Redefining the Accuracy of clinical diagnosis of Parkinson’s disease: A Systematic Review and Meta-analysis

Background: Accurate diagnosis of Parkinson’s disease (PD) remains a clinical challenge, particularly at the initial clinical assessment. Despite the introduction of MDS-PD diagnostic criteria almost a decade ago to address the limitations of earlier frameworks, their comparative performance and diagnostic precision have yet to be fully clarified. Methods: We systematically reviewed studies evaluating the accuracy of clinical PD diagnosis based on UKPDSBB, Gelb, and MDS-PD 2015 criteria, using neuropathological confirmation as the reference standard. Bayesian bivariate random-effects models were employed to estimate the pooled sensitivity and specificity for diagnoses made at the initial clinical assessment and at the final recorded clinical diagnosis. Results: Twelve studies (n = 9,659) met the inclusion criteria. At the initial assessment, pooled sensitivity was 57% and specificity was 76%, with substantial heterogeneity. At the final assessment, sensitivity and specificity were higher (87% and 89%, respectively). Among criteria evaluated at the final assessment, UKPDSBB yielded the highest sensitivity (91%), while MDSPD 2015 criteria achieved the highest specificity. Meta-regression revealed a temporal trend towards enhanced specificity in recent decades, accompanied by a modest decrease in sensitivity. Conclusions: The accuracy of clinical PD diagnosis depends strongly on the timing of assessment and is limited at the initial evaluation. Although available evidence suggests that the MDS-PD 2015 categories may favor specificity, these findings are based on a limited number of studies and require further clinicopathological validation. Integrating objective biomarkers is essential to improve diagnostic reliability and support patient selection for early-intervention trials.