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Background and Objective: Accurately extrapolating survival beyond trial follow-up is essential in a health technology assessment where model choice often substantially impacts estimates of clinical and cost effectiveness. Evidence suggests standard parametric models often provide poor fits to long-term data from immuno-oncology trials. Palmer et al. developed an algorithm to aid the selection of more flexible survival models for these interventions. We assess the usability of the algorithm, identify areas for improvement and evaluate whether it effectively identifies models capable of accurate extrapolation. Methods: We applied the Palmer algorithm to the CheckMate-649 trial, which investigated nivolumab plus chemotherapy versus chemotherapy alone in patients with gastroesophageal adenocarcinoma. We evaluated the algorithm's performance by comparing survival estimates from identified models using the 12-month data cut to survival observed in the 48-month data cut. Results: The Palmer algorithm offers a systematic procedure for model selection, encouraging detailed analyses and ensuring that crucial stages in the selection process are not overlooked. In our study, a range of models were identified as potentially appropriate for extrapolating survival, but only flexible parametric non-mixture cure models provided extrapolations that were plausible and accurately predicted subsequently observed survival. The algorithm could be improved with minor additions around the specification of hazard plots and setting out plausibility criteria. Conclusions: The Palmer algorithm provides a systematic framework for identifying suitable survival models, and for defining plausibility criteria for extrapolation validity. Using the algorithm ensures that model selection is based on explicit justification and evidence, which could reduce discordance in health technology appraisals. [ABSTRACT FROM AUTHOR]

Probabilistic sensitivity analysis (PSA) demonstrates the parameter uncertainty in a decision problem. The technique involves sampling parameters from their respective distributions (rather than simply using mean/median parameter values). Guidance in the literature, and from health technology assessment bodies, on the number of simulations that should be performed suggests a 'sufficient number', or until 'convergence', which is seldom defined. The objective of this tutorial is to describe possible outcomes from PSA, discuss appropriate levels of accuracy, and present guidance by which an analyst can determine if a sufficient number of simulations have been conducted, such that results are considered to have converged. The proposed approach considers the variance of the outcomes of interest in cost-effectiveness analysis as a function of the number of simulations. A worked example of the technique is presented using results from a published model, with recommendations made on best practice. While the technique presented remains essentially arbitrary, it does give a mechanism for assessing the level of simulation error, and thus represents an advance over current practice of a round number of simulations with no assessment of model convergence. [ABSTRACT FROM AUTHOR]

Background: Ofatumumab (Arzerra®, Novartis) is a treatment for chronic lymphocytic leukemia refractory to fludarabine and alemtuzumab [double refractory (DR-CLL)]. Ofatumumab was licensed on the basis of an uncontrolled Phase II study, Hx-CD20-406, in which patients receiving ofatumumab survived for a median of 13.9 months. However, the lack of an internal control arm presents an obstacle for the estimation of comparative effectiveness. Methods: The objective of the study was to present a method to estimate the cost effectiveness of ofatumumab in the treatment of DR-CLL. As no suitable historical control was available for modelling, the outcomes from nonresponders to ofatumumab were used to model the effect of best supportive care (BSC). This was done via a Cox regression to control for differences in baseline characteristics between groups. This analysis was included in a partitioned survival model built in Microsoft® Excel with utilities and costs taken from published sources, with costs and quality-adjusted life years (QALYs) were discounted at a rate of 3.5% per annum. Results: Using the outcomes seen in non-responders, ofatumumab is expected to add approximately 0.62 life years (1.50 vs. 0.88). Using published utility values this translates to an additional 0.30 QALYs (0.77 vs. 0.47). At the list price, ofatumumab had a cost per QALY of £130,563, and a cost per life year of £63,542. The model was sensitive to changes in assumptions regarding overall survival estimates and utility values. Conclusions: This study demonstrates the potential of using data for non-responders to model outcomes for BSC in cost-effectiveness evaluations based on single-arm trials. Further research is needed on the estimation of comparative effectiveness using uncontrolled clinical studies. [ABSTRACT FROM AUTHOR]

Background The cost of pharmaceuticals dosed by weight or body surface area (BSA) can be estimated in several ways for economic evaluations. A review of 20 recent National Institute for Health and Care Excellence appraisals showed that 17 of them took the mean weight or BSA of patients, 2 costed the individual patient data from trials, and 2 fitted a distribution to patient-level data. Objectives To investigate the estimated drug costs using different methodologies to account for patient characteristics for pharmaceuticals with a weight- or BSA-based posology. The secondary objective was to explore the suitability of general population data as a proxy for patient-level data. Methods Patient-level data were pooled from three clinical trials and used to calculate a hypothetical cost per administration of eight licensed pharmaceuticals, applying the three methods used in recent National Institute for Health and Care Excellence appraisals. The same analysis was performed using data from the Health Survey for England (in place of patient-level data) to investigate the validity of using general population data as a substitute for patient-level data. Results Compared with using patient-level data from clinical trials, the mean patient characteristics (weight or BSA) led to an underestimation of drug cost by 6.1% (range +1.5% to −25.5%). Fitting a distribution to patient-level data led to a mean difference of +0.04%. All estimates were consistent using general population data. Conclusions Estimation of drug costs in health economic evaluation should account for the distribution in weight or BSA to produce accurate results. When patient data are not available, general population data may be used as an alternative. [ABSTRACT FROM AUTHOR]

Introduction: Until recently, treatment options for damage to cartilage in the knee were limited to the use of microfracture or, occasionally, mosaicplasty. The developments of autologous and characterised chondrocyte implantation have provided new treatment options but have large upfront costs. The objective of this study was to estimate the cost effectiveness of characterised chondrocyte implantation in the UK National Health Service.Methods: An economic model was constructed in Microsoft Excel®, with patients undergoing either microfracture or chondrocyte implantation. Following treatment failure, patients can undergo a series of interventions, ultimately ending in knee replacement. Effectiveness and utility were modelled using clinical trial data, which were supplemented with synthesised registry data, and costs were taken from published sources. Results were expressed in clinical events, quality-adjusted life-years (QALYs) and British pounds. Both costs and outcomes were discounted at 3.5 % per year.Results: Chondrocyte implantation is estimated to reduce the lifetime probability of knee replacement by 50 % in comparison with microfracture, and to increase QALYs by 0.72 (16.57 vs. 15.85). Costs were estimated to be £23,307 for chondrocyte implantation, and £8008 for microfracture, with the incremental cost of £15,299 for chondrocyte implantation reflecting reduced resource use offsetting some of the procedure cost. These values gave a cost per QALY gained of £21,245.Conclusion: Chondrocyte implantation is estimated to provide substantial patient benefits over a lifetime horizon, with a considerable increase in QALYs. Despite the increase in costs, the procedure is cost effective at standard thresholds used in the UK. [ABSTRACT FROM AUTHOR]

Objective: To determine the economic impact of the introduction of carbetocin for the prevention of postpartum haemorrhage (PPH) at caesarean section, compared to oxytocin.Study Design: The model is a decision tree conducted from a UK National Health Service perspective. 1500 caesarean sections (both elective and emergency) were modelled over a 12 month period. Efficacy data was taken from a published Cochrane meta-analysis, and costs from NHS Reference costs, the British National Formulary and the NHS electronic Medicines Information Tool. A combination of hospital audit data and expert input from an advisory board of clinicians was used to inform resource use estimates. The main outcome measures were the incidence of PPH and total cost over a one year time horizon, as a result of using carbetocin compared to oxytocin for prevention of PPH at caesarean section.Results: The use of carbetocin compared to oxytocin for prevention of PPH at caesarean section was associated with a reduction of 30 (88 vs 58) PPH events (>500ml blood loss), and a cost saving of £27,518. In probabilistic sensitivity analysis, carbetocin had a 91.5% probability of producing better outcomes, and a 69.4% chance of being dominant (both cheaper and more effective) compared to oxytocin.Conclusion: At list price, the introduction of carbetocin appears to provide improved clinical outcomes along with cost savings, though this is subject to uncertainty regarding the underlying data in efficacy, resource use, and cost. [ABSTRACT FROM AUTHOR]