Tremelimumab and durvalumab with chemotherapy in first-line treatment for metastatic non-small cell lung cancer: a US-based cost-effectiveness analysis

Introduction

Lung cancer is the leading cause of cancer-related death in the United States (US), accounting for approximately one-fifth of all cancer deaths (1-3). Non-small cell lung cancer (NSCLC) is the most common type, making up 80–85% of all lung cancer cases (4). Over half of NSCLC patients are diagnosed at an advanced stage (5,6). Immunotherapies targeting the programmed cell death-1 (PD-1) receptor and its ligand (PD-L1) have revolutionized the management of metastatic NSCLC (mNSCLC) over the past decades (7,8). However, anti-PD-(L)1 therapy primarily benefits patients with high levels of tumor PD-L1 expression (9-14), while being less effective in those with low or no PD-L1 expression (15,16). Thus, there is a need for innovative therapeutic strategies to cater this particular patient group.

Durvalumab, a highly selective human IgG1 monoclonal antibody, disrupts PD-L1 interactions with PD-1 and CD80, empowering T cells to target and eliminate tumor cells, showing potential in non-small cell lung cancer when combined with novel agents (17,18). In the phase III POSEIDON trial, durvalumab was assessed in combination with tremelimumab, a novel monoclonal antibody targeting cytotoxic T-lymphocyte-associated antigen 4 (CTLA-4) (19). This study investigated the clinical efficacy and safety of adding a limited course of tremelimumab to durvalumab, alongside four cycles of platinum-doublet chemotherapy as the first-line treatment for mNSCLC patients without epidermal growth factor receptor (EGFR) mutation or anaplastic lymphoma kinase (ALK) rearrangements (19). The four-drug regimen demonstrated significant improvements in progression-free survival (PFS) and overall survival (OS) compared to chemotherapy alone, while maintaining a manageable tolerability profile (19). Furthermore, incorporating the anti-CTLA-4 antibody into first-line PD-L1-containing chemotherapy extended clinical benefits for patients with tumor PD-L1 expression <1%, a subgroup that typically responds poorly to conventional PD-L1 combined chemotherapy. These promising outcomes led to the US Food and Drug Administration (FDA)’s approval of the four-drug regimen for patients with EGFR/ALK wild-type mNSCLC on November 10, 2022 (20).

The dual immunotherapy and chemotherapy combination offer a promising and well-tolerated treatment option for patients with this disease. However, concerns about the treatment’s high cost may hinder its widespread adoption. In 2023, an estimated 202,589 new cases of mNSCLC were projected in the US (3,21), with around 65–75% of these cases exhibiting low or negative PD-L1 expression, rendering about 142,000 patients eligible for this treatment. The US healthcare insurance system is complex, with varying levels of physician and pharmaceutical access. By 2021, over half of Americans are privately insured, 8.6% are uninsured, and the rest are covered by public sources like Medicaid, Medicare, or the US military (22). Health insurance plays a pivotal role in determining access to care and health outcomes for cancer patients in the US (23). Given the imperative need for high-quality and affordable medications to improve cancer survival, effective healthcare resource allocation is crucial. Therefore, conducting cost-effectiveness analyses is imperative to ascertain if a novel, albeit costly, treatment regimen provides a clinical benefit at a justifiable cost to inform resource allocation decisions. This study aimed to evaluate the cost-effectiveness of tremelimumab with durvalumab, combined with chemotherapy (T + D + CT), as the first-line therapy for patients with EGFR/ALK wild-type mNSCLC from a US healthcare perspective. We present this article in accordance with the CHEERS reporting checklist (available at https://tlcr.amegroups.com/article/view/10.21037/tlcr-24-244/rc) (24).

Methods

Overviews

We developed a Markov model using TreeAge Pro software (version 2022, https://www.treeage.com/) for mathematical modeling and R software (version 4.2.3, http://www.r-project.org) for survival fitting to evaluate the cost-effectiveness of T + D + CT as the first-line therapy for patients with EGFR/ALK wild-type mNSCLC from a US healthcare perspective. The Markov model divides mNSCLC disease progression into distinct health states, with patients transitioning between states at discrete time intervals called cycles. Each state is linked to costs and health outcomes, with transition probabilities guiding movement between states (25). Markov models allow for the simulation of disease progression and treatment effects over time, enabling the evaluation of costs and outcomes associated with different cancer treatment strategies.

The cost-effectiveness model (CEM) considered three competitive strategies based on the POSEIDON trial: (I) T + D + CT; (II) durvalumab plus chemotherapy (D + CT); (III) chemotherapy alone (CT). The model targeted adults mNSCLC patients without sensitizing EGFR mutations or ALK rearrangements and not prior systemic therapy, in line with the POSEIDON trial criteria. Our study exclusively used pre-existing and non-identifiable data for analysis, making it exempt from institutional review board approval (26). The study was conducted in accordance with the Declaration of Helsinki (as revised in 2013).

Model structure

The Markov model included three main health states: progression-free disease (PFD), progressed disease (PD), and death. Additionally, a temporary health states called “PFD health state with discontinued first-line therapy” was incorporated to address scenarios where first-line treatment may be discontinued due to unacceptable adverse effects (AEs) before disease progresses (Figure 1).

Figure 1 Markov model diagram. (A) Markov model structure used to compare 3 strategies for treating EGFR/ALK wild-type mNSCLC. (B) Health states network showing the possible transitions between 4 health states. mNSCLC, metastatic non-small cell lung cancer; T + D + CT, tremelimumab plus durvalumab and chemotherapy; D + CT, durvalumab plus chemotherapy; CT, chemotherapy alone; PFD, progression-free disease; PD, progressed disease; AEs, adverse events.

Patients initially started in the PFD health state and were randomly assigned to one of three treatment arms: T + D + CT, D + CT, or CT, based on the POSEIDON trial protocols detailed in Table S1. If patients in the PFS health state experienced AEs-induced first-line treatment discontinuation, they transitioned to the preset temporary health state. Patients who experienced disease progression moved to the PD health state and could receive subsequent anticancer therapy at the investigator’s discretion for sustained survival benefits. Additional information on subsequent anticancer therapy can be found in Table S2. Patients in the PD health state without subsequent anticancer therapy were assumed to receive best supportive care (BSC) per the latest National Comprehensive Cancer Network (NCCN) Guidelines, with palliative care recommended before death (27). Figure 1B illustrates the possible transitions between these health states.

The CEM integrated clinical efficacy and safety, utility values and costs as inputs, with cumulative costs and quality-adjusted life-years (QALYs) over the modeling period as primary outputs. Incremental cost-effectiveness ratios (ICERs) were calculated to determine the additional costs per each additional QALY and compared to a willingness-to-pay (WTP) threshold to determine the relative cost-effectiveness of different strategies. A 10-year time horizon was chosen to ensure all model patients to reach the terminal health state (death). The model cycle is set at 3 weeks to align with the treatment schedule in the POSEIDON trial, with costs and QALYs discounted at an annual rate of 3% (28).

QALYs

QALY, a common metric in cost-effectiveness analysis, considers both quality of life and life years gained. It is calculated by multiplying health state utilities (ranging from 0 for death to 1 for perfect health), by the time spent in each health state determined by transition probabilities (29).

Transition probabilities between health states were estimated based on the data from the POSEIDON trial, the only study investigating the clinical efficacy and safety of T + D + CT, D + CT and CT in the first-line setting. Survival data for first-line CT were extracted by digitizing Kaplan-Meier (KM) curves from the trial using the GetData Graph Digitizer software (version 2.26; http://www.getdata-graphdigitizer.com/index.php). Goodness-of-fit tests were then conducted to select the optimal survival distribution for these recreated survival data, considering criteria such as the Akaike information criteria (AIC) and Bayesian information criteria (BIC), as well as graphical evaluation of fits versus observed data. Lower AIC and BIC values, along with greater overlap between the fitted and observed curves, indicated a better fit. Based on the results of the goodness-of-fit tests, the Weibull and log-logistic distributions were chosen to model and extrapolate OS and PFS for first-line CT (see Table S3 and Figures S1,S2). Transition probabilities for first-line T + D + CT and D + CT were estimated using the hazards ratio (HRs) of these two strategies relative to first-line CT, derived from the POSEIDON trial. A specific formula (30) was utilized to estimate the survival rate for these two strategies: Scompeting-strategies=(SCT)HR (30). In the base-case analysis, HRs stratified by PD-L1 expression were used to provide a comprehensive understanding of the first-line use of T + D + CT for EGFR/ALK wild-type mNSCLC.

Transition probabilities for the temporary health state were estimated using safety data from the POSEIDON trial (Table S4), with the model focusing solely on immunotherapy discontinuation caused by AEs. This decision was made due to the lack of explicit data on the discontinuation of first-line chemotherapy drugs, which are generally cheaper than immunotherapy drugs.

In the absence of health-related quality of life (HRQoL) data from the POSEIDON trial during the analysis, we utilized health utility values sourced from published literature. A health utility score of 0.754 was assigned to the PFD health state, while a score of 0.569 was assigned to the PD health state (31,32). The impact of AEs on HRQoL was assessed by incorporating utility decrements based on a report by the Institute for Clinical and Economic Review (33), as well as estimated episode durations for AEs from Yang et al.’s study (34). Further details on AE-related utility decrements can be found in Table S5.

Costs

We analyzed our model from a US healthcare perspective, considering costs such as first-line drug acquisition and administration, subsequent anticancer therapy, AEs and disease management, BSC, and palliative care. Biomarker testing costs were not included in the model, as all patients were assumed to have known PD-L1 expression status. All costs were converted to 2023 US dollars based on the Personal Consumption Expenditures-Health index (35).

Acquisition costs for first-line drugs were estimated using the dosage and schedule provided in Table S1, with average sales prices (ASP) sourced from the Centers for Medicare & Medicaid Services (CMS) (36). Drug administration costs were calculated based on infusion duration and corresponding infusion prices from the CMS Physician Fee Schedule Look-up Tool (37). Drug dosage calculations were based on a mean body surface area of 1.79 m² from Criss et al.’s economic evaluation, which analyzed data from over 3,500 lung cancer patients treated at Partners Healthcare hospital (38). Additionally, a mean creatinine clearance rate of 70 mL/min for model patients was ascertained from Wan et al.’s study (39). In the POSEIDON trial, subsequent anticancer therapies included radiotherapy, immunotherapy, cytotoxic chemotherapy, and targeted therapy (19). As the specific drugs used in subsequent anticancer therapies were not disclosed in the trial, the subsequent regimens were modeled based on the preferred regimens recommended by the latest NCCN Guidelines (27). The costs for subsequent anticancer therapies were calculated and presented in Table S2.

In this CEM, grade 3/4 AE costs were considered. To calculate AE management costs for each arm, unit AE costs were initially obtained from the Healthcare Cost and Utilization Project (HCUP) using Clinical Classification Software Refined (CCSR) diagnosis codes (40). Subsequently, these costs were multiplied by the reported incidence of each AE for each arm and then aggregated to determine the total AE management costs for each arm (refer to Table S6). The medical resources necessary for managing mNSCLC varied depending on the health state, encompassing services such as routine outpatient visits, computed tomography scans, magnetic resonance imaging, ultrasounds, and X-rays. Health state-specific disease management costs were sourced from literature (34), as well as costs for BSC and palliative care (38). Further details can be found in Table S7.

Statistical analysis

In the base-case analysis, we compared the cost-effectiveness of three treatment strategies (T + D + CT, D + CT, and CT) as the first-line treatment of EGFR/ALK wild-type mNSCLC patients. Since there is no specific WTP threshold defined in the US, we used the Institute for Clinical and Economic Review’s recommended range ($100,000–150,000 per QALY) as a reference (41). Strategies with ICERs below the preset range were considered cost-effective.

Deterministic sensitivity analyses (DSAs) were undertaken to assess how uncertainty in specific model inputs could affect the cost-effectiveness results. In the DSA, model inputs were individually tested within plausible ranges, including 95% CIs for HRs, 0–5% for discount rate, and ±50% of the baseline values for other inputs (since their 95% CIs were not available). DSA results were presented as tornado diagrams, ranking inputs by their impact on cost-effectiveness results.

To account for multiple input uncertainties, a probabilistic sensitivity analysis (PSA) was performed using 10,000 Monte Carlo simulations. Model inputs were simultaneously sampled from appropriate distributions. Cost-effectiveness acceptability curves (CEACs) were used to visualize the likelihood of achieving cost-effectiveness under different WTPs thresholds. Details of baseline values, ranges for DSA, and distributions for PSA can be found in Table S7.

Scenario analysis was performed to assess the relative cost-effectiveness of the three treatment strategies under varying key model assumptions. A summary of each scenario and its justification for inclusion can be found in Table S8.

Results

Base-case analysis

In patients with EGFR/ALK wild-type mNSCLC, first-line treatment with T + D + CT had varying effects compared to CT alone. In subgroups with PD-L1 expression ≥50%, T + D + CT resulted in the highest increase in LYs of 0.65 (equal to 0.47 QALYs), but incurred the greatest increment medical costs of $173,998 (Table 1). On the other hand, in the subgroups with PD-L1 expression <50%, T + D + CT had the smallest increase in LYs of 0.27 (equal to 0.18 QALYs) and the lowest increment medical costs of $124,533 (Table 1). In general, the ICREs for first-line T + D + CT ranged from $370,208/QALY to $691,960/QALY, consistently exceeding the recommended range of WTP thresholds recommended ($100,000–$150,000/QALY).

Compared to first-line D + CT, first-line T + D + CT had slightly lower QALY (1.35 vs. 1.36 QALY) but higher medical costs ($ 307,168 vs. $ 262,377) in the subgroup with PD-L1 expression ≥50%, therefore dominated by first-line D + CT; in other subgroups based on PD-L1 expression, although first-line T + D + CT improved survivals outcomes, its overwhelmingly high medical costs resulted in significantly higher ICER than the predefined range of WTP thresholds.

Sensitivity analysis

Our analysis focused on the cost-effectiveness of first-line T + D + CT in EGFR/ALK wild-type mNSCLC patients with PD-L1 expression <1%. We conducted sensitivity analysis specifically for this subgroup. The DSA results revealed that the upper and lower limits of any model inputs did not bring the ICER of first-line T + D + CT below the defined WTP threshold ranges of $100,000–$150,000/QALY compared to first-line D + CT or first-line CT (Figures 2,3). The most influential factors on the ICERs were the HR for OS and PFS, utilities (both PFD and PD health states) and the price of durvalumab and tremelimumab, as depicted in the tornado diagrams.

Figure 2 Deterministic sensitivity analysis results for first-line T + D + CT vs. first-line CT. ICER, incremental cost-effectiveness ratios; WTP, willingness-to-pay; QALY, quality-adjusted life-year; T + D + CT, tremelimumab plus durvalumab and chemotherapy; CT, chemotherapy alone; HR, hazard ratio; OS, overall survival; PFS, progression-free survival; PD-L1, programmed cell death ligand 1; PFD, progression-free disease; PD, progressed disease; AE, adverse event; BSC, best supportive care.

Figure 3 Deterministic sensitivity analysis results for first-line T + D + CT vs. first-line D + CT. ICER, incremental cost-effectiveness ratios; WTP, willingness-to-pay; QALY, quality-adjusted life-year; T + D + CT, tremelimumab plus durvalumab and chemotherapy; D + CT, durvalumab plus chemotherapy; CT, chemotherapy alone; HR, hazard ratio; OS, overall survival; PFS, progression-free survival; PD-L1, programmed cell death ligand 1; PFD, progression-free disease; PD, progressed disease; AEs, adverse events; BSC, best supportive care.

The PSA results revealed that, the likelihood of first-line T + D + CT being cost-effective within the WTP threshold range of $100,000–$150,000/QALY was almost zero when compared to the other treatment strategies (Figure S3). However, as the WTP threshold increased, the probability of first-line T + D + CT becoming cost-effective increased more significantly than that of first-line D + CT.

Scenario analysis

The results of the scenario analysis are presented in Table S9. The assumption that durvalumab being free had the most significant impact on model outcomes. In this scenario, first-line T + D + CT was found to be cost-effective compared to first-line CT, with ICERs ranging from $51,028 to 93,983/QALY, falling below the predefined WTP thresholds ranges. When compared to first-line D + CT, the cost-effectiveness results remained consistent with the base-case results.

In other scenarios, there was no significant changes observed in our results, and the ICERs between first-line T + D + CT and first-line D + CT or first-line CT tended to cluster around the base-case value shown in Table 1.

Discussion

In our cost-effectiveness analysis, we evaluated the addition of tremelimumab to durvalumab plus platinum-doublet chemotherapy as a first-line treatment for EGFR/ALK wild-type mNSCLC in the US. Our base case analysis revealed that using first-line T + D + CT in the subgroups with PD-L1 expression ≥50% resulted in negative incremental QALYs and higher costs compared to first-line CT, making it cost-ineffective. For other subgroups with different PD-L1 expressions, the reported ICERs for first-line T + D + CT (vs. D + CT or CT) ranged from $356,201/QALY to $1,659,846/QALY, consistently exceeding the recommended WTP thresholds ($100,000–$150,000/QALY). We concluded that regardless of their PD-L1 expression, first-line T + D + CT did not represent a cost-effective option for patients with EGFR/ALK wild-type mNSCLC.

The robustness of our CEM has been solidly confirmed through the rigorous analysis using both DSA and PSA. DSA revealed that the estimated ICERs were more sensitive to certain model inputs that influence QALYs, such as HRs for OS and PFS, as well as utilities of PFD and PD health states. It is important to note that these inputs, which reflect the efficacy and safety of treatment strategies, are unlikely to be changed through clinical or policy interventions. Alongside these important QALY drivers, the prices of tremelimumab and durvalumab exerted a substantial influence on the ICERs. However, DSA results indicated that varying these two inputs within ±25% of the base-case value did not appear to impact on our findings. Furthermore, scenario analysis revealed that even tremelimumab was assumed to be provided for free, it did not result in first-line T + D + CT being superior to D + CT in patents with different PD-L1 expression. On the other hand, assuming durvalumab was free proved sufficient to make first-line T + D + CT cost-effective compared to CT in all cases. The greater influence of durvalumab’s price on determining the cost-effectiveness of first-line T + D + CT, compared to tremelimumab’s price, was largely due to its longer treatment duration, resulting in exceptionally high cumulative drug costs.

Despite the demonstrated clinical benefits of combining anti-CTLA-4 antibodies and PD-(L)1 inhibitors in previous clinical trials (42,43), including the recent POSEIDON trial (19), further exploration is needed to assess the cost-effectiveness of dual immunotherapy. This economic evaluation suggested that first-line treatment with T + D + CT did not offer a cost-effectiveness advantage compared to CT. There are two primary reasons for this: firstly, the significant survival improvement observed in the POSEIDON trial did not translate into a substantial extension of QALYs (1.12–1.35 vs. 0.88 QALYs) in our cost-effectiveness analysis due to the limited OS. Secondly, the combination of tremelimumab (an anti-CTLA-4 drug), and durvalumab (an anti-PD-L1 drug), and conventional chemotherapy resulted in a substantial increase in total medical costs. The higher costs of T + D + CT outweighed its marginal QALY advantage, leading to its unfavorable ICERs. However, when considering PD-L1 expression and using first-line CT as a control, the survival benefits of first-line T + D + CT were comparable to D + CT in patients with PD-L1 expression >50% (0.47 and 0.46 additional QALYs) and PD-L1 expression >1% (0.27 and 0.24 QALYs); In patients with PD-L1 expression <50%, particularly those with PD-L1 expression <1%, first-line use of T + D + CT resulted in higher incremental QALYs. Adjusting the prices of key drugs may help achieve cost-effectiveness based on the exceptional clinical efficacy of first-line T + D + CT in patients with PD-L1 <1%.

This study has several notable strengths. First, we utilized comprehensive efficacy and safety data from a phase III, global, randomized trial to establish the CEM. Additionally, various analyses, including DSA, PSA with 10,000 Monte Carlo simulations, and 10 scenario analyses, were conducted to check the robustness of our CEM. Hence, this analysis provides valuable insights for making informed treatment decisions in the mNSCLC patients. Secondly, we extensively investigated the impact of varying safety profiles across three different treatment strategies by integrating first-line immunotherapy discontinuations due to AEs, along with the incidence of AEs, associated costs and disutility in the model. Thirdly, this study represents the first report on the cost-effectiveness of T + D + CT compared to PD-L1-containing chemotherapy or platinum-doublet chemotherapy as the initial treatment regimen for EGFR/ALK wild-type mNSCLC across various PD-L1 expression levels.

This study does have some limitations. Firstly, there is a lack of head-to-head clinical trials comparing T + D + CT with D + CT or CT in subgroups with different PD-L1 expression levels. Therefore, survival fitting techniques were applied to estimate transition probabilities by employing corresponding HRs. However, this approach assumed that the clinical efficacy and safety of first-line CT (as a standard control) were consistent across various subgroups, which may introduce bias into the results. Secondly, this analysis assessed long-term survival for treatment strategies beyond the short follow-up period of the trial, adding further uncertainty to the CEM. Thirdly, there may be heterogeneity in costs from various sources used in the model, but DSA showed that varying cost inputs did not materially alter the main findings of this study. Fourthly, the specific drugs used as subsequent anticancer therapies were not disclosed in the phase III POSEIDON trial. To address this uncertainty, we modeled subsequent therapy drugs based on the latest NCCN Guidelines, although this may not fully represent real-world clinical practice. Sensitivity analysis was conducted by varying the costs and frequency of subsequent anticancer therapy, and it was found that these inputs did not play a decisive role in determining the cost-effectiveness of first-line T + D + C treatment.

Conclusions

From a US health care perspective, first-line T + D + CT is not cost-effective for patients with EGFR/ALK wild-type mNSCLC, regardless of their PD-L1expression. While doublet immunotherapy holds promise in improving mNSCLC treatment, it is crucial to consider whether its clinical benefits justify its high cost.

Acknowledgments

Funding: None.

Footnote

Reporting Checklist: The authors have completed the CHEERS reporting checklist. Available at https://tlcr.amegroups.com/article/view/10.21037/tlcr-24-244/rc

Data Sharing Statement: Available at https://tlcr.amegroups.com/article/view/10.21037/tlcr-24-244/dss

Peer Review File: Available at https://tbcr.amegroups.com/article/view/10.21037/tlcr-24-244/prf

Conflicts of Interest: All authors have completed the ICMJE uniform disclosure form (available at https://tlcr.amegroups.com/article/view/10.21037/tlcr-24-244/coif). The authors have no conflicts of interest to declare.

Ethical Statement: The authors are accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved. The study was conducted in accordance with the Declaration of Helsinki (as revised in 2013). Our study exclusively used pre-existing and non-identifiable data for analysis, making it exempt from institutional review board approval.

Open Access Statement: This is an Open Access article distributed in accordance with the Creative Commons Attribution-NonCommercial-NoDerivs 4.0 International License (CC BY-NC-ND 4.0), which permits the non-commercial replication and distribution of the article with the strict proviso that no changes or edits are made and the original work is properly cited (including links to both the formal publication through the relevant DOI and the license). See: https://creativecommons.org/licenses/by-nc-nd/4.0/.

References

1. Sung H, Ferlay J, Siegel RL, et al. Global Cancer Statistics 2020: GLOBOCAN Estimates of Incidence and Mortality Worldwide for 36 Cancers in 185 Countries. CA Cancer J Clin 2021;71:209-49. [Crossref] [PubMed]
2. Siegel RL, Miller KD, Jemal A. Cancer statistics, 2019. CA Cancer J Clin 2019;69:7-34. [Crossref] [PubMed]
3. Siegel RL, Miller KD, Wagle NS, et al. Cancer statistics, 2023. CA Cancer J Clin 2023;73:17-48. [Crossref] [PubMed]
4. Suster DI, Mino-Kenudson M. Molecular Pathology of Primary Non-small Cell Lung Cancer. Arch Med Res 2020;51:784-98. [Crossref] [PubMed]
5. Hendriks LE, Kerr KM, Menis J, et al. Oncogene-addicted metastatic non-small-cell lung cancer: ESMO Clinical Practice Guideline for diagnosis, treatment and follow-up. Ann Oncol 2023;34:339-57. [Crossref] [PubMed]
6. Hendriks LE, Kerr KM, Menis J, et al. Non-oncogene-addicted metastatic non-small-cell lung cancer: ESMO Clinical Practice Guideline for diagnosis, treatment and follow-up. Ann Oncol 2023;34:358-76. [Crossref] [PubMed]
7. Reck M, Remon J, Hellmann MD. First-Line Immunotherapy for Non-Small-Cell Lung Cancer. J Clin Oncol 2022;40:586-97. [Crossref] [PubMed]
8. Kang J, Zhang C, Zhong WZ. Neoadjuvant immunotherapy for non-small cell lung cancer: State of the art. Cancer Commun (Lond) 2021;41:287-302. [Crossref] [PubMed]
9. Paz-Ares L, Luft A, Vicente D, et al. Pembrolizumab plus Chemotherapy for Squamous Non-Small-Cell Lung Cancer. N Engl J Med 2018;379:2040-51. [Crossref] [PubMed]
10. Mok TSK, Wu YL, Kudaba I, et al. Pembrolizumab versus chemotherapy for previously untreated, PD-L1-expressing, locally advanced or metastatic non-small-cell lung cancer (KEYNOTE-042): a randomised, open-label, controlled, phase 3 trial. Lancet 2019;393:1819-30. [Crossref] [PubMed]
11. Reck M, Rodríguez-Abreu D, Robinson AG, et al. Five-Year Outcomes With Pembrolizumab Versus Chemotherapy for Metastatic Non-Small-Cell Lung Cancer With PD-L1 Tumor Proportion Score ≥ 50. J Clin Oncol 2021;39:2339-49. [Crossref] [PubMed]
12. Socinski MA, Jotte RM, Cappuzzo F, et al. Atezolizumab for First-Line Treatment of Metastatic Nonsquamous NSCLC. N Engl J Med 2018;378:2288-301. [Crossref] [PubMed]
13. Herbst RS, Giaccone G, de Marinis F, et al. Atezolizumab for First-Line Treatment of PD-L1-Selected Patients with NSCLC. N Engl J Med 2020;383:1328-39. [Crossref] [PubMed]
14. Sezer A, Kilickap S, Gümüş M, et al. Cemiplimab monotherapy for first-line treatment of advanced non-small-cell lung cancer with PD-L1 of at least 50%: a multicentre, open-label, global, phase 3, randomised, controlled trial. Lancet 2021;397:592-604. [Crossref] [PubMed]
15. Waterhouse D, Lam J, Betts KA, et al. Real-world outcomes of immunotherapy-based regimens in first-line advanced non-small cell lung cancer. Lung Cancer 2021;156:41-9. [Crossref] [PubMed]
16. Sun JY, Zhang D, Wu S, et al. Resistance to PD-1/PD-L1 blockade cancer immunotherapy: mechanisms, predictive factors, and future perspectives. Biomark Res 2020;8:35. [Crossref] [PubMed]
17. Dempke WCM, Fenchel K, Reuther S, et al. Durvalumab plus novel agents in non-small cell lung cancer-a new COAST on the horizon? Transl Lung Cancer Res 2022;11:697-701. [Crossref] [PubMed]
18. Akkad N, Thomas TS, Luo S, et al. A real-world study of pneumonitis in non-small cell lung cancer patients receiving durvalumab following concurrent chemoradiation. J Thorac Dis 2023;15:6427-35. [Crossref] [PubMed]
19. Johnson ML, Cho BC, Luft A, et al. Durvalumab With or Without Tremelimumab in Combination With Chemotherapy as First-Line Therapy for Metastatic Non-Small-Cell Lung Cancer: The Phase III POSEIDON Study. J Clin Oncol 2023;41:1213-27. [Crossref] [PubMed]
20. US Food and Drug Administration. FDA approves tremelimumab in combination with durvalumab and platinum-based chemotherapy for metastatic non-small cell lung cancer. Available online: https://www.fda.gov/drugs/resources-information-approved-drugs/fda-approves-tremelimumab-combination-durvalumab-and-platinum-based-chemotherapy-metastatic-non. Accessed 2 January, 2023.
21. American Cancer Society. Key Statistics for Lung Cancer. Available online: https://www.cancer.org/cancer/lung-cancer/about/key-statistics.html. Accessed March 2, 2023.
22. Kaiser Family Foundation. Health insurance coverage of the total population. Available online: https://www.kff.org/other/state-indicator/total-population. Accessed June 24, 2024.
23. Zhao J, Han X, Nogueira L, et al. Health insurance status and cancer stage at diagnosis and survival in the United States. CA Cancer J Clin 2022;72:542-60. [Crossref] [PubMed]
24. Husereau D, Drummond M, Augustovski F, et al. Consolidated Health Economic Evaluation Reporting Standards 2022 (CHEERS 2022) Statement: Updated Reporting Guidance for Health Economic Evaluations. Pharmacoeconomics 2022;40:601-9. [Crossref] [PubMed]
25. Zhang Z, Liang G, Zhang P, et al. China county-based prostate specific antigen screening for prostate cancer and a cost-effective analysis. Transl Androl Urol 2021;10:3787-99. [Crossref] [PubMed]
26. Lester-Coll NH, Ades S, Yu JB, et al. Cost-effectiveness of Prostate Radiation Therapy for Men With Newly Diagnosed Low-Burden Metastatic Prostate Cancer. JAMA Netw Open 2021;4:e2033787. [Crossref] [PubMed]
27. National Comprehensive Cancer Network. NCCN clinical practice guidelines in oncology: Non-small cell lung cancer, Version 3. 2023. Available online: https://www.nccn.org/guidelines/category_1. Accessed September 14, 2023.
28. Sanders GD, Neumann PJ, Basu A, et al. Recommendations for Conduct, Methodological Practices, and Reporting of Cost-effectiveness Analyses: Second Panel on Cost-Effectiveness in Health and Medicine. JAMA 2016;316:1093-103. [Crossref] [PubMed]
29. Mitzman B, Varghese TK Jr, Akerley WL, et al. Surgical-decision making in the setting of unsuspected N2 disease: a cost-effectiveness analysis. J Thorac Dis 2024;16:1063-73. [Crossref] [PubMed]
30. Wu B, Dong B, Xu Y, et al. Economic evaluation of first-line treatments for metastatic renal cell carcinoma: a cost-effectiveness analysis in a health resource-limited setting. PLoS One 2012;7:e32530. [Crossref] [PubMed]
31. Nafees B, Lloyd AJ, Dewilde S, et al. Health state utilities in non-small cell lung cancer: An international study. Asia Pac J Clin Oncol 2017;13:e195-203. [Crossref] [PubMed]
32. National Institute for Health and Care Excellence. Nivolumab for advanced non-squamous non-small cell lung cancer after chemotherapy. Available online: https://www.nice.org.uk/guidance/ta713/resources/nivolumab-for-advanced-nonsquamous-nonsmallcell-lung-cancer-after-chemotherapy-pdf-82611131893189. Accessed April 4, 2023.
33. Institute for Clinical and Economic Review. Treatment Options for Advanced Non-Small Cell Lung Cancer: Effectiveness, Value and Value-Based Price Benchmarks. Available online: https://icer.org/wp-content/uploads/2020/10/MWCEPAC_NSCLC_Final_Evidence_Report_Meeting_Summary_110116.pdf. Accessed March 4, 2023.
34. Yang M, Vioix H, Sachdev R, et al. Cost-Effectiveness of Tepotinib Versus Capmatinib for the Treatment of Adult Patients With Metastatic Non-Small Cell Lung Cancer Harboring Mesenchymal-Epithelial Transition Exon 14 Skipping. Value Health 2023;26:487-97. [Crossref] [PubMed]
35. U.S. Bureau of Economic Analysis. Personal Consumption Expenditures Price Index. Available online: https://www.bea.gov/data/personal-consumption-expenditures-price-index. Accessed March 12, 2023.
36. Centers for Medicare and Medicaid Services. April 2023 ASP Pricing File. Available online: https://www.cms.gov/. Accessed April 16, 2023.
37. Centers for Medicare and Medicaid Services. Physician Fee Schedule Look-Up Tool. Available online: https://www.cms.gov/medicare/physician-fee-schedule/search. Accessed April 21, 2023.
38. Criss SD, Mooradian MJ, Watson TR, et al. Cost-effectiveness of Atezolizumab Combination Therapy for First-Line Treatment of Metastatic Nonsquamous Non-Small Cell Lung Cancer in the United States. JAMA Netw Open 2019;2:e1911952. [Crossref] [PubMed]
39. Wan X, Luo X, Tan C, et al. First-line atezolizumab in addition to bevacizumab plus chemotherapy for metastatic, nonsquamous non-small cell lung cancer: A United States-based cost-effectiveness analysis. Cancer 2019;125:3526-34. [Crossref] [PubMed]
40. Agency for Healthcare Research and Quality. Healthcare Cost and Utilization Project (HCUPnet). Available online: https://datatools.ahrq.gov/hcupnet. Accessed April 22, 2023.
41. Institute for Clinical and Economic Review. 2020-2023 Value Assessment Framework. Available online: https://icer.org/wp-content/uploads/2020/10/ICER_2020_2023_VAF_102220.pdf. Accessed January 20, 2023.
42. Hellmann MD, Paz-Ares L, Bernabe Caro R, et al. Nivolumab plus Ipilimumab in Advanced Non-Small-Cell Lung Cancer. N Engl J Med 2019;381:2020-31. [Crossref] [PubMed]
43. Paz-Ares L, Ciuleanu TE, Cobo M, et al. First-line nivolumab plus ipilimumab combined with two cycles of chemotherapy in patients with non-small-cell lung cancer (CheckMate 9LA): an international, randomised, open-label, phase 3 trial. Lancet Oncol 2021;22:198-211. [Crossref] [PubMed]