A recent New England Journal of Medicine article discussed that estrogen may reduce the risk of arterial sclerosis. Maholonobis’ blog discusses how one article does not lead to conclusive findings on any topic:
last week, the (Wall Street) Journal did a story concentrating on how the Women’s Health Initiative (WHI) misread the data by focusing on the increased heart attack risk for women over 70, While neglecting the lowered rate of heart attack for women under 60 (since the WHI’s 2002 report arguing that estrogen therapy actually raised heart disease–opposite sign to previous findings–hormone sales plummeted 30%). The WHI shot back in a letter to the WSJ, arguing they stand by their interpretation of the data, which they think is somewhat mixed, and in their words, the differences in heart disease between the older and younger (one up, one down!) is not ‘statistically significant’. If the difference isn’t statistically significant, I can’t see how the old cohort can be thought to have a higher than average risk (eg, if the sample estimate for the old is +14%, for the young, -30%, if the difference is noise, the +14% is certainly noise). As Paul Feyerabend argued, there are no definitive tests in science, as people just ignore evidence that goes against them, emphasizing the consistent results.
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I think most big policy issues in science have a strong political subtext, and you don’t have to dig very far to see a group use science to rationalize their ‘bigger picture’ concern. This is why credibility is so important to science, because you just can’t trust a scientific paper, and it often takes too much time to read all the empirical literature in a debate.