Background: Screening and vaccination against human papillomavirus (HPV) can protect against cervical cancer. Neither alone can provide 100% protection. Consequently it raises the important question about the most efficient combination of screening at specified time intervals and vaccination to prevent cervical cancer.
Objective: Our objective was to identify the mix of cervical cancer prevention strategies (screening and/or vaccination against HPV) that achieves maximum reduction in cancer cases within a fixed budget.
Methods: We assessed the optimal mix of strategies for the prevention of cervical cancer using an optimization program. The evaluation used two models. One was a Markov cohort model used as the evaluation model to estimate the costs and outcomes of 52 different prevention strategies. The other was an optimization model in which the results of each prevention strategy of the previous model were entered as input data. The latter model determined the combination of the different prevention options to minimize cervical cancer under budget, screening coverage and vaccination coverage constraints.
We applied the model in two countries with different healthcare organizations, epidemiology, screening practices, resource settings and treatment costs: the UK and Brazil. 100 000 women aged 12 years and above across the whole population over a 1-year period at steady state were included.
The intervention was papanicolaou (Pap) smear screening programmes and/or vaccination against HPV with the bivalent HPV 16/18 vaccine (Cervarix® [Cervarix is a registered trademark of the GlaxoSmithKline group of companies]). The main outcome measures were optimal distribution of the population between different interventions (screening, vaccination, screening plus vaccination and no screening or vaccination) with the resulting number of cervical cancer and associated costs.
Results: In the base-case analysis (= same budget as today), the optimal prevention strategy would be, after introducing vaccination with a coverage rate of 80% in girls aged 12 years and retaining screening coverage at pre-vaccination levels (65% in the UK, 50% in Brazil), to increase the screening interval to 6 years (from 3) in the UK and to 5 years (from 3) in Brazil. This would result in a reduction of cervical cancer by 41% in the UK and by 54% in Brazil from pre-vaccination levels with no budget increase. Sensitivity analysis shows that vaccination alone at 80% coverage with no screening would achieve a cervical cancer reduction rate of 20% in the UK and 43% in Brazil compared with the pre-vaccination situation with a budget reduction of 30% and 14%, respectively. In both countries, the sharp reduction in cervical cancer is seen when the vaccine coverage rate exceeds the maximum screening coverage rate, or when screening coverage rate exceeds the maximum vaccine coverage rate, while maintaining the budget. As with any model, there are limitations to the value of predictions depending upon the assumptions made in each model.
Conclusions: Spending the same budget that was used for screening and treatment of cervical cancer in the pre-vaccination era, results of the optimization program show that it would be possible to substantially reduce the number of cases by implementing an optimal combination of HPV vaccination (80% coverage) and screening at pre-vaccination coverage (65% UK, 50% Brazil) while extending the screening interval to every 6 years in the UK and 5 years in Brazil.
Ferlay J, Shin HR, Bray F, et al. GLOBOCAN 2008: cancer incidence, mortality and prevalence worldwide in 2008 [online]. Available from URL: http://globocan.iarc.fr [Accessed 2010 Jun 22]Google Scholar
Antilla A, Aoki D, Arbyn M, et al. Cervix cancer screening. Lyon: IARC Press, 2005. Report no.: 10Google Scholar
Arbyn M, Raifu AO, Autier P, et al. Burden of cervical cancer in Europe: estimates for 2004. Ann Oncol 2007 Apr 10; 18 (10): 1708–15PubMedCrossRefGoogle Scholar
Denny L, Quinn M, Sankaranarayanan R. Chapter 8: screening for cervical cancer in developing countries. Vaccine 2006 Aug 31; 24 Suppl. 3: S3/71–7CrossRefGoogle Scholar
Walboomers JM, Jacobs MV, Manos MM, et al. Human papillomavirus is a necessary cause of invasive cervical cancer worldwide. J Pathol 1999; 189 (1): 12–9PubMedCrossRefGoogle Scholar
zur Hausen H. Intracellular surveillance of persisting viral infections: human genital cancer results from deficient cellular control of papillomavirus gene expression. Lancet 1986 Aug 30; 328 (8505): 489–91CrossRefGoogle Scholar
Smith JS, Lindsay L, Hoots B, et al. Human papillomavirus type distribution in invasive cervical cancer and high-grade cervical lesions: a meta-analysis update. Int J Cancer 2007 Apr 2; 121 (3): 621–32PubMedCrossRefGoogle Scholar
Munoz N, Castellsague X, de Gonzalez AB, et al. HPV in the etiology of human cancer. Vaccine 2006 Jun 23; 24 Suppl. 3: S1–10CrossRefGoogle Scholar
Paavonen J, Naud P, Salmerón J, et al. Efficacy of human papillomavirus (HPV)-16/18 AS04-adjuvanted vaccine against cervical infection and precancer caused by oncogenic HPV types (PATRICIA): final analysis of a doubleblind, randomised study in young women. Lancet 2009 Jul 25; 374 (9686): 301–14PubMedCrossRefGoogle Scholar
Villa LL, Costa RL, Petta CA, et al. High sustained efficacy of a prophylactic quadrivalent human papillomavirus types 6/11/16/18 L1 virus-like particle vaccine through 5 years of follow-up. Br J Cancer 2006 Dec 4; 95 (11): 1459–66PubMedCrossRefGoogle Scholar
FUTURE II Study Group. Quadrivalent vaccine against human papillomavirus to prevent high-grade cervical lesions. N Engl J Med 2007 May 10; 356 (19): 1915–27Google Scholar
Garland SM, Hernandez-Avila M, Wheeler CM, et al. Quadrivalent vaccine against human papillomavirus to prevent anogenital diseases. N Engl J Med 2007 May 10; 356 (19): 1928–43PubMedCrossRefGoogle Scholar
Harper DM, Franco EL, Wheeler C, et al. Efficacy of a bivalent L1 virus-like particle vaccine in prevention of infection with human papillomavirus types 16 and 18 in young women: a randomised controlled trial. Lancet 2004 Nov 13; 364 (9447): 1757–65PubMedCrossRefGoogle Scholar
Munoz N, Kjaer SK, Sigurdsson K, et al. Impact of human papillomavirus (HPV)-6/11/16/18 vaccine on all HPVassociated genital diseases in young women. J Natl Cancer Inst 2010 Feb 5; 102 (5): 325–39PubMedCrossRefGoogle Scholar
Skinner R, Apter D, Chow SN, et al. Cross-protection efficacy of Cervarix™ against oncogenic HPV types beyond HPV-16/18 [abstract no. O-29.01] 25th International Papillomavirus Conference; 2009 May 8-14; MalmöGoogle Scholar
Brown DR, Kjaer SK, Sigurdsson K, et al. The impact of quadrivalent human papillomavirus (HPV; types 6, 11, 16, and 18) L1 virus-like particle vaccine on infection and disease due to oncogenic nonvaccine HPV types in generally HPV-naive women aged 16-26 years. J Infect Dis 2009 Apr 1; 199 (7): 926–35PubMedCrossRefGoogle Scholar
Brabin L, Roberts SA, Stretch R, et al. Uptake of first two doses of human papillomavirus vaccine by adolescent schoolgirls in Manchester: prospective cohort study. BMJ 2008; 336 (7652): 1056–8PubMedCrossRefGoogle Scholar
Stokley S, Dorell C. National, state, and local area vaccination coverage among adolescents aged 13–17 years–United States, 2008. MMWR Morb Mortal Wkly Rep 2010 Sep 18; 58 (36): 997–1001Google Scholar
Brisson M, Van de Velde N, Boily MC. Economic evaluation of human papillomavirus vaccination in developed countries. Public Health Genomics 2009; 12 (5-6): 343–51PubMedCrossRefGoogle Scholar
Kim JJ, Brisson M, Edmunds WJ, et al. Modeling cervical cancer prevention in developed countries. Vaccine 2008 Aug 19; 266 Suppl. 10: K76–86CrossRefGoogle Scholar
Marra F, Cloutier K, Oteng B, et al. Effectiveness and cost effectiveness of human papillomavirus vaccine: a systematic review. Pharmacoeconomics 2009; 27 (2): 127–47PubMedCrossRefGoogle Scholar
Suárez E, Smith JS, Bosch FX, et al. Cost-effectiveness of vaccination against cervical cancer: a multi-regional analysis assessing the impact of vaccine characteristics and alternative vaccination scenarios. Vaccine 2008 Sep 15; 26 Suppl. 5: F29–45CrossRefGoogle Scholar
Adang E, Voordijk L, Jan van der Witt G, et al. Cost-effectiveness analysis in relation to budgetary constraints and reallocative restrictions. Health Policy 2005 Oct; 74 (2): 146–56PubMedCrossRefGoogle Scholar
Claxton K. The irrelevance of inference: a decision-making approach to the stochastic evaluation of health care technologies. J Health Econ 1999 Jun; 18 (3): 341–64PubMedCrossRefGoogle Scholar
Gafni A, Birch S. Incremental cost-effectiveness ratios (ICERs): the silence of the lambda. Soc Sci Med 2006 May; 62 (9): 2091–100PubMedCrossRefGoogle Scholar
Hutubessy RC, Bendib LM, Evans DB. Critical issues in the economic evaluation of interventions against communicable diseases. Acta Trop 2001 Mar 30; 78 (3): 191–206PubMedCrossRefGoogle Scholar
World Health Organization. Making choices in health: WHO guide to cost-effectiveness analysis. Geneva: WHO, 2003Google Scholar
Drummond MF. Principles of economic appraisal in health care. Oxford: Oxford University Press, 1980Google Scholar
Earnshaw SR, Richter A, Sorensen SW, et al. Optimal allocation of resources across four interventions for type 2 diabetes. Med Decis Making 2002 Sep; 22 (5 Suppl.): S80–91CrossRefGoogle Scholar
Epstein DM, Chalabi Z, Claxton K, et al. Efficiency, equity, and budgetary policies: informing decisions using mathematical programming. Med Decis Making 2007 Mar; 27 (2): 128–37PubMedCrossRefGoogle Scholar
Stinnett AA, Paltiel AD. Mathematical programming for the efficient allocation of health care resources. J Health Econ 1996 Oct; 15 (5): 41–53CrossRefGoogle Scholar
Earnshaw SR, Hicks K, Richter A, et al. A linear programming model for allocating HIV prevention funds with state agencies: a pilot study. Health Care Manag Sci 2007 Sep; 10 (3): 239–52PubMedCrossRefGoogle Scholar
Richter A, Hicks KA, Earnshaw SR, et al. Allocating HIV prevention resources: a tool for state and local decision making. Health Policy 2008 Sep; 87 (3): 342–9PubMedCrossRefGoogle Scholar
Weniger BG, Chen RT, Jacobson SH, et al. Addressing the challenges to immunization practice with an economic algorithmfor vaccine selection. Vaccine 1998 Nov; 16 (19): 1885–97PubMedCrossRefGoogle Scholar
Earnshaw SR, Dennett SL. Integer/linear mathematical programming models: a tool for allocating healthcare resources. Pharmacoeconomics 2003; 21 (12): 839–51PubMedCrossRefGoogle Scholar
Luenberger DG, Yinyu Y. Linear and nonlinear programming. 3rd ed. New York: Springer, 2008Google Scholar
Debicki D, Ferko N, Demarteau N, et al. Comparison of detailed and succinct cohort modelling approaches in a multi-regional evaluation of cervical cancer vaccination. Vaccine 2008 Sep 15; 26 Suppl. 5: F16–28CrossRefGoogle Scholar
Colantonio L, Gómez JA, Demarteau N, et al. Cost-effectiveness analysis of a cervical cancer vaccine in five Latin American countries. Vaccine 2009; 27 (40): 5519–29PubMedCrossRefGoogle Scholar
Castellsague X, de Sanjose S, Aguado T, et al. HPV and cervical cancer in the world: 2007 report. Vaccine 2007; 25 Suppl. 3: C1–230Google Scholar
Tjalma W, Paavonen J, Naud P, et al. Efficacy of the HPV-16/18 AS04-adjuvanted vaccine against abnormal cytology and low-grade histopathological lesions in an oncogenic HPV-naïve population [abstract no. A-171-0004-01446]. 16th International Meeting of the European Society for Gynaecological Oncology (ESGO); 2009 Oct 11-14 Oct; BelgradeGoogle Scholar
David MP, Van Herck K, Hardt K, et al. Long-term persistence of anti-HPV-16 and -18 antibodies induced by vaccination with the AS04-adjuvanted cervical cancer vaccine: modeling of sustained antibody responses. Gynecol Oncol 2009 Feb; 115 (3 Suppl. 1): S1–6CrossRefGoogle Scholar
McKenna C, Chalabi Z, Epstein D, et al. Budgetary policies and available actions: a generalisation of decision rules for allocation and research decisions. J Health Econ 2010 Jan; 29 (1): 170–81PubMedCrossRefGoogle Scholar
Franco EL, Cuzick J. Cervical cancer screening following prophylactic human papillomavirus vaccination. Vaccine 2008 Mar 14; 26 Suppl. 1: A16–23CrossRefGoogle Scholar
Rogoza RM, Ferko N, Bentley J, et al. Optimization of primary and secondary cervical cancer prevention strategies in an era of cervical cancer vaccination: a multiregional health economic analysis. Vaccine 2008 Sep 15; 26 Suppl. 5: F46–58CrossRefGoogle Scholar