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Research Methods & Reporting

How to translate clinical trial results into gain in healthy life expectancy for individual patients

BMJ 2016; 352 doi: https://doi.org/10.1136/bmj.i1548 (Published 30 March 2016) Cite this as: BMJ 2016;352:i1548
  1. Jannick A N Dorresteijn, postdoctoral epidemiologist and resident in internal medicine1,
  2. Lotte Kaasenbrood, epidemiologist and medical doctor1,
  3. Nancy R Cook, professor of biostatistics and epidemiology2,
  4. Rob C M van Kruijsdijk, postdoctoral epidemiologist and resident in internal medicine1,
  5. Yolanda van der Graaf, professor of epidemiology and imaging3,
  6. Frank L J Visseren, professor of vascular medicine, epidemiologist, and internist1,
  7. Paul M Ridker, Eugene Braunwald professor of medicine, epidemiologist, and cardiologist2
  1. 1Department of Vascular Medicine, University Medical Centre Utrecht, PO Box 85500, 3508 GA Utrecht, Netherlands
  2. 2Harvard Medical School, Boston, MA, USA; Centre for Cardiovascular Disease Prevention, Division of Preventive Medicine, Brigham and Women’s Hospital, Boston, MA Division of Cardiovascular Medicine, Brigham and Women's Hospital, Boston, MA, USA
  3. 3Julius Centre for Health Sciences and Primary Care, University Medical Centre Utrecht, Utrecht, Netherlands
  1. Correspondence to: J A N Dorresteijn J.A.N.Dorresteijn2{at}umcutrecht.nl

Treatment effects from randomised trials are typically expressed as numbers needed to treat to prevent one adverse disease event during a fixed time interval (eg, five or 10 years). In the actual patient, however, many diseases are chronically progressive, despite treatment. Examples are diabetic nephropathy, some types of malignancies, osteoporosis, and atherosclerosis. In these examples, the aim of treatment is not to prevent but to delay the occurrence of symptomatic disease. Thus the actual effect of treatment is gain in disease-free life expectancy

Video abstract

Summary points

  • Gain in disease-free life expectancy is a more intuitive measure of treatment effect than number needed to treat for lifelong treatment for chronically progressive conditions

  • Treatment effect as gain in healthy life expectancy can be predicted based on a combination of the relative effect of treatment from a randomised trial and a lifetime prediction model

  • Lifetime prediction models are characterised by left truncation and adjustment for competing risks and can be developed using data from either observational cohort or clinical trials

  • The highest treatment effect in terms of disease-free life years gained is generally achieved in younger patients with otherwise high risk factors for disease, but not necessarily a high risk for disease, although at the cost of longer duration of drug use and exposure to possible adverse events

Healthy life expectancy is a customary outcome type in cost effectiveness studies at group level, but predictions can also be made at individual patient level.1 2 In this article we explain how clinical trial results can be translated into gains in healthy life expectancy for individual patients. We use aspirin in the primary prevention of cardiovascular disease as an illustrative example, based on real data from the Women’s Health Study.3 4

Lifetime prediction models

Traditionally, prediction models for disease risk in individual patients are limited to the follow-up time …

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