Comparing the performance of published risk scores in Brugada syndrome: a multi-center cohort study.

The management of Brugada Syndrome (BrS) patients at intermediate risk of arrhythmic events remains controversial. The present study evaluated the predictive performance of different risk scores in an Asian BrS population and its intermediate risk subgroup. This retrospective cohort study included consecutive patients diagnosed with BrS from January 1 , 1997 to June 20 , 2020 from Hong Kong. The primary outcome is sustained ventricular tachyarrhythmias. Two novel risk risk scores and seven machine learning-based models (random survival forest, Ada boost classifier, Gaussian naïve Bayes, light gradient boosting machine, random forest classifier, gradient boosting classifier and decision tree classifier) were developed. The area under the receiver operator characteristic (ROC) curve (AUC) [95% confidence intervals] was compared between the different models. This study included 548 consecutive BrS patients (7% female, age at diagnosis: 50±16 years, follow-up: 84±55 months). For the whole cohort, the score developed by Sieira et al. showed the best performance (AUC: 0.806 [0.747-0.865]). A novel risk score was developed using the Sieira score and additional variables significant on univariable Cox regression (AUC: 0.855 [0.808-0.901]). A simpler score based on non-invasive results only showed a statistically comparable AUC (0.784 [0.724-0.845]), improved using random survival forests (AUC: 0.942 [0.913-0.964]). For the intermediate risk subgroup (N=274), a gradient boosting classifier model showed the best performance (AUC: 0.814 [0.791-0.832]). A simple risk score based on clinical and electrocardiographic variables showed a good performance for predicting VT/VF, improved using machine learning. Abstract: The management of Brugada Syndrome (BrS) patients at intermediate risk of arrhythmic events remains controversial. This study evaluated the predictive performance of published risk scores in a cohort of BrS patients from Hong Kong (N=548) and its intermediate risk subgroup (N=274). A novel risk score developed by modifying the best performing existing score (by. Sieira et al.) showed an area under the curve of 0.855 and 0.760 for the whole BrS cohort and the intermediate risk subgroup, respectively. The performance of the different scores was significantly improved machine learning-based methods, such as random survival forests and gradient boosting classifier. [Abstract copyright: Copyright © 2022 The Authors. Published by Elsevier Inc. All rights reserved.

Comparing the performance of published risk scores in Brugada syndrome: a multi-center cohort study

The management of Brugada Syndrome (BrS) patients at intermediate risk of arrhythmic events remains controversial. This study evaluated the predictive performance of published risk scores in a cohort of BrS patients from Hong Kong (N=548) and its intermediate risk subgroup (N=274). A novel risk score developed by modifying the best performing existing score (by. Sieira et al.) showed an area under the curve of 0.855 and 0.760 for the whole BrS cohort and the intermediate risk subgroup, respectively. The performance of the different scores was significantly improved machine learning-based methods, such as random survival forests and gradient boosting classifier

Whole-exome sequencing identifies multiple loss-of-function mutations of NF-κB pathway regulators in nasopharyngeal carcinoma

© 2016, National Academy of Sciences. All rights reserved. Nasopharyngeal carcinoma (NPC) is an epithelial malignancy with a unique geographical distribution. The genomic abnormalities leading to NPC pathogenesis remain unclear. In total, 135 NPC tumors were examined to characterize the mutational landscape using whole-exome sequencing and targeted resequencing. An APOBEC cytidine deaminase mutagenesis signature was revealed in the somatic mutations. Noticeably, multiple loss-of-function mutations were identified in several NF-κB signaling negative regulators NFKBIA, CYLD, and TNFAIP3. Functional studies confirmed that inhibition of NFKBIA had a significant impact on NF-κB activity and NPC cell growth. The identified loss-of-function mutations in NFKBIA leading to protein truncation contributed to the altered NF-κB activity, which is critical for NPC tumorigenesis. In addition, somatic mutations were found in several cancer-relevant pathways, including cell cycle-phase transition, cell death, EBV infection, and viral carcinogenesis. These data provide an enhanced road map for understanding the molecular basis underlying NPC.Link_to_subscribed_fulltex

Genome-wide association analysis identifies three new breast cancer susceptibility loci

Breast cancer is the most common cancer among women. To date, 22 common breast cancer susceptibility loci have been identified accounting for approximately 8% of the heritability of the disease. We attempted to replicate 72 promising associations from two independent genome-wide association studies (GWAS) in approximately 70,000 cases and approximately 68,000 controls from 41 case-control studies and 9 breast cancer GWAS. We identified three new breast cancer risk loci at 12p11 (rs10771399; P = 2.7 x 10(-35)), 12q24 (rs1292011; P = 4.3 x 10(-19)) and 21q21 (rs2823093; P = 1.1 x 10(-12)). rs10771399 was associated with similar relative risks for both estrogen receptor (ER)-negative and ER-positive breast cancer, whereas the other two loci were associated only with ER-positive disease. Two of the loci lie in regions that contain strong plausible candidate genes: PTHLH (12p11) has a crucial role in mammary gland development and the establishment of bone metastasis in breast cancer, and NRIP1 (21q21) encodes an ER cofactor and has a role in the regulation of breast cancer cell growt