Adjusting for subsequent therapies in the TOURMALINE-MM1 study shows clinically meaningful improvement in overall survival with addition of ixazomib to lenalidomide and dexamethasone.

TOURMALINE-MM1, the only blinded randomized study in patients with relapsed and/or refractory multiple myeloma (RRMM; ≥1 prior therapy) in the last 10 years, investigated ixazomib+lenalidomide+dexamethasone (IRd) versus lenalidomide+dexamethasone (Rd). Final overall survival (OS) data were based on a median follow-up of 85 months. In RRMM trials where patients have had 1-3 relapses after initial treatment, a high proportion receive subsequent therapy. Application of salvage therapies in blinded trials and newer modes of therapy can increasingly complicate the interpretation of OS. This analysis explores the impact of subsequent therapies on OS outcomes in TOURMALINE-MM1. The inverse probability of censoring weights (IPCW) method, marginal structural model (MSM), and rank preserving structural failure time model (RPSFTM) were utilized to adjust for confounding on OS, introduced by subsequent therapies. Analyses were conducted for the intentto-treat (ITT) population and ≥2 prior lines subgroup. Unadjusted hazard ratio (HR) for IRd versus Rd was 0.94 (95% confidence interval [CI]: 0.78-1.13) in the ITT population. After adjusting for the impact of subsequent therapies by the RPSFTM method, estimated HR for IRd versus Rd in the ITT population was 0.89 (95% CI: 0.74-1.07). Adjusting with IPCW and MSM methods also showed an improvement in HR, favoring IRd. IRd may be particularly beneficial in patients with ≥2 prior lines of therapy (IPCW and MSM HR=0.52, 95% CI: 0.30-0.88; RPSFTM HR=0.68, 95% CI: 0.51-0.91). These analyses highlight the growing challenge of demonstrating OS benefit in multiple myeloma patients and the importance of assessing confounding introduced by subsequent therapies when interpreting OS.

An Investigation into the Relationship Between Choice of Model Structure and How to Adjust for Subsequent Therapies Using a Case Study in Oncology.

BACKGROUND: A common challenge in health technology assessments (HTAs) of cancer treatments is how subsequent therapy use within the trial follow-up may influence cost-effectiveness model outcomes. Although overall survival (OS) is often a key driver of model results, there are no guidelines to advise how to adjust for this potential confounding, with different approaches available dependent on the model structure. OBJECTIVE: We compared a partitioned survival analysis (PartSA) with a semi-Markov multi-state model (MSM) structure, with and without attempts to adjust for the impact of subsequent therapies on OS using a case study describing outcomes for people with relapsed/refractory multiple myeloma. METHODS: Both model structures included three health states: pre-progression, progressed disease and death. Three traditional crossover methods were considered within the context of the PartSA, whereas for the MSM, the probability of post-progression death was pooled across arms. Impacts on the model incremental cost-effectiveness ratio (ICER) were recorded. RESULTS: The unadjusted PartSA produced an ICER of £623,563, and after adjustment yielded an ICER range of £381,340-£386,907. The unadjusted MSM produced an ICER of £1,283,780. Adjusting OS in the MSM resulted in an ICER of £345,486. CONCLUSIONS: The simplicity of the PartSA is lost when the decision problem becomes more complex (for example, when OS data are confounded by subsequent therapies). In this setting, the MSM structure may be considered more flexible, with fewer and less restrictive assumptions required versus the PartSA. Researchers should consider important study design features that may influence the generalisability of data when undertaking model conceptualisation.

Cost-effectiveness of home-based cardiac rehabilitation: a systematic review.

OBJECTIVE: Centre-based cardiac rehabilitation (CR) is recognised as cost-effective for individuals following a cardiac event. However, home-based alternatives are becoming increasingly popular, especially since COVID-19, which necessitated alternative modes of care delivery. This review aimed to assess whether home-based CR interventions are cost-effective (vs centre-based CR). METHODS: Using the MEDLINE, Embase and PsycINFO databases, literature searches were conducted in October 2021 to identify full economic evaluations (synthesising costs and effects). Studies were included if they focused on home-based elements of a CR programme or full home-based programmes. Data extraction and critical appraisal were completed using the NHS EED handbook, Consolidated Health Economic Evaluation Reporting Standards and Drummond checklists and were summarised narratively. The protocol was registered on the PROSPERO database (CRD42021286252). RESULTS: Nine studies were included in the review. Interventions were heterogeneous in terms of delivery, components of care and duration. Most studies were economic evaluations within clinical trials (8/9). All studies reported quality-adjusted life years, with the EQ-5D as the most common measure of health status (6/9 studies). Most studies (7/9 studies) concluded that home-based CR (added to or replacing centre-based CR) was cost-effective compared with centre-based options. CONCLUSIONS: Evidence suggests that home-based CR options are cost-effective. The limited size of the evidence base and heterogeneity in methods limits external validity. There were further limitations to the evidence base (eg, limited sample sizes) that increase uncertainty. Future research is needed to cover a greater range of home-based designs, including home-based options for psychological care, with greater sample sizes and the potential to acknowledge patient heterogeneity.

Network meta-analysis of efficacy of ixazomib, lenalidomide, and dexamethasone in relapsed/refractory multiple myeloma.

OBJECTIVES: In the absence of head-to-head comparisons across relapsed/refractory multiple myeloma (RRMM) treatments following the approval of the oral proteasome inhibitor ixazomib, in combination with lenalidomide and dexamethasone (IRd), we conducted an indirect comparison of the efficacy of IRd relative to several RRMM therapies using Bayesian fixed-effects network meta-analysis (NMA) models. METHODS: Data for the NMA were obtained through a systematic literature review (conducted in June 2020), which identified randomized controlled trials (base case) and observational studies (extended network analysis) reporting overall survival (OS), progression-free survival (PFS), and overall response rate (ORR). RESULTS: In the base case, IRd was associated with a significantly longer PFS than lenalidomide and dexamethasone (Rd), bortezomib monotherapy (V), dexamethasone (Dex), and pomalidomide and dexamethasone (Pom-dex), a significantly shorter PFS than daratumumab, lenalidomide, and dexamethasone (DRd), and a PFS comparable to elotuzumab, lenalidomide, and dexamethasone (ERd) and carfilzomib, lenalidomide, and dexamethasone (KRd). IRd was associated with a significantly longer OS than V, Dex, and Pom-dex, and an OS comparable to Rd, ERd, KRd, and DRd. The ORR of IRd was significantly higher than Rd, V, and Dex, significantly lower than KRd and DRd, and comparable to Pom-dex and ERd. The extended network analyses and sensitivity analyses were consistent with the base case. DISCUSSION: This NMA shows that IRd is relatively efficacious among RRMM treatments. Being an oral regimen, IRd is also convenient to manage. CONCLUSION: IRd could be a preferable treatment option for many patients with RRMM, particularly those seeking an efficacious and convenient therapeutic option.

Brentuximab Vedotin Plus CHP in Frontline sALCL: Adjusted Estimates of Efficacy and Cost-Effectiveness Removing the Effects of Re-Treatment with Brentuximab Vedotin.

BACKGROUND: In the randomised controlled trial ECHELON-2 (NCT01777152; January 2013), brentuximab vedotin (BV) plus cyclophosphamide, doxorubicin and prednisone (CHP) demonstrated improved efficacy compared with CHOP (CHP and vincristine) in frontline CD30+ peripheral T-cell lymphoma (PTCL), an aggressive cancer with poor survival. In ECHELON-2, 70% of patients had systemic anaplastic large cell lymphoma (sALCL), a subtype of PTCL. Of sALCL patients who progressed from BV+CHP and CHOP, 36% (n = 17) and 56% (n = 36) received subsequent BV-containing therapy, respectively. As BV re-treatment was not funded in England at the time, our objective was to estimate adjusted efficacy and cost-effectiveness by excluding BV re-treatment from BV+CHP. METHODS: To remove the effects of BV re-treatment, the inverse probability of censoring weights (IPCW) and two-stage estimator (TSE) approaches, with and without re-censoring, were applied to overall survival (OS) in the BV+CHP arm of the ECHELON-2 sALCL population. Cost-effectiveness was determined in a three-state partitioned survival (PartSA) model from the perspective of the National Health Service (NHS) in England. RESULTS: The unadjusted hazard ratio (HR) for death in patients with sALCL with BV+CHP versus CHOP was 0.54 (95% CI 0.34, 0.87; p = 0.011). The model base case used TSE analysis without re-censoring, which provided an adjusted HR for death of 0.55 (95% CI 0.33, 0.86; p = 0.014). Incremental cost-effectiveness ratios (ICERs) including and excluding re-treatment with BV were £29,760/QALY and £27,761/QALY, respectively. CONCLUSION: TSE without re-censoring provided the most clinically plausible estimate of survival whilst retaining sufficient information for OS extrapolation. After adjustment for BV re-treatment, BV+CHP remains an efficacious and cost-effective treatment in frontline sALCL compared with CHOP.

The cost-effectiveness of brigatinib in adult patients with ALK inhibitor-naive ALK-positive non-small cell lung cancer from a US perspective.

BACKGROUND: The discovery of specific oncogenic drivers in non-small cell lung cancer (NSCLC) has led to the development of highly targeted anaplastic lymphoma kinase tyrosine kinase inhibitors (ALKis). Brigatinib is a next-generation ALKi associated with prolonged progression-free survival in patients with ALKi-naive ALK+ NSCLC. OBJECTIVE: To estimate the cost-effectiveness of brigatinib compared with crizotinib and alectinib in patients with ALKi-naive ALK+ NSCLC, from a US payer perspective. METHODS: A lifetime area under the curve-partitioned survival model with 4 health states was used to evaluate the relative cost-effectiveness of brigatinib in the ALKi-naive ALK+ NSCLC setting. Brigatinib was compared with crizotinib within a cost-effectiveness framework and compared with alectinib in a cost-comparison framework, where all efficacy outcomes were assumed equal. The efficacy of brigatinib and crizotinib was informed by the ALTA-1L trial, and an indirect treatment comparison was performed to inform the efficacy of brigatinib vs alectinib owing to a lack of head-to-head data. Costs were derived from public sources. The main outcomes of the model were total costs, quality-adjusted life-years (QALYs), life-years, and incremental cost-effectiveness ratios. Univariate and probabilistic sensitivity analyses, in addition to multiple scenario analyses, were conducted to assess the robustness of the model outcomes. RESULTS: The improved outcomes observed in ALTA-1L translated into QALY gains (+0.97) in the comparison of brigatinib vs crizotinib. The superior efficacy profile was associated with increased time on treatment with brigatinib, which drove the increase in costs vs crizotinib (+$210,519). The resulting base-case incremental cost-effectiveness ratio was $217,607/QALY gained. Compared with alectinib, brigatinib was associated with a cost difference of -$8,546. Sensitivity analysis suggested that extrapolation of overall survival, the assumptions relating to time on treatment, and subsequent therapy costs were the most influential determinants of results. Probabilistic sensitivity analysis suggested brigatinib had the highest probability of being cost-effective beyond willingness-to-pay thresholds of $236,000 per QALY vs crizotinib and alectinib. CONCLUSIONS: At list prices and under base-case assumptions in the current analysis, brigatinib was associated with cost-savings vs alectinib, and QALY gains but at higher costs vs crizotinib. Additional research into the real-world efficacy of ALKis is warranted to further understand the comparative cost-effectiveness of these therapies. DISCLOSURES: Ms Cranmer and Ms Kearns are employees of Takeda UK Ltd. Dr Young is a former employee of Takeda Pharmaceuticals America, Inc. Dr Humphries is an employee of Takeda Pharmaceuticals U.S.A., Inc. Mr Trueman is an employee of Source Health Economics, the consultancy company that provided health economic and writing services. This work was funded by ARIAD Pharmaceuticals, Inc., a wholly owned subsidiary of Takeda Pharmaceutical Company Limited. Work by Source Health Economics was funded by ARIAD Pharmaceuticals, Inc. Professional medical writing assistance was provided by Phillipa White, of Source Health Economics, and funded by ARIAD Pharmaceuticals, Inc.

Overall survival indirect treatment comparison between brigatinib and alectinib for the treatment of front-line anaplastic lymphoma kinase-positive non-small cell lung cancer using data from ALEX and final results from ALTA-1L.

BACKGROUND: Second-generation anaplastic lymphoma kinase (ALK) gene targeted tyrosine kinase inhibitors (TKIs) alectinib and brigatinib have shown efficacy as front-line treatments for ALK-positive non-small cell lung cancer (NSCLC). No head-to-head data are currently available for brigatinib vs alectinib in the ALK-TKI-naive population. OBJECTIVE: To estimate the relative overall survival (OS) for brigatinib vs alectinib with indirect treatment comparisons (ITCs) using ALEX and ALTA-1L clinical trial data. METHODS: The latest aggregate data from the ALEX trial and final patient-level data from ALTA-1L were used. ITCs were conducted with/without treatment crossover adjustments to estimate relative OS. Bucher methods, anchored matching-adjusted indirect comparisons (MAICs) and unanchored MAICs were employed in ITCs without treatment crossover adjustments. An inverse probability of censoring weight Cox model, a marginal structure model and rank-preserving structural failure time models (with/without re-censoring) within an anchored MAIC were used in ITCs with treatment crossover adjustments. Hazard ratios (HRs) and 95% confidence intervals (CIs) were reported. RESULTS: HRs for brigatinib vs alectinib for relative OS generated from ITCs without treatment crossover adjustments ranged from 0.90 (95% CI: 0.59-1.38) in the unanchored MAIC to 1.20 (95% CI: 0.69-2.11) using the Bucher method. Methods employing treatment switching adjustments estimated HRs for relative OS ranging from 0.74 (95% CI: 0.38-1.45) to 1.11 (95% CI: 0.63-1.94). Results from all ITCs did not indicate statistically different survival profiles. CONCLUSION: Regardless of ITC methodology, OS is comparable for brigatinib vs alectinib in patients with ALK+ NSCLC previously untreated with an ALK inhibitor.

Indirect comparisons of brigatinib and alectinib for front-line ALK-positive non-small-cell lung cancer.

Aim: To conduct an indirect treatment comparison (ITC) of the relative efficacy of brigatinib and alectinib for progression-free survival in people with tyrosine kinase inhibitor (TKI)-naive ALK-positive non-small-cell lung cancer (NSCLC). Methods: Final aggregate and patient-level data from the ALTA-1L trial comparing brigatinib to crizotinib and published aggregate data from ALEX (comparing alectinib to crizotinib) were contrasted using Bucher ITC and matching-adjusted indirect comparisons (MAICs). Results: No statistically significant differences were identified between brigatinib and alectinib in reducing the risk of disease progression overall and in patients with baseline central nervous system metastases. Conclusion: Brigatinib appeared similar to alectinib in reducing risk of disease progression for people with TKI-naive ALK-positive NSCLC.

Patients with advanced non-small-cell lung cancer (NSCLC) who have a genetic marker called rearrangement in the anaplastic lymphoma kinase, or ALK-positive disease, are treated with targeted medications taken by mouth. Two medications, alectinib and brigatinib, are both considered first-line treatment for these patients but have not been compared head-to-head. Recently, updated clinical trial results were published for these medications. The present study utilized these updated results and advanced statistical tests to indirectly compare the effectiveness of the two treatments to help guide clinical treatment choices. Results showed brigatinib and alectinib have a similar magnitude of effect in decreasing the risk of a patient with ALK-positive NSCLC developing worsening disease.

Cost-effectiveness of brentuximab vedotin for the treatment of cutaneous T-cell lymphoma.

Aim: To assess the cost-effectiveness of brentuximab vedotin (BV) versus physician's choice (methotrexate or bexarotene) for treating advanced cutaneous T-cell lymphoma. Materials & methods: A partitioned-survival model was developed from the National Health Service perspective in England and Wales. Model inputs were informed by the ALCANZA trial, real-world UK data, published literature or clinical experts. Results: Over the modeled lifetime, BV dominated physician's choice and provided an additional 1.58 life-years and 1.09 higher quality-adjusted life years with a net cost saving of £119,565. The net monetary benefit was £152,326 using a willingness-to-pay threshold of £30,000/quality-adjusted life year. Results were robust in sensitivity and scenario analyses. Conclusion: BV is a highly cost-effective treatment for advanced cutaneous T-cell lymphoma.

A comparison of partitioned survival analysis and state transition multi-state modelling approaches using a case study in oncology.

AIMS: To construct and compare a partitioned-survival analysis (PartSA) and a semi-Markov multi-state model (MSM) to investigate differences in estimated cost effectiveness of a novel cancer treatment from a UK perspective. MATERIALS AND METHODS: Data from a cohort of late-stage cancer patients (N > 700) enrolled within a randomized, controlled trial were used to populate both modelling approaches. The statistical software R was used to fit parametric survival models to overall survival (OS) and progression-free survival (PFS) data to inform the PartSA (package "flexsurv"). The package "mstate" was used to estimate the MSM transitions (permitted transitions: (T1) "progression-free" to "dead", (T2) "post-progression" to "death", and (T3) "pre-progression" to "post-progression"). Key costs included were treatment-related (initial, subsequent, and concomitant), adverse events, hospitalizations and monitoring. Utilities were stratified by progression. Outcomes were discounted at 3.5% per annum over a 15-year time horizon. RESULTS: The PartSA and MSM approaches estimated incremental cost-effectiveness ratios (ICERs) of £342,474 and £411,574, respectively. Scenario analyses exploring alternative parametric forms provided incremental discounted life-year estimates that ranged from +0.15 to +0.33 for the PartSA approach, compared with -0.13 to +0.23 for the MSM approach. This variation was reflected in the range of ICERs. The PartSA produced ICERs between £234,829 and £522,963, whereas MSM results were more variable and included instances where the intervention was dominated and ICERs above £7 million (caused by very small incremental QALYs). LIMITATIONS AND CONCLUSIONS: Structural uncertainty in economic modelling is rarely explored due to time and resource limitations. This comparison of structural approaches indicates that the choice of structure may have a profound impact on cost-effectiveness results. This highlights the importance of carefully considered model conceptualization, and the need for further research to ascertain when it may be most appropriate to use each approach.

A Review of Recent Decision-Analytic Models Used to Evaluate the Economic Value of Cancer Treatments.

Cost-effectiveness analysis provides information on the potential value of new cancer treatments, which is particularly pertinent for decision makers as demand for treatment grows while healthcare budgets remain fixed. A range of decision-analytic modelling approaches can be used to estimate cost effectiveness. This study summarises the key modelling approaches considered in oncology, alongside their advantages and limitations. A review was conducted to identify single technology appraisals (STAs) submitted to the National Institute for Health and Care Excellence (NICE) and published papers reporting full economic evaluations of cancer treatments published within the last 5 years. The review was supplemented with the existing methods literature discussing cancer modelling. In total, 100 NICE STAs and 124 published studies were included. Partitioned-survival analysis (n = 54) and discrete-time state transition structures (n = 41) were the main structures submitted to NICE. Conversely, the published studies reported greater use of discrete-time state transition models (n = 102). Limited justification of model structure was provided by authors, despite an awareness in the existing literature that the model structure should be considered thoroughly and can greatly influence cost-effectiveness results. Justification for the choice of model structure was limited and studies would be improved with a thorough rationale for this choice. The strengths and weaknesses of each approach should be considered by future researchers. Alternative methods (such as multi-state modelling) are likely to be utilised more frequently in the future, and so justification of these more advanced methods is paramount to their acceptability to inform healthcare decision making.