A machine learning-based SNP-set analysis approach for identifying disease-associated susceptibility loci.

Identifying disease-associated susceptibility loci is one of the most pressing and crucial challenges in modeling complex diseases. Existing approaches to biomarker discovery are subject to several limitations including underpowered detection, neglect for variant interactions, and restrictive dependence on prior biological knowledge. Addressing these challenges necessitates more ingenious ways of approaching the "missing heritability" problem. This study aims to discover disease-associated susceptibility loci by augmenting previous genome-wide association study (GWAS) using the integration of random forest and cluster analysis. The proposed integrated framework is applied to a hepatitis B virus surface antigen (HBsAg) seroclearance GWAS data. Multiple cluster analyses were performed on (1) single nucleotide polymorphisms (SNPs) considered significant by GWAS and (2) SNPs with the highest feature importance scores obtained using random forest. The resulting SNP-sets from the cluster analyses were subsequently tested for trait-association. Three susceptibility loci possibly associated with HBsAg seroclearance were identified: (1) SNP rs2399971, (2) gene LINC00578, and (3) locus 11p15. SNP rs2399971 is a biomarker reported in the literature to be significantly associated with HBsAg seroclearance in patients who had received antiviral treatment. The latter two loci are linked with diseases influenced by the presence of hepatitis B virus infection. These findings demonstrate the potential of the proposed integrated framework in identifying disease-associated susceptibility loci. With further validation, results herein could aid in better understanding complex disease etiologies and provide inputs for a more advanced disease risk assessment for patients.

Final Safety and Health-Related Quality of LIfe Results of the Phase 2/3 Act.In.Sarc Study With Preoperative NBTXR3 Plus Radiation Therapy Versus Radiation Therapy in Locally Advanced Soft-Tissue Sarcoma.

PURPOSE: Act.In.Sarc (NCT02379845) demonstrated that the first-in-class radioenhancer NBTXR3, activated by preoperative radiation therapy (RT), doubled the rate of pathologic complete response after resection compared with preoperative RT alone in adult patients with locally advanced soft tissue sarcoma of the extremity or trunk wall (16.1% vs 7.9%, P = .045), and more patients achieved R0 resections (77.0% vs 64.0%, P = .042). These are the toxicity and health-related quality of life (HRQoL) results. METHODS AND MATERIALS: Act.In.Sarc randomized eligible patients 1:1 to either NBTXR3 (single intratumoral injection, volume equivalent to 10% of baseline tumor volume, at 53.3 g/L) activated by external-beam RT (arm A) or external-beam RT alone (arm B) (50 Gy in 25 fractions), followed by surgery in both arms. Here, we report the safety analyses in the all-treated population with a long-term follow-up of at least 2 years, and HRQoL in the intention-to-treat full analysis set. RESULTS: During the on-treatment period, serious adverse events (SAEs) of all grades related to NBTXR3 occurred in 10.1% (9/89) of patients (arm A), and SAEs related to RT occurred in 5.6% (5/89) (arm A) versus 5.6% (5/90) (arm B); postsurgery hospitalization owing to SAEs occurred in 15.7% (14/89) (arm A) versus 24.4% (22/90) (arm B). During the follow-up period, posttreatment SAEs (regardless of relationship) occurred in 13.5% (12/89) (arm A) versus 24.4% (22/90) (arm B). NBTXR3 did not negatively affect HRQoL; during the follow-up period, there was an improvement in most mean Toronto extremity salvage, EuroQoL 5-dimension (EQ-5D), EQ5D02-EQ visual analog scale, reintegration to normal living index, and musculoskeletal tumor rating scale scores. CONCLUSIONS: NBTXR3 did not negatively affect safety or HRQoL. Long-term safety results reinforce the favorable benefit-risk ratio of NBTXR3 plus RT.

Early experience with COVID-19 patients in a private tertiary hospital in the Philippines: Implications on surge capacity, healthcare systems response, and clinical care.

BACKGROUND: Our healthcare institution was one of the first to see SARS CoV-2 cases in the country. We describe the early COVID-19 experience of a private hospital in the Philippines and discuss the healthcare system response in the setting of surge capacity. METHODS: We reviewed the medical records of adult COVID-19 hospitalized patients admitted in March 2020. We reported their demographic and clinical characteristics using descriptive statistics. RESULTS: Of 40 patients admitted, 23 (57.5%) were male and 19 (47.5%) were aged <60 years. Most (n = 27, 67.5%) had moderate-risk, 9 (22.5%) had high-risk, and 4 (10%) had low-risk COVID-19. SARS-CoV-2 testing took 5.5 (range 1-10) days. Overall mortality rate was 6/40 (15.0%). Clinical cure was documented in all low-risk patients, 25 (92.6%) moderate-risk patients, and only 1 (11.1%) high-risk patient. In response to the surge, the hospital rapidly introduced one-way traffic systems, dedicated screening, triage and Emergency Department areas for COVID-19, a clinical pathway, engineering controls, patient cohorting, and strict infection prevention and control measures. CONCLUSION: Majority of patients recovered from COVID-19. Older age and high-risk pneumonia were associated with poor outcomes. Adaptations to hospital structure and staff were quickly made in response to surge capacity, although our response was hampered by prolonged time to COVID-19 confirmation. Our study underscores the urgent need for rapid adaptive response by the healthcare system to address the surge of cases.