Randomized controlled trials (RCTs) show that few of the currently available screening tests for major diseases where death is a common outcome have documented reductions in disease-specific mortality, according to a new study published online in the International Journal of Epidemiology.
Senior author Dr. John Ioannidis, of Stanford University, and colleagues examined evidence for 39 screening tests from 48 RCTs and nine meta-analyses identified via the Cochrane Database of Systematic Reviews and PubMed. Their goal was to determine whether screening asymptomatic adults for major disease led to a decrease in disease-specific and all-cause mortality.
Randomized controlled trial data were available for 19 tests for 11 diseases, including abdominal aortic aneurysms, breast cancer, cervical cancer, colorectal cancer, hepatocellular cancer, lung cancer, oral cancer, ovarian cancer, prostate cancer, type 2 diabetes, and cardiovascular disease (Int J Epidemiol, January 15, 2015).
There was evidence of a reduction in mortality in only 30% of the disease-specific mortality estimates and 11% of the all-cause mortality estimates from the RCTs evaluated, according to Ioannidis and colleagues. Findings from the individual RCTs for disease-specific mortality were supported by evidence from four meta-analyses, but none of the six meta-analyses that included estimates of all-cause mortality showed evidence of a reduction in mortality.
RCT evidence should be considered on a case-by-case basis, depending on the disease, Ioannidis and colleagues concluded. They noted that screening is likely to be effective and justifiable for a variety of other clinical outcomes besides mortality.
![A normal mammogram confirmed by three-year radiologic follow-up illustrates reader-marked regions of interest (ROIs) during (A) unaided (round 1) and (B) artificial intelligence (AI)–assisted (round 2) reading. Each colored dot represents an ROI for recall by a human reader. Readers could mark more than one ROI per case, represented by multiple dots of the same color. During AI-assisted reading, the AI system displayed three visible prompts: two with suspicion of malignancy scores of 35% (left mediolateral oblique [L MLO] and craniocaudal [L CC]) and one with a suspicion of malignancy score of 10% (right craniocaudal [R CC]), shown as polygonal overlays. Without AI, six of 10 readers (60%) marked a false-positive ROI. With AI assistance, this fell to two of 10 (20%). R MLO = right mediolateral oblique.](https://img.auntminnie.com/mindful/smg/workspaces/default/uploads/2026/07/2026-07-14-radiology-mammogram-ai-auto-bias.H0bYO8QlWs.jpg?auto=format%2Ccompress&fit=crop&h=100&q=70&w=100)







![A normal mammogram confirmed by three-year radiologic follow-up illustrates reader-marked regions of interest (ROIs) during (A) unaided (round 1) and (B) artificial intelligence (AI)–assisted (round 2) reading. Each colored dot represents an ROI for recall by a human reader. Readers could mark more than one ROI per case, represented by multiple dots of the same color. During AI-assisted reading, the AI system displayed three visible prompts: two with suspicion of malignancy scores of 35% (left mediolateral oblique [L MLO] and craniocaudal [L CC]) and one with a suspicion of malignancy score of 10% (right craniocaudal [R CC]), shown as polygonal overlays. Without AI, six of 10 readers (60%) marked a false-positive ROI. With AI assistance, this fell to two of 10 (20%). R MLO = right mediolateral oblique.](https://img.auntminnie.com/mindful/smg/workspaces/default/uploads/2026/07/2026-07-14-radiology-mammogram-ai-auto-bias.H0bYO8QlWs.jpg?auto=format%2Ccompress&fit=crop&h=112&q=70&w=112)









