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Survival extrapolation plays a key role within cost effectiveness analysis and is often subject to substantial uncertainty. Use of external data to improve extrapolations has been identified as a key research priority. We present findings from a pilot study using data from the COU-AA-301 trial of abiraterone acetate for metastatic castration-resistant prostate cancer, to explore how external trial data may be incorporated into survival extrapolations. External trial data were identified via a targeted search of technology assessment reports. Four methods using external data were compared to simple parametric models (SPMs): informal reference to external data to select appropriate SPMs, piecewise models with, and without, hazard ratio adjustment, and Bayesian models fitted with a prior on the shape parameter(s). Survival and hazard plots were compared, and summary metrics (point estimate accuracy and restricted mean survival time) were calculated. Without consideration of external data, several SPMs may have been selected as the 'best-fitting' model. The range of survival probability estimates was generally reduced when external data were included in model estimation, and external hazard plots aided model selection. Different methods yielded varied results, even with the same data source, highlighting potential issues when integrating external trial data within model estimation. By using external trial data, the most (in)appropriate models may be more easily identified. However, benefits of using external data are contingent upon their applicability to the research question, and the choice of method can have a large impact on extrapolations. [ABSTRACT FROM AUTHOR]

Objective: The objective was to assess the cost-effectiveness of transcatheter aortic valve implantation (TAVI) in patients with severe aortic stenosis with intermediate surgical risk in Singapore. Methods: A de novo Markov model with three health states – stroke with long-term sequelae, no stroke, and death – was developed and simulated using Monte Carlo simulations with 10,000 iterations over a five-year time horizon from the Singapore healthcare system perspective. A 3% annual discount rate for costs and outcomes and monthly cycle lengths were used. By applying the longest available published clinical evidence, simulated patients received either TAVI or surgical aortic valve replacement (SAVR) and were at risk of adverse events (AEs) such as moderate-to-severe paravalvular aortic regurgitation (PAR). Results: When five-year PARTNER 2A data was applied, base-case analyses showed that the incremental cost-effectiveness ratio (ICER) for TAVI compared to SAVR was US$315,760 per quality-adjusted life year (QALY) gained. The high ICER was due to high incremental implantation and procedure costs of TAVI compared to SAVR, and marginal improvement of 0.10 QALYs as simulated mortality of TAVI exceeded SAVR at 3.75 years post-implantation. One-way sensitivity analysis showed that the ICERs were most sensitive to cost of PAR, utility values of SAVR patients, and cost of TAVI and SAVR implants and procedures. When disutilities for AEs were additionally applied, the ICER decreased to US$300,070 per QALY gained. TAVI was dominated by SAVR when the time horizon increased to 20 years. Clinical outcomes projected from one-year PARTNER S3i data further reduced the ICER to US$86,337 per QALY gained for TAVI, assuming early all-cause mortality benefits from TAVI continued to persist. This assumption was undermined when longer term data showed that TAVI's early mortality benefits diminished at five years. Limitations and conclusion: TAVI is unlikely to be cost-effective in intermediate surgical-risk patients compared to SAVR in Singapore. [ABSTRACT FROM AUTHOR]

This study aimed to conduct a review of existing methods used to incorporate life cycle drug pricing (LCDP) in cost-effectiveness analyses (CEAs), identify common methodological challenges, and suggest modeling approaches for prospectively implementing LCDP in CEA. Two complementary searches were conducted in PubMed, combined with hand searching and reference mining, to identify English language full-text articles that explored (1) how drug prices change over time and (2) methods used to apply dynamic pricing in cost-effectiveness models (CEMs). Relevant articles were reviewed, and authors discussed the common methodological practices used in the literature and their associated challenges on prospectively implementing LCDP in CEMs. For each key challenge identified, we provide modeling suggestions to address the issue. We screened 1200 studies based on title and abstract; 117 were reviewed for eligibility, and 47 individual studies were included across both searches. Variations in prices over a product's life cycle are complex and multifactorial, and models applying LCDP in CEA varied in their methodology. We identified 4 key challenges to modeling LCDP in CEA, including how to model price trends before and after loss of exclusivity, how to capture the effect of price changes on future patient cohorts, and how to report results. Accurately quantifying the impact of LCDP requires careful consideration of multiple aspects pertaining to both the evolution of drug prices and how to reflect these in CEA. Although uncertainties remain, our findings can aid implementation and evaluation of LCDP in economic evaluations. • Drug prices are intrinsically dynamic across their life cycle, yet most cost-effectiveness analyses (CEA) assume they remain constant across the modeled time horizon. In part, this is because of uncertainties around when loss of exclusivity (LoE) will occur and how prices will change, both before and after LoE. • Based on the literature reviewed, we summarize 4 key challenges to model life cycle drug pricing (LCDP) in CEA including how to model price trends before and after LoE, how to capture the effect of price changes on future patient cohorts, and how to report results. • Notable heterogeneity was observed in current approaches to incorporating LCDP within CEAs. The methodological suggestions we provide on prospectively implementing LCDP in CEA will help improve the transparency, robustness, consistency, and hence relevance of LCPD-based economic evaluations. [ABSTRACT FROM AUTHOR]

As part of its single technology appraisal (STA) process, the National Institute for Health and Care Excellence (NICE) invited the company that manufactures cabazitaxel (Jevtana®, Sanofi, UK) to submit evidence for the clinical and cost effectiveness of cabazitaxel for treatment of patients with metastatic hormone-relapsed prostate cancer (mHRPC) previously treated with a docetaxel-containing regimen. The School of Health and Related Research Technology Appraisal Group at the University of Sheffield was commissioned to act as the independent Evidence Review Group (ERG). The ERG produced a critical review of the evidence for the clinical and cost effectiveness of the technology based upon the company's submission to NICE. Clinical evidence for cabazitaxel was derived from a multinational randomised open-label phase III trial (TROPIC) of cabazitaxel plus prednisone or prednisolone compared with mitoxantrone plus prednisone or prednisolone, which was assumed to represent best supportive care. The NICE final scope identified a further three comparators: abiraterone in combination with prednisone or prednisolone; enzalutamide; and radium-223 dichloride for the subgroup of people with bone metastasis only (no visceral metastasis). The company did not consider radium-223 dichloride to be a relevant comparator. Neither abiraterone nor enzalutamide has been directly compared in a trial with cabazitaxel. Instead, clinical evidence was synthesised within a network meta-analysis (NMA). Results from TROPIC showed that cabazitaxel was associated with a statistically significant improvement in both overall survival and progression-free survival compared with mitoxantrone. Results from a random-effects NMA, as conducted by the company and updated by the ERG, indicated that there was no statistically significant difference between the three active treatments for both overall survival and progression-free survival. Utility data were not collected as part of the TROPIC trial, and were instead taken from the company's UK early access programme. Evidence on resource use came from the TROPIC trial, supplemented by both expert clinical opinion and a UK clinical audit. List prices were used for mitoxantrone, abiraterone and enzalutamide as directed by NICE, although commercial in-confidence patient-access schemes (PASs) are in place for abiraterone and enzalutamide. The confidential PAS was used for cabazitaxel. Sequential use of the advanced hormonal therapies (abiraterone and enzalutamide) does not usually occur in clinical practice in the UK. Hence, cabazitaxel could be used within two pathways of care: either when an advanced hormonal therapy was used pre-docetaxel, or when one was used post-docetaxel. The company believed that the former pathway was more likely to represent standard National Health Service (NHS) practice, and so their main comparison was between cabazitaxel and mitoxantrone, with effectiveness data from the TROPIC trial. Results of the company's updated cost-effectiveness analysis estimated a probabilistic incremental cost-effectiveness ratio (ICER) of £45,982 per quality-adjusted life-year (QALY) gained, which the committee considered to be the most plausible value for this comparison. Cabazitaxel was estimated to be both cheaper and more effective than abiraterone. Cabazitaxel was estimated to be cheaper but less effective than enzalutamide, resulting in an ICER of £212,038 per QALY gained for enzalutamide compared with cabazitaxel. The ERG noted that radium-223 is a valid comparator (for the indicated sub-group), and that it may be used in either of the two care pathways. Hence, its exclusion leads to uncertainty in the cost-effectiveness results. In addition, the company assumed that there would be no drug wastage when cabazitaxel was used, with cost-effectiveness results being sensitive to this assumption: modelling drug wastage increased the ICER comparing cabazitaxel with mitoxantrone to over £55,000 per QALY gained. The ERG updated the company's NMA and used a random effects model to perform a fully incremental analysis between cabazitaxel, abiraterone, enzalutamide and best supportive care using PASs for abiraterone and enzalutamide. Results showed that both cabazitaxel and abiraterone were extendedly dominated by the combination of best supportive care and enzalutamide. Preliminary guidance from the committee, which included wastage of cabazitaxel, did not recommend its use. In response, the company provided both a further discount to the confidential PAS for cabazitaxel and confirmation from NHS England that it is appropriate to supply and purchase cabazitaxel in pre-prepared intravenous-infusion bags, which would remove the cost of drug wastage. As a result, the committee recommended use of cabazitaxel as a treatment option in people with an Eastern Cooperative Oncology Group performance status of 0 or 1 whose disease had progressed during or after treatment with at least 225 mg/m2 of docetaxel, as long as it was provided at the discount agreed in the PAS and purchased in either pre-prepared intravenous-infusion bags or in vials at a reduced price to reflect the average per-patient drug wastage. [ABSTRACT FROM AUTHOR]