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Comparing hormone therapy effects in two RCTs and two large observational studies that used similar methods for comprehensive data collection and outcome assessment
  1. Arthur Hartz1,
  2. Tao He2,
  3. Robert Wallace3,
  4. John Powers4
  1. 1Huntsman Cancer Institute at the University of Utah, St Louis, Missouri, USA
  2. 2Health Services Research, University of Utah College of Medicine, Salt Lake City, Utah, USA
  3. 3Department of Epidemiology, College of Public Health, University of Iowa, Iowa City, Iowa, USA
  4. 4Department of Medicine, George Washington University School of Medicine, District of Columbia, DC, USA
  1. Correspondence to Dr Arthur Hartz; hartzarthur{at}gmail.com

Abstract

Objectives Prospective observational studies (OSs) that collect adequate information about confounders can validly assess treatment consequences. However, what constitutes adequate information is unknown. This study investigated whether the extensive information collected by the Women's Health Initiative (WHI) in two OSs and two randomised controlled trials (RCTs) was adequate.

Design Secondary analysis of WHI data. Cox regression was used to select from all baseline risk factors those that best predicted outcome. Cox regression that included these risk factors was used for two types of analyses: (1) comparing RCT and OS assessments of the effects of hormone therapy on outcome for participants with specific characteristics and (2) evaluating whether adjustment for measured confounders could eliminate outcome differences among datasets.

Setting The WHI included more than 800 baseline risk factors and outcomes during a median follow-up of 8 years.

Participants 151 870 postmenopausal women ages 50–79.

Primary and secondary outcome measures Myocardial infarction and stroke.

Results RCT and OS results differed for the association of hormone therapy with outcome after adjusting for confounding factors and stratifying on factors that were hypothesised to modulate the effects of hormone therapy (eg, age and time since menopause) or that empirically modulated the effects of hormone therapy in this dataset (eg, blood pressure, previous coronary revascularisation and private medical insurance). Some of the four WHI datasets had significantly worse outcomes than others even after adjusting for risk and stratifying by type of hormone therapy, for example, the risk-adjusted HR for myocardial infarction was 1.37 (p<0.0001) in an RCT placebo group compared with an OS group not taking hormone therapy.

Conclusions Apparently the WHI did not collect sufficient information to give reliable assessments of treatment effects. If the WHI did not collect sufficient data, it is likely that few OSs collect sufficient information.

This is an Open Access article distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 3.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/3.0/

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