Early-Life Social Determinants of SCA6 Age at Onset, Severity, and Progression.

SCA6 patients with the same size CAG repeat allele can vary significantly in age at onset (AAO) and clinical progression. The specific external factors affecting SCA6 have yet to be investigated. We assessed the effect of early life events on AAO, severity, and progression in SCA6 patients using a social determinant of health approach. We performed a survey of biological and social factors in SCA6 patients enrolled in the SCA6 Network at the University of Chicago. AAO of ataxia symptoms and patient-reported outcome measure (PROM) of ataxia were used as primary outcome measures. Least absolute shrinkage and selection operation (LASSO) regressions were used to identify which early life factors are predictive of SCA6 AAO, severity, and progression. Multiple linear regression models were then used to assess the degree to which these determinants influence SCA6 health outcomes. A total of 105 participants with genetically confirmed SCA6 completed the assessments. SCA6 participants with maternal difficulty during pregnancy, active participation in school sports, and/or longer CAG repeats were determined to have earlier AAO. We found a 13.44-year earlier AAO for those with maternal difficulty in pregnancy than those without (p = 0.008) and a 12.31-year earlier AAO for those active in school sports than those who were not (p < 0.001). Higher education attainment was associated with decreased SCA6 severity and slower progression. Early life biological and social factors can have a strong influence on the SCA6 disease course, indicating that non-genetic factors can contribute significantly to SCA6 health outcomes.

Development and Validation of a Patient-Reported Outcome Measure of Ataxia.

BACKGROUND: Assessment of cerebellar ataxia has been confined to rating scales, gait laboratories, and wearable sensors agnostic to patient input. OBJECTIVES: The objective of this study was to develop a Patient-Reported Outcome Measure of Ataxia. METHODS: (1) The conceptual framework, item pool development, and domain selection were developed using online surveys completed by 147 ataxia patients. Responses generated the 70-item Patient-Reported Outcome Measure of Ataxia, scored on a 0-4 Likert scale. (2) Cognitive debrief in 17 patients grouped by ataxia severity assessed content validity, readability, and comprehension. (3) Psychometric validation by 78 anonymized ataxia patients included test-retest reliability, responsiveness to ataxia severity, internal consistency (Cronbach's alpha), and item-total score correlations. (4) Validation was tested against measures of ataxia and quality of life in 20 patients. (5) Items were rank-ordered to develop the Patient-Reported Outcome Measure of Ataxia Short Form. RESULTS: Three thousand eight hundred fifty-five symptoms were grouped into 3 domains (physical, activities of daily living, mental health) and 14 subdomains. The Patient-Reported Outcome Measure of Ataxia was comprehensible, important, and relevant. Internal consistency, reliability, and test-retest reliability were high. Scores were responsive to ataxia severity stages 1, 2, and 3: mean ± standard deviation 81.0 ± 37.0, 129.6 ± 32.0, and 151.1 ± 41.3, respectively (r = 0.58, P < 0.0001). The Patient-Reported Outcome Measure of Ataxia was validated against measures of motor ataxia, quality of life, and mental health. It had an R2 of 0.82 (P < 0.0001) with the preliminary Patient-Reported Outcome Measure of Ataxia Short Form. CONCLUSIONS: The Patient-Reported Outcome Measure of Ataxia is valid and reliable in cerebellar ataxia patients. It has the potential to improve patient care and natural history studies and quantify the efficacy of novel therapeutics in clinical trials. © 2021 International Parkinson and Movement Disorder Society.

Projecting long-term graft and patient survival after transplantation.

OBJECTIVE: In spite of increases in short-term kidney transplant survival rates and reductions in acute rejection rates, increasing long-term graft survival rates remains a major challenge. The objective here was to project long-term graft- and survival-related outcomes occurring among renal transplant recipients based on short-term outcomes including acute rejection and estimated glomerular filtration rates observed in randomized trials. METHODS: We developed a two-phase decision model including a trial phase and a Markov state transition phase to project long-term outcomes over the lifetimes of hypothetical renal graft recipients who survived the trial period with a functioning graft. Health states included functioning graft stratified by level of renal function, failed graft, functioning regraft, and death. Transitions between health states were predicted using statistical models that accounted for renal function, acute rejection, and new-onset diabetes after transplant and for donor and recipient predictors of long-term graft and patient survival. Models were estimated using data from 38,015 renal transplant recipients from the United States Renal Data System. The model was populated with data from a 3-year, randomized phase III trial comparing belatacept to cyclosporine. RESULTS: The decision model was well calibrated with data from the United States Renal Data System. Long-term extrapolation of Belatacept Evaluation of Nephroprotection and Efficacy as Firstline Immunosuppression Trial was projected to yield a 1.9-year increase in time alive with a functioning graft and a 1.2 life-year increase over a 20-year time horizon. CONCLUSIONS: This is the first long-term follow-up model of renal transplant patients to be based on renal function, acute rejection, and new-onset diabetes. It is a useful tool for undertaking comparative effectiveness and cost-effectiveness studies of immunosuppressive medications.

Development of a General Composite Scale (GENCOMS) for Progressive Neurodegenerative Diseases and Implications for the Assessment of Disease-Modifying Therapies.

INTRODUCTION: The reliable assessment of treatment outcomes for disease-modifying therapies (DMT) in neurodegenerative disease is challenging. The objective of this paper is to describe a generalized framework for developing composite scales that can be applied in diverse, degenerative conditions, termed "GENCOMS." Composite scales optimize the sensitivity for detecting clinically meaningful effects that slow disease progression. METHODS: The GENCOMS method relies on robust natural history data and/or placebo arm data from DMT trials. Validated scales that are core to the disease process have been identified, and item level data obtained to standardize the response outcomes from 0 (best possible score) to 1 (worst possible score). A partial least squares regression analysis was conducted with temporal change as the dependent variable and change scores in standardized items as the explanatory variables. The derived model coefficients constitute a weighted sum of items that most effectively measure disease progression. RESULTS: The resultant composite scale was optimized to detect disease progression and can be examined in a range of slow or fast progressing populations. The scale can be used in studies with comparable patient populations as an endpoint optimized to measure disease progression and therefore ideally suited to assess treatment effects in DMTs. CONCLUSION: The methodology presented here provides a generalizable framework for developing composite scales in the assessment of neurodegenerative disease progression and evaluation of DMT effects. By objectively selecting and weighting items from previously validated measures based solely on their sensitivity to disease progression, this methodology allows for the creation of a more responsive measurement of clinical decline. This heightened sensitivity to clinical decline can be utilized to detect modest yet meaningful treatment effects in the early stages of neurogenerative diseases, when it is optimal to begin a DMT.

Video-Based Kinematic Analysis of Movement Quality in a Phase 3 Clinical Trial of Troriluzole in Adults with Spinocerebellar Ataxia: A Post Hoc Analysis.

INTRODUCTION: Traditional methods for assessing movement quality rely on subjective standardized scales and clinical expertise. This limitation creates challenges for assessing patients with spinocerebellar ataxia (SCA), in whom changes in mobility can be subtle and varied. We hypothesized that a machine learning analytic system might complement traditional clinician-rated measures of gait. Our objective was to use a video-based assessment of gait dispersion to compare the effects of troriluzole with placebo on gait quality in adults with SCA. METHODS: Participants with SCA underwent gait assessment in a phase 3, double-blind, placebo-controlled trial of troriluzole (NCT03701399). Videos were processed through a deep learning pose extraction algorithm, followed by the estimation of a novel gait stability measure, the Pose Dispersion Index, quantifying the frame-by-frame symmetry, balance, and stability during natural and tandem walk tasks. The effects of troriluzole treatment were assessed in mixed linear models, participant-level grouping, and treatment group-by-visit week interaction adjusted for age, sex, baseline modified Functional Scale for the Assessment and Rating of Ataxia (f-SARA), and time since diagnosis. RESULTS: From 218 randomized participants, 67 and 56 participants had interpretable videos of a tandem and natural walk attempt, respectively. At Week 48, individuals assigned to troriluzole exhibited significant (p = 0.010) improvement in tandem walk Pose Dispersion Index versus placebo {adjusted interaction coefficient: 0.584 [95% confidence interval (CI) 0.137 to 1.031]}. A similar, nonsignificant trend was observed in the natural walk assessment [coefficient: 1.198 (95% CI - 1.067 to 3.462)]. Further, lower baseline Pose Dispersion Index during the natural walk was significantly (p = 0.041) associated with a higher risk of subsequent falls [adjusted Poisson coefficient: - 0.356 [95% CI - 0.697 to - 0.014)]. CONCLUSION: Using this novel approach, troriluzole-treated subjects demonstrated improvement in gait as compared to placebo for the tandem walk. Machine learning applied to video-captured gait parameters can complement clinician-reported motor assessment in adults with SCA. The Pose Dispersion Index may enhance assessment in future research. TRIAL REGISTRATION-CLINICALTRIALS. GOV IDENTIFIER: NCT03701399.

The burden of illness for patients with viral hepatitis C: evidence from a national survey in Japan.

OBJECTIVE: Viral hepatitis C (HCV) affects 170 million patients worldwide and 2 million patients in Japan. The objective of the current study was to examine the burden of HCV in Japan from a patient's perspective. METHODS: Using data from the 2008 and 2009 Japan National Health and Wellness Surveys, patients who reported an HCV diagnosis (n = 306) were compared with a propensity-score-matched control group (n = 306) on measures of quality of life (using the Medical Outcomes Study 12-Item Short Form Survey Instrument version 2), work productivity (using the Work Productivity and Activity Impairment questionnaire), and health-care resource use. All analyses applied sampling weights to project to the population. RESULTS: Prior to matching, patients with HCV had higher rates of hepatocellular carcinoma (4.88% vs. 0.02%) and cirrhosis (12.20% vs. 0.11%) than did subjects without HCV. The propensity-matching process eliminated differences between the two groups on demographics and patient characteristics. The postmatching analysis found significantly lower levels of quality of life for patients with HCV as measured by bodily pain (72.07 vs. 76.28), general health (44.64 vs. 48.61), and mental health (66.50 vs. 70.32) (all Ps < 0.05). Furthermore, compared with the matched group, the HCV group had significantly higher workplace absenteeism (8.59% vs. 4.12%), overall work impairment (26.08% vs. 17.32%), and health-care provider visits in the past 6 months (14.80 vs. 9.74). CONCLUSIONS: The results of this study suggest that HCV can be a substantial burden on patients in terms of quality of life in both physical and mental health measures. In addition, HCV can be a significant cost driver in terms of health-care use and lost productivity.

Association between second-generation antipsychotics and newly diagnosed treated diabetes mellitus: does the effect differ by dose?

BACKGROUND: The benefits of some second-generation antipsychotics (SGAs) must be weighed against the increased risk for diabetes mellitus. This study examines whether the association between SGAs and diabetes differs by dose. METHODS: Patients were ≥18 years of age from three US healthcare systems and exposed to an SGA for ≥45 days between November 1, 2002 and March 31, 2005. Patients had no evidence of diabetes before index date and no previous antipsychotic prescription filled within 3 months before index date.49,946 patients were exposed to SGAs during the study period. Person-time exposed to antipsychotic dose (categorized by tertiles for each drug) was calculated. Newly treated diabetes was identified using pharmacy data to determine patients exposed to anti-diabetic therapies. Adjusted hazard ratios for diabetes across dose tertiles of SGA were calculated using the lowest dose tertile as reference. RESULTS: Olanzapine exhibited a dose-dependent relationship for risk for diabetes, with elevated and progressive risk across intermediate (diabetes rate per 100 person-years = 1.9; adjusted Hazard Ratio (HR), 1.7, 95% confidence interval (CI), 1.0-3.1) and top tertile doses (diabetes rate per 100 person-years = 2.7; adjusted HR, 2.5, 95% CI, 1.4-4.5). Quetiapine and risperidone exhibited elevated risk at top dose tertile with no evidence of increased risk at intermediate dose tertile. Unlike olanzapine, quetiapine, and risperidone, neither aripiprazole nor ziprasidone were associated with risk of diabetes at any dose tertile. CONCLUSIONS: In this large multi-site epidemiologic study, within each drug-specific stratum, the risk of diabetes for persons exposed to olanzapine, risperidone, and quetiapine was dose-dependent and elevated at therapeutic doses. In contrast, in aripiprazole-specific and ziprasidone-specific stratum, these newer agents were not associated with an increased risk of diabetes and dose-dependent relationships were not apparent. Although, these estimates should be interpreted with caution as they are imprecise due to small numbers.

UK cost-consequence analysis of aripiprazole in schizophrenia: diabetes and coronary heart disease risk projections (STAR study).

Patients with schizophrenia experience elevated rates of morbidity and mortality, largely due to an increased incidence of cardiovascular disease and diabetes. There is increasing concern that some atypical antipsychotic therapies are associated with adverse metabolic symptoms, such as weight gain, dyslipidaemia and glucose dysregulation. These metabolic symptoms may further increase the risk of coronary heart disease (CHD) and diabetes in this population and, subsequently, the cost of treating these patients' physical health. The STAR study showed that the metabolic side effects of aripiprazole treatment are less than that experienced by those receiving standard-of-care (SOC). In a follow-up study the projected risks for diabetes or CHD, calculated using the Stern and Framingham models, were lower in the aripiprazole treatment group. Assuming the risk of diabetes onset/CHD events remained linear over 10 years, these risks were used to estimate the difference in direct and indirect cost consequences of diabetes and CHD in schizophrenia patients treated with aripiprazole or SOC over a 10-year period. Diabetes costs were estimated from the UKPDS and UK T(2)ARDIS studies, respectively, and CHD costs were estimated using prevalence data from the Health Survey of England and the published literature. All costs were inflated to 2007 costs using the NHS pay and prices index. The number of avoided diabetes cases (23.4 cases per 1,000 treated patients) in patients treated with aripiprazole compared with SOC was associated with estimated total (direct and indirect) cost savings of 37,261,293 pounds over 10 years for the UK population. Similarly, the number of avoided CHD events (3.7 events per 1,000 treated patients) was associated with estimated total cost savings of 7,506,770 pounds over 10 years. Compared with SOC, aripiprazole treatment may provide reductions in the health and economic burden to schizophrenia patients and health care services in the UK as a result of its favourable metabolic profile.

Risk of diabetes mellitus associated with atypical antipsychotic use among Medicaid patients with bipolar disorder: a nested case-control study.

STUDY OBJECTIVE: To quantify the risk of diabetes mellitus associated with atypical antipsychotics compared with conventional antipsychotics in managed care Medicaid patients with bipolar disorder. DESIGN: Retrospective nested case-control study. DATA SOURCE: Integrated seven-state Medicaid managed care claims database from January 1, 1998-December 31, 2002. PATIENTS: Two hundred eighty-three patients with diabetes (cases) and 1134 controls matched by age, sex, and the index date on which bipolar disorder was diagnosed. MEASUREMENTS AND MAIN RESULTS: Cases were defined as those having an International Classification of Diseases, Ninth Revision diagnosis of diabetes or those receiving treatment with antidiabetic drugs. Both case and control patients had at least a 3-month exposure to either conventional or atypical antipsychotic agents or three filled prescriptions related to treatment for bipolar disorder. Of the 283 cases, 139 (49%) received atypical antipsychotics (olanzapine, risperidone, quetiapine, ziprasidone, and clozapine) and 133 (47%) were prescribed conventional antipsychotics. To compare the risk for new-onset diabetes associated with atypical versus conventional antipsychotics, we conducted a Cox proportional hazard regression, in which we controlled for age; sex; duration of bipolar disorder follow-up; use of lithium, anticonvulsants, antidepressants, and other drugs; and psychiatric and medical comorbidities. Compared with patients receiving conventional antipsychotics, the risk of diabetes was greatest among patients taking risperidone (hazard ratio [HR] 3.8, 95% confidence interval [CI] 2.7-5.3), olanzapine (3.7, 95% CI 2.5-5.3), and quetiapine (2.5, 95% CI 1.4-4.3). The risk for developing diabetes was also associated with weight gain (HR 2.5, 95% CI 1.9-3.4), hypertension (HR 1.6, 95% CI 1.2-2.2), and substance abuse (HR 1.5, 95% CI 1.0-2.2). CONCLUSION: Olanzapine, risperidone, and quetiapine are all associated with development or exacerbation of diabetes mellitus in patients with bipolar disorder. When prescribing therapy for this patient population, metabolic complications such as diabetes, weight gain, and hypertension need to be considered.