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Research Methods & Reporting

Prognosis and prognostic research: what, why, and how?

BMJ 2009; 338 doi: https://doi.org/10.1136/bmj.b375 (Published 23 February 2009) Cite this as: BMJ 2009;338:b375
  1. Karel G M Moons, professor of clinical epidemiology1,
  2. Patrick Royston, senior statistician2,
  3. Yvonne Vergouwe, assistant professor of clinical epidemiology1,
  4. Diederick E Grobbee, professor of clinical epidemiology1,
  5. Douglas G Altman, professor of statistics in medicine3
  1. 1Julius Centre for Health Sciences and Primary Care, University Medical Centre Utrecht, Utrecht, Netherlands
  2. 2MRC Clinical Trials Unit, London NW1 2DA
  3. 3Centre for Statistics in Medicine, University of Oxford, Oxford OX2 6UD
  1. Correspondence to: K G M Moons k.g.m.moons{at}umcutrecht.nl
  • Accepted 6 October 2008

Doctors have little specific research to draw on when predicting outcome. In this first article in a series Karel Moons and colleagues explain why research into prognosis is important and how to design such research

Hippocrates included prognosis as a principal concept of medicine.1 Nevertheless, principles and methods of prognostic research have received limited attention, especially compared with therapeutic and aetiological research. This article is the first in a series of four aiming to provide an accessible overview of these principles and methods. Our focus is on prognostic studies aimed at predicting outcomes from multiple variables rather than on studies investigating whether a single variable (such as a tumour or other biomarker) may be prognostic. Here we consider the principles of prognosis and multivariable prognostic studies and the reasons for and settings in which multivariable prognostic models are developed and used. The other articles in the series will focus on the development of multivariable prognostic models,2 their validation,3 and the application and impact of prognostic models in practice.4

Summary points

  • Prognosis is estimating the risk of future outcomes in individuals based on their clinical and non-clinical characteristics

  • Predicting outcomes is not synonymous with explaining their cause

  • Prognostic studies require a multivariable approach to design and analysis

  • The best design to address prognostic questions is a cohort study

What is prognosis?

Prognosis simply means foreseeing, predicting, or estimating the probability or risk of future conditions; familiar examples are weather and economic forecasts. In medicine, prognosis commonly relates to the probability or risk of an individual developing a particular state of health (an outcome) over a specific time, based on his or her clinical and non-clinical profile. Outcomes are often specific events, such as death or complications, but they may also be quantities, such as disease progression, (changes in) pain, or quality of …

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