Bernard Asselain, Jean Marie Boher, Thomas Filleron, Andrew Kramar, Eve Leconte, and Serge Somda, “Optimal scheduling of post-therapeutic follow-up of patients treated for cancer for early detection of relapses.”, Statistical Methods in Medical Research, vol. 25, n. 6, December 2016, pp. 2457–2471.
Post-therapeutic surveillance is one important component of cancer care. However, there still is no evidence-based strategies to schedule patients' follow-up examinations. Our approach is based on the modeling of the probability of the onset of relapse at an early asymptotic or preclinical stage and its transition to a clinical stage. For that we consider a multistate homogeneous Markov model, which includes the natural history of relapse. The model also handles separately the different types of possible relapses. The optimal schedule is provided by the calendar visit that maximizes a utility function. The methodology has been applied to laryngeal cancer. The different follow-up strategies revealed to be more efficient than those proposed by different scientific societies.