METHODS: After 10 min of supine rest, the subject was tilted at a 70-degree angle on a tilt table for approximately a total of 35 min. 400 µg of glyceryl trinitrate (GTN) was administered sublingually after the first 20 min and monitoring continued for another 15 min. Mean imputation and K-nearest neighbors (KNN) imputation approaches to handle missing values. Next, feature selection techniques were implemented, including genetic algorithm, recursive feature elimination, and feature importance, to determine the crucial features. The Mann-Whitney U test was then performed to determine the statistical difference between two groups. Patients with VVS are categorized via machine learning models including Support Vector Machine (SVM), Gaussian Naïve Bayes (GNB), Multinomial Naïve Bayes (MNB), KNN, Logistic Regression (LR), and Random Forest (RF). The developed model is interpreted using an explainable artificial intelligence (XAI) model known as partial dependence plot.
RESULTS: A total of 137 subjects aged between 9 and 93 years were recruited for this study, 54 experienced clinical symptoms were considered positive tests, while the remaining 83 tested negative. Optimal results were obtained by combining the KNN imputation technique and three tilting features with SVM with 90.5% accuracy, 87.0% sensitivity, 92.7% specificity, 88.6% precision, 87.8% F1 score, and 95.4% ROC (receiver operating characteristics) AUC (area under curve).
CONCLUSIONS: The proposed algorithm effectively classifies VVS patients with over 90% accuracy. However, the study was confined to a small sample size. More clinical datasets are required to ensure that our approach is generalizable.
METHODS: Through the Association of Southeast Asian Nations Costs in Oncology study, 1490 newly diagnosed cancer patients were followed-up in Malaysia for 1 year. Health-related quality of life was assessed by using the European Organization for Research and Treatment of Cancer Quality of Life Questionnaire Core 30 (EORTC QLQ-C30) and EuroQol-5 (EQ-5D) dimension questionnaires at baseline, 3 and 12 months. Psychological distress was assessed by using Hospital Anxiety and Depression Scale. Data were modeled by using general linear and logistic regressions analyses.
RESULTS: One year after diagnosis, the mean EORTC QLQ-C30 Global Health score of the cancer survivors remained low at 53.0 over 100 (SD 21.4). Fifty-four percent of survivors reported at least moderate levels of anxiety, while 27% had at least moderate levels of depression. Late stage at diagnosis was the strongest predictor of low HRQoL. Increasing age, being married, high-income status, hospital type, presence of comorbidities, and chemotherapy administration were also associated with worse HRQoL. The significant predictors of psychological distress were cancer stage and hospital type.
CONCLUSION: Cancer survivors in this middle-income setting have persistently impaired HRQoL and high levels of psychological distress. Development of a holistic cancer survivorship program addressing wider aspects of well-being is urgently needed in our settings.
METHODS: Through the Association of Southeast Asian Nations Costs in Oncology study, 1,294 newly diagnosed patients with cancer (Ministry of Health [MOH] hospitals [n = 577], a public university hospital [n = 642], private hospitals [n = 75]) were observed in Malaysia. Cost diaries and questionnaires were used to measure incidence of financial toxicity, encompassing financial catastrophe (FC; out-of-pocket costs ≥ 30% of annual household income), medical impoverishment (decrease in household income from above the national poverty line to below that line after subtraction of cancer-related costs), and economic hardship (inability to make necessary household payments). Predictors of financial toxicity were determined using multivariable analyses.
RESULTS: One fifth of patients had private health insurance. Incidence of FC at 1 year was 51% (MOH hospitals, 33%; public university hospital, 65%; private hospitals, 72%). Thirty-three percent of households were impoverished at 1 year. Economic hardship was reported by 47% of families. Risk of FC attributed to conventional medical care alone was 18% (MOH hospitals, 5%; public university hospital, 24%; private hospitals, 67%). Inclusion of expenditures on nonmedical goods and services inflated the risk of financial toxicity in public hospitals. Low-income status, type of hospital, and lack of health insurance were strong predictors of FC.
CONCLUSION: Patients with cancer may not be fully protected against financial hardships, even in settings with universal health coverage. Nonmedical costs also contribute as important drivers of financial toxicity in these settings.
METHODS: This multi-center, cross-sectional, descriptive survey was conducted at 54 study sites in seven Asia-Pacific countries. A modified Likert-scale questionnaire was used to determine the importance of each element in the ICF among research participants of a biomedical study, with an anchored rating scale from 1 (not important) to 5 (very important).
RESULTS: Of the 2484 questionnaires distributed, 2113 (85.1%) were returned. The majority of respondents considered most elements required in the ICF to be 'moderately important' to 'very important' for their decision making (mean score, ranging from 3.58 to 4.47). Major foreseeable risk, direct benefit, and common adverse effects of the intervention were considered to be of most concerned elements in the ICF (mean score = 4.47, 4.47, and 4.45, respectively).
CONCLUSIONS: Research participants would like to be informed of the ICF elements required by ethical guidelines and regulations; however, the importance of each element varied, e.g., risk and benefit associated with research participants were considered to be more important than the general nature or technical details of research. Using a participant-oriented approach by providing more details of the participant-interested elements while avoiding unnecessarily lengthy details of other less important elements would enhance the quality of the ICF.
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.