Objective: To validate an MDS-UPDRS component score for predicting conversion to freezing of gait in Parkinson’s disease.
Background: Freezing of gait (FOG) is a debilitating gait disorder in Parkinson’s disease (PD) that shows a variable response to medication1 and physiotherapy2. For both clinical management and research stratification, a valid prediction tool for detecting patients at risk of conversion is essential. Previous work showed that a specific MDS-UPDRS component was a consistent predictor of FOG in mid-stage PD3. Here, we validated this FOG-component score as a predictive tool in the PPMI de-novo cohort.
Method: MDS-UPDRS and demographic data of the PPMI PD cohort (424 participants) was downloaded in July 2018. Time point of conversion to FOG was defined as the first visit with an MDS-UPDRS score > 0 on either item 2.13 (self-report FOG) or 3.11 (observed FOG in OFF), resulting in 153 converters during the 5-year follow-up. FOG-component score was calculated as the aggregate of 13 items. Linear mixed models evaluated progression in the FOG-component score, while logistic regression models at each visit evaluated prediction performance of conversion at the following visit. Linear and quadratic effects of age, and gender were used as covariates in all models.
Results: Significant interaction effects were found with a faster rate of progression in FOG-component score for converters versus non-converters (F(1,3139)=60.05, p<0.0001, β = 0.049 points/month, CI = 0.037 – 0.062). Logistic regression revealed that FOG-component score was a significant predictor of conversion at the following visit (average over 13 visits- odds ratio: 1.25, CI = 1.19 – 1.3, p = 0.011) and models had an average area under the curve of 0.80 (CI = 0.77 – 0.84), indicating that performance was fair to good. Importantly, the model was able to discriminate between converters and non-converters from the baseline visit until study completion.
Conclusion: The FOG-component score showed faster progression in converters and was a significant predictor of FOG conversion within the first five years in de-novo PD. These findings validate the predictive ability of the FOG-component, further work is required to refine the model to bring it to clinical use.
References: 1: Lucas McKay, J., Goldstein, F.C., Sommerfeld, B. et al. Freezing of Gait can persist after an acute levodopa challenge in Parkinson’s disease. npj Parkinsons Dis. 5, 25 (2019). https://doi.org/10.1038 2: Cosentino, C., Baccini, M., Putzolu, M., Ristori, D., Avanzino, L. and Pelosin, E. (2020), Effectiveness of Physiotherapy on Freezing of Gait in Parkinson’s Disease: A Systematic Review and Meta‐Analyses. Mov Disord. doi:10.1002/mds.27936 3: D’Cruz, Nicholas et al. ‘Repetitive Motor Control Deficits Most Consistent Predictors of Conversion to Freezing of Gait in Parkinson’s Disease: A Prospective Cohort Study’. 1 Jan. 2020 : 1 – 13.
To cite this abstract in AMA style:N. D'Cruz, W. Vandenberghe, A. Nieuwboer. Validation of MDS-UPDRS-based score to predict conversion to freezing of gait in Parkinson’s disease [abstract]. Mov Disord. 2020; 35 (suppl 1). https://www.mdsabstracts.org/abstract/validation-of-mds-updrs-based-score-to-predict-conversion-to-freezing-of-gait-in-parkinsons-disease/. Accessed December 11, 2023.
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