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Abstract

Background:

Immune checkpoint inhibitor (ICI)-based combination therapies have been recommended as first-line options for metastatic renal cell carcinoma (mRCC); however, no head-to-head randomized controlled trials (RCTs) have compared all existing ICI-based therapies.

Objective:

We aimed to analyze the updated data to compare the efficacy of all available ICI-based options for mRCC.

Design:

A systematic review and Bayesian network analysis.

Data sources and methods:

A systematic literature search was undertaken up to September 15, 2024, and subsequent analysis was performed using a Bayesian fixed-effect model.

Results:

This study included 30 RCTs involving 14,959 patients. The results revealed that nivolumab plus cabozantinib (hazard ratio (HR): 0.77; 95% credible interval (CrI): 0.63–0.93), pembrolizumab plus lenvatinib (HR: 0.79; 95% CrI: 0.64–0.99), toripalimab plus axitinib (HR: 0.62; 95% CrI: 0.42–0.97), nivolumab plus ipilimumab (HR: 0.72; 95% CrI: 0.62–0.84), pembrolizumab plus axitinib (HR: 0.84; 95% CrI: 0.71–0.98), and avelumab plus axitinib (HR: 0.79; 95% CrI: 0.64–0.98) were significantly more effective than sunitinib for overall survival (OS). Most ICI-based combination treatments resulted in fewer or similar high-grade adverse events compared to sunitinib, except for pembrolizumab plus lenvatinib. For favorable-risk patients, ICI-based combination therapies were not more effective than sunitinib in OS, while six ICI-based combination therapies were associated with significantly improved OS compared to sunitinib for intermediate-risk or poor-risk patients.

Conclusion:

Our findings demonstrated that combination therapies including nivolumab plus cabozantinib, pembrolizumab plus lenvatinib, toripalimab plus axitinib, nivolumab plus ipilimumab, pembrolizumab plus axitinib, and avelumab plus axitinib significantly improved OS versus sunitinib. For subgroup analysis, ICI-based combination therapies exhibited significant advantages over sunitinib for intermediate-risk or poor-risk patients, while such advantages were diminished in treating favorable-risk patients.

Keywords

first-line treatment immune checkpoint inhibitors metastasis network meta-analysis renal cell carcinoma

Introduction

Renal cell carcinoma (RCC) is among the top 10 most commonly diagnosed malignancies globally.¹ Worldwide, approximately 430,000 individuals are afflicted with RCC annually, and over 179,000 die of the disease.² Due to the lack of obvious clinical symptoms, many patients with RCC have advanced-stage disease at diagnosis.³ Although targeted therapy has been the standard first-line treatment for advanced RCC, almost all patients eventually develop drug resistance.⁴

In recent years, immune checkpoint inhibitors (ICIs) have emerged as promising treatment options for RCC.⁵ To date, five different ICI-based systemic combination therapies, including nivolumab plus ipilimumab, nivolumab plus cabozantinib, pembrolizumab plus lenvatinib, pembrolizumab plus axitinib, and avelumab plus axitinib, have been recommended as first-line treatment options for metastatic RCC (mRCC).⁶ However, there remains no direct head-to-head randomized clinical trial (RCTs) covering all ICI-based and conventional first-line therapies to determine the optimal option. Under these circumstances, network analysis is valuable for clinical decision-making.

Recently, five RCTs have released findings pertaining to the clinical outcomes and adverse events (AEs) of ICI-based therapies,^7–11 while four earlier RCTs have been updated with further follow-up data.^12–15 However, these data were not included in the previous network analysis.¹⁶ Therefore, we aimed to compare the efficacy of all available ICI-based options for mRCC based on updated data using a Bayesian network meta-analysis.

Methods

Search strategy

This study was conducted in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) statement.¹⁷ The study protocol has been registered with PROSPERO (CRD42024603066). A comprehensive literature search was performed using PubMed, Cochrane Library, Web of Science, and ClinicalTrials.gov to identify RCTs that compared at least two systemic therapies for mRCC on September 15, 2024. All identified trials and reviews were screened to identify additional evidence. No limitations were placed on language or publication date. Details of the search strategy are provided in the Supplemental Material.

Selection criteria

For inclusion, the studies had to be RCTs of patients with mRCC who received systemic therapies. All studies were initially screened by title and abstract and excluded if they were duplicates, non-RCT designs (case–control, cohort, and cross-sectional studies), or RCTs containing less than two systemic therapies (sorafenib, sunitinib, pazopanib, anlotinib, cabozantinib, axitinib, tivozanib, savolitinib, everolimus, temsirolimus, lenvatinib, bevacizumab, nivolumab, ipilimumab, pembrolizumab, avelumab, atezolizumab, toripalimab, chemotherapy, immune checkpoint blockade, and immunotherapy). Following the full-text review, RCTs that met our eligibility criteria were included. Eligible patients were 18 years of age or older, had histologically unresectable or metastatic clear-cell RCC, had at least one measurable lesion according to the Response Evaluation Criteria in Solid Tumors (RECIST), version 1.1, and had a Karnofsky performance status score of at least 70 (scores range from 0 to 100, with lower scores indicating greater disability). Patients were excluded if they had received previous systemic anticancer therapy for advanced RCC (except cytokine treatment), had symptomatic central nervous system metastases, had active autoimmune disease, or had poorly controlled hypertension (systolic blood pressure ⩾150 mmHg or diastolic blood pressure ⩾90 mmHg).

Outcomes

Overall survival (OS) was explored as the primary outcome, whereas progression-free survival (PFS) and grade 3/4 drug-related AEs were evaluated as secondary outcomes.

Data extraction and quality assessment

Two independent reviewers (J.W. and X.L.) screened the titles and abstracts for potential inclusion. A standardized electronic form was developed a priori to extract data regarding patient characteristics (age, gender, number of patients), treatment strategies, relevant outcomes, and AEs by a single reviewer (M.L.), and checked by another reviewer (Q.L.). Attempts were made to extract population-level data for all treatment comparisons by two reviewers (Z.X. and X.S.). Any disagreements were resolved by a third reviewer (D.D.) through consensus discussion. The risk of bias of the included RCTs was assessed using the Cochrane Collaboration’s tool.¹⁸

Data synthesis and analysis

We used both fixed-effects and random-effects models with a Bayesian approach to analyze the pooled data.¹⁹ Time-to-event variables, including OS and PFS outcomes, were expressed as hazard ratios (HR) with their 95% credible interval (CrI) using Open BUGS version 3.2.2.²⁰ If HRs were not directly reported, the HRs and their 95% CrIs were calculated according to Tierney’s methods.²¹ The dichotomous variable (drug-related AE) was evaluated using the odds ratio (OR) in GeMTC version 0.14.3.²⁰ For OS and PFS, we used 30,000 iterations (10,000 per chain) obtained after a 5000-iteration training phase. To minimize autocorrelation, we applied a thinning interval of 50 for each chain. For high-grade AEs, we computed the ORs on the averages of 30,000 iterations after a training phase of 30,000 iterations. The ranking probabilities of each treatment intervention based on OS, PFS, and high-grade AEs were calculated by Surface Under the Cumulative Ranking curve (SUCRA), respectively.²²

The connectivity of the treatment networks in terms of OS, PFS, and high-grade AEs was illustrated using network plots. When two or more trials were available, the Chi-square test and I² statistic were used to test the heterogeneity between trials. Significant heterogeneity was considered to exist p value of the Chi-square test <0.10 and I² >50%.²³ The assessment of model fit was based on the deviance information criterion (DIC) and between-study standard deviation.^19,24,25 Differences in DIC values between models of >3–5 were considered significant.^19,26 A key presupposition behind network meta-analysis is that the analyzed network is consistent, meaning that direct and indirect evidence on the same comparisons do not disagree beyond chance.¹⁹ Most of the direct comparisons in our networks included only one trial, whereas comparisons with both direct and indirect evidence were uncommon; thus, we assumed overall consistency for our analysis. Any inconsistency in closed loops was assessed using a node-splitting approach.¹⁹ The assumption of transitivity was tested by checking the distribution of potential effect modifiers (age and sex ratio) across comparisons in the networks.²⁷ Sensitivity analyses were conducted by excluding studies that selected the non-clear-cell carcinoma subtype, enrolled only intermediate/high-risk patients, had not been published within the past 10 years, or were either phase II trials or non-global trials.

Results

Search results and study characteristics

Initially, 7382 potentially eligible studies were identified, and 7136 irrelevant articles were excluded by screening based on the titles and abstracts (Figure S1). With the full-text assessment of 246 articles, 30 unique RCTs, including 14,959 patients, were enrolled in this network meta-analysis (Table 1). A total of 28 different treatment regimens were investigated in these RCTs, and all treatments were assessed in at least one RCT. The mean sample size was 218 patients in each group, with a range of 33–557 patients. Twenty-six RCTs were on clear-cell carcinoma,^{7–15,28–44} and four RCTs also involved limited subsets of non-clear-cell histotypes, each corresponding to 4%–15% of the overall study population.^45–48 The characteristics of the RCT are presented in Table 1. No major discrepancies were observed in the characteristics of the included studies. The included patients had a median age of 59 years and were predominantly male (71%). As illustrated in the network plots, 15, 23, and 20 treatments in terms of OS (Figure 1(a)), PFS (Figure 1(b)), and high-grade AEs (Figure 1(c)) were observed to be connected to at least one other treatment.

Table 1.

Studies included in the multiple-treatments meta-analysis.

Study	Number of patients	Age (years)median (range)	Sex (% male)	Median PFS in months	PFS HR (95% CI)	Median OS in months	OS HR (95% CI)	High-grade AE, %
Yan 2024 (RENOTORCH)
Toripalimab plus axitinib	210	60.0 (20–78)	162 (77.1)	18	0.651 (0.490–0.864)	NR	0.613 (0.404–0.922)	71.2
Sunitinib	211	60.0 (28–78)	157 (74.4)	9.8	1 (Ref)	26.8	1 (Ref)	67.1
Motzer 2024 (CLEAR)
Pembrolizumab plus lenvatinib	355	64 (34–88)	255 (72)	23.9	0.47 (0.38–0.57)	53.7	0.79 (0.63–0.99)	84.9
Lenvatinib plus everolimus	357	62 (32–86)	266 (74.5)	14.7	0.65 (0.53–0.80)	NR	1.15 (0.88–1.50)	83.1
Sunitinib	357	61 (29–82)	275 (77)	9.2	1 (Ref)	54.3	1 (Ref)	74.7
Vasudev 2024
Modified ipilimumab plus nivolumab	128	61 (39–81)	101 (78.9)	NR	NA	NR	NA	32.8
Nivolumab and ipilimumab	64	65 (28–81)	48 (75.0)	NR	NA	NR	NA	53.1
Motzer 2023 (CheckMate9ER)
Nivolumab plus cabozantinib	323	62 (29–90)	249 (77)	16.4	0.58 (0.49–0.70)	46.5	0.77 (0.63–0.95)	67.5
Sunitinib	328	61 (28–86)	232 (71)	8.4	1 (Ref)	36	1 (Ref)	55.3
Choueiri 2023
Cabozantinib plus nivolumab and ipilimumab	428	61 (19–85)	326 (76)	NR	0.73 (0.57–0.94)	NR	NR	79.0
Nivolumab and ipilimumab	427	60 (28–87)	312 (73)	11.3	1 (Ref)	NR	NR	56.0
Motzer 2022 (IMmotion 151)
Atezolizumab plus bevacizumab	454	62 (24–88)	318 (70)	11.2	0.83 (0.70–0.97)	36.1	0.91 (0.76–1.08)	46.0
Sunitinib	461	60 (18–84)	350 (76)	8.4	1 (Ref)	35.3	1 (Ref)	56.0
Pal 2020 (IMmotion150)
Atezolizumab plus bevacizumab	101	NA	NA	11.7	1.00 (0.69–1.45)	NA	NA	39.6
Atezolizumab	103	NA	NA	6.1	1.19 (0.8–1.71)	NA	NA	15.5
Sunitinib	101	NA	NA	8.4	1 (Ref)	NA	NA	56.4
Rini 2019 (KEYNOTE-426)
Pembrolizumab plus axitinib	432	62 (30–89)	308 (71.3)	15.1	0.69 (0.57–0.84)	47.2	0.84 (0.71–0.99)	75.8
Sunitinib	429	61 (26–90)	320 (74.6)	11.1	1 (Ref)	40.8	1 (Ref)	70.6
Motzer 2019 (JAVELIN Renal 101)
Avelumab plus axitinib	442	62 (29–83)	316 (71.5)	13.9	0.67 (0.568–0.785)	NR	0.79 (0.643–0.969)	81.1
Sunitinib	444	61 (27–88)	344 (77.5)	8.5	1 (Ref)	37.8	1 (Ref)	77.4
Motzer 2018 (CheckMate 214)
Nivolumab plus ipilimumab	550	62 (26–85)	413 (75)	11.6	0.86 (0.73–1.01)	55.7	0.72 (0.62–0.85)	48.0
Sunitinib	546	62 (21–85)	395 (72)	8.4	1 (Ref)	38.4	1 (Ref)	64.0
Cirkel 2017 (ROPETAR)
Pazopanib plus everolimus	52	65 (44–87)	38 (73)	7.4	0.81 (0.50–1.29)	35	0.90 (0.51–1.58)	42.3
Pazopanib	49	67 (38–82)	31 (63)	9.4	1 (Ref)	18.5	1 (Ref)	49.0
Choueiri 2017 (CABOSUN)
Cabozantinib	79	63.0 (40–82)	66 (83.5)	8.2	0.66 (0.46–0.95)	30.3	0.8 (0.50–1.26)	66.7
Sunitinib	78	64.0 (31–87)	57 (73.1)	5.6	1 (Ref)	21.8	1 (Ref)	68.1
Tomita 2017
Sunitinib	57	NA	NA	8.7	0.67 (0.42–1.08)	NA	NA	NA
Sorafenib	63	NA	NA	7	1 (Ref)	NA	NA	NA
Eisen 2015
Nintedanib	64	62 (42–86)	44 (68.8)	8.44	1.12 (0.70–1.80)	20.37	0.92 (0.54–1.56)	48.4
Sunitinib	32	58 (29–79)	22 (68.8)	8.83	1 (Ref)	21.22	1 (Ref)	59.4
Eichelberg 2015 (SWITCH)
Sorafenib	182	64 (39–84)	139 (76)	5.9	1.19 (0.97–1.47)^a	NA	NA	64.4
Sunitinib	183	65 (40–83)	135 (74)	8.5	1 (Ref)	NA	NA	64.8
Ravaud 2015 (RECORD-2)
Everolimus plus bevacizumab	182	60 (20–84)	138 (75.8)	9.3	0.91 (0.69–1.19)	27.1	1.01 (0.75–1.34)	80.6
Bevacizumab plus IFN	183	60 (31–81)	131 (71.6)	10	1 (Ref)	27.1	1 (Ref)	76.2
Motzer 2014 (RECORD-3)
Everolimus	238	62 (20–89)	166 (69.7)	7.9	1.4 (1.2–1.8)	NA	NA	NA
Sunitinib	238	62 (29–84)	176 (73.9)	10.7	1 (Ref)	NA	NA	NA
Motzer 2014 (COMPARZ)
Pazopanib	557	61 (18–88)	398 (71)	8.4	1.05 (0.90–1.22)	28.4	0.91 (0.76–1.08)	74.4
Sunitinib	553	62 (23–86)	415 (75)	9.5	1 (Ref)	29.3	1 (Ref)	73.4
Rini 2014 (INTORACT)
Temsirolimus plus bevacizumab	400	59 (22–87)	288 (72)	9.1	1.1 (0.9–1.3)	25.8	1.0 (0.9–1.3)	79.9
Bevacizumab plus IFN	391	58 (23–81)	270 (69)	9.3	1 (Ref)	25.5	1 (Ref)	76.0
Procopio 2013 (ROSORC)
Sorafenib plus interleukin-2	66	64 (57–69)^b	52 (79)	NA	0.91 (0.62–1.35)^c	38	0.91 (0.59–1.41)	37.9
Sorafenib	62	62 (52–69)^b	43 (69)	NA	1 (Ref)	33	1 (Ref)	25.8
Hutson 2013
Axitinib	192	58 (23–83)	134 (70)	10·1	0.77 (0.56–1.05)	NA	NA	33.3
Sorafenib	96	58 (20–77)	74 (77)	6.5	1 (Ref)	NA	NA	25.0
Motzer 2013
Tivozanib	181	59 (23–83)	185 (71)	12.7	0.756 (0.580–0.985)	28.8	NA	61.0
Sorafenib	181	59 (23–85)	189 (74)	9.1	1 (Ref)	29.3	NA	70.0
Rini 2012
Sorafenib plus trebananib (10 mg/kg)	50	60 (39–80)	41 (82)	9	0.80 (0.50–1.28)	NR	NA	66.0
Sorafenib plus trebananib (3 mg/kg)	51	58 (28–84)	35 (68)	8.5	0.96 (0.61–1.50)	29.2	NA	72.5
Sorafenib plus placebo	51	59 (38–84)	38 (74.5)	9	1 (Ref)	27.1	NA	86.3
Negrier 2011 (TORAVA)
Temsirolimus plus bevacizumab	88	62·0 (33–83)	65 (74)	8.2	0.95 (0.62–1.45)^c	NA	NA	77.0
Bevacizumab plus IFN	41	61·9 (40–79)	27 (66)	16.8	0.65 (0.34–1.24)^c	NA	NA	70.0
Sunitinib	42	61·2 (33–83)	32 (76)	8.2	1 (Ref)	NA	NA	60.0
Rini 2010 (CALGB 90206)
Bevacizumab plus IFN	369	61 (56–70)	269 (73)	8.5	0.71 (0.61–0.83)	18.3	0.86 (0.73–1.01)	80.1
IFN	363	62 (55–70)	239 (66)	5.2	1 (Ref)	17.4	1 (Ref)	63.1
Escudier 2010 (AVOREN)
Bevacizumab plus IFN	327	61 (30–82)	222 (68)	10.2	0.61 (0.51–0.73)	23.3	0.78 (0.63–0.96)	60.2
IFN	322	60 (18–81)	234 (73)	5.4	1 (Ref)	21.3	1 (Ref)	45.1
Jonasch 2010
Sorafenib plus IFN	40	60.7 (43–81)	29 (72.5)	7.56	0.847 (0.506–1.416)	27.04	2.172 (0.921–5.122)	NA
Sorafenib	40	62.4 (45–83)	32 (80)	7.39	1 (Ref)	NR	1 (Ref)	NA
Motzer 2009
Sunitinib	375	62 (27–87)	267 (71)	11	0.539 (0.451–0.643)	26.4	0.808 (0.661–0.987)	NA
IFN	375	59 (34–85)	269 (72)	5	1 (Ref)	21.8	1 (Ref)	NA
Escudier 2009
Sorafenib	97	62.0 (34–78)	65 (67.0)	5.7	0.88 (0.61–1.27)	NA	NA	41.2
IFN	92	62.5 (18–80)	52 (56.5)	5.6	1 (Ref)	NA	NA	35.6
Hudes 2007 (ARCC)
Temsirolimus	209	58 (32–81)	139 (66)	5.5	0.82 (0.64–1.06)^c	10.9	0.73 (0.58–0.92)	66.8
Temsirolimus plus IFN	210	59 (32–82)	145 (69)	4.7	0.74 (0.61–0.89)^c	8.4	0.96 (0.76–1.20)	77.9
IFN	207	60 (23–86)	148 (71)	3.1	1 (Ref)	7.3	1 (Ref)	87.0

90% CI.

Interquartile range.

HRs and CIs were calculated according to the approach reported by Tierney et al.

AE, adverse event; CI, confidence interval; HR, hazard ratio; IFN, interferon-α; NA, not available; NR, not reached; OS, overall survival; PFS, progression-free survival; Ref, reference group (hence HR set to 1).

Figure 1.

Network of comparisons for the Bayesian network meta-analysis. Network plot for (a) OS, (b) PFS, and (c) high-grade AEs. The size of every treatment node corresponds to the number of randomly assigned patients. The width of the lines is proportional to the number of trials.

First, we compared the model fit of the fixed-effect model and random-effect model and found that the fixed-effect model had lower DIC values (or between-study standard deviation values for OR) compared to the random-effect model without significance (Tables S1–S3). Due to the fact that the majority of the direct comparisons were informed by a single trial, very low heterogeneity was observed (I² <50%, Figure S2). Thus, we chose a fixed-effects model according to both DIC and heterogeneity for the analyses. The results obtained using the random effects model are described in the Supplemental Material. The inconsistency test did not demonstrate any evidence of statistical inconsistency in the network (Table S4).

Overall survival

Nineteen first-line systemic treatments from 21 RCTs (10,899 patients) were analyzed for OS.^{7,8,11–15,29,30,32,34–36,38,40,41,43,44,47} The results revealed that patients treated with nivolumab plus cabozantinib (HR: 0.77; 95% CrI: 0.63–0.93), pembrolizumab plus lenvatinib (HR: 0.79; 95% CrI: 0.64–0.99), toripalimab plus axitinib (HR: 0.62; 95% CrI: 0.42–0.97), nivolumab plus ipilimumab (HR: 0.72; 95% CrI: 0.62–0.84), pembrolizumab plus axitinib (HR: 0.84; 95% CrI: 0.71–0.98), and avelumab plus axitinib (HR: 0.79; 95% CrI: 0.64–0.98) were associated with significantly improved OS compared to those treated with sunitinib (Figure 2(a)). When compared with those treated with toripalimab plus axitinib, patients treated with lenvatinib plus everolimus (HR: 1.82; 95% CrI: 1.17–3.08), temsirolimus plus interferon-α (IFN; HR: 1.88; 95% CrI: 1.13–3.07), bevacizumab plus IFN (HR: 1.66; 95% CrI: 1.01–2.67), and sunitinib (HR: 1.61; 95% CrI: 1.09–2.52) showed significantly inferior OS (Figure 2(b)). Ranking results indicated that among the evaluated regimens, toripalimab plus axitinib (SUCRA = 91.0%), nivolumab plus ipilimumab (SUCRA = 85.3%), and nivolumab plus cabozantinib (SUCRA = 75.0%) demonstrated relatively higher probabilities of prolonging OS in mRCC (Figure S3 and Table S5). In addition, we performed subgroup analyses based on different risk groups according to the International Metastatic Renal Cell Carcinoma Database Consortium (IMDC) criteria. Data on OS in patients with favorable risk from the four trials were analyzed.^7,11,14,49 Figure 3(a) illustrates the available pairwise comparisons, including six direct comparisons of the seven treatments. Subgroup analysis of the results demonstrated that nivolumab plus cabozantinib, pembrolizumab plus lenvatinib, nivolumab plus ipilimumab, pembrolizumab plus axitinib, avelumab plus axitinib, and lenvatinib plus everolimus did not significantly improve OS in patients with favorable risk compared with sunitinib (Figure 3(b)). Next, we analyzed the data of patients with intermediate or poor risk from six trials.^{7,8,11,12,14,44} Figure 3(c) illustrates the available pairwise comparisons, including eight direct comparisons of the nine treatments. For patients with intermediate or poor risk, nivolumab plus cabozantinib (HR: 0.73; 95% CrI: 0.59–0.90), pembrolizumab plus lenvatinib (HR: 0.74; 95% CrI: 0.58–0.97), toripalimab plus axitinib (HR: 0.61; 95% CrI: 0.40–0.92), nivolumab plus ipilimumab (HR: 0.73; 95% CrI: 0.61–0.88), pembrolizumab plus axitinib (HR: 0.76 95% CrI: 0.63–0.93), and avelumab plus axitinib (HR: 0.80; 95% CrI: 0.64–0.99) prolonged OS significantly than sunitinib (Figure 3(d)).

Figure 2.

Pooled HRs for overall survival. (a) Forest plot, with sunitinib as the comparator. (b) Forest plot, with toripalimab plus axitinib as the comparator. Numbers in parentheses indicate 95% CrI.

Figure 3.

Subgroup analyses of overall survival based on IMDC criteria. Network graph for favorable risk group (a) and intermediate or poor risk group (c). The size of every treatment node corresponds to the number of randomly assigned patients. The width of the lines is proportional to the number of trials. Forest plot for favorable risk group (with sunitinib as the comparator) (b) and intermediate or poor risk group (with sunitinib as the comparator) (d). Numbers in parentheses indicate 95% CrI.

Progression-free survival

For PFS, data on 28 systemic treatments from 29 trials (14,403 patients) were assessed.^{7–9,11–15,28–48} The comparison showed that cabozantinib plus nivolumab and ipilimumab (HR: 0.62; 95% CrI: 0.47–0.85), nivolumab plus cabozantinib (HR: 0.58; 95% CrI: 0.49–0.71), pembrolizumab plus lenvatinib (HR: 0.47; 95% CrI: 0.38–0.58), toripalimab plus axitinib (HR: 0.65; 95% CrI: 0.49–0.86), pembrolizumab plus axitinib (HR: 0.69; 95% CrI: 0.57–0.85), avelumab plus axitinib (HR: 0.67; 95% CrI: 0.57–0.78), atezolizumab plus bevacizumab (HR: 0.85; 95% CrI: 0.75–0.99), lenvatinib plus everolimus (HR: 0.65; 95% CrI: 0.53–0.79), and cabozantinib (HR: 0.66; 95% CrI: 0.47–0.98) were statistically better than sunitinib (Figure 4(a)). When compared with toripalimab plus axitinib, none of the treatments had significantly better efficacies, and more than half of the treatments (15/28) were statistically inferior in terms of PFS benefit (Figure 4(b)). Ranking of PFS indicated that pembrolizumab plus lenvatinib had the highest probability (80.8%) to be the preferred option (SUCRA = 99.0%; Table S6).

Figure 4.

Pooled HRs for progression-free survival. (a) Forest plot, with sunitinib as the comparator. (b) Forest plot, with toripalimab plus axitinib as the comparator. Numbers in parentheses indicate 95% CrI.

Subgroup analyses were also conducted based on the different risk groups (according to the IMDC criteria). Data on PFS in patients with favorable risk from the four trials were analyzed.^7,11,14,49 Figure 5(a) illustrates the available pairwise comparisons, including six direct comparisons of the seven treatments. Subgroup analyses revealed that pembrolizumab plus lenvatinib (HR: 0.50; 95% CrI: 0.35–0.72) and lenvatinib plus everolimus (HR: 0.54; 95% CrI: 0.38–0.83) could significantly extend the PFS of patients with favorable risk compared with sunitinib (Figure 5(b)). We next analyzed the data of patients with intermediate or poor risk from seven trials.^{7–9,11,12,14,44} Figure 5(c) illustrates the available pairwise comparisons, including 9 direct comparisons of the 10 treatments. For patients with intermediate or poor risk, cabozantinib plus nivolumab and ipilimumab (HR: 0.53; 95% CrI: 0.40–0.71), nivolumab plus cabozantinib (HR: 0.56; 95% CrI: 0.46–0.69), pembrolizumab plus lenvatinib (HR: 0.43; 95% CrI: 0.43–0.53), toripalimab plus axitinib (HR: 0.66; 95% CrI: 0.49–0.86), nivolumab plus ipilimumab (HR: 0.73; 95% CrI: 0.64–0.83), pembrolizumab plus axitinib (HR: 0.68; 95% CrI: 0.55–0.83), avelumab plus axitinib (HR: 0.66; 95% CrI: 0.55–0.79), and cabozantinib (HR: 0.67; 95% CrI: 0.48–0.98) were associated with significantly prolonged PFS than sunitinib (Figure 5(d)).

Figure 5.

Subgroup analyses of progression-free survival based on IMDC criteria. Network graph for favorable risk group (a) and intermediate or poor risk group (c). The size of every treatment node corresponds to the number of randomly assigned patients. The width of the lines is proportional to the number of trials. Forest plot for favorable risk group (with sunitinib as the comparator) (b) and intermediate or poor risk group (with sunitinib as the comparator) (d). Numbers in parentheses indicate 95% CrI.

High-grade AEs

Regarding high-grade AEs, the pooled results of 26 RCTs enrolling a total of 11,879 patients and 26 treatments are shown in Figure 1(c).^{7–15,29–33,35,37–45,47,48} In comparison with sunitinib, the incidence of high-grade AEs was significantly lower with nivolumab plus ipilimumab (OR: 0.50; 95% CrI: 0.29–0.90), atezolizumab plus bevacizumab (OR: 0.55; 95% CrI: 0.35–0.87), modified ipilimumab plus nivolumab (OR: 0.23; 95% CrI: 0.08–0.56), sorafenib plus trebananib (OR: 0.30; 95% CrI: 0.08–0.92), atezolizumab (OR: 0.15; 95% CrI: 0.07–0.31), and temsirolimus (OR: 0.23; 95% CrI: 0.08–0.56). Pembrolizumab plus lenvatinib (OR: 1.90; 95% CrI: 1.01–03.44) and temsirolimus plus bevacizumab (OR: 2.12; 95% CrI: 1.07–4.00) were associated with a significantly higher rate of high-grade AEs (Figure 6). Based on the SUCRA, the best tolerability profile was found for atezolizumab and temsirolimus (SUCRA = 97.3% and 92.5%, respectively), whereas temsirolimus plus bevacizumab was least well-tolerated (SUCRA = 11.5%; Table S7).

Figure 6.

Pooled ORs for high-grade adverse events. The column treatment is compared with the row treatment. ORs lower than 1 favor the column-defining treatment. Numbers in parentheses indicate 95% CrI. Significant results are underscored.

Network assumptions, sensitivity analysis, publication bias, and risk of bias

To verify the robustness of the results, sensitivity analyses were carried out by excluding trials that selected the non-clear-cell carcinoma subtype, enrolled only intermediate/high-risk patients, had not been published within the past 10 years, or were either phase II trials or non-global trials. The results from the sensitivity analyses after removing these studies were generally consistent with the primary analyses (Tables S8–S16), suggesting the robustness of our findings. The comparison-adjusted funnel plot of OS was shaped with bilateral symmetry and indicated no evidence of small study effects or publication bias (Figure S4). Overall, the studies included in this network analysis had moderate methodological quality. None of the remaining studies seemed to have a definite high risk of bias due to random sequence generation, allocation concealment, incomplete outcome data, or selective outcome reporting (Figure S5).

Discussion

In this updated network meta-analysis, 28 first-line systemic treatments for mRCC were compared based on 30 RCTs, including 14,959 patients. First, combination therapies including nivolumab plus cabozantinib, pembrolizumab plus lenvatinib, toripalimab plus axitinib, nivolumab plus ipilimumab, pembrolizumab plus axitinib, and avelumab plus axitinib significantly improved OS versus sunitinib. Second, although pembrolizumab plus lenvatinib was the preferred treatment strategy for extending PFS, it did not have a significant PFS advantage when compared with toripalimab plus axitinib. Third, for favorable-risk patients, ICI-based combination therapies were not found to be more effective than sunitinib in OS, although pembrolizumab plus lenvatinib and lenvatinib plus everolimus were better than sunitinib in improving PFS. Fourth, for patients with intermediate or poor risk, six ICI-based combination therapies (nivolumab plus ipilimumab, pembrolizumab plus axitinib, avelumab plus axitinib, nivolumab plus cabozantinib, pembrolizumab plus lenvatinib, and toripalimab plus axitinib) were associated with significantly improved PFS and OS compared with sunitinib. Finally, temsirolimus and atezolizumab were the best-tolerated drugs. Most ICI-based combination treatments resulted in fewer or similar high-grade AEs to sunitinib, except for pembrolizumab plus lenvatinib. These findings may help physicians to make optimal treatment decisions.

According to the results of our analysis, significant OS and PFS advantages for toripalimab plus axitinib were observed over sunitinib. Data on toripalimab plus axitinib were derived from the phase III RCT RENOTORCH. In the RENOTORCH trial, toripalimab plus axitinib was reported to provide significantly longer PFS, longer OS, and higher objective response rate (ORR) than sunitinib with a manageable safety profile, which is largely in line with our results.⁸ Toripalimab is a recombinant humanized anti-PD-1 monoclonal antibody approved by China’s National Medical Products Administration for the treatment of unresectable or metastatic melanoma, locally advanced or metastatic urothelial cancer, and recurrent or metastatic nasopharyngeal cancer.⁵⁰ Toripalimab binds to PD-1 mainly in the FG loop of PD-1.⁵¹ In contrast to toripalimab, nivolumab and pembrolizumab mainly bind to the N-terminal loop of PD-1 and the C′ D loop, respectively.^52,53 It has been shown that toripalimab could bind to PD-1 with affinity 12-fold higher than pembrolizumab and promote significantly more Th1- and myeloid-derived inflammatory cytokine responses in healthy human peripheral blood mononuclear cells (PBMCs) in vitro,⁵⁴ which may be an important reason for toripalimab-based therapy to demonstrate a better survival advantage than the combination therapy based on pembrolizumab. Moreover, toripalimab more potently upregulated IFN-γ-related gene signatures in dissociated and stimulated human non-small-cell lung cancer (NSCLC) in an ex vivo system compared to pembrolizumab.

Toripalimab plus axitinib is an ICI-tyrosine kinase inhibitor (TKI) combination therapy. In addition to toripalimab plus axitinib, other ICI-TKI combination therapies, including pembrolizumab plus axitinib, avelumab plus axitinib, nivolumab plus cabozantinib, and pembrolizumab plus lenvatinib, were also associated with significantly improved PFS and OS compared with sunitinib. Preclinical studies have demonstrated that antiangiogenic and anti-PD-L1 therapies could facilitate each other’s anti-tumor response by regulating the tumor microenvironment.^55,56 Based on existing evidence, ICI-TKI combination therapies may replace sunitinib as an attractive and effective option for mRCC patients in the future. Head-to-head clinical trials are required to determine the optimal ICI-TKI combination treatment regimen for mRCC.

We noticed that nivolumab plus ipilimumab, an ICI-ICI combination therapy, also appeared to have advantages in prolonging OS compared with sunitinib. Nivolumab and ipilimumab are monoclonal antibodies targeting PD-1 and CTLA-4, respectively. A direct comparison between nivolumab plus ipilimumab and sunitinib for advanced RCC was reported in the CheckMate 214 trial in 2018.⁴⁹ The CheckMate 214 trial showed that nivolumab plus ipilimumab resulted in a higher OS and ORR than sunitinib.⁴⁹ However, approximately 20% of patients who were treated with nivolumab plus ipilimumab presented with progressive disease as the best response.^57,58 Recently, a phase III RCT (COSMIC-313) explored the efficacy and safety of cabozantinib combined with nivolumab and ipilimumab in patients with advanced RCC. Compared with nivolumab plus ipilimumab, cabozantinib plus nivolumab and ipilimumab could significantly prolong PFS in patients.⁹ Using indirect comparisons in our study, we found that cabozantinib plus nivolumab and ipilimumab were significantly superior to sunitinib but not superior to toripalimab plus axitinib in terms of PFS. Due to the lack of OS data, we could not evaluate whether cabozantinib plus nivolumab and ipilimumab could provide better OS benefits than other therapies. Considering the extended timeframe spanning over 10 years during which these studies were published, we restricted our sensitivity analysis to studies published within the past 10 years. This was done to minimize the potential confounding effects of changes in later lines of treatment on OS outcomes in extended follow-ups. The findings from this sensitivity analysis were consistently aligned with the original results.

Unlike the previous network meta-analysis, we also performed subgroup efficacy analyses of different risk groups according to the IMDC risk classification.^16,59 We found that for patients with intermediate or poor risk, ICI-based combination therapies could offer distinct advantages over sunitinib, as six ICI-based combination therapies (nivolumab plus ipilimumab, pembrolizumab plus axitinib, avelumab plus axitinib, nivolumab plus cabozantinib, pembrolizumab plus lenvatinib, and toripalimab plus axitinib) were associated with significantly improved PFS and OS. However, such an advantage of ICI-based combination therapies became less pronounced when they were used to treat favorable-risk patients. ICI-based combination therapies were not found to be more effective than sunitinib in OS, although pembrolizumab plus lenvatinib and lenvatinib plus everolimus were better than sunitinib in improving PFS. These results suggest that when considering therapeutic options for patients with mRCC, the IMDC risk should be considered. ICI-based combination therapies should be prioritized for the treatment of patients with intermediate or poor-risk mRCC.

AEs can be classified into 1–4 grades, with grades 3 and 4 representing serious and life-threatening AEs, respectively.⁶⁰ In our analysis, we examined high-grade AEs (grade 3/4 AEs) as a measure of treatment safety. The incidence of patients treated with atezolizumab, temsirolimus, nivolumab plus ipilimumab, modified ipilimumab plus nivolumab, atezolizumab plus bevacizumab, and sorafenib plus trebananib was significantly lower than that of patients treated with sunitinib. Among the above therapies, only nivolumab plus ipilimumab exhibited both the OS advantage and better tolerability than sunitinib. Current evidence suggests nivolumab plus ipilimumab may be a sound clinical option for mRCC patients, offering an optimal balance between long-term efficacy and safety. In 2023, a phase III RCT further investigated whether administering ipilimumab once every 12 weeks (modified), instead of once every 3 weeks (standard), in combination with nivolumab, could reduce toxicity, and demonstrated that modified ipilimumab plus nivolumab was associated with a significantly lower rate of high-grade AEs than nivolumab plus ipilimumab.¹⁰ Moreover, an informal comparison did not suggest any reduction in efficacy with modified ipilimumab plus nivolumab. Similarly, low-dose and/or increased interval dosing of ipilimumab combined with anti-PD-1 blockade was suggested to remain efficacious while reducing toxicity in patients with melanoma and NSCLC.^61,62 Optimization of the dose and schedule of drugs to improve safety is a concern and an extensively studied issue.

A network meta-analysis was reported by Yanagisawa et al.⁶³ in January 2024 to evaluate first-line treatments for mRCC with extended follow-up data. Compared to this meta-analysis, the major contributions of our study are as follows: First, we included the three most recent RCTs, which enabled us to evaluate the efficacy and safety of new treatment regimens such as toripalimab plus axitinib, modified ipilimumab in combination with nivolumab, and cabozantinib plus nivolumab and ipilimumab.^8–10 However, these three RCTs were not included in Takafumi’s analysis. Hence, assessments of toripalimab plus axitinib, modified ipilimumab in combination with nivolumab, and cabozantinib plus nivolumab and ipilimumab were absent in Takafumi’s study. In addition, data from the CheckMate 9ER and CLEAR trials were updated in 2024, and our analysis was conducted based on these updated data.^7,11 Lastly, we included and analyzed all existing targeted and immune-related treatment options for mRCC from RCTs, while Yanagisawa et al.⁶³ only focused on ICI-based combination therapies. Thus, our study design was more comprehensive than that of Takafumi.

Our study had several strengths. First, we included the most updated data on the clinical efficacy and safety of first-line treatment for mRCC, which enabled us to obtain more stable results. To our knowledge, the present meta-analysis represents the latest and most comprehensive comparison. Furthermore, we performed a Bayesian network meta-analysis to indirectly compare first-line therapies for mRCC even in the absence of head-to-head trials. In addition, multiple statistical models were employed to guarantee the credibility and precision of the outcomes. Ultimately, evaluating the efficacy and safety of different systemic treatments based on updated data may offer fresh perspectives and guide patients and clinicians in making treatment choices and devising future comparative trials. Our findings provided clinically relevant guidance for the treatment of mRCC. When selecting therapies for mRCC patients, clinicians should incorporate IMDC risk stratification and prioritized ICI-based combination regimens for intermediate- or poor-risk cases. However, our results should be interpreted with caution due to several potential limitations. The primary limitation of this study stems from the reporting quality and reliability of the reviewed trials, which may have been influenced by various biases, thereby diminishing the precision of the findings. Second, this meta-analysis was based on combined data rather than individual patient data. At the individual patient level, confounding factors could potentially impact the effectiveness and AEs of systemic treatments. However, it was not possible to adjust for these factors because of data scarcity. Furthermore, the toripalimab plus axitinib combination regimen was conducted exclusively in Chinese cohorts, introducing potential demographic particularities that may limit direct comparability with global populations in existing multicenter trials and potentially compromise the generalizability of our findings. Finally, cross-trial comparisons inherently carry limitations due to confounding factors such as differences in study design, dose, inclusion criteria, and duration of follow-up. In addition, we were unable to consider all factors in the sensitivity analysis, which might reduce the comparability of the different treatments and affect the generalizability of our findings.

Conclusion

Our findings demonstrated that combination therapies including nivolumab plus cabozantinib, pembrolizumab plus lenvatinib, toripalimab plus axitinib, nivolumab plus ipilimumab, pembrolizumab plus axitinib, and avelumab plus axitinib significantly improved OS versus sunitinib. For subgroup analysis, ICI-based combination therapies exhibited significant advantages over sunitinib for intermediate-risk or poor-risk patients, while these advantages were diminished in the treatment of favorable-risk patients. However, the use of pooled rather than individual-level data may limit the precision and generalizability of the results. Further head-to-head RCTs are required to confirm our results.

Supplemental Material

sj-docx-1-tam-10.1177_17588359251353259 – Supplemental material for Unveiling the best immune checkpoint inhibitor-based therapy for metastatic renal cell carcinoma in the first-line setting: an updated systematic review and Bayesian network analysis

Supplemental material, sj-docx-1-tam-10.1177_17588359251353259 for Unveiling the best immune checkpoint inhibitor-based therapy for metastatic renal cell carcinoma in the first-line setting: an updated systematic review and Bayesian network analysis by Junpeng Wang, Xin Li, Mengjun Li, Qingyuan Liu, Zixuan Xie, Xiaotian Si, Lei Yang, Zhifeng Wang and Degang Ding in Therapeutic Advances in Medical Oncology

Supplemental Material

sj-docx-2-tam-10.1177_17588359251353259 – Supplemental material for Unveiling the best immune checkpoint inhibitor-based therapy for metastatic renal cell carcinoma in the first-line setting: an updated systematic review and Bayesian network analysis

Supplemental material, sj-docx-2-tam-10.1177_17588359251353259 for Unveiling the best immune checkpoint inhibitor-based therapy for metastatic renal cell carcinoma in the first-line setting: an updated systematic review and Bayesian network analysis by Junpeng Wang, Xin Li, Mengjun Li, Qingyuan Liu, Zixuan Xie, Xiaotian Si, Lei Yang, Zhifeng Wang and Degang Ding in Therapeutic Advances in Medical Oncology

Footnotes

Acknowledgements

None.

Declarations

ORCID iD

Degang Ding

Supplemental material

Supplemental material for this article is available online.

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