New Microsimulation Models to Inform Cervical Cancer Control
2021
Health decision models consider the lifetime natural history of human papillomavirus (HPV) infection and pathogenesis of cervical cancer, and estimate the long-term impact of preventive interventions. We propose a new health decision modeling framework that de-emphasizes previously used cytologic-colposcopic-histologic diagnoses, which are subjective and lack reproducibility, relying instead on HPV type and duration of infection as the major determinants of model transition probabilities. We posit that new model health states and corollary transitions are universal, but transition probabilities may vary by population, as inferred from HPV prevalence patterns in different regions across the lifespan. By prioritizing direct estimation of model transition probabilities from longitudinal data (and limiting reliance on model-fitting techniques that may propagate error when applied to multiple transitions), we aim to improve model transparency and reliability.
New Microsimulation Models to Inform Cervical Cancer Control
Source:
Campos NG, Demarco M, Bruni L et al. A Proposed New Generation of Evidence-Based Microsimulation Models to Inform Global Control of Cervical Cancer. Preventive Medicine 2021; 144. https://doi.org/10.1016/j.ypmed.2021.106438