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March 15, 2026Medical Decision MakingOpen Access

A Comparison of Methods for Modeling Multistate Cancer Progression Using Screening Data with Censoring after Intervention

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Authors

EAEddymurphy U. AkwiwuVCVeerle M.H. CoupéJBJohannes Berkhof

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Overview

This comparison reveals the impact of censoring on risk estimates in colorectal cancer, indicating robust results from specific multistate models.

Key Points

  • The aim is to understand the performance of multistate cancer models in the context of treatment upon detection of cancer precursors.
  • Compared 6 multistate models using R software
  • Assumed progression hazards in a 3-state model: healthy, cancer precursor, and cancer
  • Analyzed colorectal cancer surveillance data from 734 individuals
  • Time-independent hazards yielded unbiased estimates across all models
  • BayesTSM and smms provided unbiased estimates with time-dependent hazards
  • Censoring after intervention significantly affects hazard dependency and estimates

Cite This Study

Akwiwu et al. (2026) studied this question.

synapsesocial.com/papers/69b5ff5c83145bc643d1bdd4https://doi.org/10.1177/0272989x261422681
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