Peer review of prediction model studies in oncology needs improvement: A systematic review of open peer review reports from BMC journals

Abstract

Our findings show that peer reviews of prediction models lack depth, methodological scrutiny, and enforcement of reporting standards. This risks clinical harm from biased models and perpetuates research waste. Reforms are urgently needed, including implementing reporting guidelines (eg, TRIPOD+AI), mandatory reviewer training, and recognition of peer review as scholarly labor. Journals must prioritize methodological rigor in reviews to ensure reliable prediction models and safeguard patient care.

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