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. 2026 Aug 21;22(1):2720165. doi: 10.1080/21645515.2026.2720165

Cost‑effectiveness of first‑line immunotherapy-based combination regimens for advanced renal cell carcinoma in China and the United States

Chunyan Yan a,*, Zhengxiong Li b,*, Quan Zhao a,*, Yuan Gao a, Jiayan Li a, Ruigang Diao a,✉
PMCID: PMC13502016  PMID: 42630013

ABSTRACT

Immunotherapy‑based combination regimens provide significant clinical benefits but impose substantial economic burdens on national healthcare systems. This study assessed the cost-effectiveness of immunotherapy‑based combination regimens as first-line treatments for advanced renal cell carcinoma (aRCC) in China and the United States (US). A partitioned survival model was developed to evaluate the cost-effectiveness of all approved regimens with a lifetime horizon. The primary outcomes were total costs, quality-adjusted life-years (QALYs), and incremental cost-effectiveness ratios (ICERs). Sensitivity analyses were performed to evaluate model uncertainty. Compared to the sunitinib regimen, the ICERs for the toripalimab plus axitinib (T + A), nivolumab plus ipilimumab (N + I), lenvatinib plus pembrolizumab (L + P), pembrolizumab plus axitinib (P + A), nivolumab plus cabozantinib (N + C), avelumab plus axitinib (A + A) and atezolizumab plus bevacizumab (A + B) regimens in China were $64,536.98/QALY, $135,593.25/QALY, $174,956.58/QALY, $231,908.95/QALY, $728,876.75/QALY, $1,232,070.43/QALY, and $2,496,799.42/QALY, respectively. The ICERs for the N + I, T + A, N + C, P + A, L + P, A + A, and A + B regimens in the US were $160,243.50/QALY, $468,156.65/QALY, $804,963.69/QALY, $907,549.79/QALY, $2,170,769.66/QALY, $2,623,809.39/QALY, and $12,712,147.95/QALY, respectively. Probabilistic sensitivity analyses indicated that the probability of cost-effectiveness corresponding to N + I vs. sunitinib was 33.6% in the US. In China and the US, none of the seven first-line immunotherapy-based combination regimens was cost-effective compared with sunitinib for aRCC.

KEYWORDS: Cost-effectiveness, immunotherapy-based combination regimens, sunitinib, advanced renal cell carcinoma

Introduction

Renal cell carcinoma (RCC), a malignant tumor of the urinary tract originating from the renal tubular epithelium, accounts for approximately 80–90% of renal malignancies.1 It ranks as the sixth most common cancer in men and the eighth in women.2 In recent years, its incidence has increased at an annual rate of 1.6%, and poor prognosis is more prevalent in males.3 Although localized RCC can be managed with surgical resection to achieve long-term survival, approximately 30% of patients present with distant metastases at initial diagnosis. Furthermore, up to 40% of patients with localized disease experience recurrence or metastasis after surgery, eventually progressing to advanced renal cell carcinoma (aRCC).4 The prognosis for aRCC remains poor, with a five-year survival rate below 20%. Moreover, aRCC demonstrates limited sensitivity to conventional chemotherapy and radiotherapy, historically imposing significant constraints on treatment options.5

With the continuous advancement in research on the molecular biological mechanisms of RCC, the emergence of targeted therapy and immunotherapy has significantly transformed the treatment landscape for aRCC. Historically, targeted drugs (such as sunitinib, sorafenib, and axitinib), which inhibit the VEGF and mTOR pathways, were established as standard first-line treatments for aRCC, significantly prolonging progression-free survival (PFS) and overall survival (OS).6 However, targeted therapies face efficacy limitations, with patients eventually developing acquired resistance. Additionally, adverse reactions such as hypertension, hand-foot syndrome, and fatigue occur frequently, impacting patients’ quality of life.7 In recent years, the advent of immune checkpoint inhibitors (ICIs) has brought new breakthroughs to aRCC treatment. ICIs activate the body’s immune system to recognize and eliminate tumor cells by blocking the programmed death receptor-1 (PD-1) and its ligand (PD-L1) or the cytotoxic T-lymphocyte-associated protein 4 (CTLA-4) pathway, significantly improving objective response rates (ORR) and long-term survival.8 However, the efficacy of monotherapy with ICIs remains limited in certain subgroups (e.g., IMDC low-risk patients), and the complex management of immune-related adverse events (irAEs) restricts their widespread application.

In this context, combination strategies of targeted therapy and immunotherapy (referred to as “targeted-immunotherapy combinations”) have progressively emerged as a research focus for first-line treatment of aRCC. Multiple Phase III randomized controlled trials (RCTs) have demonstrated9–13 that tyrosine kinase inhibitor-immunotherapy combination (TKI + IO) regimens (e.g., pembrolizumab plus axitinib, nivolumab plus cabozantinib) are significantly superior to conventional targeted therapy in intermediate to high-risk aRCC patients according to the International Metastatic RCC Database Consortium (IMDC) criteria. These combinations markedly prolong PFS and OS, improve ORR, and have been established as the standard first-line treatment recommended by authoritative guidelines worldwide.

Despite multiple treatment options currently available, the optimal first-line treatment strategy for aRCC remains undetermined. Furthermore, although TKI+IO regimens provide significant clinical benefits, they impose substantial economic burdens on both individual patients and national healthcare systems. Given the large potential beneficiary population and the possible negative economic consequences, evaluating the cost‑effectiveness of these treatment regimens among patients with advanced RCC is crucial for determining their suitability for widespread clinical adoption. Accordingly, this study comprehensively assessed the cost‑effectiveness of all available immunotherapy‑based combination regimens as first‑line treatments for aRCC in China and the United States (US). This study aimed to inform evidence‑based decision‑making for relevant healthcare institutions and to optimize the allocation and utilization of immunotherapy resources.

Material and methods

This study was conducted in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA)14 and the Consolidated Health Economic Evaluation Reporting Standards 2022 (CHEERS 2022) guideline (Supplement Table 1),15 respectively. As this study comprised systematic reviews and modeling analyses without primary patient data, institutional review board approval was deemed unnecessary.

Systematic reviews

Study strategy

Before the formal literature retrieval, we reviewed the management strategies for RCC recommended by the National Comprehensive Cancer Network (NCCN) guidelines and Chinese Society of Clinical Oncology (CSCO) guidelines to identify the immunotherapy‑based combination regimens. We searched for Phase III randomized controlled trials (RCTs) on immunotherapy‑based combination regimens in first-line treatment for aRCC published before April 28, 2025, in the PubMed, Web of Science, Cochrane Library, Scopus, and Embase databases. Search terms included “immune checkpoint inhibitors,” “Immunotherapy,” “PD-1 inhibitor,” “PD-L1 inhibitor,” “pembrolizumab,” “nivolumab,” “avelumab,” “ipilimumab,” “atezolizumab,” “toripalimab,” “renal,” “kidney,” “carcinoma” and “randomized controlled trial.” The detailed search strategy is represented in Supplement Table 2. This study was registered on the PROSPERO website (ID: CRD420251050081). The screening process is described in Supplement Figure 1.

Selection criteria

The studies should meet the following inclusion criteria1: Patients were aged ≥18 with unresectable advanced or metastatic RCC who have not previously received treatment2; whose tumors contain clear cell components, and who have at least one measurable lesion; and3 RCTs that reported PFS, OS and treatment-related adverse events (AEs). Exclusion criteria were as follows1: Research on insufficient information and inability to extract available data2; Abstract, letter, case report, review or meta-analysis3; and multiple publications on the same clinical study.

Data extraction and quality assessment

Two reviewers (JYL and YG) independently removed duplicates, screened literature, extracted data, and assessed methodological quality. The primary characteristics of each trial were shown in Supplement Table 3, which included details such as study names, treatment regimens, and other pertinent information. The risk of bias was evaluated with the Cochrane Collaboration’s risk of bias assessment tool and classified as low risk, some concerns, or high risk.

Statistical analysis

Individual-level time-to-event data were reconstructed from digitized Kaplan–Meier curves and numbers at risk.16 The proportional-hazards (PH) assumption was assessed using trial-stratified Schoenfeld-residual tests, within each trial and across the network. Because non-proportionality was detected for both OS and PFS (Supplement Figure 2), time-varying relative treatment effects vs. sunitinib were estimated using a consistency network meta-analysis with fractional-polynomial (FP) time functions17,18 (Supplement Figure 3). A first-order FP was pre-specified for the base case, and the power was selected by AIC using observed-period data. Absolute survival for sunitinib was estimated from pooled control-arm data using restricted cubic-spline parametric survival models (Supplement Tables 4–5) and was combined with the time-varying relative effects to generate treatment-specific curves (Supplement Figures 4–5). Treatment effects after a common 24-month anchor were maintained in the base case, with alternative anchor times and waning or stopping assumptions explored in sensitivity analyses.

Cost-effectiveness analysis

Model structure

A partitioned survival model (PSM) was used to simulate patient-level data to compare the cost-effectiveness of different combination regimens as first-line treatment for aRCC from the perspectives of the US and China. This model was constructed using TreeAge Pro 2019 (TreeAge Software, MA, USA; https://www.treeage.com) which included three mutually independent health states: PFS, progressive disease (PD), and death19 (Supplement Figure 6). All individuals were initially assumed to be in the PFS state and were at the risk of PD or death. This intuitive structure facilitates its understanding and verification, meeting the transparency standards for models set by health technology assessment agencies. The cycle length was set at three weeks, and the time horizon was set at lifetimes. The primary outputs focused on total costs, quality-adjusted life-years (QALYs), net monetary benefits (NMBs), incremental net monetary benefits (INMBs) and incremental cost-effectiveness ratios (ICERs). All costs and utilities were discounted by 3.0% for the US20 and 4.5% for China annually.21 The willingness-to-pay (WTP) thresholds in this study were set at $150,000/QALY and two times gross domestic product (GDP) per capita in 2024 ($26,889/QALY) for the US22 and China,21,23 respectively.

Cost and utility inputs

Our study considers only direct healthcare costs in China and the US, covering first-line and subsequent therapy, drug administration, treating serious adverse events (SAEs), best supportive care (BSC), laboratory tests, routine monitoring, and end-stage care. Drug costs in China were derived from the average of the 2024 bid-winning prices in the Yaozhi database (https://data.yaozh.com/),24 while those in the United States were obtained from Red Book Online25 using the average wholesale cost and from the Centers for Medicare & Medicaid Services’ (CMS) Average Sale Price Drug Pricing file.26 Since cabozantinib and avelumab are not currently available in mainland China, Hong Kong pricing was used in this study.27 To calculate the dosages of nivolumab, ipilimumab, avelumab and bevacizumab, we made an assumption regarding patient weight: 65 kg28 for patients in China and 70 kg29 for those in the US. All costs other than drug costs were derived from published literatures.28–37 To simplify the model, this study considered only SAEs of grade ≥ 3 with an incidence rate exceeding 5%. The incidence of SAEs for sunitinib, the reference drug, was derived from the CheckMate 214 trial due to its longest available follow-up period. All these costs were reported in 2024 US dollars at a conversion rate of $1 = ¥7.1217.38

Health utility values for PFS and PD were derived from published studies,39 as these were not reported in the included clinical trials. Utility values were assigned as follows: 0.78 for PFS, 0.70 for PD, and 0 for death. Additionally, disutility values for SAEs were sourced from published studies.40 All cost and utility model parameters are provided in Tables 1 and 2.

Table 1.

Cost parameters and the range of the sensitivity analysis.

Parameters China value (range) United States value (range) Distribution References
Cost of drugs per 1 mg, $  
Nivolumab 12.99 (10.39–15.59) 33.00 (26.40–39.60) Gamma 24,26
Ipilimumab 50.55 (40.44–60.66) 183.41 (146.73–220.09) Gamma 24,26
Cabozantinib 17.37 (13.90–20.84) 21.36 (17.09–25.63) Gamma 25,27
Avelumab 8.27 (6.62–9.92) 10.03 (8.02–12.04) Gamma 25,27
Axitinib 5.52 (4.42–6.63) 68.75 (55.00–82.50) Gamma 24,26
Atezolizumab 3.84 (3.07–4.61) 18.2 (14.56–21.84) Gamma 24,26
Bevacizumab 29.59 (23.67–35.51) 7.30 (5.84–8.76) Gamma 24,26
Lenvatinib 1.21 (0.97–1.45) 81.17 (64.94–97.40) Gamma 24,26
Pembrolizumab 25.16 (20.13–30.19) 58.56 (46.85–70.27) Gamma 24,26
Toripalimab 1.10 (0.88–1.32) 39.50 (31.60–47.40) Gamma 24,26
Sunitinib 0.20 (0.16–0.25) 8.49 (6.79–10.19) Gamma 24,26
Cost of AEs per cycle, $  
Alanine aminotransferase increased 23.84 (19.07–28.61) 9,036.95 (7,229.56 - 10,844.3) Gamma 32,34
Anaemia 467.73 (374.18–561.28) 82.19 (65.75–98.63) Gamma 29,32
Aspartate aminotransferase increased 23.84 (19.07–28.61) 9,036.95 (7,229.56 - 10,844.34) Gamma 32,34
Blood triglycerides increased 8.41 (6.73–10.10) 14,824.43 (11,859.54 - 17,789.32) Gamma 30,34
Diarrhoea 41.05 (32.84–49.26) 9,376.32 (7,501.06–11251.58) Gamma 32,35
Fatigue 106.96 (85.57–128.35) 9,670.85 (7,736.68 - 11,605.02) Gamma 30,35
Hepatic function abnormal 23.84 (19.07–28.61) 9,036.95 (7,229.56 - 10,844.34) Gamma 32,35
Hypertension 11.28 (9.03–13.54) 8,512.14 (6,809.71 - 10,214.57) Gamma 28,35
Lipase increased 44.85 (35.88–53.83) 8,060.05 (6,448.04–9,672.06) Gamma 33,34
Neutropenia 405.95 (324.76–487.14) 41,798.2 (33,438.56 - 50,157.84) Gamma 29,32
Neutrophil count decreased 405.95 (324.76–487.14) 41,798.2 (33,438.56 - 50,157.84) Gamma 29,32
Palmar–plantar erythrodysaesthesia 91.97 (73.57–110.36) 8,673.34 (6,938.67 - 10,408.01) Gamma 28,34
Palmoplantar erythema 14.82 (11.85–17.78) 8,673.34 (6,938.67 - 10,408.01) Gamma 34,37
Platelet count decreased 3,124.74 (2,499.79–3,749.69) 11,239.65 (8,991.72 - 13,487.58) Gamma 29,32
Proteinuria 115.38 (92.30–138.46) 9,526.61 (7,621.29 - 11,431.93) Gamma 32,35
Thrombocytopenia 3,124.74 (2,499.79–3,749.69) 11,239.65 (8,991.72 - 13,487.58) Gamma 29,32
Weight decrease 0.00 (NA) 8,611.78 (6,889.42 - 10,334.14) Gamma 29,32
White blood cell count decreased 440.08 (352.07–528.10) 10,474.43 (8,379.54 - 12,569.32) Gamma 32,34
Other costs per cycle, $  
Best supportive care 298.89 (239.11–358.67) 3,803.37 (3,042.70–4,564.04) Gamma 32,34
Laboratory tests and radiological examinations 532.62 (426.10–639.15) 392.64 (314.11–471.17) Gamma 31,36
Cost of drug administration 41.75 (33.40–50.10) 166.70 (133.36–200.04) Gamma 28,29
Routine follow-up 65.17 (52.13–78.20) 511.68 (409.34–614.02) Gamma 28,29
Terminal care 1,702.08 (1,361.67–2,042.50) 12,996.97 (10,397.58 - 15,596.36) Gamma 28,29
Other parameters
Discount rate (%) 4.5 (0–5.0) 3.0 (0–5.0) Fixed 20,21
Weight (kg) 6541− 78) 70 (56–84) Gamma 28,29
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Table 2.

Clinical and health utility parameters.

Parameters Value (range) Distribution References
Incidence of SAEs in the Nivolumab + Cabozantinib arm
Diarrhoea 6.0% (4.8% −7.2%) Beta 42
Palmar–plantar erythrodysaesthesia 8.0% (6.4% −9.6%) Beta 42
Hypertension 12.0% (9.6% −14.4%) Beta 42
Lipase increased 7.0% (5.6% −8.4%) Beta 42
Alanine aminotransferase increased 6.0% (4.8% −7.2%) Beta 42
Incidence of SAEs in the Avelumab + Axitinib arm
Hypertension 25.6% (20.5% −30.7%) Beta 43
Diarrhoea 6.7% (5.4% −8.0%) Beta 43
Palmar–plantar erythrodysesthesia syndrome 5.8% (4.6% −6.9%) Beta 43
Alanine aminotransferase increased 6.0% (4.8% −7.2%) Beta 43
Incidence of SAEs in the Atezolizumab + Bevacizumab arm
Hypertension 14.0% (11.2% −16.8%) Beta 44
Incidence of SAEs in the Lenvatinib + Pembrolizumab arm
Diarrhoea 9.7% (7.8% −11.6%) Beta 12
Hypertension 27.6% (22.1% −33.1%) Beta 12
Weight decrease 8.0% (6.4% −9.6%) Beta 12
Proteinuria 7.7% (6.2% −9.2%) Beta 12
Incidence of SAEs in the Toripalimab + Axitinib arm
Proteinuria 11.1% (8.9% −13.3%) Beta 45
Diarrhoea 6.3% (5.0% −7.6%) Beta 45
Hypertension 15.4% (12.3% −18.5%) Beta 45
Hepatic function abnormal 5.3% (4.2% −6.4%) Beta 45
Alanine aminotransferase increased 7.2% (5.8% −8.6%) Beta 45
Hypertriglyceridemia 6.3% (5.0% −7.6%) Beta 45
Incidence of SAEs in the Pembrolizumab + Axitinib arm
Diarrhoea 10.0% (8.0% −12.0%) Beta 11
Hypertension 22.0% (17.6% −26.4%) Beta 11
Palmar–plantar erythrodysesthesia syndrome 5.0% (4.0% −6.0%) Beta 11
Aspartate aminotransferase increased 6.0% (4.8% −7.2%) Beta 11
Alanine aminotransferase increased 13.0% (10.4% −15.6%) Beta 11
Incidence of SAEs in the Sunitinib arm
Fatigue 10.0% (8.0% −12.0%) Beta 46
Diarrhoea 6.0% (4.8% −7.2%) Beta 46
Hypertension 17.0% (13.6% −20.4%) Beta 46
Palmoplantar erythema 9.0% (7.2% −10.8%) Beta 46
Utility estimate
Progression-free disease 0.78 (0.76–0.80) Beta 39
Progressive disease 0.70 (0.66–0.74) Beta 39
Disutility due to grade 3–5 SAEs 0.157 (0.11–0.204) Beta 40
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Abbr. A + A, avelumab + axitinib; A + B, atezolizumab + bevacizumab; L + P, lenvatinib + pembrolizumab; N + C, nivolumab + cabozantinib; N + I, nivolumab + ipilimumab; P + A, pembrolizumab + axitinib; SAEs, serious adverse events; T + A, toripalimab + axitinib.

Simulation of the model

The clinical trials included in this study did not announce the subsequent treatment plan. Cabozantinib or lenvatinib are the two preferred NCCN‑recommended subsequent therapies after first-line immunotherapy combinations for clear cell RCC.47 Therefore, these were the therapies selected for second-line treatment on PD in our study. Treatments could be either cabozantinib alone if treated previously with an ICI, or lenvatinib if treated with cabozantinib in the first line. For patients who received first-line sunitinib monotherapy, second-line therapy was nivolumab, which was given for up to two years or until progression, followed by best supportive care (BSC).

Sensitivity analysis

Sensitivity analyses were conducted to test the robustness of the model. In the deterministic one-way sensitivity analysis (OWSA), the annual discount rate was examined across a range of 0 to 5%. For other parameters, the range of variation was determined by their 95% confidence intervals; when a confidence interval was unavailable, the range was defined as the baseline value ± 20%. A set of tornado diagrams was plotted to depict the analysis results, INMB was used as a measure of economic efficiency. The probabilistic sensitivity analysis (PSA) was then conducted using 1,000 Monte Carlo simulations. In these simulations, parameters were randomly sampled from predefined distributions: costs were assigned a gamma distribution; probabilities, proportions, and utility values were modeled using beta distributions. The results of PSA were presented as scatter plots and cost-effectiveness acceptability curves (CEAC).

Results

Studies included and the risk of bias

After screening, seven clinical trials involving 5,542 patients were included in the final analysis. Patients received one of the following first-line treatment regimens: nivolumab plus ipilimumab (N + I),46 nivolumab plus cabozantinib (N + C),42 avelumab plus axitinib (A + A),43 atezolizumab plus bevacizumab (A + B),44 lenvatinib plus pembrolizumab (L + P),12,48 toripalimab plus axitinib (T + A),45 or pembrolizumab plus axitinib (P + A).11 The risks of bias assessments for the included trials were presented as a traffic-light plot in Supplement Figure 7.

Base-case results

The results of the base-case analysis are shown in Tables 3 and 4. Patients who received the pooled sunitinib group gained 3.21 QALYs and 3.52 QALYs with associated costs of $75,722.88 and $478,390.24 in China and the US, respectively. Compared to the sunitinib regimen, the ICERs for the T + A, N + I, L + P, P + A, N + C, A + A, and A + B regimens in China were $64,536.98/QALY, $135,593.25/QALY, $174,956.58/QALY, $231,908.95/QALY, $728,876.75/QALY, $1,232,070.43/QALY, and $2,496,799.42/QALY, respectively (Table 3). Compared to sunitinib in the US, the ICERs for the N + I, T + A, N + C, P + A, L + P, A + A, and A + B regimens were $160,243.50/QALY, $468,156.65/QALY, $804,963.69/QALY, $907,549.79/QALY, $2,170,769.66/QALY, $2,623,809.39/QALY, and $12,712,147.95/QALY, respectively (Table 4). Based on the NMB value, the cost-effectiveness ranking in China was: sunitinib > T + A > N + I > L + P > P + A > A + B > A + A > N + C. In the US, the ranking was: sunitinib > N + I > T + A > P + A > A + A > N + C > A + B > L + P.

Table 3.

The results of base-case analysis in China.

Strategy Total cost ($) QALYs NMBs ($) ICERs ($/QALY)
Sunitinib T + A L + P N + I P + A A + B A + A
Sunitinib 75,722.88 3.21 10,510.04 / / / / / / /
T + A 181,566.81 4.85 −51,234.57 64,536.98 / / / / / /
L + P 240,824.65 4.15 −129,217.31 174,956.58 Dominated / / / / /
N + I 247,117.79 4.47 −126,896.18 135,593.25 Dominated 19,643.71 / / / /
P + A 258,827.87 4.00 −151,364.59 231,908.95 Dominated Dominated Dominated / / /
A + B 316,317.99 3.30 −227,494.01 2,496,799.42 Dominated Dominated Dominated Dominated / /
A + A 447,541.82 3.51 −353,194.24 1,232,070.43 Dominated Dominated Dominated Dominated 638,799.91 /
N + C 837,542.68 4.25 −723,205.46 728,876.75 Dominated 5,877,595.07 Dominated 2,263,774.81 549,330.87 524,608.49
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Abbr. N + I, nivolumab + ipilimumab; N + C, nivolumab + cabozantinib; A + A, avelumab + axitinib; A + B, atezolizumab + bevacizumab; L + P, lenvatinib + pembrolizumab; T + A, toripalimab + axitinib; P + A, pembrolizumab + axitinib; QALYs, quality-adjusted life years; NMBs, Net monetary benefits; ICERs; incremental cost-effectiveness ratios.

Table 4.

The results of base-case analysis in the United States.

Strategy Total cost ($) QALYs NMBs ($) ICERs ($/QALY)
Sunitinib N + I P + A A + A T + A A + B N + C
Sunitinib 478,390.24 3.52 50,313.51 / / / / / / /
N + I 717,237.11 5.02 35,045.33 160,243.50 / / / / / /
P + A 1,292,993.12 4.42 −629,651.65 907,549.79 Dominated / / / / /
A + A 1,305,616.65 3.84 −729,621.37 2,623,809.39 Dominated Dominated / / / /
T + A 1,393,182.91 5.48 −571,374.49 468,156.65 1,458,330.52 94,836.61 53,434.65 / / /
A + B 1,434,085.25 3.60 −894,104.56 12,712,147.95 Dominated Dominated Dominated Dominated / /
N + C 1,458,542.90 4.74 −747,193.77 804,963.69 Dominated 517,260.48 169,473.85 Dominated 21,407.95 /
L + P 2,798,332.38 4.59 −2,109,320.82 2,170,769.66 Dominated 8,796,264.64 1,981,195.70 Dominated 1,373,118.79 Dominated
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Abbr. A + A, avelumab + axitinib; A + B, atezolizumab + bevacizumab; L + P, lenvatinib + pembrolizumab; N + C, nivolumab + cabozantinib; N + I, nivolumab + ipilimumab; P + A, pembrolizumab + axitinib; T + A, toripalimab + axitinib; QALYs, quality-adjusted life years; NMBs, Net monetary benefits; ICERs; incremental cost-effectiveness ratios.

One-way sensitivity analysis

The top 10 variables significantly influencing the values of INMB were visualized using a tornado diagram. As shown in Supplement Figure 8 and Supplement Figure 9, the INMB values for all seven combination regimens were most sensitive to the variations in drug costs and discount rates in both the Chinese and US analyses. Furthermore, the INMB values of the A + A vs. sunitinib and A + B vs. sunitinib were also sensitive to the weight parameter in China. Nevertheless, variations in these parameters within the specific ranges consistently yielded INMB < 0, further confirming the robustness of the base‑case results.

Probabilistic sensitivity analysis

The incremental cost-effectiveness scatter plot and CEAC are presented in Figures 1 and 2. The results indicated that, at the WTP threshold of $26,889/QALY in China, the probability of the immunotherapy‑based combination regimens being cost-effective compared with sunitinib was 0%. In the US, the N + I regimen had a 33.6% probability of being cost-effective at the WTP threshold of $150,000/QALY, while the probabilities for all other regimens were 0%.

Figure 1.

Scatter plots showing incremental cost and incremental effectiveness for multiple regimens compared with Sun. Image A displays a scatter plot with axes for Incremental Effectiveness (QALYs) ranging from -0.5 to 2.0 and Incremental Cost (x $1,000) from 0 to 1,000. A reference line marks WTP at $26,889/QALY. Seven series are analyzed: Ate+Bev, Ave+Axi, Niv+Ipi, Niv+Cab, Pem+Axi, Tor+Axi, Len+Pem vs. Sun. Clusters are noted at effectiveness 0.0-0.2, cost 200-300; 0.2-0.4, cost 250-520; 0.5-1.5, cost 140-220; 0.8-1.2, cost 600-950; 1.4-2.0, cost 80-130. Image B shows a scatter plot with axes for Incremental Effectiveness (QALYs) from -0.5 to 2.5 and Incremental Cost (x $1,000) from 0 to 3,200. A reference line indicates WTP at $150,000/QALY. The same seven series are compared. Clusters appear at effectiveness 0.0-0.2, cost 650-1,250; 0.2-0.4, cost 600-1,100; 0.6-1.0, cost 550-1,050; 0.9-1.3, cost 800-1,300; 1.6-2.2, cost 650-1,200; 0.6-1.3, cost 1,700-3,000; 1.2-1.7, cost 100-350.

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Scatterplots of the ICERs for immunotherapy‑based combination regimens vs. pooled sunitinib treatment.

Abbr. Ave + Axi, avelumab + axitinib; Ate + Bev, atezolizumab + bevacizumab; Len + Pem, lenvatinib + pembrolizumab; Niv + Cab, nivolumab +cabozantinib; Niv + Ipi, nivolumab +ipilimumab; Pem + Axi, pembrolizumab + axitinib; QALY, quality-adjusted life year; SUN, sunitinib; Tor + Axi, toripalimab + axitinib; WTP, willingness-to-pay.

Figure 2.

A line graph showing cost effectiveness probability versus willingness to pay thresholds in two sub images. Image A: Line graph shows probability of cost-effectiveness (0-100%) vs. willingness to pay (0-160,000 dollars). Key point: WTP = 26,889 dollars/QALY. Legend includes various drug combinations. Notable series: Sunitinib starts at 100% effectiveness, drops to 0% by 96,000 dollars. Tor plus Axi starts at 0%, reaches 100% by 96,000 dollars. Image B: Similar graph with range up to 1,500,000 dollars. WTP = 150,000 dollars/QALY. Vertical line near 150,000. Notable series: Sunitinib starts at 100%, drops to 0% by 150,000 dollars. Niv plus Ipi starts at 0%, peaks at 100% by 150,000, then declines. Tor plus Axi starts at 0%, reaches 100% by 1,200,000 dollars.

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The cost-effectiveness acceptability curves for immunotherapy‑based combination regimens.

Abbr. Ave + Axi, avelumab + axitinib; Ate + Bev, atezolizumab + bevacizumab; Len + Pem, lenvatinib + pembrolizumab; Niv + Cab, nivolumab +cabozantinib; Niv + Ipi, nivolumab +ipilimumab; Pem + Axi, pembrolizumab + axitinib; QALY, quality-adjusted life year; Tor + Axi, toripalimab + axitinib; WTP, willingness-to-pay.

Discussion

Cost-effectiveness analysis is crucial for determining whether new interventions offer clinical benefits at a reasonable cost, with significant implications for public health policy. Clarifying the most cost-effective regimen and identifying the preferred option among immunotherapy‑based combination regimens are also valuable, assisting clinical oncologists and healthcare decision-makers in optimizing resource allocation within finite healthcare settings. Therefore, our study evaluated the cost-effectiveness of several available ICI combination regimens for treating aRCC in China and the US, respectively.

To the best of our knowledge, this is the first study to simultaneously incorporate all seven clinically available first‑line immunotherapy‑based combinations and sunitinib into a decision-analytic model for economic evaluation. Our base‑case analysis showed that the T + A regimen yielded the highest QALY gains among all combination strategies. In the NMB‑based cost‑effectiveness ranking, T + A ranked second and third in China and the US, respectively, while sunitinib ranked first in both countries. This indicates that, at the current WTP thresholds in the two countries, the other combination strategies were not cost‑effective. Sensitivity analyses both confirmed the robustness of these findings. Nevertheless, given the marked differences in drug pricing, reimbursement mechanisms, and market access between the two countries, the generalizability of our results is limited to China and the US.

Sensitivity analyses further revealed that, from both the Chinese and US perspectives, the costs for the more expensive drugs and the discount rates had the greatest impact on the cost-effectiveness across all immunotherapy‑based combination regimens. Although these combination regimens significantly improved survival benefits for aRCC patients, the current prices of most ICIs far exceeded their incremental clinical benefits, which may be a primary reason for the unfavorable cost-effectiveness of these combination therapies. Notably, among all immunotherapy‑based combination regimens, only toripalimab was currently included in the Chinese national reimbursement drug list, yielding a relatively lower ICER; however, it still failed to be cost‑effective vs. sunitinib. In the US, cancer drug pricing is minimally related to clinical utility because regulations require the largest insurer to reimburse all approved cancer treatments, which limited negotiations with pharmaceutical companies.49 Thus, our findings suggested that under the current high prices of ICIs, combination regimens were also unlikely to be cost-effective compared with sunitinib. Additionally, for the A + A and A + B regimens, patient body weight emerged as another critical determinant, given that avelumab and bevacizumab were dosed based on the weight. Consequently, the A + A and A + B regimens are disadvantageous for overweight or obese patients due to higher dosing requirements. Future clinical research should investigate appropriate dosing and assess whether dose modifications affect the clinical activity or the incidence of severe AEs associated with avelumab and bevacizumab.

Previous economic evaluations of first-line immunotherapy-based combinations for aRCC have largely focused on head-to-head comparisons between a single or a few combination strategies and sunitinib. For instance, Zheng et al.50 based on the CLEAR trial, reported that lenvatinib plus pembrolizumab or everolimus was not cost-effective from either the Chinese or the US perspective. Kang et al.32 and Alfayoumi et al.51 independently evaluated the combination of toripalimab and axitinib on the basis of the RENOTORCH trial from the China and US perspectives, respectively. Their conclusions are consistent with ours: toripalimab plus axitinib was unlikely to be the cost-effective first-line therapy for patients with aRCC compared with sunitinib. In terms of analytic breadth, the study by Yoo et al.52 most closely resembles ours, incorporating six immunotherapy-based regimens within a partitioned survival model over a 10 y time horizon from a US public payer perspective. Their results indicated that nivolumab plus ipilimumab yielded the highest QALY gains, but remained not cost-effective at the US WTP threshold of $150,000/QALY. These results align substantively with our findings. However, Yoo et al.52 did not include a Chinese perspective in their analysis, nor did they incorporate the toripalimab plus axitinib regimen.

The discrepancies observed across these studies and between them and our own results can be partly attributed to heterogeneity in modeling assumptions and parameter selections. Differences in the functional forms used for survival modeling, the composition and allocation of subsequent therapies, and the sources of key model parametersare all liable to exert asymmetric effects on both the direction and magnitude of ICERs. In addition, the drug pricing benchmarks adopted and the time horizons analyzed varied considerably across studies. In contrast, our study applied a consistent modeling framework and a uniform set of parameters, enabling a simultaneous head‑to‑head comparison of all regimens on a common scale. This approach, to some extent, enhances the internal validity of cross‑regimen comparisons and improves the reliability of our findings.

It should also be recognized that the therapeutic landscape of advanced RCC continues to evolve. Several emerging strategies, including triplet regimens and HIF-2α inhibitor–based therapies, have emerged as promising treatment options.41,53 However, mature overall survival data and robust evidence regarding their long-term effectiveness, safety, and optimal treatment sequencing remain limited. Accordingly, the present analysis focused on currently available first-line TKI + IO regimens supported by mature phase III survival data. These newer strategies were not covered within the scope of the present study but should be incorporated into future economic evaluations as more mature clinical evidence becomes available.

Limitation

This study still has some limitations. First, due to the absence of head-to-head comparison trials, we integrated multiple RCTs to perform indirect treatment comparisons. In this study, differences in patient characteristics across trials (which include comorbidities and prior treatment history) were not accounted for. These patient-level inconsistencies, combined with other trial-specific factors, inevitably introduced potential heterogeneity. Second, although IPD were reconstructed in the model, the survival curves for immunotherapy‑based combination regimens were indirectly derived based on hazard ratios from comparisons with sunitinib. The algorithm and modeling techniques inevitably introduced uncertainty. Third, the health utility values used in the model were extracted from previous cost-effectiveness studies in aRCC and may not fully reflect the characteristics of the population simulated in this analysis. Future studies would benefit from using utility values specifically derived from different combination regimen cohorts, which could improve the accuracy and robustness of the model. Fourth, the exclusive use of sunitinib as the comparator, while methodologically consistent with prior trials and cost-effectiveness analyses, limits the direct clinical relevance of our base-case findings. To address this limitation, our manuscript includes a comprehensive indirect ICER comparison across multiple immunotherapy‑based combination regimens, providing an economic ranking among currently relevant therapies. Finally, the selection of second-line and subsequent treatments was based on guideline-recommended assumptions. In real-world clinical practice, post-progression treatment is highly individualized, encompassing strategies such as immunotherapy, anti-angiogenic agents, and other targeted therapies. This assumption may have underestimated the actual cost-effectiveness outcomes for patients who could receive effective subsequent therapies in clinical practice, future validation using real-world data would be valuable.

Conclusion

In conclusion, this study evaluated the cost‑effectiveness of seven first‑line immunotherapy‑based combination regimens vs. sunitinib for advanced RCC from Chinese and US perspectives. The cost‑effectiveness rankings of the combination regimens differed between the two countries, but none of the regimens was cost‑effective compared with sunitinib monotherapy at current WTP thresholds in either setting. These results suggest that the current prices of ICIs are the primary barrier to cost‑effectiveness, and substantial price reductions may be necessary to improve their economic viability.

Supplementary Material

Supplement.docx
KHVI_A_2720165_SM7833.docx (4.3MB, docx)

Biography

Ruigang Diao, an associate chief pharmacist, currently serves as the Deputy Director of the Pharmacy Department at Yantai Yuhuangding Hospital. For over two decades, he has been actively engaged in scientific research, primarily focusing on pharmaceutical management, intelligent pharmacy, and pharmacoeconomics analysis.

Funding Statement

The author(s) reported there is no funding associated with the work featured in this article.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Data availability statement

The datasets supporting the conclusions of this article are included within the article and its additional files.

Ethics approval and consent to participate

This article does not contain any studies with human participants performed by any of the authors. Informed consent: Informed consent was not necessary because none of individual participants were included in the study.

Supplementary material

Supplemental data for this article can be accessed online at https://doi.org/10.1080/21645515.2026.2720165.

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Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

Supplement.docx
KHVI_A_2720165_SM7833.docx (4.3MB, docx)

Data Availability Statement

The datasets supporting the conclusions of this article are included within the article and its additional files.

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