title: Using the SAEM algorithm for mechanistic joint models characterizing the relationship between nonlinear PSA kinetics and survival in prostate cancer patients.
abstract: Joint modeling is increasingly popular for investigating the relationship between longitudinal and time-to-event data. However, numerical complexity often restricts this approach to linear models for the longitudinal part. Here, we use a novel development of the Stochastic-Approximation Expectation Maximization algorithm that allows joint models defined by nonlinear mixed-effect models. In the context of chemotherapy in metastatic prostate cancer, we show that a variety of patterns for the Prostate Specific Antigen (PSA) kinetics can be captured by using a mechanistic model defined by nonlinear ordinary differential equations. The use of a mechanistic model predicts that biological quantities that cannot be observed, such as treatment-sensitive and treatment-resistant cells, may have a larger impact than PSA value on survival. This suggests that mechanistic joint models could constitute a relevant approach to evaluate the efficacy of treatment and to improve the prediction of survival in patients.
authors.affiliation: INSERM, IAME, UMR 1137, F-75018 Paris, France.|Université Paris Diderot, IAME, UMR 1137, Sorbonne Paris Cité, F-75018 Paris, France.
authors.forename: Solène
authors.initials: S
authors.lastname: Desmée
authors.affiliation: INSERM, IAME, UMR 1137, F-75018 Paris, France.|Université Paris Diderot, IAME, UMR 1137, Sorbonne Paris Cité, F-75018 Paris, France.
authors.forename: France
authors.initials: F
authors.lastname: Mentré
authors.affiliation: Drug Disposition, Disposition Safety and Animal Research Department, Sanofi, Alfortville, France.
authors.forename: Christine
authors.initials: C
authors.lastname: Veyrat-Follet
authors.affiliation: Biostatistics and Programming, Sanofi, Chilly-Mazarin, France.
authors.forename: Bernard
authors.initials: B
authors.lastname: Sébastien
authors.affiliation: INSERM, IAME, UMR 1137, F-75018 Paris, France.|Université Paris Diderot, IAME, UMR 1137, Sorbonne Paris Cité, F-75018 Paris, France.
authors.forename: Jérémie
authors.initials: J
authors.lastname: Guedj
mesh_terms: D000465:Algorithms; D001699:Biometry / Q000379:methods*; D003627:Data Interpretation, Statistical; D006801:Humans; D007700:Kinetics; D008297:Male; D011379:Prognosis; D017430:Prostate-Specific Antigen / Q000032:analysis*; D011471:Prostatic Neoplasms / Q000401:mortality*; D013269:Stochastic Processes; D016019:Survival Analysis; D016896:Treatment Outcome
chemical_list: D017430:Prostate-Specific Antigen
keywords: Joint model; Metastatic prostate cancer; Nonlinear mixed effect model; Prostate specific antigen; SAEM algorithm; Survival