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. 2013 Feb 5:346:e5595.
doi: 10.1136/bmj.e5595.

Prognosis research strategy (PROGRESS) 1: a framework for researching clinical outcomes

Harry Hemingway  1 , Peter Croft, Pablo Perel, Jill A Hayden, Keith Abrams, Adam Timmis, Andrew Briggs, Ruzan Udumyan, Karel G M Moons, Ewout W Steyerberg, Ian Roberts, Sara Schroter, Douglas G Altman, Richard D Riley; PROGRESS Group
Collaborators, Affiliations

Prognosis research strategy (PROGRESS) 1: a framework for researching clinical outcomes

Harry Hemingway et al. BMJ. .

Abstract

Understanding and improving the prognosis of a disease or health condition is a priority in clinical research and practice. In this article, the authors introduce a framework of four interrelated themes in prognosis research, describe the importance of the first of these themes (understanding future outcomes in relation to current diagnostic and treatment practices), and introduce recommendations for the field of prognosis research

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Conflict of interest statement

Competing interests: All authors have completed the ICMJE uniform disclosure form at www.icmje.org/coi_disclosure.pdf (available on request from the corresponding author) and declare: no support from any organisation for the submitted work; no financial relationships with any organisations that might have an interest in the submitted work in the previous three years, no other relationships or activities that could appear to have influenced the submitted work. SS is a full time employee of the BMJ Group but is not involved in deciding which manuscripts are accepted for publication.

Figures

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Fig 1 Framework of four different types of prognosis research question, illustrated for breast cancer. a) Fundamental prognosis research: variations between countries in age adjusted, five year survival (with permission from Cancer Research UK6). b) Prognostic factor research: survival curves showing that patients with “positive” values (>8.9 ng/mL) of the extracellular domain of human epidermal growth factor receptor 2 (HER2 ECD) have a worse survival than those with negative values (≤8.9 ng/mL), and thus HER ECD is a potential prognostic factor (from Tsai et al7). c) Prognostic model research: use of multiple clinical variables in a model to estimate risk of endpoint, and then combined with evidence of treatment effectiveness to inform clinical decisions (ER=oestrogen receptor) (from Adjuvant! Online8). d) Stratified medicine research: predictors of differential treatment response identified in randomised trials, showing that the benefit of tamoxifen is confined to those with positive oestrogen receptor (ER) status (based on data from Early Breast Cancer Trialists Collaborative Group9)
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Fig 2 Example of use of fundamental prognosis research to examine variations in outcomes from medical care: inter-hospital variation in mortality per 100 population within 30 days of admission with acute myocardial infarction (created using fictional data for illustration purposes, but based on the findings of Krumholz et al18)
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Fig 3 Example of use of fundamental prognosis research to discover new associations between diseases: cancer among non-smoking people with Parkinson’s disease (drawn using data from Bajaj et al42). Path element adapted from chart 7.1 in the Cooksey report (2006) http://bit.ly/Ro27rL (made available for use through the Open Government License)
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Fig 4 Example of use of fundamental prognosis research to define clinically relevant subgroups: duration of low back pain at presentation (<3 or ≥3 years) and the time to improvement of disability disease (drawn using data from Dunn et al46). Path element adapted from chart 7.1 in the Cooksey report (2006) http://bit.ly/Ro27rL (made available for use through the Open Government License)
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Fig 5 Example of use of fundamental prognosis research to distinguish clinically relevant groups: people admitted with suspected acute myocardial infarction (results based on an analysis of 180 000 patients in the Myocardial Ischaemia National Audit Project, A Timmis and H Hemingway personal communication)
See this image and copyright information in PMC

References

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    1. Department of Health. White paper. Equity and excellence: liberating the NHS. Stationery Office, 2010.
    1. Riley RD, Hayden JA, Steyerberg EW, Moons KGM, Abrams K, Kyzas PA, et al. Prognosis research strategy (PROGRESS) 2: Prognostic factor research. PLoS Med 2013, 10.1371.journal/pmed.1001380. - DOI - PMC - PubMed
    1. Steyerberg EW, Moons KGM, van der Windt DA, Hayden JA, Perel P, Schroter S, et al. Prognosis research strategy (PROGRESS) 3: Prognostic model research. PLoS Med 2013, 10.1371.journal/pmed.1001381. - DOI - PMC - PubMed
    1. Hingorani AD, van der Windt DA, Riely RD, Abrams K, Moons KGM, Steyerberg EW, et al. Prognosis research strategy (PROGRESS) 4: stratified medicine research. BMJ 2013;346:e5793. - PMC - PubMed

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