The research, published in JNCI, the Journal of the National Cancer Institute, is a meta-analysis that brings together data from all eight randomised controlled trials of mammography screening ever conducted: the New York Health Insurance Plan trial, the Malmö trial, the Two-County trial, the Edinburgh trial, the Canadian National Breast Screening Study, the Stockholm trial, the Gothenburg trial and the UK Age trial. Rather than treating each trial as an isolated source of truth, the team reanalysed the pooled evidence against a real-world benchmark, using two Danish regional screening programmes as a reference population. The comparison included both invasive breast cancer and ductal carcinoma in situ, the non-invasive condition often picked up through calcifications on mammograms.

The central finding is striking in its simplicity. When the researchers accounted for the temporal dynamics of screening, the excess number of breast cancer cases detected in the randomised trials closely matched what would be expected in a Danish screening population, where overdiagnosis is estimated to be below five percent. In other words, the apparent surplus of cancers in the trials, which has long been cited as proof that overdiagnosis is a substantial problem, looks far more like the ordinary lead-time effect of finding cancers earlier than they otherwise would have been found.

Understanding why earlier estimates were so high requires a technical detour into how screening changes the timing of diagnosis. When a screening programme is introduced, the number of breast cancer diagnoses initially rises sharply, because cancers are detected earlier than they would have been without screening. Over time, this initial surge should be followed by a compensatory drop, as some of the cancers counted in the early period would otherwise have been diagnosed later in the absence of screening. If researchers fail to take this pattern into account, the temporary increase can be mistaken for overdiagnosis, inflating the estimate considerably.

Professor Elsebeth Lynge, professor emerita at the Department of Public Health at the University of Copenhagen, explained the mechanics behind the distortion. She noted that the pattern can also be affected if women in either the screening or control groups continue to undergo screening after the trials had ended, which was common in practice. Contamination of this kind blurs the boundary between the compared groups and can make the control group’s later diagnoses look like a shortfall rather than a delay. The Danish experience offered a natural laboratory for disentangling these effects, because organised screening was introduced in some Danish regions 17 years before others, allowing the researchers to observe how breast cancer diagnoses changed both when screening was introduced and over the longer term.

By comparing breast cancer incidence at identical timepoints in the trials and in Danish routine screening data, the team could examine how similar the observed patterns were and what that similarity implies for overdiagnosis estimates. The alignment between trial data and routine programme data suggests that the trials, when interpreted in their full temporal context, are consistent with overdiagnosis of less than five percent rather than with estimates approaching 50 percent. Matejka Rebolj, senior epidemiologist at Queen Mary University of London, said that some previous high estimates, which influenced screening guidelines and patient communication, were based on evidence gathered before trial data had fully matured.

The analysis also corrected for three structural differences between the trials that can skew overdiagnosis calculations. The first was whether women in the control groups were themselves screened, either after the trial ended or following the introduction of routine programmes, which erodes the contrast between screened and unscreened populations. The second was the number of screening rounds offered in each group, since more rounds provide more opportunities to detect cancers early and shift diagnoses forward in time. The third was the length of follow-up, because a longer observation period allows time for cancers detected early through screening to be diagnosed later in the control group, which is exactly what the lead-time model predicts. After accounting for these differences in screening intensity and follow-up between the groups, the results point to overdiagnosis being substantially less common than previously believed.

The definition of overdiagnosis itself deserves attention, because it is broader than many people assume. It occurs when screening detects a cancer that would never have become life-threatening or caused symptoms during a woman’s lifetime, meaning that without screening she would never have known she had it. It can also include women who die from other causes shortly after a breast cancer diagnosis, since poor health or limited life expectancy means these women were unlikely to benefit from early detection in the first place, as treating the cancer had little chance of improving their health or prolonging their lives. Distinguishing genuine overdiagnosis from cancers that were simply found earlier is therefore one of the hardest measurement problems in screening research, and it is precisely the problem the Danish reference data helped solve.

For Sisse Helle Njor, professor at the University of Southern Denmark and Lillebælt Hospital, the motivation was to bring together all the randomised evidence for a clearer picture. She observed that randomised trials have often been cited as evidence that overdiagnosis is a substantial problem, but that this interpretation is not as straightforward as it may seem. Her conclusion for women is direct: most women will not develop breast cancer, but the study offers reassurance that the benefits of detecting breast cancer early and preventing premature death will outweigh the small risk of unnecessary treatment. Accurate information about how often benefits and harms occur is essential for women weighing whether to attend screening, and the new figures suggest that the balance tilts more favourably than earlier communications implied.

The implications extend beyond the clinic into public health policy. Overdiagnosis estimates have shaped screening guidelines, invitation letters and the international debate about population-based mammography for decades, and figures as high as one in two screen-detected cancers have fuelled scepticism about organised programmes. If the matured trial data support estimates below five percent, the framework for communicating risk to invited women may need revision, and the researchers hope their analysis will provide a basis for a more realistic interpretation of the evidence. The work was supported by the Novo Nordisk Foundation and Cancer Research UK, and its publication in a leading oncology journal signals that the long-running controversy over mammography’s harms may be entering a more settled phase, one in which the fear of unnecessary treatment no longer overshadows the demonstrated capacity of screening to prevent deaths from breast cancer.

Subject of Research: Overdiagnosis in mammography screening estimated through a meta-analysis of randomised trials benchmarked against Danish screening data

Article Title: New analysis points to low overdiagnosis in breast cancer screening

Article References: New analysis points to low overdiagnosis in breast cancer screening. (n.d.). Original publication

Image Credits: AI Generated

DOI: Not provided

Keywords: breast cancer, mammography screening, overdiagnosis, meta-analysis, randomised controlled trials, lead-time bias, Danish screening programmes, ductal carcinoma in situ, cancer epidemiology, screening guidelines, JNCI, public health