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Comment & Response
July 11, 2017

Posing Causal Questions When Analyzing Observational Data

Author Affiliations
  • 1Department of Nutrition, Harvard T. H. Chan School of Public Health, Boston, Massachusetts
  • 2Department of Epidemiology, Harvard T. H. Chan School of Public Health, Boston, Massachusetts
  • 3Department of Medicine, Brigham and Women's Hospital, Boston, Massachusetts
JAMA. 2017;318(2):201. doi:10.1001/jama.2017.6227

To the Editor In their Editorial on evaluating data from observational research, Dr Goodman and colleagues1 mischaracterized the reasons for the apparent difference between the results of the Nurses’ Health Study (NHS) and the Women’s Health Initiative Trial (WHI) of hormone therapy (HT). The main reason for the difference was that in the observational studies, including the NHS, nearly all HT use began in early menopause (within a few years of onset), and most was estrogen alone, without progestin. Because coronary disease is uncommon in early menopause, the WHI targeted an older age group (mean age, 63 years [range, 50-79 years]) to increase statistical power. This created a deviation from the “like vs like” principle enunciated by Goodman and colleagues.1

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