METHODS: This study included participants from the intervention arm of a randomised controlled trial which was conducted to evaluate the effects of pharmacist-led interventions on CML patients treated with TKIs. Participants were recruited and followed up in the haematology clinics of two hospitals in Malaysia from March 2017 to January 2019. A pharmacist identified DRPs and helped to resolve them. Patients were followed-up for six months, and their DRPs were assessed based on the Pharmaceutical Care Network Europe Classification for DRP v7.0. The identified DRPs, the pharmacist's interventions, and the acceptance and outcomes of the interventions were recorded. A Poisson multivariable regression model was used to analyse factors associated with the number of identified DRPs per participant.
RESULTS: A total of 198 DRPs were identified from 65 CML patients. The median number of DRPs per participants was 3 (interquartile range: 2, 4). Most participants (97%) had at least one DRP, which included adverse drug events (45.5%), treatment ineffectiveness (31.5%) and patients' treatment concerns or dissatisfaction (23%). The 228 causes of DRPs identified comprised the following: lack of disease or treatment information, or outcome monitoring (47.8%), inappropriate drug use processes (23.2%), inappropriate patient behaviour (19.9%), suboptimal drug selection (6.1%), suboptimal dose selection (2.6%) and logistic issues in dispensing (0.4%). The number of concomitant medications was significantly associated with the number of DRPs (adjusted Odds Ratio: 1.100; 95% CI: 1.005, 1.205; p = 0.040). Overall, 233 interventions were made. These included providing patient education on disease states or TKI-related side effects (75.1%) and recommending appropriate instructions for taking medications (7.7%). Of the 233 interventions, 94.4% were accepted and 83.7% were implemented by the prescriber or patient. A total of 154 DRPs (77.3%) were resolved.
CONCLUSIONS: The pharmacist-led interventions among CML patients managed to identify various DRPs, were well accepted by both TKI prescribers and patients, and had a high success rate of resolving the DRPs.
OBJECTIVES: We aimed to assess the extent of treatment interruption caused by efavirenz-associated ADEs.
METHODS: A case-control study of efavirenz recipients who did, versus did not (control) develop adverse drug events (ADE), and who were matched for baseline CD4 + at a ratio of 1:1.3 was conducted. Antiretroviral -naïve patients who were started on efavirenz were followed up retrospectively, and their records scrutinized every month for 2 years. Demographic and clinical predictors of treatment interruption were computed using Cox proportional hazard models. Kaplan- Meier curves were plotted to assess time to treatment interruption for the two groups. Clinical endpoints were: i) efficacy -improved CD4 + counts and/or viral load (VL) suppression, ii) safety -absence of treatment-limiting toxicities, and iii) durability - no interruption until follow-up ended.
RESULTS: Both groups had comparable CD4 + counts at baseline (p = 0.15). At t = 24-months, VL in both groups were suppressed to undetectable levels (<20 copies/mL) while median CD4 + was 353 cells/µL (IQR: 249-460). The mean time on treatment was 23 months (95% CI, 22.3 -23.4) in the control group without ADE and 20 months (95% CI, 18.9 - 21.6) in the ADE group (p = 0.001). Kaplan-Meier plots demonstrated that 59.5% of patients who experienced ≥ 1 ADE versus 81% of those who did not experience any ADE were estimated to continue treatment for up to 24 months with no interruption (p = 0.001). Most interruptions to EFV treatment occurred in the presence of opportunistic infections and these were detected within the first 5 months of treatment initiation. Independent predictors which negatively impacted the dependent variable i.e., treatment durability, were intravenous drug use (adjusted hazard ratio, aHR 2.17, 95% CI, 1.03-4.61, p = 0.043), presence of ≥ 1 opportunistic infection(s) (aHR 2.2, 95% CI, 1.13-4.21, p = 0.021), and presence of ≥ 1 serious ADE(s) (aHR 4.18, 95% CI, 1.98-8.85, p = 0.00).
CONCLUSION: Efavirenz' role as the preferred first-line regimen for South-East Asia's resource-limited regions will need to be carefully tailored to suit the regional population. Findings have implications to policy-makers and clinicians, particularly for the treatment of patients who develop ADEs and opportunistic infections, and for intravenous drug user subgroups.
METHODS: This was a questionnaire-based, cross-sectional study. Data was collected from cancer patients attending to three departments: surgical, medical and gynaecology at a local hospital in Malaysia. Ethical approval was obtained from the Medical Research Ethics Committee, Ministry of Health, Malaysia.
RESULTS: A total of 273 patients were recruited. Prevalence of CAM used for CRSE management was 166 (60.8%). Of the CAM users, 144 (86.7%) were female, 102 (61.4%) were employed and 123 (74.1%) were married. Breast cancer patients were found to be the highest users of CAM (n=76; 45.8%). The top three CAM used by patients in managing CRSE were dietary supplements (n=166; 100%); herbal products (n=154; 92.8%) and traditional Malay therapy (n=147; 88.6%). About 83% (n=137) patients disclosed CAM use to their prescribers. Among these, 58 (42.3%) reported that their doctors encouraged the use, whereas 89 (65.0%) patients claimed their doctors disagreed the use of CAM.
CONCLUSIONS: Prescribers still have doubt in combining chemotherapy with CAM, hence patients use CAM discreetly. Increasing the awareness and understanding of CAM use are mandatory to distinguish its possible synergistic or adverse reactions with cancer patients.
METHODS: All ADR associated with the use of CAM products (including health supplements) submitted to the Malaysian Centre for ADR Monitoring, National Pharmaceutical Regulatory Agency over a 15-year period were reviewed and analysed. Multivariate logistic regression analysis was performed to identify predictors of serious ADR.
RESULTS AND DISCUSSION: From a total of 74 997 reports in the database, 930 (1.2%) involved CAM products, and 242 (26%) were serious with 36 deaths. About a third of the reports involved used CAM products for health maintenance. Most (78.1%) of the ADR reports implicated unregistered products with 16.7% confirmed to contain adulterants which were mainly dexamethasone. Of the 930 reports, the ADR involved skin and appendages disorders (18.4%) followed by liver and biliary system disorders (13.7%). The odds of someone experiencing serious ADR increased if the CAM products were used for chronic illnesses (odds ratio [OR] 1.99, confidence interval [CI] 1.46-2.71), having concurrent diseases (OR 1.51, CI 1.04-2.19) and taking concurrent drugs (OR 1.44, CI 1.03-2.02).
WHAT IS NEW AND CONCLUSIONS: The prevalence of serious ADR associated with CAM products is high. Factors identified with serious ADR included ethnicity, CAM users with pre-existing diseases, use of CAM for chronic illnesses and concomitant use of CAM products with other drugs. The findings could be useful for planning strategies to institute measures to ensure safe use of CAM products.
OBJECTIVE: From the considerable amount of clinical narrative text, natural language processing (NLP) researchers have developed methods for extracting ADEs and their related attributes. This work presents a systematic review of current methods.
METHODOLOGY: Two biomedical databases have been searched from June 2022 until December 2023 for relevant publications regarding this review, namely the databases PubMed and Medline. Similarly, we searched the multi-disciplinary databases IEEE Xplore, Scopus, ScienceDirect, and the ACL Anthology. We adopted the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) 2020 statement guidelines and recommendations for reporting systematic reviews in conducting this review. Initially, we obtained 5,537 articles from the search results from the various databases between 2015 and 2023. Based on predefined inclusion and exclusion criteria for article selection, 100 publications have undergone full-text review, of which we consider 82 for our analysis.
RESULTS: We determined the general pattern for extracting ADEs from clinical notes, with named entity recognition (NER) and relation extraction (RE) being the dual tasks considered. Researchers that tackled both NER and RE simultaneously have approached ADE extraction as a "pipeline extraction" problem (n = 22), as a "joint task extraction" problem (n = 7), and as a "multi-task learning" problem (n = 6), while others have tackled only NER (n = 27) or RE (n = 20). We further grouped the reviews based on the approaches for data extraction, namely rule-based (n = 8), machine learning (n = 11), deep learning (n = 32), comparison of two or more approaches (n = 11), hybrid (n = 12) and large language models (n = 8). The most used datasets are MADE 1.0, TAC 2017 and n2c2 2018.
CONCLUSION: Extracting ADEs is crucial, especially for pharmacovigilance studies and patient medications. This survey showcases advances in ADE extraction research, approaches, datasets, and state-of-the-art performance in them. Challenges and future research directions are highlighted. We hope this review will guide researchers in gaining background knowledge and developing more innovative ways to address the challenges.