Wendelberger, Barbara

AbstractBackgroundPathogenic mutations in the MAPT (tau) gene cause familial frontotemporal lobar degeneration (f‐FTLD). No disease‐modifying treatments exist. Tau therapeutics being tested in other tauopathies may be suitable candidates, but the small number of identified mutation carriers prohibits traditional clinical trial designs from achieving adequate power. Platform trial designs permit multiple therapies to be tested in parallel and improve power by sharing placebo groups across treatment arms. We evaluate whether a platform design could improve the likelihood of identifying an effective treatment for MAPT mutation carriers.MethodALLFTD and GENFI observational data were used to simulate MAPT prevention and early symptomatic clinical trials (CDR®+NACC‐FTLD≤1). Only presymptomatic participants (CDR®+NACC‐FTLD = 0) within 2.5 years of expected symptom onset based on disease progression models (DPM) were included. First, we evaluated the time and sample size required to test five treatments using a platform design compared to sequential randomized control trials. Platform designs assumed a max of three treatment arms at any time, with new arms enrolling upon completion of prior arms. Each arm randomized 60 mutations carriers 3:1 treatment to placebo, with a placebo group shared across arms. Minimum follow up was 1.5 years with common close. Sequential trials assumed 90 participants allocated 1:1 treatment to placebo, with three‐month intervals between trials. Using a platform design, we compared a novel method for testing therapeutic effects using DPMs to account for differential rates of expected progression compared to traditional mixed models for repeated measures (MMRM) tests controlling for baseline CDR®+NACC‐FTLD.ResultFive treatments could be tested in a platform design using 300 participants (75% treated) over five years, compared to 450 participants (50% treated) over 13 years using traditional, sequential trials. Platform trial simulations indicated that with 80% power, DPM‐based analytic approach could detect a 25% treatment effect, whereas traditional MMRM could only detect a 40% effect.ConclusionPlatform designs combined with DPM‐based analyses provide a path to testing more treatments with fewer participants. Adequately powered MAPT platform trials are feasible but require a global clinical trial infrastructure.

AbstractBackgroundClinical trials are underway to treat familial frontotemporal lobar degeneration (f‐FTLD). This is a rare disease, and a limited number of mutation carriers have been identified; thus, efficient trial design is critical. Multimodal, latent disease progression models (DPM) can estimate time to symptom onset and define the temporal ordering of biomarker changes. DPMs can also be leveraged to select endpoints and potentially supplement analyses by integrating historical data. Recent draft FDA guidance for gene therapy trials in neurological disease supports these novel approaches to clinical trials.MethodParticipants included 1,049 members of families affected by f‐FTLD, due to mutations in GRN, MAPT, or C9orf72 genes, who were enrolled in ALLFTD or GENFI. A Bayesian repeated measures model incorporated multimodal data to estimate disease progression, conditional on latent disease age (proximity to symptom onset), in 677 mutations carriers (GRN (n=233), MAPT (n=151) and C9orf72 (n=293)). Family members without pathogenic mutations were used as the reference group. Mean follow‐up was 1.1 (SD=1.1) years. Jointly modeled longitudinal variables included neuropsychological scores, CDR®+NACC‐FTLD Box Score, MRI volumes of brain regions affected by f‐FTLD, and plasma levels of neurofilament light chain (NfL).ResultDisease progression curves were similar across ALLFTD and GENFI cohorts. Plasma NfL elevations occurred earliest, up to 10 years before symptom onset, and NfL was the most powerful endpoint in the asymptomatic stage. MRI abnormalities occurred next, closer to symptom onset. The earliest MRI changes relative to symptom onset were observed in C9orf72+. GRN mutation carriers showed the most rapid acceleration in all biomarkers, and this acceleration occurred in close proximity to symptom onset. Neuropsychological measures and CDR®+NACC‐FTLD Box Score were among the most promising endpoints in the symptomatic stage. Trial simulations indicated that using latent disease age as an enrollment criterion would allow some asymptomatic mutation carriers to be enrolled without sacrificing power.ConclusionSimilarity in disease progression across ALLFTD and GENFI participants suggests these models will apply to international trials. Model‐derived estimates of disease progression curves indicate that endpoint selection should be specific to disease stage and mutation, and DPMs would facilitate greater participant enrollment.

AbstractBackgroundMeasuring changes in the earliest phases of familial frontotemporal lobar degeneration (f‐FTLD) and estimating symptom onset has important implications for clinical care. Early stage clinical trials have begun for f‐FTD, but the low prevalence of f‐FTLD mutation carriers and heterogeneous symptomology challenges trial design. Bayesian disease progression models (DPM) incorporate clinical data, neuroimaging metrics, and fluid biomarker concentrations to estimate latent disease age, providing estimates of symptom onset and progression status. Such models may facilitate enrollment in studies (i.e., inclusion of presymptomatic individuals) and provide more powerful analysis methods for trials.MethodA Bayesian latent variable repeated measures model was used to estimate disease progression, conditional on latent disease age (proximity to symptom onset), in 275 participants with mutations in GRN (n=68), MAPT (n=80) and C9orf72 (n=127). Median follow‐up was one year (range: 0‐4). Jointly modeled longitudinal variables included neuropsychological scores, CDR®+NACC‐FTLD box score, 3T MRI frontotemporal brain volumes, and plasma levels of neurofilament light chain (NfL). Sample size estimates for detecting treatment effects were generated by varying thresholds of estimated proximity to symptom onset.ResultThe Bayesian DPM provided a clear picture of clinical and neurological progression within each mutation group. Neuroimaging and NfL captured early progression rates (1 SD from controls) 5‐10 years before symptom onset. After symptom onset, CDR®+NACC‐FTLD box score was the most sensitive measure of disease progression. GRN mutation carriers had the largest annual progression rates (and lowest variability) compared to MAPT and C9orf72. Between 5 years pre‐ and 10 years post‐onset, CDR®+NACC‐FTLD box score progressed by 2 units/year (SD=2.7) in GRN mutation carriers ‐ almost twice the rate of progression in MAPT (M=1.2;SD=2.5) and C9orf72 (M=1.1;SD=2.2) mutation carriers. Compared to a trial enrolling only early symptomatic cases (CDR®+NACC‐FTLD=0.5 or 1), utilizing latent disease age would facilitate enrollment of asymptomatic cases with the same power.ConclusionBased on an estimation of symptom onset, Bayesian DPMs suggest clinical trials in GRN mutation carriers would require the smallest sample sizes. Furthermore, leveraging these DPMs would allow novel, powerful trial designs that may facilitate greater participant enrollment.