First-line treatments for metastatic non-small-cell lung cancer with Sugemalimab plus chemotherapy: a China-based cost-effectiveness analysis

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Methods A three-state Markov model with 21-day cycles over 10 years was developed to compare sugemalimab plus chemotherapy versus placebo plus chemotherapy. Key model inputs were derived from the 4-year survival data of the GEMSTONE-302 trial and publicly available sources. Outcomes were measured in quality-adjusted life years(QALYs) and incremental cost-effectiveness ratios(ICERs). The willingness-to-pay(WTP) threshold was set at three times the per capita GDP of China in 2024(40,062.34 $ /QALY). Sensitivity analyses were performed to assess model robustness. Results Base-case ICERs were 65,766.82 $ /QALY for squamous and 70,117.72 $ /QALY for non-squamous NSCLC, both above the WTP threshold. Subgroup analyses indicated that patients with PD-L1 expression ≥ 50% had the most favorable ICER(60,516.14 $ /QALY), while those with PD-L1 < 1% had the least favorable outcome(80,599.12 $ /QALY). Sensitivity analyses identified drug price and utility values as the most influential parameters affecting ICERs. Conclusion Sugemalimab plus platinum-based chemotherapy offers long-term clinical benefits for metastatic NSCLC but is not cost-effective at current prices in China. Improving cost-effectiveness may require targeting patients with high PD-L1 expression, adjusting reimbursement policies, and reducing drug prices. Sugemalimab Non-small cell lung cancer Immunotherapy Cost-effectiveness analysis Markov model Figures Figure 1 Figure 2 Figure 3 Figure 4 1. Introduction According to the 2022 Global Cancer Burden data, lung cancer remains one of the most commonly diagnosed malignancies worldwide, with nearly 2.5 million new cases annually—accounting for approximately one-eighth of all newly diagnosed cancers [ 1 ] .Non-small cell lung cancer(NSCLC) is the predominant histological subtype of lung cancer, accounting for approximately 85% of all cases. Among these, adenocarcinoma and squamous cell carcinoma represent about 60% and 15%, respectively [ 2 ] . Histological classification is not only essential for the diagnosis of NSCLC but also plays a critical role in guiding treatment strategies, assessing drug efficacy, and predicting toxicity. In recent years, immune checkpoint inhibitors(ICIs) targeting PD-1/PD-L1 have made significant advances in the treatment of NSCLC, prolonging survival in patients with advanced disease and becoming a cornerstone of first-line therapy for metastatic NSCLC. Numerous studies have confirmed that ICIs combined with platinum-based chemotherapy improve overall survival while maintaining an acceptable safety profile, solidifying their role in first-line treatment [ 3 – 6 ] . Sugemalimab is a fully human monoclonal antibody that specifically targets PD-L1, demonstrating favorable immunogenicity control and tumor-targeting capabilities. The GEMSTONE-302 study is a pivotal, randomized, double-blind, multicenter Phase III clinical trial designed to evaluate the efficacy and safety of sugemalimab combined with platinum-based chemotherapy in treatment-naïve patients with metastatic NSCLC. The results showed that the combination regimen significantly prolonged progression-free survival and exhibited a favorable safety profile, providing strong evidence to support its use as a first-line immunotherapy option for NSCLC [ 7 ] . With ongoing research, the 4-year long-term follow-up results of the GEMSTONE-302 study have recently been published, further confirming the sustained benefits of the regimen in terms of overall survival and long-term disease control. These updated data provide a new foundation for more accurate health economic modeling [ 8 ] . Despite the clinical benefits of sugemalimab, its high cost imposes a significant burden on China’s healthcare system and patients, making cost-effectiveness a key barrier to its broader adoption and reimbursement. Currently, economic evaluations based on long-term follow-up data remain lacking. Therefore, this study, from the perspective of China’s healthcare system, utilizes the latest 4-year data from the GEMSTONE-302 trial to construct a Markov model for systematically assessing the cost-effectiveness of sugemalimab plus platinum-based chemotherapy as a first-line treatment for metastatic NSCLC, aiming to enhance the long-term accuracy and real-world applicability of economic projections. 2. Methods 2.1 Model Structure A Markov model was developed to evaluate the cost-effectiveness of sugemalimab combined with platinum-based chemotherapy as a first-line treatment for NSCLC. The model consisted of three health states: progression-free survival(PFS), progressive disease(PD), and death, as illustrated in Fig. 1 . Each treatment strategy assumed a cohort of 1,000 patients, all starting in the PFS state. The model employed a cycle length of 21 days to simulate transitions between health states over time. A 10-year time horizon was adopted to capture most patients’lifetimes, ensuring model stability and convergence of outcomes. Transitions were assumed to be unidirectional: from PFS to PD or death, with no possibility of reversal once progression or death occurred. The primary outcomes included total treatment cost, QALYs, and ICER. 2.2 Intervention The intervention strategies in this study were based on the design of the GEMSTONE-302 trial. Eligible patients with metastatic NSCLC were randomly assigned in a 2:1 ratio to receive either sugemalimab plus chemotherapy or placebo plus chemotherapy. Patients with non-squamous NSCLC received sugemalimab or placebo in combination with carboplatin and pemetrexed every 3 weeks for up to four cycles, followed by maintenance therapy with sugemalimab or placebo plus pemetrexed. Patients with squamous NSCLC received sugemalimab or placebo with carboplatin and paclitaxel for four cycles, followed by maintenance monotherapy with sugemalimab or placebo. Sugemalimab or placebo was administered for a maximum of 35 cycles or until disease progression or unacceptable toxicity occurred. Dose modification of sugemalimab or placebo was not permitted unless prespecified criteria were met, while dose adjustments for chemotherapy agents were allowed based on toxicity. Patients in the placebo group who experienced disease progression were eligible to cross over to receive sugemalimab monotherapy. Upon progression, second-line treatment followed the recommendations of the 2025 edition of the Chinese Society of Clinical Oncology guidelines for NSCLC, with docetaxel used as the standard therapy [ 9 ] . 2.3 Transition Probabilities To obtain survival-related parameters, this study first employed the WebPlotDigitizer tool to extract PFS and overall survival(OS) Kaplan-Meier curve data from the publicly reported 4-year follow-up results of the GEMSTONE-302 trial. The reconstructed individual patient data were then generated using the IPDfromKM software package. Multiple parametric survival distributions—including exponential, Weibull, log-logistic, log-normal, Gompertz, gamma, generalized gamma, and generalized F distributions—were fitted to the PFS and OS data. Based on the Akaike Information Criterion, the log-logistic distribution was identified as the best fit for modeling both OS and PFS in the squamous NSCLC group. For the non-squamous NSCLC group, the log-logistic distribution was optimal for fitting the control group’s PFS and the treatment group’s OS, while the log-normal distribution provided the best fit for the treatment group’s PFS and the control group’s OS. Based on the selected distribution models, the transition probability from one cycle to the next was calculated using the following equation: tp(t u ) = 1-S(t)/S(t-u) In addition, age-specific background mortality rates from other causes were incorporated into the model based on the China Population Census Yearbook 2020, to enhance the model’s alignment with real-world survival patterns [ 10 ] . 2.4 Costs and Utilities This study conducted a cost-effectiveness evaluation from the perspective of the Chinese healthcare system, incorporating only direct medical costs. Direct costs included the expenses of sugemalimab and chemotherapy drugs, management of grade ≥ 3 adverse events(with an incidence ≥ 5%), routine follow-up, best supportive care, and terminal care. Drug prices were based on 2024 national bid-winning prices across provinces, obtained from Yaozhi Network, and were determined by calculating the weighted national average [ 11 ] . Other medical service-related costs were obtained through a systematic literature review. All financial figures are presented in US dollars, with the exchange rate set at $ 1 to ¥7.17. Medication dosages were estimated based on a model patient assumption: a creatinine clearance rate of 70 mL/min and a body surface area of 1.72 m². Based on these parameters, the actual dosages and corresponding drug costs for sugemalimab and chemotherapy agents were calculated. The costs of adverse event management included only those related to grade ≥ 3 adverse events with an incidence ≥ 5%, namely: Anemia, Decreased white blood cell count, Decreased neutrophil count, and Decreased platelet count. These costs were only included once, during the first treatment cycle. Grade ≤ 2 adverse events were not costed separately as they typically do not require specific treatment. Regarding health utilities, as the GEMSTONE-302 study did not collect quality-of-life data directly, utility values were obtained from published domestic literature. The utility value was set at 0.75 for the PFS state and 0.59 for the PD state [ 12 ] . In accordance with the China Guidelines for Pharmacoeconomic Evaluations(2020), all cost and utility inputs were discounted at an annual rate of 5% to account for time preference [ 13 ] . Table 1 Model parameters Parameters Specific parameters base line Range distribution Sources Min Max Drug costs( $ ) Sugemalimab 600mg 1725.9 1380.7 2071.1 Gamma [ 11 ] Carboplatin 100mg 5.7 4.6 6.8 Gamma [ 11 ] Pemetrexed 100mg 78.2 62.6 93.8 Gamma [ 11 ] Paclitaxel 100mg 13.3 10.6 15.9 Gamma [ 11 ] Docetaxel 40mg 12.8 10.2 15.7 Gamma [ 11 ] Cost of Adverse Reaction Management( $ ) Anemia 537 478 585 Gamma [ 14 ] Decreased white blood cell count 466 415 508 Gamma [ 14 ] Decreased neutrophil count 466 415 508 Gamma [ 14 ] Decreased platelet count 6397 5117 7676 Gamma [ 14 ] Health-care costs( $ ) Routine follow-up cost per cycle 55.6 27.8 83.4 Gamma [ 15 ] Best supportive care per cycle 337.5 168.7 506.2 Gamma [ 15 ] terminal care 2627.8 1313.9 3941.7 Gamma [ 15 ] Risks of SAEs in SC arm (grade 3 or 4)% Anemia 14 11.2 16.8 Beta [ 8 ] Decreased white blood cell count 15 12 18 Beta [ 8 ] Decreased neutrophil count 33 26.4 39.6 Beta [ 8 ] Decreased platelet count 11 8.8 13.2 Beta [ 8 ] Risks of SAEs in PC arm (grade 3 or 4)% Anemia 11 8.8 13.2 Beta [ 8 ] Decreased white blood cell count 17 13.6 20.4 Beta [ 8 ] Decreased neutrophil count 33 26.4 39.6 Beta [ 8 ] Decreased platelet count 9 7.2 10.8 Beta [ 8 ] 2.5 Subgroup Scenario Analysis To further assess the cost-effectiveness of sugemalimab combined with chemotherapy as a first-line treatment across different PD-L1 expression subgroups, a scenario-based subgroup analysis was conducted using the 4-year survival data from the GEMSTONE-302 study. Patients were categorized into four subgroups based on tumor PD-L1 expression levels: 1. PD-L1 ≥ 50%: High expressers, who have been shown in multiple immunotherapy studies to respond well to immune checkpoint inhibitors; 2. 1% ≤ PD-L1 ≤ 49%: Intermediate expressers, with clinical outcomes exhibiting some heterogeneity; 3. PD-L1 < 1%: Low or negative expressers, traditionally considered less responsive to immunotherapy; 4. PD-L1 ≥ 1%: A combined group of intermediate and high expressers, included for broader comparison with the PD-L1 < 1% group. Median PFS and OS parameters for each subgroup were derived from the publicly available 4-year follow-up data of the GEMSTONE-302 study. Based on these inputs, separate Markov models were constructed for each subgroup to evaluate the ICERs of sugemalimab plus platinum-based chemotherapy versus the control group under different PD-L1 expression levels. 2.6 Statistical Analysis 2.6.1 Base-case ICERs Cost-effectiveness analysis was performed using R software(version 4.5.0) as the primary analytical tool. The WTP threshold was set at three times the per capita GDP of China in 2024, equating to 40,062.34 $ /QALY [ 16 ] . The cost-effectiveness of each treatment strategy was determined by comparing its ICER against the predefined WTP threshold. An ICER below this threshold was considered cost-effective. 2.6.2 Sensitivity analysis To assess the impact of parameter uncertainty on model outcomes, both one-way sensitivity analysis and probabilistic sensitivity analysis were conducted. In the one-way sensitivity analysis, input parameters were varied within their reported 95% confidence intervals. For parameters lacking explicit ranges, a ± 20% variation from the base value was applied. The discount rate was explored within a range of 0% to 8%. Results were visualized using tornado diagrams to identify key drivers of ICER variation. In the probabilistic sensitivity analysis, Monte Carlo simulation was performed with 5,000 iterations based on the predefined probability distributions for model parameters. The results were presented using cost-effectiveness scatter plots and cost-effectiveness acceptability curves to reflect the overall uncertainty and the probability of cost-effectiveness at different WTP thresholds. 3. Results 3.1 Base-case ICERs In the squamous NSCLC patient group, the sugemalimab plus platinum-based chemotherapy regimen yielded 2.31 QALYs with a total treatment cost of $ 88,585.1. In comparison, the control group achieved 1.26 QALYs at a total cost of $ 19,666.5. This represents an incremental gain of 1.05 QALYs and an additional cost of $ 68,918.6 for the sugemalimab regimen, resulting in an ICER of $ 65,766.82 per QALY. Table 2 Analysis results for the squamous NSCLC group Sugemalimab + chemotherapy Placebo + chemotherapy Total cost( $ ) 88,585.1 19,666.5 QALYs 2.31 1.26 Incremental cost( $ ) 68,918.6 Incremental utility(QALYs) 1.05 ICER( $ /QALY) 65,766.82 In the non-squamous NSCLC patient group, the sugemalimab plus platinum-based chemotherapy regimen yielded 2.67 QALYs with a total treatment cost of $ 98,553.7. In contrast, the control group achieved 1.64 QALYs at a total cost of $ 26,159.4. Compared with the control group, the sugemalimab regimen resulted in an incremental gain of 1.03 QALYs and an additional cost of $ 72,394.3, leading to an ICER of $ 70,117.72 per QALY. Table 3 Analysis results for the NSCLC group Sugemalimab + chemotherapy Placebo + chemotherapy Total cost( $ ) 98,553.7 26,159.4 QALYs 2.67 1.64 Incremental cost( $ ) 72,394.3 Incremental utility(QALYs) 1.03 ICER( $ /QALY) 70,117.72 3.2 Subgroup Scenario Analysis The results of the subgroup cost-effectiveness analysis based on PD-L1 expression levels are as follows: for patients with PD-L1 expression ≥ 50%, the ICER was $ 60,516.14 per QALY. For those with PD-L1 expression between 1% and 49%, the ICER was $ 79,564.19 per QALY. In the subgroup with PD-L1 expression < 1%, the ICER reached $ 80,599.12 per QALY. For patients with PD-L1 expression ≥ 1%, the ICER was $ 67,961.85 per QALY. Table 4 Results of subgroup scenario analysis Population Treatment Cost ( $ ) QALYs Incremental cost Incremental QALYs ICER PD-L1 ≥ 50% SC 112,506.8 3.31 85,776.6 1.42 60,516.14 PC 26,730,2 1.89 1%≤PD-L1 ≤ 49% SC 88,608.8 2.34 66,324.0 0.84 79,564.19 PC 22,284.8 1.50 PD-L1 < 1% SC 78,432.5 1.97 59,226.2 0.74 80,599.12 PC 19,206.3 1.23 PD-L1 ≥ 1% SC 101,933.1 2.85 77,220.1 1.14 67,961.85 PC 24,713.0 1.71 3.3 Sensitivity analysis 3.3.1 Sensitivity Analysis for Squamous NSCLC The one-way sensitivity analysis(Fig. 2 A) showed that the model was most sensitive to the drug cost of sugemalimab, which had the greatest impact on ICER when varied. Other influential parameters included the utility values during the PFS and PD phases, as well as the discount rate. These findings highlight the critical role of drug pricing and patient quality-of-life assessments in determining the economic viability of the treatment. The probabilistic sensitivity analysis based on 5,000 Monte Carlo simulations(Fig. 3 A) demonstrated that most simulated ICER values were distributed above the WTP threshold, suggesting that the sugemalimab regimen is unlikely to be cost-effective for patients with squamous NSCLC under current parameter settings. The cost-effectiveness acceptability curve(Fig. 4 A) indicated that the probability of the regimen being cost-effective at the current WTP threshold was approximately 0.12%. Although this probability increases with higher WTP thresholds, it remains low within the range of realistic payer capacities. 3.3.2 Sensitivity Analysis for Non-squamous NSCLC As shown in Fig. 2 B, for non-squamous NSCLC patients, the cost of sugemalimab remained the most influential factor affecting ICER variability. This was followed by utility values in the PFS and PD health states, the discount rate, and best supportive care costs—all of which had a significant impact on ICER results. These findings suggest that the cost-effectiveness of this treatment strategy is highly dependent on drug pricing and improvements in patients’ quality of life. The cost-effectiveness scatter plot(Fig. 3 B) indicates that the vast majority of simulation points lie above the WTP threshold, suggesting that the treatment is not cost-effective in the non-squamous population. The cost-effectiveness acceptability curve(Fig. 4 B) shows that, at the current WTP threshold, the probability of this regimen being cost-effective is approximately 0.26%.. 4. Discussion This study constructed a Markov model based on the latest 4-year follow-up results from the GEMSTONE-302 trial to evaluate the long-term cost-effectiveness of sugemalimab plus platinum-based chemotherapy as a first-line treatment for metastatic NSCLC from the perspective of China’s healthcare system. Compared with earlier studies that relied on mid-term follow-up data, the use of long-term survival data in this analysis provides more comprehensive and accurate simulations of survival duration and health state transitions, thereby greatly improving the real-world relevance and reliability of the economic evaluation. A key finding is the significant reduction in ICER results after incorporating the 4-year follow-up data. In previous research based on median survival modeling, the estimated ICER was 109,480.97 $ /QALY—far exceeding the WTP threshold in China [ 12 ] . In contrast, this study found that the ICER decreased to 65,766.82 $ /QALY in squamous NSCLC patients and 70,117.72 $ /QALY in non-squamous patients, indicating a trend toward improved cost-effectiveness with long-term observation. This change is largely attributable to the sustained survival benefits observed in the GEMSTONE-302 four-year data: the median overall survival in the combination group was extended by nearly 8 months compared to placebo, and the 4-year overall survival rate was almost doubled. Notably, several patients remained on treatment for more than two years, with the longest duration reaching 52 months—demonstrating strong long-term disease control. These extended clinical benefits translated into a greater gain in QALYs than earlier models predicted, effectively diluting the long-term treatment costs. Compared with other PD-L1 inhibitors such as atezolizumab and durvalumab, which failed to demonstrate significant improvements in OS when combined with chemotherapy in the IMpower and CASPIAN trials, sugemalimab in the GEMSTONE-302 study exhibited more consistent and broad long-term efficacy. This was particularly evident in patients with low PD-L1 expression and those with brain metastases, where sugemalimab showed breakthrough survival advantages [ 3 , 17 ] . Moreover, compared with dual immunotherapy regimens combining PD-(L)1 and CTLA-4 inhibitors—which may offer some long-term survival benefits—sugemalimab demonstrates superior safety. The incidence of grade ≥ 3 immune-related adverse events remains below 5%, reducing the likelihood of severe toxicities while maintaining efficacy. This favorable safety profile contributes to a higher cost-effectiveness potential in health economic evaluations [ 18 ] . Although the current ICER results exceed the WTP threshold, sugemalimab-based therapy still demonstrates substantial clinical value in select high-benefit populations. Policymakers are therefore encouraged to consider the following strategies: prioritize inclusion of patients with PD-L1 expression ≥ 50% in reimbursement coverage to improve resource allocation efficiency; negotiate drug pricing to enhance affordability; and promote precise patient selection to increase the economic efficiency of treatment. This study has several limitations. First, the survival data were derived from a clinical trial setting, and although 4-year follow-up information was used, long-term outcomes may still differ from real-world results. Second, certain model inputs were based on literature-derived estimates, which may introduce potential bias. Additionally, indirect costs and a societal perspective were not incorporated, nor were the long-term costs of post-progression crossover therapies modeled. Future research should validate these modeling outcomes using real-world evidence, explore more representative patient populations in economic assessments, and strengthen simulation analyses of alternative reimbursement schemes to provide evidence-based support for a multi-tiered health insurance system. 5. Conclusion This study demonstrates that, at current pricing levels, sugemalimab combined with platinum-based chemotherapy as a first-line treatment for metastatic NSCLC is not cost-effective in China, particularly among patients with low PD-L1 expression. Although the regimen shows clear survival benefits and a favorable safety profile, its economic viability remains limited. Precision treatment targeting patients with high PD-L1 expression, along with drug price optimization, may help improve the cost-effectiveness and accessibility of this regimen within China’s healthcare system. Declarations Author Contribution ZZ: Writing-original draft. KM: Writing-original draft. 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UniversityPathology","correspondingAuthor":false,"prefix":"","firstName":"Yang","middleName":"","lastName":"Wang","suffix":""}],"badges":[],"createdAt":"2025-10-27 11:31:18","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-7953546/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-7953546/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":95655870,"identity":"d2a17b19-c2ce-4795-ab5d-d7e5c4398669","added_by":"auto","created_at":"2025-11-11 16:17:05","extension":"docx","order_by":0,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":233415,"visible":true,"origin":"","legend":"","description":"","filename":"Manuscriptwithauthordetails.docx","url":"https://assets-eu.researchsquare.com/files/rs-7953546/v1/b6949b06c544c163dcb9036d.docx"},{"id":95565165,"identity":"44a4c129-d1fc-48dc-bbab-ec617b10190e","added_by":"auto","created_at":"2025-11-10 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16:14:34","extension":"xml","order_by":17,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":77142,"visible":true,"origin":"","legend":"","description":"","filename":"7bb16c64f5fc4d9da1c6e3f768157a161structuring.xml","url":"https://assets-eu.researchsquare.com/files/rs-7953546/v1/6e558f429cb639dcc66e4401.xml"},{"id":95565187,"identity":"99979488-2708-4f0f-906b-332d59d2045a","added_by":"auto","created_at":"2025-11-10 16:13:03","extension":"html","order_by":18,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":85566,"visible":true,"origin":"","legend":"","description":"","filename":"earlyproof.html","url":"https://assets-eu.researchsquare.com/files/rs-7953546/v1/c6912ea01a0f4dcc33f1a2c7.html"},{"id":95565163,"identity":"7a614fd3-3777-4b70-9683-3d7c2e296019","added_by":"auto","created_at":"2025-11-10 16:13:02","extension":"jpg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":18713,"visible":true,"origin":"","legend":"\u003cp\u003eStructure of the markov model\u003c/p\u003e","description":"","filename":"Picture1.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7953546/v1/f7b75bcf6e0966aa8dfb59fd.jpg"},{"id":95655282,"identity":"200de444-7a43-45f7-80af-2518c7fa89e8","added_by":"auto","created_at":"2025-11-11 16:15:08","extension":"jpg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":264224,"visible":true,"origin":"","legend":"\u003cp\u003e2A \u0026nbsp;One-way sensitivity tornado diagram for squamous NSCLC\u003c/p\u003e\n\u003cp\u003e2B \u0026nbsp;One-way sensitivity tornado diagram for non-squamous NSCLC\u003c/p\u003e","description":"","filename":"2.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7953546/v1/b48516a015366ec5bc466831.jpg"},{"id":95654608,"identity":"d46603b6-20db-402c-9a8e-7ac7eac742c2","added_by":"auto","created_at":"2025-11-11 16:12:33","extension":"jpg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":323794,"visible":true,"origin":"","legend":"\u003cp\u003e3A \u0026nbsp;Cost-effectiveness scatter plot for squamous NSCLC\u003c/p\u003e\n\u003cp\u003e3B \u0026nbsp;Cost-effectiveness scatter plot for non-squamous NSCLC\u003c/p\u003e","description":"","filename":"3.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7953546/v1/6c872ce9516feaf404ad6e8b.jpg"},{"id":95565167,"identity":"f11b3685-e7ff-4bcb-9683-b5c4e8c833f3","added_by":"auto","created_at":"2025-11-10 16:13:02","extension":"jpg","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":252418,"visible":true,"origin":"","legend":"\u003cp\u003e4A \u0026nbsp;Cost-effectiveness acceptability curve for squamous NSCLC\u003c/p\u003e\n\u003cp\u003e4B \u0026nbsp;Cost-effectiveness acceptability curve for non-squamous NSCLC\u003c/p\u003e","description":"","filename":"4.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7953546/v1/2fb1395a38165d1bf2329f8a.jpg"},{"id":101206055,"identity":"f9070e21-79c1-4b13-9834-8e852d41f855","added_by":"auto","created_at":"2026-01-27 09:52:57","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1735565,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7953546/v1/4bf0b303-18e1-4e56-9665-3c3c1f1b578a.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"First-line treatments for metastatic non-small-cell lung cancer with Sugemalimab plus chemotherapy: a China-based cost-effectiveness analysis","fulltext":[{"header":"1. Introduction","content":"\u003cp\u003eAccording to the 2022 Global Cancer Burden data, lung cancer remains one of the most commonly diagnosed malignancies worldwide, with nearly 2.5\u0026nbsp;million new cases annually\u0026mdash;accounting for approximately one-eighth of all newly diagnosed cancers\u003csup\u003e[\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]\u003c/sup\u003e.Non-small cell lung cancer(NSCLC) is the predominant histological subtype of lung cancer, accounting for approximately 85% of all cases. Among these, adenocarcinoma and squamous cell carcinoma represent about 60% and 15%, respectively\u003csup\u003e[\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]\u003c/sup\u003e. Histological classification is not only essential for the diagnosis of NSCLC but also plays a critical role in guiding treatment strategies, assessing drug efficacy, and predicting toxicity.\u003c/p\u003e\u003cp\u003eIn recent years, immune checkpoint inhibitors(ICIs) targeting PD-1/PD-L1 have made significant advances in the treatment of NSCLC, prolonging survival in patients with advanced disease and becoming a cornerstone of first-line therapy for metastatic NSCLC. Numerous studies have confirmed that ICIs combined with platinum-based chemotherapy improve overall survival while maintaining an acceptable safety profile, solidifying their role in first-line treatment\u003csup\u003e[\u003cspan additionalcitationids=\"CR4 CR5\" citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]\u003c/sup\u003e. Sugemalimab is a fully human monoclonal antibody that specifically targets PD-L1, demonstrating favorable immunogenicity control and tumor-targeting capabilities. The GEMSTONE-302 study is a pivotal, randomized, double-blind, multicenter Phase III clinical trial designed to evaluate the efficacy and safety of sugemalimab combined with platinum-based chemotherapy in treatment-na\u0026iuml;ve patients with metastatic NSCLC. The results showed that the combination regimen significantly prolonged progression-free survival and exhibited a favorable safety profile, providing strong evidence to support its use as a first-line immunotherapy option for NSCLC\u003csup\u003e[\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]\u003c/sup\u003e. With ongoing research, the 4-year long-term follow-up results of the GEMSTONE-302 study have recently been published, further confirming the sustained benefits of the regimen in terms of overall survival and long-term disease control. These updated data provide a new foundation for more accurate health economic modeling\u003csup\u003e[\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003eDespite the clinical benefits of sugemalimab, its high cost imposes a significant burden on China\u0026rsquo;s healthcare system and patients, making cost-effectiveness a key barrier to its broader adoption and reimbursement. Currently, economic evaluations based on long-term follow-up data remain lacking. Therefore, this study, from the perspective of China\u0026rsquo;s healthcare system, utilizes the latest 4-year data from the GEMSTONE-302 trial to construct a Markov model for systematically assessing the cost-effectiveness of sugemalimab plus platinum-based chemotherapy as a first-line treatment for metastatic NSCLC, aiming to enhance the long-term accuracy and real-world applicability of economic projections.\u003c/p\u003e"},{"header":"2. Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\u003ch2\u003e2.1 Model Structure\u003c/h2\u003e\u003cp\u003eA Markov model was developed to evaluate the cost-effectiveness of sugemalimab combined with platinum-based chemotherapy as a first-line treatment for NSCLC. The model consisted of three health states: progression-free survival(PFS), progressive disease(PD), and death, as illustrated in Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e. Each treatment strategy assumed a cohort of 1,000 patients, all starting in the PFS state. The model employed a cycle length of 21 days to simulate transitions between health states over time. A 10-year time horizon was adopted to capture most patients\u0026rsquo;lifetimes, ensuring model stability and convergence of outcomes. Transitions were assumed to be unidirectional: from PFS to PD or death, with no possibility of reversal once progression or death occurred. The primary outcomes included total treatment cost, QALYs, and ICER.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec4\" class=\"Section2\"\u003e\u003ch2\u003e2.2 Intervention\u003c/h2\u003e\u003cp\u003eThe intervention strategies in this study were based on the design of the GEMSTONE-302 trial. Eligible patients with metastatic NSCLC were randomly assigned in a 2:1 ratio to receive either sugemalimab plus chemotherapy or placebo plus chemotherapy. Patients with non-squamous NSCLC received sugemalimab or placebo in combination with carboplatin and pemetrexed every 3 weeks for up to four cycles, followed by maintenance therapy with sugemalimab or placebo plus pemetrexed. Patients with squamous NSCLC received sugemalimab or placebo with carboplatin and paclitaxel for four cycles, followed by maintenance monotherapy with sugemalimab or placebo.\u003c/p\u003e\u003cp\u003eSugemalimab or placebo was administered for a maximum of 35 cycles or until disease progression or unacceptable toxicity occurred. Dose modification of sugemalimab or placebo was not permitted unless prespecified criteria were met, while dose adjustments for chemotherapy agents were allowed based on toxicity. Patients in the placebo group who experienced disease progression were eligible to cross over to receive sugemalimab monotherapy.\u003c/p\u003e\u003cp\u003eUpon progression, second-line treatment followed the recommendations of the 2025 edition of the Chinese Society of Clinical Oncology guidelines for NSCLC, with docetaxel used as the standard therapy\u003csup\u003e[\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]\u003c/sup\u003e.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec5\" class=\"Section2\"\u003e\u003ch2\u003e2.3 Transition Probabilities\u003c/h2\u003e\u003cp\u003eTo obtain survival-related parameters, this study first employed the WebPlotDigitizer tool to extract PFS and overall survival(OS) Kaplan-Meier curve data from the publicly reported 4-year follow-up results of the GEMSTONE-302 trial. The reconstructed individual patient data were then generated using the IPDfromKM software package. Multiple parametric survival distributions\u0026mdash;including exponential, Weibull, log-logistic, log-normal, Gompertz, gamma, generalized gamma, and generalized F distributions\u0026mdash;were fitted to the PFS and OS data.\u003c/p\u003e\u003cp\u003eBased on the Akaike Information Criterion, the log-logistic distribution was identified as the best fit for modeling both OS and PFS in the squamous NSCLC group. For the non-squamous NSCLC group, the log-logistic distribution was optimal for fitting the control group\u0026rsquo;s PFS and the treatment group\u0026rsquo;s OS, while the log-normal distribution provided the best fit for the treatment group\u0026rsquo;s PFS and the control group\u0026rsquo;s OS. Based on the selected distribution models, the transition probability from one cycle to the next was calculated using the following equation:\u003c/p\u003e\u003cp\u003e\u003cem\u003etp(t\u003c/em\u003e\u003csub\u003e\u003cem\u003eu\u003c/em\u003e\u003c/sub\u003e\u003cem\u003e)\u0026thinsp;=\u0026thinsp;1-S(t)/S(t-u)\u003c/em\u003e\u003c/p\u003e\u003cp\u003eIn addition, age-specific background mortality rates from other causes were incorporated into the model based on the China Population Census Yearbook 2020, to enhance the model\u0026rsquo;s alignment with real-world survival patterns\u003csup\u003e[\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]\u003c/sup\u003e.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec6\" class=\"Section2\"\u003e\u003ch2\u003e2.4 Costs and Utilities\u003c/h2\u003e\u003cp\u003eThis study conducted a cost-effectiveness evaluation from the perspective of the Chinese healthcare system, incorporating only direct medical costs. Direct costs included the expenses of sugemalimab and chemotherapy drugs, management of grade\u0026thinsp;\u0026ge;\u0026thinsp;3 adverse events(with an incidence\u0026thinsp;\u0026ge;\u0026thinsp;5%), routine follow-up, best supportive care, and terminal care.\u003c/p\u003e\u003cp\u003eDrug prices were based on 2024 national bid-winning prices across provinces, obtained from Yaozhi Network, and were determined by calculating the weighted national average\u003csup\u003e[\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]\u003c/sup\u003e. Other medical service-related costs were obtained through a systematic literature review. All financial figures are presented in US dollars, with the exchange rate set at \u003cspan\u003e$\u003c/span\u003e1 to \u0026yen;7.17. Medication dosages were estimated based on a model patient assumption: a creatinine clearance rate of 70 mL/min and a body surface area of 1.72 m\u0026sup2;. Based on these parameters, the actual dosages and corresponding drug costs for sugemalimab and chemotherapy agents were calculated. The costs of adverse event management included only those related to grade\u0026thinsp;\u0026ge;\u0026thinsp;3 adverse events with an incidence\u0026thinsp;\u0026ge;\u0026thinsp;5%, namely: Anemia, Decreased white blood cell count, Decreased neutrophil count, and Decreased platelet count. These costs were only included once, during the first treatment cycle. Grade\u0026thinsp;\u0026le;\u0026thinsp;2 adverse events were not costed separately as they typically do not require specific treatment.\u003c/p\u003e\u003cp\u003eRegarding health utilities, as the GEMSTONE-302 study did not collect quality-of-life data directly, utility values were obtained from published domestic literature. The utility value was set at 0.75 for the PFS state and 0.59 for the PD state\u003csup\u003e[\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]\u003c/sup\u003e. In accordance with the China Guidelines for Pharmacoeconomic Evaluations(2020), all cost and utility inputs were discounted at an annual rate of 5% to account for time preference\u003csup\u003e[\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eModel parameters\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"7\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003eParameters\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003eSpecific parameters\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003ebase line\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\u003cp\u003eRange\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003edistribution\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c7\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003eSources\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eMin\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eMax\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"4\" rowspan=\"5\"\u003e\u003cp\u003eDrug costs(\u003cspan\u003e$\u003c/span\u003e)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eSugemalimab 600mg\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1725.9\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1380.7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e2071.1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eGamma\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e\u003csup\u003e[\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eCarboplatin 100mg\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e5.7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e4.6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e6.8\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eGamma\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e\u003csup\u003e[\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003ePemetrexed 100mg\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e78.2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e62.6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e93.8\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eGamma\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e\u003csup\u003e[\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003ePaclitaxel 100mg\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e13.3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e10.6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e15.9\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eGamma\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e\u003csup\u003e[\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eDocetaxel 40mg\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e12.8\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e10.2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e15.7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eGamma\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e\u003csup\u003e[\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"3\" rowspan=\"4\"\u003e\u003cp\u003eCost of Adverse Reaction Management(\u003cspan\u003e$\u003c/span\u003e)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eAnemia\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e537\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e478\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e585\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eGamma\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e\u003csup\u003e[\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eDecreased white blood cell count\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e466\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e415\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e508\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eGamma\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e\u003csup\u003e[\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eDecreased neutrophil count\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e466\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e415\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e508\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eGamma\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e\u003csup\u003e[\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eDecreased platelet count\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e6397\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e5117\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e7676\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eGamma\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e\u003csup\u003e[\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e\u003cp\u003eHealth-care costs(\u003cspan\u003e$\u003c/span\u003e)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eRoutine follow-up cost per cycle\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e55.6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e27.8\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e83.4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eGamma\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e\u003csup\u003e[\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eBest supportive care per cycle\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e337.5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e168.7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e506.2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eGamma\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e\u003csup\u003e[\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eterminal care\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e2627.8\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1313.9\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e3941.7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eGamma\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e\u003csup\u003e[\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eRisks of SAEs in SC arm (grade 3 or 4)%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eAnemia\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e14\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e11.2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e16.8\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eBeta\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e\u003csup\u003e[\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eDecreased white blood cell count\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e15\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e12\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e18\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eBeta\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e\u003csup\u003e[\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eDecreased neutrophil count\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e33\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e26.4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e39.6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eBeta\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e\u003csup\u003e[\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eDecreased platelet count\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e11\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e8.8\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e13.2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eBeta\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e\u003csup\u003e[\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eRisks of SAEs in PC arm (grade 3 or 4)%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eAnemia\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e11\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e8.8\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e13.2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eBeta\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e\u003csup\u003e[\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eDecreased white blood cell count\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e17\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e13.6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e20.4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eBeta\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e\u003csup\u003e[\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eDecreased neutrophil count\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e33\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e26.4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e39.6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eBeta\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e\u003csup\u003e[\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eDecreased platelet count\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e9\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e7.2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e10.8\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eBeta\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e\u003csup\u003e[\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec7\" class=\"Section2\"\u003e\u003ch2\u003e2.5 Subgroup Scenario Analysis\u003c/h2\u003e\u003cp\u003eTo further assess the cost-effectiveness of sugemalimab combined with chemotherapy as a first-line treatment across different PD-L1 expression subgroups, a scenario-based subgroup analysis was conducted using the 4-year survival data from the GEMSTONE-302 study. Patients were categorized into four subgroups based on tumor PD-L1 expression levels: 1. PD-L1\u0026thinsp;\u0026ge;\u0026thinsp;50%: High expressers, who have been shown in multiple immunotherapy studies to respond well to immune checkpoint inhibitors; 2. 1% \u0026le; PD-L1\u0026thinsp;\u0026le;\u0026thinsp;49%: Intermediate expressers, with clinical outcomes exhibiting some heterogeneity; 3. PD-L1\u0026thinsp;\u0026lt;\u0026thinsp;1%: Low or negative expressers, traditionally considered less responsive to immunotherapy; 4. PD-L1\u0026thinsp;\u0026ge;\u0026thinsp;1%: A combined group of intermediate and high expressers, included for broader comparison with the PD-L1\u0026thinsp;\u0026lt;\u0026thinsp;1% group.\u003c/p\u003e\u003cp\u003eMedian PFS and OS parameters for each subgroup were derived from the publicly available 4-year follow-up data of the GEMSTONE-302 study. Based on these inputs, separate Markov models were constructed for each subgroup to evaluate the ICERs of sugemalimab plus platinum-based chemotherapy versus the control group under different PD-L1 expression levels.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e\u003ch2\u003e2.6 Statistical Analysis\u003c/h2\u003e\u003cdiv id=\"Sec9\" class=\"Section3\"\u003e\u003ch2\u003e2.6.1 Base-case ICERs\u003c/h2\u003e\u003cp\u003eCost-effectiveness analysis was performed using R software(version 4.5.0) as the primary analytical tool. The WTP threshold was set at three times the per capita GDP of China in 2024, equating to 40,062.34\u003cspan\u003e$\u003c/span\u003e/QALY\u003csup\u003e[\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]\u003c/sup\u003e. The cost-effectiveness of each treatment strategy was determined by comparing its ICER against the predefined WTP threshold. An ICER below this threshold was considered cost-effective.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec10\" class=\"Section3\"\u003e\u003ch2\u003e2.6.2 Sensitivity analysis\u003c/h2\u003e\u003cp\u003eTo assess the impact of parameter uncertainty on model outcomes, both one-way sensitivity analysis and probabilistic sensitivity analysis were conducted. In the one-way sensitivity analysis, input parameters were varied within their reported 95% confidence intervals. For parameters lacking explicit ranges, a\u0026thinsp;\u0026plusmn;\u0026thinsp;20% variation from the base value was applied. The discount rate was explored within a range of 0% to 8%. Results were visualized using tornado diagrams to identify key drivers of ICER variation.\u003c/p\u003e\u003cp\u003eIn the probabilistic sensitivity analysis, Monte Carlo simulation was performed with 5,000 iterations based on the predefined probability distributions for model parameters. The results were presented using cost-effectiveness scatter plots and cost-effectiveness acceptability curves to reflect the overall uncertainty and the probability of cost-effectiveness at different WTP thresholds.\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e"},{"header":"3. Results","content":"\u003cdiv id=\"Sec12\" class=\"Section2\"\u003e\u003ch2\u003e3.1 Base-case ICERs\u003c/h2\u003e\u003cp\u003eIn the squamous NSCLC patient group, the sugemalimab plus platinum-based chemotherapy regimen yielded 2.31 QALYs with a total treatment cost of \u003cspan\u003e$\u003c/span\u003e88,585.1. In comparison, the control group achieved 1.26 QALYs at a total cost of \u003cspan\u003e$\u003c/span\u003e19,666.5. This represents an incremental gain of 1.05 QALYs and an additional cost of \u003cspan\u003e$\u003c/span\u003e68,918.6 for the sugemalimab regimen, resulting in an ICER of \u003cspan\u003e$\u003c/span\u003e65,766.82 per QALY.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eAnalysis results for the squamous NSCLC group\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"3\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eSugemalimab\u0026thinsp;+\u0026thinsp;chemotherapy\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003ePlacebo\u0026thinsp;+\u0026thinsp;chemotherapy\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTotal cost(\u003cspan\u003e$\u003c/span\u003e)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e88,585.1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e19,666.5\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eQALYs\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e2.31\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1.26\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eIncremental cost(\u003cspan\u003e$\u003c/span\u003e)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u003cp\u003e68,918.6\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eIncremental utility(QALYs)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u003cp\u003e1.05\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eICER(\u003cspan\u003e$\u003c/span\u003e/QALY)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u003cp\u003e65,766.82\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eIn the non-squamous NSCLC patient group, the sugemalimab plus platinum-based chemotherapy regimen yielded 2.67 QALYs with a total treatment cost of \u003cspan\u003e$\u003c/span\u003e98,553.7. In contrast, the control group achieved 1.64 QALYs at a total cost of \u003cspan\u003e$\u003c/span\u003e26,159.4. Compared with the control group, the sugemalimab regimen resulted in an incremental gain of 1.03 QALYs and an additional cost of \u003cspan\u003e$\u003c/span\u003e72,394.3, leading to an ICER of \u003cspan\u003e$\u003c/span\u003e70,117.72 per QALY.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eAnalysis results for the NSCLC group\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"3\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eSugemalimab\u0026thinsp;+\u0026thinsp;chemotherapy\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003ePlacebo\u0026thinsp;+\u0026thinsp;chemotherapy\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTotal cost(\u003cspan\u003e$\u003c/span\u003e)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e98,553.7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e26,159.4\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eQALYs\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e2.67\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1.64\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eIncremental cost(\u003cspan\u003e$\u003c/span\u003e)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u003cp\u003e72,394.3\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eIncremental utility(QALYs)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u003cp\u003e1.03\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eICER(\u003cspan\u003e$\u003c/span\u003e/QALY)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u003cp\u003e70,117.72\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec13\" class=\"Section2\"\u003e\u003ch2\u003e3.2 Subgroup Scenario Analysis\u003c/h2\u003e\u003cp\u003eThe results of the subgroup cost-effectiveness analysis based on PD-L1 expression levels are as follows: for patients with PD-L1 expression\u0026thinsp;\u0026ge;\u0026thinsp;50%, the ICER was \u003cspan\u003e$\u003c/span\u003e60,516.14 per QALY. For those with PD-L1 expression between 1% and 49%, the ICER was \u003cspan\u003e$\u003c/span\u003e79,564.19 per QALY. In the subgroup with PD-L1 expression\u0026thinsp;\u0026lt;\u0026thinsp;1%, the ICER reached \u003cspan\u003e$\u003c/span\u003e80,599.12 per QALY. For patients with PD-L1 expression\u0026thinsp;\u0026ge;\u0026thinsp;1%, the ICER was \u003cspan\u003e$\u003c/span\u003e67,961.85 per QALY.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eResults of subgroup scenario analysis\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"7\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePopulation\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eTreatment\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eCost (\u003cspan\u003e$\u003c/span\u003e)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eQALYs\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eIncremental cost\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003eIncremental QALYs\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c7\"\u003e\u003cp\u003eICER\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003ePD-L1\u0026thinsp;\u0026ge;\u0026thinsp;50%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eSC\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e112,506.8\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e3.31\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e85,776.6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e1.42\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e60,516.14\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003ePC\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e26,730,2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1.89\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e1%\u0026le;PD-L1\u0026thinsp;\u0026le;\u0026thinsp;49%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eSC\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e88,608.8\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e2.34\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e66,324.0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e0.84\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e79,564.19\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003ePC\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e22,284.8\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1.50\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003ePD-L1\u0026thinsp;\u0026lt;\u0026thinsp;1%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eSC\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e78,432.5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1.97\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e59,226.2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e0.74\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e80,599.12\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003ePC\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e19,206.3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1.23\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003ePD-L1\u0026thinsp;\u0026ge;\u0026thinsp;1%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eSC\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e101,933.1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e2.85\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e77,220.1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e1.14\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e67,961.85\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003ePC\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e24,713.0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1.71\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec14\" class=\"Section2\"\u003e\u003ch2\u003e3.3 Sensitivity analysis\u003c/h2\u003e\u003cdiv id=\"Sec15\" class=\"Section3\"\u003e\u003ch2\u003e3.3.1 Sensitivity Analysis for Squamous NSCLC\u003c/h2\u003e\u003cp\u003eThe one-way sensitivity analysis(Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e2\u003c/span\u003eA) showed that the model was most sensitive to the drug cost of sugemalimab, which had the greatest impact on ICER when varied. Other influential parameters included the utility values during the PFS and PD phases, as well as the discount rate. These findings highlight the critical role of drug pricing and patient quality-of-life assessments in determining the economic viability of the treatment.\u003c/p\u003e\u003cp\u003eThe probabilistic sensitivity analysis based on 5,000 Monte Carlo simulations(Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e3\u003c/span\u003eA) demonstrated that most simulated ICER values were distributed above the WTP threshold, suggesting that the sugemalimab regimen is unlikely to be cost-effective for patients with squamous NSCLC under current parameter settings. The cost-effectiveness acceptability curve(Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e4\u003c/span\u003eA) indicated that the probability of the regimen being cost-effective at the current WTP threshold was approximately 0.12%. Although this probability increases with higher WTP thresholds, it remains low within the range of realistic payer capacities.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec16\" class=\"Section3\"\u003e\u003ch2\u003e3.3.2 Sensitivity Analysis for Non-squamous NSCLC\u003c/h2\u003e\u003cp\u003eAs shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e2\u003c/span\u003eB, for non-squamous NSCLC patients, the cost of sugemalimab remained the most influential factor affecting ICER variability. This was followed by utility values in the PFS and PD health states, the discount rate, and best supportive care costs\u0026mdash;all of which had a significant impact on ICER results. These findings suggest that the cost-effectiveness of this treatment strategy is highly dependent on drug pricing and improvements in patients\u0026rsquo; quality of life.\u003c/p\u003e\u003cp\u003eThe cost-effectiveness scatter plot(Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e3\u003c/span\u003eB) indicates that the vast majority of simulation points lie above the WTP threshold, suggesting that the treatment is not cost-effective in the non-squamous population. The cost-effectiveness acceptability curve(Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e4\u003c/span\u003eB) shows that, at the current WTP threshold, the probability of this regimen being cost-effective is approximately 0.26%..\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e"},{"header":"4. Discussion","content":"\u003cp\u003eThis study constructed a Markov model based on the latest 4-year follow-up results from the GEMSTONE-302 trial to evaluate the long-term cost-effectiveness of sugemalimab plus platinum-based chemotherapy as a first-line treatment for metastatic NSCLC from the perspective of China\u0026rsquo;s healthcare system. Compared with earlier studies that relied on mid-term follow-up data, the use of long-term survival data in this analysis provides more comprehensive and accurate simulations of survival duration and health state transitions, thereby greatly improving the real-world relevance and reliability of the economic evaluation.\u003c/p\u003e\u003cp\u003eA key finding is the significant reduction in ICER results after incorporating the 4-year follow-up data. In previous research based on median survival modeling, the estimated ICER was 109,480.97\u003cspan\u003e$\u003c/span\u003e/QALY\u0026mdash;far exceeding the WTP threshold in China\u003csup\u003e[\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]\u003c/sup\u003e. In contrast, this study found that the ICER decreased to 65,766.82\u003cspan\u003e$\u003c/span\u003e/QALY in squamous NSCLC patients and 70,117.72\u003cspan\u003e$\u003c/span\u003e/QALY in non-squamous patients, indicating a trend toward improved cost-effectiveness with long-term observation. This change is largely attributable to the sustained survival benefits observed in the GEMSTONE-302 four-year data: the median overall survival in the combination group was extended by nearly 8 months compared to placebo, and the 4-year overall survival rate was almost doubled. Notably, several patients remained on treatment for more than two years, with the longest duration reaching 52 months\u0026mdash;demonstrating strong long-term disease control. These extended clinical benefits translated into a greater gain in QALYs than earlier models predicted, effectively diluting the long-term treatment costs.\u003c/p\u003e\u003cp\u003eCompared with other PD-L1 inhibitors such as atezolizumab and durvalumab, which failed to demonstrate significant improvements in OS when combined with chemotherapy in the IMpower and CASPIAN trials, sugemalimab in the GEMSTONE-302 study exhibited more consistent and broad long-term efficacy. This was particularly evident in patients with low PD-L1 expression and those with brain metastases, where sugemalimab showed breakthrough survival advantages\u003csup\u003e[\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e, \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]\u003c/sup\u003e. Moreover, compared with dual immunotherapy regimens combining PD-(L)1 and CTLA-4 inhibitors\u0026mdash;which may offer some long-term survival benefits\u0026mdash;sugemalimab demonstrates superior safety. The incidence of grade\u0026thinsp;\u0026ge;\u0026thinsp;3 immune-related adverse events remains below 5%, reducing the likelihood of severe toxicities while maintaining efficacy. This favorable safety profile contributes to a higher cost-effectiveness potential in health economic evaluations\u003csup\u003e[\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]\u003c/sup\u003e. Although the current ICER results exceed the WTP threshold, sugemalimab-based therapy still demonstrates substantial clinical value in select high-benefit populations. Policymakers are therefore encouraged to consider the following strategies: prioritize inclusion of patients with PD-L1 expression\u0026thinsp;\u0026ge;\u0026thinsp;50% in reimbursement coverage to improve resource allocation efficiency; negotiate drug pricing to enhance affordability; and promote precise patient selection to increase the economic efficiency of treatment.\u003c/p\u003e\u003cp\u003eThis study has several limitations. First, the survival data were derived from a clinical trial setting, and although 4-year follow-up information was used, long-term outcomes may still differ from real-world results. Second, certain model inputs were based on literature-derived estimates, which may introduce potential bias. Additionally, indirect costs and a societal perspective were not incorporated, nor were the long-term costs of post-progression crossover therapies modeled. Future research should validate these modeling outcomes using real-world evidence, explore more representative patient populations in economic assessments, and strengthen simulation analyses of alternative reimbursement schemes to provide evidence-based support for a multi-tiered health insurance system.\u003c/p\u003e"},{"header":"5. Conclusion","content":"\u003cp\u003eThis study demonstrates that, at current pricing levels, sugemalimab combined with platinum-based chemotherapy as a first-line treatment for metastatic NSCLC is not cost-effective in China, particularly among patients with low PD-L1 expression. Although the regimen shows clear survival benefits and a favorable safety profile, its economic viability remains limited. Precision treatment targeting patients with high PD-L1 expression, along with drug price optimization, may help improve the cost-effectiveness and accessibility of this regimen within China\u0026rsquo;s healthcare system.\u003c/p\u003e"},{"header":"Declarations","content":"\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eZZ: Writing-original draft. KM: Writing-original draft. MW: Writing-original draft. AL: Writing-original draft. YY.Writing-original draft. CS.Writing-original draft.XW.Writing-original draft. CT: Writing-review and editing. YW: Writing-review and editing.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eBRAY F, LAVERSANNE M (2024) Global cancer statistics 2022: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries [J]. CA Cancer J Clin 74(3):229\u0026ndash;263\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eARBOUR K C (2019) RIELY G J. Systemic Therapy for Locally Advanced and Metastatic Non-Small Cell Lung Cancer: A Review [J]. JAMA 322(8):764\u0026ndash;774\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003ePAZ-ARES L, DVORKIN M, CHEN Y et al (2019) Durvalumab plus platinum-etoposide versus platinum-etoposide in first-line treatment of extensive-stage small-cell lung cancer (CASPIAN): a randomised, controlled, open-label, phase 3 trial [J]. Lancet 394(10212):1929\u0026ndash;1939\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eCHENG Y, HAN L, WU L et al (2022) Effect of First-Line Serplulimab vs Placebo Added to Chemotherapy on Survival in Patients With Extensive-Stage Small Cell Lung Cancer: The ASTRUM-005 Randomized Clinical Trial [J]. JAMA 328(12):1223\u0026ndash;1232\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eWANG J, ZHOU C, YAO W et al (2022) Adebrelimab or placebo plus carboplatin and etoposide as first-line treatment for extensive-stage small-cell lung cancer (CAPSTONE-1): a multicentre, randomised, double-blind, placebo-controlled, phase 3 trial [J]. Lancet Oncol 23(6):739\u0026ndash;747\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eRUDIN C M, AWAD M M, NAVARRO A et al (2020) Pembrolizumab or Placebo Plus Etoposide and Platinum as First-Line Therapy for Extensive-Stage Small-Cell Lung Cancer: Randomized, Double-Blind, Phase III KEYNOTE-604 Study [J]. J Clin Oncol 38(21):2369\u0026ndash;2379\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eZHOU C, WANG Z, SUN Y et al (2022) Sugemalimab versus placebo, in combination with platinum-based chemotherapy, as first-line treatment of metastatic non-small-cell lung cancer (GEMSTONE-302): interim and final analyses of a double-blind, randomised, phase 3 clinical trial [J]. Lancet Oncol 23(2):220\u0026ndash;233\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eZHOU C, WANG Z (2025) Sugemalimab versus placebo, in combination with platinum-based chemotherapy, as first-line treatment of metastatic non-small-cell lung cancer (GEMSTONE-302): 4-year outcomes from a double-blind, randomised, phase 3 trial [J]. Lancet Oncol 26(7):887\u0026ndash;897\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eCHEN S, WANG Z (2025) Chinese Society of Clinical Oncology Non-small Cell Lung Cancer (CSCO NSCLC) guidelines in 2024: key update on the management of early and locally advanced NSCLC [J]. Cancer Biol Med 22(3):191\u0026ndash;196\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eOffice of the Leading Group of the State Councilfor the Seventh National Population Census (2023) China population census yearbook 2020. China Statistics, Beijing\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eKangzhou Big Data (2023) DRUGDATAEXPY. Available at: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.yaozh.com/\u003c/span\u003e\u003cspan address=\"https://www.yaozh.com/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (Accessed July 28, 2025)\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eLI W (2022) Cost-effectiveness analysis of sugemalimab vs. placebo, in combination with chemotherapy, for treatment of first-line metastatic NSCLC in China [J]. Front Public Health 10:1015702\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eLiu GHS, Wu J, Wu J, Dong Z, Li H (2020) China guidelines for pharmacoeconomic evaluations(2020). China Market, Beijing\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eKANG S, WANG X, ZHANG Y et al (2021) First-Line Treatments for Extensive-Stage Small-Cell Lung Cancer With Immune Checkpoint Inhibitors Plus Chemotherapy: A Network Meta-Analysis and Cost-Effectiveness Analysis [J]. Front Oncol 11:740091\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eZHOU QIAOL, ZENG Z (2021) Cost-Effectiveness of Domestic PD-1 Inhibitor Camrelizumab Combined With Chemotherapy in the First-Line Treatment of Advanced Nonsquamous Non-Small-Cell Lung Cancer in China [J]. Front Pharmacol 12:728440\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eNational Bureau of Statistics of China (2025) Statistical Bulletin of the People\u0026rsquo;s Republic of China on the 2024 National Economic and Social Development. Available at: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.stats.gov.cn/sj/zxfb/202502/t20250228_1958817.html\u003c/span\u003e\u003cspan address=\"https://www.stats.gov.cn/sj/zxfb/202502/t20250228_1958817.html\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (Accessed July 28, 2025)\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eWEST H, MCCLEOD M, HUSSEIN M et al (2019) Atezolizumab in combination with carboplatin plus nab-paclitaxel chemotherapy compared with chemotherapy alone as first-line treatment for metastatic non-squamous non-small-cell lung cancer (IMpower130): a multicentre, randomised, open-label, phase 3 trial [J]. Lancet Oncol 20(7):924\u0026ndash;937\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003ePAZ-ARES L, CIULEANU T E, COBO M et al (2021) 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 [J]. Lancet Oncol 22(2):198\u0026ndash;211\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Sugemalimab, Non-small cell lung cancer, Immunotherapy, Cost-effectiveness analysis, Markov model","lastPublishedDoi":"10.21203/rs.3.rs-7953546/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7953546/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eObjective\u003c/h2\u003e\u003cp\u003eTo assess the cost-effectiveness of sugemalimab plus chemotherapy as first-line treatment for metastatic Non-small cell lung cancer(NSCLC) in China.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e\u003cp\u003eA three-state Markov model with 21-day cycles over 10 years was developed to compare sugemalimab plus chemotherapy versus placebo plus chemotherapy. Key model inputs were derived from the 4-year survival data of the GEMSTONE-302 trial and publicly available sources. Outcomes were measured in quality-adjusted life years(QALYs) and incremental cost-effectiveness ratios(ICERs). The willingness-to-pay(WTP) threshold was set at three times the per capita GDP of China in 2024(40,062.34\u003cspan\u003e$\u003c/span\u003e/QALY). Sensitivity analyses were performed to assess model robustness.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e\u003cp\u003eBase-case ICERs were 65,766.82\u003cspan\u003e$\u003c/span\u003e/QALY for squamous and 70,117.72\u003cspan\u003e$\u003c/span\u003e/QALY for non-squamous NSCLC, both above the WTP threshold. Subgroup analyses indicated that patients with PD-L1 expression\u0026thinsp;\u0026ge;\u0026thinsp;50% had the most favorable ICER(60,516.14\u003cspan\u003e$\u003c/span\u003e/QALY), while those with PD-L1\u0026thinsp;\u0026lt;\u0026thinsp;1% had the least favorable outcome(80,599.12\u003cspan\u003e$\u003c/span\u003e/QALY). Sensitivity analyses identified drug price and utility values as the most influential parameters affecting ICERs.\u003c/p\u003e\u003ch2\u003eConclusion\u003c/h2\u003e\u003cp\u003eSugemalimab plus platinum-based chemotherapy offers long-term clinical benefits for metastatic NSCLC but is not cost-effective at current prices in China. Improving cost-effectiveness may require targeting patients with high PD-L1 expression, adjusting reimbursement policies, and reducing drug prices.\u003c/p\u003e","manuscriptTitle":"First-line treatments for metastatic non-small-cell lung cancer with Sugemalimab plus chemotherapy: a China-based cost-effectiveness analysis","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-11-10 16:12:58","doi":"10.21203/rs.3.rs-7953546/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"0e3d5332-f99f-4a50-a0a3-2b796b7c122f","owner":[],"postedDate":"November 10th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2026-01-26T10:56:34+00:00","versionOfRecord":[],"versionCreatedAt":"2025-11-10 16:12:58","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-7953546","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7953546","identity":"rs-7953546","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}