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We formulate the relapse time estimation problem in the framework of Piecewise Deterministic Markov processes (PDMP), where the Euclidean component is a surrogate biomarker for patient state. This approach enables continuous-time estimation of the status-change dates, which in turn allows for accurate inference of the relapse time distribution. A key challenge lies in the partial observability of the process, a complexity that has been rarely addressed in previous studies. We evaluate the performance of our procedure through a simulation study and compare it with different approaches. This work is a proof of concept on biomarker trajectories with simple behaviour, but our method can easily be extended to more complex dynamics.<\/jats:p>","DOI":"10.1515\/ijb-2025-0054","type":"journal-article","created":{"date-parts":[[2026,10,14]],"date-time":"2026-10-14T13:56:23Z","timestamp":1791986183000},"source":"Crossref","is-referenced-by-count":0,"title":["Estimating relapse time distribution from longitudinal biomarker trajectories using iterative regression and continuous time Markov processes"],"prefix":"10.1515","author":[{"given":"Alice","family":"Cleynen","sequence":"first","affiliation":[{"name":"Univ Montpellier, CNRS , Montpellier , France"},{"name":"John Curtin School of Medical Research, The Australian National University , Canberra , ACT , Australia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Beno\u00eete","family":"de Saporta","sequence":"additional","affiliation":[{"name":"Univ Montpellier, CNRS , Montpellier , France"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0006-2001-3732","authenticated-orcid":false,"given":"Am\u00e9lie","family":"Vernay","sequence":"additional","affiliation":[{"name":"Univ Montpellier, CNRS , Montpellier , France"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"374","published-online":{"date-parts":[[2026,10,14]]},"reference":[{"key":"2026101413561918177_j_ijb-2025-0054_ref_001","doi-asserted-by":"crossref","unstructured":"Attal, M, Lauwers-Cances, V, Hulin, C, Leleu, X, Caillot, D, Escoffre, M, et al.. 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