based measures areadvantageous because they are an appropriate means for calculating qualityadjusted life years (QALYs) for subsequent application to cost-utility analysis(CUA) and allow for easy comparisons of HRQL burden across different condi-tions and treatments.
Among the generic measures available, the EQ-5D is widely used and sim-ple to administer and score. A preference-based set of weights are used to con-vert patient responses to a health state classifier into a single index of HRQL.Each of the five dimensions (mobility, self care, usual activities, pain/discomfort,and anxiety/depression) on the health state classifier has three levels of respon-se: no problems, some problems, or extreme problems. In addition to the self-classifier, the EQ-5D contains a 20 centimeter visual analogue scale (VAS) ran-ging from 0 (worst imaginable health state) to 100 (best imaginable healthstate) on which an individual places their current health state. The index-basedscore is typically interpreted along a continuum where 1 represents best possi-ble health and 0 represents dead, with some health states being worst thandead (<0). The ability to convert self classifier responses into a single preferen-ce-based score makes the EQ-5D practical for clinical and economic evaluation7.Algorithms have been developed based on the preferences of the generalUnited Kingdom population8, and other country-specific algorithms have beendeveloped for further use9,10.
It is common, if not usual practice, to include HRQL measures in clinicaltrials in oncology. Such trials, as well as some cross-sectional studies intended todescribe burden of HRQL in a cancer, may include utility-based measures suchas EQ-5D which provide quality weights for the calculation of QALYs in econo-
mic evaluation. National catalogs of preference-based scores for chronic condi-tions have begun to appear in the literature11. A catalog of preference-basedscores for cancer-related conditions and stages/phases of treatment would beuseful to compare of the burden of specific cancers relative to the other healthconditions. A catalog of HRQL burden in cancer would help can help to informutilities assigned to different health state endpoints in decision models for eco-nomic evaluations of cancer therapy. Earle and colleagues (2000) previouslyreported a catalogue of utility weights in oncology12. Many advances haveoccurred since that review, including current practice in economic evaluation aswell as a greatly expanded literature using preference-based HRQL measures incancer13,14. A summary of studies that have applied a specific measure such asthe EQ-5D to describe the burden of cancer may further support consistency incost-effectiveness and cost-utility analysis.
This study had 2 objectives. First, the objective was to examine the eviden-ce to support the validity and reliability of the EQ-5D in cancer. Second, wesought to describe the burden of illness associated with various types of cancerin terms of HRQL as defined by the EQ-5D self-classifier and summary scores. Asecondary objective was to provide guidance for future studies to increase uni-formity and usefulness of results reported in cancer studies using the EQ-5D.
••• METHODS
DATA COLLECTION AND ASSESSMENT
A computerized search of the current published literature was performedusing MEDLINE and EMBASE for years 1988 to January 2006. The search strategycombined medical subject headings and keywords relating to cancer and theEQ-5D as follows: (‘cancer’/de OR ‘cancer’) OR (‘oncology’/de OR ‘oncology’) OR(‘neoplasms’/de OR ‘neoplasms’) AND Euroqol OR ‘EQ 5D’ OR ‘EQ5D’. Authorlibraries were also hand-searched for references. Only papers which werepublished in full were included for analysis. The inclusion criteria required thatthe paper was original research, patients had a diagnosis of cancer, and that thearticle reported EQ-5D psychometric properties or reported EQ-5D index, visualanalog scale, or % dimension scores for cancer patients. There were no langua-ge restrictions15. Study abstracts that potentially met the inclusion criteria wereidentified, and full text articles were retrieved for further review15. A standar-dized data abstraction form was developed to facilitate the structured review,which included study design, patient characteristics, intervention information,published source of index-based preference weights and EQ-5D scores. The abs-traction form is available upon request. Two of the authors reviewed abstractsof unique citations identified in the literature search (ASP, CTW). Articles mee-
373
ting the inclusion criteria were abstracted and checked for veracity (CTW, HWL).Any disagreements between the reviewers in screening and selecting the arti-cles for review were resolved by consensus.
DATA ANALYSIS
Studies that reported EQ-5D index-based scores and/or VAS scores weresorted by cancer type and last name of the first author. Studies reporting mul-tiple cancer types were included at the end of the table. Standard deviationswere calculated from 95% confidence intervals when not reported directly inthe paper. Y-error bars in figures 3-5 represent the 95% confidence intervalabout the mean score, which was calculated from reported standard deviations.
Psychometric properties presented in table 2 were summarized as follows:type of validity/reliability, comparison performed, and statistical test result.Known-groups comparisons were not included in this summary of psychometricproperties unless clearly indicated for the purpose of psychometric evaluation.
An attempt was made to summarize the burden of cancer for each subty-pe by calculating pooled means across studies. Random effects-based pooledmeans were calculated using the DerSimonian and Laird method16 for thosetypes of cancer which had more than one reported mean/standard deviation,first calculating an inverse variance fixed effects pooled mean (1) and tau sta-tistic of heterogeneity (2):
(1) (2)
Where θi is the mean for each individual study, Q is a measure of hetero-geneity, k-1 is the degrees of freedom for the studies included in the pooledestimate, and wi is the weight of each term, calculated as follows:
(3)
374
The Dersimonian and Laird random effects pooled mean is calculated witha weight adjusted for τ:
(4) (5)
with standard error calculation:
(6)
Serial assessments of HRQL reported in a paper were included in theresults, but only the baseline mean scores were included in pooled mean esti-mates. This was consistent with the objective of summarizing the burden of ill-ness attributed to different types of cancer without incorporating repeatedmeasurements into the pooled estimate of HRQL burden. When calculable, ran-dom effects pooled means were plotted alongside results for each cancer type.The formulas were inputted and statistics calculated with MS Office Excel ver-sion 2003.
••• RESULTS
The electronic search of databases on January 12, 2006 returned 57 papers.An additional 7 articles were identified in personal libraries for a total of 63articles. Of 46 publications retrieved for review, 34 papers met the selection cri-teria, 31 which reported an EQ-5D index score, VAS score, and/or responses tothe self-classifier system and 12 papers presented evidence of the psychometricproperties of the EQ-5D (Figure 1). The number of cancer-related studies thatreported HRQL using EQ-5D has increased over the past decade (Figure 2).
Measurement of HRQL using EQ-5D has been performed in a variety ofcancer subtypes, severities (tumor/cancer stages), and treatment regimens.HRQL assessments using the EQ-5D were reported primarily in studies of cancerof the breast11,18-23, digestive system24-30, Hodgkin and/or non-Hodgkin lymp-homas31-34, and prostate11,35-38. Other cancer studies using the EQ-5D includedpatients with neoplasms of the bones and joints, cranial nerves and other ner-
375
376
vous system, multiple myelomas, and lung cancer39-42. Some studies did notreport the nature/location of the cancer, where patients were characterized aseither simply having ‘cancer’, or stating that multiple types of cancer weregrouped together11,32,43-48. Of studies reporting mode of administration (n=27,87%), 30% were on-site self-report, 52% were mailed-out questionnaires, and18% were administered by in-person interview. The study setting was prima-rily hospital-based (81% of studies). The majority of studies (57%) involved mul-tiple settings, while 43% were administered at a single setting. Most studies(88%) reported EQ-5D index scores using the York MVH derived algorithm.Study populations varied with respect to therapy, age distribution, and stage oftreatment (Table 1).
A wide range of mean/median EQ-5D scores were reported in the literatu-re (Table 3). The lowest five EQ-5D index scores reported occurred in the follo-wing populations: cancer-related anorexia cachexia syndrome patients measu-red at baseline44, multiple myeloma patients discharged after high dose che-motherapy41, patients receiving palliative treatment for oesophageal carcino-ma26, patients with Hodgkin or non-Hodgkin lymphoma 14 days post-autolo-gous peripheral blood stem cell transplantation or autologous bone marrowtransplantation33, and elderly non-Hodgkin lymphoma patients with age-adjus-ted IPI of 2-3 at baseline, prior to treatment with CHOP chemotherapy31. Lowscores were not related solely to one particular type of cancer, but rather variedaccording to treatment type and patient subgroup (Figures 3 - 5).
Most studies of cancer patients that reported psychometric properties ofthe EQ-5D investigated construct validity of the EQ-5D, typically through corre-lations with cancer-related clinical characteristics or with cancer-specific HRQLmeasures (Table 2). Evidence of validity and reliability were reported most fre-quently in breast and prostate cancer studies as well as studies that combinedcancer types. Convergent validity was the most common property assessed,typically reported in the form of association with another measure usingPearson’s correlation coefficient. Comparisons were made between the EQ-5Dand Musculoskeletal Tumor Society functional evaluation system (MTSS), TTOmeasurements, Functional Living Index- Cancer (FLIC), EORTC- QLQ C-30, SF-36,and simple VAS scales.
Of the 69 EQ-5D index-based scores shown in Figures 3, 4, and Table 3, 26studies (37.7%) did not report a standard deviation. Of studies that reportedEQ-5D index or VAS scores, 7 out of 31 studies (22.6%) did not report standarddeviations (Figure 5). The random effects pooled mean of prostate cancer EQ-5D mean index scores was 0.756 (SE 0.07) and 0.785 (SE 0.05) for cancers of thedigestive system. Insufficient statistical data were available from articles inother cancer types to enable the calculation of pooled mean summary scores.For instance, only one breast cancer study and no Hodgkin’s or Non-Hodgkinlymphoma studies reported standard deviations for mean EQ-5D index scores,
precluding the estimation of fixed or random effects pooled means. In exami-ning the dimension-specific burden of disease among studies that reported per-centage of problems by dimension, usual activities and anxiety/depression ten-ded to be more adversely affected by cancer (Figures 6 – 10).
••• DISCUSSION
The available literature on the HRQL burden of cancer using EQ-5D hasgreatly expanded in recent years. This trend is consistent with the acceptanceof patient reported outcomes and quality of life as a routine measures to beincorporated into clinical trials, and of the EQ-5D as one of the internationalstandard metric of health status. The catalog of preference-based summary sco-res based on the EQ-5D index-based and VAS reported in this paper for cancer-related conditions elaborates upon the more general catalogs of scores repor-ted by Sullivan et al11 and Tengs51. Cost-utility analyses rely heavily on genericmeasures such as the EQ-5D for the determination of quality adjusted life years(QALYs). This review expands upon Earle et al’s (2000) examination of cost-uti-lity assessment in the field of oncology, with an exclusive focus on studies usingthe EQ-5D12. The EQ-5D index values found in Figures 3 and 4 could be used tocalculate QALYs in a similar fashion to compliment the previous paper.
The number of studies published on the various types of cancer mirroredtheir relative prevalence. Breast cancer was the most prevalent cancer worldwi-de in 2000, followed by colorectal cancer and prostate cancer1. This reviewfound studies of those types of cancer to be the most common among the lite-rature that included the EQ-5D.
As would be expected, cancer patients had lower index and VAS scoreswhen compared to the studies of the general population using the EQ-5D.Across all cancer studies, the median index scores summarized was 0.75 (IQR0.61 - 0.84) and median VAS score was 71.5 (IQR 60.3 - 76.7), much lower thanmean scores reported for the US general population of 0.87 (SD 0.01)52 and 82(SD 14) with median score 8553, respectively. A general population survey fromAlberta, Canada reported an index-based mean score of 0.914 (SD 0.15) andVAS mean score of 84.8 (11.6) for individuals with no medical problems. Thatstudy also reported mean estimates index-based mean score of 0.77 (0.20) andVAS of 70.4 (SD 19.6) for community-based individuals with cancer,54 similar tothe average burden observed in studies included in this review. Among the can-cer studies reporting problems according to dimension, usual activities,pain/discomfort and anxiety/depression were the greatest sources of burden.
Psychometric properties, when reported, supported the use of the EQ-5Din the various types of cancer. There was evidence of agreement betweenresults reported by the EQ-5D and those reported by both generic and specific
377
measures of HRQL in cancer populations. The validity and test-retest reliabilityof the EQ-5D was generally supported. Several studies used relationships bet-ween EQ-5D and other measures to support their validity, evidence that the EQ-5D is recognized as one of the standards in the field of HRQL and patient-repor-ted outcomes in oncology.
Much heterogeneity in scores was observed across studies. Differences inHRQL burden between cancer studies was not solely attributed to subtype ofcancer, as the diverse range of mean/median scores could have been due tostage of illness, treatment phase, and non-cancer related sample characteristicssuch as co-morbid conditions and age as well as other unmeasured factors. Inaddition, not all studies used the same algorithm to calculate index-based sco-res. The choice of algorithm used to convert self-classifier scores will affect theindex score presented, as seen in Hamashima et al’s study on rectal cancer inJapan, which reported index scores calculated by both the Ikeda and Dolanalgorithms24. Country specific scoring would be most useful to decision makersin health care that use evidence from CUA to guide allocation of resources. Forenhanced comparability between studies in the literature, however, a “com-mon currency” for calculating EQ-5D index-based scores for the classifier maybe a worthwhile consideration. The expanding body of literature in cancer stu-dies that employ the EQ-5D suggests that the EuroQol group establish an onco-logy repository for EQ-5D scores for the continuance of this review. While onlya handful of studies reported HRQL values according to stage of disease andlevel of toxicity at present, a repository would be important resource to thosewho wish to model cancer-related endpoints in economic evaluations of healthcare interventions.
Statistics for group level data as commonly reported in the literature is notconducive to meta-analysis. Studies often reported only medians, or meansunaccompanied by standard deviations. We calculated pooled mean estimatesfor several types of cancer, but acknowledge there were substantial and statis-tically significant heterogeneity between pooled studies, and many studiescould not be included in a pooled mean estimate due to the absence of a repor-ted mean and standard deviation. In addition to statistical heterogeneity, subs-tantial differences in study designs and patient demographic and clinical cha-racteristics were noted.
In summary, the number of published studies reporting the use of EQ-5Din cancer has increased in recent years. The broad range of EQ-5D index-basedand VAS mean scores in these studies likely reflects some systematic varianceattributable to stage of treatment protocols, progression of disease, and typeof cancer in addition to patient characteristics such as age. The report of bothmean (standard deviation) and median (interquartile range) EQ-5D scores instudies of cancer would facilitate comparisons burden of HRQL between studiesand conditions. There is an emerging interest in health state preferences as
378
experienced by patients with the condition which may represent a future areafor research using the EQ-5D in cancer. There continues to be much opportunityfor research using EQ-5D in cancer that would fill gaps in knowledge relatingto values associated with cancer stage by type of cancer; values associated withcommon sites of metastases within various types of cancer; and values for com-mon treatment-induced toxicities.
379
••• REFERENCES
1 World Cancer Report. Lyon: IARC Press, 2003
2 Jemal A, Murphy T, Ward E, Samuel A, Tiwari RC, Ghafoor A, et al. CancerStatistics, 2005. CA Cancer J Clin 2005; 55:10-30
3 Aaronson NK, Ahmedzai S, Bergman B, Bullinger M, Cull A, Duez NJ, et al.The European Organization for Research and Treatment of Cancer QLQ-C30: a quality-of-life instrument for use in international clinical trials inoncology. J Natl Cancer Inst 1993; 85:365-76
4 de Haes J, Curran D, Young T, Bottanbley A, Flechtner H, Aaronson N, et al.Quality of life evaluation in oncological clinical trials - the EORTC model.The EORTC Quality of Life Study Group. Eur J Cancer 2000; 36:821-5
5 Webster K, Cella D, Yost K. The Functional Assessment of Chronic IllnessTherapy (FACIT) Measurement System: properties, applications, and inter-pretation. Health Qual Life Outcomes 2003; 1:79
6 Feeny D, Furlong W, Boyle M, Torrance GW. Multiattribute Health-StatusClassification Systems - Health Utilities Index. Pharmacoeconomics 1995;7:490-502
7 Rabin R, de Charro F. EQ-5D: a measure of health status from the EuroQolGroup. Ann Med 2001; 33:337-43
8 Dolan P. Modeling valuations for EuroQol health states. Med Care 1997;35:1095-108
9 Tsuchiya A, Ikeda S, Ikegami N, et al. Estimating an EQ-5D population valueset: The case of Japan. Health Econ 2002; 11:341-53
10 Shaw JW, Johnson JA, Coons SJ. US valuation of the EQ-5D health states:development and testing of the D1 valuation model. Med Care 2005;43:203-20
11 Sullivan PW, Lawrence WF, Ghushchyan V. A national catalog of preferen-ce-based scores for chronic conditions in the United States. Med Care 2005;43:736-49
380
12 Earle CC, Chapman RH, Baker CS, et al. Systematic overview of cost-utilityassessments in oncology. J Clin Oncol 2000; 18:3302-17
13 NICE. Technical guidance for manufacturers and sponsors on making a sub-mission to a technology appraisal: UK, 2001
14 Russell LB, Gold MR, Siegel JE, Daniels N, Weinstein MC. The role of cost-effectiveness analysis in health and medicine. Panel on Cost-Effectivenessin Health and Medicine. JAMA 1996; 276:1172-1177
15 Moher D, Cook DJ, Eastwood S, Olkin I, Rennie D, Stroup DF. Improving thequality of reports of meta-analyses of randomised controlled trials: TheQUOROM statement. Lancet 1999; 354:1896-900
16 DerSimonian R, Laird N. Meta-analysis in clinical trials. Control Clin Trials1986; 7:177-88
17 Deeks J, Altman D, Bradburn M. Statistical methods for examinine hetero-geneity and combining results from several studies in meta-analysis. In:Egger M, Smilth G, Altman D, eds. Systematic Reviews in Health Care:Meta-analysis in context. London: BMJ Publishing, 2001. p. 285-311
18 Conner-Spady B, Cumming C, Nabholtz JM, Jacobs P, Stewart D.Responsiveness of the EuroQol in breast cancer patients undergoing highdose chemotherapy. Qual Life Res 2001; 10:479-86
19 Conner-Spady BL, Cumming C, Nabholtz JM, Jacobs P, Stewart D. A longi-tudinal prospective study of health-related quality of life in breast cancerpatients following high-dose chemotherapy with autologous blood stemcell transplantation. Bone Marrow Transplant 2005; 36:251-9
20 Jansen SJ, Otten W, van de Velde CJ, Nortier JW, Stiggelbout AM. Theimpact of the perception of treatment choice on satisfaction with treat-ment, experienced chemotherapy burden and current quality of life. Br JCancer 2004; 91:56-61
21 Polsky D, Keating NL, Weeks JC, Schulman KA. Patient choice of breast can-cer treatment: impact on health state preferences. Med Care 2002;40:1068-79
22 Verkooijen HM, Buskens E, Peeters PH, Borel Rinkes IH, de Koning HI, vanVrounhoven TJ, et al. Diagnosing non-palpable breast disease: short-term
381
impact on quality of life of large-core needle biopsy versus open breastbiopsy. Surg Oncol 2002; 10:177-81
23 Gerard K, Johnston K, Brown J. The role of a pre-scored multi-attributehealth classification measure in validating condition-specific health statedescriptions. Health Econ 1999; 8:685-99
24 Hamashima C. Long-term quality of life of postoperative rectal cancerpatients. J Gastroenterol Hepatol 2002; 17:571-6
25 Norum J, Vonen B, Olsen JA, Reuhaug A. Adjuvant chemotherapy (5-fluo-rouracil and levamisole) in Dukes' B and C colorectal carcinoma. A cost-effectiveness analysis. Ann Oncol 1997; 8:65-70
26 Homs MY, Essink-Bot ML, Borsboom GJ, Steyerberg EW, Siersema PD.Quality of life after palliative treatment for oesophageal carcinoma -- aprospective comparison between stent placement and single dose brachyt-herapy. Eur J Cancer 2004; 40:1862-71
27 Wildi SM, Cox MH, Clark LL, Turner R, Hawes RH, Hoffman Bj, et al.Assessment of health state utilities and quality of life in patients withmalignant esophageal Dysphagia. Am J Gastroenterol 2004; 99:1044-9
28 Krabbe PF, Peerenboom L, Langenhoff BS, Ruers TJ. Responsiveness of thegeneric EQ-5D summary measure compared to the disease-specific EORTCQLQ C-30. Qual Life Res 2004; 13:1247-1253
29 McMillan DC, Wigmore SJ, Fearon KC, O’Gorman, Wright CE, McArdle CS.A prospective randomized study of megestrol acetate and ibuprofen ingastrointestinal cancer patients with weight loss. Br J Cancer 1999; 79:495-500
30 O'Gorman P, McMillan DC, McArdle CS. Impact of weight loss, appetite,and the inflammatory response on quality of life in gastrointestinal cancerpatients. Nutr Cancer 1998; 32:76-80
31 Doorduijn J, Buijt I, Holt B, Steijaert M, Uyl-de-Groot C, Sonneveld P. Self-reported quality of life in elderly patients with aggressive non-Hodgkin'slymphoma treated with CHOP chemotherapy. Eur J Haematol 2005;75:116-23
382
32 Norum J. Quality of life (QoL) measurement in economical analysis in can-cer: A comparison of the EuroQol questionnaire, a simple QoL-scale andthe global QoL measure of the EORTC QLQ-C30. Oncology Reports 1996;3:787-91
33 van Agthoven M, Vellenga E, Fibbe WE, Kingma T, Uyl-de-Groot CA. Costanalysis and quality of life assessment comparing patients undergoingautologous peripheral blood stem cell transplantation or autologous bonemarrow transplantation for refractory or relapsed non-Hodgkin's lympho-ma or Hodgkin's disease. a prospective randomised trial. Eur J Cancer 2001;37:1781-9
34 Norum J, Angelsen V, Wist E, Olsen JA. Treatment costs in Hodgkin's dise-ase: a cost-utility analysis. Eur J Cancer 1996; 32A:1510-7
35 Sandblom G, Carlsson P, Sennfalt K, Varenhost E. A population-based studyof pain and quality of life during the year before death in men with pros-tate cancer. Br J Cancer 2004; 90:1163-8
36 Sandblom G, Carlsson P, Sigsjo P, Varenhost E. Pain and health-related qua-lity of life in a geographically defined population of men with prostatecancer. Br J Cancer 2001; 85:497-503
37 Bertaccini A, Ceccarelli R, Urbinati M, Galassi P, Viluto G, De Stefano, et al.BSP-PC (Bononian Satisfaction Profile--Prostate Cancer): development andvalidation of a "disease-specific" questionnaire for the evaluation ofhealth-related quality of life in patients with prostate cancer. Arch Ital UrolAndrol 2003; 75:187-94
38 Korfage IJ, Essink-Bot ML, Borsboom GJ, Malalinska JB, Kirkels WI,Habbema JD, et al. Five-year follow-up of health-related quality of lifeafter primary treatment of localized prostate cancer. Int J Cancer 2005;116:291-6
39 Lee SH, Kim DJ, Oh JH, Han HS, Yoo KH, Kim HS. Validation of a functionalevaluation system in patients with musculoskeletal tumors. Clin OrthopRelat Res 2003:217-26
40 van Roijen L, Nijs HG, Avezaat CJ, Karlsson G, Linquist C, Pauw KH, et al.Costs and effects of microsurgery versus radiosurgery in treating acousticneuroma. Acta Neurochir (Wien) 1997; 139:942-8
383
41 Uyl-de Groot CA, Buijt I, Gloudemans IJ, Ossenkoppele GJ, Berg HP,Huijgens PC. Health related quality of life in patients with multiple myelo-ma undergoing a double transplantation. Eur J Haematol 2005; 74:136-43
42 Trippoli S, Vaiani M, Lucioni C, Messori A. Quality of life and utility inpatients with non-small cell lung cancer. Quality-of-life Study Group of theMaster 2 Project in Pharmacoeconomics. Pharmacoeconomics 2001;19:855-63
43 Ananth H, Jones L, King M, Tookman A. The impact of cancer on sexualfunction: a controlled study. Palliat Med 2003; 17:202-205
44 Mantovani G, Madeddu C, Maccio A, Gramignano G, Lusso MR, Massa E, etal. Cancer-related anorexia/cachexia syndrome and oxidative stress: aninnovative approach beyond current treatment. Cancer EpidemiolBiomarkers Prev 2004; 13:1651-9
45 Slovacek L, Slovackova B, Jebavy L. Global quality of life in patients whohave undergone the hematopoietic stem cell transplantation: Findingfrom transversal and retrospective study. Exp Oncol 2005; 27:238-42
46 Ravasco P, Monteiro-Grillo I, Camilo ME. Does nutrition influence quality oflife in cancer patients undergoing radiotherapy? Radiother Oncol 2003;67:213-20
47 Weze C, Leathard HL, Grange J, et al. Evaluation of healing by gentletouch in 35 clients with cancer. Eur J Oncol Nurs 2004; 8:40-9
48 Desandes E, Conroy T, Briancon S, Guillermin F, Empereur F, Bey P, et al.Relationship between quality of life and satisfaction with care in patientstreated in a Regional Centre Against Cancer. Revue Francophone dePsycho Oncologie 2005; 4:29-35
49 Schneider SM, Pouget I, Staccini P, Rampal P, Hebuterne X. Quality of lifein long-term home enteral nutrition patients. Clin Nutr 2000; 19:23-8
50 Sullivan PW, Lawrence WF, Ghushchyan V. A national catalog of preferen-ce-based scores for chronic conditions in the United States. Med Care 2005;43:736-49
51 Tengs TO, Wallace A. One thousand health-related quality-of-life estima-tes. Med Care 2000; 38:583-637
384
385
52 Luo N, Johnson JA, Shaw JW, Feeny D, Coons SJ. Self-reported health sta-tus of the general adult U.S. population as assessed by the EQ-5D andhealth utilities index. Med Care 2005; 43:1078-86
53 Johnson JA, Coons SJ. Comparison of the EQ-5D and SF-12 in an adult USsample. Qual Life Res 1998; 7:155-66
54 Johnson JA, Pickard AS. Comparison of the EQ-5D and SF-12 health surveys ina general population survey in Alberta, Canada. Med Care 2000; 38:115-21
386
Tab
le 1
: Des
crip
tio
n o
f st
ud
y ch
arac
teri
stic
s
Canc
er T
ype
Aut
hor,
Year
St
udy
desi
gnD
isea
se/ t
reat
men
t Tr
eatm
ent
regi
men
Pati
ent
% M
/ %M
ean
Age
[Can
cer
Det
ails
][R
efer
ence
No]
stag
esu
bgro
upF
Age
(SD
)Ra
nge
BON
JNT
Lee
et a
l, 20
0339
Cros
s-se
ctio
nal:
Activ
e tr
eatm
ent
Prev
ious
ope
ratio
n on
tum
ors;
60/4
034
14-7
4ev
alua
tion
of
mai
ntai
ning
abi
lity
to w
alk
anot
her H
RQL
mea
sure
BRN
Van
Roje
n et
al,
Qua
si-e
xper
imen
tal
Activ
e tr
eatm
ent
Com
paris
on o
f mic
rosu
rger
y an
d M
icro
surg
ery
51/4
952
(11)
1997
40no
n-ra
ndom
ized
ra
diot
hera
py w
ith G
amm
a Kn
ifein
terv
entio
n tr
ial
Radi
othe
rapy
34/6
655
(14)
BRE
[Sta
ge II
Co
nner
-Spa
dy
Long
itudi
nal
Activ
e tr
eatm
ent
FAC
chem
othe
rapy
: 4
cycl
es
and
III]
et a
l, 20
0519
(repe
ated
eve
ry 2
1 da
ys);
incr
ease
d do
se m
itoxa
ntra
ne, v
inbl
astin
e, &
cy
clop
hosp
ham
ide;
loca
l rad
ioth
erap
yBR
EJa
nsen
et a
l, Cr
oss-
sect
iona
lPo
st tr
eatm
ent
38%
repo
rted
pre
viou
s ad
juva
nt20
0420
chem
othe
rapy
1/99
57 (1
1)BR
EPo
lsky
et a
l, Lo
ngitu
dina
lAc
tive
trea
tmen
tCh
oice
inSe
e or
igin
al p
aper
trea
tmen
t for
20
0221
stra
tifie
d ag
e di
strib
utio
nN
o ch
oice
Se
e or
igin
al p
aper
for s
trat
ified
in
trea
tmen
tag
e di
strib
utio
nVe
rkoo
jen
et a
l, Q
uasi
-exp
erim
enta
lPr
etre
atm
ent
Stud
y: L
arge
cor
e ne
edle
bio
psy
0/10
057
2002
22no
n-ra
ndom
ized
Co
ntro
l: O
pen
brea
st b
iops
y0/
100
58in
terv
entio
n tr
ial
GI-
CoRe
Ham
isha
ma
et a
l,Cr
oss-
sect
iona
lPo
st tr
eatm
ent-
54/4
669
(12)
2002
24po
stop
erat
ive
GI-C
oRe
Nor
um e
t al,
Post
test
-onl
y Ac
tive
trea
tmen
tSt
udy:
Adj
uvan
t che
mot
hera
py44
/56
Med
: 62
36-7
619
9725
Cont
rol G
roup
(5-fl
uoro
urac
il an
d le
vam
isol
e)De
sign
+ s
urge
ryCo
ntro
l: su
rger
y al
one
GI-
ESO
Hom
s et
al,
2004
26Ra
ndom
ized
Lo
ng Te
rm Tr
eatm
ent
12 G
y br
achy
ther
apy
75/2
569
(13)
cont
rol t
rial
(intr
alum
inal
radi
othe
rapy
)U
ltraf
lex
sten
t80
/20
69 (1
1)G
I- ES
OW
ildi e
t al,
2004
27Cr
oss-
sect
iona
l Pr
etre
atm
ent;
16/8
464
46-8
3Ac
tive
Trea
tmen
t
387
Tab
le 1
: Des
crip
tio
n o
f st
ud
y ch
arac
teri
stic
s
Canc
er T
ype
Aut
hor,
Year
St
udy
desi
gnD
isea
se/ t
reat
men
t Tr
eatm
ent
regi
men
Pati
ent
% M
/ %M
ean
Age
[Can
cer
Det
ails
][R
efer
ence
No]
stag
esu
bgro
upF
Age
(SD
)Ra
nge
GI-C
oRe
[with
Kr
abbe
et a
l, 20
0428
Pros
pect
ive
coho
rtAc
tive
trea
tmen
t;liv
er m
etas
tasi
s]Po
st tr
eatm
ent
All p
atie
nts
had
lapa
roto
my.
Gro
up I:
sur
gica
l liv
er re
sect
ion
with
or
with
out a
dditi
onal
abl
ativ
e th
erap
yG
roup
II: l
ocal
abl
ativ
e th
erap
y al
one
Gro
up II
I: no
trea
tmen
t (n
o su
rger
y co
uld
be p
erfo
rmed
)G
IM
cMill
an e
t al,
Rand
omiz
ed
Activ
e tr
eatm
ent
Stud
y: M
eges
trol
ace
tate
& ib
upro
fen
55/4
572
50-9
019
9929
cont
rol t
rial
Cont
rol:
Meg
estr
ol a
ceta
te &
pla
cebo
63/3
769
52-8
8G
IO
'Gor
man
et a
l, Cr
oss-
sect
iona
lAc
tive
trea
tmen
tO
vern
ight
fast
ing
befo
re te
stin
gW
eigh
t 55
/45
7049
-84
1998
30St
able
HdN
k [O
ral c
avity
Sch
neid
er e
t al,
Cros
s-se
ctio
nal
Activ
e tr
eatm
ent
Hom
e en
tera
l nut
ritio
n63
/37
56 (2
5)an
d ph
aryn
x;
2000
49
Head
and
nec
k]N
HL
Door
dujin
et a
l, Lo
ngitu
dina
lAc
tive
trea
tmen
tCy
clop
hosp
ham
ide,
dox
orub
icin
,56
/44
7265
-84
[Sta
ges
II, II
I, IV
]20
0531
vinc
ristin
e, p
redn
ison
e ch
emot
hera
pyHO
DN
orum
et a
l, 19
9634
Retr
ospe
ctiv
e Po
st tr
eatm
ent
Radi
othe
rapy
(10)
; ch
emot
hera
py (1
6);
43/5
738
15-7
0co
hort
: cos
t util
ityRa
diot
hera
py a
nd c
hem
othe
rapy
(16)
anal
ysis
HOD,
NHL
van
Agth
oven
et a
l,Ra
ndom
ized
con
trol
Ac
tive
trea
tmen
tIn
duct
ion
chem
othe
rapy
(DHA
P &
PBSC
T68
/32
Med
: 49
18-6
420
01 3
3tr
ial
VIM
cou
rse)
; Ran
dom
ized
to P
BSCT
or A
BMT;
Anot
her D
HAP
cour
se a
nd
high
-dos
e co
nditi
onin
g ch
emot
hera
pyAM
BT48
/52
Med
: 46
18-6
3M
TMY
Uyl
-de
Gro
ot e
t al,
Long
itudi
nal
Activ
e tr
eatm
ent
2 co
urse
s VAD
or v
incr
istin
e, a
dria
myc
in,
64/3
653
(8)
2005
41&
met
hyl p
redn
ison
e ch
emot
hera
py;
HDM
follo
wed
by
tran
spla
ntat
ion
of
who
le b
lood
; col
lect
ion
of r-
met
Hu
G-C
SF m
obili
sed
perip
hera
l blo
od
prog
enito
r cel
ls b
y le
ukop
here
sis;
high
-do
se c
hem
othe
rapy
; rei
nfus
ion
of
prev
ious
ly c
olle
cted
per
iphe
ral s
tem
cel
ls
388
Tab
le 1
: Des
crip
tio
n o
f st
ud
y ch
arac
teri
stic
s
Canc
er T
ype
Aut
hor,
Year
St
udy
desi
gnD
isea
se/ t
reat
men
t Tr
eatm
ent
regi
men
Pati
ent
% M
/ M
ean
Age
[Can
cer
Det
ails
][R
efer
ence
No]
stag
esu
bgro
up%
FA
ge (S
D)
Rang
ePR
O [N
on-
Bert
acci
ni e
t al,
Cros
s-se
ctio
nal
Stag
e no
t rep
orte
d10
0/0
68 (7
)m
etas
tatic
]20
03 3
7
PRO
Korfa
ge e
t al,
Pros
pect
ive
coho
rtAc
tive
trea
tmen
tPr
osta
tect
omy
100/
062
(5)
49-7
420
05 3
8
Radi
othe
rapy
100/
068
(6)
49-8
2PR
OSa
ndbl
om e
t al,
Cros
s-se
ctio
nal
Activ
e tr
eatm
ent;
77(8
)20
01 3
6Po
st tr
eatm
ent;
Long
term
trea
tmen
tPR
OSa
ndbl
om e
t al,
Cros
s-se
ctio
nal
2004
35Ac
tive
trea
tmen
t;76
(10)
Post
trea
tmen
t;Lo
ng te
rm tr
eatm
ent
LUN
GTr
ippo
li et
al,
Cros
s-se
ctio
nal
Activ
e tr
eatm
ent;
See
orig
inal
pap
er fo
r pre
viou
s su
rger
y,93
/762
(9)
2001
42Po
st tr
eatm
ent
radi
othe
rapy
, and
che
mot
hera
py re
gim
ens
GEN
Anan
th e
t al,
Activ
e tr
eatm
ent;
2003
43Ca
se-c
ontr
olLo
ng te
rm tr
eatm
ent
Palli
ativ
e Ca
re38
/63
57 (1
4)O
ncol
ogy
48/5
259
(13)
Gen
eral
Pra
ctic
e37
/63
57 (1
5)G
EN [S
tom
ach;
Man
tova
ni e
t al,
Qua
si-e
xper
imen
tal
Activ
e tr
eatm
ent
Poly
phen
ols,
p.o.
pha
rmac
onut
ritio
nal
Colo
n an
d re
ctum
;200
444
non
rand
omiz
edsu
pple
men
t, m
etro
xipr
oges
tero
ne
40/ 6
058
(9)
Panc
reas
; Lun
g an
d in
terv
entio
n tr
ial
acet
ate
bron
chus
; Bre
ast;
Ova
ry; U
terin
e;
Head
and
nec
k]HO
D (n
=9)
; NHL
Sl
ovac
ek e
t al,
Cros
s-se
ctio
nal
Prev
ious
aut
olog
us/ a
lloge
nous
71/2
956
(n=
15);
MTM
Y 20
0545
hem
atop
olet
ic s
tem
cel
l tra
nspl
anta
tion
(n=
32)
; LEU
(n
=15
) Lo
w-r
isk
[incl
udes
Rav
asco
et a
l,Pr
ospe
ctiv
e co
hort
Activ
e tr
eatm
ent
Radi
othe
rapy
66/3
463
(11)
33-8
6LU
NG,
BRE
, PRO
, 20
02 4
6
BRAI
N, fe
mal
e ge
nita
l sys
tem
]; ES
O; S
TO; C
oRe
389
Tab
le 1
: Des
crip
tio
n o
f st
ud
y ch
arac
teri
stic
s
Canc
er T
ype
Aut
hor,
Year
St
udy
desi
gnD
isea
se/ t
reat
men
t Tr
eatm
ent
regi
men
Pati
ent
% M
/ M
ean
Age
[Can
cer
Det
ails
][R
efer
ence
No]
stag
esu
bgro
up%
FA
ge (S
D)
Rang
eBR
E;Su
lliva
n et
al,
Cros
s-se
ctio
nal
Canc
er o
f Bre
ast
6420
05 1
1
PRO
Canc
er o
f Pro
stat
e70
SKIN
Canc
er o
f the
Ski
n66
GEN
[Doe
sO
ther
Can
cers
44no
t inc
lude
br
east
, pro
stat
e,
skin
can
cers
]G
I- Co
Re; H
OD
Nor
um e
t al,
Cros
s-se
ctio
nal
Post
trea
tmen
t19
9632
GEN
[GI (
n=3)
; W
eze
et a
l,Pr
ospe
ctiv
e co
hort
Com
plem
enta
ry c
are
Gen
tle to
uch-
4 s
essi
ons;
See
orig
inal
LUN
G (n
=1)
; 20
04 4
7pa
per f
or o
ther
regi
men
s31
/66
Med
:57
24-8
0BR
E (n
=17
); PR
O (n
=2)
; BR
AIN
(n=
1);
LEU
(n=
1);
Fem
ale
geni
tal
syst
em (n
=1)
; un
disc
lose
d (2
0)]
GEN
Desa
ndes
et a
l,20
0548
36/6
455
(13)
See
Appe
ndix
5 fo
r Abb
revi
atio
ns
390
Tab
le 2
: Su
mm
ary
of
stu
die
s ex
amin
ing
val
idit
y an
d r
elia
bili
ty o
f EQ
-5D
in c
ance
r
Canc
er
Auth
or, Y
ear
Relia
bilit
yVa
lidity
Resp
onsi
vene
ss
Type
[Ref
eren
ce]
BON
JNT
Lee
et a
l, 2
003
39In
tern
al c
onsi
sten
cy:
• Co
nver
gent
val
idity
: MTS
S an
d EQ
-5D
Cron
bach
a fo
r ful
l EQ
-5D
= 0
.71.
rela
ted
dim
ensi
ons
com
pare
d us
ing
Pear
son
corr
elat
ion.
Mod
erat
e to
str
ong
corr
elat
ions
(R
ange
: 0.3
9-0.
6).
• Di
scrim
inan
t val
idity
: MTS
S an
d EQ
-5D
rela
ted
dim
ensi
ons
com
pare
d us
ing
Pear
son
corr
elat
ion.
La
ck o
f dis
crim
inat
ion
in a
ll bu
t Pai
n di
men
sion
of M
TSS.
BR
ECo
nner
-Spa
dy e
t al,
• Co
nstr
uct v
alid
ity: F
LIC
and
EQ-5
D co
mpa
red.
Ef
fect
Siz
e fo
r EQ
-5D
inde
x. B
asel
ine
2001
18Si
mila
r pat
tern
s of
cha
nge
over
tim
e.to
3 w
k po
st H
DC is
larg
e (1
.16)
; 3
wk
to 8
wk
post
HDC
is m
oder
ate
(0.6
6).
BRE
Ger
ard
et a
l, 19
9923
Test
-ret
est:
40%
agr
eem
ent (
with
in.
• Co
nver
gent
val
idity
: EQ
-5D
and
TTO
com
pare
d1
of th
e m
ean
diffe
renc
e) a
fter 4
wks
fo
r sho
rt te
rm a
nd lo
ng te
rm o
f tru
e ne
gativ
efo
r val
uatio
ns o
f fal
se p
ositi
ve a
nd tr
ue
(tn) a
nd fa
lse
posi
tive
(fp) %
agr
eem
ent.
nega
tive
and
26%
agr
eem
ent f
or tr
ue
Shor
t ter
m: 3
2% (t
n), 1
8% (f
p);
posi
tive
and
fals
e ne
gativ
e br
east
Lo
ng te
rm: 2
0% (t
n), 2
2% (f
p).
scre
enin
g sc
ores
.Pa
ired
rank
s: Sh
ort-
term
agr
eem
ent
Inte
rnal
con
sist
ency
: Con
ditio
n ra
nkin
g be
twee
n EQ
-5D
and
TTO.
tn>
fp:
and
EQ-5
D sc
ore
% a
gree
men
t com
pare
d.56
.7%
; tn≥
fp: 3
1.2%
;Tr
ue n
egat
ive
: 69.
2%, F
alse
pos
itive
: 30.
7%.
tn=
fp: 5
.6%
. Dis
agre
emen
t in
7.6%
.Be
twee
n si
te a
gree
men
t: TT
O =
EQ
-5D
test
ed b
y F-
ratio
s fo
r bet
wee
n-si
te
varia
tion.
Fai
led
to re
ject
the
null.
GI-C
oRe
Krab
be e
t al,
2004
28•
Conv
erge
nt v
alid
ity: E
Q- 5
D in
dex
and
EORT
C Ef
fect
siz
e: m
oder
ate
to la
rge
for S
C,Q
LQ C
-30
com
pare
d. E
ffect
siz
es c
ompa
rabl
e UA
, MO
and
PD
dim
ensi
ons
and
smal
lfo
r cor
resp
ondi
ng d
omai
ns.
for A
D. E
ffect
siz
e de
crea
ses
as ti
me
past
sur
gery
incr
ease
s.HO
DN
orum
et a
l, 19
9634
• Co
nver
gent
Val
idity
: Si
mpl
e VA
S sc
ores
and
EQ
-5D
scor
es c
ompa
red.
Hig
h co
rrel
atio
n re
port
ed, b
ut P
ears
on c
orre
latio
n no
t giv
en.
391
Tab
le 2
: Su
mm
ary
of
stu
die
s ex
amin
ing
val
idit
y an
d r
elia
bili
ty o
f EQ
-5D
in c
ance
r
Canc
er
Auth
or, Y
ear
Relia
bilit
yVa
lidity
Resp
onsi
vene
ss
Type
[Ref
eren
ce]
PRO
Bert
acci
ni e
t al,
2003
37•
Cons
truc
t val
idity
: Bon
ian
Satis
fact
ion
Prof
ile-
Pros
tate
Can
cer c
ompa
red
to E
Q-5
D us
ing
Pear
son
corr
elat
ion.
Item
s w
ith r≥
0.5
(p<
0.00
5)
sele
cted
for B
SP-P
C.
• Kn
own-
grou
ps: B
onfe
rron
i pos
t hoc
test
co
mpa
ring
pros
tate
can
cer w
ith h
ealth
y su
bjec
ts
and
othe
r dis
ease
s. Si
gnifi
cant
diff
eren
ce fr
om
heal
thy
(M=
0.84
vs.
M=
0.94
, p<
0.00
1) b
ut n
ot
sign
ifica
nt fr
om o
ther
dis
ease
s (M
=0.
84 v
s M
=0.
85, p
=1)
.PR
OSa
ndbl
om e
t al,
• Pr
edic
tive
valid
ity: S
core
of E
Q-5
D VA
S pr
edic
ted
by20
0435
regr
essi
on. I
tem
s w
ith p
<.0
1 si
gnifi
canc
e fo
r pr
edic
tion
incl
uded
: wor
st p
ain
last
wee
k, D
ied
befo
re
31 D
ecem
ber 2
000,
Age
(yea
rs),
Heal
th-c
are
avai
labi
lity
and
palli
ativ
e tr
eatm
ent.
LUN
GTr
ippo
li et
al,
• Co
nstr
uct v
alid
ity: E
Q-5
D re
sults
com
pare
d to
oth
er
2001
42st
udie
s. Fo
und
com
para
ble
with
Kur
tz, M
agio
ne,
and
Wan
g st
udie
s. •
Conv
erge
nt v
alid
ity: P
ears
on c
orre
latio
n us
ed to
co
mpa
re E
Q-5
D in
dex,
EQ
5D V
AS, a
nd S
F-36
dom
ains
. St
rong
inde
x co
rrel
atio
n w
ith V
AS(r
= 0
.54)
.M
oder
ate
to s
tron
g re
latio
nshi
p fo
r SF-
36 d
omai
ns
and
inde
x sc
ore
(rang
e: .3
5-.7
32) w
ith h
ighe
st c
orre
latio
n fo
r SF-
36 p
hysi
cal f
unct
ioni
ng; m
oder
ate
to s
tron
g re
latio
nshi
p fo
r EQ
-VAS
and
SF-
36 d
omai
ns (r
ange
: .40
1-.6
85) w
ith h
ighe
st
corr
elat
ion
for S
F-36
Vita
lity.
GEN
Anan
th e
t al,
Test
-ret
est r
elia
bilit
y: k
>0.
720
0343
for p
atie
nts
test
ed (n
= 1
6).
392
Tab
le 2
: Su
mm
ary
of
stu
die
s ex
amin
ing
val
idit
y an
d r
elia
bili
ty o
f EQ
-5D
in c
ance
r
Canc
er
Auth
or, Y
ear
Relia
bilit
yVa
lidity
Resp
onsi
vene
ss
Type
[Ref
eren
ce]
HOD,
Slov
acek
et a
l,•
Disc
rimin
ant v
alid
ity: H
RQL
diffe
renc
e in
pat
ient
s w
ith d
iffer
ent
NHL
,20
0545
num
ber o
f dis
ease
s an
d hi
gher
age
at h
emat
opoi
etic
ste
m c
ell
MTM
Y,tr
ansp
lant
atio
n.LE
UG
I-ESO
Rava
sco
et a
l, 20
0246
• Co
nten
t val
idity
: wor
se m
obili
ty a
nd u
sual
act
iviti
es s
core
s as
soci
ated
with
mal
nutr
ition
or r
educ
ed e
nerg
y; S
tron
g co
rrel
atio
n be
twee
n nu
triti
onal
inta
ke p
ost-
radi
othe
rapy
and
impr
ovem
ent
with
QO
L.G
I-N
orum
et a
l,•
Conv
erge
nt v
alid
ity: E
Q-5
D in
dex
com
pare
d w
ith E
ORT
CCo
Re;
1996
32Q
LQ-C
30 a
nd s
impl
e VA
S sc
ale.
HOD
High
cor
rela
tion
(p <
0.0
001
for r
2 ).
GEN
Desa
ndes
et a
l,•
Conv
erge
nt v
alid
ity: E
Q-5
D in
dex
and
Patie
nt Ju
dgm
ents
of H
ospi
tal
2005
48Q
ualit
y co
mpa
red
usin
g Pe
arso
n co
rrel
atio
n.Lo
w c
orre
latio
n (r2
= 0
.10
– 0.
16).
393
Tab
le 3
: Su
mm
ary
of
EQ-5
D a
sses
smen
ts r
epo
rted
in c
ance
r st
ud
ies
Auth
or, Y
ear
Canc
er ty
pe:
nIn
dex
VAS
%%
%%
%Sc
orin
gAu
thor
Revi
ewer
(Ref
eren
ce N
o)Su
bgro
up
mea
nm
ean
MO
SCUA
PDAD
Algo
rithm
Com
men
tsCo
mm
ents
[Ref
eren
ce]
(SD)
(SD)
Leee
t al,
2003
39BO
NJN
T 49
0.68
73
(19)
Dola
n 19
97,
Conc
entr
atio
n on
the
(0.2
2)U
nite
d M
uscu
losk
elet
al Tu
mor
King
dom
Soci
ety
Func
tiona
l (U
K)Ev
alua
tion
Syst
em.
Van
Roje
n et
al,
BRAI
N: M
icro
surg
ery;
530.
77
Dola
n 19
97,
1997
401
of 2
(0
.18)
UK
EQ-5
D no
t a m
ain
focu
s.BR
AIN
: Rad
iosu
rger
y;92
0.89
2 of
2
(0.1
5)Co
nner
-Spa
dy e
t al,
Dola
n 19
97,
Som
e da
ta p
rese
nted
2001
18U
Kbe
low
was
giv
en in
this
pre
limin
ary
pape
r.Co
nner
-Spa
dy e
t al,
BRE-
Base
line:
480.
78 (0
.18)
1-98
1-98
1-60
1-56
1-31
Dola
n 19
97,
The
EQ-5
D in
dex
resu
lts20
0519
Pret
reat
men
t;2-
22-
22-
382-
442-
64U
Kar
e ta
ken
from
the
sam
e1
of 7
3-0
3-0
3-2
3-0
3-4
coho
rt a
s th
e ch
arac
teris
tics
pres
ente
d ab
ove.
BRE:
1st
day
of 3
rd
480.
75 (0
.18)
1-96
1-90
1-44
1-35
1-46
FAC
cycl
e; 2
of 7
2-4
2-10
2-52
2-65
2-52
3-0
3-0
3-4
3-0
3-2
BRE:
3 w
k po
st48
0.61
(0.2
9)1-
641-
851-
151-
401-
51HD
C; 3
of 7
2-36
2-15
2-52
2-58
2-42
3-0
3-0
3-33
3-2
3-7
BRE:
6 m
o po
st45
0.79
(0.1
9)1-
931-
100
1-40
1-47
1-51
HDC;
4 o
f 72-
72-
02-
532-
532-
423-
03-
03-
43-
03-
7BR
E: 1
2 m
o po
st40
0.84
(0.1
9)1-
881-
100
1-73
1-48
1-60
HDC;
5 o
f 72-
122-
02-
252-
532-
353-
03-
03-
33-
03-
5BR
E: 1
8 m
o po
st
360.
84 (0
.13)
1-92
1-97
1-66
1-47
1-61
HDC;
6 o
f 72-
82-
32-
342-
532-
393-
03-
03-
03-
03-
0BR
E: 2
4 m
o po
st
370.
89 (0
.13)
1-92
1-97
1-76
1-62
1-68
HDC;
7 7
of 7
2-
82-
32-
242-
382-
303-
03-
03-
03-
03-
3
394
Tab
le 3
: Su
mm
ary
of
EQ-5
D a
sses
smen
ts r
epo
rted
in c
ance
r st
ud
ies
Auth
or, Y
ear
Canc
er ty
pe:
nIn
dex
VAS
%%
%%
%Sc
orin
gAu
thor
Revi
ewer
(Ref
eren
ce N
o)Su
bgro
up
mea
nm
ean
MO
SCUA
PDAD
Algo
rithm
Com
men
tsCo
mm
ents
[Ref
eren
ce]
(SD)
(SD)
Ger
ard
et a
l,19
99 2
344
0EQ
-5D
scor
es w
ere
spec
ulat
ive
from
wom
en
elig
ible
for b
reas
t ca
ncer
scr
eeni
ng.
Jans
en e
t al,
BRE:
Che
mo
540.
84
7720
04 2
0+
cho
ice
in tr
eatm
ent;
Dola
n 19
97,
Non
resp
onde
rs C
hoic
e in
trea
tmen
t was
1 of
4 *
*U
Kw
ere
slig
htly
repo
rted
by
the
patie
nt. T
heBR
E: N
o ch
emo
280.
7469
olde
r and
3rd
purp
ose
of th
is s
tudy
+ c
hoic
e in
trea
tmen
t;tr
eate
d w
ith"w
heth
er th
e pr
opor
tion
of
2 of
4**
chem
othe
rapy
trea
tmen
t cho
ice
is re
late
d to
BRE:
Che
mo
105
0.82
75le
ss fr
eque
ntly
satis
fact
ion
with
the
assi
g-+
no
choi
ce in
ne
d tx
, exp
erie
nced
che
mot
-tr
eatm
ent;
3 of
4**
hera
py b
urde
n an
d cu
rren
t BR
E: N
o ch
emo
174
0.83
77Q
OL"
is re
late
d to
our
stu
dy
+ n
o ch
oice
inpu
rpos
e.tr
eatm
ent;
4 of
4 *
*
Pols
ky e
t al,
BRE:
Cho
ice
in56
679
(16
Dola
n 19
97,
2002
21
trea
tmen
t; 1
of 2
)U
KBR
E: N
o ch
oice
in11
775
(17)
trea
tmen
t; 2
of 2
Verk
ooje
n et
al,
BRE:
Bef
ore
need
le30
0.73
80Do
lan
1997
,20
0222
biop
sy; 1
of 4
*U
KBR
E: A
fter n
eedl
e 30
0.71
80bi
opsy
; 2 o
f 4*
BRE:
Bef
ore
open
27
0.69
80br
east
bio
psy;
3 o
f 4*
BRE:
Afte
r ope
n 27
0.61
76br
east
bio
psy;
4 o
f 4*
Ham
isha
ma
et a
l,G
I-CoR
e: S
tom
a;72
0.87
72
(16)
2/3-
202/
3-7
2/3-
292/
3-21
2/3-
14Ik
eda
1999
,20
0224
Iked
a; 1
of 4
(0.1
6)Ja
pan
395
Tab
le 3
: Su
mm
ary
of
EQ-5
D a
sses
smen
ts r
epo
rted
in c
ance
r st
ud
ies
Auth
or, Y
ear
Canc
er ty
pe:
nIn
dex
VAS
%%
%%
%Sc
orin
gAu
thor
Revi
ewer
(Ref
eren
ce N
o)Su
bgro
up
mea
nm
ean
MO
SCUA
PDAD
Algo
rithm
Com
men
tsCo
mm
ents
[Ref
eren
ce]
(SD)
(SD)
GI-C
oRe:
No
380.
84
70 (1
5)2/
3-26
2/3-
132/
3-32
2/3-
342/
3-24
Stom
a; Ik
eda;
2 o
f 4
(0.1
7)G
I-CoR
e: S
tom
a;
720.
87
Dola
n 19
97,
Dola
n; 3
of 4
(0.2
2)U
KG
I-CoR
e: N
o St
oma;
380.
84
Dola
n al
gorit
hm;
(0.1
9)4
of 4
Nor
um e
t al,
GI-C
oRe
62M
ed: 0
.78)
Dola
n 19
97,
1997
25(0
.33
to 1
UK
Hom
s et
al,
GI-E
SO: A
ll pa
tient
s0.
42
59Do
lan
1997
,N
o si
gnifi
cant
diff
eren
ce20
04 2
6po
st tr
eatm
ent;
1 of
3*
(0.3
6)U
Kbe
twee
n EQ
-5D
scor
es o
f th
e 2
trea
tmen
ts; B
asel
ine
core
s fo
r the
se p
atie
nts
are
belo
w th
e po
pula
tion
norm
s.G
I-ESO
:; 10
147
(13)
Brac
hyth
erap
y 2
of 3
GI-E
SO: S
tent
10
843
(13)
Plac
emen
t; 3
of 3
Wild
i et a
l,G
I-ESO
: SEE
R 50
0.93
20
0427
Stag
e 0;
1 o
f 4(0
.12)
GI-E
SO: S
EER
0.6
Stag
e 1;
2 o
f 4(0
.29)
GI-E
SO: S
EER
0.71
St
age
2; 3
of 4
(0.2
1)G
I-ESO
: SEE
R 0.
69
Stag
e 3;
4 o
f 4(0
.31)
Krab
be e
t al,
GI-L
IV :
Base
line
750.
84
75 (1
4)1-
891-
100
1-76
1-83
1-61
Dola
n 19
97,
Post
3 m
onth
s al
so re
port
ed.
2004
28
pre-
surg
ery;
1 o
f 3(0
.12)
UK
EQ-5
D is
com
para
ble
to
2-10
2-0
2-21
2-17
2-36
dise
ase-
spec
ific
HRQ
L.3-
03-
03-
33-
03-
3G
I-LIV
: Pos
t 1/2
74
0.68
58
(19)
1-55
1-78
1-19
1-38
1-69
mon
th; 2
of 3
(0.2
3)
396
Tab
le 3
: Su
mm
ary
of
EQ-5
D a
sses
smen
ts r
epo
rted
in c
ance
r st
ud
ies
Auth
or, Y
ear
Canc
er ty
pe:
nIn
dex
VAS
%%
%%
%Sc
orin
gAu
thor
Revi
ewer
(Ref
eren
ce N
o)Su
bgro
up
mea
nm
ean
MO
SCUA
PDAD
Algo
rithm
Com
men
tsCo
mm
ents
[Ref
eren
ce]
(SD)
(SD)
2-39
2-18
2-42
2-61
2-13
3-5
3-4
3-39
3-1
3-0
GI-L
IV: P
ost 6
69
0.84
75
(14)
1-81
1-97
1-64
1-71
1-78
mon
ths;
3 of
3(0
.11)
2-18
2-3
2-35
2-29
2-22
3-0
3-0
3-1
3-0
3-0
McM
illan
et a
l,G
I :M
A+ p
lace
bo;
38M
ed:
Dola
n 19
97,
Sign
ifica
nt im
prov
emen
t19
99 2
91
of 2
0.63
UK
in E
Q-5
D sc
ore
of ib
upro
fen
(-0.1
to
grou
p (p
<.0
5),
1.00
)va
lues
not
sho
wn.
GI:
MA+
ibup
rofe
n;35
Med
:1
of 2
0.
69
(-0.2
6 to
1.
01)
O'G
orm
an e
t al,
GI:
Wei
ght S
tabl
e;22
M
ed:
Dola
n 19
97,
No
sign
ifica
nt d
iffer
ence
1998
301
of 2
0.85
U
Kin
EQ
-5D
betw
een
(0.0
3 to
gr
oups
.1.
00)
GI:
Wei
ght L
osin
g;
97M
ed:
2 of
20.
52
(-0.2
6 to
1.00
)
Door
dujin
et a
l,N
HL: B
asel
ine,
630.
74Do
lan
1997
,Li
ttle
focu
s on
EQ
-5D;
2005
31aa
IPI 0
-1; 1
of 4
U
KAf
ter 2
nd a
nd 4
th C
HOP
NHL
: Bas
elin
e,53
0.44
cycl
e re
port
ed a
s w
ell.
aaIP
I 2-3
; 2 o
f 4
NHL
: pos
t 6th
CHO
P54
0.69
cycl
e, a
aPI 0
-1; 3
of 4
NHL
: pos
t 6th
CHO
P 44
0.53
cycl
e, a
aPI 2
-3; 4
of 4
397
Tab
le 3
: Su
mm
ary
of
EQ-5
D a
sses
smen
ts r
epo
rted
in c
ance
r st
ud
ies
Auth
or, Y
ear
Canc
er ty
pe:
nIn
dex
VAS
%%
%%
%Sc
orin
gAu
thor
Revi
ewer
(Ref
eren
ce N
o)Su
bgro
up
mea
nm
ean
MO
SCUA
PDAD
Algo
rithm
Com
men
tsCo
mm
ents
[Ref
eren
ce]
(SD)
(SD)
Nor
um e
t al,
HOD
420.
7880
Dola
n 19
97,
1996
34**
Uni
ted
King
dom
van
Agth
oven
et a
l,N
HL, H
OD:
PBS
CT, D
ay
620.
7568
Dola
n 19
97,
Two
time
poin
ts n
ot
2001
33be
fore
tran
spla
ntat
ion;
Uni
ted
pres
ente
d in
this
tabl
e.1
of 4
*Ki
ngdo
mN
HL, H
OD:
ABM
T, Da
y29
0.78
66be
fore
tran
spla
ntat
ion;
2
of 4
*N
HL, H
OD:
PBS
CT, 1
462
0.53
55da
ys p
ost t
rans
plan
ta-
tion;
3 o
f 4*
NHL
, HO
D: A
BMT,
14
290.
4250
days
pos
t tra
nspl
anta
-tio
n; 4
of 4
*U
yl-d
e G
root
et a
l,M
TMY:
Bas
elin
e;25
0.52
2005
41
1 of
4(0
.33)
Dola
n 19
97,
Not
bas
ed o
n a
Ther
e w
ere
a to
tal o
f 7U
nite
d pr
etre
atm
ent
time
poin
ts re
port
ed;
King
dom
base
line,
so
this
Base
line,
T3,
T5,
T7
inM
TMY:
dis
char
ge24
0.38
stud
y pr
obab
ly
tabl
e.HD
M; 2
of 4
unde
rest
imat
e M
TMY:
dis
char
ge14
0.66
impr
ovem
ents
in
PSCT
]; 3
of 4
qual
ity o
f life
.M
TMY:
12
mo
120.
69fo
llow
up; 4
of 4
Bert
acci
ni e
t al,
PRO
: Hea
lthy;
570.
94
Dola
n 19
97,
Sign
ifica
nt d
iffer
ence
EQ-5
D us
ed p
rimar
ily20
0337
1 of
3
(0.0
2)U
Kin
pat
ient
s w
ith
to e
nsur
e th
e va
lidity
PRO
: Pro
stat
e Ca
ncer
;10
30.
84pr
osta
te c
ance
r vs.
of B
onia
n Sa
tisfa
ctio
n2
of 3
he
alth
y in
divi
dual
s, Pr
ofile
- Pro
stat
ePR
O: O
ther
Dis
ease
s;10
10.
85
but n
ot s
igni
fican
t Ca
ncer
.3
of 3
(0.0
2)co
mpa
red
to in
divi
dual
sw
ith o
ther
dis
ease
s.
398
Tab
le 3
: Su
mm
ary
of
EQ-5
D a
sses
smen
ts r
epo
rted
in c
ance
r st
ud
ies
Auth
or, Y
ear
Canc
er ty
pe:
nIn
dex
VAS
%%
%%
%Sc
orin
gAu
thor
Revi
ewer
(Ref
eren
ce N
o)Su
bgro
up
mea
nm
ean
MO
SCUA
PDAD
Algo
rithm
Com
men
tsCo
mm
ents
[Ref
eren
ce]
(SD)
(SD)
Korfa
ge e
t al,
PRO
: Pro
stat
ecto
my
127
0.89
79
(17)
2005
38
-pre
trea
tmen
t; 1
of 6
*(0
.15)
Dola
n 19
97,
Data
from
Rot
terd
amU
Kst
udy;
Tim
e po
int a
t 12
PRO
: Pro
stat
ecto
my
0.91
84m
onth
s no
t in
this
tabl
e.po
st-6
mo;
2 o
f 6*
(0.1
6)(1
2)PR
O: P
rost
atec
tom
y,0.
8881
post
-52
mo;
3 o
f 6*
(0.1
6)(1
3)PR
O: R
adio
ther
apy,
187
0.81
72pr
etre
atm
ent;
4 of
6*
(0.2
0)(1
7)PR
O: R
adio
ther
apy-
0.83
76po
st 6
mo;
5 o
f 6*
(0.2
1)(1
7)PR
O: R
adio
ther
apy-
0.76
74po
st 5
2 m
onth
s; 6
of 6
*(0
.23)
(16)
Sand
blom
et a
l,PR
O12
431-
621-
871-
751-
381-
66Do
lan
1997
,EQ
-5D
resu
lts in
2001
36U
Kgr
aphi
cal f
orm
,2-
362-
112-
182-
572-
32by
age
.3-
153-
23-
73-
53-
2
Sand
blom
et a
l,PR
O:
660.
538
54 (2
2)Do
lan
1997
,Pa
tient
s dy
ing
of o
ther
2004
35
Died
of P
RO b
y 31
(0.3
2)U
Kca
uses
not
pre
sent
edDe
c 20
01; 1
of 2
in
this
tabl
e.PR
O: S
till A
live
3110
760.
7770
(20)
Dec
2001
; 2 o
f 2
(0.2
5)Tr
ippo
li et
al,
LUN
G92
/94
0.58
58 (2
)Do
lan
1997
,Goo
d ag
reem
ent
Scor
es w
ere
divi
ded
by20
0142
(0.3
3)U
Kw
ith W
ang,
Kur
tz,
gend
er, s
urge
ry, c
he-
& M
angi
one
stud
ies.
mot
hera
py, r
adio
ther
apy
met
asta
sis,
age,
and
time
sinc
e di
agno
sis.
Anan
th e
t al,
GEN
: Pal
liativ
e Ca
re;
640.
52Do
lan
1997
,EQ
-5D
inco
rpor
ated
into
2003
431
of 3
*(0
.18)
UK
anot
her q
uest
ionn
aire
.G
EN: O
ncol
ogy;
560.
67
2 of
3*
(0.1
9)
399
Tab
le 3
: Su
mm
ary
of
EQ-5
D a
sses
smen
ts r
epo
rted
in c
ance
r st
ud
ies
Auth
or, Y
ear
Canc
er ty
pe:
nIn
dex
VAS
%%
%%
%Sc
orin
gAu
thor
Revi
ewer
(Ref
eren
ce N
o)Su
bgro
up
mea
nm
ean
MO
SCUA
PDAD
Algo
rithm
Com
men
tsCo
mm
ents
[Ref
eren
ce]
(SD)
(SD)
GEN
: Gen
eral
67
0.75
Prac
tice;
3 o
f 3*
(0.1
5)M
anto
vani
et a
l,G
EN: B
asel
ine;
250.
3344
(2.2
)20
0444
1 of
4(0
.4)
Not
repo
rted
EQ-5
D in
dex
impr
oved
at 4
mon
ths;
VAS
impr
oved
at
1 an
d 2
mon
ths.
GEN
: Af
ter 1
mon
th;
250.
4556
(2.2
)2
of 4
(0
.3)
GEN
: Afte
r 2 m
onth
s;18
0.59
62 (2
)3
of 4
(0
.3)
GEN
: Afte
r 4 m
onth
s;12
0.54
62 (2
)4
of 4
(0
.3)
Slov
acek
et a
l,HO
D, N
HL, M
TMY,
30
0.84
76 (1
2)Da
nkov
ain
fluen
ce o
f pol
ymor
bidi
ty,
Resu
lts a
lso
sum
ma-
2005
45LE
U: 0
Ass
oc. D
isea
ses;
(0.1
6)20
01,C
zech
age
, and
relig
ion
on E
Q 5
Driz
ed b
y be
lief i
n G
od1
of 3
*Re
publ
icin
dex
and
Visu
al A
nalo
g HO
D, N
HL, M
TMY
130.
7572
(18)
Scal
e ar
e st
atis
tical
ly
LEU
: 1 A
ssoc
. Dis
ease
s(0
.19)
sign
ifica
nt (P
<.0
1).
2 of
3*
HOD,
NHL
, MTM
Y 14
0.71
66 (1
3)LE
U: 2
Ass
oc. D
isea
ses;
(0.1
5)3
of 3
*Ra
vasc
o et
al,
GI –
ESO
; 1 o
f 56
1-83
1-66
1-0
1-67
1-50
Reco
mm
enda
tion
that
Onl
y en
d re
sults
repo
rted
2002
462-
172-
172-
502-
332-
33Eu
roqo
l sho
uld
be u
sed
to c
onse
rve
spac
e.3-
03-
173-
503-
03-
17as
a ro
utin
e in
suc
h Pa
tient
s gr
oupe
d as
GI –
STO
; 2 o
f 55
1-10
01-
100
1-40
1-80
1-80
patie
nts,
sinc
e qu
ality
of
"hig
h ris
k" o
r "lo
w ri
sk".
2-0
2-0
2-60
2-20
2-20
life
is a
maj
or o
utco
me.
3-0
3-0
3-0
3-0
3-0
GI-C
oRe;
3 o
f 546
1-63
1-89
1-26
1-83
1-16
2-22
2-7
2-41
2-15
2-43
3-15
3-4
3-33
3-2
3-41
HdN
k; 4
of 5
231-
531-
481-
51-
831-
02-
302-
302-
432-
132-
483-
173-
223-
523-
43-
52
400
Tab
le 3
: Su
mm
ary
of
EQ-5
D a
sses
smen
ts r
epo
rted
in c
ance
r st
ud
ies
Auth
or, Y
ear
Canc
er ty
pe:
nIn
dex
VAS
%%
%%
%Sc
orin
gAu
thor
Revi
ewer
(Ref
eren
ce N
o)Su
bgro
up
mea
nm
ean
MO
SCUA
PDAD
Algo
rithm
Com
men
tsCo
mm
ents
[Ref
eren
ce]
(SD)
(SD)
GEN
: Low
Ris
k; 5
of 5
45
1-94
1-10
01-
941-
891-
842-
42-
02-
22-
72-
93-
23-
03-
43-
43-
7Sc
hnei
der e
t al,
2000
49Hd
Nk
110.
54
56Do
lan
1997
,Sm
all s
ampl
e si
ze fo
r can
cer.
(0.3
3)(2
.3)
UK
Sulli
van
et a
l,20
05 1
1BR
E; 1
of 4
236
0.81
Shaw
200
5,Co
ncer
n ab
out c
eilin
gDi
sutil
ity o
f con
ditio
n re
por-
Uni
ted
effe
cts
and
pote
ntia
lte
d fo
r all
grou
ps; 2
5%,
Stat
esla
ck o
f dis
crim
inat
ion.
50%
, and
75%
EQ
-5D
PRO
; 2 o
f 4
171
0.77
scor
es a
lso
give
n.G
EN: O
ther
Can
cer;
132
0.85
3 of
4
SKIN
; 4 o
f 450
50.
82N
orum
et a
l,G
I-CoR
e; H
OD*
*98
0.79
80 (2
0)19
9632
(0.2
3)W
eze
et a
l,20
0447
GEN
: Pre
-tre
atm
ent;
351-
381-
741-
141-
201-
9Do
lan
1997
,In
fo o
n M
O, S
C, a
nd U
A w
as1
of 2
U
Kon
ly fo
und
in a
bar
gra
ph.
2-62
2-23
2-63
2-71
2-77
3-0
3-3
3-23
3-9
3-14
GEN
: Pos
t- tr
eatm
ent;
1-50
1-74
1-14
1-23
1-34
2 of
22-
472-
262-
692-
662-
573-
33-
03-
173-
113-
9De
sand
es e
t al,
GEN
2005
48
62 (1
9)
* in
dex
sco
res
wer
e tr
ansf
orm
ed w
ith
in t
able
s to
a 0
-1 s
cale
fo
r co
nsi
sten
cy**
V
AS
sco
res
wer
e tr
ansf
orm
ed w
ith
in t
able
s an
d f
igu
res
to a
0-1
00 s
cale
fo
r co
nsi
sten
cySe
e A
pp
end
ix f
or
abb
revi
atio
ns
Figure 1: Summary of Article Retrieval
401
Fig
ure
2:
Tren
ds
in P
ub
licat
ion
s o
f C
ance
r St
ud
ies
usi
ng
EQ
-5D
402
403
Fig
ure
3:
EQ-5
D In
dex
Mea
n/M
edia
n S
core
s fo
r B
reas
t, P
rost
ate
and
Dig
esti
ve S
yste
m C
ance
rs
�M
ean
(95
% C
I);
� M
edia
n; �
Poo
led
mea
n
404
Fig
ure
4:
EQ-5
D In
dex
Mea
n/M
edia
n S
core
s fo
r A
ll O
ther
Can
cer
Typ
es
�M
ean
(95
% C
I);
405
Fig
ure
5:
Vis
ual
An
alo
g S
cale
Mea
n/M
edia
n S
core
s fo
r A
ll C
ance
r Ty
pes
�M
ean
(95
% C
I);
� M
edia
n;
406
Fig
ure
6:
Dis
trib
uti
on
of
Res
po
nse
s to
Mo
bili
ty D
imen
sio
n o
f EQ
-5D
407
Fig
ure
7:
Dis
trib
uti
on
of
Res
po
nse
s to
Sel
f C
are
Dim
ensi
on
of
EQ-5
D
408
Fig
ure
8:
Dis
trib
uti
on
of
Res
po
nse
s to
Usu
al A
ctiv
itie
s D
imen
sio
n o
f EQ
-5D
409
Fig
ure
9:
Dis
trib
uti
on
of
Sco
res
for
Pain
/ Dis
com
fort
Dim
ensi
on
of
EQ-5
D
410
Fig
ure
10:
D
istr
ibu
tio
n o
f Sc
ore
s fo
r A
nxi
ety/
Dep
ress
ion
Dim
ensi
on
of
EQ-5
D
411
••• APPENDIX 1:
ABBREVIATIONS USED IN TABLES/FIGURES
Cancer TypesBONJNT Bones and jointsBRE BreastGI Digestive SystemCoRe Colon and Rectum (Colorectal)ESO EsophagusLIV LiverSTO StomachNHL Non-Hodgkin LymphomaHOD Hodgkin’s DiseaseMTMY Multiple MyelomaPROS ProstateLUNG LungGEN General cancer – no type specifiedLEU LeukemiaHdNk Head and Neck
Study AbbreviationsaaIPI age-adjusted International Prognostic IndexABMT autologous bone marrow transplantationAssoc. associatedchemo chemotherapyCHOP cyclophosphamide, doxorubicin, vincristine, prednisoneDHAP cisplatin, cytarabine, dexamethasoneHDC High dose chemotherapyHDM high-dose melphalanFAC Fluorouracil, adriamycin, cyclosphosphamideFLIC Functional Living Index- CancerMA Megestrol acetateMed MedianMTSS Musculoskeletal Tumor Society functional evaluation systemPBSCT (PSCT) peripheral blood stem cell transplantationSEER Surveillance Epidemiology and End ResultsTTO time tradeoffTx treatmentVAD vincristine, adriamycin and dexamethasonVAS visual analog scaleVIM etoposide, ifosfamide, methotrexate