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 = 9659) 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 MDS-PD 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.