METHODS: The predictive eight biomarker set is derived from prospective observational clinical trials, representing 280 treatments with Pembrolizumab, Atezolizumab, Durvalumab, Nivolumab, and Avelumab in a broad range of indications: melanoma, lung, hepatocellular, renal, breast, bladder, colon, head and neck, bone, brain, lymphoma, prostate, vulvar, and cervical cancers.
RESULTS: The 3D genomic eight biomarker panel for response to immune checkpoint therapy achieved a high accuracy of 85%, sensitivity of 93%, and specificity of 82%.
CONCLUSIONS: This study demonstrates that a 3D genomic approach can be used to develop a predictive clinical assay for response to PD-1/PD-L1 checkpoint inhibition in cancer patients.
OBJECTIVE: The aim of this study was to identify the clinical features that affect age at diagnosis (AD) and time to the diagnosis of SCID.
METHODS: From 2005 to 2016, 147 SCID patients were referred to the Asian Primary Immunodeficiency Network. Patients with genetic diagnosis, age at presentation (AP), and AD were selected for study.
RESULTS: A total of 88 different SCID gene mutations were identified in 94 patients, including 49 IL2RG mutations, 12 RAG1 mutations, 8 RAG2 mutations, 7 JAK3 mutations, 4 DCLRE1C mutations, 4 IL7R mutations, 2 RFXANK mutations, and 2 ADA mutations. A total of 29 mutations were previously unreported. Eighty-three of the 94 patients fulfilled the selection criteria. Their median AD was 4 months, and the time to diagnosis was 2 months. The commonest SCID was X-linked (n = 57). A total of 29 patients had a positive FH. Candidiasis (n = 27) and bacillus Calmette-Guérin (BCG) vaccine infection (n = 19) were the commonest infections. The median age for candidiasis and BCG infection documented were 3 months and 4 months, respectively. The median absolute lymphocyte count (ALC) was 1.05 × 10(9)/L with over 88% patients below 3 × 10(9)/L. Positive FH was associated with earlier AP by 1 month (p = 0.002) and diagnosis by 2 months (p = 0.008), but not shorter time to diagnosis (p = 0.494). Candidiasis was associated with later AD by 2 months (p = 0.008) and longer time to diagnosis by 0.55 months (p = 0.003). BCG infections were not associated with age or time to diagnosis.
CONCLUSION: FH was useful to aid earlier diagnosis but was overlooked by clinicians and not by parents. Similarly, typical clinical features of SCID were not recognized by clinicians to shorten the time to diagnosis. We suggest that lymphocyte subset should be performed for any infant with one or more of the following four clinical features: FH, candidiasis, BCG infections, and ALC below 3 × 10(9)/L.
Objective: To evaluate the efficacy of oral mixed tocotrienols for patients with diabetic peripheral neuropathy.
Design, Setting, and Participants: The Vitamin E in Neuroprotection Study (VENUS) was a parallel, double-blind, placebo-controlled trial that recruited participants from January 30, 2011, to December 7, 2014, with 12 months of follow-up. This trial screened 14 289 patients with diabetes from 6 health clinics and ambulatory care units from 5 public hospitals in Malaysia. A total of 391 patients who reported neuropathic symptoms were further assessed with Total Symptom Score (TSS) and Neuropathy Impairment Score (NIS). Patients 20 years or older with a TSS of 3 or higher and an NIS of 2 or higher were recruited.
Interventions: Patients were randomized to receive 200 mg of mixed tocotrienols twice daily or matching placebo for 12 months. Patients with hyperhomocysteinemia (homocysteine level ≥2.03 mg/L) received oral folic acid, 5 mg once daily, and methylcobalamin, 500 μg thrice daily, in both groups.
Main Outcomes and Measures: The primary outcome was patient-reported neuropathy TSS (lancinating pain, burning pain, paresthesia, and asleep numbness) changes at 12 months. The secondary outcomes were NIS and sensory nerve conduction test result.
Results: Of 391 eligible patients, 300 were recruited (130 [43.3%] male; mean [SD] age, 57.6 [8.9] years; mean [SD] duration of diabetes, 11.4 [7.8] years) and 229 (76.3%) completed the trial. The TSS changes between the tocotrienols and placebo groups at 12 months (-0.30; 95% CI, -1.16 to 0.56; P = .49) were similar. No significant differences in NIS (0.60; 95% CI, -1.37 to 2.65; P = .53) and sensory nerve conduction test assessments were found between both groups. In post hoc subgroup analyses, tocotrienols reduced lancinating pain among patients with hemoglobin A1C levels greater than 8% (P = .03) and normohomocysteinemia (homocysteine level <2.03 mg/L; P = .008) at 1 year. Serious adverse events in both groups were similar, except more infections were observed in the tocotrienols group (6.7% vs 0.7%, P = .04). Results reported were of modified intention-to-treat analyses.
Conclusions and Relevance: Supplementation of oral mixed tocotrienols, 400 mg/d for 1 year, did not improve overall neuropathic symptoms. The preliminary observations on lancinating pain among subsets of patients require further exploration.
Trial Registration: National Medical Research Registry Identifier: NMRR-10-948-7327 and clinicaltrials.gov Identifier: NCT01973400.
METHODS: This was a multi-national survey of ophthalmologists between March 1st, 2020 to February 29th, 2021 disseminated via the major global ophthalmology societies. The survey was designed based on microsystem, mesosystem and macrosystem questions, and the software as a medical device (SaMD) regulatory framework chaired by the Food and Drug Administration (FDA). Factors associated with AI adoption for ophthalmology analyzed with multivariable logistic regression random forest machine learning.
RESULTS: One thousand one hundred seventy-six ophthalmologists from 70 countries participated with a response rate ranging from 78.8 to 85.8% per question. Ophthalmologists were more willing to use AI as clinical assistive tools (88.1%, n = 890/1,010) especially those with over 20 years' experience (OR 3.70, 95% CI: 1.10-12.5, p = 0.035), as compared to clinical decision support tools (78.8%, n = 796/1,010) or diagnostic tools (64.5%, n = 651). A majority of Ophthalmologists felt that AI is most relevant to DR (78.2%), followed by glaucoma (70.7%), AMD (66.8%), and cataract (51.4%) detection. Many participants were confident their roles will not be replaced (68.2%, n = 632/927), and felt COVID-19 catalyzed willingness to adopt AI (80.9%, n = 750/927). Common barriers to implementation include medical liability from errors (72.5%, n = 672/927) whereas enablers include improving access (94.5%, n = 876/927). Machine learning modeling predicted acceptance from participant demographics with moderate to high accuracy, and area under the receiver operating curves of 0.63-0.83.
CONCLUSION: Ophthalmologists are receptive to adopting AI as assistive tools for DR, glaucoma, and AMD. Furthermore, ML is a useful method that can be applied to evaluate predictive factors on clinical qualitative questionnaires. This study outlines actionable insights for future research and facilitation interventions to drive adoption and operationalization of AI tools for Ophthalmology.
METHODS: A panel of experts convened to develop consensus statements by synthesizing the current literature and leveraging clinical expertise. The review encompassed long-term anti-osteoporosis medication goals, first-line treatments for individuals at very high fracture risk, and the strategic integration of anabolic and antiresorptive agents in sequential therapy approaches.
RESULTS: The panelists reached a consensus on 12 statements. Key recommendations included advocating for anabolic agents as the first-line treatment for individuals at very high fracture risk and transitioning to antiresorptive agents following the completion of anabolic therapy. Anabolic therapy remains an option for individuals experiencing new fractures or persistent high fracture risk despite antiresorptive treatment. In cases of inadequate response, the consensus recommended considering a switch to more potent medications. The consensus also addressed the management of medication-related complications, proposing alternatives instead of discontinuation of treatment.
CONCLUSIONS: This consensus provides a comprehensive, cost-effective strategy for fracture prevention with an emphasis on shared decision-making and the incorporation of country-specific case management systems, such as fracture liaison services. It serves as a valuable guide for healthcare professionals in the Asia-Pacific region, contributing to the ongoing evolution of osteoporosis management.
METHODS: The Mainstreaming Genetic Counselling for Ovarian Cancer Patients (MaGiC) study is a prospective, two-arm observational study comparing oncologist-led and genetics-led counselling. This study included 790 multiethnic patients with ovarian cancer from 23 sites in Malaysia. We compared the impact of different method of delivery of genetic counselling on the uptake of genetic testing and assessed the feasibility, knowledge and satisfaction of patients with ovarian cancer.
RESULTS: Oncologists were satisfied with the mainstreaming experience, with 95% indicating a desire to incorporate testing into their clinical practice. The uptake of genetic testing was similar in the mainstreaming and genetics arm (80% and 79%, respectively). Patient satisfaction was high, whereas decision conflict and psychological impact were low in both arms of the study. Notably, decisional conflict, although lower than threshold, was higher for the mainstreaming group compared with the genetics arm. Overall, 13.5% of patients had a pathogenic variant in BRCA1 or BRCA2, and there was no difference between psychosocial measures for carriers in both arms.
CONCLUSION: The MaGiC study demonstrates that mainstreaming cancer genetics is feasible in low-resource and middle-resource Asian setting and increased coverage for genetic testing.
Methods: A survey regarding the practice of EUS in the evaluation of PCLs was drafted by the committee member of the International Society of EUS Task Force (ISEUS-TF). It was disseminated to experts of EUS who were also members of the ISEUS-TF. In some cases, percentage agreement with some statements was calculated; in others, the options with the greatest numbers of responses were summarized.
Results: Fifteen questions were extracted and disseminated among 60 experts for the survey. Fifty-three experts completed the survey within the specified time frame. The average volume of EUS cases at the experts' institutions is 988.5 cases per year.
Conclusion: Despite the limitations of EUS alone in the morphologic diagnosis of PCLs, the results of the survey indicate that EUS-guided fine-needle aspiration is widely expected to become a more valuable method.
METHODS: We analyzed data from 524 families with PALB2 PVs from 21 countries. Complex segregation analysis was used to estimate relative risks (RRs; relative to country-specific population incidences) and absolute risks of cancers. The models allowed for residual familial aggregation of breast and ovarian cancer and were adjusted for the family-specific ascertainment schemes.
RESULTS: We found associations between PALB2 PVs and risk of female breast cancer (RR, 7.18; 95% CI, 5.82 to 8.85; P = 6.5 × 10-76), ovarian cancer (RR, 2.91; 95% CI, 1.40 to 6.04; P = 4.1 × 10-3), pancreatic cancer (RR, 2.37; 95% CI, 1.24 to 4.50; P = 8.7 × 10-3), and male breast cancer (RR, 7.34; 95% CI, 1.28 to 42.18; P = 2.6 × 10-2). There was no evidence for increased risks of prostate or colorectal cancer. The breast cancer RRs declined with age (P for trend = 2.0 × 10-3). After adjusting for family ascertainment, breast cancer risk estimates on the basis of multiple case families were similar to the estimates from families ascertained through population-based studies (P for difference = .41). On the basis of the combined data, the estimated risks to age 80 years were 53% (95% CI, 44% to 63%) for female breast cancer, 5% (95% CI, 2% to 10%) for ovarian cancer, 2%-3% (95% CI females, 1% to 4%; 95% CI males, 2% to 5%) for pancreatic cancer, and 1% (95% CI, 0.2% to 5%) for male breast cancer.
CONCLUSION: These results confirm PALB2 as a major breast cancer susceptibility gene and establish substantial associations between germline PALB2 PVs and ovarian, pancreatic, and male breast cancers. These findings will facilitate incorporation of PALB2 into risk prediction models and optimize the clinical cancer risk management of PALB2 PV carriers.