30-Second Takeaway
- Medical AI clinical evidence is largely preclinical; **only 2.4%** of primary AI studies were RCTs.
- EMR-integrated family history collection can identify previously unrecognized inherited cancer risk during routine visits.
- HF drug efficacy appears similar between sexes despite persistent female underrepresentation.
Latest - Week ending May 2, 2026
Selected recent evidence briefs for general internists
Most medical AI studies are preclinical; RCT evidence is scarce and concentrated geographically.
A scoping review of 218 systematic reviews identified 4667 primary AI studies, of which 88.2% were preclinical and 2.4% were RCTs. RCTs were geographically concentrated, with the top 10 countries contributing 75.5% and the US and China contributing 47.5%. Among RCTs, 67.3% were single-center and 71.7% did not report adherence to reporting guidelines. Authors report 82.3% of RCTs had favorable outcomes but note frequent methodological concerns in allocation concealment and blinding.
EMR-integrated risk assessment identified additional patients meeting guidelines for genetic counseling.
In a single-arm EMR-integrated trial, 1685 consented patients were offered a 24-syndrome family health history assessment and 636 completed it. Of completers, 155 (28.5%) met guideline criteria for genetic counseling, and only 31 attended counseling. About half (47.7%) of those meeting criteria had previously been identified by billing codes, showing added case-finding value. The intervention increased identification of at-risk adults in routine primary care but produced modest downstream counseling uptake.
Cancer drug trials in China commonly use restrictive eligibility beyond NCI guidance.
Reviewing 2448 registered cancer drug trials (2013–2021) found 97.0% applied at least one eligibility criterion considered restrictive versus NCI guidance. Median restrictive criteria per trial rose from 2 (IQR 1–3) in 2013–2015 to 3 (IQR 2–4) by 2019–2021. Use of restrictive rules increased over time for performance status, cardiac function, and prior/concurrent malignancies. Authors conclude narrower eligibility likely reduces generalizability and call for more inclusive, modernized criteria.
References
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Additional Reads
Optional additional studies from this edition.