Reanalysis: lessons great and small

Debate and critique are fundamental to the scientific method. The closest scientists ever get to “proof” is the persistence of a hypothesis after repeated attempts to refute it. For this reason, free exchange of opinions about the interpretation of data is essential. In epidemiology, it can be useful to challenge a study’s conclusions by conducting a reanalysis of the data, with new investigators starting from different assumptions and using different methods. Consistent findings can strengthen confidence in the conclusions, as in the Health Effects Institute’s reanalysis of the Harvard Six Cities and American Cancer Society air pollution studies.1 2 But reanalysis can also create confusion and impede scientific progress if it is not done in the service of impartial inquiry. After initial comments on an important reanalysis of a study of beryllium and lung cancer in this issue (see page 379), I will step back to consider broader themes in reanalysis: why it is done, and the problem of conflicts of interest.

Schubauer-Berigan and colleagues3 conducted a reanalysis of a nested case–control study of beryllium and lung cancer originally published by Sanderson and colleagues.4 The reanalysis makes a valuable contribution by strengthening the original study’s finding of an association between beryllium and lung cancer. The authors investigated potential confounding and effect modification by birth year, and assessed the findings’ sensitivity to a small but potentially important methodological choice …