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The Effect of the Distribution of the Inverse Growth Rate on Pancreatic Cancer Progression

Pancreatic cancer is a low-incidence disease, where tumor progression studies using patient longitudinal data had limited sample sizes. Estimating the tumor inverse growth rate and its distribution are a challenge. Using a tumor progression model that incorporates the distribution of the inverse growth rate as the underlying assumption of the model, pancreatic cancer progression models were built assuming two distributions for the inverse growth rate: Uniform and Gamma. This study uses simulation to evaluate the effect of the tumor inverse growth rate distribution on the tumor progression models by examining tumor timelines. It was found that the tumor timeline is about nine months longer under the assumption that the inverse growth rate follows Gamma distribution. It was inconclusive whether tumor progression is faster or slower in older patients as the tumor progression models with the different underlying assumptions on the inverse growth rate yielded opposite results.