METHODS: A systematic search of English articles and gray literature, published from January 2010, was performed on databases including MEDLINE, Embase, Scopus, NHSEED, health technology assessment, Cochrane Library, etc. The included studies were EEs with DAMs that compared the costs and outcomes of angiotensin-converting enzyme inhibitors, angiotensin-receptor blockers, angiotensin-receptor neprilysin inhibitors, beta-blockers, mineralocorticoid-receptor agonists, and sodium-glucose cotransporter-2 inhibitors. The study quality was evaluated using the Bias in Economic Evaluation (ECOBIAS) 2015 checklist and Consolidated Health Economic Evaluation Reporting Standards (CHEERS) 2022 checklists.
RESULTS: A total of 59 EEs were included. Markov model, with a lifetime horizon and a monthly cycle length, was most commonly used in evaluating GDMTs for HFrEF. Most EEs conducted in the high-income countries demonstrated that novel GDMTs for HFrEF were cost-effective compared with the standard of care, with the standardized median incremental cost-effectiveness ratio (ICER) of $21 361/quality-adjusted life-year. The key factors influencing ICERs and study conclusions included model structures, input parameters, clinical heterogeneity, and country-specific willingness-to-pay threshold.
CONCLUSIONS: Novel GDMTs were cost-effective compared with the standard of care. Given the heterogeneity of the DAMs and ICERs, alongside variations in willingness-to-pay thresholds across countries, there is a need to conduct country-specific EEs, particularly in low- and middle-income countries, using model structures that are coherent with the local decision context.
METHODS: We surveyed HFrEF patients from two hospitals in Malaysia, using Malay, English or Chinese versions of EQ-5D-5L. EQ-5D-5L dimensional scores were converted to utility scores using the Malaysian value set. A confirmatory factor analysis longitudinal model was constructed. The utility and visual analog scale (VAS) scores were evaluated for validity (convergent, known-group, responsiveness), and measurement equivalence of the three language versions.
RESULTS: 200 HFrEF patients (mean age = 61 years), predominantly male (74%) of Malay ethnicity (55%), completed the admission and discharge EQ-5D-5L questionnaire in Malay (49%), English (26%) or Chinese (25%) languages. 173 patients (86.5%) were followed up at 1-month post-discharge (1MPD). The standardized factor loadings and average variance extracted were ≥ 0.5 while composite reliability was ≥ 0.7, suggesting convergent validity. Patients with older age and higher New York Heart Association (NYHA) class reported significantly lower utility and VAS scores. The change in utility and VAS scores between admission and discharge was large, while the change between discharge and 1MPD was minimal. The minimal clinically important difference for utility and VAS scores was ±0.19 and ±11.01, respectively. Malay and English questionnaire were equivalent while the equivalence of Malay and Chinese questionnaire was inconclusive.
LIMITATION: This study only sampled HFrEF patients from two teaching hospitals, thus limiting the generalizability of results to the entire heart failure population.
CONCLUSION: EQ-5D-5L is a valid questionnaire to measure health-related quality of life and estimate utility values among HFrEF patients in Malaysia. The Malay and English versions of EQ-5D-5L appear equivalent for clinical and economic assessments.
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.