RESUMO
We previously reported a basic algorithm to identify the risk of Parkinson's disease (PD) using published data on risk factors and prodromal features. Using this algorithm, the PREDICT-PD study identified individuals at increased risk of PD and used tapping speed, hyposmia and REM sleep behaviour disorder (RBD) as "intermediate" markers of prodromal PD in the absence of sufficient incident cases. We have now developed and tested an enhanced algorithm which incorporates the intermediate markers into the risk model. Risk estimates were compared using the enhanced and the basic algorithm in members of the PREDICT-PD pilot cohort. The enhanced PREDICT-PD algorithm yielded a much greater range of risk estimates than the basic algorithm (93-609-fold difference between the 10th and 90th centiles vs 10-13-fold respectively). There was a greater increase in the risk of PD with increasing risk scores for the enhanced algorithm than for the basic algorithm (hazard ratios per one standard deviation increase in log risk of 2.75 [95% CI 1.68-4.50; p < 0.001] versus 1.47 [95% CI 0.86-2.51; p = 0.16] respectively). Estimates from the enhanced algorithm also correlated more closely with subclinical striatal DaT-SPECT dopamine depletion (R2 = 0.164, p = 0.005 vs R2 = 0.043, p = 0.17). Incorporating the previous intermediate markers of prodromal PD and using likelihood ratios improved the accuracy of the PREDICT-PD prediction algorithm.
RESUMO
BACKGROUND: Hyposmia can develop with age and in neurodegenerative conditions, including Parkinson's disease (PD). The University of Pennsylvania Smell Identification Test (UPSIT) is a 40-item smell test widely used for assessing hyposmia. However, in a number of situations, such as identifying hyposmic individuals in large populations, shorter tests are preferable. METHODS: We assessed the ability of shorter UPSIT subsets to detect hyposmia in 891 healthy participants from the PREDICT-PD study. Shorter subsets included Versions A and B of the 4-item Pocket Smell Test (PST) and 12-item Brief Smell Identification Test (BSIT). Using a data-driven approach, we evaluated screening performances of 23,231,378 combinations of 1-7 smell items from the full UPSIT to derive "winning" subsets, and validated findings separately in another 191 healthy individuals. We then compared discriminatory UPSIT smells between PREDICT-PD participants and 40 PD patients, and assessed the performance of "winning" subsets containing discriminatory smells in PD patients. RESULTS: PST Versions A and B achieved sensitivity/specificity of 76.8%/64.9% and 86.6%/45.9%, respectively, while BSIT Versions A and B achieved 83.1%/79.5% and 96.5%/51.8%. From the data-driven analysis, 2 "winning" 7-item subsets surpassed the screening performance of 12-item BSITs (validation sensitivity/specificity of 88.2%/85.4% and 100%/53.5%), while a "winning" 4-item subset had higher sensitivity than PST-A, -B, and even BSIT-A (validation sensitivity 91.2%). Interestingly, several discriminatory smells featured within "winning" subsets, and demonstrated high-screening performances for identifying hyposmic PD patients. CONCLUSION: Using abbreviated smell tests could provide a cost-effective means of large-scale hyposmia screening, allowing more targeted UPSIT administration in general and PD-related settings.
