journa l homepage: www.e lsev ier .com/ locate /vacc ine
creening, prevention and treatment of cervical cancer—A global and regionaleneralized cost-effectiveness analysis
ary Michael Ginsberg a,∗, Tessa Tan-Torres Edejer a, Jeremy A. Lauer a, Cecilia Sepulveda b
World Health Organization, Health Systems Financing Department, Costs, Effectiveness, Expenditure and Priority Setting Unit, Geneva, SwitzerlandWorld Health Organization, Chronic Diseases and Health Promotion Department, Chronic Diseases Prevention and Management Unit, Geneva, Switzerland
r t i c l e i n f o
rticle history:eceived 16 April 2008eceived in revised form 6 July 2009ccepted 10 July 2009vailable online 31 July 2009
The paper calculates regional generalized cost-effectiveness estimates of screening, prevention, treatmentand combined interventions for cervical cancer.
Using standardised WHO-CHOICE methodology, a cervical cancer model was employed to provide esti-mates of screening, vaccination and treatment effectiveness. Intervention effectiveness was determinedvia a population state-transition model (PopMod) that simulates the evolution of a sub-regional popula-tion accounting for births, deaths and disease epidemiology. Economic costs of procedures and treatmentwere estimated, including programme overhead and training costs.
In regions characterized by high income, low mortality and high existing treatment coverage, theaddition of any screening programme to the current high treatment levels is very cost-effective. However,based on projections of the future price per dose (representing the economic costs of the vaccinationexcluding monopolistic rents and vaccine development cost) vaccination is the most cost-effectiveintervention.
In regions characterized by low income, low mortality and existing treatment coverage around 50%,expanding treatment with or without combining it with screening appears to be cost-effective or verycost-effective. Abandoning treatment in favour of screening in a no-treatment scenario would not becost-effective. Vaccination is usually the most cost-effective intervention. Penta or tri-annual PAP smearsappear to be cost-effective, though when combined with HPV-DNA testing they are not cost-effective.
In regions characterized by low income, high mortality and low treatment levels, expanding treatmentwith or without adding screening would be very cost-effective. A one off vaccination plus expandingtreatment was usually very cost-effective. One-off PAP or VIA screening at age 40 are more cost-effectivethan other interventions though less effective overall.
From a cost-effectiveness perspective, consideration should be given to implementing vaccination(depending on cost per dose and longevity of efficacy) and screening programmes on a worldwide basisto reduce the burden of disease from cervical cancer. Treatment should also be increased where coverage
is low.
. Introduction
Cervical cancer is the second most common cancer in femalesith around 500,000 new cases occurring annually. In 2002, cervi-
al cancer accounted for 239,000 deaths (7.6% of female deaths dueo malignant neoplasm) worldwide [1], around 2% of total weightedears of life lost in women aged 25–64 [2] and around 9.4% of the
urden of disease in females caused by malignant neoplasm [1].
The Burden of Disease in terms of Disability adjusted life yearsDALY) per million population was inversely related to the coun-ries level of development, increasing from 286 (in counties with
very low child and very low adult mortality – see Appendix A1, WHOmortality stratum A), to 386 (in countries with low child and lowadult mortality – WHO mortality stratum B), to 699 (in countrieswith low child and high adult mortality – WHO mortality stratumC), rising to 784 (in countries with high child and high or very highadult mortality – WHO mortality strata D and E) [1]. Deaths per mil-lion female population ranged from 35.5 (stratum A), 55.5 (stratumB), 89.4 (stratum C) to 120.1 in strata D and E.
Prevention by using cervical smears to detect pre-invasive andearly disease has been shown to lead to significant reductions in
both incidence and mortality in many countries [3,4].
The number of available strategies in the fight against cer-vical cancer has increased considerably, and making the rightchoices has therefore become more complex than ever before.Cost-effectiveness analyses, which combine the disciplines of
pidemiology and economics, will not only help guide decision-akers to choose the optimal allocation of resources amongst the
arious cervical cancer interventions, but also between cervicalancer interventions and interventions for other conditions andiseases [5,6].
The purpose of this study, utilizing standard methods and com-anion tools [7–13], is to compare and evaluate the costs andffectiveness of different screening and prevention strategies relat-ng to cervical cancer in all 14 WHO regions (see Appendix A1) ofhe world.
This cost-effectiveness analysis will hopefully help answermportant policy questions such as whether and what type and fre-uency of screening programme for cervical cancer should be added
n developed countries, where a high proportion of the populationas access to treatment. In developing countries, the relevant policyuestion could be phrased as whether to put scarce resources intocreening programmes or into expanding the low existing levelsf treatment coverage, or to provide both screening and treatmentrogrammes.
. Methods
.1. The WHO-CHOICE framework
Generalized cost-effectiveness analysis (GCEA) is characterizedy the assessment of costs and effects against the “null scenario”,hich represents the theoretical absence of interventions for a
articular condition. WHO-CHOICE (CHOosing Interventions thatre Cost Effective) [6,10] comprises sector and population-levelost-effectiveness analyses (CEA) based on the GCEA framework.his approach facilitates and enhances [14] the ability to compareEA findings across a wide range of competing interventions [15].HOICE also aims to identify order-of-magnitude differences in theelative cost-effectiveness of (single and combined) interventiontrategies, with a view to identifying combinations of interventionshat would generate most health gains within existing resourceonstraints. Worldwide, the CHOICE approach has elicited interestrom developing countries equal to or greater than from developedountries.
The ideal of systematically evaluating all possible combinationsf implemented and potential interventions at the country level
s a gigantic task, which has not yet been achieved by any singleountry. On the other hand, global estimates are of little use tondividual country’s decision making processes. However, a com-romise can be reached by performing analyses within a definedegion characterized by similar epidemiological and developmen-al profiles that broadly classify interventions that are likely to beery cost-effective, cost-effective or cost ineffective [5].
This study models the costs and effects of key interventions for4 WHO-classified regions (see Appendix A1), formed by groupinghe WHO member states into six regional and five mortality stratan the basis of their child and adult mortality levels [15].
In addition, regional analysis provides results in such a way thatnalysts from an individual country within a region can adapt toheir own setting if they so wish.
.2. Choice of the interventions
The various screening interventions and frequencies chosen fornclusion were as follows:
.2.1. Screening (followed by removal of any discovered cancerousesions)(a) PAP smear (annually, tri-annually and penta-annually between
the ages of 20–65, at ages 35, 40, 45, once at age 40); sensitivity
27 (2009) 6060–6079 6061
for low grade lesions = 0.60 [16] (plausible range 0.34–0.86 [17]),specificity = 0.95 [16,18] (plausible range 0.88–0.99 [18])).
(b) HPV-DNA testing (at ages 35, 40, 45, once at age 40); sensitivityfor low grade lesions = 0.84 (personal communication, Jane Kim)(plausible range 0.50–1.00 [18])), specificity = 0.88 (personalcommunication, Jane Kim) (plausible range 0.82–0.97 [17]).
(c) Visual inspection after application of 3–5% acetic acid (VIA)(at ages 35, 40, 45, once at age 40); sensitivity for low gradelesions = 0.68 (personal communication, Jane Kim) plausiblerange (0.60–0.90 [19]), specificity = 0.85 (personal communica-tion, Jane Kim) plausible range (0.66–0.96 [19]).
(d) PAP (annually, tri-annually and penta-annually between ages20 and 29) then PAP and HPV combined (annually, tri-annuallyand penta-annually from 30 to 65 years of age); sensitivity forlow grade lesions = 0.94 (plausible range 0.87–0.98 [17]), speci-ficity = 0.93 (plausible range 0.77–0.96 [17]).
These interventions include screening and lesion removal in scenar-ios where no treatment (radiotherapy, surgery or chemotherapy)for cancers is available. In scenarios where programmes screenevery 1, 3 or 5 years, no intervention is offered for low grade lesionssince their growth or disappearance will be regularly monitored.
In scenarios with less frequent screening schedules (once orthrice a lifetime) involving PAP or HPV, screening will result inaround 72.25% of women with low grade lesions receiving cryother-apy (based on 85% being targeted for cryotherapy adjusted by a15% loss to follow-up). Around 12.75% of women with low gradelesions will receive a colposcopy examination (based on 15% beingtargeted adjusted for loss to follow-up), with 11.8% (after a fur-ther 15% follow-up loss) eventually receiving either LEEP (loopelectrosurgical excision procedure), conanization or a simple hys-terectomy. In total 83.1% of women with low grade lesions have theirlesions removed. Using VIA techniques, the initial loss to follow-upis avoided in what is in fact a “see and treat” scenario. Therefore 85%of women with low grade lesions receive cryotherapy, resulting ina removal of 95.4% of all low grade lesions.
For high grade lesions, the more frequent screening schedules(every 1, 3 or 5 years) involving PAP or HPV, will result in around56.7% of women with high grade lesions receiving a colposcopy(including biopsy) examination (based on 66.7% being targeted forcolposcopy adjusted by a 15% loss to follow-up). 56.7% will receivecryotherapy during the same visit. Around 28.3% (i.e. one thirdadjusted for a 15% loss) will receive either LEEP, conanization ora simple hysterectomy. In total, 85.0% of high grade lesions will beremoved.
The less frequent screening schedules (once or thrice a lifetime)involving PAP or HPV, will result in around 63.7% of women withhigh grade lesions receiving cryotherapy (based on 75% being tar-geted for cryotherapy directly, without a colposcopy, adjusted bya 15% loss to follow-up). Around 21.2% will receive a colposcopyexamination (based on 25% being targeted adjusted for 15% loss tofollow-up), with 18.1% (after a further 15% follow-up loss) eventu-ally receiving either conanization or a simple hysterectomy. In total,81.8% of high grade lesions are removed. Using VIA techniques, theinitial loss to follow-up is averted. Therefore 75% of women withhigh grade lesions receive cryotherapy, resulting in a removal of93.1% of all high grade lesions.
2.2.2. PreventionVaccination against HPV at age 12: In June 2006, the USA FDA
approved [20] the introduction of a safe, well tolerated [21] and
immunogenic vaccine, which has proved effective [22–25] againstthe cancer-causing human papillomaviruses [26–29]. Our modelwas based on delivering three doses of the vaccination to all femalesaged 12 in their school setting. All females who do not attendschools, ranging from 67.5% in the African region to less than 1%
6 accine
ib
2
rsw
tsciiseca4rcawop
orMcr
2
r
2
a
2
m
2
m
art
ceitis
2
aes
062 G.M. Ginsberg et al. / V
n the low-mortality Western Pacific region [30], were assumed toe vaccinated in health centers.
.2.3. TreatmentWhile current access to treatment varied considerably across
egions (see Appendix A2), intervention scenarios were explored inituations where no treatment was supplied and where resourcesere available to treat everyone who fell ill with invasive cancer.
Stage-specific treatment protocols were based on the assump-ion that resources would be available to maintain the currenttandard practice available in developed nations ([31,32], personalommunication Inbar Ben Shahar) in all the regions of the worldn the scenarios where treatment is available for all those withnvasive cancer. Based on the distribution of cancer cases betweentages [33] and the probability of receiving a procedure, it wasstimated that for local cancers (Stages 1a1 to 2a), 3% receive aonanization (all at stage 1a1), 10% a simple hysterectomy (allt stage 1a1), 78% a radical hysterectomy, 45% radiotherapy and5% chemotherapy, 15% intercavity radiation brachytherapy. Foregional cancers (Stages 2b to 3b), everyone receives radiotherapy,hemotherapy and intercavity brachytherapy. For distant cancers,ll persons at stage 4a receive radiotherapy and chemotherapy,hile all persons at stage 4b receive palliative chemotherapy based
n cisplatin with gemcitabine or plaxitaxel [34,35] and 50% receivealliative radiotherapy.
We took into account the approximately 11.6%, 30% and 13.0%f local, regional and distant cases that were estimated to suffer aelapse [36,37] approximately 1 year after their initial therapy [38].
ost relapsing persons would have additional radiotherapy andhemotherapy, while around 7.5% would have extensive extenu-ation surgery.
.2.4. Screening (with lesion removal) and treatmentThe screening interventions listed above (ia–id) with lesion
emovals in a setting where treatment of cancers is also available.
.2.5. Prevention and treatmentVaccination at age 12 in a setting where treatment of cancers is
lso available.
.2.6. Prevention and screeningVaccination at age 12, screening (ia–id) in a setting where treat-
ent of cancers is not available
.2.7. Prevention, screening and treatmentVaccination at age 12, screening (ia-id) in a setting where treat-
ent of cancers is available.Despite evidence suggestive of a causal link between active [39]
nd passive [40] exposure to tobacco smoke and cervical cancer,educing tobacco use was not considered as an intervention becauseobacco use is a risk factor for many other diseases.
Other preventive interventions, such as introducing mass mediaampaigns to promote safe sex [41], were excluded as their cost-ffectiveness ratio is liable to be greatly overestimated since thesenterventions are likely to reduce the risk of other sexually transmit-ed diseases. Finally, the addition of folate was not included sincets effect has not been supported by the few nested case-controltudies on non-invasive cervical cancer [42].
.3. Efficacy of screening interventions
To compensate for the lack of evidence from randomized trials,nd the considerable time and resources required, various math-matical models have been constructed to estimate the effects ofcreening for cervical cancer. As a result of variations in the model’s
27 (2009) 6060–6079
quality of specification and parameter values, the results from mod-eling vary considerably, and no single model can be regarded asbeing the “gold-standard”.
Our estimates of the age-specific efficacy of the screening inter-ventions were based on a model constructed by researchers atHarvard (Jane Kim and Sue Goldie). The model was based on thedata estimating transition probabilities to low grade lesions, highgrade lesions, local, regional and distant cancers in subjects whereHPV was detectable or undetectable [17,18,43].
The Harvard model estimated age-specific rates of the effect ofthe screening intervention on decreasing incidence and mortalityrates. Additional estimates were supplied for age-specific reduc-tions in low and high grade lesions, as well as for improvementin stage distribution of cancers (i.e. more cancers discovered at anearlier stage).
Screening enables the detection and removal of potentially can-cerous lesions, thereby reducing the incidence of cervical cancer,even in situations where no treatment for cancer is available. Ifcancer treatment is available, screening will also enable their treat-ment at an earlier less-severe stage, thus reducing the case-fatalityrate from cervical cancer.
2.4. Vaccine efficacy
Vaccination has an efficacy of 90% against genotypes 16 or 18[44]. Regional estimates of the percentage of cancers attributableto these genotypes (ranging from 51.0% in WprB to 86.5% in EmrD),were based on pooled estimates (n = 14,063, see Appendix A2)from meta-analyses ([26,45], supplemented by individual studies[46,47]. Two scenarios were analyzed, one where vaccine efficacywanes at an absolute rate of 2.5% per annum after 10 years, and onewhere no waning occurred.
2.5. Treatment efficacy
Estimates of 10-year cancer mortality were based on data fromthe WHO global burden of disease (GBD) project for the year 2000.In regions where mortality data were incomplete, GBD estimateswere based on adjusting survival data for the level of economicdevelopment in each region [48,49].
Data on 10-year survival from AmrA and AfrE regions, whereage-specific treatment coverage rates were 90–100% and 2–10%respectively, were used as anchor points to enable linear extrap-olations to be made for estimating:
(i) age-specific case fatality rates under a “full treatment” scenario,and
(ii) age-specific case fatality rates in the “null scenario”.
The first (i) is primarily a scenario where addition of chemother-apy to radiotherapy is rare. Efficacy was nevertheless adjusted totake into account of the additional benefit gained by the additionof chemotherapy to radiotherapy [50]. The second (ii) is a scenariowhere absolutely no treatment is provided.
The 10-year rates were converted to annual hazard rates accord-ing to the following formula [51]:
ln(1 − % dying from cervical cancer)10 years
Age-specific treatment efficacy was then estimated as the pro-portional decrease in annual hazard rates attained when moving
from the “null” to “full-treatment scenario”.
Before 2000, significant screening was only carried out inthe AmrA [52–55], EurA [55], WprA [55], and AmrB and AmrD[56] regions. In other regions, screening was mainly opportunis-tic. Reported regional age-specific cervical cancer incidence rates
G.M. Ginsberg et al. / Vaccine 27 (2009) 6060–6079 6063
[ht
mswcraobwdc
icer
2
trotbccsiacFm
thc
dugtma
Table 1aUnit costs ($I at 2000 price levels) of screening and prevention procedures in selectedregions.
AmrA EurA EurC SearD AfrD
Taking PAP smear 8.90 6.60 4.00 2.09 2.52Reading PAP smear 7.53 5.62 3.26 1.76 2.25PAP smear total 16.43 12.22 7.26 3.85 4.77
PAP and HPV-DNA collection 12.64 9.69 7.01 4.70 5.42PAP and HPV-DNA total 42.69 34.38 30.37 24.78 27.71
VIA 8.60 6.32 3.67 1.76 2.15
Vaccination at Health Centera 8.37 6.81 6.30 5.19 4.32
type of activities required (e.g. less frequent interventions requirefewer overhead staff). Programme costs for other regions wereadjusted to reflect differences in the population size and density.
Table 1bUnit costs ($I at 2000 price levels) of treatment procedures in selected regions.
49,50] were adjusted using efficacy estimates by calculating theigher null-scenario incidence that would have occurred if none ofhe population had been screened.
By substituting region-specific population, incidence andortality rates into the PopMod model (see Appendix A2), region-
pecific estimates of intervention efficacies were generated. Theseere then further modified by the effect on incidence (for vac-
ination and screening scenarios) and the effect on case-fatalityates (for screening and treatment scenarios). The model takes intoccount not only the influence of differences in regional prevalencen the probability that screening interventions will detect cases,ut also that in scenarios where HPV vaccination is provided, thisill cause a subsequent decrease in disease prevalence and inci-
ence, so any screening interventions would be less likely to detectases.
The estimated decreases in incidence and case fatality from 58ntervention scenarios representing various combinations of vac-ination, screening and treatment were calculated. The resultingfficacy estimate (i.e. intervention impact) was applied to eachegion’s null-scenario incidence and case-fatality rates.
.6. Population model (PopMod) for cervical cancer
Intervention effectiveness was determined using a state transi-ion population model [51], which simulates the development of aegional population accounting for births, deaths and the epidemi-logy of the disease in question (Fig. 1). Susceptible women (i.e.hose free of cervical cancer) become cases at a rate determinedy incidence, i, including re-occurrence of cancers. Women withervical cancer can die either from cervical cancer (modeled byase-fatality, f) or other causes (background mortality, m). Remis-ions are indirectly modeled by using a lower case-fatality ratenstead of setting an artificial age limit (e.g. 10 years) to define theverage duration after which remissions are deemed to occur. Sus-eptibles are also subject to the general background mortality rate.or all rates, units are the number of events per year at risk. Theodel is segmented into 1 year age groups.
Time spent with cervical cancer is discounted according to aariff (disability weight) estimated at 0.075, yielding an averageealth state valuation (HSV) for cervical cancer of 0.925 (personalommunication, K. Shibuya, WHO).
Each scenario was simulated in a model run of 100 years. The
ifference in the total number of healthy years lived by the pop-lation between each intervention scenario and the null scenarioives the population-level health gain (DALYs averted) attributableo implementation of the intervention. In accordance with GBD
ethodology, DALYs averted were discounted at a rate of 3% pernnum and are age-weighted [57].
Vaccination at schoola 8.91 7.02 4.59 3.48 3.60
a For 3 doses, including 10% wastage at $0.60 per dose.
2.7. Costs of screening and preventive interventions
Intervention costs for the 10-year implementation period werediscounted at 3% and expressed in international dollars ($I) atyear 2000 price levels. An international dollar has the equiva-lent purchasing power that a US dollar has in the USA. Costsin local currency units are converted to international dollars bymeans of purchasing-power-parity (PPP) exchange rates, instead oftrade-weighted exchange rates. A PPP exchange rate represents thenumber of units of a country’s currency that is required to buy thesame amounts of goods and services in the domestic market thata US dollar would buy in the USA [11]. Expressing costs in inter-national dollars facilitates more meaningful comparisons acrosssub-regions by adjusting for differences in relative price levels (i.e.purchasing power).
Provision was made for repeat PAP and HPV smears in 7% ofscreenings, based on UK targets [58]. For a tri-annual PAP screen-ing, programme costs (i.e. any costs not incurred at point of contact),were based on an estimate of around four administrative posts (fornotification, coordination, follow-up and monitoring) per millionpopulation in each region, in addition to an estimate of costs formedia, office space and other items. Programme costs for otherscreening interventions were proportionally adjusted to reflect the
a 4000 mg flouracil, 80 mg cisplatin and 0.22 mg metoclopromide.b Includes 12 days’ hospitalization.c Includes biopsy, 1 day’s hospitalization, blood test and 2 follow-up visits.d 244 mg plaxitaxel, 120 mg cisplatin and 0.22 mg metoclopromide.e Includes 5 days’ hospitalization.f Includes 4 days’ hospitalization.
6064 G.M. Ginsberg et al. / Vaccine 27 (2009) 6060–6079
Table 2Costs ($I) and effectiveness per averted DALY by intervention by selected regions.
(Age-weighted and discounted at 3% per annum)
AmrA EurC AfrD
GDP per capita Costs Effectiveness Costs Effectiveness Costs Effectiveness
Per woman 20–65 Per woman 20–65 Per woman 20–65
PAP smears (a)Annual (20–65) PAP (1, 20, 65) 107 0.01005 45 0.00748 67 0.01274Tri-annual (20–65) PAP (3, 20, 65) 59 0.00919 24 0.00680 29 0.01105Penta-annual (20–65) PAP (5, 20, 65) 39 0.00812 15 0.00605 18 0.01017At 35, 40, 45 years of age PAP (5, 35, 45) 15 0.00680 5 0.00506 6 0.00747At 40 years of age PAP (40) 6 0.00372 2 0.00279 3 0.00473
PAP then PAP/HPV (a)Annual PAP (20–29), PAP and HPV (30–65) COM (1, 20, 65) 202 0.01062 101 0.00790 109 0.01326Tri-annual PAP (20–29), PAP and HPV (30–65) COM (3, 20, 65) 97 0.01003 44 0.00743 44 0.01180Penta-annual PAP (20–29), PAP and HPV (30–65) COM (5, 20, 65) 62 0.00914 28 0.00681 28 0.01120
HPV tests (a)At 35, 40, 45 years of age HPV (5, 35, 45) 30 0.00756 14 0.00562 13 0.00824At 40 years of age HPV (40) 12 0.00436 5 0.00327 5 0.00559
VIA (a)At 35, 40, 45 years of age VIA (5, 35, 45) 22 0.00733 7 0.00546 7 0.00802At 40 years of age VIA (40) 9 0.00416 3 0.00311 3 0.00532HPV vaccination at age 12At $0.60 per dose Vac $0.60 1 0.00673 1 0.00546 1 0.01070At $2.00 per dose Vac $2.00 2 0.00673 2 0.00546 3 0.01070At $0.60 per dose with waning immunity Wan Vac $0.60 1 0.00462 1 0.00382 1 0.00856At $2.00 per dose with waning immunity Wan Vac $2.00 2 0.00462 2 0.00382 3 0.00856
Treatment (Rx) of invasive cancer Rx 17 0.01968 7 0.01926 5 0.02528
PAP smears (a) + RxAnnual (20–65) PAP (1, 20, 65) + Rx 122 0.02760 51 0.02509 72 0.03507Tri-annual (20–65) PAP (3, 20, 65) + Rx 76 0.02690 30 0.02456 34 0.03384Penta-annual (20–65) PAP (5, 20, 65) + Rx 57 0.02600 22 0.02392 24 0.03309At 35, 40, 45 years of age PAP (5, 35, 45) + Rx 36 0.02481 14 0.02290 13 0.03061At 40 years of age PAP (40) + Rx 29 0.02245 11 0.02124 9 0.02862
PAP then PAP/HPV (a) + RxAnnual PAP (20–29), PAP and HPV (30–65) COM (1, 20, 65) + Rx 217 0.02804 106 0.02553 113 0.03567Tri-annual PAP (20–29), PAP and HPV (30–65) COM (3, 20, 65) + Rx 112 0.02758 50 0.02515 49 0.03451Penta-annual PAP (20–29), PAP and HPV (30–65) COM (5, 20, 65) + Rx 78 0.02687 34 0.02462 33 0.03398
HPV tests (a) + RxAt 35, 40, 45 years of age HPV (5, 35, 45) + Rx 50 0.02539 21 0.02332 19 0.03117At 40 years of age HPV (40) + Rx 34 0.02293 14 0.02157 12 0.02923
VIA (a) + RxAt 35, 40, 45 years of age VIA (5, 35, 45) + Rx 42 0.02522 14 0.02320 13 0.03101At 40 years of age VIA (40) + Rx 31 0.02277 11 0.02146 9 0.02904
HPV vaccination at age 12 m + RxAt $0.60 per dose Vac $0.60 + Rx 27 0.02469 10 0.02319 9 0.03332At $2.00 per dose Vac $2.00 + Rx 28 0.02469 11 0.02319 10 0.03332At $0.60 per dose with waning immunity Wan Vac $0.60 + Rx 28 0.02313 11 0.02206 9 0.03185At $2.00 per dose with waning immunity Wan Vac $2.00 + Rx 29 0.02313 12 0.02206 11 0.03185
HPV vaccine + PAP smearsAnnual (20–65) PAP (1, 20, 65) + Vac 121 0.01104 51 0.00855 71 0.01681Tri-annual (20–65) PAP (3, 20, 65) + Vac 69 0.01053 27 0.00816 32 0.01586Penta-annual (20–65) PAP (5, 20, 65) + Vac 45 0.00986 18 0.00770 21 0.01525At 35, 40, 45 years of age PAP (5, 35, 45) + Vac 18 0.00768 7 0.00609 8 0.01208At 40 years of age PAP (40) + Vac 8 0.00610 3 0.00493 4 0.01050
HPV vaccine (b) + PAP then PAP/HPV (a)Annual PAP (20–29), PAP and HPV (30–65) COM (1, 20, 65) + Vac 234 0.01140 116 0.00883 121 0.01718Tri-annual PAP (20–29), PAP and HPV (30–65) COM (3, 20, 65) + Vac 113 0.01109 51 0.00858 50 0.01641Penta-annual PAP (20–29), PAP and HPV (30–65) COM (5, 20, 65) + Vac 73 0.01056 33 0.00821 32 0.01600
HPV vaccine (b)** + HPV tests (a)At 35, 40, 45 years of age HPV (5, 35, 45) + Vac 35 0.00801 16 0.00634 16 0.01244At 40 years of age HPV (40) + Vac 14 0.00636 7 0.00512 7 0.01085
HPV vaccine (b) + VIA (a)At 35, 40, 45 years of age VIA (5, 35, 45) + Vac 36 0.00791 16 0.00627 16 0.01234At 40 years of age VIA (40) + Vac 11 0.00627 4 0.00506 4 0.01074
G.M. Ginsberg et al. / Vaccine 27 (2009) 6060–6079 6065
Table 2 (Continued )
(Age-weighted and discounted at 3% per annum)
AmrA EurC AfrD
GDP per capita Costs Effectiveness Costs Effectiveness Costs Effectiveness
Per woman 20–65 Per woman 20–65 Per woman 20–65
At 35, 40, 45 years of age PAP (5, 35, 45) + Vac + Rx 39 0.02547 15 0.02376 15 0.03441At 40 years of age PAP (40) + Vac + Rx 30 0.02424 12 0.02287 11 0.03323
HPV vaccine (b) + PAP then PAP/HPV (a) + RxAnnual PAP (20–29), PAP and HPV (30–65) COM (1, 20, 65) + Vac + Rx 249 0.02859 122 0.02625 125 0.03881Tri-annual PAP (20–29), PAP and HPV (30–65) COM (3, 20, 65) + Vac + Rx 129 0.02834 57 0.02604 55 0.03817Penta-annual PAP (20–29), PAP and HPV (30–65) COM (5, 20, 65) + Vac + Rx 89 0.02789 39 0.02569 37 0.03779
HPV vaccine (b) + HPV tests (a) + RxAt 35, 40, 45 years of age HPV (5, 35, 45) + Vac + Rx 56 0.02573 24 0.02396 22 0.03468At 40 years of age HPV (40) + Vac + Rx 36 0.02443 15 0.02301 14 0.03348
HPV vaccine (b) + VIA (a) + RxAt 35, 40, 45 years of age VIA (5, 35, 45) + Vac + Rx 47 0.02565 16 0.02390 14 0.03460A 33
K ose. Y6
aacf
mw
TE
AVRVPPCC
EVRVPVPCCC
WVRVPVPPP
NVCfetet
t 40 years of age VIA (40) + Vac + Rx
ey: (a) including removal of lesions. (b) With waning immunity costing $0.60 per d5) PAP every x years from 20 to 29, then PAP and HPV every x years until 65.
In addition, the costs for each hypothetical programme includedprovision for national-level posts for management, monitoring
er Screening Programmes) and provision for training of staff (e.g.or smear-taking, smear-reading and vaccination).
Quantities (labor, rooms, drugs, disposable and reusable equip-ent) for the delivery of screening tests and treatment proceduresere based mainly on data from the WHO Collaborating Centre for
able 3axpansion paths for interventions in ‘A’ regions.
otes: (a) Vaccination at age 12 with lifelong immunity costing $0.60 per dose. (b)accination with waning immunity costing $0.60 per dose. Rx: Treatment of Invasiveancer. Includes removal of lesions. PAP: (x, 20, 65) Screening by PAP, every x years
rom age 20 until age 65. VIA: (5, 35, 45) screening by visual inspection with acid,very 5 years from age 35 until age 45. COM: (x, 20, 65) PAP every x years from 20o 29, then PAP and HPV-DNA every x years until age 65. **Intervention is very cost-ffective. *Intervention is cost-effective. N: not cost-effective as in excess of threeimes GNP per head.
0.02437 12 0.02296 11 0.03341
YY (x, 20, 65) Screening by YYY, every x years from age 20 until age 65. COM (x, 20,
Essential Health Technologies (EHTP) data base (personal commu-nication, Peter Heinman).
Unit costs of secondary hospital in-patient days and out-patientvisits were based on an econometric analysis of a multinationaldataset of hospital costs controlling for differences in income andother covariates [8]. Pharmaceutical prices were obtained frominternational sources [59] or from the British National Health Ser-vice [60], adjusted to year 2000 price levels. To calculate total costs,average unit costs were multiplied by the number of units of careused in the region (at a population coverage rate of 100%).
2.8. Decision rules
By combining estimates of costs and effects, the cost perDALY averted (i.e. cost-effectiveness) was calculated for each inter-vention. An intervention is defined as very cost-effective andcost-effective if the cost per DALY averted is less than the per capitaGDP or between 1 and 3 times the per capita GDP, respectively. If thecost per DALY averted is more than three times the GDP per capita.The intervention is defined as not cost-effective [61]. Sensitivityanalyses were performed to generate costs per DALY averted with-out age-weighting and discounting DALYs at 3% per annum. Owingto the large number of interventions in 14 different regions and thenumber of potentially sensitive variables, space does not permit usto carry out either probabilistic uncertainty analysis or to generatecost-effectiveness acceptability curves, which show the probabilityof an intervention falling below a threshold. Due to the large num-ber of data points estimated we present only point-estimates of thecost-effectiveness ratios.
3. Results
3.1. Unit costs
Unit costs of interventions included costs of facilities, humanresources, disposable medical devices, reusable medical devicesand pharmaceuticals, the latter two including costs of transporta-tion. Unit costs for screening or vaccination (including programmeand training overheads) varied considerably (Table 1a) across
regions primarily due to differentials in labour costs. Costs in AfrDexceeded those in SearD mainly because of higher labour andtransportation costs. VIA was the cheapest intervention in all theregions, and the PAP-HPV combination was the most expensive. Inthe A sub-regions (low adult, very low child mortality), the costs
6 accine 27 (2009) 6060–6079
ohtb
occHet
3
esdlo
wcmw$rb
smwqfanotto
4
TArtdRcac
4A
egHi
sTv
Table 3bExpansion paths for interventions in ‘B and C’ regions.
Notes: (a) Vaccination at age 12 with lifelong immunity costing $0.60 per dose. (b)Vaccination with waning immunity costing $0.60 per dose. Rx: treatment of invasivecancer. Includes removal of lesions. PAP: (x, 20, 65) Screening by PAP, every x yearsfrom age 20 until age 65. VIA: (5, 35, 45) Screening by Visual Inspection with Acid,every 5 years from age 35 until age 45. COM: (x, 20, 65) PAP every x years from 20
066 G.M. Ginsberg et al. / V
f school-based vaccination exceeded centre-based vaccination asigher labour costs in the school setting (as a result of the extraime taken by nurses to travel from the clinic to the school andack) more than offset the savings in facility costs.
Estimates of unit costs per test or vaccination (Table 1a), andf procedures used for removing lesions and treating cervical can-er including programme and training overheads (Table 1b), varyonsiderably by region, primarily due to differences in labour costs.owever for chemotherapy, costs in developing regions sometimesxceeded those in more developed regions mainly due to the higherransport costs for pharmaceuticals offsetting lower costs of labour.
.2. Costs and effectiveness
While costs of tradable goods, such as pharmaceuticals andquipment, are assumed by the WHO POPMOD software to be theame across regions, variations in total costs occurred due to theifferences in labour and capital cost of inputs (e.g. vaccination,
esion removal, cancer treatment), as well as due to the influencesf population density on the cost of programme delivery.
Table 2 lists total costs by selected regions of interventions peroman aged 20–65, comprising of the sum of the programme
ost, lesion-removal and cancer treatment costs. Programmes withore frequent screening protocols, and where cancer treatmentas available, were more costly. Vaccination, at a vaccine cost of
0.60 per dose, was the cheapest intervention. However in someegions, a one-off PAP smear, or VIA inspection at age 40, wouldecome cheaper at a vaccine cost of $2.00 per dose.
Treatment of cancer yielded the highest effectiveness of anyingle intervention in DALY terms (Table 2). DALYs averted by treat-ent exceeded those gained by vaccination at age 12 in conjunctionith screening. Among screening interventions of the same fre-
uency, the PAP-HPV combinations had the highest effectivenessollowed by PAP HPV-DNA and VIA. Higher effectiveness levels weressociated with more frequent screening. In many regions, vacci-ation (with no waning) only attained the level of effectivenessf thrice-lifetime VIA, though in AFRD the effectiveness of vaccina-ion was roughly equivalent to five-yearly PAP smears. With waningaken into account, vaccine effectiveness usually failed to reach thatf thrice-lifetime PAP smears except in AfrD.
. Cost-utility analysis
Interventions on the expansion path are shown inables 3a, 3b and 3c and are shown in boldface type in Appendices3–A5 along with other interventions. The comparator for every
ow in the tables is the null scenario (i.e.: no intervention orreatments provided). This means that the costs per averted DALYata presented represent the ACER (Average Cost Effectivenessatios). The ACERs provided in the tables enable direct informedomparisons to be made between the interventions .and thus serves a summary measure of cost-effectiveness on the basis of whichoncise overview judgments can be made.
.1. Very low child and adult mortality sub-regions (suffix—Table 3a and Appendix A3)
In regions characterized by high income, low mortality and highxisting treatment coverage, the addition of any screening pro-ramme to the current high treatment levels is very cost-effective.owever, vaccination and treatment are the most cost-effective
nterventions.Treatment, with a cost per DALY averted below I$ 1000 (repre-
enting only 3–4.2% of the per capita GDP), is very cost-effective.he main policy questions in these regions are whether inter-entions should be added to high-coverage status-quo treatment
to 29, then PAP and HPV-DNA every x years until age 65. **Intervention is very cost-effective. *Intervention is cost-effective. N: not cost-effective as in excess of threetimes GNP per head.
programmes. The addition of any screening is still very cost-effective. However, by examining the expansion path we canidentify the most desirable options that dominate others by avert-ing more DALYs at a lower cost for a given budget level.
For a low budget level, for all three “A” regions (characterized
by very low child and adult mortality) a one-off HPV vaccination atage 12 (costing $0.60 per dose) is the initial option on the expan-sion path (Table 3a). As resource availability increase, providingtreatment (Rx) is the next point on the expansion path (essentially
G.M. Ginsberg et al. / Vaccine
Table 3cExpansion paths for interventions in ‘D and E’ regions.
Notes: (a) Vaccination at age 12 with lifelong immunity costing $0.60 per dose. (b)Vaccination with waning immunity costing $0.60 per dose. Rx: treatment of invasivecancer. Includes removal of lesions. PAP: (x, 20, 65) Screening by PAP, every x yearsfrom age 20 until age 65. VIA: (5, 35, 45) screening by visual inspection with acid,every 5 years from age 35 until age 45. COM:(x, 20, 65) PAP every x years from 20tet
tata
p(apcpA
bI
one-off Pap smears or VIA at age forty represent more cost-effective
o 29, then PAP and HPV-DNA every x years until age 65. **Intervention is very cost-ffective. *Intervention is cost-effective. N: not cost-effective as in excess of threeimes GNP per head.
he currently situation), followed by the combination of treatmentnd vaccination. However, the addition or substitution of screeningo (or instead of) vaccination, averts extra DALYs at an affordabledditional cost.
In AmrA for example, the next point on the expansion path isenta-annual PAP smears (from ages 25 to 65) and vaccinationsat $0.60 per dose) every ten years (i.e.: waning efficiency)). Withn incremental cost-effectiveness ratio (ICER) of I$13,867 (com-ared to vaccination + Rx), this is the preferred level of (veryost-effective) intervention if we are using as a yardstick a cut-offoint corresponding to the GNP per capita (of around I$31,500 in
mrA).
The ICER of moving to a tri-annual and annual PAP-HPV com-ination plus waning vaccination and treatment is I$ 92,608 and
$ 468,785 respectively. Applying the less stringent “cost-effective”
27 (2009) 6060–6079 6067
threshold, means interventions should be chosen up to the pointwhere their ICER is less than three times the per capita GDP (aroundI$ 94,500 for AmrA). Therefore tri-annual PAP-HPV plus vaccinationand treatment should be provided. Note that the ICER of providingannual PAP-HPV combination is not cost-effective as it exceeds the3xGDP threshold.
For EurA region, thrice a lifetime PAP or VIA (at ages 35, 40and 45) + Rx are the very cost-effective options (that provide thelargest aversion of DALYs), although the ICER of the penta-annualPAP smear with waning vaccination + Rx only just exceeds the GDPper capita guideline. Penta-annual PAP and HPV-DNA with waningvaccination + Rx is very cost-effective. Expansion to a tri-annualor annual combination is not recommended as they are not cost-effective.
For the WprA region, due to its differential cost structures,adding waning vaccination to screening and treatment is not cost-effective. VIA at ages 35,40 and 45 + Rx is next to the verycost-effective cut-off, while penta-annual PAP smears with waningvaccination + Rx is next to the cost-effective cut-off. Taking morefrequent PAP smears is not cost-effective.
In regions characterized by low income, high mortality and lowtreatment levels (those with suffixes “D” or “E”, Appendix A5),expanding treatment coverage with or without screening is verycost-effective. Due to tight resource constraints, perhaps only thecheapest programmes would be feasible, in other words one-offPAP or VIA screening at age 40 or vaccinations, which are all similarin cost despite the latter’s greater cost-effectiveness. If only lim-ited resources are available, then for all “D” and “E” regions exceptEmrD, one-off vaccination (at $0.60 per dose) would be the pre-ferred option. If resource availability increases, providing treatmentis the next point on the expansion path (Table 3c) (or the first pointin EmrD), followed by the combination of one-off vaccination + Rxin all regions except SearD.
One-off vaccination + Rx is the closest intervention to thevery cost-effective threshold in AfrA, AfrE and EmrD. Penta-annualPaps (with waning vaccination + Rx) are the closest to the cost-effectiveness threshold in AfrE and SearD, while in the relativelymore affluent AmrD region, they are closest to the very cost-effective threshold, with penta-annual combinations of PAP andHPV-DNA testing (with waning vaccination + Rx) being closestto the cost-effectiveness threshold. Combinations are not cost-effective in any other region.
In these regions, the low-cost thrice a lifetime VIA interventiontogether with waning vaccination + Rx is not cost-effective in AfrD(despite being on the expansion path) but is cost-effective in AfrE,SearD and (without the waning vaccination) in AfrD. A one-off VIAat age 40 with waning vaccination + Rx is very cost-effective inSearD.
4.2. Sensitivity analysis
Applying age-weights to health effects is controversial [54].Without age weighting but with discounting of future benefits,there is an overall decrease in the cost per DALY averted of the inter-ventions studied here (Appendices A6–A8) Without discounting orage-weighting, cost per DALY is reduced still further. These changesaffect the expansion path in some cases.
The price of the HPV vaccine is currently around $120 per dose[20]. Under the assumption that its price will eventually be around$2.00 per dose, the vaccine still remains the most cost-effectiveintervention in twelve of the regions. However in EmrD and AfrE,
options in terms of the average cost-effectiveness ratio (ACER).A further unknown is long-term vaccine efficacy. We assumed
that the vaccine’s 90% efficacy against the 16/18 genotypes wouldstart to wane at an absolute rate of 2.5% per annum after 10 years.
6 accine
T3aWbab
ppdao
5
cmScmc
Dc
wist
cdadtpcd
twpoaIdtisv
nstsp
orc
dt
Taghreed Adam (WHO/EIP), Martin L. Brown (NIH, Bethesda
068 G.M. Ginsberg et al. / V
his has the effect of increasing the cost per DALY averted by0–50%. In the scenario where the vaccine costs $2.00 per dose andlso has waning efficacy, one-off Pap smears at age 40 in AmrB and
prB, or VIA screening at age 40 in AmrD, EmrD, AfrE and SearDecome most cost-effective options. In AfrE, Pap or VIA screeningt ages 35, 40 and 45 also is more cost-effective than vaccinationy ACER criteria.
Cost effectiveness ratios is insensitive to changes in compliance,articularly in scenarios that include access to treatment and whererogramme operational overheads are low since the increases orecreases in programme efficacy resulting from changes in compli-nce are largely counterbalanced (except for the programme costverheads) by decreases or increases in costs.
. Discussion
Overall, screening or vaccination offer cost-effective or veryost-effective interventions against cervical cancer. Cancer treat-ent also falls on the expansion path of every sub-region.
ince average procedure costs were used, estimates of treatmentosts (and, hence, of costs per DALY averted) may be underesti-ated in regions lacking basic hospital infrastructures for surgical,
hemotherapy and radiotherapy treatments.The relatively high unit price of $11.63 for the reagent HPV-
NA test kit was the main factor in its relative cost-ineffectivenessompared to screening with PAP or VIA once or thrice per life-time.
The effectiveness estimates of vaccination should be viewedith caution as the duration of efficacy and the rate of waning used
n the model are based on assumptions as opposed to empiricaltudies. There may well be a need for booster vaccinations in ordero sustain protective efficacy against HPV.
Clearly vaccine interventions are sensitive to the vaccine unitost. While published vaccine unit costs in June 2006 were $120 perose [20], our model assumed vaccine unit costs of $0.60 or $2.00,s in the past it has not been uncommon to witness instances of 99%ecreases in vaccine unit costs in the years following its introduc-ion (e.g. Hepatitis B vaccination costs). These costs are based onrojections of the future price per dose, representing the economicosts of the vaccination excluding monopolistic rents and vaccineevelopment costs.
The model underestimated the effectiveness of certain interven-ions as no disability weight was attached to persons whose lesionsere removed, while there is clearly both discomfort and pre- andost-removal anxiety. The model could be further improved if datan stage-specific disability weights for cervical cancer were avail-ble. The model assumed 100% compliance with initial screening.n reality compliance (and hence overall reductions in burden ofisease) will be lower, especially in programmes with annual andri-annual screening protocols. Due to the difficulties of estimat-ng compliance over a 45-year period, implying between 15 and 45creening visits, the estimates of compliance used here should beiewed as rough approximations.
The model also underestimated the cost effectiveness of vacci-ation as it does not include the potential disability gains and costavings resulting from a decrease in condyloma (genital warts) ifhe quadravalent vaccine is used [62]. We did not examine whethercreening should be stopped following the advent of vaccinationrogrammes.
We did not consider the option of allowing for early withdrawalf women from screening programmes, since the incremental
esource savings appear not to justify the higher rates of invasiveancer that would occur [63].
The sensitivity and specificity of screening interventions mayiffer both within and between regions, reflecting differences inhe expertise and experience of medical, technical and laboratory
27 (2009) 6060–6079
personnel. Our using sensitivity and specificity values from a devel-oped country (USA) could introduce a source of downward biasin the cost per averted DALY ratios of less developed countries(if sensitivity and specificity are indeed lower). However, we aredescribing an ideal situation where sufficient resources would beavailable to developing countries so that they do attain the samelevel of medical quality that developing countries have, whetherpreventive, diagnostic or curative. It should be noted that sensitiv-ity and specificity data on VIA, which does not require laboratoryfacilities was based on observations in developing countries.
Our estimates of cost effectiveness are also biased upwards (ordownwards) to the extent that transport and costs of work losses ortime costs for treatment exceed (or are exceeded by) the transportand work losses or time costs due to complying with a screeningintervention. A study in the USA indicated that time costs couldaccount for up to 25% of cervical cancer screening costs [64].
Policy analysts at the country level should also be aware of theoption of targeting screening to high-risk populations, when theycan be easily defined, so as to reduce the cost per DALY averted. Tar-geting screening and vaccination of HIV-positive women would beone option [65]. The research presented here could be extended byincluding data on regional age-specific HIV incidence, the percent-age receiving antiretroviral therapy and the relative risks of cervicalcancer by HIV-antiretroviral status.
A key factor in deciding which option or mix of options to adoptwould be estimates of the highest expected attainable rate of cov-erage. In this respect, the ease of reaching 12-year-old girls, themajority of whom are in schools, would indicate that a higher com-pliance is likely to be attained with vaccination than with screeningprogrammes.
Cost-effectiveness models based mainly on developed countries(e.g. USA and Europe) have reported a wide range of incremen-tal costs per life year for some of the cervical cancer screeninginterventions examined in this article, over and above that of treat-ment alone. Major factors contributing to such wide ranges in thepublished estimates are the heterogeneous nature of the modelspecifications regarding effectiveness and wide variation in the esti-mates of the unit costs.
Variations in the duration of operation of screening programmesalso influence the cost per life year reported (usually in an inverserelationship), as do variations in the overhead costs of organisingprogrammes. In our model, the AmrA programme costs accountedfor between 4.9% (HPV-DNA at 35, 40, 45) and 17.1% (Annual PAP) oftotal costs. However in developing regions, these costs accountedfor far higher percentages, ranging, in AfrD for example, from 20.7%(for vaccination at $0.60 per dose) to 64.9% (annual PAP).
Our estimates of the cost utility ratios effectiveness of the incre-mental addition of screening to treatment (when discounted at3% but not age-weighted for comparability with the literature; seeAppendices A6–A8) generally fall towards the lower end of resultsreported elsewhere, in some cases this is because our analysis isbased on actual costs as opposed to prices.
Acknowledgements
The authors are particularly grateful to Jane Kim and Sue Goldieof the Harvard School of Public Health for supplying us with datafrom their model. The authors also wish to thank the followingindividuals for contributing data and/or knowledge to the study:
MD), Inbar Ben-Shahar (Hadassah Hospital, Jerusalem), DanChisholm (WHO/EIP), Peter Heinmann (Essential Health Technolo-gies Medical Research Council, Cape Town). Ben Johns (WHO/EIP),Cedric Mahe (IARC, Lyon), Julia Patnick (NHS Screening Programme,Sheffield), Kenji Shibuya (WHO/EIP).
G.M. Ginsberg et al. / Vaccine 27 (2009) 6060–6079 6069
Table A1Regional reporting categories for Global Burden of Disease 2000 project: WHO regions and 14 subregions.
WHO region Mortality stratum WHO Member States
AFRO D Algeria, Angola, Benin, Burkina Faso, Cameroon, Cape Verde, Chad, Comoros, Equatorial Guinea, Gabon, Gambia, Ghana,Guinea, Guinea-Bissau, Liberia, Madagascar, Mali, Mauritania, Mauritius, Niger, Nigeria, Sao Tome And Principe, Senegal,Seychelles, Sierra Leone, Togo
AFRO E Botswana, Burundi, Central African Republic, Congo, Côte d’Ivoire, Democratic Republic Of The Congo, Eritrea, Ethiopia, Kenya,Lesotho, Malawi, Mozambique, Namibia, Rwanda, South Africa, Swaziland, Uganda, United Republic of Tanzania, Zambia,Zimbabwe
AMRO A Canada, United States Of America, CubaAMRO B Antigua and Barbuda, Argentina, Bahamas, Barbados, Belize, Brazil, Chile, Colombia, Costa Rica, Dominica, Dominican
Republic, El Salvador, Grenada, Guyana, Honduras, Jamaica, Mexico, Panama, Paraguay, Saint Kitts And Nevis, Saint Lucia, SaintVincent And The Grenadines, Suriname, Trinidad and Tobago, Uruguay, Venezuela
AMRO D Bolivia, Ecuador, Guatemala, Haiti, Nicaragua, PeruEMRO B Bahrain, Cyprus, Iran (Islamic Republic Of), Jordan, Kuwait, Lebanon, Libyan Arab Jamahiriya, Oman, Qatar, Saudi Arabia, Syrian
Arab Republic, Tunisia, United Arab EmiratesEMRO D Afghanistan, Djibouti, Egypt, Iraq, Morocco, Pakistan, Somalia, Sudan, YemenEURO A Andorra, Austria, Belgium, Croatia, Czech Republic, Denmark, Finland, France, Germany, Greece, Iceland, Ireland, Israel, Italy,
Luxembourg, Malta, Monaco, Netherlands, Norway, Portugal, San Marino, Slovenia, Spain, Sweden, Switzerland, UnitedKingdom
EURO B Albania, Armenia, Azerbaijan, Bosnia and Herzegovina, Bulgaria, Georgia, Kyrgyzstan, Poland, Romania, Slovakia, Tajikistan,The Former Yugoslav Republic Of Macedonia, Turkey, Turkmenistan, Uzbekistan, Yugoslavia
EURO C Belarus, Estonia, Hungary, Kazakhstan, Latvia, Lithuania, Republic of Moldova, Russian Federation, UkraineSEARO B Indonesia, Sri Lanka, ThailandSEARO D Bangladesh, Bhutan, Democratic People’s Republic Of Korea, India, Maldives, Myanmar, NepalWPRO A Australia, Japan, Brunei Darussalam, New Zealand, SingaporeWPRO B Cambodia, China, Lao People’s Democratic Republic, Malaysia, Mongolia, Philippines, Republic Of Korea, Viet NamWPRO C* Cook Islands, Fiji, Kiribati, Marshall Islands, Micronesia (Federated States Of), Nauru, Niue, Palau, Papua New Guinea, Samoa,
a) Source: WHO data. (b) Source: Global Burden of Disease Data. (c) Based on meta-analyith non-16/18 genotypes.
able A3ost per DALY averted ($I) by intervention (’A’ regions).
Age weighted and discounted at 3% per annum)
AP smears (a)nnual (20–65) PAP (1, 20, 65)ri-annual (20–65) PAP (3, 20, 65)enta-annual (20–65) PAP (5, 20, 65)t 35, 40, 45 years of age PAP (5, 35, 45)t 40 years of age PAP (40)
AP then PAP/HPV-DNA (a)nnual PAP (20–29), PAP and HPV (30–65) COM (1, 20, 65)ri-annual PAP (20–29), PAP and HPV (30–65) COM (3, 20, 65)enta-annual PAP (20–29), PAP and HPV (30–65) COM (5, 20, 65)
PV-DNA tests (a)t 35, 40, 45 years of age HPV (5, 35, 45)t 40 years of age HPV (40)
IA (a)t 35, 40, 45 years of age VIA (5, 35, 45)t 40 years of age VIA (40)
PV vaccination at age 12t $0.60 per dose Vac $0.60t $2.00 per dose Vac $2.00t $0.60 per dose with waning immunity Wan Vac $0.60t $2.00 per dose with waning immunity Wan Vac $2.00
reatment (Rx) of invasive cancer Rx
AP smears (a) + Rxnnual (20–65) PAP (1, 20, 65) + Rxri-annual (20–65) PAP (3, 20, 65) + Rxenta-annual (20–65) PAP (5, 20, 65) + Rxt 35, 40, 45 years of age PAP (5, 35, 45) + Rxt 40 years of age PAP (40) + Rx
AP then PAP/HPV-DNA (a) + Rxnnual PAP (20–29), PAP and HPV (30–65) COM (1, 20, 65) + Rxri-annual PAP (20–29), PAP and HPV (30–65) COM (3, 20, 65) + Rxenta-annual PAP (20–29), PAP and HPV (30–65) COM (5, 20, 65) + Rx
PV tests (a) + Rxt 35, 40, 45 years of age HPV (5, 35, 45) + Rxt 40 years of age HPV (40) + Rx
IA (a) + Rxt 35, 40, 45 years of age VIA (5, 35, 45) + Rxt 40 years of age VIA (40) + Rx
PV vaccination at age 12 m + Rxt $0.60 per dose Vac $0.60 + Rxt $2.00 per dose Vac $2.00 + Rxt $0.60 per dose with waning immunity Wan Vac $0.60 + Rxt $2.00 per dose with waning immunity Wan Vac $2.00 + Rx
PV vaccine + PAP smearsnnual (20–65) PAP (1, 20, 65) + Vacri-annual (20–65) PAP (3, 20, 65) + Vacenta-annual (20–65) PAP (5, 20, 65) + Vac
sis of literature [26,45–47]. (d) Assumes 6.5% are caused by 16 and/or 18 together
G.M. Ginsberg et al. / Vaccine 27 (2009) 6060–6079 6071
Table A3 (Continued)
(Age weighted and discounted at 3% per annum)
AMRA WPRA EURA
At 35, 40, 45 years of age PAP (5, 35, 45) + Vac 2,368** 4,882** 4,319**At 40 years of age PAP (40) + Vac 1,280** 3,087** 2,708**
HPV vaccine (b) + PAP then PAP/HPV (a)Annual PAP (20–29), PAP and HPV (30–65) COM (1, 20, 65) + Vac 20,514** 42,686* 35,327*Tri-annual PAP (20–29), PAP and HPV (30–65) COM (3, 20, 65) + Vac 10,218** 20,590** 17,111**Penta-annual PAP (20–29), PAP and HPV (30–65) COM (5, 20, 65) + Vac 6,889** 13,953** 11,597**
HPV vaccine (b)** + HPV-DNA tests (a)At 35, 40, 45 years of age HPV (5, 35, 45) + Vac 4,402** 9,540** 7,718**At 40 years of age HPV (40) + Vac 2,262** 5,352** 4,387**
HPV Vaccine (b) + VIA (a)At 35, 40, 45 years of age VIA (5, 35, 45) + Vac 4,584** 9,934** 8,023**At 40 years of age VIA (40) + Vac 1,711** 3,917** 3,379**
HPV vaccine (b) + PAP smears (a) + RxAnnual (20–65) PAP (1, 20, 65) + Vac + Rx 4,831** 7,513** 7,603**Tri-annual (20–65) PAP (3, 20, 65) + Vac + Rx 3,049** 4,533** 4,487**Penta-annual (20–65) PAP (5, 20, 65) + Vac + Rx 2,311** 3,347** 3,313**At 35, 40, 45 years of age PAP (5, 35, 45) + Vac + Rx 1,535** 2,033** 2,065**At 40 years of age PAP (40) + Vac + Rx 1,242** 1,552** 1,572**
HPV vaccine (b) + PAP then PAP/HPV-DNA (a) + RxAnnual PAP (20–29), PAP and HPV (30–65) COM (1, 20, 65) + Vac + Rx 8,700** 14,552** 13,480**Tri-annual PAP (20–29), PAP and HPV (30–65) COM (3, 20, 65) + Vac + Rx 4,537** 7,188** 6,735**Penta-annual PAP (20–29), PAP and HPV (30–65) COM (5, 20, 65) + Vac + Rx 3,185** 4,938** 4,654**
HPV vaccine (b) + HPV-DNA tests (a) + RxAt 35, 40, 45 years of age HPV (5, 35, 45) + Vac + Rx 2,169** 3,133** 3,006**At 40 years of age HPV (40) + Vac + Rx 1,494** 1,980** 1,966**
HPV vaccine (b) + VIA (a) + RxAt 35, 40, 45 years of age VIA (5, 35, 45) + Vac + Rx 1,823** 2,456** 2,470**At 40 years of age VIA (40) + Vac + Rx 1,351** 1,711** 1,731**GDP (I$) per Capita 31,477 27,534 23,927C
KS
TC
(
PPPPPP
PCCC
HHH
VVV
HVVWW
R
PPPPP
urrent Scenario Current
ey: *intervention is cost-effective. **intervention is very cost-effective. (a) Including remcreening by YYY, every x years from age 20 until age 65; COM (x, 20, 65) PAP every x yea
able A4ost per DALY averted ($I) by intervention (‘B’ and ‘C’ regions).
Key: *intervention is cost-effective. **Intervention is very cost-effective. (a) Including removal of lesions. (b) With waning immunity costing $0.60 per dose. YYY (x, 20, 65).Screening by YYY, every x years from age 20 until age 65. COM (x, 20, 65) PAP every x years from 20 to 29, then PAP and HPV-DNA every x years until age 65.
Table A5Cost per DALY averted ($I) by intervention (‘D’ and ‘E’ regions).
Key: *intervention is cost-effective. **Intervention is very cost-effective. (a) Including removal of lesions. (b) With waning immunity costing $0.60 per dose. YYY (x, 20, 65).Screening by YYY, every x years from age 20 until age 65. COM (x, 20, 65) PAP every x years from 20 to 29, then PAP and HPV-DNA every x years until age 65.
6074 G.M. Ginsberg et al. / Vaccine 27 (2009) 6060–6079
Table A6Cost per DALY averted ($I) by intervention (‘A’ regions).
(Discounted at 3% per annum)
AmrA WprA EurA
PAP smears (a) PAP smears (a)Annual (20–65) PAP (1, 20, 65) 9,071** 14,699** 15,031**Tri-annual (20–65) PAP (3, 20, 65) 5,457** 8,559** 8,558**Penta-annual (20–65) PAP (5, 20, 65) 4,021** 6,243** 6,269**At 35, 40, 45 years of age PAP (5, 35, 45) 1,768** 2,515** 2,720**At 40 years of age PAP (40) 1,267** 1,763** 2,095**
PAP then PAP/HPV-DNA (a) PAP then PAP/HPV-DNA (a)Annual PAP (20–29), PAP and HPV (30–65) COM (1, 20, 65) 16,320** 28,032* 25,971*Tri-annual PAP (20–29), PAP and HPV (30–65) COM (3, 20, 65) 8,230** 13,515** 12,606**Penta-annual PAP (20–29), PAP and HPV (30–65) COM (5, 20, 65) 5,728** 9,269** 8,733**
HPV tests (a) HPV tests (a)At 35, 40, 45 years of age HPV (5, 35, 45) 3,125** 4,839** 4,704**At 40 years of age HPV (40) 2,080** 3,041** 3,302**VIA (a) VIA (a)At 35, 40, 45 years of age VIA (5, 35, 45) 2,365** 3,377** 3,538**At 40 years of age VIA (40) 1,596** 2,173** 2,491**
HPV Vaccination at age 12 HPV Vaccination at age 12At $0.60 per dose Vac $0.60 127** 540** 447**At $2.00 per dose Vac $2.00 282** 834** 651**At $0.60 per dose with waning immunity Wan Vac $0.60 197** 970** 756**At $2.00 per dose with waning immunity Wan Vac $2.00 438** 1,497** 1,103**
Treatment (Rx) of invasive cancer Rx 839** 804** 836**
PAP smears (a) + Rx PAP smears (a) + RxAnnual (20–65) PAP (1, 20, 65) + Rx 4,091** 5,666** 6,012**Tri-annual (20–65) PAP (3, 20, 65) + Rx 2,608** 3,409** 3,542**Penta-annual (20–65) PAP (5, 20, 65) + Rx 2,033** 2,544** 2,643**At 35, 40, 45 years of age PAP (5, 35, 45) + Rx 1,340** 1,489** 1,589**At 40 years of age PAP (40) + Rx 1,207** 1,220** 1,310**
PAP then PAP/HPV-DNA (a) + Rx PAP then PAP/HPV-DNA (a) + RxAnnual PAP (20–29), PAP and HPV (30–65) COM (1, 20, 65) + Rx 7,158** 10,644** 10,314**Tri-annual PAP (20–29), PAP and HPV (30–65) COM (3, 20, 65) + Rx 3,767** 5,261** 5,152**Penta-annual PAP (20–29), PAP and HPV (30–65) COM (5, 20, 65) + Rx 2,699** 3,648** 3,600**
HPV-DNA tests (a) + Rx HPV-DNA tests (a) + RxAt 35, 40, 45 years of age HPV (5, 35, 45) + Rx 1,813** 2,231** 2,252**At 40 years of age HPV (40) + Rx 1,389** 1,504** 1,582**
VIA (a) + Rx VIA (a) + RxAt 35, 40, 45 years of age VIA (5, 35, 45) + Rx 1,547** 1,762** 1,860**At 40 years of age VIA (40) + Rx 1,279** 1,317** 1,412**
HPV Vaccination at age 12 m + Rx HPV Vaccination at age 12 m + RxAt $0.60 per dose Vac $0.60 + Rx 1,044** 1,148** 1,100**At $2.00 per dose Vac $2.00 + Rx 1,090** 1,204** 1,153**At $0.60 per dose with waning immunity Wan Vac $0.60 + Rx 1,172** 1,255** 1,231**At $2.00 per dose with waning immunity Wan Vac $2.00 + Rx 1,221** 1,315** 1,288**
HPV Vaccine + PAP smears HPV Vaccine + PAP smearsAnnual (20–65) PAP (1, 20, 65) + Vac 9,657** 17,261** 16,282**Tri-annual (20–65) PAP (3, 20, 65) + Vac 5,709** 10,073** 9,249**Penta-annual (20–65) PAP (5, 20, 65) + Vac 4,017** 7,191** 6,556**At 35, 40, 45 years of age PAP (5, 35, 45) + Vac 2,071** 3,866** 3,588**At 40 years of age PAP (40) + Vac 1,144** 2,498** 2,297**
HPV Vaccine (b) + PAP then PAP/HPV-DNA (a) HPV Vaccine (b) + PAP then PAP/HPV-DNA (a)Annual PAP (20–29), PAP and HPV (30–65) COM (1, 20, 65) + Vac 18,015** 34,059* 29,325*Tri-annual PAP (20–29), PAP and HPV (30–65) COM (3, 20, 65) + Vac 8,950** 16,361** 14,169**Penta-annual PAP (20–29), PAP and HPV (30–65) COM (5, 20, 65) + Vac 6,022** 11,043** 9,577**
HPV Vaccine (b)** + HPV-DNA tests (a) HPV Vaccine (b)** + HPV-DNA tests (a)At 35, 40, 45 years of age HPV (5, 35, 45) + Vac 3,836** 7,533** 6,391**At 40 years of age HPV (40) + Vac 2,008** 4,294** 3,693**
HPV vaccine (b) + VIA (a) HPV vaccine (b) + VIA (a)At 35, 40, 45 years of age VIA (5, 35, 45) + Vac 3,998** 7,849** 6,649**At 40 years of age VIA (40) + Vac 1,522** 3,150** 2,850**
HPV vaccine (b) + PAP smears (a) + Rx HPV vaccine (b) + PAP smears (a) + RxAnnual (20–65) PAP (1, 20, 65) + Vac + Rx 4,487** 6,401** 6,606**Tri-annual (20–65) PAP (3, 20, 65) + Vac + Rx 2,837** 3,867** 3,903**Penta-annual (20–65) PAP (5, 20, 65) + Vac + Rx 2,158** 2,861** 2,888**At 35, 40, 45 years of age PAP (5, 35, 45) + Vac + Rx 1,445** 1,753** 1,813**At 40 years of age PAP (40) + Vac + Rx 1,183** 1,352** 1,394**
G.M. Ginsberg et al. / Vaccine 27 (2009) 6060–6079 6075
Table A6 (Continued)
(Discounted at 3% per annum)
AmrA WprA EurA
HPV Vaccine (b) + PAP then PAP/HPV-DNA (a) + Rx HPV Vaccine (b) + PAP then PAP/HPV-DNA (a) + RxAnnual PAP (20–29), PAP and HPV (30–65) COM (1, 20, 65) + Vac + Rx 8,078** 12,382** 11,696**Tri-annual PAP (20–29), PAP and HPV (30–65) COM (3, 20, 65) + Vac + Rx 4,213** 6,116** 5,844**Penta-annual PAP (20–29), PAP and HPV (30–65) COM (5, 20, 65) + Vac + Rx 2,961** 4,204** 4,041**
HPV vaccine (b) + HPV-DNA tests (a) + Rx HPV vaccine (b) + HPV-DNA tests (a) + RxAt 35, 40, 45 years of age HPV (5, 35, 45) + Vac + Rx 2,036** 2,695** 2,634**At 40 years of age HPV (40) + Vac + Rx 1,419** 1,721** 1,739**
HPV vaccine (b) + VIA (a) + Rx HPV vaccine (b) + VIA (a) + RxAt 35, 40, 45 years of age VIA (5, 35, 45) + Vac + Rx 1,712** 2,114** 2,165**At 40 years of age VIA (40) + Vac + Rx 1,284** 1,489** 1,532**GDP (I$) per capita GDP (I$) per capita 31,477 27,534 23,927Current scenario Current 4,016** 3,505** 3,926**
Key: *intervention is cost-effective. **Intervention is very cost-effective. (a) Including removal of lesions. (b) With waning immunity costing $0.60 per dose. YYY (x, 20, 65).Screening by YYY, every x years from age 20 until age 65. COM (x, 20, 65) PAP every x years from 20 to 29, then PAP and HPV every x years until age 65.
Table A7Cost per DALY averted ($I) by intervention (‘B’ and ‘C’ regions).
Key: *intervention is cost-effective. **Intervention is very cost-effective. (a) Including removal of lesions. (b) With waning immunity costing $0.60 per dose. YYY (x, 20, 65).Screening by YYY, every x years from age 20 until age 65. COM (x, 20, 65) PAP every x years from 20 to 29, then PAP and HPV every x years until age 65.
Table A8Cost per DALY averted ($I) by intervention (‘D’ and ‘E’ regions).
ey: *intervention is cost-effective. **Intervention is very cost-effective. (a) Includincreening by YYY, every x years from age 20 until age 65. COM (x, 20, 65) PAP every
ppendix A.
See Tables A1–A8.
eferences
[1] WHO. The world health report 2004—changing history. Geneva: WHO; 2002.
1,576 1,449 1,3815,047 515** 21,970
oval of lesions. (b) With waning immunity costing $0.60 per dose. YYY (x, 20, 65).s from 20 to 29, then PAP and HPV every x years until age 65.
[2] Yang BH, Bray FI, Parkin DM, Selloprs JW, Zhang Z-F. Cervical cancer as a priorityfor prevention in different world regions: an evaluation using years of life lost.Int J Cancer 2004;109:418–24.
[3] Symonds RP. Beatson Oncology Centre, Western Infirmary, Glasgow, UK. Screen-ing for cervical cancer: different problems in the developing and the developedworld. Eur J Cancer Care (Engl) 1997;6(December(4)):275–9.
[4] Gustafsson L, Ponten J, Zack M, Adami HO. International incidence rates of inva-sive cervical cancer after introduction of cytological screening. Cancer CausesContr 1997;8:755–63.
6 accine
[
[
[
[
[
[
[
[
[
[
[
[
[
[
[
[
[
[
[
[
[
[[
[
[
[
[
[
[
[
[
[
[
[
[
[
[
[
[
[
[
[
[
[
[
[
[
[
[
[[
[
078 G.M. Ginsberg et al. / V
[5] Murray CJ, Lauer JA, Hutubessy RC, Niessen L, Tomijima N, Rodgers A, et al.Effectiveness and costs of interventions to lower systolic blood pressure andcholesterol: a global and regional analysis on reduction of cardiovascular-disease risk. Lancet 2003;361:717–25.
[6] WHO-CHOICE. Choosing interventions that are cost effective, http://www3.who.int/whosis/menu.cfm?path=whosis,ceaandlanguage=english.
[7] Johns B, Baltussen R, Hutubessy R. Programme costs in the economic evaluationof health interventions. Cost Eff Resour Alloc 2003;26(February (1)):1.
[8] Adam T, Evans DB, Murray CJ. Econometric estimation of country-specific hos-pital costs. Cost Eff Resour Alloc 2003;1(February (1)):3.
[9] Adam T, Koomanchap MA. Cost-effectiveness analysis: can we reduce variabilityin costing methods? Int J Tech Assess Health Care 2002;19:407–20.
10] World Health Organization. Tan-Torres Edejer, T, Baltussen R, Adam T, et al.,editors. Making choices in health: WHO guide to cost-effectiveness analysis.WHO: Geneva; 2003.
11] Murray CJ, Evans DB, Acharya A, Baltussen RM. Development of WHO guidelineson generalized cost-effectiveness analysis. Health Econ 2000;9:235–51.
12] Hutubessy RC, Baltussen RM, Torres-Edejer TT, Evans DB. Generalised cost-effectiveness analysis: an aid to decision making in health. Appl Health EconHealth Policy 2002;1:89–95.
13] Baltussen RM, Hutubessy RC, Evans DB, Murray CJ. Uncertainty in cost-effectiveness analysis. Probabilistic uncertainty analysis and stochastic leaguetables. Int J Technol Assess Health Care 2002;18:112–9.
14] Baltussen R, Adam T, Tan-Torres Edejer T, Hutubessy R, Acharya A, Evans DB,et al. What is Generalised Cost-Effectiveness Analysis? In: Tan-Torres Edejer T,Bltussen R, Adam T, Hutubessy R, Acharya A, Evans DB, et al., editors. Makingchoices in health. WHO guide to cost-effectiveness analysis. Geneva: WHO;2003 [chapter 1].
15] WHO. The World Health Report 2002. Reducing risks, promoting healthy life.Geneva: WHO; 2002.
16] Goldie SJ, Khun L, Denny L, Pollack A, Wright TC. Policy analysis ofcervical cancer screening strategies in low-resource settings: clinical bene-fits and cost-effectiveness. JAMA 2001;285(24):3107–15 [Erratum in: JAMA2001:286(9);1026].
17] Goldie SJ, Grima D, Kohli M, Wright TC, Weinstein M, Franco E. A com-prehensive natural history model of HPV infection and cervical cancer toestimate the clinical impact of a prophylactic HPV-16/18 vaccine. Int J Cancer2003;106(6):896–904.
18] Kim JJ, Wright TC, Goldie SJ. Cost-effectiveness of alternative triage strate-gies for atypical squamous cells of undetermined significance. JAMA2002;287:2382–90.
19] Goldie SJ, Gaffikin L, Goldhaber-Fiebert JD, Gordillo-Tobar A, Levin C, Mahe C, etal. Cost-effectiveness of cervical cancer screening in five developing countries.N Engl J Med 2005;353:2158–68.
20] U.S. Approves use of vaccine for cervical cancer by Gardiner Harris. New YorkTimes. June 9th 2006.
21] Harro CD, Pang YYS, Roden RBS, Hildenstein A, Wang Z, Reynolds MJ, et al. Safetyand immunogenicity trial in adult volunteers of a human papillomavirus 16 L1virus-like particle vaccine. J Natl Cancer Inst 2001;93:284–92.
22] Koutsky IA, Ault KA, Wheeler CM, Brown DR, Barr E, Alvarez FB, et al. A controlledtrial of a human papilomavirus type 16 vaccine. N Engl J Med 2002;347:1645–51.
23] Franco EL, Harper DM. Vaccination against human papillomavirus infection: anew paradigm in cervical cancer control. Vaccine 2005;23:2388–94.
24] Harper DM, Franco EL, Wheeler C, Moscicki AB, Bomanowski B, Roteli-MartinsCM, et al. Efficacy of a bivalent L1 virus-like particle vaccine in preventionof infection with human papillomavirus types 16 and 18 in young women: arandomized controlled trial. Lancet 2004;364:1757–65.
25] Villa LL, Costa LR, Petta CA, Andrade RP, Paavonen J, Iversen OE, et al. Prophy-lactic quadrivalent human papillomavirus (types 6, 11, 16 and 18) L1 virus-likeparticle vaccine in young womeb: a randomized double-blind placebo-controlled multicentre phase Ii efficacy trial. Lancet Oncol 2005;6:271–8.
26] Munoz N, Bosch FX, Castellsague X, Diaz M, de Sanjose S, Hammouda D, et al.Against which human papillomavirus types shall we vaccinate and screen? Theinternational perspective. Int J Cancer 2004;111:278–85.
27] Munoz N, Bosch FX, de Sanjose S, Herrera R, Castellsague X, Shah KV. Epidemi-ologic classification of human papillomavirus types associated with cervicalcancer. N Engl J Med 2003;348:518–27.
28] Schiffman MH, Bauer HM, Hoover RN, Glass AG, Cadell DM, Rush BB. Epidemi-ologic evidence showing that human papillomavirus infection causes mostcervical intraepithelial neoplasma. J Natl Cancer Inst 1993;85:958–64.
29] Munoz N. Human papillomavirus and cancer: the epidemiological evidence. JClin Virol 2000;19:1–5.
30] The State of the World’s Children 2005: Childhood under threat. United NationsChildren’s Fund (UNICEF). New York: Oxford University Press; 2004.
31] Waggoner SE. Cervical cancer. Lancet 2003;361:2217–25.32] National Cancer Institute Recommendations: US National Institute of Health
33] Benedet JL, Odicino F, Maisonneuve P, Beller U, Creasman WT, Heintz AP. Carci-noma of the cervix uteri. J Epidemiol Biostatist 2001;6(1) [European data from
1993–1995].
34] Rose PG, Blessing JA, Gershenson DM, McGehee R. Paclitaxel and cisplatin asfirst-line therapy in recurrent or advanced squamous cell carcinoma of thecervix: a gynecologic oncology group study. J Clin Oncol 1999;17(9):2676–80.
35] Burnett AF, Roman LD, Garcia AA, Muderspach LI, Brader KR, Morrow CP. Aphase II study of gemcitabine and cisplatin in patients with advanced, per-
[
27 (2009) 6060–6079
sistent, or recurrent squamous cell carcinoma of the cervix. Gynecol Oncol2000;76(1):63–6.
36] Cancer Care Center. Cancer overviews. http//www.cancercarecenter.org[accessed 25.05.05].
37] Benedet JL, Odicino F, Maisonneuve P, Beller U, Creasman WT, Heinz AP. Carci-noma of the cervix uteri. J Epidemiol Biostatist 2001;6(1):5–44.
38] van Nagell Jr JR, Rayburn W, Donaldson ES, et al. Therapeutic implicationsof patterns of recurrence in cancer of th euterine cervix. Cancer 1979;44:2354–61.
39] Carcinoma of the cervix and tobacco smoking: Collaborative reanalysis of indi-vidual data on 13,541 women with carcinoma of the cervix and 23, 017 womenwithout carcinoma of the cervix from 23 epidemiological studies. Int J Cancer2006; 118:1481–95.
40] Sobti RC, Kaur S, Kaor P, et al. Interaction of passive smoking with GST (GSTM1,GSTT1 and GSTP1) genotypes in the risk of cervical cancer in India. Cancer GenetCytogenet 2006;166:117–23.
41] Slaymaker F, Walker N, Zaba B, Collumbien M. Unsafe sex. In: Ezatti M, LopezAD, Rodgers A, Murray CJL, editors. Comparative quantification of health risks:global and regional burden of disease attributable to selected major risk factors.Geneva: World Health Organization; 2004. p. 1177–254.
42] Eichholzer M, Luthy J, Moser U, Fowler B. Folate and the risk of colorectal,breast and cervix cancer: the epidemiological evidence. Swiss Med Weekly2001;131:539–49.
43] Goldie SJ, Kim JJ, Wright TC. Cost-effectiveness of human papillomavirus DNAtesting for cervical cancer screening in women aged 30 years or more. ObstetGynecol 2004;103:619–31.
44] Goldie SJ, Kohli M, Grima D, Weinstein MC, Wright TC, Bosch FX, et al. Projectedclinical benefits and cost-effectiveness of a human papilomavirus 16/18 vaccine.J Natl Cancer Inst 2004;96:604–15.
45] Clifford GM, Smith JS, Plummer M, Munoz N, Franceschi S. Human papillo-mavirus types in invasive cervical cancer worldwide: a meta-analysis. Br JCancer 2003;88:63–73.
46] Lo KWK, Wong YF, Chan MKM, Li JC, Poon JS, Wang VW. Prevalence of humanpapillomavirus in cervical cancer: a multicenter study in China. Int J Cancer2002;100:327–31.
47] Franceschi S, Rajkumar T, Vaccarella S, Gajalakshni V, Sharmila A, Snidjers PJ, etal. Human papillomavirus and risk factors for cervical cancer in Chennai, India:a case–control study. Int J Cancer 2003:127–33.
48] Mathers CD, Shibuya K, Boschi-Pinto C, Lopez AD, Murray CJL. Global andregional estimates of cancer mortality and incidence by site: 1. Applicationof regional cancer survival model to estimate cancer mortality distribution bysite. BMC Cancer 2002;2:36.
49] Shibuya K, Mathers CD, Boschi-Pinto C, Lopez AD, Murray CJ. Global and regionalestimates of cancer mortality and incidence by site. II. Results for the globalburden of disease 2000. BMC Cancer 2002;2:37.
50] Green J, Kirwan J, Tierney J, Vale C, Symonds P, Fresco L, et al. Concomi-tant chemotherapy and radiation therapy for cancer of the uterine cervix. TheCochrane Database of Systematic Reviews 2005, Issue 3. Art. No.: CD002225.DOI: 10.1002/14651858.CD002225.
51] Lauer JA, Murray CJL, Roehrich K, Wirth H. PopMod: a longitudinal popula-tion model with two interacting disease states. Cost Effect Resource Allocat2003;1:6, www.resource-allocation.com.
52] Blackman DK, Bennett EM, Miller DS. Trends in self-reported use ofmammograms (1989–1997) and Papanicolaou tests (1991–1997)—behavioralRisk Factor Surveillance System. MMWR CDC Surveill Summ 1999;48:1–22.
53] Statistics Canada. The Canadian Community Health Survey Cycle 2002, 1.1Ottawa.
54] Quickstats. Percentage of US and Canadian women aged 50–69 who werescreened in accordance with National Guidelines for Papanicolai (Pap) testsand Mammograms by country and health insurance status 2002–2003. MMWRSept 9th 2005:54;879.
55] Cervix Cancer screening/IARC Working Group on the Evaluation of Cancer Pre-vention Strategies 2004: Lyon, France (IARC Handbooks of Cancer Prevention;10).
56] A situational analysis of cervical cancer in Latin American and the Caribbean.Washington D.C.: PAHO; 2004.
57] Baltussen R, Adam T, Tan-Torres Edejer T, Hutubessy R, Acharya A, EvansDB, et al. Chapter 4. Health effects. In: Tan-Torres Edejer T, BltussenR, Adam T, Hutubessy R, Acharya A, Evans DB, et al., editors. Makingchoices in health. WHO guide to cost-effectiveness analysis. Geneva: WHO;2003.
58] Report by the Comptroller and Auditor general. NHS Executive. The Perfor-mance of the NHS Cervical Screening Programme in England. HC 678 Session1997–98, 22nd April 1998.
59] International Drug Price Indicator Guide. Arlington (VI): MSH; 2003.60] British National Formulary No 47, March 2004. Published by the British Medi-
cal Association, London and the Royal Pharmaceutical Society of Great Britain,London.
61] WHO Commission on MacroEconomics and Health. Macroeconomics and
health: investing in health for economic development. Report of the com-mission on Macroeconomics and health. Geneva: World Health Organization;2001.
62] Bosch FX, Manos MM, Munoz N, Sherman M, Jansen AM, Peto J, et al. Prevalenceof human papillomavirus in cervical cancer: a worldwide perspective. J NatlCancer Inst 1995;87(11):796–802.
63] Philips Z, Whynes DK. Early withdrawal from cervical cancer screening: thequestion of cost-effectiveness. Eur J Cancer 2001:1775–80.
64] Shireman TI, Tsevat J, Goldie SJ. Time costs associated with cervical cancerscreening. Int J Tech Assess in Health Care 1991;17:146–52.
[
27 (2009) 6060–6079 6079
65] Clifford GM, Polesel J, Rickenbach M, Dal Maso L, Keiser O, Kofler A, et al. Can-cer risk in the Swiss HIV Cohort Study: associations with immunodeficiency,smoking and highly active antiretroviral therapy. J Natl Cancer Inst 2005;97:425–32.
