• ViscondiJuliana Yukari KodairaJYKDepartamento de Medicina Preventiva, Faculdade de Medicina FMUSP, Universidade de Sao Paulo, Sao Paulo, SP, BR., Christine Grutzmann Faustino, Alessandro Gonçalves Campolina, Alexander Itria, and Patricia Coelho de Soárez.
• Departamento de Medicina Preventiva, Faculdade de Medicina FMUSP, Universidade de Sao Paulo, Sao Paulo, SP, BR.
• Clinics (Sao Paulo). 2018 Jul 10; 73: e385e385.

AbstractThe aim of this study was to critically evaluate the quality of the models used in economic evaluations of screening strategies for cervical cancer prevention. We systematically searched multiple databases, selecting model-based full economic evaluations (cost-effectiveness analyses, cost-utility analyses, and cost-benefit analyses) of cervical cancer screening strategies. Two independent reviewers screened articles for relevance and performed data extraction. Methodological assessment of the quality of the models utilized formal checklists, and a qualitative narrative synthesis was performed. Thirty-eight articles were reviewed. The majority of the studies were conducted in high-income countries (82%, n=31). The Pap test was the most used screening strategy investigated, which was present in 86% (n=33) of the studies. Half of the studies (n=19) used a previously published Markov model. The deterministic sensitivity analysis was performed in 92% (n=35) of the studies. The mean number of properly reported checklist items was 9 out of the maximum possible 18. Items that were better reported included the statement of decision problem, the description of the strategies/comparators, the statement of time horizon, and information regarding the disease states. Compliance with some items of the checklist was poor. The Markov models for economic evaluation of screening strategies for cervical cancer varied in quality. The following points require improvement: 1) assessment of methodological, structural, heterogeneity, and parameter uncertainties; 2) model type and cycle length justification; 3) methods to account for heterogeneity; and 4) report of consistency evaluation (through calibration and validation methods).

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