SPES/SCOPA and MDS-UPDRS: Formulas for converting scores of two motor scales in Parkinson’s disease

Verbaan, Dagmar; Rooden, Stephanie M. van; Benit, C; Zwet, Erik W. van; Marinus, Johan; Hilten, J.J. van

doi:10.1016/j.parkreldis.2011.05.022

Cited by 30 publications

(28 citation statements)

References 11 publications

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“…Cohort-specific definitions of Parkinson’s disease dementia were used (appendix table 1). The MDS-Unified PD Rating Scale (UPDRS) part II and III scores were obtained from four cohorts, and estimated for the five remaining cohorts using the UPDRS or SPES/SCOPA-motor scales 18 based on published conversion formulas 19,20 (table 1). Hoehn and Yahr scales (HY) 14 were longitudinally collected in all cohorts.…”

Section: Methodsmentioning

confidence: 99%

See 1 more Smart Citation

Prediction of cognition in Parkinson's disease with a clinical–genetic score: a longitudinal analysis of nine cohorts

Liu¹,

Locascio²,

Corvol³

et al. 2017

The Lancet Neurology

149

157

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Summary Background Cognitive decline is a debilitating manifestation of disease progression in Parkinson’s disease. We aimed to develop a clinical-genetic score to predict global cognitive impairment in patients with the disease. Methods A prediction algorithm for global cognitive impairment (defined as Mini Mental State Exam (MMSE) ≤25) was built using data from 1,350 patients with 5,165 longitudinal visits over 12.8 (median, 2.8) years. Age at onset, MMSE, education, motor exam score, gender, depression and GBA mutations, machine selected through stepwise Cox’ hazards analysis and Akaike’s information criterion, were used to compute the multivariable predictor. Independent validation was achieved in another 1,132 patients with 19,127 visits over 8.6 (median, 6.5) years. Findings The cognitive risk score accurately predicted cognitive impairment within ten years of disease onset with an area under the curve (AUC) of >0.85 in both the discovery (95% CI, 0.821–0.902) and validation populations (95% CI, 0.779 – 0.913). 72.6% of patients scoring in the highest quartile were cognitively impaired by ten years vs. 3.7% in the lowest quartile (hazard ratio, 18.4, 95% CI, 9.4 – 36.1). Dementia or disabling cognitive impairment was predicted with an AUC of 0.877 (95% CI 0.788–0.943) and high negative predictive value (0.920, 95% 0.877–0.954) at the predefined cutoff (0.196). Performance was stable in 10,000 randomly resampled subsets. Interpretation Our predictive algorithm provides a potential test for future cognitive health or impairment in patients with Parkinson’s. It could improve trials of cognitive interventions and inform on prognosis.

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Section: Methodsmentioning

confidence: 99%

“…The SPES/SCOPA-motor scale was converted into MDS-UPDRS III score according to Ref. 20 . The MoCA from PDBP and PPMI was converted into MMSE score according to Ref.…”

Section: Figurementioning

confidence: 99%

Prediction of cognition in Parkinson's disease with a clinical–genetic score: a longitudinal analysis of nine cohorts

Liu¹,

Locascio²,

Corvol³

et al. 2017

The Lancet Neurology

149

157

View full text Add to dashboard Cite

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“…The results suggest that the mobility, ADL, and bodily discomfort domains of the PDQ-39 are also related to motor signs of PD in addition to motor difficulties of daily living. PD motor features are frequently evaluated to help healthcare professionals understand the response to dopaminergic therapy [42]. Our findings suggest that the PDQ-39 may be a more responsive tool than the SF-36 for reflecting HRQoL changes related to motor signs.…”

Section: Discussionmentioning

confidence: 90%

Determinants of generic and specific health-related quality of life in patients with Parkinson’s disease

Hwang

Ing

et al. 2017

PLoS ONE

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ObjectivesGeneric and disease-specific health-related quality of life (HRQoL) instruments may reflect different aspects of lives in patients with Parkinson’s disease (PD) and thus be associated with different determinants. We used the same cluster of predictors for the generic and disease-specific HRQoL instruments to examine and compare the determinants of HRQoL.MethodHRQoL was measured in 92 patients with PD by the 36-item Short-Form Health Survey (SF-36) and the 39-item Parkinson’s Disease Questionnaire (PDQ-39). The predictors included demographic and disease characteristics, and motor and non-motor symptoms. Multiple regression analyses were used to identify HRQoL determinants.ResultsDepressive symptoms and motor difficulties of daily living were the first two significant determinants for both instruments. The other significant determinant for the SF-36 was fatigue and non-motor difficulties of daily living, and for the PDQ-39 was motor signs of PD.ConclusionsThe results suggest the importance of the evaluation and intervention focused on depressive symptoms and motor difficulties of daily living in patients with PD. In addition, the SF-36 seems more related to non-motor symptoms, while the PDQ-39 appears more associated with motor symptoms. This information is important for understanding results from these two instruments and for choosing which to use.

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“…MDS-UPDRS has reported excellent factor validity [63]. However, the MDS-UPDRS takes a long time, which causes difficulty in clinical and research settings [64]. The included articles used the UPDRS as the inclusion criteria, except one article using both UPDRS and MDS-UPDRS.…”

Section: Discussionmentioning

confidence: 99%

Comparison of the Efficacy of Different Drugs on Non-Motor Symptoms of Parkinson’s Disease: a Network Meta-Analysis

Li¹,

Cui²,

Song³

et al. 2018

Cell Physiol Biochem

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Background/Aims: A network meta-analysis is used to compare the efficacy of ropinirole, rasagiline, rotigotine, entacapone, apomorphine, pramipexole, sumanirole, bromocriptine, piribedil and levodopa, with placebo as a control, for non-motor symptoms in Parkinson’s disease (PD). Methods: PubMed, Embase and the Cochrane Library were searched from their establishment dates up to January 2017 for randomized controlled trials (RCTs) investigating the efficacy of the above ten drugs on the non-motor symptoms of PD. A network meta-analysis combined the evidence from direct comparisons and indirect comparisons and evaluated the pooled weighted mean difference (WMD) values and surfaces under the cumulative ranking curves (SUCRA). The network meta-analysis included 21 RCTs. Results: The analysis results indicated that, using the United Parkinson’s Disease Rating Scale (UPDRS) III, the efficacies of placebo, ropinirole, rasagiline, rotigotine, entacapone, pramipexole, sumanirole and levodopa in treating PD were lower than that of apomorphine (WMD = -10.90, 95% CI = -16.12∼-5.48; WMD = -11.85, 95% CI = -17.31∼-6.16; WMD = -11.15, 95% CI = -16.64∼-5.04; WMD = -11.70, 95% CI = -16.98∼-5.60; WMD = -11.04, 95% CI = -16.97∼-5.34; WMD = -13.27, 95% CI = -19.22∼-7.40; WMD = -10.25, 95% CI = -15.66∼-4.32; and WMD = -11.60, 95% CI = -17.89∼-5.57, respectively). Treatment with ropinirole, rasagiline, rotigotine, entacapone, pramipexole, sumanirole, bromocriptine, piribedil or levodopa, with placebo as a control, on PD exhibited no significant differences on PD symptoms when the UPDRS II was used for evaluation. Moreover, using the UPDRS III, the SUCRA values indicated that a pomorphine had the best efficacy on the non-motor symptoms of PD (99.0%). Using the UPDRS II, the SUCRA values for ropinirole, rasagiline, rotigotine, entacapone, pramipexole, sumanirole, bromocriptine, piribedil and levodopa treatments, with placebo as a control, indicated that bromocriptine showed the best efficacy on the non-motor symptoms of PD (75.6%). Conclusion: Among ropinirole, rasagiline, rotigotine, entacapone, apomorphine, pramipexole, sumanirole, bromocriptine, piribedil and levodopa, with placebo as a control, apomorphine may be the most efficacious drug for therapy in treating the non-motor symptoms of PD.

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SPES/SCOPA and MDS-UPDRS: Formulas for converting scores of two motor scales in Parkinson’s disease

Abstract: With the equation models identified in this study, scores from SPES/SCOPA-motor can be converted to scores from MDS-UPDRS motor examination and vice versa.

Cited by 30 publications

References 11 publications

Prediction of cognition in Parkinson's disease with a clinical–genetic score: a longitudinal analysis of nine cohorts

Prediction of cognition in Parkinson's disease with a clinical–genetic score: a longitudinal analysis of nine cohorts

Determinants of generic and specific health-related quality of life in patients with Parkinson’s disease

Comparison of the Efficacy of Different Drugs on Non-Motor Symptoms of Parkinson’s Disease: a Network Meta-Analysis

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