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Prostatectomized patients are at risk of resurgence: this is the reason why,during a follow-up period, they are monitored for PSA growth, an indicator oftumor progression. The presence of tumors can be evaluated with an expensiveexam, called PET-PSMA (Positron Emission Tomography with Prostate-SpecificMembrane Antigen). But, to optimize the benefit/risk ratio, patients should bereferred to this exam only when the evidence is strong. The aim is to estimatethe optimal time to recommend the exam, based on patients' history andcollected data. We build a Hierarchical Bayesian model that describes, jointly,the PSA growth curve and the probability of a positive PET-PSMA. Our proposalis to process all information about the patient in order to give an informedestimate of the optimal time.

Estimating the optimal time to perform a PET-PSMA exam in prostatectomized patients based on data from clinical practice