The cost-effectiveness of NT-proBNP for assessment of suspected acute heart failure in the emergency department.

AIMS: When relying on clinical assessment alone, an estimated 22% of acute heart failure (AHF) patients are missed, so clinical guidelines recommend the use of N-terminal pro-B-type natriuretic peptide (NT-proBNP) for AHF diagnosis. Since publication of these guidelines, there has been poor uptake of NT-proBNP testing in part due to concerns over excessive false positive referrals resulting from the low specificity of a single 'rule-out' threshold of <300 pg/mL. Low specificity can be mitigated by the addition of age-specific 'rule-in' NT-proBNP thresholds. METHODS AND RESULTS: A theoretical hybrid decision tree/semi-Markov model was developed, combining global trial and audit data to evaluate the cost-effectiveness of NT-proBNP testing using age-specific rule-in/rule-out (RI/RO) thresholds, compared with NT-proBNP RO only and with clinical decision alone (CDA). Cost-effectiveness was measured as the incremental cost per quality-adjusted life year (QALY) gained and incremental net health benefit. In the base case, using UK-specific inputs, NT-proBNP RI/RO was associated with both greater QALYs and lower costs than CDA. At a willingness-to-pay threshold of £20 000/QALY, NT-proBNP RO was also cost-effective compared with CDA [incremental cost-effectiveness ratio (ICER) of £8322/QALY], but not cost-effective vs. RI/RO (ICER of £64 518/QALY). Overall, NT-proBNP RI/RO was the most cost-effective strategy. Sensitivity and scenario analyses were undertaken; the conclusions were not impacted by plausible variations in parameters, and similar conclusions were obtained for the Netherlands and Spain. CONCLUSIONS: An NT-proBNP strategy that combines an RO threshold with age-specific RI thresholds provides a cost-effective alternative to the currently recommended NT-proBNP RO only strategy, achieving greater diagnostic specificity with minimal reduction in sensitivity and thus reducing unnecessary echocardiograms and hospital admissions.

What is the optimal management of potentially resectable stage III-N2 NSCLC? Results of a fixed-effects network meta-analysis and economic modelling.

Introduction: There is a critical need to understand the optimal treatment regimen in patients with potentially resectable stage III-N2 nonsmall cell lung cancer (NSCLC). Methods: A systematic review of randomised controlled trials was carried out using a literature search including the CDSR, CENTRAL, DARE, HTA, EMBASE and MEDLINE bibliographic databases. Selected trials were used to perform a Bayesian fixed-effects network meta-analysis and economic modelling of treatment regimens relevant to current-day treatment options: chemotherapy plus surgery (CS), chemotherapy plus radiotherapy (CR) and chemoradiotherapy followed by surgery (CRS). Findings: Six trials were prioritised for evidence synthesis. The fixed-effects network meta-analyses demonstrated an improvement in disease-free survival (DFS) for CRS versus CS and CRS versus CR of 0.34 years (95% CI 0.02-0.65) and 0.32 years (95% CI 0.05-0.58) respectively, over a 5-year period. No evidence of effect was observed in overall survival although point estimates favoured CRS. The probabilities that CRS had a greater mean survival time and greater probability of being alive than the reference treatment of CR at 5 years were 89% and 86% respectively. Survival outcomes for CR and CS were essentially equivalent. The economic model calculated that CRS and CS had incremental cost-effectiveness ratios of £19 000/quality-adjusted life-year (QALY) and £78 000/QALY compared to CR. The probability that CRS generated more QALYs than CR and CS was 94%. Interpretation: CRS provides an extended time in a disease-free state leading to improved cost-effectiveness over CR and CS in potentially resectable stage III-N2 NSCLC.

Brain imaging in lung cancer staging: A real-world, multi-centre study of prevalence of brain metastases, impact on treatment and re-modelling of the NICE health economic analysis.

INTRODUCTION: In 2019, the National Institute for Health and Care Excellence (NICE) updated their recommendations with respect to brain imaging in the staging of non-small cell lung cancer (NSCLC) based on an analytic cost-effectiveness model using published data and modelling assumptions from committee experts. In this study, we aimed to re-run this model using real-world multi-centre UK data. MATERIALS AND METHODS: Retrospective data was collected on consecutive patients with radically treatable clinical stage II and III lung cancer from eleven acute NHS Trusts during the calendar year 01/01/2018 to 31/12/2018. Following a written application to the NICE lung cancer guideline committee, we were granted access to the NG122 brain imaging economic model for the purpose of updating the input parameters in line with the real-world findings from this study. RESULTS: A total of 444 patients had data for analysis. The combined prevalence of occult brain metastases was 6.2% (10/165) in stage II and 6% (17/283) in stage III, compared to 9.5% and 9.3% used in the NICE economic model. 30% of patients with clinical stage III NSCLC and occult BMs on pre-treatment imaging went onto complete the planned curative intent treatment of extracranial disease, 60% completed SRS to the brain and 30% completed WBRT. This compares to 0%, 10% and 0% in the NICE assumptions. The health economic analysis concluded that brain imaging was no longer cost-effective in stage II disease (ICERs £50,023-£115,785) whilst brain imaging remained cost-effective for stage III patients (ICERs 17,000-£22,173), with MRI being the most cost-effective strategy. CONCLUSION: This re-running of the NICE health economic model with real-world data strongly supports the NICE guideline recommendation for brain imaging prior to curative-intent treatment in stage III lung cancer but questions the cost-effectiveness of CT brain imaging prior to curative-intent treatment in stage II lung cancer.

A non-parametric approach for jointly combining evidence on progression free and overall survival time in network meta-analysis.

Randomised controlled trials of cancer treatments typically report progression free survival (PFS) and overall survival (OS) outcomes. Existing methods to synthesise evidence on PFS and OS either rely on the proportional hazards assumption or make parametric assumptions which may not capture the diverse survival curve shapes across studies and treatments. Furthermore, PFS and OS are not independent; OS is the sum of PFS and post-progression survival (PPS). Our aim was to develop a non-parametric approach for jointly synthesising evidence from published Kaplan-Meier survival curves of PFS and OS without assuming proportional hazards. Restricted mean survival times (RMST) are estimated by the area under the survival curves (AUCs) up to a restricted follow-up time. The correlation between AUCs due to the constraint that OS > PFS is estimated using bootstrap re-sampling. Network meta-analysis models are given for RMST for PFS and PPS and ensure that OS = PFS + PPS. Both additive and multiplicative network meta-analysis models are presented to obtain relative treatment effects as either differences or ratios of RMST. The methods are illustrated with a network meta-analysis of treatments for stage IIIA-N2 non-small cell lung cancer. The approach has implications for health economic models of cancer treatments, which require estimates of the mean time spent in the PFS and PPS health-states. The methods can be applied to a single time-to-event outcome, and so have wide applicability in any field where time-to-event outcomes are reported, the proportional hazards assumption is in doubt, and survival curve shapes differ across studies and interventions.

Leveraging DICE (Discretely-Integrated Condition Event) Simulation to Simplify the Design and Implementation of Hybrid Models.

OBJECTIVES: Using an example of an existing model constructed by the National Institute for Health and Care Excellence (NICE) to inform a real health technology assessment, this study seeks to demonstrate how a discretely integrated condition event (DICE) simulation can improve the implementation of Markov models. METHODS: Using the technical report and spreadsheet, the original model was translated to a standard DICE simulation without making any changes to the design. All original analyses were repeated and the results were compared. Aspects that could have improved the original design were then considered. RESULTS: The original model consisted of 32 copies (8 risk strata × 4 treatments) of the Markov structure, containing more than 6000 Microsoft Excel® formulas (18 MB files). Three aspects (nonadherence, scheduled treatment stop, and end of fracture risk) were handled by incorporating weighted averages into the cycle-specific calculations. The DICE implementation used 3 conditions to represent the states and a single transition event to apply the probabilities; 3 additional events processed the special aspects, and profiles handled the 8 strata (0.12 MB file). One replication took 16 seconds. The original results were reproduced but extensive additional sensitivity analyses, including structural analyses, were enabled. CONCLUSION: Implementing a real Markov model using DICE simulation both preserves the advantages of the approach and expands the available tools, improving transparency and ease of use and review.

Cost-utility analysis of searching electronic health records and cascade testing to identify and diagnose familial hypercholesterolaemia in England and Wales.

BACKGROUND AND AIMS: The cost effectiveness of cascade testing for familial hypercholesterolaemia (FH) is well recognised. Less clear is the cost effectiveness of FH screening when it includes case identification strategies that incorporate routinely available data from primary and secondary care electronic health records. METHODS: Nine strategies were compared, all using cascade testing in combination with different index case approaches (primary care identification, secondary care identification, and clinical assessment using the Simon Broome (SB) or Dutch Lipid Clinic Network (DLCN) criteria). A decision analytic model was informed by three systematic literature reviews and expert advice provided by a NICE Guideline Committee. RESULTS: The model found that the addition of primary care case identification by database search for patients with recorded total cholesterol >9.3 mmol/L was more cost effective than cascade testing alone. The incremental cost-effectiveness ratio (ICER) of clinical assessment using the DLCN criteria was £3254 per quality-adjusted life year (QALY) compared with case-finding with no genetic testing. The ICER of clinical assessment using the SB criteria was £13,365 per QALY (compared with primary care identification using the DLCN criteria), indicating that the SB criteria was preferred because it achieved additional health benefits at an acceptable cost. Secondary care identification, with either the SB or DLCN criteria, was not cost effective, alone (dominated and dominated respectively) or combined with primary care identification (£63, 514 per QALY, and £82,388 per QALY respectively). CONCLUSIONS: Searching primary care databases for people at high risk of FH followed by cascade testing is likely to be cost-effective.