PURPOSE: The study aimed to evaluate the budget impact of increasing the uptake of denosumab for the management of postmenopausal osteoporosis in Malaysia.
METHODS: A Markov budget impact model was developed to estimate the financial impact of osteoporosis treatment. We modelled a scenario in which the uptake of denosumab would increase each year compared with a static scenario. A 5-year time horizon from the perspective of a Malaysian MOH healthcare provider was used. Model inputs were based on Malaysian sources where available. Sensitivity analyses were performed to examine the robustness of the modelled results.
RESULTS: An increase in denosumab uptake of 8% per year over a 5-year time horizon would result in an additional budget impact, from MYR 0.26 million (USD 0.06 million) in the first year to MYR 3.25 million (USD 0.78 million) in the fifth year. When expressed as cost per-member-per-month (PMPM), these were less than MYR 0.01 across all five years of treatment. In sensitivity analyses, the acquisition cost of denosumab and medication persistence had the largest impact on the budget.
CONCLUSION: From the perspective of a Malaysian MOH healthcare provider, moderately increasing uptake of denosumab would have a minimal additional budget impact, partially offset by savings in fracture treatment costs. Increasing the use of denosumab appears affordable to reduce the economic burden of osteoporosis in Malaysia.
METHODS: A total of 6221 tweets related to breast cancer posted between 2018 and 2022 were collected. An oncologist and two pharmacists coded the tweets to differentiate between true information and misinformation, and to analyse the misinformation content. Binary logistic regression was conducted to identify determinants of misinformation.
RESULTS: There were 780 tweets related to breast cancer prevention and treatment, and 456 (58.5%) contain misinformation, with significantly more misinformation in Malay compared to English tweets (OR = 6.18, 95% CI: 3.45-11.07, p
AIM: The aim of this study was to determine the characteristics of medication complexity and polypharmacy and determine their relationship with drug-related problems (DRP) and control of iron overload in transfusion-dependent thalassaemia patients.
METHOD: Data were derived from a cross-sectional observational study on characteristics of DRPs conducted at a Malaysian tertiary hospital. The medication regimen complexity index (MRCI) was determined using a validated tool, and polypharmacy was defined as the chronic use of five or more medications. The receiver operating characteristic curve analysis was used to determine the optimal cut-off value for MRCI, and logistic regression analysis was conducted.
RESULTS: The study enrolled 200 adult patients. The MRCI cut-off point was proposed to be 17.5 (Area Under Curve = 0.722; sensitivity of 73.3% and specificity of 62.0%). Approximately 73% and 64.5% of the patients had polypharmacy and high MRCI, respectively. Findings indicated that DRP was a full mediator in the association between MRCI and iron overload.
CONCLUSION: Transfusion-dependent thalassaemia patients have high MRCI and suboptimal control of iron overload conditions in the presence of DRPs. Thus, future interventions should consider MRCI and DRP as factors in serum iron control.