Ash Bullement

To assess use of external evidence for overall survival (OS) estimation in oncology single-technology appraisals (STAs) by the National Institute for Health and Care Excellence (NICE). STAs for oncology drugs appraised by NICE between January 2021 and March 2023 were identified. For each eligible STA, OS extrapolation methods used, the rationale for using external data, the source and type of data, and information on acceptance by the evidence review group (ERG) and the appraisal committee were extracted. Initially, 215 STAs were identified, of which 82 were eligible for the study. Of these, 32 STAs used external data for OS extrapolation, including trial data (44%), real-world data (47%), clinical opinion (25%), meta-analysis (1%) and previous STA (1%). External data were used more frequently in state-transition models for post-event transitions and cure assumptions, and in partitioned-survival models to replace pivotal trial OS, inform long-term survival estimates or to estimate OS based on surrogacy analysis. Sensitivity analyses on use of external data was explored in 16 (50%) of the STAs. The committee accepted use of external data in half of the analysed STAs, acknowledging uncertainty in OS extrapolation.

To investigate the differences in clinical outcomes and costs for the treatment of recurrent and/or metastatic squamous cell carcinoma of the head and neck (R/M SCCHN) with a combined positive score (CPS) of 1-19, with pembrolizumab ± chemotherapy or a cetuximab-containing regimen (CCR) in Italy. A naïve indirect treatment comparison was conducted, and outcomes were incorporated into a newly developed cost-utility model. Inputs were derived from clinical trials, technology appraisal reports, and published literature. Scenario analyses were undertaken to explore key areas of uncertainty. Across the comparisons of pembrolizumab ± chemotherapy versus CCRs, incremental life-years ranged from - 0.502 to 0.155, while incremental quality-adjusted life years (QALYs) ranged from - 0.379 to 0.085. In some scenarios, CCRs dominated pembrolizumab ± chemotherapy (i.e. more QALYs at lower costs). In others, CCRs yielded similar estimates of QALYs at lower costs. CCRs are likely to represent a comparable or more effective treatment option compared to pembrolizumab ± chemotherapy. Model results consistently demonstrated that CCRs are a cost-effective treatment strategy. CCRs remain a relevant treatment option for R/M SCCHN and a CPS of 1-19, for whom a targeted, patient-focused approach is warranted.

Survival extrapolation often plays an important role in health technology assessment (HTA), and there are a range of different approaches available. Approaches that can leverage external evidence (i.e. data or information collected outside the main data source of interest) may be helpful, given the extent of uncertainty often present when determining a suitable survival extrapolation. One of these methods is the multi-parameter evidence synthesis (MPES) approach, first proposed for use in HTA by Guyot et al., and more recently by Jackson. While MPES has potential benefits over conventional extrapolation approaches (such as simple or flexible parametric models), it is more computationally complex and requires use of specialist software. This tutorial presents an introduction to MPES for HTA, alongside a user-friendly, publicly available operationalisation of Guyot’s original MPES that can be executed using the statistical software package R. Through two case studies, both Guyot’s and Jackson’s MPES approaches are explored, along with sensitivity analyses relevant to HTA. Finally, the discussion section of the tutorial details important considerations for analysts considering use of an MPES approach, along with potential further developments. MPES has not been used often in HTA, and so there are limited examples of how it has been used and perceived. However, this tutorial may aid future research efforts exploring the use of MPES further.

Chimeric antigen receptor T-cell therapy (CAR T) has revolutionized the treatment of hematological cancers. Its production requires a complex logistical process, and the time from leukapheresis to patient infusion (known as the vein-to-vein time [V2VT]) can be long during which a patients clinical condition may deteriorate. This study was designed to estimate the benefits of reduced V2VT for third-line or later (3L+) relapsed/refractory large B-cell lymphoma (R/R LBCL) patients treated with CAR T. A mathematical model was developed to estimate the lifetime outcomes of a hypothetical cohort of patients who had either a long or short V2VT. Life-years (LYs), quality-adjusted LYs (QALYs), and costs were estimated. Scenario analyses were performed to assess the robustness of results to key assumptions. The results of the model show that reducing V2VT from 54 days (tisa-cel median V2VT; JULIET) to 24 days (axi-cel median V2VT; ZUMA-1) led to a 3.2-year gain in life expectancy (4.2 vs 7.7 LYs), and 2.4 additional QALYs (3.2 vs 5.6) per patient. Furthermore, a shorter V2VT was shown to be cost-effective under conventional willingness-to-pay thresholds in the United States. Results are driven by a higher infusion rate and a better efficacy of CAR T for those infused. Scenario analyses using a smaller difference in V2VT (24 vs 36 days) produced consistent results. Our study is the first to quantify lifetime V2VT-related outcomes for 3L+ R/R LBCL patients treated with CAR T utilizing currently available evidence. Shorter V2VTs led to improved outcomes, demonstrating the importance of timely infusion achievable by faster manufacturing times and optimization of hospital delivery.

Cost-effectiveness analyses commonly use population or sample averages, which can mask key differences across subgroups and may lead to suboptimal resource allocation. Despite there being several new methods developed over the last decade, there is no recent summary of what methods are available to researchers. This review sought to identify advances in methods for addressing patient heterogeneity in economic evaluations and to provide an overview of these methods. A literature search was conducted using the Econlit, Embase and MEDLINE databases to identify studies published after 2011 (date of a previous review on this topic). Eligible studies needed to have an explicit methodological focus, related to how patient heterogeneity can be accounted for within a full economic evaluation. Sixteen studies were included in the review. Methodologies were varied and included regression techniques, model design and value of information analysis. Recent publications have applied methodologies more commonly used in other fields, such as machine learning and causal forests. Commonly noted challenges associated with considering patient heterogeneity included data availability (e.g., sample size), statistical issues (e.g., risk of false positives) and practical factors (e.g., computation time). A range of methods are available to address patient heterogeneity in economic evaluation, with relevant methods differing according to research question, scope of the economic evaluation and data availability. Researchers need to be aware of the challenges associated with addressing patient heterogeneity (e.g., data availability) to ensure findings are meaningful and robust. Future research is needed to assess whether and how methods are being applied in practice.

Aim: The cost–effectiveness of avelumab first-line maintenance treatment for locally advanced or metastatic urothelial carcinoma in Scotland was assessed. Materials & methods: A partitioned surviva... Plain language summary What is this article about? This study looked at the costs of avelumab when given as maintenance treatment for people in Scotland with advanced urothelial carcinoma, compared... Tweetable abstract Avelumab first-line maintenance is a cost-effective treatment option for patients with locally advanced or metastatic urothelial carcinoma in Scotland #BladderCancer

Background: External evidence is commonly used to inform survival modeling for health technology assessment (HTA). While there are a range of methodological approaches that have been proposed, it is unclear which methods could be used and how they compare. Purpose: This review aims to identify, describe, and categorize established methods to incorporate external evidence into survival extrapolation for HTA. Data Sources: Embase, MEDLINE, EconLit, and Web of Science databases were searched to identify published methodological studies, supplemented by hand searching and citation tracking. Study Selection: Eligible studies were required to present a novel extrapolation approach incorporating external evidence (i.e., data or information) within survival model estimation. Data Extraction: Studies were classified according to how the external evidence was integrated as a part of model fitting. Information was extracted concerning the model-fitting process, key requirements, assumptions, software, application contexts, and presentation of comparisons with, or validation against, other methods. Data Synthesis: Across 18 methods identified from 22 studies, themes included use of informative prior(s) ( n = 5), piecewise ( n = 7), and general population adjustment ( n = 9), plus a variety of “other” ( n = 8) approaches. Most methods were applied in cancer populations ( n = 13). No studies compared or validated their method against another method that also incorporated external evidence. Limitations: As only studies with a specific methodological objective were included, methods proposed as part of another study type (e.g., an economic evaluation) were excluded from this review. Conclusions: Several methods were identified in this review, with common themes based on typical data sources and analytical approaches. Of note, no evidence was found comparing the identified methods to one another, and so an assessment of different methods would be a useful area for further research. Highlights This review aims to identify methods that have been used to incorporate external evidence into survival extrapolations, focusing on those that may be used to inform health technology assessment. We found a range of different approaches, including piecewise methods, Bayesian methods using informative priors, and general population adjustment methods, as well as a variety of “other” approaches. No studies attempted to compare the performance of alternative methods for incorporating external evidence with respect to the accuracy of survival predictions. Further research investigating this would be valuable.

Background: The current work was designed to estimate the cost–effectiveness of trifluridine/tipiracil (T/T) versus best supportive care (BSC) for patients with advanced stage or metastatic gastroe...