2026-06-14T03:44:43Zhttps://repisalud.isciii.es/rest/oai/request

oai:repisalud.isciii.es:20.500.12105/157702025-06-11T12:36:53Zcom_20.500.12105_2052com_20.500.12105_2051com_20.500.12105_15322col_20.500.12105_19612col_20.500.12105_16961

00925njm 22002777a 4500 dc Torres Moral, Teresa author Sanchez-Niubo, Albert author Monistrol-Mula, Anna author Gerardi, Chiara author Banzi, Rita author Garcia, Paula author Demotes-Mainard, Jacques author Haro, Josep Maria author The Permit Group author Imaz-Iglesia, Iñaki author 2022-04-26 Personalized medicine requires large cohorts for patient stratification and validation of patient clustering. However, standards and harmonized practices on the methods and tools to be used for the design and management of cohorts in personalized medicine remain to be defined. This study aims to describe the current state-of-the-art in this area. A scoping review was conducted searching in PubMed, EMBASE, Web of Science, Psycinfo and Cochrane Library for reviews about tools and methods related to cohorts used in personalized medicine. The search focused on cancer, stroke and Alzheimer's disease and was limited to reports in English, French, German, Italian and Spanish published from 2005 to April 2020. The screening process was reported through a PRISMA flowchart. Fifty reviews were included, mostly including information about how data were generated (25/50) and about tools used for data management and analysis (24/50). No direct information was found about the quality of data and the requirements to monitor associated clinical data. A scarcity of information and standards was found in specific areas such as sample size calculation. With this information, comprehensive guidelines could be developed in the future to improve the reproducibility and robustness in the design and management of cohorts in personalized medicine studies. J Pers Med. 2022 Apr 26;12(5):688. 10.3390/jpm12050688 2075-4426 Journal of personalized medicine 35629113 http://hdl.handle.net/20.500.12105/15770 Cohorts Sample size Stratification Personalized medicine Methods for Stratification and Validation Cohorts: A Scoping Review