Coffey, Christopher S.

AbstractObjectivesDetection of α‐synuclein aggregates by seed amplification is a promising Parkinson disease biomarker assay. Understanding intraindividual relationships of α‐synuclein measures could inform optimal biomarker development. The objectives were to test accuracy of α‐synuclein seed amplification assay in central (cerebrospinal fluid) and peripheral (submandibular gland) sources, compare to total α‐synuclein measures, and investigate within‐subject relationships.MethodsThe Systemic Synuclein Sampling Study aimed to characterize α‐synuclein in multiple tissues and biofluids within Parkinson disease subjects (n = 59) and compared to healthy controls (n = 21). Motor and non‐motor measures and dopamine transporter scans were obtained. Four measures of α‐synuclein were compared: seed amplification assay in cerebrospinal fluid and formalin‐fixed paraffin‐embedded submandibular gland, total α‐synuclein quantified in biofluids using enzyme‐linked immunoassay, and aggregated α‐synuclein in submandibular gland detected by immunohistochemistry. Accuracy of seed amplification assay for Parkinson disease diagnosis was examined and within‐subject α‐synuclein measures were compared.ResultsSensitivity and specificity of α‐synuclein seed amplification assay for Parkinson disease diagnosis was 92.6% and 90.5% in cerebrospinal fluid, and 73.2% and 78.6% in submandibular gland, respectively. 25/38 (65.8%) Parkinson disease participants were positive for both cerebrospinal fluid and submandibular gland seed amplification assay. Comparing accuracy for Parkinson disease diagnosis of different α‐synuclein measures, cerebrospinal fluid seed amplification assay was the highest (Youden Index = 83.1%). 98.3% of all Parkinson disease cases had ≥1 measure of α‐synuclein positive.Interpretationα‐synuclein seed amplification assay (cerebrospinal fluid>submandibular gland) had higher sensitivity and specificity compared to total α‐synuclein measures, and within‐subject relationships of central and peripheral α‐synuclein measures emerged.

Given the Food and Drug Administration's (FDA's) acceptance of master protocol designs in recent guidance documents, the oncology field is rapidly moving to address the paradigm shift to molecular subtype focused studies. Identifying new “marker‐based” treatments requires new methodologies to address the growing demand to conduct clinical trials in smaller molecular subpopulations, identify effective treatment and marker interactions, and control for false positives. We introduce our methodology, Hierarchical Bayesian Clustering Design of Multiple Biomarker Subgroups (HCOMBS), a two‐stage umbrella Phase II design with effect size clustering and information borrowing across multiple biomarker‐treatment pairs. HCOMBS was designed to reduce required sample size, differentiate between varying effect sizes, and control for operating characteristics in the multi‐arm setting. When compared to independently applied Simon's Optimal two‐stage design, we showed through simulations that HCOMBS required less participants per treatment arm with a well‐controlled family‐wise error rate and desirable marginal power. Additionally, HCOMBS features a statistical approach that simultaneously conducts clustering and hypothesis testing in one step. We also applied the proposed design on the alliance brain metastases umbrella trial.