Earlier this week researchers from Norway, led by Dr Michael Bretthauer (seen right), published a paper in JAMA Internal Medicine entitled “Estimated lifetime gained with cancer screening tests: a meta-analysis of randomized clinical trials.” One of their main findings was that current evidence does not substantiate the claim that common cancer screening tests – such as mammography – saves lives by extending lifetime. Not surprisingly, there has been a deluge of responses from a range of experts criticizing the study, with Dr Daniel Kopans of Harvard commenting, “It is unclear how papers such as this pass peer review.”

One of the primary criticisms levelled at the research is the end point – “all-cause mortality” rather than “dying from breast cancer.” Dr Mary Newell from Atlanta, who is president of the Society of Breast Imaging, said this was an impractical and unfair test. She imagined herself speaking to a patient: “I have good news and bad news about screening mammograms. The good news is that women who undergo routine screening are up to 48% less likely to die of breast cancer. The bad news is it can’t prevent your neighbour from getting hit by a bus. So, I think we should skip your mammogram.”

Dr Perry Wilson from Yale (seen left, © MedScape) who writes a weekly column entitled “Impact Factor”, was also critical of the paper. Since a meta-analysis is a statistical analysis that combines the results of multiple scientific studies, Wilson pointed out a major problem with the research: it relied on only two randomized trials of mammography screening and one of these from Canada had fundamental flaws, including questions about patient selection, poor quality images, and inadequately trained radiologists.

Interestingly, the other research included in the analysis was a 1989 paper by Dr László Tabár from Sweden (seen below right) who commented that all-cause mortality can give “seriously misleading results.” In fact, he published a paper in the Journal of Medical Screening in 2002 in which he argued that breast cancer mortality was a far more appropriate end point than all-cause mortality.

Both Kopans and Newell pointed out that it would be necessary to enrol millions of participants in a randomized clinical trial to prove statistically significant reductions in all-cause mortality. Clearly that is not feasible, with Kopans commenting, “While we wait for a universal cure, instead of wasting time and resources devising ‘alternative facts,’ we should be developing better ways to detect more breast cancers at a time when cure is possible.”