METHODS: A cross-sectional survey using the EQ-5D-3L instrument was conducted between May to September 2018 across various public hospitals in Malaysia. Using a multi-stage sampling, patients diagnosed with TDT and receiving iron chelating therapy were sampled. The findings on the EQ-5D-3L survey were converted into utility values using local tariff values. A two-part model was used to examine and derive the HSUVs associated with the treatment and complications of iron overload in TDT.

RESULTS: A total of 585 patients were surveyed. The unadjusted mean (SD) EQ-5D-3L utility value for TDT patients were 0.893 (0.167) while mean (SD) EQ VAS score was 81.22 (16.92). Patients who had more than two iron overload complications had a significant decline in HRQoL. Patients who were on oral monotherapy had a higher utility value of 0.9180 compared to other regimen combinations.

METHODS: The algorithm was developed using data from 345 TDT patients. Spearman's rank correlation was used to evaluate the conceptual overlap between the instruments. Model specifications were chosen using a stepwise regression. Both direct and response mapping methods were attempted. Six mapping estimation methods ordinary least squares (OLS), a log-transformed response using OLS, generalized linear model (GLM), two-part model (TPM), Tobit and multinomial logistic regression (MLOGIT) were tested to determine the root mean squared error (RMSE) and mean absolute error (MAE). Other criterion used were accuracy of the predicted utility score, proportions of absolute differences that was less than 0.03 and intraclass correlation coefficient. An in-sample, leave-one-out cross validation was conducted to test the generalizability of each model.

RESULTS: The best performing model was specified with three out of the four PedsQL GCS scales-the physical, emotional and social functioning score. The best performing estimation method for direct mapping was a GLM with a RMSE of 0.1273 and MAE of 0.1016, while the best estimation method for response mapping was the MLOGIT with a RMSE of 0.1597 and MAE of 0.0826.

METHODS: The total lifetime cost per TDT patient (TC1) is the sum of lifetime healthcare cost (TC2) and lifetime patient and family healthcare expenditure (TC3). TC2 was simulated using the Markov model, taking into account all costs subsidized by the government, and TC3 was estimated through a cross-sectional health survey approach. A survey was performed using a two-stage sampling method in 13 thalassaemia centres covering all regions in Malaysia.

RESULTS: A TDT patient is expected to incur TC2 of USD 561,208. ICT was the main driver of cost and accounted for 56.9% of the total cost followed by blood transfusion cost at 13.1%. TC3 was estimated to be USD 45,458. Therefore, the estimated TC1 of a TDT patient was USD 606,665. Sensitivity analyses showed that if all patients were prescribed oral ICT deferasirox for their lifetime, the total healthcare cost would increase by approximately 65%. Frequency of visits to health facilities for blood transfusion/routine monitoring and patients who were prescribed desferrioxamine were observed to be factors affecting patient and family monthly expenses.

METHODS: A cross-sectional HRQoL survey of Malaysian children with TDT was conducted using the PedsQL™ 4.0 Generic Core Scales. Patients with non-transfusion dependent thalassemia and other haemoglobinopathies were excluded. Parent-proxy and self-reported HRQoL scores were obtained using a multi-stage convenient sampling. The relationship between HRQoL scores and demographic factors were tested using association, correlation and regression analysis.

METHOD: Data from 30 public hospitals with thalassaemia care centres were collected. A double bootstrap data envelopment analysis (DEA) approach is used with the assumption of input-oriented and variable-to-scale DEA models to generate technical efficiency scores. Bootstrap truncated regression was later conducted to identify the factors affecting the efficiency scores.

RESULTS: The mean bias-corrected technical efficiency score has improved to 0.75 in 2017 from 0.71 in 2016. In both years, more than 50% of thalassaemia care centres showed good efficiency scores (0.8-1.0). Management factors that affect the efficiency scores include separation of patient management (β = 0.0653) and budget (β = 0.0843), where they are found to positively affect the efficiency scores. In contrast, having longer operating hours is found to inversely influence the performance levels (β = - 0.4023).

PATIENTS AND METHODS: Semi-structured online interviews comprised of six focus group discussions and five individual interviews were performed with 26 breast cancer patients. The interviews were recorded, transcribed, and analyzed using the reflexive thematic analysis approach.

RESULTS: Four main themes were derived: (1) positive treatment outcomes; (2) the negative impact of treatment-related side effects on quality of life; (3) treatment accessibility, availability, and timeliness; (4) cost of treatment. Patients revealed a strong preference towards treatments that yield longer survival, achieve remission, and prevent cancer recurrence. Additionally, patients favored treatments with minimal side effects that had minimal impact on their quality of life. There was a notable preference for treatments that were easily accessible and available in a timely manner. However, patients faced challenging decisions in balancing the costs of treatments with their benefits, leading to a consistent preference for treatments supported by government funding or medical insurance to alleviate financial burdens.