Modelling approaches for histology-independent cancer drugs to inform NICE appraisals: a systematic review and decision-framework

Multi-indication Evidence Synthesis in Oncology Health Technology Assessment: Meta-analysis Methods and Their Application to a Case Study of Bevacizumab

BACKGROUND

Multi-indication cancer drugs receive licensing extensions to include additional indications, as trial evidence on treatment effectiveness accumulates. We investigate how sharing information across indications can strengthen the inferences supporting health technology assessment (HTA).

METHODS

We applied meta-analytic methods to randomized trial data on bevacizumab, to share information across oncology indications on the treatment effect on overall survival (OS) or progression-free survival (PFS) and on the surrogate relationship between effects on PFS and OS. Common or random indication-level parameters were used to facilitate information sharing, and the further flexibility of mixture models was also explored.

RESULTS

Treatment effects on OS lacked precision when pooling data available at present day within each indication separately, particularly for indications with few trials. There was no suggestion of heterogeneity across indications. Sharing information across indications provided more precise estimates of treatment effects and surrogacy parameters, with the strength of sharing depending on the model. When a surrogate relationship was used to predict treatment effects on OS, uncertainty was reduced only when sharing effects on PFS in addition to surrogacy parameters. Corresponding analyses using the earlier, sparser (within and across indications) evidence available for particular HTAs showed that sharing on both surrogacy and PFS effects did not notably reduce uncertainty in OS predictions. Little heterogeneity across indications meant limited added value of the mixture models.

CONCLUSIONS

Meta-analysis methods can be usefully applied to share information on treatment effectiveness across indications in an HTA context, to increase the precision of target indication estimates. Sharing on surrogate relationships requires caution, as meaningful precision gains in predictions will likely require a substantial evidence base and clear support for surrogacy from other indications.

HIGHLIGHTS

We investigated how sharing information across indications can strengthen inferences on the effectiveness of multi-indication treatments in the context of health technology assessment (HTA).Multi-indication meta-analysis methods can provide more precise estimates of an effect on a final outcome or of the parameters describing the relationship between effects on a surrogate endpoint and a final outcome.Precision of the predicted effect on the final outcome based on an effect on the surrogate endpoint will depend on the precision of the effect on the surrogate endpoint and the strength of evidence of a surrogate relationship across indications.Multi-indication meta-analysis methods can be usefully applied to predict an effect on the final outcome, particularly where there is limited evidence in the indication of interest.

Trends in NICE technology appraisals of non-small cell lung cancer drugs over the last decade

OBJECTIVES

The aim of this study is to analyse the trends in technology appraisals for non-small cell lung cancer (NSCLC) treatments performed by the National Institute for Health and Care Excellence (NICE) over the last ten years.

METHODS

A systematic search was conducted for single technology appraisals of NSCLC drugs in the online NICE database from 2012 to 2022. Search terms used were 'non small cell lung cancer', and 'NSCLC'. Appraisals that were under development or terminated as well as multiple technology appraisals were considered out of scope.

RESULTS

In the 30 included appraisals for targeted therapies and immunotherapies within NSCLC, a total of 53 different comparators were included by NICE for 41 assorted indications or subgroups. Partitioned survival models were most frequently used, often including three health states and time horizons of up to 30 years. Throughout the decade the use of indirect comparisons was high and became more established and complex over time. Of all appraisals, 90% positively recommended the treatment for use in the UK.

CONCLUSION

Technology appraisals became more complex over time due to the emergence of targeted therapies and immunotherapies, leading to multiple different indications, subpopulations and comparators that needed to be included in appraisals. Partitioned Survival Analysis (PartSA) models became the cornerstone within NSCLC, with time horizons up to 30 years and over time methods for indirect treatment comparisons became more established. The majority of the appraisals resulted in a positive recommendation for reimbursement.

Estimating the Prognostic Value of the NTRK Fusion Biomarker for Comparative Effectiveness Research in The Netherlands

OBJECTIVES

We evaluated the prognostic value of the neurotrophic tyrosine receptor kinase (NTRK) gene fusions by comparing the survival of patients with NTRK+ tumours with patients without NTRK+ tumours.

METHODS

We used genomic and clinical registry data from the Center for Personalized Cancer Treatment (CPCT-02) study containing a cohort of cancer patients who were treated in Dutch clinical practice between 2012 and 2020. We performed a propensity score matching analysis, where NTRK+ patients were matched to NTRK- patients in a 1:4 ratio. We subsequently analysed the survival of the matched sample of NTRK+ and NTRK- patients using the Kaplan-Meier method and Cox regression, and performed an analysis of credibility to evaluate the plausibility of our result.

RESULTS

Among 3556 patients from the CPCT-02 study with known tumour location, 24 NTRK+ patients were identified. NTRK+ patients were distributed across nine different tumour types: bone/soft tissue, breast, colorectal, head and neck, lung, pancreas, prostate, skin and urinary tract. NTRK fusions involving the NTRK3 gene (46%) and NTRK1 gene (33%) were most common. The survival analysis rendered a hazard ratio (HR) of 1.44 (95% CI 0.81-2.55) for NTRK+ patients. Using the point estimates of three prior studies on the prognostic value of NTRK fusions, our finding that the HR is > 1 was deemed plausible.

CONCLUSIONS

NTRK+ patients may have an increased risk of death compared with NTRK- patients. When using historic control data to assess the comparative effectiveness of TRK inhibitors, the prognostic value of the NTRK fusion biomarker should therefore be accounted for.

Cost-Effectiveness Analysis of Adjuvant Olaparib Versus Watch and Wait in the Treatment of Germline BRCA1/2-Mutated, High-Risk, HER2-Negative Early Breast Cancer in Sweden

INTRODUCTION

This study evaluated the cost effectiveness of adjuvant olaparib versus watch and wait (WaW) in patients with germline breast cancer susceptibility gene 1/2 (gBRCA1/2)-mutated, high-risk, human epidermal growth factor receptor 2 (HER2)-negative early breast cancer (eBC), previously treated with neoadjuvant or adjuvant chemotherapy, from a Swedish healthcare perspective.

METHODS

A five-state (invasive disease-free survival [IDFS], non-metastatic breast cancer [non-mBC], early-onset mBC, late-onset mBC, death) semi-Markov state transition model with a lifetime horizon was developed. Transition probabilities were informed by data from the Phase III OlympiA trial, supplemented with data from additional studies in BRCA-mutated, HER2-negative mBC. Health state utilities were derived via mapping of OlympiA data and supplemented by literature estimates. Treatment, adverse events and other medical costs were extracted from publicly available Swedish sources. Incremental cost per life-year (LY) and quality-adjusted life-year (QALY) gained were estimated. Costs and outcomes were discounted at 3% annually. One-way deterministic and probabilistic sensitivity analyses (PSA) were conducted.

RESULTS

Over a lifetime horizon, adjuvant olaparib was associated with an additional 1.50 LYs and 1.22 QALYs, and incremental cost of 471,156 Swedish krona (SEK) versus WaW (discounted). The resulting ICER was 385,183SEK per QALY gained for olaparib versus WaW. ICERs remained below 1,000,000SEK across a range of scenarios, and were consistent across subgroups (hormone receptor [HR]-positive/HER2-negative and triple-negative breast cancer [TNBC]). In PSA, the probability of olaparib being cost effective at 1,000,000SEK per QALY was 99.8%.

CONCLUSIONS

At list price, adjuvant olaparib is a cost-effective alternative to WaW in patients with gBRCA1/2-mutated, high-risk, HER2-negative eBC in Sweden.

Cost-effectiveness of pembrolizumab for previously treated MSI-H/dMMR solid tumours in the UK

OBJECTIVES

Patients with previously treated microsatellite instability-high (MSI-H)/mismatch repair deficient (dMMR) tumours have limited chemotherapeutic treatment options. Pembrolizumab received approval from the EMA in 2022 for the treatment of colorectal, endometrial, gastric, small intestine, and biliary MSI-H/dMMR tumour types. This approval was supported by data from the KEYNOTE-164 and KEYNOTE-158 clinical trials. This study evaluated the cost-effectiveness of pembrolizumab compared with standard of care (SoC) for previously treated MSI-H/dMMR solid tumours in line with the approved EMA label from a UK healthcare payer perspective.

METHODS

A multi-tumour partitioned survival model was built consisting of pre-progression, progressed disease, and dead health states. Pembrolizumab survival outcomes were extrapolated using Bayesian hierarchical models (BHMs) fitted to pooled data from KEYNOTE-164 and KEYNOTE-158. Comparator outcomes were informed by published sources. Tumour sites were modelled independently and then combined, weighted by tumour site distribution. A SoC comparator was used to formulate the overall cost-effectiveness result with pembrolizumab as the intervention. SoC comprised a weighted average of the comparators by tumour site based on market share. Drug acquisition, administration, adverse events, monitoring, subsequent treatment, end-of-life costs, and testing costs were included. Sensitivity and scenario analyses were performed, including modelling pembrolizumab efficacy using standard parametric survival models.

RESULTS

Pembrolizumab, at list price, was associated with £129,469 in total costs, 8.30 LYs, and 3.88 QALYs across the pooled tumour sites. SoC was associated with £28,222 in total costs, 1.14 LYs, and 0.72 QALYs across the pooled tumour sites. This yields an incremental cost-effectiveness ratio (ICER) of £32,085 per QALY. Results were robust to sensitivity and scenario analyses.

CONCLUSIONS

This model demonstrates pembrolizumab provides a valuable new alternative therapy for UK patients with MSH-H/dMMR cancer at the cost of £32,085 per QALY, with confidential discounts anticipated to improve cost-effectiveness further.

Toward Best Practices for Economic Evaluations of Tumor-Agnostic Therapies: A Review of Current Barriers and Solutions

OBJECTIVES

Cancer therapies targeting tumor-agnostic biomarkers are challenging traditional health technology assessment (HTA) frameworks. The high prevalence of nonrandomized single-arm trials, heterogeneity, and small benefiting populations are driving outcomes uncertainty, challenging healthcare decision making. We conducted a structured literature review to identify barriers and prioritize solutions to generating economic evidence for tumor-agnostic therapies.

METHODS

We searched MEDLINE and Embase for English-language studies conducting economic evaluations of tumor-agnostic treatments or exploring related challenges and solutions. We included studies published by December 2022 and supplemented our review with Canadian Agency for Drugs and Technologies in Health and National Institute for Health and Care Excellence technical reports for approved tumor-agnostic therapies. Three reviewers abstracted and summarized key methodological and empirical study characteristics. Challenges and solutions were identified through authors' statements and categorized using directed content analysis.

RESULTS

Twenty-six studies met our inclusion criteria. Studies spanned economic evaluations (n = 5), reimbursement reviews (n = 4), qualitative research (n = 1), methods validations (n = 3), and commentaries or literature reviews (n = 13). Challenges encountered related to (1) the treatment setting and clinical trial designs, (2) a lack of data or low-quality data on clinical and cost parameters, and (3) an inability to produce evidence that meets HTA guidelines. Although attempted solutions centered on analytic approaches for managing missing data, proposed solutions highlighted the need for real-world evidence combined with life-cycle HTA to reduce future evidentiary uncertainty.

CONCLUSIONS

Therapeutic innovation outpaces HTA evidence generation and the methods that support it. Existing HTA frameworks must be adapted for tumor-agnostic treatments to support future economic evaluations enabling timely patient access.

Evaluating treatments in rare indications warrants a Bayesian approach

Evaluating efficacy and real-world effectiveness for novel therapies targeting rare mutations or patient subpopulations with unmet needs is a growing challenge in health economics and outcomes research (HEOR). In these settings it may be difficult to recruit enough patients to run adequately powered randomized clinical trials, resulting in greater reliance on single-arm trials or basket trial designs. Additionally, evidence networks for performing network meta-analysis may be sparse or disconnected when comparing available treatments in narrower patient populations. These challenges create an increased need for use of appropriate methods for handling small sample sizes, structural modelling assumptions and more nuanced decision rules to arrive at "best-available evidence" on comparative and non-comparative efficacy/effectiveness. We advocate for greater use of Bayesian methods to address these challenges as they can facilitate efficient and transparent borrowing of information across varied data sources under flexible modelling assumptions, probabilistic sensitivity analysis to assess model assumptions, and more nuanced decision-making where limited power reduces the utility of classical frequentist hypothesis testing. We illustrate how Bayesian methods have been recently used to overcome several challenges of rare indications in HEOR, including approaches to borrowing information from external data sources, evaluation of efficacy in basket trials, and incorporating non-randomized studies into network meta-analysis. Lastly, we provide several recommendations for HEOR practitioners on appropriate use of Bayesian methods to address challenges in the rare disease setting.

Bayesian hierarchical model-based network meta-analysis to overcome survival extrapolation challenges caused by data immaturity

Aim: This research evaluated standard Weibull mixture cure (WMC) network meta-analysis (NMA) with Bayesian hierarchical (BH) WMC NMA to inform long-term survival of therapies. Materials & methods: Four trials in previously treated metastatic non-small-cell lung cancer with PD-L1 >1% were used comparing docetaxel with nivolumab, pembrolizumab and atezolizumab. Cure parameters related to a certain treatment class were assumed to share a common distribution. Results: Standard WMC NMA predicted cure rates were 0.03 (0.01; 0.07), 0.18 (0.12; 0.24), 0.07 (0.02; 0.15) and 0.03 (0.00; 0.09) for docetaxel, nivolumab, pembrolizumab and atezolizumab, respectively, with corresponding incremental life years (LY) of 3.11 (1.65; 4.66), 1.06 (0.41; 2.37) and 0.42 (-0.57; 1.68). The Bayesian hierarchical-WMC-NMA rates were 0.06 (0.03; 0.10), 0.17 (0.11; 0.23), 0.12 (0.05; 0.20) and 0.12 (0.03; 0.23), respectively, with incremental LY of 2.35 (1.04; 3.93), 1.67 (0.68; 2.96) and 1.36 (-0.05; 3.64). Conclusion: BH-WMC-NMA impacts incremental mean LYs and cost-effectiveness ratios, potentially affecting reimbursement decisions.

COVID-19 rapid molecular point-of-care testing is effective and cost-beneficial for the acute care of trauma patients

PURPOSE

To evaluate the accuracy and cost benefit of a rapid molecular point-of-care testing (POCT) device detecting COVID-19 within a traumatological emergency department.

BACKGROUND

Despite continuous withdrawal of COVID-19 restrictions, hospitals will remain particularly vulnerable to local outbreaks which is reflected by a higher institution-specific basic reproduction rate. Patients admitted to the emergency department with unknown COVID-19 infection status due to a- or oligosymptomatic COVID-19 infection put other patients and health care workers at risk, while fast diagnosis and treatment is necessary. Delayed testing results in additional costs to the health care system.

METHODS

From the 8th of April 2021 until 31st of December 2021, all patients admitted to the emergency department were tested with routine RT-PCR and rapid molecular POCT device (Abbott ID NOW™ COVID-19). COVID-19-related additional costs for patients admitted via shock room or emergency department were calculated based on internal cost allocations.

RESULTS

1133 rapid molecular tests resulted in a sensitivity of 83.3% (95% CI 35.9-99.6%), specificity of 99.8% (95% CI 99.4-100%), a positive predictive value of 71.4% (95% CI 29-96.3%) and a negative predictive value of 99.9% (95% CI 99.5-100%) as compared to RT-PCR. Without rapid COVID-19 testing, each emergency department and shock room admission with subsequent surgery showed additional direct costs of 2631.25€, without surgery of 729.01€.

CONCLUSION

Although rapid molecular COVID-19 testing can initially be more expensive than RT-PCR, subsequent cost savings, improved workflows and workforce protection outweigh this effect by far. The data of this study support the use of a rapid molecular POCT device in a traumatological emergency department.

Impact of non-pharmaceutical interventions on SARS-CoV-2 outbreaks in English care homes: a modelling study

BACKGROUND

COVID-19 outbreaks still occur in English care homes despite the interventions in place.

METHODS

We developed a stochastic compartmental model to simulate the spread of SARS-CoV-2 within an English care home. We quantified the outbreak risk with baseline non-pharmaceutical interventions (NPIs) already in place, the role of community prevalence in driving outbreaks, and the relative contribution of all importation routes into a fully susceptible care home. We also considered the potential impact of additional control measures in care homes with and without immunity, namely: increasing staff and resident testing frequency, using lateral flow antigen testing (LFD) tests instead of polymerase chain reaction (PCR), enhancing infection prevention and control (IPC), increasing the proportion of residents isolated, shortening the delay to isolation, improving the effectiveness of isolation, restricting visitors and limiting staff to working in one care home. We additionally present a Shiny application for users to apply this model to their facility of interest, specifying care home, outbreak and intervention characteristics.

RESULTS

The model suggests that importation of SARS-CoV-2 by staff, from the community, is the main driver of outbreaks, that importation by visitors or from hospitals is rare, and that the past testing strategy (monthly testing of residents and daily testing of staff by PCR) likely provides negligible benefit in preventing outbreaks. Daily staff testing by LFD was 39% (95% 18-55%) effective in preventing outbreaks at 30 days compared to no testing.

CONCLUSIONS

Increasing the frequency of testing in staff and enhancing IPC are important to preventing importations to the care home. Further work is needed to understand the impact of vaccination in this population, which is likely to be very effective in preventing outbreaks.