Epidemiologists are well aware of the negative consequences of measurement error in exposure and outcome variables to their ability to detect putative causal associations. However, empirical proof that remedying the misclassification problem improves estimates of epidemiologic effect is seldom examined in detail. Of all areas in cancer epidemiology, perhaps the best example of the consequences of misclassification and of the steps taken to circumvent them was the pursuit, beginning in the mid-1980s, of the human papillomavirus (HPV) infection–cervical cancer association. The stakes were high: Had the wrong conclusions been reached epidemiologists would have been led astray in the search for competing hypotheses for the sexually transmissible agent causing cervical cancer or in ascribing to HPV infection a mere ancillary role among many lifestyle, hormonal, and environmental factors. The article by Castle et al. in this issue of the Journal (Am J Epidemiol. 2010;171(2):155–163) provides a detailed account of the joint influences of improved HPV and cervical precancer measurements in gradually unveiling the strong magnitude of the underlying association between viral exposure and cervical lesion risk. In this commentary, the authors extend the findings of Castle et al. by providing additional empirical evidence in support of their arguments.