METHODS: A validated computer simulation model (the IMS CORE Diabetes Model) was used to estimate the long-term projection of costs and clinical outcomes. The model was populated with published characteristics of Thai patients with type 2 diabetes. Baseline risk factors were obtained from Thai cohort studies, while relative risk reduction was derived from a meta-analysis study conducted by the Canadian Agency for Drugs and Technology in Health. Only direct costs were taken into account. Costs of diabetes management and complications were obtained from hospital databases in Thailand. Both costs and outcomes were discounted at 3 % per annum and presented in US dollars in terms of 2014 dollar value. Incremental cost-effectiveness ratio (ICER) was calculated. One-way and probabilistic sensitivity analyses were also performed.
RESULTS: IGlar is associated with a slight gain in quality-adjusted life years (0.488 QALYs), an additional life expectancy (0.677 life years), and an incremental cost of THB119,543 (US$3522.19) compared with NPH insulin. The ICERs were THB244,915/QALY (US$7216.12/QALY) and THB176,525/life-year gained (LYG) (US$5201.09/LYG). The ICER was sensitive to discount rates and IGlar cost. At the acceptable willingness to pay of THB160,000/QALY (US$4714.20/QALY), the probability that IGlar was cost effective was less than 20 %.
CONCLUSIONS: Compared to treatment with NPH insulin, treatment with IGlar in type 2 diabetes patients who had uncontrolled blood glucose with oral anti-diabetic drugs did not represent good value for money at the acceptable threshold in Thailand.
RESULTS: We present an automated gene prediction pipeline, Seqping that uses self-training HMM models and transcriptomic data. The pipeline processes the genome and transcriptome sequences of the target species using GlimmerHMM, SNAP, and AUGUSTUS pipelines, followed by MAKER2 program to combine predictions from the three tools in association with the transcriptomic evidence. Seqping generates species-specific HMMs that are able to offer unbiased gene predictions. The pipeline was evaluated using the Oryza sativa and Arabidopsis thaliana genomes. Benchmarking Universal Single-Copy Orthologs (BUSCO) analysis showed that the pipeline was able to identify at least 95% of BUSCO's plantae dataset. Our evaluation shows that Seqping was able to generate better gene predictions compared to three HMM-based programs (MAKER2, GlimmerHMM and AUGUSTUS) using their respective available HMMs. Seqping had the highest accuracy in rice (0.5648 for CDS, 0.4468 for exon, and 0.6695 nucleotide structure) and A. thaliana (0.5808 for CDS, 0.5955 for exon, and 0.8839 nucleotide structure).
CONCLUSIONS: Seqping provides researchers a seamless pipeline to train species-specific HMMs and predict genes in newly sequenced or less-studied genomes. We conclude that the Seqping pipeline predictions are more accurate than gene predictions using the other three approaches with the default or available HMMs.
METHODS: A validated IMS CORE Diabetes Model was used to estimate the long-term costs and outcomes. The efficacy parameters were identified and synthesized using a systematic review and meta-analysis. Baseline characteristics and cost parameters were obtained from published studies and hospital databases in Thailand. Costs were expressed in 2014 US Dollars. Outcomes were presented as an incremental cost-effectiveness ratio (ICER). One-way and probabilistic sensitivity analyses were performed to estimate parameter uncertainty.
RESULTS: From a societal perspective, treatment with DPP-4 inhibitors yielded more quality-adjusted life years (QALYs) (0.024) at a higher cost (>66,000 Thai baht (THB) or >1,829.27 USD) per person than SFU, resulting in the ICER of >2.7 million THB/QALY (>74,833.70 USD/QALY). The cost-effectiveness results were mainly driven by differences in HbA1c reduction, hypoglycemic events, and drug acquisition cost of DPP-4 inhibitors. At the ceiling ratio of 160,000 THB/QALY (4,434.59 USD/QALY), the probability that DPP-4 inhibitors are cost-effective compared to SFU was less than 10%.
CONCLUSIONS: Compared to SFU, DPP-4 inhibitor monotherapy is not a cost-effective treatment for people with T2DM and CKD in Thailand.
METHODS: Cost-effectiveness analysis used decision tree and Markov models to estimate lifetime costs and health benefits from societal perspective, based on a cohort of 509 metabolic syndrome patients in Thailand. Data were obtained from published literatures and Thai database. Results were reported as incremental cost-effectiveness ratios (ICERs) in 2014 US dollars (USD) per quality-adjusted life year (QALY) gained with discount rate of 3%. Sensitivity analyses were performed to assess the influence of parameter uncertainty on the results.
RESULTS: The ICER of ultrasonography screening of 50-year-old metabolic syndrome patients with intensive weight reduction program was 958 USD/QALY gained when compared with no screening. The probability of being cost-effective was 67% using willingness-to-pay threshold in Thailand (4848 USD/QALY gained). Screening before 45 years was cost saving while screening at 45 to 64 years was cost-effective.
CONCLUSIONS: For patients with metabolic syndromes, ultrasonography screening for NAFLD with intensive weight reduction program is a cost-effective program in Thailand. Study can be used as part of evidence-informed decision making.
TRANSLATIONAL IMPACTS: Findings could contribute to changes of NAFLD diagnosis practice in settings where economic evidence is used as part of decision-making process. Furthermore, study design, model structure, and input parameters could also be used for future research addressing similar questions.