Biometrics & Biostatistics

Biography

Biography: Serge M A Somda

Abstract

Organizing the surveillance of patients treated for cancer, for early diagnosis of recurrences, is still a subject of debate. Evidence needs to be highlighted to determine when a particular follow-up strategy is efficient enough to have a significant impact on survival. However, the clinical evaluation of follow-up programs after primary treatment is difficult to undertake. This work proposes an algorithm to evaluate a novel follow-up surveillance strategy after treatment in oncology. A computer based randomized two parallel arms non-inferiority clinical trial is simulated to compare two strategies. Overall survival and cancer specific mortality were the two endpoints evaluated. The methodology of Discrete Events Simulation, based on Patient Oriented Simulation Technique, was used. The natural history of the patient’s disease after primary treatment was generated for each individual. Then, for each scheduled visit date, this history could be modified if a relapse was detected early enough and efficient treatment options are available. An application of the algorithm based on breast cancer data shows its advantages in decision making.