As the number of patients in cancer remission increases every year, an economically attractive option is to reduce duration of follow-up according to prognostic factors. In the present study we propose a statistical method to define an optimal duration of follow-up for patients in remission after treatment for cancer, for detection of recurrences.Background:
The objective of this study was to present a statistical method to define an optimal duration of follow-up for patients in remission after treatment for cancer, for detection of recurrences.Patients and Methods:
Surveillance duration was estimated using the 2-step approach proposed by Mould et al. Relapse-free interval was modeled using the parametric cure model proposed by Boag. The optimal length of follow-up was then estimated as the minimal elapsed time after which the probability of a patient to relapse and to be cured with success is below a given threshold value. The method is applied to 2 real data sets of patients treated for metastatic non seminomatous germ-cell tumors: T93BP and T93MP.Results:
For the T93BP, cure rate was estimated at 91.3% and proportions of patients who relapsed after 3 and 5 years were estimated at 0.5% and 0.2%. With a probability of success of salvage treatment equal to 80% and 50%, numbers of delayed cases after 5 years were 2 and 1. For T93MP, the proportion of patients who presented relapse after 5 and 10 years were estimated at 5.2% and 2.6%. Considering a probability of salvage treatment equal to 20%, the number of delayed cases after 5 and 10 years were 10 and 5.Conclusion:
Using this methodology, duration of post-therapeutic follow-up might be tailored according to an objective criteria: the number of patients who present relapse after the end of follow-up and who could have been treated with success in case of early detection.