Recalibrating evidence hierarchies in populous low- and middle-income countries: Opportunity cost, epistemic alignment, and the overproduction of systematic reviews.

Systematic reviews and meta-analyses (SR-MA) occupy the apex of evidence hierarchies within evidence-based medicine (EBM). Their rapid proliferation over the past three decades has strengthened guideline development and policy formulation but has also generated concerns regarding redundancy, structural bias, and disproportionate prioritization, particularly in low- and middle-income countries (LMICs). To critically examine the overproduction and over prioritization of SR-MA in populous LMIC contexts through the lenses of opportunity cost, epistemic alignment, and global research inequities. A narrative critical review with conceptual synthesis was conducted using structured searches of PubMed/MEDLINE, Scopus, and Google Scholar (January 2024-February 2026). Literature addressing systematic review proliferation, methodological redundancy, publication bias, language bias, authorship inequity, research incentives, and methodological pluralism was included. Interpretive thematic synthesis was undertaken. Rapid expansion of SR-MA has been accompanied by overlapping reviews, variable methodological rigor, and structural biases, including publication and language bias. In LMIC research ecosystems, excessive emphasis on SR-MA may generate opportunity costs by diverting intellectual labour away from primary investigation, pragmatic trials, and translational innovation. Illustrative case studies from North India demonstrate how locally conducted primary research can drive institutional redesign, service innovation, and culturally adapted implementation outcomes not achievable through aggregation alone. While systematic reviews remain indispensable, disproportionate prioritization in populous LMICs risks underutilizing demographic and epidemiological advantage. Recalibrating incentive structures to restore equilibrium between synthesis and discovery is essential for sustainable and context-sensitive global health knowledge production.