Broadcom (Canada)

IntroductionMeasures designed to comprehensively assess Parkinson’s disease (PD) irrespective of disease stage and treatment status may be unable to capture nuances in disease progression, particularly in early-stage PD. The objective of this paper is to develop PARkinson’s COMposite Scales (PARCOMS) with increased responsiveness to clinical decline using items of the Movement Disorder Society Unified Parkinson’s Disease Rating Scale (MDS-UPDRS) for three discrete cohorts of patients.MethodsPatients with confirmed PD from the Parkinson’s Progression Markers Initiative (PPMI) data were assigned to three cohorts based on use of dopaminergic treatment, stage of disease, and presence of motor complication. For each cohort, items from MDS-UPDRS Part I (PARCOMS-Non-Motor) and Parts II and III (PARCOMS-Motor) were selected based on responsiveness using partial least squares (PLS) regression. The responsiveness of the scales was estimated using mean-to-standard deviation ratios (MSDRs) of their change values.ResultsCompared to the original MDS-UPDRS, MSDRs for PARCOMS-Motor increased 13.1% (untreated cohort, n = 430), 78.2% (treated-without-motor-complications cohort, n = 426), and 100.6% (treated-with-motor-complications cohort, n = 538). The MSDR increases observed for PARCOMS-Non-Motor were 13.9%, 6.8%, and 20.7%, respectively. Across cohorts, turning in bed and speech items were large contributors to the PARCOMS-Motor scales. Items for cognitive impairment and urinary problems were substantial contributors to PARCOMS-Non-Motor across cohorts. There was variability in the weighting of items representing different clinical concepts across cohorts for each composite, confirming heterogeneity in disease progression across disease stages.ConclusionsPD stage-specific composite measures were developed and demonstrated greater sensitivity to change than the original MDS-UPDRS, supporting the value of weighted composites tailored for disease stage.Supplementary InformationThe online version contains supplementary material available at 10.1007/s40120-025-00771-5.

IntroductionDuchenne muscular dystrophy (DMD) is a rare, severe progressive neuromuscular disease. Health insurance claims allow characterization of population-level real-world outcomes, based on observed healthcare resource use. An analysis of data specific to those with Medicaid insurance is presently unavailable. The objective was to describe the real-world clinical course of DMD based on claims data from Medicaid-insured individuals in the USA.MethodsIndividuals with DMD were identified from the MarketScan Multi-State Medicaid datasets (2013–2018). Diagnosis and procedure codes from healthcare claims were used to characterize the occurrence of DMD-relevant clinical observations; categories were scoliosis, cardiovascular-related, respiratory and severe respiratory-related, and neurologic/neuropsychiatric. Age-restricted analyses were conducted to focus on the ages at which DMD-relevant clinical observations were more likely to be captured, and to better understand the impact of both age and follow-up time.ResultsOf 2007 patients with DMD identified, median (interquartile range) age at index was 14 (9–20) years, and median follow-up was 3.1 (1.6–4.7) years. Neurologic and neuropsychiatric observations were most frequently identified, among 49.3% of the cohort; followed by cardiovascular (48.5%), respiratory (38.1%), scoliosis (36.3%), and severe respiratory (25.0%). Prevalence estimates for each category were higher when analyzed within age-restricted subgroups; and increased as follow-up time increased.ConclusionsThis study is the first to use diagnosis and procedure codes from real-world Medicaid claims to document the clinical course in DMD. Findings were consistent with previously published estimates from commercially insured populations and clinical registries; and contribute to the expanding body of real-world evidence around clinical progression of patients with DMD.Supplementary InformationThe online version contains supplementary material available at 10.1007/s12325-024-02865-2.

ObjectiveThe objective of this study was to explore patient preference for attributes of calcitonin gene‐related peptide (CGRP) inhibitors for the preventive treatment of migraine and to describe differences in treatment preferences between patients.BackgroundCGRP inhibitors are a novel class of migraine drugs specifically developed for the preventive treatment of migraine. Clinicians should understand patient preferences for CGRP inhibitors to inform and support prescribing choices.MethodsPatients with migraine in the US and Germany were recruited to participate in an online discrete choice experiment (DCE) survey, which presented hypothetical treatment choices using five attributes: mode of administration, side effects, migraine frequency, migraine severity, and consistency of treatment effectiveness. Attribute selection was informed by a literature review and semi‐structured patient interviews (n = 35), and evaluated using patient cognitive debriefing interviews (n = 5).ResultsOf 680 who consented to participate, 506 participants completed the survey and were included in the study (US = 257; Germany = 249). Overall, participants placed highest importance (preference weight, beta = 1.65, p < 0.001) on the treatment's ability to reduce the severity of migraine (mild vs. unchanged severity), followed by consistent treatment effectiveness (beta = 1.13, p < 0.001), and higher chance of reduced migraine frequency (beta = 1.00, p < 0.001). Participants preferred an oral tablet every other day (beta = 1.00, p < 0.001) over quarterly infusion, quarterly injections (p = 0.019), or monthly injection (p < 0.001). Preference for all treatment attributes were heterogeneous, and the subgroup analyses found that participants naïve to CGRP monoclonal antibody treatments had a stronger preference for oral therapy compared to those with such experience (p = 0.006).ConclusionIn this DCE assessing CGRP inhibitors attributes, the main driver of patient choice was treatment effectiveness, specifically reduced migraine severity, and consistent treatment effectiveness. Further, patients exhibited an overall preference for an oral tablet every other day over injectables. Patients' experience with previous treatments informs the value they place on treatment characteristics.

This paper proposes a flexible and efficient subband adaptive second order Volterra filter structure for nonlinear system identification. Acoustic echo cancellation is an application of system identification that is critical in hands-free telephony, for which a linear model is usually assumed. However, echo cancellation is limited by inherent system nonlinearities, of which loudspeaker distortion is one of the main sources. Experimental results, obtained in an office room environment, show that the proposed structure was able to model the nonlinear room transfer function more accurately than a linear only model by up to 10 dB lower mean square error, at a comparable computational complexity.