Modeling the economic outcomes of immuno-oncology drugs: alternative model frameworks to capture clinical outcomes

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 Analysis of Six Immunotherapy-Based Regimens and Sunitinib in Metastatic Renal Cell Carcinoma: A Public Payer Perspective

PURPOSE

Several new treatment combinations have been approved in metastatic renal cell carcinoma (mRCC). To determine the optimal therapy on the basis of cost and health outcomes, we performed a cost-effectiveness analysis of approved immunotherapy-tyrosine kinase inhibitor/immunotherapy drug combinations and sunitinib using public payer acquisition costs in the United States.

METHODS

We constructed a decision model with a 10-year time horizon. The seven treatment drug strategies included atezolizumab + bevacizumab, avelumab + axitinib, pembrolizumab + axitinib, nivolumab + ipilimumab (NI), nivolumab + cabozantinib, lenvatinib + pembrolizumab, and sunitinib. The effectiveness outcome in our model was quality-adjusted life-years (QALYs) with utility values on the basis of the published literature. Costs included drug acquisition costs and costs for management of grade 3-4 drug-related adverse events. We used a partitioned survival model in which patients with mRCC transitioned between three health states (progression-free, progressive disease, and death) at monthly intervals on the basis of parametric survival function estimated from published survival curves. To determine cost-effectiveness, we constructed incremental cost-effectiveness ratios (ICERs) by dividing the difference in cost by the difference in effectiveness between nondominated treatments.

RESULTS

The least expensive treatment was sunitinib ($357,948 US dollars [USD]-$656,100 USD), whereas the most expensive was either lenvatinib + pembrolizumab or pembrolizumab + axitinib ($959,302 USD-$1,403,671 USD). NI yielded the most QALYs (3.6), whereas avelumab + axitinib yielded the least (2.5). NI had an incremental ICER of $297,465 USD-$348,516 USD compared with sunitinib. In sensitivity analyses, this ICER fell below $150,000 USD/QALY if the initial 4-month cost of NI decreased by 22%-38%.

CONCLUSION

NI was the most effective combination for mRCC, but at a willingness-to-pay threshold of $150,000 USD/QALY, sunitinib was the most cost-effective approach.

Estimating and Extrapolating Survival Using a State-Transition Modeling Approach: A Practical Application in Multiple Myeloma

OBJECTIVES

State-transition models (STMs) applied in oncology have given limited considerations to modeling postprogression survival data. This study presents an application of an STM focusing on methods to evaluate the postprogression transition and its impact on survival predictions.

METHODS

Data from the lenalidomide plus dexamethasone arm of the ASPIRE trial was used to estimate transition rates for an STM. The model accounted for the competing risk between the progression and preprogression death events and included an explicit structural link between the time to progression and subsequent death. The modeled transition rates were used to simulate individual disease trajectories in a discrete event simulation framework, based on which progression-free survival and overall survival over a 30-year time horizon were estimated. Survival predictions were compared with the observed trial data, matched external data, and estimates obtained from a more conventional partitioned survival analysis approach.

RESULTS

The rates of progression and preprogression death were modeled using piecewise exponential functions. The rate of postprogression mortality was modeled using an exponential function accounting for the nonlinear effect of the time to progression. The STM provided survival estimates that closely fitted the trial data and gave more plausible long-term survival predictions than the best-fitting Weibull model applied in a partitioned survival analysis.

CONCLUSIONS

The fit of the STM suggested that the modeled transition rates accurately captured the underlying disease process over the modeled time horizon. The considerations of this study may apply to other settings and facilitate a wider use of STMs in oncology.

Estimated Cost-effectiveness of Atezolizumab Plus Cobimetinib and Vemurafenib for Treatment of BRAF V600 Variation Metastatic Melanoma

IMPORTANCE

In the IMspire150 trial, triplet treatment with atezolizumab and vemurafenib plus cobimetinib significantly improved progression-free survival (PFS) compared with vemurafenib plus cobimetinib alone for treatment of BRAF V600 variation metastatic melanoma. However, considering high cost of this combination, it is unclear if the incremental cost is worth the additional survival benefit.

OBJECTIVE

To evaluate the cost-effectiveness of atezolizumab and vemurafenib plus cobimetinib vs vemurafenib plus cobimetinib alone in patients with newly diagnosed unresectable BRAF V600 variation metastatic melanoma from the US health care perspective.

DESIGN, SETTING, AND PARTICIPANTS

This economic evaluation study used a 3-state partitioned survival model to assess the cost-effectiveness of the combination of atezolizumab with vemurafenib plus cobimetinib vs vemurafenib plus cobimetinib alone. The observed Kaplan-Meier curves for overall survival and PFS were digitized from the IMspire150 trial (January 2017-April 2018) and the long-term survivals (over a lifetime horizon) beyond the end of the trial were extrapolated using 7 different survival models. The cost and health preference data were collected from a literature review. This study was performed from March 2021 through June 2021.

MAIN OUTCOMES AND MEASURES

The outcomes of interest were expected life-years (LYs) gained and quality-adjusted life-years (QALYs), costs, and incremental cost-effectiveness ratio (ICER), expressed as cost per LYs and per QALYs saved.

RESULTS

Adding atezolizumab to vemurafenib and cobimetinib provided an additional 3.267 QALYs compared with the doublet regimen of vemurafenib plus cobimetinib, at an ICER of $271 669 per QALY, which is not considered cost-effective at the willingness-to-pay threshold of $150 000 per QALY. However, the scenario analyses found that atezolizumab combined with vemurafenib plus cobimetinib could be cost-effective at 20-year (ICER, $121 432 per QALY) and 30-year ($98 092 per QALY) time horizons when both strategies were stopped after 2 years of treatments, and over a lifetime horizon ($122 220 per QALY) when only immunotherapy with atezolizumab was stopped after 2 years of treatment.

CONCLUSIONS AND RELEVANCE

These findings suggest that the atezolizumab and vemurafenib plus cobimetinib regimen provides significant survival benefits over vemurafenib plus cobimetinib alone, and a price reduction would be encouraged to maximize the value of its survival gain.

Onwards and Upwards: A Systematic Survey of Economic Evaluation Methods in Oncology

INTRODUCTION

The type of methods used in economic evaluations of health technology can lead to results that may influence decisions. Despite the potential impact on decision making, there is very little documentation of methods used in economic evaluation in oncology pertaining to key assumptions and extrapolation methods of survival benefits, especially in terms of survival analysis techniques and methods for extrapolation.

OBJECTIVES

The primary objectives of this study were to identify, examine, and describe the methods used in economic evaluations in oncology over a 10-year period, while secondary objectives included examining the use of identified methods across different geographic regions.

METHODS

A systematic search of the published oncology literature was conducted to identify economic evaluations of advanced or metastatic cancers published between 2010 and 2019 using the PUBMED, Ovid MEDLINE, and EMBASE databases. A random sample was taken, and information on type of study, data source, modeling techniques, and survival analysis methods were abstracted and descriptively summarized.

RESULTS

A total of 8481 abstracts were identified and 76 economic evaluations were abstracted and assessed. Most identified studies were from North America (38%), East Asia (21%), continental Europe (18%), or the UK (16%), and most commonly focused on lung cancer (18%), colorectal cancer (16%), or breast cancer (13%). A large majority of studies were based on data from randomized controlled trials (82%), utilized a cost-utility approach (82%), and took a public healthcare system perspective (83%). Common model structures included Markov (49%) and partitioned survival (17%). Fitted parametric curves were the most commonly used extrapolation method (89%) for overall survival and most often utilized the Weibull distribution (64%). Secondary assessments showed modest regional variation in the use of identified methods, including the use of fitted parametric curves, testing of the proportional hazards assumption, and validation of results.

CONCLUSION

A majority of papers in the study sample reported basic characteristics of study type, data source used, modeling techniques, and utilization of survival analysis methods. However, greater detail in reporting extrapolation methods, statistical analyses, and validation of results could be potential improvements, especially across regions, in order to support greater consistency in decision making. Future research could document the diffusion of novel modeling techniques into economic evaluation.

Cost-Effectiveness of Lenvatinib in the Treatment of Patients With Unresectable Hepatocellular Carcinomas in Japan: An Analysis Using Data From Japanese Patients in the REFLECT Trial

BACKGROUND

Hepatocellular carcinoma (HCC) is one of the leading causes of cancer-related mortality in Japan. Prognosis is poor, and until recently sorafenib was the only treatment option available for patients with unresectable disease. Lenvatinib is the first therapy to demonstrate noninferiority to sorafenib. An analysis was conducted using clinical data from Japanese patients in the phase III REFLECT trial to assess the cost-effectiveness of lenvatinib versus sorafenib for first-line treatment of unresectable HCC in Japan.

METHODS

A partitioned survival model was implemented adopting the perspective of the Japanese healthcare system, with costs and outcomes modeled over a lifetime horizon and using a discount rate of 2%, as per Japanese guidelines. Population data from the Japanese subpopulation of REFLECT were used to extrapolate outcomes, and costs and resource use were based on Japanese sources. The Japanese tariff was applied to EQ-5D data collected during the REFLECT clinical trial to obtain utility values reflecting the preferences of the Japanese population.

RESULTS

Compared with sorafenib, lenvatinib is dominant because it is associated with a reduction in incremental costs of ¥156 799 and incremental quality-adjusted life-years of 0.31. These results were robust to changes in key assumptions, and probabilistic outcomes aligned with deterministic outcomes.

CONCLUSION

Given the use of Japan-specific data in the cost-effectiveness model, it is expected that the use of lenvatinib as a first-line treatment in Japan will be associated with cost savings and improved clinical outcomes versus sorafenib for patients with unresectable HCC.

Challenges in synthesising cost-effectiveness estimates

Economic evaluations help decision-makers faced with tough decisions on how to allocate resources. Systematic reviews of economic evaluations are useful as they allow readers to assess whether interventions have been demonstrated to be cost effective, the uncertainty in the evidence base, and key limitations or gaps in the evidence base. The synthesis of systematic reviews of economic evaluations commonly takes a narrative approach whereas a meta-analysis is common step for reviews of clinical evidence (e.g. effectiveness or adverse event outcomes). As they are common objectives in other reviews, readers may query why a synthesis has not been attempted for economic outcomes. However, a meta-analysis of incremental cost-effectiveness ratios, costs, or health benefits (including quality-adjusted life years) is fraught with issues largely due to heterogeneity across study designs and methods and further practical challenges. Therefore, meta-analysis is rarely feasible or robust. This commentary outlines these issues, supported by examples from the literature, to support researchers and reviewers considering systematic review of economic evidence.

Partitioned Survival and State Transition Models for Healthcare Decision Making in Oncology: Where Are We Now?

OBJECTIVES

Partitioned survival models (PSMs) are routinely used to inform reimbursement decisions for oncology drugs. We discuss the appropriateness of PSMs compared to the most common alternative, state transition models (STMs).

METHODS

In 2017, we published a National Institute for Health and Care Excellence (NICE) Technical Support Document (TSD 19) describing and critically reviewing PSMs. This article summarizes findings from TSD 19, reviews new evidence comparing PSMs and STMs, and reviews recent NICE appraisals to understand current practice.

RESULTS

PSMs evaluate state membership differently from STMs and do not include a structural link between intermediate clinical endpoints (eg, disease progression) and survival. PSMs directly consider clinical trial endpoints and can be developed without access to individual patient data, but limit the scope for sensitivity analyses to explore clinical uncertainties in the extrapolation period. STMs facilitate these sensitivity analyses but require development of robust survival models for individual health-state transitions. Recent work has shown PSMs and STMs can produce substantively different survival extrapolations and that extrapolations from STMs are heavily influenced by specification of the underlying survival models. Recent NICE appraisals have not generally included both model types, reviewed individual clinical event data, or scrutinized life-years accrued in individual health states.

CONCLUSIONS

The credibility of survival predictions from PSMs and STMs, including life-years accrued in individual health states, should be assessed using trial data on individual clinical events, external data, and expert opinion. STMs should be used alongside PSMs to support assessment of clinical uncertainties in the extrapolation period, such as uncertainty in post-progression survival.

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 cost-utility analysis of atezolizumab in the second-line treatment of patients with metastatic bladder cancer

Background

Despite initial promising results, the IMvigor211 clinical trial failed to demonstrate an overall survival (os) benefit for atezolizumab compared with chemotherapy as second-line treatment for metastatic bladder cancer (mbc). However, given lessened adverse events (aes) and preserved quality of life (qol) with atezolizumab, there might still be investment value. To evaluate that potential value, we conducted a cost-utility analysis (cua) of atezolizumab compared with chemotherapy from the perspective of the Canadian health care payer.

Methods

A partitioned survival model was used to evaluate atezolizumab compared with chemotherapy over a lifetime horizon (5 years). The base-case analysis was conducted for the intention-to-treat (itt) population, with additional scenario analyses for subgroups by IMvigor-defined PD-L1 status. Health outcomes were evaluated through life-year gains and quality-adjusted life-years (qalys). Cost estimates in 2018 Canadian dollars for systemic treatment, aes, and end-of-life care were incorporated. The incremental cost-effectiveness ratio (icer) was used to compare treatment strategies. Parameter and model uncertainty were assessed through sensitivity and scenario analyses. Per Canadian guidelines, cost and effectiveness were discounted at 1.5%.

Results

For the itt population, the expected qalys for atezolizumab and chemotherapy were 0.75 and 0.56, with expected costs of $90,290 and $8,466 respectively. The resultant icer for atezolizumab compared with chemotherapy was $430,652 per qaly. Scenario analysis of patients with PD-L1 expression levels of 5% or greater led to a lower icer ($334,387 per qaly). Scenario analysis of observed compared with expected benefits demonstrated a higher icer, with a shorter time horizon ($928,950 per qaly).

Conclusions

Despite lessened aes and preserved qol, atezolizumab is not considered cost-effective for the second-line treatment of mbc.

Economic Evaluation of Single versus Combination Immuno-Oncology Therapies: Application of a Novel Modelling Approach in Metastatic Melanoma

Background

Existing economic model frameworks may not adequately capture the atypical treatment response patterns in immuno-oncology (I-O) compared with conventional therapies and thus may fail to represent the full clinical value associated with disease dynamics and improved survival.

Objective

A cost-effectiveness analysis (CEA) of the I-O Regimen (nivolumab/ipilimumab) versus ipilimumab alone in advanced melanoma was carried out by applying a 5-state partitioned survival model (PSM) as a case study, to explore the I-O treatment response and clinical outcomes. The findings were compared with those of a conventional 3-state PSM.

Materials and Methods

The case study extends the conventional 3-state PSM, by separating the pre-progression state into non-responders and responders, and the post-progression state into normal and I-O progression to account for delayed treatment effects preceding clinical response. Model states were populated using patient-level data (where possible), mapping from the best overall response (BOR), and survival analysis with flexible and traditional parametric methods. Survival functions were applied to progression-free survival (PFS) and overall survival (OS) endpoints across treatment arms using the 4-year follow-up data (data available at the time of the research; since then 5-year follow-up data have been published) from the CheckMate 067 trial. Information on BOR was used as a means of differentiating the I-O treatment response in addition to the outcomes of progression-free and progressed disease. A UK National Health Service and personal social services (NHS/PSS) perspective over a lifetime horizon was used with outcomes discounted at 3.5% annually.

Results

The 5-state PSM generated an increase in quality adjusted life years (QALYs) in both treatment arms and gave a more granular description of patients’ health profiles compared with the traditional 3-state PSM. The incremental QALY increased by 13% (from 2.62 to 2.95 QALYs) and the incremental cost decreased by 12% (£29,125 to £25,678) with the 5-state model. In both models, the Regimen had an incremental cost-effectiveness ratio (ICER) relative to ipilimumab alone within the lower bound of the National Institute for Health and Care Excellence (NICE) reference range (£20,000 per QALY gained).

Conclusion

A 5-state economic model, incorporating relevant I-O health states, can be more informative to gain insight into treatment response and progression differences that are not commonly captured in existing economic models. Clinical trial endpoints, including those relating to treatment response, which are not directly reported in ongoing I-O trials, can be mapped on to the proposed modelled health states (although assumptions are required to do so). Improvements in reporting treatment response in future I-O clinical trials could help to further validate and improve the proposed model framework.