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As a mega-biobank linked to a national healthcare system, the Million Veteran Program (MVP) can directly improve the health care of participants. To determine the feasibility and outcomes of returning medically actionable genetic results to MVP participants, the program launched the MVP Return of Actionable Results (MVP-ROAR) Study, with familial hypercholesterolemia (FH) as an exemplar actionable condition. The MVP-ROAR Study consists of a completed single-arm pilot phase and an ongoing randomized clinical trial (RCT), in which MVP participants are recontacted and invited to receive clinical confirmatory gene sequencing testing and a telegenetic counseling intervention. The primary outcome of the RCT is 6-month change in low-density lipoprotein cholesterol (LDL-C) between participants receiving results at baseline and those receiving results after 6 months. The pilot developed processes to identify and recontact participants nationally with probable pathogenic variants in low-density lipoprotein receptor (LDLR) on the MVP genotype array, invite them to clinical confirmatory gene sequencing, and deliver a telegenetic counseling intervention. Among participants in the pilot phase, 8 (100%) had active statin prescriptions after 6 months. Results were shared with 16 first-degree family members. Six-month ΔLDL-C (low-density lipoprotein cholesterol) after the genetic counseling intervention was −37 mg/dL (95% CI: −12 to −61; P =.03). The ongoing RCT will determine between-arm differences in this primary outcome. While underscoring the importance of clinical confirmation of research results, the pilot phase of the MVP-ROAR Study marks a turning point in MVP and demonstrates the feasibility of returning genetic results to participants and their providers. The ongoing RCT will contribute to understanding how such a program might improve patient health care and outcomes. Clinical Trial Registration: ClinicalTrials.gov ID NCT04178122. [ABSTRACT FROM AUTHOR]

Objectives: In this study, we developed a deep learning pipeline that detects large vessel occlusion (LVO) and predicts functional outcome based on computed tomography angiography (CTA) images to improve the management of the LVO patients.Methods: A series identifier picked out 8650 LVO-protocoled studies from 2015 to 2019 at Rhode Island Hospital with an identified thin axial series that served as the data pool. Data were annotated into 2 classes: 1021 LVOs and 7629 normal. The Inception-V1 I3D architecture was applied for LVO detection. For outcome prediction, 323 patients undergoing thrombectomy were selected. A 3D convolution neural network (CNN) was used for outcome prediction (30-day mRS) with CTA volumes and embedded pre-treatment variables as inputs.Result: For LVO-detection model, CTAs from 8,650 patients (median age 68 years, interquartile range (IQR): 58-81; 3934 females) were analyzed. The cross-validated AUC for LVO vs. not was 0.74 (95% CI: 0.72-0.75). For the mRS classification model, CTAs from 323 patients (median age 75 years, IQR: 63-84; 164 females) were analyzed. The algorithm achieved a test AUC of 0.82 (95% CI: 0.79-0.84), sensitivity of 89%, and specificity 66%. The two models were then integrated with hospital infrastructure where CTA was collected in real-time and processed by the model. If LVO was detected, interventionists were notified and provided with predicted clinical outcome information.Conclusion: 3D CNNs based on CTA were effective in selecting LVO and predicting LVO mechanical thrombectomy short-term prognosis. End-to-end AI platform allows users to receive immediate prognosis prediction and facilitates clinical workflow. [ABSTRACT FROM AUTHOR]

Purpose: To compare overall survival (OS) of ablation with no treatment for patients with advanced stage non-small cell lung cancer.Methods: Patients with clinical stage IIIB (T1-4N3M0, T4N2M0) and stage IV (T1-4N0-3M1) non-small cell lung cancer, in accordance with the American Joint Committee on Cancer, 7th edition, who did not receive treatment or who received ablation as their sole primary treatment besides chemotherapy from 2004 to 2014, were identified from the National Cancer Data Base. OS was estimated using the Kaplan-Meier method and evaluated by log-rank test, univariate and multivariate Cox proportional hazard regression, and propensity score-matched analysis. Relative survival analyses comparing age- and sex-matched United States populations were performed.Results: A total of 140,819 patients were included. The 1-, 2-, 3- and 5-year survival rates relative to age- and sex-matched United States population were 28%, 18%, 12%, and 10%, respectively, for ablation (n = 249); and 30%, 15%, 9%, and 5%, respectively for no treatment (n = 140,570). Propensity score matching resulted in 249 patients in the ablation group versus 498 patients in the no-treatment group. After matching, ablation was associated with longer OS than that in the no-treatment group (median, 5.9 vs 4.7 months, respectively; hazard ratio, 0.844; 95% confidence interval, 0.719-0.990; P = .037). These results persisted in patients with an initial tumor size of ≤3 cm.Conclusions: Preliminary results suggest ablation may be associated with longer OS in patients with late-stage non-small cell lung cancer than survival in those who received no treatment. [ABSTRACT FROM AUTHOR]