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|Title:||Prognosis Research Strategy (PROGRESS) 2: Prognostic Factor Research|
|Authors:||Riley, Richard D.|
Hayden, Jill A.
Steyerberg, Ewout W.
Moons, Karel G.M.
Kyzas, Panayiotis A.
Altman, Douglas G.
|Publisher:||Public Library of Science|
|Citation:||PLoS Medicine, 2013, 10 (2), e1001380.|
|Abstract:||Summary Points: The PROGRESS series (http://www.progress-partnership.org) sets out a framework of four interlinked prognosis research themes and provides examples from several disease fields to show why evidence from prognosis research is crucial to inform all points in the translation of biomedical and health related research into better patient outcomes. Recommendations are made in each of the four papers to improve current research standards. What is prognosis research? Prognosis research seeks to understand and improve future outcomes in people with a given disease or health condition. However, there is increasing evidence that prognosis research standards need to be improved. Why is prognosis research important? More people now live with disease and conditions that impair health than at any other time in history; prognosis research provides crucial evidence for translating findings from the laboratory to humans, and from clinical research to clinical practice. A prognostic factor is any measure that, among people with a given startpoint (such as diagnosis of disease), is associated with a subsequent endpoint (such as death). Prognostic factors have many potential uses: for example, they help define disease at diagnosis, inform clinical and therapeutic decisions (either directly or as part of prognostic models for individualised risk prediction), enhance the design and analysis of intervention trials, and help identify targets for new interventions that aim to modify the course of a disease or health condition. Limitations in current prognostic factor research include publication bias, reporting biases, poor statistical analyses, and inadequate replication of initial findings. To address these issues we recommend that large, prospective, registered, and protocol supported prognostic factor studies are needed with suitable sample size, appropriate statistical analyses, and transparent reporting of all factors and outcomes considered. Initial exploratory studies are also important, but must be labelled as such. A factor's prognostic ability should be examined across multiple studies, and we recommend increased use of (ideally prospectively planned) meta-analysis of individual participant data, as it potentially alleviates any reporting biases and analysis deficiencies in primary studies. For each factor identified as prognostic, there should be greater understanding of how it can be used to improve clinical outcomes, including whether it is useful within the clinical management of patients and whether it informs the development of novel interventions. The other papers in the series are: ○. PROGRESS 1: BMJ 2013, doi:10.1136/bmj.e5595 ○. PROGRESS 3: PLOS Med 2013, doi:10.1371/journal.pmed.1001381 ○. PROGRESS 4: BMJ 2013, doi:10.1136/bmj.e5793|
|Rights:||Copyright: © 2013 Riley et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.|
|Appears in Collections:||Published Articles, Dept. of Health Sciences|
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