Ischemic Stroke and Savings in Time to Achieve Functional Recovery: Experience from NeuroAiD.

Despite recent progress with revascularisation interventions after acute ischemic stroke, many patients remain disabled after stroke. Using data from a multi-centre, randomised, double-blind, placebo-controlled trial of a neuro-repair treatment (NeuroAiD/MLC601) with a long-term follow-up, we analysed the savings in time to functional recovery, measured by a modified Rankin Scale (mRS) score of 0 or 1, in patients receiving a 3-month oral course of MLC601. Analysis of time to recovery was assessed by a log-rank test and hazard ratios (HRs) adjusted for prognosis factors. A total of 548 patients with baseline NIHSS scores 8-14, mRS scores ≥ 2 at day 10 post-stroke, and at least one mRS assessment on or after month 1 were included in the analysis (placebo = 261; MLC601 = 287). Time to functional recovery was significantly shortened for patients receiving MLC601 versus patients receiving placebo (log-rank test: p = 0.039). This result was confirmed by Cox regression adjusting for the main baseline prognostic factors (HR: 1.30 [0.99, 1.70]; p = 0.059) and was more pronounced in patients with additional poor prognosis factors. The Kaplan-Meier plot showed that approximately 40% cumulative incidence of functional recovery was achieved within 6 months after stroke onset in the MLC601 group versus 24 months in the placebo group. The main findings are that MLC601 reduced the time to achieve functional recovery, and a 40% functional recovery rate was achieved 18 months earlier compared to placebo.

What are the impacts of increasing cost-effectiveness Threshold? a protocol on an empirical study based on economic evaluations conducted in Thailand.

BACKGROUND: Economic evaluations have been widely used to inform and guide policy-making process in healthcare resources allocation as a part of an evidence package. An intervention is considered cost-effective if an ICER is less than a cost-effectiveness threshold (CET), where a CET represents the acceptable price for a unit of additional health gain which a decision-maker is willing to pay. There has been discussion to increase a CET in many settings such as the United Kingdom and Thailand. To the best of our knowledge, Thailand is the only country that has an explicit CET and has revised their CET, not once but twice. Hence, the situation in Thailand provides a unique opportunity for evaluating the impact of changing CET on healthcare expenditure and manufacturers' behaviours in the real-world setting. Before we decide whether a CET should be increased, information on what happened after the CET was increased in the past could be informative and helpful. OBJECTIVES: This study protocol describes a proposed plan to investigate the impact of increased cost-effectiveness threshold using Thailand as a case study. Specifically, we will examine the impact of increasing CET on the drug prices submitted by pharmaceutical companies to the National List of Essential Medicine (NLEM), the decision to include or exclude medications in the NLEM, and the overall budget impact. MATERIALS AND DESIGNS: Retrospective data analysis of the impact of increased CET on national drug committee decisions in Thailand (an upper middle-income country) will be conducted and included data from various sources such as literature, local organizations (e.g. Thai Food and Drug Administration), and inputs from stakeholder consultation meetings. The outcomes include: (1) drug price submitted by the manufacturers and final drug price included in the NLEM if available; (2) decisions about whether the drug was included in the NLEM for reimbursement; and (3) budget impact. The independent variables include a CET, the variable of interest, which can take values of THB100,000, THB120,000, or THB160,000, and potential confounders such as whether this drug was for a chronic disease, market size, and primary endpoint. We will conduct separate multivariable regression analysis for each outcome specified above. DISCUSSION: Understanding the impact of increasing the CET would be helpful in assisting the decision to use and develop an appropriate threshold for one's own setting. Due to the nature of the study design, the findings will be prone to confounding effect and biases; therefore, the analyses will be adjusted for potential confounders and statistical methods will be explored to minimize biases. Knowledge gained from the study will be conveyed to the public through various disseminations such as reports, policy briefs, academic journals, and presentations.

Cost effectiveness analysis of a polygenic risk tailored breast cancer screening programme in Singapore.

BACKGROUND: This study aimed to evaluate the cost-effectiveness of a breast cancer screening programme that incorporates genetic testing using breast cancer associated single nucleotide polymorphisms (SNPs), against the current biennial mammogram-only screening programme to aid in its implementation into the current programme in Singapore. METHODS: A Markov model was used to compare the costs and health outcomes of the current screening programme, against a polygenic risk-tailored screening programme, which can advise a long-term screening strategy depending on the individual's polygenic risk. The model took the perspective of the healthcare system, with a time horizon of 40 years, following women from the age of 35 to 74. Epidemiological and cost data were taken from Asian studies, and an annual discount rate of 3% was used. The model outcome was the incremental cost-effectiveness ratio (ICER), calculated from the difference in costs per quality-adjusted life year (QALY). Scenarios with varying risk thresholds for each polygenic risk group were examined. One-way and probabilistic sensitivity analyses were performed to assess parameter uncertainty. RESULTS: The ICER for a polygenic risk-tailored breast cancer screening programme, compared with the current biennial mammogram-only screening programme, was - 3713.80 SGD/QALY, with incremental costs < 0 and incremental effects > 0. The scenario analysis of different polygenic risk cutoffs showed that the ICERs remain negative, with all ICERs falling within the south-east quadrant of the cost-effectiveness plane, indicating that tailored screening is more cost effective than mammogram-only screening, with lower costs and higher QALYs to be gained. This suggests that a polygenic risk-tailored breast cancer screening programme is cost effective, entailing lower cost than the current mammogram-only programme, while causing no additional harm to women. CONCLUSION: Results from this cost-effectiveness analysis show that polygenic risk-tailored screening is cost effective with an ICER of - 3713.80 SGD/QALY. Tailored screening remains cost effective even across varying percentile cutoffs for each risk group. While the results look promising for incorporating polygenic risk into the current breast cancer screening programme, further studies should be conducted to address various limitations.

Indirect derivation of biological variation data and analytical performance specifications for therapeutic drug monitoring activities.

We applied the indirect approach using anonymised data from an Australian and a Singapore laboratory to derive biological variation data for a group of 10 therapeutic drugs routinely monitored. A series of inclusion and exclusion criteria were applied on the data. The within- (CVi) and between-individual (CVg) biological variation data were then derived as previously described. The corresponding index of individuality and analytical performance specifications were also calculated. The biological variation data were overall very similar between the two study sites. Moreover, the biological variation data were also comparable between males and females, as well as whether the data originated from patients who only had two episodes of measurement during the study period or from the last two results from patients who had more than two episodes of measurement during the study period. The results presented in this study contribute towards the biological variation data for therapeutic drugs, which can be used to inform discussions about the setting of harmonised analytical performance specifications for these measurands.

Cost-benefit analysis of introducing next-generation sequencing (metagenomic) pathogen testing in the setting of pyrexia of unknown origin.

Pyrexia of unknown origin (PUO) is defined as a temperature of >38.3°C that lasts for >3 weeks, where no cause can be found despite appropriate investigation. Existing protocols for the work-up of PUO can be extensive and costly, motivating the application of recent advances in molecular diagnostics to pathogen testing. There have been many reports describing various analytical methods and performance of metagenomic pathogen testing in clinical samples but the economics of it has been less well studied. This study pragmatically evaluates the feasibility of introducing metagenomic testing in this setting by assessing the relative cost of clinically-relevant strategies employing this investigative tool under various cost and performance scenarios using Singapore as a demonstration case, and assessing the price and performance benchmarks, which would need to be achieved for metagenomic testing to be potentially considered financially viable relative to the current diagnostic standard. This study has some important limitations: we examined only impact of introducing the metagenomic test to the overall diagnostic cost and excluded costs associated with hospitalization and makes assumptions about the performance of the routine diagnostic tests, limiting the cost of metagenomic test, and the lack of further work-up after positive pathogen detection by the metagenomic test. However, these assumptions were necessary to keep the model within reasonable limits. In spite of these, the simplified presentation lends itself to the illustration of the key insights of our paper. In general, we find the use of metagenomic testing as second-line investigation is effectively dominated, and that use of metagenomic testing at first-line would typically require higher rates of detection or lower cost than currently available in order to be justifiable purely as a cost-saving measure. We conclude that current conditions do not warrant a widespread rush to deploy metagenomic testing to resolve any and all uncertainty, but rather as a front-line technology that should be used in specific contexts, as a supplement to rather than a replacement for careful clinical judgement.

Impact of analytical and biological variations on classification of diabetes using fasting plasma glucose, oral glucose tolerance test and HbA1c.

Historically, diabetes is diagnosed by measuring fasting (FPG) and two-hour post oral glucose load (OGTT) plasma concentration and interpreting it against recommended clinical thresholds of the patient. More recently, glycated haemoglobin A1c (HbA1c) has been included as a diagnostic criterion. Within-individual biological variation (CVi), analytical variation (CVa) and analytical bias of a test can impact on the accuracy and reproducibility of the classification of a disease. A test with large biological and analytical variation increases the likelihood of erroneous classification of the underlying disease state of a patient. Through numerical simulations based on the laboratory results generated from a large population health survey, we examined the impact of CVi, CVa and bias on the classification of diabetes using fasting plasma glucose (FPG), oral glucose tolerance test (OGTT) and HbA1c. From the results of the simulations, HbA1c has comparable performance to FPG and is better than OGTT in classifying subjects with diabetes, particularly when laboratory methods with smaller CVa are used. The use of the average of the results of the repeat laboratory tests has the effect of ameliorating the combined (analytical and biological) variation. The averaged result improves the consistency of the disease classification.