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Background: The Huntington’s Disease Integrated Staging System (HD-ISS) has four stages that characterize disease progression. Classification is based on CAG length as a marker of Huntington’s disease (Stage 0), striatum atrophy as a biomarker of pathogenesis (Stage 1), motor or cognitive deficits as HD signs and symptoms (Stage 2), and functional decline (Stage 3). One issue for implementation is the possibility that not all variables are measured in every study, and another issue is that the stages are broad and may benefit from progression subgrouping. Objective: Impute stages of the HD-ISS for observational studies in which missing data precludes direct stage classification, and then define progression subgroups within stages. Methods: A machine learning algorithm was used to impute stages. Agreement of the imputed stages with the observed stages was evaluated using graphical methods and propensity score matching. Subgroups were defined based on descriptive statistics and optimal cut-point analysis. Results: There was good overall agreement between the observed stages and the imputed stages, but the algorithm tended to over-assign Stage 0 and under-assign Stage 1 for individuals who were early in progression. Conclusion: There is evidence that the imputed stages can be treated similarly to the observed stages for large-scale analyses. When imaging data are not available, imputation can be avoided by collapsing the first two stages using the categories of Stage≤1, Stage 2, and Stage 3. Progression subgroups defined within a stage can help to identify groups of more homogeneous individuals.

Huntington’s disease (HD) is a devastating neurodegenerative disorder that urgently needs disease-modifying therapeutics. To this end, collaboration to standardize clinical research practices in the field and drive progress in addressing drug development challenges is paramount. At a meeting in 2017 organized by CHDI Foundation and the Critical Path Institute, stakeholders across the pharmaceutical industry, academia, regulatory agencies, and patient advocacy groups discussed the need for and potential impact of a consortium dedicated to HD regulatory science. Consequently, the Huntington’s Disease Regulatory Science Consortium (HD-RSC) was formed, a precompetitive consortium that is dedicated to building a regulatory strategy to expedite the approval of HD therapeutics.

BackgroundDespite the monogenic autosomal dominant nature of Huntington’s disease (HD), the current research paradigm is still based on overt clinical phenotypes and does not address disease pathobiology and biomarkers that are evident decades before functional decline. A new research framework is needed to standardize clinical research and enable interventional studies earlier in the course of HD.MethodsThe HD Regulatory Science Consortium (HD-RSC), a precompetitive Critical Path Institute initiative that includes 37 member organizations, created the Regulatory Science Forum working group (RSF), which includes industry and academic representatives. To generate a new evidenced-based HD Integrated Staging System (HD-ISS) using a formal consensus methodology, the RSF considered prognostic biomarkers, signs, and symptoms of HD, and performed empirical data analysis. We used observational data to calculate healthy-control-based landmark variable cut-offs for Stage classification and to internally validate the framework.FindingsThe HD-ISS starts with Stage 0, which comprises individuals with ≥ 40 cytosine-adenine-guanine repeats (CAG) in the huntingtin gene (HTT), before detectable indications of disease. We concluded that detectable HD progression is verified with measurable indicators of underlying pathophysiology (Stage 1), proceeds to a detectable clinical phenotype (Stage 2), and continues to a decline in function (Stage 3). Operationally, individuals can be unambiguously classified into Stages 1-3 based on CAG-independent thresholds of landmark assessments. Both cross-sectional status and longitudinal HD-ISS Stage progress align with HD natural history, and Stage transitions accelerate as CAG increase.InterpretationThe HD-ISS encompasses the full course of HD starting at birth, defined by the presence of the genetic expansion. This new framework aims to standardize language for clinical research and its immediate use will enable further validation. The HD-ISS provides structure to harmonize clinical study populations and facilitates the clinical assessment of interventions earlier in HD to prevent or slow disease progression.FundingCHDI Foundation Inc.

Background HD is an inherited autosomal dominant neurodegenerative disease. While there is biological certainty that individuals with a pathogenic expansion in the huntingtin gene (HTT) will develop the signs and symptoms of HD within a normal lifespan, this is not reflected in present terminology. Current staging methods do not address disease progression before an overt clinical phenotype, despite well-accepted biomarkers of neurodegeneration predating clinical diagnosis. Aims To propose a new HD framework, referred to as the HD-ISS, that comprises an HD biological research definition and evidence-based staging centered on prognostic biological, clinical, and functional landmarks. Methods This framework is the result of a formal consensus process by the HD-RSC’s Regulatory Science Forum (RSF), a working group of expert representatives from industry and academia. Observational data was employed to calculate ‘cut-offs’ using the extreme values in models of the control population to define the HD-ISS Stages and to evaluate the framework. Results The HD-ISS defines HD biologically as the presence of the expanded HTT gene. The HD-ISS landmarks demonstrate robust prognostic value to classify individuals into each Stage and data-driven landmark thresholds to define Stage boundaries that are not CAG-dependent. Individual study visits, participant Stage progression, and longitudinal models of Stage progression align with the natural history of HD and with increased CAG predicting accelerated transitions. Conclusions The RSF has developed a biological definition of HD and an evidence-based staging system that encompass the full course of the disease and are unconstrained by concepts such as ‘manifest’ or ‘pre-manifest.’ The HD-ISS is intended for research settings to allow clinical trials earlier in the disease course, and provides a new structure to anchor and harmonize clinical study populations. The immediate use of the HD-ISS will allow for further validation.