Methods: Data were derived from 20 focus group discussions that were conducted in five public and private Malaysian hospitals, which included 102 adults with breast, cervical, colorectal or prostate cancers. The discussions were segregated by type of healthcare setting and gender. Thematic analysis was performed.
Results: Five major themes related to cancer costs emerged: 1) cancer therapies and imaging services, 2) supportive care, 3) complementary therapies, 4) non-medical costs and 5) loss of household income. Narratives on out-of-pocket medical costs varied not only by type of healthcare setting, clinical factors and socioeconomic backgrounds, but also by private health insurance ownership. Non-health costs (e.g. transportation, food) and loss of income were nonetheless recurring themes. Coping mechanisms that were raised included changing of cancer treatment decisions, continuing work despite ill health and seeking financial assistance from third parties. Unmet needs in coping with financial distress were especially glaring among the women.
Conclusion: The long-term costs of cancer (medications, cancer surveillance, supportive care, complementary medicine) should not be overlooked even in settings where there is access to highly subsidised cancer care. In such settings, patients may also have unmet needs related to non-health costs of cancer and loss of income.
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.
INTRODUCTION AND OBJECTIVE: T-score discordance between hip and spine is a common problem in bone mineral density assessment. A difference ≥ 1 standard deviation (SD) (regardless of diagnostic class) is considered minor, and a difference more than one diagnostic class is considered major discordance. This study aimed to determine the prevalence and factors of hip and spine T-score discordance in a population aged ≥ 40 years in Klang Valley, Malaysia.
SUBJECTS AND METHODS: In this cross-sectional study, subjects answered a demographic questionnaire and underwent body composition and bone health assessment using dual-energy X-ray absorptiometry. Chi-square and binary logistic regression analysis were used to assess the prevalence of T-score discordance among the subjects.
RESULTS: A total of 786 Malaysians (382 men, 404 women) subjects were recruited. The prevalence of minor and major discordance was 30.3% and 2.3%, respectively. Overall, factors related to T-score discordance were advanced age, decreased height, and being physically active. Sub-analysis showed that decreased height and being physically active predicted T-score discordance in men, being menopausal and Indian (vs Chinese) were predictors in women.
CONCLUSIONS: T-score discordance between hip and spine is common among Malaysian middle-aged and elderly population. Diagnosis of osteopenia/osteoporosis should be based on the T-score of more than one skeletal site as per the current recommendations.
Methods: A cross-sectional study was conducted amongst university students from a Malaysian's public university. A total of 228 students responded to a self-administered questionnaire consisting of items evaluating knowledge and practices of osteoporosis.
RESULTS: The students showed a moderate level of osteoporosis awareness with a score of 63.3%. Male subjects had higher awareness scores of osteoporosis complications compared to female subjects (p= 0.010). Malay (p= 0.002) and Chinese (p= 0.005) had higher levels of osteoporosis awareness compared to Indian students. Coffee and alcohol intakes were significantly different between the sexes (p= 0.013) and the ethnic groups (p= 0.029). Most of the subjects in our study were minimally active (43.9%).
CONCLUSIONS: The students had a reasonable levels of knowledge about osteoporosis, but their health activities to avoid osteoporosis were insufficient. This illustrates the need for educational programmes to improve students' knowledge and awareness for successful osteoporosis prevention.
OBJECTIVE: This study aimed to compare the circulating markers of osteocytes and calcium homeostasis between Malaysian postmenopausal women with and without osteoporosis.
METHODS: Postmenopausal women with (n=20) or without osteoporosis (n=20) as determined by dual- energy X-ray absorptiometry were randomly drawn from a bone health cohort. Their fasting blood was collected and assayed by a multiplex immunoassay panel.
RESULTS: The results showed that osteoprotegerin and sclerostin levels were significantly lower among postmenopausal women with osteoporosis than the normal control. No significant differences in other markers were observed between the two groups. Sclerostin level correlated positively with spine Bone Mineral Density (BMD), while 25-hydroxyvitamin D correlated negatively with hip BMD in the control group. No significant correlation was observed between other markers with spine or hip BMD.
CONCLUSION: These data provide an insight into the possible roles of osteocyte markers, especially osteoprotegerin and sclerostin, in classifying subjects with osteoporosis. However, the lack of association between these markers and BMD indicates that osteoporosis is a complex and multifactorial condition.
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.