Validation of a prognostic index for Huntington's disease

Characterizing progression in Huntington's disease is important for study the natural course and selecting appropriate participants for clinical trials.

The aim was to develop a prognostic index for motor diagnosis in Huntington's disease and examine its predictive performance in external observational studies.

The prediagnosis Neuro-biological Predictors of Huntington's Disease study (N = 945 gene-positive) was used to select a Cox regression model for computing a prognostic index. Cross-validation was used for selecting a model with good internal validity performance using the research sites as natural splits of the data set. Then, the external predictive performance was assessed using prediagnosis data from three additional observational studies, The Cooperative Huntington Observational Research Trial (N = 358), TRACK-HD (N = 118), and REGISTRY (N = 480).

Model selection yielded a prognostic index computed as the weighted combination of the UHDRS total motor score, Symbol Digit Modalities Test, baseline age, and cytosine-adenine-guanine expansion. External predictive performance was very good for the first two of the three studies, with the third being a much more progressed cohort than the other studies. The databases were pooled and a final Cox regression model was estimated. The regression coefficients were scaled to produce the prognostic index for Huntington's disease, and a normed version, which is scaled relative to a 10-year 50% probability of motor diagnosis.

The positive results of this comprehensive validity analysis provide evidence that the prognostic index is generally useful for predicting Huntington's disease progression in terms of risk of future motor diagnosis. The variables for the index are routinely collected in ongoing observational studies and the index can be used to identify cohorts for clinical trial recruitment. © 2016 International Parkinson and Movement Disorder Society.