Systematic Review on the Clinical Utility of Biomarkers in Early Diagnosis and Prognosis of Human Diseases

Abstract

Background: Biomarkers may improve early diagnosis and prognostic stratification across human diseases, but translation into clinical practice remains inconsistent. Objective: To systematically evaluate evidence on diagnostic and prognostic utility and clinical readiness of biomarkers across diverse disease domains. Methods: A systematic review of systematic reviews and meta-analyses was conducted using PubMed, Scopus, and Google Scholar. Ten eligible reviews (2008–2024) were included after predefined screening. Data were synthesized narratively due to heterogeneity in diseases, biomarker platforms, matrices, and validation stages. Results: Biomarker clinical utility demonstrated marked heterogeneity driven by validation maturity and biological context. Alzheimer’s disease CSF biomarkers (T-tau, P-tau, Aβ42, NFL) showed the strongest readiness for clinical implementation, supported by large meta-analytic evidence (15,699 patients and 13,018 controls) with robust disease–control separation (e.g., CSF T-tau ratio 2.54; P-tau ratio 1.88; Aβ42 ratio 0.56; all p<0.0001). Promising candidates in other domains remained in early validation or discovery phases, including pancreatic cancer microRNA panels with sensitivity and specificity exceeding 90%, uterine disease metabolomics models with AUC up to 0.99, and acute kidney injury biomarkers such as cystatin C, KIM-1, IL-18, and NGAL. Endometriosis peripheral biomarkers demonstrated persistent validation failure despite extensive candidate identification. Conclusion: Biomarkers are clinically implementable only in select contexts, while most candidates require external validation, assay standardization, and demonstration of incremental value over existing clinical pathways before routine adoption.