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On the Importance of a Clear Definition of Time Horizon for Time-to-Event Dynamic Predictions: A Systematic Review and a Concrete Illustration in Kidney Transplantation
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DOI：10.2147/CLEP.S572750.png)
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Abstract
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Lucas Chabeau,1,2 Vincent Bonnemains,1 Pierre Rinder,2 Magali Giral,3,4 Solène Desmée,5 Etienne Dantan1 1Nantes Université, Univ Tours, INSERM UMR 1246, MethodS in Patients-Centered Outcomes and HEalth Research, SPHERE, Nantes, France; 2SEMEIA, Paris, Toulouse, France; 3Nantes Université, CHU Nantes, INSERM, Center for Research in Transplantation and Translational Immunology, UMR 1064, ITUN, F-44000, Nantes, France; 4Centre d’Investigation Clinique en Biothérapie, Nantes, France; 5Univ Tours, Nantes Université, INSERM UMR 1246, MethodS in Patients-centered outcomes and HEalth Research, SPHERE, Tours, France Correspondence: Etienne Dantan, Nantes Université, Univ Tours, INSERM UMR 1246, MethodS in Patients-centered outcomes and HEalth Research, SPHERE, IRS2, 22 Boulevard Bénoni Goullin, Nantes, 44200, France, Tel +33 2 53 00 91 28, Email Etienne.Dantan@univ-nantes.fr Introduction: Dynamic predictions estimate survival probability until a given horizon, conditionally on being event-free at landmark times and additional information on predictive variables available at these times. The horizon may be defined as a final time horizon or the end of a sliding horizon window. Methods: Following PRISMA, CHARMS, and TRIPOD recommendations, a systematic review of dynamic predictions, querying Medline in May 2025 with no date restriction and including only English articles, assessed heterogeneity in time horizon reporting. Moreover, from 2,523 kidney recipients, prognostic capacities of the Dynamic predictions of Patient and kidney Graft survival have been studied considering either a final time horizon or a sliding horizon window. Results: From 171 articles included in the systematic review, 97 articles (57%) used a sliding horizon window, 36 (21%) a final time horizon and 38 articles (22%) had no clear time horizon definition. From the kidney transplant recipients’ sample, discrimination and calibration of dynamic predictions are not comparable between the two time horizon definitions due to differing event incidence depending on the nature of the prediction window that can be either reduced or sliding. For a 5-year sliding horizon window, discrimination slightly increased with landmark times, and calibration appeared reasonable, especially at earliest landmark times. For an 11-year final time horizon, discrimination was high for earliest landmark times and increased over time, while calibration revealed underestimated predictions for earliest landmark times and overestimated for later ones. Discussion: Our systematic review highlights the need for clearer time horizon reporting due to heterogeneous definitions. Our renal transplantation illustration revealed that the prognostic performances of Dynamic predictions of Patient and kidney Graft survival differ given the time horizon definition. More broadly, this study highlights the need for caution when interpreting prognostic performances, as it depends on whether the horizon window is sliding or reduced. Keywords: time-to-event dynamic predictions, landmark times, horizon window, time horizon, discrimination, calibration
Keywords:
time-to-event dynamic predictions
landmark times
horizon window
time horizon
discrimination
calibration
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