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Problems With the Development and Validation of a Prognostic Model
Author(s) -
Collins G. S.,
Manach Y. L.
Publication year - 2015
Publication title -
american journal of transplantation
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.89
H-Index - 188
eISSN - 1600-6143
pISSN - 1600-6135
DOI - 10.1111/ajt.13391
Subject(s) - medicine , scopus , overfitting , medline , statistics , artificial intelligence , computer science , mathematics , political science , artificial neural network , law
With high quality data and appropriate statistical methods, prognostic models can hold enormous potential for identifying individuals at increased risk developing a health condition. Unfortunately, the recent study described by He et al (1) not only fails to omit key important information as suggested the TRIPOD Initiative (2) (www.tripodstatement.org), but has numerous methodological problemswhich deserve highlighting so that future investigators do not fall into the same trap.