On the probability of cost-effectiveness using data from randomized clinical trials

BACKGROUND: Acceptability curves have been proposed for quantifying the probability that a treatment under investigation in a clinical trial is cost-effective. Various definitions and estimation methods have been proposed. Loosely speaking, all the definitions, Bayesian or otherwise, relate to the probability that the treatment under consideration is cost-effective as a function of the value placed on a unit of effectiveness. These definitions are, in fact, expressions of the certainty with which the current evidence would lead us to believe that the treatment under consideration is cost-effective, and are dependent on the amount of evidence (i.e. sample size). METHODS: An alternative for quantifying the probability that the treatment under consideration is cost-effective, which is independent of sample size, is proposed. RESULTS: Non-parametric methods are given for point and interval estimation. In addition, these methods provide a non-parametric estimator and confidence interval for the incremental cost-effectiveness ratio. An example is provided. CONCLUSIONS: The proposed parameter for quantifying the probability that a new therapy is cost-effective is superior to the acceptability curve because it is not sample size dependent and because it can be interpreted as the proportion of patients who would benefit if given the new therapy. Non-parametric methods are used to estimate the parameter and its variance, providing the appropriate confidence intervals and test of hypothesis

Current sample size conventions: Flaws, harms, and alternatives

<p>Abstract</p> <p>Background</p> <p>The belief remains widespread that medical research studies must have statistical power of at least 80% in order to be scientifically sound, and peer reviewers often question whether power is high enough.</p> <p>Discussion</p> <p>This requirement and the methods for meeting it have severe flaws. Notably, the true nature of how sample size influences a study's projected scientific or practical value precludes any meaningful blanket designation of <80% power as "inadequate". In addition, standard calculations are inherently unreliable, and focusing only on power neglects a completed study's most important results: estimates and confidence intervals. Current conventions harm the research process in many ways: promoting misinterpretation of completed studies, eroding scientific integrity, giving reviewers arbitrary power, inhibiting innovation, perverting ethical standards, wasting effort, and wasting money. Medical research would benefit from alternative approaches, including established <it>value of information </it>methods, simple choices based on cost or feasibility that have recently been justified, sensitivity analyses that examine a meaningful array of possible findings, and following previous analogous studies. To promote more rational approaches, research training should cover the issues presented here, peer reviewers should be extremely careful before raising issues of "inadequate" sample size, and reports of completed studies should not discuss power.</p> <p>Summary</p> <p>Common conventions and expectations concerning sample size are deeply flawed, cause serious harm to the research process, and should be replaced by more rational alternatives.</p

Cost-Effectiveness of Haemorrhoidal Artery Ligation versus Rubber Band Ligation for the Treatment of Grade II–III Haemorrhoids: Analysis Using Evidence from the HubBLe Trial

Aim Haemorrhoids are a common condition, with nearly 30,000 procedures carried out in England in 2014/15, and result in a significant quality-of-life burden to patients and a financial burden to the healthcare system. This study examined the cost effectiveness of haemorrhoidal artery ligation (HAL) compared with rubber band ligation (RBL) in the treatment of grade II–III haemorrhoids. Method This analyses used data from the HubBLe study, a multicentre, open-label, parallel group, randomised controlled trial conducted in 17 acute UK hospitals between September 2012 and August 2015. A full economic evaluation, including long-term cost effectiveness, was conducted from the UK National Health Service (NHS) perspective. Main outcomes included healthcare costs, quality-adjusted life-years (QALYs) and recurrence. Costeffectiveness results were presented in terms of incremental cost per QALY gained and cost per recurrence avoided. Extrapolation analysis for 3 years beyond the trial follow-up, two subgroup analyses (by grade of haemorrhoids and recurrence following RBL at baseline), and various sensitivity analyses were undertaken. Results In the primary base-case within-trial analysis, the incremental total mean cost per patient for HAL compared with RBL was £1027 (95% confidence interval [CI] £782– £1272, p\0.001). The incremental QALYs were 0.01 QALYs (95% CI -0.02 to 0.04, p = 0.49). This generated an incremental cost-effectiveness ratio (ICER) of £104,427 per QALY. In the extrapolation analysis, the estimated probabilistic ICER was £21,798 per QALY. Results from all subgroup and sensitivity analyses did not materially change the base-case result. Conclusions Under all assessed scenarios, the HAL procedure was not cost effective compared with RBL for the treatment of grade II-III haemorrhoids at a cost-effectiveness threshold of £20,000 per QALY; therefore

A feasibility study incorporating a pilot randomised controlled trial of oral feeding plus pre-treatment gastrostomy tube versus oral feeding plus as-needed nasogastric tube feeding in patients undergoing chemoradiation for head and neck cancer (TUBE trial): study protocol

Background There are 7000 new cases of head and neck squamous cell cancers (HNSCC) treated by the NHS each year. Stage III and IV HNSCC can be treated non-surgically by radio therapy (RT) or chemoradiation therapy (CRT). CRT can affect eating and drinking through a range of side effects with 90 % of patients undergoing this treatment requiring nutritional support via gastrostomy (G) or nasogastric (NG) tube feeding. Long-term dysphagia following CRT is a primary concern for patients. The effect of enteral feeding routes on swallowing function is not well understood, and the two feeding methods have, to date, not been compared to assess which leads to a better patient outcome. The purpose of this study is to explore the feasibility of conducting a randomised controlled trial (RCT) comparing these two options with particular emphasis on patient willingness to be randomised and clinician willingness to approach eligible patients. Methods/design This is a mixed methods multicentre study to establish the feasibility of a randomised controlled trial comparing oral feeding plus pre-treatment gastrostomy versus oral feeding plus as required nasogastric tube feeding in patients with HNSCC. A total of 60 participants will be randomised to the two arms of the study (1:1 ratio). The primary outcome of feasibility is a composite of recruitment (willingness to randomise and be randomised) and retention. A qualitative process evaluation investigating patient, family and friends and staff experiences of trial participation will also be conducted alongside an economic modelling exercise to synthesise available evidence and provide estimates of cost-effectiveness and value of information. Participants will be assessed at baseline (pre-randomisation), during CRT weekly, 3 months and 6 months. Discussion Clinicians are in equipoise over the enteral feeding options for patients being treated with CRT. Swallowing outcomes have been identified as a top priority for patients following treatment and this trial would inform a future larger scale RCT in this area to inform best practice

Towards causal benchmarking of bias in face analysis algorithms

Measuring algorithmic bias is crucial both to assess algorithmic fairness, and to guide the improvement of algorithms. Current methods to measure algorithmic bias in computer vision, which are based on observational datasets, are inadequate for this task because they conflate algorithmic bias with dataset bias. To address this problem we develop an experimental method for measuring algorithmic bias of face analysis algorithms, which manipulates directly the attributes of interest, e.g., gender and skin tone, in order to reveal causal links between attribute variation and performance change. Our proposed method is based on generating synthetic ``transects'' of matched sample images that are designed to differ along specific attributes while leaving other attributes constant. A crucial aspect of our approach is relying on the perception of human observers, both to guide manipulations, and to measure algorithmic bias. Besides allowing the measurement of algorithmic bias, synthetic transects have other advantages with respect to observational datasets: they sample attributes more evenly allowing for more straightforward bias analysis on minority and intersectional groups, they enable prediction of bias in new scenarios, they greatly reduce ethical and legal challenges, and they are economical and fast to obtain, helping make bias testing affordable and widely available. We validate our method by comparing it to a study that employs the traditional observational method for analyzing bias in gender classification algorithms. The two methods reach different conclusions. While the observational method reports gender and skin color biases, the experimental method reveals biases due to gender, hair length, age, and facial hair

A Guide to Handling Missing Data in Cost-Effectiveness Analysis Conducted Within Randomised Controlled Trials

The authors would like to thank Professor Adrian Grant and the team at the University of Aberdeen (Professor Craig Ramsay, Janice Cruden, Charles Boachie, Professor Marion Campbell and Seonaidh Cotton) who kindly allowed the REFLUX dataset to be used for this work, and Eldon Spackman for kindly sharing the Stata (R) code for calculating the probability that an intervention is cost effective following MI. The authors are grateful to the reviewers for their comments, which greatly improved this paper. M. G. is recipient of a Medical Research Council Early Career Fellowship in Economics of Health (grant number: MR/K02177X/1). I. R. W. was supported by the Medical Research Council [Unit Programme U105260558]. No specific funding was obtained to produce this paper. The authors declare no conflicts of interest.Missing data are a frequent problem in cost-effectiveness analysis (CEA) within a randomised controlled trial. Inappropriate methods to handle missing data can lead to misleading results and ultimately can affect the decision of whether an intervention is good value for money. This article provides practical guidance on how to handle missing data in within-trial CEAs following a principled approach: (i) the analysis should be based on a plausible assumption for the missing data mechanism, i.e. whether the probability that data are missing is independent of or dependent on the observed and/or unobserved values; (ii) the method chosen for the base-case should fit with the assumed mechanism; and (iii) sensitivity analysis should be conducted to explore to what extent the results change with the assumption made. This approach is implemented in three stages, which are described in detail: (1) descriptive analysis to inform the assumption on the missing data mechanism; (2) how to choose between alternative methods given their underlying assumptions; and (3) methods for sensitivity analysis. The case study illustrates how to apply this approach in practice, including software code. The article concludes with recommendations for practice and suggestions for future research.Medical Research Council Early Career Fellowship in Economics of Health MR/K02177X/1Medical Research Council UK (MRC) U105260558Medical Research Council UK (MRC) MC_U105260558 MR/K02177X/

Cost-effectiveness of a national exercise referral programme for primary care patients in Wales: results of a randomised controlled trial

This article is published under license to BioMed Central Ltd. This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.The research was independent and funded by the Welsh Assembly Government. RTE is supported by Public Health Wales. Additional support for LM and SM during write up was provided by The Centre for the Development and Evaluation of Complex Interventions for Public Health Improvement (DECIPHer), a UKCRC Public Health Research: Centre of Excellence. Funding from the British Heart Foundation, Cancer Research UK, Economic and Social Research Council (RES-590-28-0005), Medical Research Council, the Welsh Assembly Government and the Wellcome Trust (WT087640MA), under the auspices of the UK Clinical Research Collaboration, is gratefully acknowledged

Comparing multiple competing interventions in the absence of randomized trials using clinical risk-benefit analysis

<p>Abstract</p> <p>Background</p> <p>To demonstrate the use of risk-benefit analysis for comparing multiple competing interventions in the absence of randomized trials, we applied this approach to the evaluation of five anticoagulants to prevent thrombosis in patients undergoing orthopedic surgery.</p> <p>Methods</p> <p>Using a cost-effectiveness approach from a clinical perspective (i.e. risk benefit analysis) we compared thromboprophylaxis with warfarin, low molecular weight heparin, unfractionated heparin, fondaparinux or ximelagatran in patients undergoing major orthopedic surgery, with sub-analyses according to surgery type. Proportions and variances of events defining risk (major bleeding) and benefit (thrombosis averted) were obtained through a meta-analysis and used to define beta distributions. Monte Carlo simulations were conducted and used to calculate incremental risks, benefits, and risk-benefit ratios. Finally, net clinical benefit was calculated for all replications across a range of risk-benefit acceptability thresholds, with a reference range obtained by estimating the case fatality rate - ratio of thrombosis to bleeding.</p> <p>Results</p> <p>The analysis showed that compared to placebo ximelagatran was superior to other options but final results were influenced by type of surgery, since ximelagatran was superior in total knee replacement but not in total hip replacement.</p> <p>Conclusions</p> <p>Using simulation and economic techniques we demonstrate a method that allows comparing multiple competing interventions in the absence of randomized trials with multiple arms by determining the option with the best risk-benefit profile. It can be helpful in clinical decision making since it incorporates risk, benefit, and personal risk acceptance.</p

Methods for specifying the target difference in a randomised controlled trial : the Difference ELicitation in TriAls (DELTA) systematic review

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