Multiparameter Calibration of a Natural History Model of Cervical Cancer
2007
This paper presents a two-step approach to model calibration of a comprehensive natural history model of human papillomavirus (HPV) and cervical cancer. Using primary epidemiologic data from a longitudinal study of women in Brazil, a plausible range for each input parameter was identified that would produce model output within the 95% confidence intervals of the data.
The authors then performed a simultaneous search over all input parameters to identify parameter sets that produced output consistent with data from multiple sources not used to generate the parameters. Using a likelihood-based approach 555,000 unique parameter sets were scored for goodness of fit and a sample of these were used to demonstrate the advantage of this calibration approach.
The authors found that model parameterization of the unobservable nature of HPV infection and its role in the development of cervical cancer was enhanced through the leveraging of primary data from longitudinal studies. They showed that the calibrated model fit the data reasonably for duration and prevalence of HPV infection for high-risk types, prevalence of precancerous lesions, and cancer incidence.
Multiparameter Calibration of a Natural History Model of Cervical Cancer
Source:
Kim JJ, Kuntz KM, Stout NK, Mahmud S, Villa LL, Franco EL, Goldie SJ. Multiparameter Calibration of a Natural History Model of Cervical Cancer. American Journal of Epidemiology 2007; 166 (2): 137-150. https://doi.org/10.1093/aje/kwm086
Not open access.