Statistical Ethics in Medical Research: A Narrative Review

Abstract

Bioethics necessitates the meticulous planning, application and interpretation of statistics in medical research. However, the pervasive misapplication and misinterpretation of statistical methods pose significant challenges. Common errors encompass p-hacking, misconceptions regarding statistical significance, neglecting to address study limitations and failing to evaluate data fragility. Historically, such statistical missteps have led to regrettable and severe adverse health outcomes for society. For instance, prominent research on hormone replacement therapy likely resulted in an increased incidence of heart attacks, strokes and cardiovascular death in postmenopausal women, rectified only after the errors were identified. Likewise, past vaccine trials have oscillated between overemphasizing and underemphasizing side effects, resulting in public harm. This narrative review scrutinizes prevalent statistical errors and presents historical case examples. Recommendations for future research include: a) ethical review boards should incorporate a more rigorous evaluation of statistical methodologies in their assessment of clinical trial proposals; b) journals should mandate that research data become open-access rather than proprietary to allow for improved post-publication peer review; and c) in addition to addressing study limitations, articles should encompass a discussion of the ethical ramifications of their findings.