Pembrolizumab-axitinib versus nivolumab-cabozantinib as first-line therapy in patients with metastatic renal cell carcinoma: a retrospective real-world comparison (ARON-1)

Pembrolizumab-axitinib versus nivolumab-cabozantinib as first-line therapy in patients with metastatic renal cell carcinoma: a retrospective real-world comparison (ARON-1) | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Pembrolizumab-axitinib versus nivolumab-cabozantinib as first-line therapy in patients with metastatic renal cell carcinoma: a retrospective real-world comparison (ARON-1) Matteo Santoni, Giandomenico Roviello, Enrique Grande, Ugo Giorgi, and 32 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4125332/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 27 May, 2025 Read the published version in Cancer Immunology, Immunotherapy → Version 1 posted 10 You are reading this latest preprint version Abstract Background The optimal first-line therapy for metastatic renal cell carcinoma (mRCC) remains uncertain, despite recent advancements in immune-based combinations. This retrospective study compares the effectiveness of pembrolizumab plus axitinib (PA) and nivolumab plus cabozantinib (NC) as first-line treatments for mRCC in a real-world setting. Methods Patient data were collected from 55 centres across 16 countries, encompassing individuals diagnosed with mRCC receiving first-line treatment with PA or NC between January 2016 and October 2023. Clinical and tumour features and treatment responses were recorded. The primary endpoints were overall response rate (ORR), overall survival (OS), progression-free survival (PFS), and time to second progression. Statistical analyses included Kaplan-Meier survival estimates, Cox proportional hazard models, and chi-square tests. Results A total of 760 patients with a median age of 64 years (range, 29–88) were included. Of them, 607 received PA, and only 153 NC. Median OS was 55.7 months and not reached (NR) for PA and NC, respectively (P = .51), while median PFS was longer with NC (27.6 months) than for PA (16.2 months, P = .003). Subgroup analysis suggested a PFS benefits for NC in male, younger patients, intermediate-risk group, clear cell histology, and lung involvement, as well as ORR favoured NC in good risk patients. Multivariate analysis identified first-line therapy as a significant factor associated with PFS. Conclusions In this certainly biased retrospective comparison, NC demonstrated superior ORR and longer PFS compared to PA in mRCC. These findings underscore the importance of considering individual patient characteristics and risk profiles when selecting first-line therapy for mRCC. ARON-1 study axitinib plus pembrolizumab cabozantinib plus nivolumab immune-oncology combinations Figures Figure 1 Figure 2 Figure 3 Figure 4 Introduction Renal cell carcinoma (RCC) comprises 90–95% of kidney cancers and 3% of all adult cancers [ 1 ]. Among RCC histological subtypes, clear cell cancer histology is the most common, accounting for 75% of them, followed by papillary, chromophobe, and a number of rarer entities [ 2 ]. RCC is typically diagnosed as localized disease, with approximately 25% of cases relapsing after the radical resection of the primary tumor, while one-third of patients already have metastatic disease at diagnosis [ 3 ]. Despite the diagnostic and therapeutic progresses achieved over the past decade, RCC remains one of the most deadly urological malignancies [ 1 ]. Since the advent of cytokines, patients with metastatic RCC have been categorized into three prognostic groups based on clinical and laboratory features: favorable, intermediate, and poor. Currently, the Memorial Sloan Kettering Cancer Center (MSKCC) and International mRCC Database Consortium (IMDC) models remain the predominant prognostic tools used in clinical practice [ 4 , 5 ]. In the last few years, a number of phase III randomized clinical trials, utilizing sunitinib as the comparator arm, have established a novel standard of care incorporating immune checkpoint inhibitors (ICIs) in the management of advanced RCC [ 6 – 11 ]. Although there have been notable advances in treatment with the introduction of immunotherapy, patient stratification remains an essential component of clinical decision-making and treatment selection for this patient population. Notably, pembrolizumab plus axitinib (PA) (Keynote-426), nivolumab plus cabozantinib (NC) (CheckMate 9ER), pembrolizumab plus lenvatinib (CLEAR), and avelumab plus axitinib (JAVELIN Renal 101) have received approval (although with huge geographical differences), irrespective of the IMDC risk group [ 6 – 9 ]. However, nivolumab plus ipilimumab (CheckMate 214) has only been approved for patients with intermediate/poor risk according to the IMDC criteria [ 10 ]. With such a wide range of different treatment combinations now available, comparative analyses of their effectiveness and safety would be needed for guiding optimal first-line therapy selection. On this scenario, the ARON-1 study (NCT05287464) was designed to globally collect real-world data on the use of immune combinations as first-line therapy for mRCC [ 12 – 15 ]. In this sub-analysis, we conducted a retrospective comparison of the effectiveness of PA versus NC as first-line therapy in patients with advanced RCC. Patients and Methods Study population We retrospectively collected data from patients aged ≥ 18 years with a histologically confirmed diagnosis of RCC and histologically or radiologically confirmed metastatic disease. We included patients treated with first-line PA or NC between January 1st 2016 to October 1st 2023 from 55 centers from 16 countries. We retrospectively extracted from patients’ paper and electronic charts data about age, gender, tumor histology, nephrectomy, sites of metastases, type of immuno-combination and response to therapy. Patients with insufficient data on tumour assessment or response to therapy were excluded from the ARON-1 study. First-line therapy was continued till the evidence of clinical and/or radiological tumor progression, unacceptable toxicities, or death. Computed tomography or magnetic resonance imaging scans were performed following standard local procedures every 8–12 weeks. Physical examination and laboratory tests were carried out every 4–6 weeks during patients’ follow-up. Study endpoints The primary objective of our retrospective study was to assess the outcome of patients treated with first-line PA or NC for advanced RCC. Tumor radiological assessment was led according to the RECIST 1.1 criteria [ 16 ] and data on tumor response (complete [CR] or partial responses [PR], stable [SD] or progressive disease [PD]) were collected and analyzed. Overall Response Rate (ORR) was defined as the proportion of patients who achieve a CR or PR per RECIST criteria. Overall Survival (OS) was calculated from the start of treatment to death for any cause. Progression-Free Survival (PFS) was defined as the time from the start of first-line therapy to progression or death from any cause. Time to second progression (PFS2) was defined as the time from the start of first-line therapy to objective tumour progression on next-line treatment or death from any cause. Patients without a tumor progression to following line of treatment or death or lost at follow-up at the time of analysis were censored at their last follow-up date. Statistical Analysis OS, PFS and PFS2 were estimated using the Kaplan-Meier method with Rothman’s 95% confidence intervals (CI), and comparisons between survival distributions were led byusing the log-rank test. Univariate and multivariate analyses were carried out by using Cox proportional hazard models, Hazard Ratio (HR) and their 95% confidence intervals (95%CI). The chi-square test was employed to compare groups for categorical variables. Significance levels were set at a value of 0.05, and all p values were two-sided. The statistical analysis was performed by MedCalc version 19.6.4 (MedCalc Software, Broekstraat 52, 9030 Mariakerke, Belgium). Results Study Population In the ARON-1 study, we analyzed data relative to 3902 mRCC patients. Of them, 760 (19%) were included in this analysis (Figure S1). The median follow-up time was 17.0 months (95%CI 15.9−68.1), 557 patients (73%) were males. Median age was 64 years (range 29−88). Tumour histology was clear cell RCC in 643 patients (85%), Sarcomatoid feature was reported in 87 patients (11%). Most patients underwent a nephrectomy (63%). The most frequent sites of metastases were lungs (64%) and bones (36%). Six hundred and seven patients (80%) received PA as first-line therapy while 153 patients (20%) were treated with the NC combination, due to the different timing of availability of the two options, 184 patients (24%) had died at the time of analysis. Baseline clinical and pathological characteristics of the overall population are shown in Table 1. Notably, patients receiving NC were enriched for poor prognostic features such as IMDC risk classification and presence of bone and liver metastasis. Survival analysis In the overall study population, the median OS and PFS were 52.2 months (95%CI 34.4−55.7) and 17.6 months (95%CI 15.4−22.7), respectively. The median OS was 55.7 months (95%CI 31.7−55.7) in patients receiving PA and not reached (NR) (95%CI NR−NR) in patients receiving NC (P=.51, Figure 1). The 1y-, 2y- and 3y-OS rates were 81% vs. 82% (P=.85), 68% vs . 74% (P=.61) and 56% vs . 64% (P=.24) for PA vs. NC, respectively. Median PFS, it was 16.2 months (95%CI 14.2−20.2) in patients receiving PA and 27.6 months (95%CI 23.2−51.5) in patients receiving NC (P=.003, Figure 1). The 1y-, 2y- and 3y-PFS rates were 62% vs 77% (P=.02), 43% vs. 56% (P=.06) and 29% vs . 45% (P=.01) for PA vs. NC, respectively. In patients with good-risk features, the median OS was NR in both subgroups (P=.15), while the median PFS was 30.7 months (95%CI 23.7−35.0) for PA and NR (95%CI NR−NR) for NC (P=.05). In the intermediate risk subgroup, the median OS was 40.5 months (95%CI 29.0−55.7) for PA and NR (95%CI NR−NR) for NC (P=.11), with a significantly longer median PFS (31.3 months, 95%CI 27.6−40.6 vs 15.2 months, 95%CI 13.3−53.3, P=.004) in patients receiving NC (Figure 2). Finally, poor risk patients showed a median OS and PFS of 15.5 months (95%CI 12.4−22.1) and 7.8 months (95%CI 5.6−11.4) in those receiving PA and 22.1 months (95%CI 11.7−32.7, P=.86) and 15.4 months (95%CI 6.6−51.5, P=.18) in patients treated with NC. We further stratified patients based on tumor histology. No significant differences were found in terms of OS in both patients with clear cell (PA: 55.7 months, 95%CI 55.7−55.7, NC: NR, 95%CI NR−NR, P=.74) and non-clear cell RCC histology (PA: 31.1 months, 95%CI 24.5−40.5, NC: 24.9 months, 95%CI 14.9−34.9, P=.98). On the other hand, we observed longer median PFS in patients with clear cell RCC histology treated with NC (31.3 months, 95%CI 23.2−51.5) compared to PA (17.1 months, 95%CI 23.2−51.5, P=.005, Figure S2). In the 87 patients with sarcomatoid feature, the median OS and PFS were NR (95%CI NR−NR) and 11.4 months (95%CI 4.1−28.0) for PA and 25.3 months (95%CI 8.3−34.4, P=.69) and 23.2 months (95%CI 5.5−23.2, P=.73) for NC. We further stratified patients by site of metastasis, showing no differences in terms of median OS between patients treated by PA and NC with lung (NR, 95%CI NR−NR, vs. NR, 95%CI NR−NR, P=.37), liver (55.7 months, 95%CI 19.5−55.7, vs. 32.7 months, 95%CI 15.4−52.2, P=.86), or bone (29.0 months, 95%CI 23.6−55.7, vs . 22.1 months, 95%CI 14.9−40.0, P=.26) or brain metastases (29.0 months, 95%CI 15.4−40.5, vs . 11.7 months, 95%CI 1.3−11.7, P=.64). Median PFS, was significantly longer in patients with lung metastases treated with NC (15.4 months, 95%CI 13.4−18.0, vs. 40.6 months, 95%CI 16.6−51.5, P=.003, Figure S2), while no statistically significant differences were found in patients with bone (12.0 months, 95%CI 9.9−14.5, vs . 16.5 months, 95%CI 11.0−16.6, P=.19), liver (12.2 months, 95%CI 6.2−17.3, vs . 16.5 months, 95%CI 6.6−27.6, P=.38) or brain metastases (9.9 months, 95%CI 7.0−30.7 vs . 6.9 months, 95%CI 1.3−6.9, P=.78). Subgroup analyses for OS and PFS are shown in Figure 3 and 4. Response to first-line therapy In the overall study population, NC yielded higher ORR (59% vs. 49%, Table 2), as compared to PA, furthermore 7% CR, 52% PR, 27% SD and 14% PD were observed the former combination, as compared to 5% CR, 44% PR, 34% SD and 18% PD with PA. Notably enough, a statistically significant difference in terms of response to therapy in favor of NC was observed also in patients with good risk features (Table 2). Second-line therapies Three hundred and thirty-nine patients (45%) progressed during first-line therapy, 297 patients during PA and 42 patients with NC. Of them, 206 patients (69%) and 18 patients (43%) received second-line therapies, respectively. The median OS of the 224 patients who received second-line treatments was 31.1 months (95%CI 24.5−40.5) for PA and 40.0 months (95%CI 11.7−52.2) for NC (P=.75). Moreover, the median PFS2 was 20.7 months (95%CI 18.2−52.5) for PA and 21.8 months (95%CI 10.8−59.4) for NC (P=.48). The median OS of the 536 patients who did not receive second-line treatments was 55.7 months (95%CI 55.7−55.7) for PA and NR (95%CI NR−NR) for NC (P=.38). Univariate and Multivariate analyses In the overall study population, IMDC group, nephrectomy status, sarcomatoid differentiation, and the presence of bone, liver or brain metastases were correlated with both OS and PFS at multivariate analyses (Table 3). Interestingly, the choice of NC as first-line therapy was significantly associated with longer PFS at multivariate analysis (Table 3). Discussion The cornerstone of first-line therapy of mRCC has been TKI monotherapy for many years. However, a significant increase in survival rates has been reached using immune-based combinations. At present, for the first-line treatment of mRCC, international guidelines endorse the use of one of the following combinations: pembrolizumab plus axitinib or lenvatinib, and nivolumab plus cabozantinib or ipilimumab. As a whole, all these combinations, and the immune doublet in particular, proved to be less active and effective in good risk patients. PA, based on the outcomes of the Keynote-426 clinical trial, secured its position as the first approved combination therapy [ 17 ]. In this RCT, untreated metastatic RCC patients were randomized to receive either PA or sunitinib [ 18 ]. The PA group displayed a one-year OS rate of 89.9% alongside a PFS of 15.1 months and an ORR of 59.3%. Notably, the benefits of this combination extended across all subgroups, irrespective of programmed death-ligand 1 (PD-L1) expression or IMDC risk group. Upon an updated follow-up (with a median duration of 67.2 months), PA maintained an OS of 47.2 months and a PFS of 15.7 months. The experimental arm exhibited an ORR of 60.6%, a DCR of 83.3%, and a median duration of response of 23.6 months. The primary refractory rate was 17.0% in the PA group [ 19 ]. The most recent combination added to the armamentarium is NC, based on the positive results of the phase III trial, CheckMate 9ER [ 20 ]. This trial investigated nivolumab in combination with cabozantinib as compared to sunitinib in treatment-naïve metastatic RCC patients, irrespective of PD-L1 expression or IMDC prognostic group [ 21 ]. In the initial analysis, NC achieved a PFS of 16.6 months, with a not reached OS. The ORR was reported at 55.7% [ 22 ]. The subsequent update confirmed the superiority of NC over sunitinib, with a PFS of 16.6 months and an OS of 49.5 months within the intent-to-treat (ITT) population [ 23 ]. Notably, no head-to-head randomized clinical trials have yet compared these therapeutic approaches, while several metanalysis have been performed, yielding conflicting results. Indeed, on one hand, Qual et al. and Riatz et al.'s meta-analyses suggested that NC may lead to the highest likelihood of delivering maximal OS [ 24 , 25 ]; on the other hand, the network meta-analysis conducted by Lombardi et al. after the release of updated KEYNOTE 426 results [ 26 ] suggested that lenvatinib plus pembrolizumab had the highest probability of being the optimal treatment in terms of OS and PFS. However, among patients with sarcomatoid histology, NC demonstrated the highest rate in terms of survival outcomes. To our knowledge, this study represents the first real-world, observational, retrospective analysis comparing PA to NC in metastatic RCC patients. Our results showed a significantly longer median PFS with NC compared to PA (27.6 vs. 16.2 months, respectively), a huge difference, especially considering the longer follow-up available for the PA doublet. It's worth noting that the PFS observed with NC is longer than that reported in the CheckMate 9ER study, while the PFS recorded with PA is in line with the Keynote 426 results. On the contrary, no differences were observed in median OS. In our study, more patients with poor prognostic features (poor risk IMDC, bone and liver metastases) received NC, and this might partially explain why this combination yielded a clear ORR and PFS benefit, but no OS advantage in the overall population. Subgroup analyses revealed PFS benefits for NC among intermediate-risk IMDC, clear cell RCC histology, and patients with lung metastases. Moreover, in younger patients (< 65 years) and in males, NC demonstrated superior PFS, as well as in patients who had undergone nephrectomy. Response rates favoured NC, especially in patients with good risk features, where CR rates almost reached 30%. Although the use of an IO-TKI combination is recommended by most international guidelines also for the first line treatment of IMDC good risk mRCC patients, there is an open debate about the impact of immune checkpoint inhibitors in this population, since longer follow-up of registration trials has shown declining HRs for OS in this population [ 27 ]. As a whole, our data suggest that this strategy should remain the preferred treatment. Outcomes in the second-line therapy setting showed no significant differences between treatment groups, findings consistent with previous real-world data [ 11 ]. Multivariate analysis identified NC as a significant factor associated with longer PFS. Notably, contrary to prior data, there was no evidence for additional benefit with NC in the sarcomatoid subgroup. Differences in survival outcomes related to age and gender have been reported in the CheckMate 9ER trial, where young patients (< 65 years) and males showed a major OS benefit from NC, with no disparities in PFS. Furthermore, patients who had previously undergone nephrectomy benefited significantly in terms of OS, although not PFS, when treated with NC if compared to sunitinib. Notably, these subgroup differences were not highlighted in the Keynote 426 study. In the first-line setting, ICI-based combination therapy significantly reduced the risk of disease progression in both male and female patients compared to sunitinib alone, with no statistically significant differences in PFS and OS between gender [ 28 ]. Likely, prior nephrectomy did not appear to influence the efficacy of ICI in metastatic RCC [ 29 ]. Conversely, the OS benefit from first-line ICI-based combinations was notably more substantial in younger patients [ 30 ]. Among the several limitations inherent in our study, the major one is related to its retrospective nature and subsequent bias, particularly considering the non-randomized allocation of patients; assignment of patients to one treatment group over the other might have been influenced by unmeasured or unaccounted-for factors, thereby potentially impacting the study outcomes. Additionally, only 20% of the patients here analyzed did receive the NC combination, the vast majority having been treated with PA, a difference which could have introduced another important bias in our analysis. Furthermore, the proportion of patients receiving second-line therapy upon disease progression was higher among those initially treated with PA in the first line, realistically a time-lead bias related to the different timing of availability of the two combinations in clinical practice; obviously, this phenomenon could serve as a confounding factor affecting OS. Moreover, the absence of data on safety in general, and on therapy management (dose modifications, treatment interruptions, etc ) hinders the ability to make a thorough comparison between the two-treatment regimen. Finally, the lack of numerically adequate data relative to the third, and more recent, combination of PA, prevented us to perform a more comprehensive comparison between all the different standard treatment options presently available. Despite all the above, given the lack of data directly comparing first-line therapeutic combinations in RCC, our study offers valuable insights for treatment decisions. Indeed, it suggests a potential advantage in terms of PFS when utilizing NC as a first-line treatment, both in the overall population and among specific subgroups. Conclusion Our study represents the first real-world, observational, retrospective investigation comparing PA to NC in all treatment naive metastatic RCC patients. Although inevitably biased, our results showed a significantly longer median PFS with NC compared to PA, while no differences were observed in median OS. Subgroup analyses suggested a PFS benefits for NC in various mRCC subpopulations, and an ORR benefits in the good risk population. Additional indirect insights for treatment choice of first-line treatment between the two therapeutic regimens could be drawn from this study, although the lack of a prospective randomised comparisons between the two treatment options (which realistically will never be performed) remains a relevant drawback of this study to take into account. Declarations Funding: The authors declare that no funds, grants, or other support were received during the preparation of this manuscript. Data Availability The data are available to researchers upon request by submitting a proposal in writing to the Principal Investigator of the ARON-1 study, Dr Matteo Santoni, in the Oncology Unit, Macerata Hospital. Competing Interest Matteo Santoni has received research support and honoraria from Janssen, Bristol Myers Squibb, Ipsen, MSD, Astellas and Bayer, all unrelated to the present paper. Enrique Grande has received honoraria for speaker engagements, advisory roles or funding of continuous medical education from Adacap, AMGEN, Angelini, Astellas, Astra Zeneca, Bayer, Blueprint, Bristol Myers Squibb, Caris Life Sciences, Celgene, Clovis-Oncology, Eisai, Eusa Pharma, Genetracer, Guardant Health, HRA-Pharma, IPSEN, ITM-Radiopharma, Janssen, Lexicon, Lilly, Merck KGaA, MSD, Nanostring Technologies, Natera, Novartis, ONCODNA (Biosequence), Palex, Pharmamar, Pierre Fabre, Pfizer, Roche, Sanofi-Genzyme, Servier, Taiho, and Thermo Fisher Scientific, he also has received research grants from Pfizer, Astra Zeneca, Astellas, and Lexicon Pharmaceuticals R. Kanesvaran has received fees for speaker bureau and advisory board activities from the following companies: Pfizer, MSD, BMS, Eisai, Ipsen, Johnson and Johnson, Merck, Amgen, Astellas and Bayer. Tomas Buchler has received research support: AstraZeneca, Roche, Bristol Myers Squibb, Exelixis, Merck KGaA, MSD, and Novartis, consulting fees from Bristol Myers Squibb, Astellas, Janssen, and Sanofi/Aventis, payment or honoraria for lectures, presentations, speakers’ bureaus, manuscript writing, or educational events from Ipsen, Bristol-Myers Squibb, AstraZeneca, Roche, Servier, Accord, MSD, and Pfizer. Camillo Porta has received honoraria from Angelini Pharma, AstraZeneca, BMS, Eisai, Ipsen and MSD and acted as a Protocol Steering Committee Member for BMS, Eisai and MSD. Alfonso Gómez de Liaño has received consulting fees from BMS, Ipsen, Merck, MSD, payment or honoraria for lectures, presentations, speakers’ bureaus, or educational events from BMS, Ipsen, MSD, Roche, and Pfizer, and research support (institution) from AstraZeneca, MSD and Roche. Pasquale Rescigno has served as a consultant/advisory board member for MSD, Astra Zeneca, Janssen, Pfizer and travel grant from Ipsen. Linda Cerbone has received honoraria for advisory boards, speaker engagements and scientific consultancy for educational purposes from AstraZeneca, EISAI, MSD, Ipsen, BMS, A.A.A., past MSD employee in Medical Affairs. The other authors declare to have no conflicts of interest. Author contributions: All authors contributed to the study conception and design. Material preparation, data collection and analysis were performed by Matteo Santoni, Giandomenico Roviello, Enrique Grande, Ugo De Giorgi, Ondrej Fiala, Emmanuel Seront, Javier Molina-Cerrillo , Renate Pichler, Zin W. Myint, Jakub Kucharz, Ravindran Kanesvaran , Thomas Büttner , Martin Pichler, Umberto Basso, Jindrich Kopecky, Maria T. Bourlon, Linda Cerbone, Tomas Buchler, Alvaro Pinto, Alfonso Gómez de Liaño , Caterina Gianni, Anca Zgura, Pasquale Rescigno, Jawaher Ansari, Orazio Caffo, Zsófia Küronya, Maria Giuseppa Vitale, Dipen Bhuva, Martina Catalano, Nuno Vau, Ray Manneh Kopp, Sebastiano Buti, Aristotelis Bamias , Camillo Porta, Kaisa Sunela, and Francesco Massari . The first draft of the manuscript was written by Matteo Santoni and all authors commented on previous versions of the manuscript. All authors read and approved the final manuscript. Ethic approval: This study was performed in line with the principles of the Declaration of Helsinki. Approval was granted by the Ethics Committee of Marche (CERM) n. 1164/2020 and written informed consent was obtained from all participating patients. Consent to participate: Informed consent was obtained from all individual participants included in the study. 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Urol Oncol Semin Orig Investig 40:64.e17-64.e24. https://doi.org/10.1016/j.urolonc.2021.09.009 Yanagisawa T, Quhal F, Kawada T, et al (2023) Association between age and efficacy of first-line immunotherapy-based combination therapies for mRCC: a meta-analysis. Immunotherapy 15:. https://doi.org/10.2217/IMT-2023-0039 Tables Table 1. Baseline patients’ characteristics. Patients Overall 760 (%) Pembrolizumab + Axitinib 607 (%) Nivolumab + Cabozantinib 153 (%) P Gender Male Female 557 (73) 203 (27) 447 (74) 160 (26) 110 (72) 43 (28) .75 Age, years (y) Range 64 29 − 88 65 34 − 88 64 29 − 87 - Metastatic at diagnosis 415 (55) 338 (56) 77 (50) .48 Prior nephrectomy 477 (63) 382 (63) 95 (62) .88 Clear cell histology 643 (85) 513 (85) 130 (85) >.99 Sarcomatoid feature 87 (11) 67 (11) 20 (13) .66 IMDC risk stratification Favorable risk Intermediate risk Poor risk 163 (22) 413 (55) 184 (23) 130 (21) 343 (57) 134 (22) 33 (22) 70 (46) 50 (32) .21 Common sites of metastasis Lung Bone Liver Brain 483 (64) 271 (36) 139 (18) 57 (8) 384 (63) 203 (33) 102 (17) 47 (8) 99 (65) 68 (44) 37 (24) 7 (5) .76 .11 .22 .39 Median follow-up 17.0 months 18.3 months 15.1 months .38 Second-line therapies 224 (29) 206 (34) 18 (12) <.001 Type of second-line therapy Cabozantinib Sunitinib Clinical Trials Other 191 (25) 15 (2) 7 (1) 11 (1) 191 (31) 0 (0) 4 (1) 11 (2) 0 (0) 15 (10) 3 (2) 0 (0) - IMDC: International Metastatic RCC Database Consortium Table 2. Response to therapy in RCC patients stratified by type of first-line therapy and IMDC group. Patients Overall (%) Pembrolizumab + Axitinib (%) Nivolumab + Cabozantinib (%) p Overall Study Population Complete Response Partial Response Stable Disease Progressive Disease 5 45 33 17 5 44 34 18 7 52 27 14 .51 IMDC Good Risk Complete Response Partial Response Stable Disease Progressive Disease 10 49 40 1 7 49 36 8 27 53 20 0 <.001 IMDC Intermediate Risk Complete Response Partial Response Stable Disease Progressive Disease 5 44 34 17 5 42 37 16 4 46 31 19 .78 IMDC Poor Risk Complete Response Partial Response Stable Disease Progressive Disease 1 45 24 30 2 43 25 30 0 50 19 31 .33 IMDC: International Metastatic RCC Database Consortium Table 3. Univariate and multivariate analyses. Overall Survival Univariate Cox Regression Multivariate Cox Regression HR (95%CI) p-value HR (95%CI) p-value Gender (females vs males) 1.17 (0.84−1.63) .34 Age (≥65y vs <65y) 1.47 (1.10−1.97) .009 1.85 (1.36−2.51) <.001 IMDC prognostic group 3.13 (2.47−3.97) <0.001 2.66 (2.03−3.48) <.001 Nephrectomy (yes vs no) 0.40 (0.30−0.54) <0.001 0.60 (0.43−0.83) .002 Histology (ccRCC vs nccRCC) 1.41 (0.97−2.04) .06 Sarcomatoid features (yes vs no) 1.82 (1.23−2.68) .02 1,75 (1.18−2.60) .005 Lung metastases (yes vs no) 1.11 (0.82−1.51) .50 Bone metastases (yes vs no) 2.02 (1.52-2.70) <.001 1.54 (1.13−2.09) .006 Liver metastases (yes vs no) 1.77 (1.29−2.42) <.001 1.44 (1.03−2.01) .032 Brain metastases (yes vs no) 2.05 (1.34−3.16) .001 1.86 (1.17−2.96) .009 Nivolumab/Cabozantinib vs Pembrolizumab/Axitinib 0.87 (0.58−1.31) .51 Progression-Free Survival Univariate Cox Regression Multivariate Cox regression HR (95%CI) p-value HR (95%CI) p-value Gender (females vs males) 1.25 (0.98−1.59) .07 Age (≥65y vs <65y) 1.05 (0.84−1.31) .68 IMDC prognostic group 1.78 (1.52−2.10) <0.001 1.54 (1.27−1.86) <.001 Nephrectomy (yes vs no) 0.51 (0.41−0.64) <0.001 0.63 (0.49−0.81) <.001 Histology (ccRCC vs nccRCC) 1.40 (1.06−1.85) .01 1.14 (0.85−1.52) .38 Sarcomatoid features (yes vs no) 1.59 (1.16−2.18) .004 1.53 (1.11−2.11) .008 Lung metastases (yes vs no) 1.13 (0.83−1.54) .43 Bone metastases (yes vs no) 1.67 (1.33−2.08) <.001 1.36 (1.08−1.72) .01 Liver metastases (yes vs no) 1.49 (1.16−1.92) .002 1.36 (1.04−1.78) .02 Brain metastases (yes vs no) 1.76 (1.24−2.49) .001 1.48 (1.02−2.15) .03 Nivolumab/Cabozantinib vs Pembrolizumab/Axitinib 0.60 (0.43−0.84) .003 0.53 (0.37−0.74) <.001 ccRCC = clear cell Renal Cell Carcinoma; IMDC = International Metastatic RCC Database Consortium; nccRCC = non-clear cell Renal Cell Carcinoma Additional Declarations No competing interests reported. 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Consorziale Policlinico di Bari","correspondingAuthor":false,"prefix":"","firstName":"Camillo","middleName":"","lastName":"Porta","suffix":""},{"id":281465769,"identity":"9b823b3d-7ac8-4528-933e-0f70351e6022","order_by":34,"name":"Kaisa Sunela","email":"","orcid":"","institution":"Finnish Medicines Agency Fimea","correspondingAuthor":false,"prefix":"","firstName":"Kaisa","middleName":"","lastName":"Sunela","suffix":""},{"id":281465771,"identity":"a3c9ef3e-ac3e-48a5-9757-8a812a41f25b","order_by":35,"name":"Francesco Massari","email":"","orcid":"","institution":"IRCCS Azienda Ospedaliero-Universitaria di Bologna","correspondingAuthor":false,"prefix":"","firstName":"Francesco","middleName":"","lastName":"Massari","suffix":""}],"badges":[],"createdAt":"2024-03-18 18:27:18","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4125332/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4125332/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1007/s00262-025-04043-x","type":"published","date":"2025-05-27T15:57:03+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":53200457,"identity":"e440a3a2-1d64-4830-8d1d-3cd45a15c5c1","added_by":"auto","created_at":"2024-03-21 19:27:24","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":392664,"visible":true,"origin":"","legend":"\u003cp\u003eOverall survival and progression free survival among metastatic renal cell carcinoma patients.\u003c/p\u003e","description":"","filename":"Figure12.png","url":"https://assets-eu.researchsquare.com/files/rs-4125332/v1/3467629e996c74cb500a1022.png"},{"id":53200455,"identity":"19e2a3b5-afe3-4a5c-b486-baec6087d284","added_by":"auto","created_at":"2024-03-21 19:27:24","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":147454,"visible":true,"origin":"","legend":"\u003cp\u003eProgression Free Survival according to International Metastatic RCC Database Consortium score.\u003c/p\u003e","description":"","filename":"Figure21.png","url":"https://assets-eu.researchsquare.com/files/rs-4125332/v1/5943c76c44d7f48af2c770ab.png"},{"id":53201270,"identity":"ca3500f9-79aa-4c7f-ad66-8403a347e407","added_by":"auto","created_at":"2024-03-21 19:35:30","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":73384,"visible":true,"origin":"","legend":"\u003cp\u003eSubgroup analysis of overall survival.\u003c/p\u003e","description":"","filename":"Figure31.png","url":"https://assets-eu.researchsquare.com/files/rs-4125332/v1/a2dbae71d87001fe91077ccd.png"},{"id":53200458,"identity":"21bda0ef-c398-425d-b7a1-a60288ba5062","added_by":"auto","created_at":"2024-03-21 19:27:25","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":51857,"visible":true,"origin":"","legend":"\u003cp\u003eSubgroup analysis of progression free survival.\u003c/p\u003e","description":"","filename":"Figure4.png","url":"https://assets-eu.researchsquare.com/files/rs-4125332/v1/3b4ab4b44678ef8c3d479e46.png"},{"id":83782886,"identity":"4d77b7fa-44d1-44c4-b61d-312b78c0f527","added_by":"auto","created_at":"2025-06-02 16:08:02","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":2025041,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4125332/v1/94c4241d-57f3-4da8-a38d-ce2e7f59fa73.pdf"},{"id":53200459,"identity":"d2241100-415d-4543-bf02-5d175e652ff3","added_by":"auto","created_at":"2024-03-21 19:27:25","extension":"tif","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":178576,"visible":true,"origin":"","legend":"","description":"","filename":"FigureS1.tif","url":"https://assets-eu.researchsquare.com/files/rs-4125332/v1/fd309861feba894013d3310d.tif"},{"id":53201268,"identity":"a0bdae74-2e90-4256-8da0-f036394e3a00","added_by":"auto","created_at":"2024-03-21 19:35:24","extension":"tif","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":91934,"visible":true,"origin":"","legend":"","description":"","filename":"FigureS2.tif","url":"https://assets-eu.researchsquare.com/files/rs-4125332/v1/c69f863331ca5c56188dc3fb.tif"}],"financialInterests":"No competing interests reported.","formattedTitle":"Pembrolizumab-axitinib versus nivolumab-cabozantinib as first-line therapy in patients with metastatic renal cell carcinoma: a retrospective real-world comparison (ARON-1)","fulltext":[{"header":"Introduction","content":"\u003cp\u003eRenal cell carcinoma (RCC) comprises 90\u0026ndash;95% of kidney cancers and 3% of all adult cancers [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. Among RCC histological subtypes, clear cell cancer histology is the most common, accounting for 75% of them, followed by papillary, chromophobe, and a number of rarer entities [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. RCC is typically diagnosed as localized disease, with approximately 25% of cases relapsing after the radical resection of the primary tumor, while one-third of patients already have metastatic disease at diagnosis [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. Despite the diagnostic and therapeutic progresses achieved over the past decade, RCC remains one of the most deadly urological malignancies [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eSince the advent of cytokines, patients with metastatic RCC have been categorized into three prognostic groups based on clinical and laboratory features: favorable, intermediate, and poor. Currently, the Memorial Sloan Kettering Cancer Center (MSKCC) and International mRCC Database Consortium (IMDC) models remain the predominant prognostic tools used in clinical practice [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e, \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eIn the last few years, a number of phase III randomized clinical trials, utilizing sunitinib as the comparator arm, have established a novel standard of care incorporating immune checkpoint inhibitors (ICIs) in the management of advanced RCC [\u003cspan additionalcitationids=\"CR7 CR8 CR9 CR10\" citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. Although there have been notable advances in treatment with the introduction of immunotherapy, patient stratification remains an essential component of clinical decision-making and treatment selection for this patient population.\u003c/p\u003e \u003cp\u003eNotably, pembrolizumab plus axitinib (PA) (Keynote-426), nivolumab plus cabozantinib (NC) (CheckMate 9ER), pembrolizumab plus lenvatinib (CLEAR), and avelumab plus axitinib (JAVELIN Renal 101) have received approval (although with huge geographical differences), irrespective of the IMDC risk group [\u003cspan additionalcitationids=\"CR7 CR8\" citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. However, nivolumab plus ipilimumab (CheckMate 214) has only been approved for patients with intermediate/poor risk according to the IMDC criteria [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eWith such a wide range of different treatment combinations now available, comparative analyses of their effectiveness and safety would be needed for guiding optimal first-line therapy selection. On this scenario, the ARON-1 study (NCT05287464) was designed to globally collect real-world data on the use of immune combinations as first-line therapy for mRCC [\u003cspan additionalcitationids=\"CR13 CR14\" citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. In this sub-analysis, we conducted a retrospective comparison of the effectiveness of PA \u003cem\u003eversus\u003c/em\u003e NC as first-line therapy in patients with advanced RCC.\u003c/p\u003e"},{"header":"Patients and Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eStudy population\u003c/h2\u003e \u003cp\u003eWe retrospectively collected data from patients aged\u0026thinsp;\u0026ge;\u0026thinsp;18 years with a histologically confirmed diagnosis of RCC and histologically or radiologically confirmed metastatic disease. We included patients treated with first-line PA or NC between January 1st 2016 to October 1st 2023 from 55 centers from 16 countries.\u003c/p\u003e \u003cp\u003eWe retrospectively extracted from patients\u0026rsquo; paper and electronic charts data about age, gender, tumor histology, nephrectomy, sites of metastases, type of immuno-combination and response to therapy. Patients with insufficient data on tumour assessment or response to therapy were excluded from the ARON-1 study.\u003c/p\u003e \u003cp\u003eFirst-line therapy was continued till the evidence of clinical and/or radiological tumor progression, unacceptable toxicities, or death. Computed tomography or magnetic resonance imaging scans were performed following standard local procedures every 8\u0026ndash;12 weeks. Physical examination and laboratory tests were carried out every 4\u0026ndash;6 weeks during patients\u0026rsquo; follow-up.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003eStudy endpoints\u003c/h2\u003e \u003cp\u003eThe primary objective of our retrospective study was to assess the outcome of patients treated with first-line PA or NC for advanced RCC. Tumor radiological assessment was led according to the RECIST 1.1 criteria [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e] and data on tumor response (complete [CR] or partial responses [PR], stable [SD] or progressive disease [PD]) were collected and analyzed. Overall Response Rate (ORR) was defined as the proportion of patients who achieve a CR or PR per RECIST criteria. Overall Survival (OS) was calculated from the start of treatment to death for any cause. Progression-Free Survival (PFS) was defined as the time from the start of first-line therapy to progression or death from any cause. Time to second progression (PFS2) was defined as the time from the start of first-line therapy to objective tumour progression on next-line treatment or death from any cause. Patients without a tumor progression to following line of treatment or death or lost at follow-up at the time of analysis were censored at their last follow-up date.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003eStatistical Analysis\u003c/h2\u003e \u003cp\u003eOS, PFS and PFS2 were estimated using the Kaplan-Meier method with Rothman\u0026rsquo;s 95% confidence intervals (CI), and comparisons between survival distributions were led byusing the log-rank test. Univariate and multivariate analyses were carried out by using Cox proportional hazard models, Hazard Ratio (HR) and their 95% confidence intervals (95%CI). The chi-square test was employed to compare groups for categorical variables. Significance levels were set at a value of 0.05, and all \u003cem\u003ep\u003c/em\u003e values were two-sided. The statistical analysis was performed by MedCalc version 19.6.4 (MedCalc Software, Broekstraat 52, 9030 Mariakerke, Belgium).\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cp\u003e\u003cem\u003eStudy Population\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eIn the ARON-1 study, we analyzed data relative to 3902 mRCC patients. Of them, 760 (19%) were included in this analysis\u0026nbsp;(Figure S1).\u0026nbsp;The median follow-up time was 17.0 months (95%CI 15.9−68.1), 557 patients (73%) were males.\u0026nbsp;Median age was 64 years (range 29−88).\u0026nbsp;Tumour histology was clear cell RCC in 643 patients (85%), Sarcomatoid feature was reported in 87 patients (11%).\u0026nbsp;Most patients underwent a nephrectomy (63%). The most frequent sites of metastases were\u0026nbsp;lungs (64%) and bones (36%).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eSix hundred and seven patients (80%) received PA as first-line therapy while 153 patients (20%) were treated with the NC combination, due to the different timing of availability of the two options, 184 patients (24%) had died at the time of analysis.\u0026nbsp;Baseline clinical and pathological characteristics of the overall population are shown in Table 1. Notably, patients receiving NC were enriched for poor prognostic features such as IMDC risk classification and presence of bone and liver metastasis.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eSurvival analysis\u0026nbsp;\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eIn the overall study population, the median OS and PFS were 52.2 months (95%CI 34.4−55.7) and 17.6 months (95%CI 15.4−22.7), respectively.\u0026nbsp;The median OS was 55.7 months (95%CI 31.7−55.7) in patients receiving PA and not reached (NR) (95%CI NR−NR) in patients receiving NC (P=.51,\u0026nbsp;Figure 1). The 1y-, 2y- and 3y-OS rates were 81% \u003cem\u003evs.\u003c/em\u003e 82% (P=.85), 68% \u003cem\u003evs\u003c/em\u003e. 74% (P=.61) and 56% \u003cem\u003evs\u003c/em\u003e. 64% (P=.24) for PA \u003cem\u003evs.\u003c/em\u003e NC, respectively.\u003c/p\u003e\n\u003cp\u003eMedian PFS, it was 16.2 months (95%CI 14.2−20.2) in patients receiving PA and 27.6 months (95%CI 23.2−51.5) in patients receiving NC (P=.003, Figure 1).\u0026nbsp;The 1y-, 2y- and 3y-PFS rates were 62% vs 77% (P=.02), 43% \u003cem\u003evs.\u003c/em\u003e 56% (P=.06) and 29% \u003cem\u003evs\u003c/em\u003e. 45% (P=.01) for PA \u003cem\u003evs.\u003c/em\u003e NC, respectively.\u003c/p\u003e\n\u003cp\u003eIn patients with good-risk features, the median OS was NR in both subgroups (P=.15), while the median PFS was 30.7 months (95%CI 23.7−35.0) for PA and NR (95%CI NR−NR) for NC (P=.05). In the intermediate risk subgroup, the median OS was 40.5 months (95%CI 29.0−55.7) for PA and NR (95%CI NR−NR) for NC (P=.11), with a significantly longer median PFS (31.3 months, 95%CI 27.6−40.6 vs 15.2 months, 95%CI 13.3−53.3, P=.004) in patients receiving NC (Figure 2). Finally, poor risk patients showed a median OS and PFS of 15.5 months (95%CI 12.4−22.1) and 7.8 months (95%CI 5.6−11.4) in those receiving PA and 22.1 months (95%CI 11.7−32.7, P=.86) and 15.4 months (95%CI 6.6−51.5, P=.18) in patients treated with NC.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eWe further stratified patients based on tumor histology. No significant differences were found in terms of OS in both patients with clear cell (PA: 55.7 months, 95%CI 55.7−55.7, NC: NR, 95%CI NR−NR, P=.74) and non-clear cell RCC histology (PA: 31.1 months, 95%CI 24.5−40.5, NC: 24.9 months, 95%CI 14.9−34.9, P=.98). On the other hand, we observed longer median PFS in patients with clear cell RCC histology treated with NC (31.3 months, 95%CI 23.2−51.5) compared to PA (17.1 months, 95%CI 23.2−51.5, P=.005, Figure S2).\u003c/p\u003e\n\u003cp\u003eIn the 87 patients with sarcomatoid feature, the median OS and PFS were NR (95%CI NR−NR) and 11.4 months (95%CI 4.1−28.0) for PA and 25.3 months (95%CI 8.3−34.4, P=.69) and 23.2 months (95%CI 5.5−23.2, P=.73) for NC.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eWe further stratified patients by site of metastasis, showing no differences in terms of median OS between patients treated by PA and NC with lung (NR, 95%CI NR−NR, \u003cem\u003evs.\u003c/em\u003e NR, 95%CI NR−NR, P=.37), liver (55.7 months, 95%CI 19.5−55.7, \u003cem\u003evs.\u003c/em\u003e 32.7 months, 95%CI 15.4−52.2, P=.86), or bone (29.0 months, 95%CI 23.6−55.7, \u003cem\u003evs\u003c/em\u003e. 22.1 months, 95%CI 14.9−40.0, P=.26) or brain metastases (29.0 months, 95%CI 15.4−40.5, \u003cem\u003evs\u003c/em\u003e. 11.7 months, 95%CI 1.3−11.7, P=.64).\u003c/p\u003e\n\u003cp\u003eMedian PFS, was significantly longer in patients with lung metastases treated with NC (15.4 months, 95%CI 13.4−18.0, \u003cem\u003evs.\u003c/em\u003e 40.6 months, 95%CI 16.6−51.5, P=.003, Figure S2), while no statistically significant differences were found in patients with bone (12.0 months, 95%CI 9.9−14.5,\u003cem\u003e\u0026nbsp;vs\u003c/em\u003e. 16.5 months, 95%CI 11.0−16.6, P=.19), liver (12.2 months, 95%CI 6.2−17.3, \u003cem\u003evs\u003c/em\u003e. 16.5 months, 95%CI 6.6−27.6, P=.38) or brain metastases (9.9 months, 95%CI 7.0−30.7 \u003cem\u003evs\u003c/em\u003e. 6.9 months, 95%CI 1.3−6.9, P=.78).\u003c/p\u003e\n\u003cp\u003eSubgroup analyses for OS and PFS are shown in Figure 3 and 4.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eResponse to first-line therapy\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eIn the overall study population, NC yielded higher ORR (59%\u003cem\u003e\u0026nbsp;vs.\u0026nbsp;\u003c/em\u003e49%, Table 2), as compared to PA, furthermore 7% CR, 52% PR, 27% SD and 14% PD were observed the former combination, as compared to 5% CR, 44% PR, 34% SD and 18% PD with PA. Notably enough, a statistically significant difference in terms of response to therapy in favor of NC was observed also in patients with good risk features (Table 2).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eSecond-line therapies\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eThree hundred and thirty-nine patients (45%) progressed during first-line therapy, 297 patients during PA and 42 patients with NC.\u0026nbsp;Of them, 206 patients (69%) and 18 patients (43%) received second-line therapies, respectively.\u0026nbsp;The median OS of the 224 patients who received second-line treatments was 31.1 months (95%CI 24.5−40.5) for PA and 40.0 months (95%CI 11.7−52.2) for NC (P=.75). Moreover, the median PFS2 was 20.7 months (95%CI 18.2−52.5) for PA and 21.8 months (95%CI 10.8−59.4) for NC (P=.48). The median OS of the 536 patients who did not receive second-line treatments was 55.7 months (95%CI 55.7−55.7) for PA and NR (95%CI NR−NR) for NC (P=.38).\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eUnivariate and Multivariate analyses\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eIn the overall study population, IMDC group, nephrectomy status, sarcomatoid differentiation, and the presence of bone, liver or brain metastases were correlated with both OS and PFS at multivariate analyses (Table 3). Interestingly, the choice of NC as first-line therapy was significantly associated with longer PFS at multivariate analysis (Table 3).\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eThe cornerstone of first-line therapy of mRCC has been TKI monotherapy for many years. However, a significant increase in survival rates has been reached using immune-based combinations. At present, for the first-line treatment of mRCC, international guidelines endorse the use of one of the following combinations: pembrolizumab plus axitinib or lenvatinib, and nivolumab plus cabozantinib or ipilimumab. As a whole, all these combinations, and the immune doublet in particular, proved to be less active and effective in good risk patients. PA, based on the outcomes of the Keynote-426 clinical trial, secured its position as the first approved combination therapy [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]. In this RCT, untreated metastatic RCC patients were randomized to receive either PA or sunitinib [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]. The PA group displayed a one-year OS rate of 89.9% alongside a PFS of 15.1 months and an ORR of 59.3%. Notably, the benefits of this combination extended across all subgroups, irrespective of programmed death-ligand 1 (PD-L1) expression or IMDC risk group. Upon an updated follow-up (with a median duration of 67.2 months), PA maintained an OS of 47.2 months and a PFS of 15.7 months. The experimental arm exhibited an ORR of 60.6%, a DCR of 83.3%, and a median duration of response of 23.6 months. The primary refractory rate was 17.0% in the PA group [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThe most recent combination added to the armamentarium is NC, based on the positive results of the phase III trial, CheckMate 9ER [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]. This trial investigated nivolumab in combination with cabozantinib as compared to sunitinib in treatment-na\u0026iuml;ve metastatic RCC patients, irrespective of PD-L1 expression or IMDC prognostic group [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]. In the initial analysis, NC achieved a PFS of 16.6 months, with a not reached OS. The ORR was reported at 55.7% [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. The subsequent update confirmed the superiority of NC over sunitinib, with a PFS of 16.6 months and an OS of 49.5 months within the intent-to-treat (ITT) population [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eNotably, no head-to-head randomized clinical trials have yet compared these therapeutic approaches, while several metanalysis have been performed, yielding conflicting results. Indeed, on one hand, Qual et al. and Riatz et al.'s meta-analyses suggested that NC may lead to the highest likelihood of delivering maximal OS [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e, \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]; on the other hand, the network meta-analysis conducted by Lombardi et al. after the release of updated KEYNOTE 426 results [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e] suggested that lenvatinib plus pembrolizumab had the highest probability of being the optimal treatment in terms of OS and PFS. However, among patients with sarcomatoid histology, NC demonstrated the highest rate in terms of survival outcomes.\u003c/p\u003e \u003cp\u003eTo our knowledge, this study represents the first real-world, observational, retrospective analysis comparing PA to NC in metastatic RCC patients. Our results showed a significantly longer median PFS with NC compared to PA (27.6 \u003cem\u003evs.\u003c/em\u003e 16.2 months, respectively), a huge difference, especially considering the longer follow-up available for the PA doublet.\u003c/p\u003e \u003cp\u003eIt's worth noting that the PFS observed with NC is longer than that reported in the CheckMate 9ER study, while the PFS recorded with PA is in line with the Keynote 426 results. On the contrary, no differences were observed in median OS.\u003c/p\u003e \u003cp\u003eIn our study, more patients with poor prognostic features (poor risk IMDC, bone and liver metastases) received NC, and this might partially explain why this combination yielded a clear ORR and PFS benefit, but no OS advantage in the overall population.\u003c/p\u003e \u003cp\u003eSubgroup analyses revealed PFS benefits for NC among intermediate-risk IMDC, clear cell RCC histology, and patients with lung metastases. Moreover, in younger patients (\u0026lt;\u0026thinsp;65 years) and in males, NC demonstrated superior PFS, as well as in patients who had undergone nephrectomy. Response rates favoured NC, especially in patients with good risk features, where CR rates almost reached 30%.\u003c/p\u003e \u003cp\u003eAlthough the use of an IO-TKI combination is recommended by most international guidelines also for the first line treatment of IMDC good risk mRCC patients, there is an open debate about the impact of immune checkpoint inhibitors in this population, since longer follow-up of registration trials has shown declining HRs for OS in this population [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e]. As a whole, our data suggest that this strategy should remain the preferred treatment. Outcomes in the second-line therapy setting showed no significant differences between treatment groups, findings consistent with previous real-world data [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. Multivariate analysis identified NC as a significant factor associated with longer PFS. Notably, contrary to prior data, there was no evidence for additional benefit with NC in the sarcomatoid subgroup.\u003c/p\u003e \u003cp\u003eDifferences in survival outcomes related to age and gender have been reported in the CheckMate 9ER trial, where young patients (\u0026lt;\u0026thinsp;65 years) and males showed a major OS benefit from NC, with no disparities in PFS. Furthermore, patients who had previously undergone nephrectomy benefited significantly in terms of OS, although not PFS, when treated with NC if compared to sunitinib. Notably, these subgroup differences were not highlighted in the Keynote 426 study.\u003c/p\u003e \u003cp\u003eIn the first-line setting, ICI-based combination therapy significantly reduced the risk of disease progression in both male and female patients compared to sunitinib alone, with no statistically significant differences in PFS and OS between gender [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]. Likely, prior nephrectomy did not appear to influence the efficacy of ICI in metastatic RCC [\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e]. Conversely, the OS benefit from first-line ICI-based combinations was notably more substantial in younger patients [\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eAmong the several limitations inherent in our study, the major one is related to its retrospective nature and subsequent bias, particularly considering the non-randomized allocation of patients; assignment of patients to one treatment group over the other might have been influenced by unmeasured or unaccounted-for factors, thereby potentially impacting the study outcomes. Additionally, only 20% of the patients here analyzed did receive the NC combination, the vast majority having been treated with PA, a difference which could have introduced another important bias in our analysis.\u003c/p\u003e \u003cp\u003eFurthermore, the proportion of patients receiving second-line therapy upon disease progression was higher among those initially treated with PA in the first line, realistically a time-lead bias related to the different timing of availability of the two combinations in clinical practice; obviously, this phenomenon could serve as a confounding factor affecting OS.\u003c/p\u003e \u003cp\u003eMoreover, the absence of data on safety in general, and on therapy management (dose modifications, treatment interruptions, \u003cem\u003eetc\u003c/em\u003e) hinders the ability to make a thorough comparison between the two-treatment regimen.\u003c/p\u003e \u003cp\u003eFinally, the lack of numerically adequate data relative to the third, and more recent, combination of PA, prevented us to perform a more comprehensive comparison between all the different standard treatment options presently available.\u003c/p\u003e \u003cp\u003eDespite all the above, given the lack of data directly comparing first-line therapeutic combinations in RCC, our study offers valuable insights for treatment decisions. Indeed, it suggests a potential advantage in terms of PFS when utilizing NC as a first-line treatment, both in the overall population and among specific subgroups.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eOur study represents the first real-world, observational, retrospective investigation comparing PA to NC in all treatment naive metastatic RCC patients. Although inevitably biased, our results showed a significantly longer median PFS with NC compared to PA, while no differences were observed in median OS. Subgroup analyses suggested a PFS benefits for NC in various mRCC subpopulations, and an ORR benefits in the good risk population.\u003c/p\u003e \u003cp\u003eAdditional indirect insights for treatment choice of first-line treatment between the two therapeutic regimens could be drawn from this study, although the lack of a prospective randomised comparisons between the two treatment options (which realistically will never be performed) remains a relevant drawback of this study to take into account.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eFunding:\u0026nbsp;\u003c/strong\u003eThe authors declare that no funds, grants, or other support were received during the preparation of this manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData Availability\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe data are available to researchers upon request by submitting a proposal in writing to the Principal Investigator of the ARON-1 study,\u0026nbsp;Dr Matteo Santoni, in the Oncology Unit, Macerata Hospital.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting Interest\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eMatteo Santoni has received research support and honoraria from Janssen, Bristol Myers Squibb, Ipsen, MSD, Astellas and Bayer, all unrelated to the present paper.\u003c/p\u003e\n\u003cp\u003eEnrique Grande has received honoraria for speaker engagements, advisory roles or funding of continuous medical education from Adacap, AMGEN, Angelini, Astellas, Astra Zeneca, Bayer, Blueprint, Bristol Myers Squibb, Caris Life Sciences, Celgene, Clovis-Oncology, Eisai, Eusa Pharma, Genetracer, Guardant Health, HRA-Pharma, IPSEN, ITM-Radiopharma, Janssen, Lexicon, Lilly, Merck KGaA, MSD, Nanostring Technologies, Natera, Novartis, ONCODNA (Biosequence), Palex, Pharmamar, Pierre Fabre, Pfizer, Roche, Sanofi-Genzyme, Servier, Taiho, and Thermo Fisher Scientific, he also has received research grants from Pfizer, Astra Zeneca, Astellas, and Lexicon Pharmaceuticals\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eR. Kanesvaran has received fees for speaker bureau and advisory board activities from the following companies: Pfizer, MSD, BMS, Eisai, Ipsen, Johnson and Johnson, Merck, Amgen, Astellas and Bayer.\u003c/p\u003e\n\u003cp\u003eTomas Buchler has received research support: AstraZeneca, Roche, Bristol Myers Squibb, Exelixis, Merck KGaA, MSD, and Novartis, consulting fees from Bristol Myers Squibb, Astellas, Janssen, and Sanofi/Aventis, payment or honoraria for lectures, presentations, speakers’ bureaus, manuscript writing, or educational events from Ipsen, Bristol-Myers Squibb, AstraZeneca, Roche, Servier, Accord, MSD, and Pfizer.\u003c/p\u003e\n\u003cp\u003eCamillo Porta has received honoraria from Angelini Pharma, AstraZeneca, BMS, Eisai, Ipsen and MSD and acted as a Protocol Steering Committee Member for BMS, Eisai and MSD.\u003c/p\u003e\n\u003cp\u003eAlfonso Gómez de Liaño has received\u0026nbsp;consulting fees from BMS, Ipsen, Merck, MSD, payment or honoraria for lectures, presentations, speakers’ bureaus, or educational events from BMS, Ipsen, MSD, Roche, and Pfizer, and research support (institution) from AstraZeneca, MSD and Roche.\u003c/p\u003e\n\u003cp\u003ePasquale Rescigno has served as a consultant/advisory board member for MSD, Astra Zeneca, Janssen, Pfizer and travel grant from Ipsen.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eLinda Cerbone has received honoraria for advisory boards, speaker engagements and scientific consultancy for educational purposes from AstraZeneca, EISAI, MSD, Ipsen, BMS, A.A.A., past MSD employee in Medical Affairs.\u003c/p\u003e\n\u003cp\u003eThe other authors declare to have no conflicts of interest.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor contributions:\u0026nbsp;\u003c/strong\u003eAll authors contributed to the study conception and design.\u0026nbsp;Material preparation, data collection and analysis were performed by \u003cstrong\u003eMatteo Santoni, Giandomenico Roviello, Enrique Grande, Ugo De Giorgi, Ondrej Fiala, Emmanuel Seront,\u0026nbsp;\u003c/strong\u003eJavier Molina-Cerrillo\u003cstrong\u003e, Renate Pichler, Zin W. Myint,\u0026nbsp;\u003c/strong\u003eJakub Kucharz, Ravindran Kanesvaran\u003cstrong\u003e,\u0026nbsp;\u003c/strong\u003eThomas Büttner\u003cstrong\u003e, Martin Pichler, Umberto Basso,\u0026nbsp;\u003c/strong\u003eJindrich Kopecky,\u0026nbsp;\u003cstrong\u003eMaria T. Bourlon, Linda Cerbone, Tomas Buchler, Alvaro Pinto, Alfonso\u0026nbsp;\u003c/strong\u003eGómez de Liaño\u003cstrong\u003e,\u0026nbsp;\u003c/strong\u003eCaterina Gianni,\u0026nbsp;\u003cstrong\u003eAnca Zgura, Pasquale Rescigno,\u0026nbsp;\u003c/strong\u003eJawaher Ansari, Orazio Caffo, Zsófia Küronya, Maria Giuseppa Vitale, Dipen Bhuva, Martina Catalano, Nuno Vau,\u0026nbsp;\u003cstrong\u003eRay Manneh Kopp, Sebastiano Buti,\u0026nbsp;\u003c/strong\u003eAristotelis Bamias\u003cstrong\u003e, Camillo Porta, Kaisa Sunela, and Francesco Massari\u003c/strong\u003e.\u0026nbsp;The first draft of the manuscript was written by \u003cstrong\u003eMatteo Santoni\u003c/strong\u003e and all authors commented on previous versions of the manuscript. All authors read and approved the final manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthic approval:\u003c/strong\u003e This study was performed in line with the principles of the Declaration of Helsinki. Approval was granted by the Ethics Committee of Marche (CERM) n. 1164/2020 and written informed consent was obtained from all participating patients.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent to participate:\u003c/strong\u003e Informed consent was obtained from all individual participants included in the study.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eSung H, Ferlay J, Siegel RL, et al (2021) Global Cancer Statistics 2020: GLOBOCAN Estimates of Incidence and Mortality Worldwide for 36 Cancers in 185 Countries. CA Cancer J Clin 71:209\u0026ndash;249. https://doi.org/10.3322/CAAC.21660\u003c/li\u003e\n\u003cli\u003eCheville JC, Lohse CM, Zincke H, et al (2003) Comparisons of outcome and prognostic features among histologic subtypes of renal cell carcinoma. Am J Surg Pathol 27:612\u0026ndash;624. https://doi.org/10.1097/00000478-200305000-00005\u003c/li\u003e\n\u003cli\u003eDabestani S, Thorstenson A, Lindblad P, et al (2016) Renal cell carcinoma recurrences and metastases in primary non-metastatic patients: a population-based study. World J Urol 34:1081\u0026ndash;1086. https://doi.org/10.1007/s00345-016-1773-y\u003c/li\u003e\n\u003cli\u003eMotzer RJ, Bacik J, Murphy BA, et al (2002) Interferon-Alfa as a Comparative Treatment for Clinical Trials of New Therapies Against Advanced Renal Cell Carcinoma. J Clin Oncol 20:289\u0026ndash;296. https://doi.org/10.1200/jco.2002.20.1.289\u003c/li\u003e\n\u003cli\u003eHeng DYC, Xie W, Regan MM, et al (2009) Prognostic factors for overall survival in patients with metastatic renal cell carcinoma treated with vascular endothelial growth factor-targeted agents: Results from a large, multicenter study. J Clin Oncol 27:5794\u0026ndash;5799. https://doi.org/10.1200/JCO.2008.21.4809\u003c/li\u003e\n\u003cli\u003eRini BI, Plimack ER, Stus V, et al (2019) Pembrolizumab plus Axitinib versus Sunitinib for Advanced Renal-Cell Carcinoma. N Engl J Med 380:1116\u0026ndash;1127. https://doi.org/10.1056/nejmoa1816714\u003c/li\u003e\n\u003cli\u003eChoueiri TK, Powles T, Burotto M, et al (2021) Nivolumab plus Cabozantinib versus Sunitinib for Advanced Renal-Cell Carcinoma. N Engl J Med 384:829\u0026ndash;841. https://doi.org/10.1056/nejmoa2026982\u003c/li\u003e\n\u003cli\u003eMotzer R, Alekseev B, Rha S-Y, et al (2021) Lenvatinib plus Pembrolizumab or Everolimus for Advanced Renal Cell Carcinoma. N Engl J Med 384:1289\u0026ndash;1300. https://doi.org/10.1056/nejmoa2035716\u003c/li\u003e\n\u003cli\u003eMotzer RJ, Penkov K, Haanen J, et al (2019) Avelumab plus Axitinib versus Sunitinib for Advanced Renal-Cell Carcinoma. N Engl J Med 380:1103\u0026ndash;1115. https://doi.org/10.1056/nejmoa1816047\u003c/li\u003e\n\u003cli\u003eMotzer RJ, Tannir NM, McDermott DF, et al (2018) Nivolumab plus Ipilimumab versus Sunitinib in Advanced Renal-Cell Carcinoma. N Engl J Med 378:1277\u0026ndash;1290. https://doi.org/10.1056/nejmoa1712126\u003c/li\u003e\n\u003cli\u003eShah NJ, Sura SD, Shinde R, et al (2023) Real-world Treatment Patterns and Clinical Outcomes for Metastatic Renal Cell Carcinoma in the Current Treatment Era. Eur Urol Open Sci 49:110. https://doi.org/10.1016/J.EUROS.2022.12.015\u003c/li\u003e\n\u003cli\u003eSantoni M, Massari F, Myint ZW, et al (2023) Global Real-World Outcomes of Patients Receiving Immuno-Oncology Combinations for Advanced Renal Cell Carcinoma: The ARON-1 Study. Target Oncol 18:559\u0026ndash;570. https://doi.org/10.1007/s11523-023-00978-2\u003c/li\u003e\n\u003cli\u003eSantoni M, Massari F, Myint ZW, et al (2023) Clinico-Pathological Features Influencing the Prognostic Role of Body Mass Index in Patients With Advanced Renal Cell Carcinoma Treated by Immuno-Oncology Combinations (ARON-1). Clin Genitourin Cancer 309\u0026ndash;320. https://doi.org/10.1016/j.clgc.2023.03.006\u003c/li\u003e\n\u003cli\u003eSantoni M, Buti S, Myint ZW, et al (2023) Real-world Outcome of Patients with Advanced Renal Cell Carcinoma and Intermediate- or Poor-risk International Metastatic Renal Cell Carcinoma Database Consortium Criteria Treated by Immune-oncology Combinations: Differential Effectiveness by Risk Group? Eur Urol Oncol. https://doi.org/10.1016/j.euo.2023.07.003\u003c/li\u003e\n\u003cli\u003ePorta C, Bamias A, Zakopoulou R, et al (2023) Geographical differences in the management of metastatic de novo renal cell carcinoma in the era of immune-combinations. Minerva Urol Nephrol 75:460\u0026ndash;470. https://doi.org/10.23736/S2724-6051.23.05369-7\u003c/li\u003e\n\u003cli\u003eSchwartz LH, Liti\u0026egrave;re S, De Vries E, et al (2016) RECIST 1.1 - Update and clarification: From the RECIST committee. Eur J Cancer 62:132\u0026ndash;137. https://doi.org/10.1016/j.ejca.2016.03.081\u003c/li\u003e\n\u003cli\u003eFDA approves pembrolizumab plus axitinib for advanced renal cell carcinoma. Case Med Res. https://doi.org/10.31525/fda1-ucm636395.htm\u003c/li\u003e\n\u003cli\u003eRini BI, Plimack ER, Stus V, et al (2019) Pembrolizumab plus Axitinib versus Sunitinib for Advanced Renal-Cell Carcinoma. N Engl J Med 380:1116\u0026ndash;1127. https://doi.org/10.1056/nejmoa1816714\u003c/li\u003e\n\u003cli\u003eRini BI, Plimack ER, Stus V, et al (2023) Pembrolizumab plus axitinib versus sunitinib as first-line therapy for advanced clear cell renal cell carcinoma: 5-year analysis of KEYNOTE-426. J Clin Oncol 41:LBA4501\u0026ndash;LBA4501. https://doi.org/10.1200/JCO.2023.41.17_SUPPL.LBA4501\u003c/li\u003e\n\u003cli\u003eFDA Approves Nivolumab Plus Cabozantinib for Advanced Renal Cell Carcinoma - The ASCO Post. https://ascopost.com/issues/february-10-2021/fda-approves-nivolumab-plus-cabozantinib-for-advanced-renal-cell-carcinoma/. Accessed 27 Oct 2023\u003c/li\u003e\n\u003cli\u003eChoueiri TK, Powles T, Burotto M, et al (2021) Nivolumab plus Cabozantinib versus Sunitinib for Advanced Renal-Cell Carcinoma. N Engl J Med 384:829\u0026ndash;841. https://doi.org/10.1056/nejmoa2026982\u003c/li\u003e\n\u003cli\u003eChoueiri TK, Powles T, Burotto M, et al (2020) 696O_PR Nivolumab + cabozantinib vs sunitinib in first-line treatment for advanced renal cell carcinoma: First results from the randomized phase III CheckMate 9ER trial. Ann Oncol 31:S1159. https://doi.org/10.1016/j.annonc.2020.08.2257\u003c/li\u003e\n\u003cli\u003eBurotto M, Powles T, Escudier B, et al (2023) Nivolumab plus cabozantinib vs sunitinib for first-line treatment of advanced renal cell carcinoma (aRCC): 3-year follow-up from the phase 3 CheckMate 9ER trial. J Clin Oncol 41:603\u0026ndash;603. https://doi.org/10.1200/JCO.2023.41.6_suppl.603\u003c/li\u003e\n\u003cli\u003eQuhal F, Mori K, Bruchbacher A, et al (2021) First-line Immunotherapy-based Combinations for Metastatic Renal Cell Carcinoma: A Systematic Review and Network Meta-analysis. Eur Urol Oncol 4:755\u0026ndash;765. https://doi.org/10.1016/j.euo.2021.03.001\u003c/li\u003e\n\u003cli\u003eRiaz I Bin, He H, Ryu AJ, et al (2021) A Living, Interactive Systematic Review and Network Meta-analysis of First-line Treatment of Metastatic Renal Cell Carcinoma[Formula presented]. Eur. Urol. 80:712\u0026ndash;723\u003c/li\u003e\n\u003cli\u003eLombardi P, Filetti M, Falcone R, et al (2022) New first-line immunotherapy-based combinations for metastatic renal cell carcinoma: A systematic review and network meta-analysis. Cancer Treat Rev 106:102377. https://doi.org/10.1016/j.ctrv.2022.102377\u003c/li\u003e\n\u003cli\u003eCatalano M, Procopio G, Sepe P, et al (2023) Tyrosine kinase and immune checkpoints inhibitors in favorable risk metastatic renal cell carcinoma: Trick or treat? Pharmacol Ther 249:. https://doi.org/10.1016/J.PHARMTHERA.2023.108499\u003c/li\u003e\n\u003cli\u003eYanagisawa T, Kawada T, Quhal F, et al (2023) Impact of sex on the efficacy of immune checkpoint inhibitors in kidney and urothelial cancers: a systematic review and meta-analysis. World J Urol 41:1763\u0026ndash;1774. https://doi.org/10.1007/s00345-023-04412-0\u003c/li\u003e\n\u003cli\u003eSatkunasivam R, Guzman JC, Klaassen Z, et al (2022) Association between prior nephrectomy and efficacy of immune checkpoint inhibitor therapy in metastatic renal cell carcinoma - A systematic review and meta-analysis. Urol Oncol Semin Orig Investig 40:64.e17-64.e24. https://doi.org/10.1016/j.urolonc.2021.09.009\u003c/li\u003e\n\u003cli\u003eYanagisawa T, Quhal F, Kawada T, et al (2023) Association between age and efficacy of first-line immunotherapy-based combination therapies for mRCC: a meta-analysis. Immunotherapy 15:. https://doi.org/10.2217/IMT-2023-0039\u003c/li\u003e\n\u003c/ol\u003e"},{"header":"Tables","content":"\u003cp\u003e\u003cstrong\u003eTable 1.\u0026nbsp;\u003c/strong\u003eBaseline patients\u0026rsquo; characteristics.\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"680\" style=\"margin-right: calc(0%); width: 100%;\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"29.11764705882353%\" valign=\"top\" style=\"width: 36.5625%;\"\u003e\n \u003cp\u003e\u003cstrong\u003ePatients\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.970588235294118%\" valign=\"top\" style=\"width: 15.5625%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eOverall\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e760 (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.941176470588236%\" valign=\"top\" style=\"width: 17.3691%;\"\u003e\n \u003cp\u003e\u003cstrong\u003ePembrolizumab + Axitinib\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e607 (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.470588235294116%\" valign=\"top\" style=\"width: 17.9766%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eNivolumab + Cabozantinib\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e153 (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.5%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eP\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"29.11764705882353%\" valign=\"top\" style=\"width: 36.5625%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eGender\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003eMale\u003c/p\u003e\n \u003cp\u003eFemale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.970588235294118%\" style=\"width: 15.5625%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e557 (73)\u003c/p\u003e\n \u003cp\u003e203 (27)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.941176470588236%\" style=\"width: 17.3691%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e447 (74)\u003c/p\u003e\n \u003cp\u003e160 (26)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.470588235294116%\" style=\"width: 17.9766%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e110 (72)\u003c/p\u003e\n \u003cp\u003e43 (28)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.5%\"\u003e\n \u003cp\u003e.75\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"29.11764705882353%\" valign=\"top\" style=\"width: 36.5625%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eAge, years (y)\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003eRange\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.970588235294118%\" style=\"width: 15.5625%;\"\u003e\n \u003cp\u003e64\u003c/p\u003e\n \u003cp\u003e29 \u0026minus; 88\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.941176470588236%\" style=\"width: 17.3691%;\"\u003e\n \u003cp\u003e65\u003c/p\u003e\n \u003cp\u003e34 \u0026minus; 88\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.470588235294116%\" style=\"width: 17.9766%;\"\u003e\n \u003cp\u003e64\u003c/p\u003e\n \u003cp\u003e29 \u0026minus; 87\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.5%\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"29.11764705882353%\" valign=\"top\" style=\"width: 36.5625%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eMetastatic at diagnosis\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.970588235294118%\" style=\"width: 15.5625%;\"\u003e\n \u003cp\u003e415 (55)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.941176470588236%\" style=\"width: 17.3691%;\"\u003e\n \u003cp\u003e338 (56)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.470588235294116%\" style=\"width: 17.9766%;\"\u003e\n \u003cp\u003e77 (50)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.5%\"\u003e\n \u003cp\u003e.48\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"29.11764705882353%\" valign=\"top\" style=\"width: 36.5625%;\"\u003e\n \u003cp\u003e\u003cstrong\u003ePrior nephrectomy\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.970588235294118%\" style=\"width: 15.5625%;\"\u003e\n \u003cp\u003e477 (63)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.941176470588236%\" style=\"width: 17.3691%;\"\u003e\n \u003cp\u003e382 (63)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.470588235294116%\" style=\"width: 17.9766%;\"\u003e\n \u003cp\u003e95 (62)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.5%\"\u003e\n \u003cp\u003e.88\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"29.11764705882353%\" valign=\"top\" style=\"width: 36.5625%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eClear cell histology\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.970588235294118%\" style=\"width: 15.5625%;\"\u003e\n \u003cp\u003e643 (85)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.941176470588236%\" style=\"width: 17.3691%;\"\u003e\n \u003cp\u003e513 (85)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.470588235294116%\" style=\"width: 17.9766%;\"\u003e\n \u003cp\u003e130 (85)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.5%\"\u003e\n \u003cp\u003e\u0026gt;.99\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"29.11764705882353%\" valign=\"top\" style=\"width: 36.5625%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSarcomatoid feature\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.970588235294118%\" style=\"width: 15.5625%;\"\u003e\n \u003cp\u003e87 (11)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.941176470588236%\" style=\"width: 17.3691%;\"\u003e\n \u003cp\u003e67 (11)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.470588235294116%\" style=\"width: 17.9766%;\"\u003e\n \u003cp\u003e20 (13)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.5%\"\u003e\n \u003cp\u003e.66\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"29.11764705882353%\" valign=\"top\" style=\"width: 36.5625%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eIMDC risk stratification\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003eFavorable risk\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eIntermediate risk\u003c/p\u003e\n \u003cp\u003ePoor risk\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.970588235294118%\" style=\"width: 15.5625%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e163 (22)\u003c/p\u003e\n \u003cp\u003e413 (55)\u003c/p\u003e\n \u003cp\u003e184 (23)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.941176470588236%\" style=\"width: 17.3691%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e130 (21)\u003c/p\u003e\n \u003cp\u003e343 (57)\u003c/p\u003e\n \u003cp\u003e134 (22)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.470588235294116%\" style=\"width: 17.9766%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e33 (22)\u003c/p\u003e\n \u003cp\u003e70 (46)\u003c/p\u003e\n \u003cp\u003e50 (32)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.5%\"\u003e\n \u003cp\u003e.21\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"29.11764705882353%\" valign=\"top\" style=\"width: 36.5625%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCommon sites of metastasis\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003eLung\u003c/p\u003e\n \u003cp\u003eBone\u003c/p\u003e\n \u003cp\u003eLiver\u003c/p\u003e\n \u003cp\u003eBrain\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.970588235294118%\" style=\"width: 15.5625%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e483 (64)\u003c/p\u003e\n \u003cp\u003e271 (36)\u003c/p\u003e\n \u003cp\u003e139 (18)\u003c/p\u003e\n \u003cp\u003e57 (8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.941176470588236%\" style=\"width: 17.3691%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e384 (63)\u003c/p\u003e\n \u003cp\u003e203 (33)\u003c/p\u003e\n \u003cp\u003e102 (17)\u003c/p\u003e\n \u003cp\u003e47 (8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.470588235294116%\" style=\"width: 17.9766%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e99 (65)\u003c/p\u003e\n \u003cp\u003e68 (44)\u003c/p\u003e\n \u003cp\u003e37 (24)\u003c/p\u003e\n \u003cp\u003e7 (5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.5%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e.76\u003c/p\u003e\n \u003cp\u003e.11\u003c/p\u003e\n \u003cp\u003e.22\u003c/p\u003e\n \u003cp\u003e.39\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"29.11764705882353%\" valign=\"top\" style=\"width: 36.5625%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eMedian follow-up\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.970588235294118%\" style=\"width: 15.5625%;\"\u003e\n \u003cp\u003e17.0 months\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.941176470588236%\" style=\"width: 17.3691%;\"\u003e\n \u003cp\u003e18.3 months\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.470588235294116%\" style=\"width: 17.9766%;\"\u003e\n \u003cp\u003e15.1 months\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.5%\"\u003e\n \u003cp\u003e.38\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"29.11764705882353%\" valign=\"top\" style=\"width: 36.5625%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSecond-line therapies\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.970588235294118%\" style=\"width: 15.5625%;\"\u003e\n \u003cp\u003e224 (29)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.941176470588236%\" style=\"width: 17.3691%;\"\u003e\n \u003cp\u003e206 (34)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.470588235294116%\" style=\"width: 17.9766%;\"\u003e\n \u003cp\u003e18 (12)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.5%\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"29.11764705882353%\" valign=\"top\" style=\"width: 36.5625%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eType of second-line therapy\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003eCabozantinib\u003c/p\u003e\n \u003cp\u003eSunitinib\u003c/p\u003e\n \u003cp\u003eClinical Trials\u003c/p\u003e\n \u003cp\u003eOther\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.970588235294118%\" style=\"width: 15.5625%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e191 (25)\u003c/p\u003e\n \u003cp\u003e15 (2)\u003c/p\u003e\n \u003cp\u003e7 (1)\u003c/p\u003e\n \u003cp\u003e11 (1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.941176470588236%\" style=\"width: 17.3691%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e191 (31)\u003c/p\u003e\n \u003cp\u003e0 (0)\u003c/p\u003e\n \u003cp\u003e4 (1)\u003c/p\u003e\n \u003cp\u003e11 (2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.470588235294116%\" style=\"width: 17.9766%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e0 (0)\u003c/p\u003e\n \u003cp\u003e15 (10)\u003c/p\u003e\n \u003cp\u003e3 (2)\u003c/p\u003e\n \u003cp\u003e0 (0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.5%\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"100%\" colspan=\"5\" valign=\"top\"\u003e\n \u003cp\u003eIMDC: International Metastatic RCC Database Consortium\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 2.\u0026nbsp;\u003c/strong\u003eResponse to therapy in RCC patients stratified by type of first-line therapy and IMDC group.\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"642\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"30.793157076205286%\" valign=\"top\" style=\"width: 42.9055%;\"\u003e\n \u003cp\u003e\u003cstrong\u003ePatients\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.81959564541213%\" valign=\"top\" style=\"width: 12.5462%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eOverall\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e(%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.63919129082426%\" valign=\"top\" style=\"width: 19.0056%;\"\u003e\n \u003cp\u003e\u003cstrong\u003ePembrolizumab + Axitinib\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e(%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.48367029548989%\" valign=\"top\" style=\"width: 14.2523%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eNivolumab + Cabozantinib\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e(%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.26438569206843%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003ep\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"30.793157076205286%\" valign=\"top\" style=\"width: 42.9055%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eOverall Study Population\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003eComplete Response\u003c/p\u003e\n \u003cp\u003ePartial Response\u003c/p\u003e\n \u003cp\u003eStable Disease\u003c/p\u003e\n \u003cp\u003eProgressive Disease\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.81959564541213%\" valign=\"top\" style=\"width: 12.5462%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003cp\u003e45\u003c/p\u003e\n \u003cp\u003e33\u003c/p\u003e\n \u003cp\u003e17\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.63919129082426%\" valign=\"top\" style=\"width: 19.0056%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003cp\u003e44\u003c/p\u003e\n \u003cp\u003e34\u003c/p\u003e\n \u003cp\u003e18\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.48367029548989%\" valign=\"top\" style=\"width: 14.2523%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e7\u003c/p\u003e\n \u003cp\u003e52\u003c/p\u003e\n \u003cp\u003e27\u003c/p\u003e\n \u003cp\u003e14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.26438569206843%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e.51\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"30.793157076205286%\" valign=\"top\" style=\"width: 42.9055%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eIMDC Good Risk \u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003eComplete Response\u003c/p\u003e\n \u003cp\u003ePartial Response\u003c/p\u003e\n \u003cp\u003eStable Disease\u003c/p\u003e\n \u003cp\u003eProgressive Disease\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.81959564541213%\" valign=\"top\" style=\"width: 12.5462%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e10\u003c/p\u003e\n \u003cp\u003e49\u003c/p\u003e\n \u003cp\u003e40\u003c/p\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.63919129082426%\" valign=\"top\" style=\"width: 19.0056%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e7\u003c/p\u003e\n \u003cp\u003e49\u003c/p\u003e\n \u003cp\u003e36\u003c/p\u003e\n \u003cp\u003e8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.48367029548989%\" valign=\"top\" style=\"width: 14.2523%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e27\u003c/p\u003e\n \u003cp\u003e53\u003c/p\u003e\n \u003cp\u003e20\u003c/p\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.26438569206843%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"30.793157076205286%\" valign=\"top\" style=\"width: 42.9055%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eIMDC Intermediate Risk \u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003eComplete Response\u003c/p\u003e\n \u003cp\u003ePartial Response\u003c/p\u003e\n \u003cp\u003eStable Disease\u003c/p\u003e\n \u003cp\u003eProgressive Disease\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.81959564541213%\" valign=\"top\" style=\"width: 12.5462%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003cp\u003e44\u003c/p\u003e\n \u003cp\u003e34\u003c/p\u003e\n \u003cp\u003e17\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.63919129082426%\" valign=\"top\" style=\"width: 19.0056%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003cp\u003e42\u003c/p\u003e\n \u003cp\u003e37\u003c/p\u003e\n \u003cp\u003e16\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.48367029548989%\" valign=\"top\" style=\"width: 14.2523%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003cp\u003e46\u003c/p\u003e\n \u003cp\u003e31\u003c/p\u003e\n \u003cp\u003e19\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.26438569206843%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e.78\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"30.793157076205286%\" valign=\"top\" style=\"width: 42.9055%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eIMDC Poor Risk \u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003eComplete Response\u003c/p\u003e\n \u003cp\u003ePartial Response\u003c/p\u003e\n \u003cp\u003eStable Disease\u003c/p\u003e\n \u003cp\u003eProgressive Disease\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.81959564541213%\" valign=\"top\" style=\"width: 12.5462%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003cp\u003e45\u003c/p\u003e\n \u003cp\u003e24\u003c/p\u003e\n \u003cp\u003e30\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.63919129082426%\" valign=\"top\" style=\"width: 19.0056%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003cp\u003e43\u003c/p\u003e\n \u003cp\u003e25\u003c/p\u003e\n \u003cp\u003e30\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.48367029548989%\" valign=\"top\" style=\"width: 14.2523%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003cp\u003e50\u003c/p\u003e\n \u003cp\u003e19\u003c/p\u003e\n \u003cp\u003e31\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.26438569206843%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e.33\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"100%\" colspan=\"5\" valign=\"top\"\u003e\n \u003cp\u003eIMDC: International Metastatic RCC Database Consortium\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 3.\u0026nbsp;\u003c/strong\u003eUnivariate and multivariate analyses.\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"679\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"38.70014771048744%\" rowspan=\"2\" valign=\"top\" style=\"width: 29.3988%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eOverall Survival\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"29.246676514032497%\" colspan=\"2\" valign=\"top\" style=\"width: 35.0889%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eUnivariate Cox Regression\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"32.05317577548006%\" colspan=\"2\" valign=\"top\" style=\"width: 15.055%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eMultivariate Cox Regression\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"29.567307692307693%\" valign=\"top\" style=\"width: 21.6935%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eHR (95%CI)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.26923076923077%\" valign=\"top\" style=\"width: 13.3954%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003ep-value\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"33.41346153846154%\" valign=\"top\" style=\"width: 10.5504%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eHR (95%CI)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.75%\" valign=\"top\" style=\"width: 4.5047%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003ep-value\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"38.64306784660767%\" valign=\"top\" style=\"width: 29.3988%;\"\u003e\n \u003cp\u003eGender (females vs males)\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.141592920353983%\" valign=\"top\" style=\"width: 21.6935%;\"\u003e\n \u003cp\u003e1.17 (0.84\u0026minus;1.63)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.2094395280236%\" valign=\"top\" style=\"width: 13.3954%;\"\u003e\n \u003cp\u003e.34\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.50147492625369%\" valign=\"top\" style=\"width: 10.5504%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.504424778761061%\" valign=\"top\" style=\"width: 4.5047%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"38.64306784660767%\" valign=\"top\" style=\"width: 29.3988%;\"\u003e\n \u003cp\u003eAge (\u0026ge;65y vs \u0026lt;65y)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.141592920353983%\" valign=\"top\" style=\"width: 21.6935%;\"\u003e\n \u003cp\u003e1.47 (1.10\u0026minus;1.97)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.2094395280236%\" valign=\"top\" style=\"width: 13.3954%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e.009\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.50147492625369%\" valign=\"top\" style=\"width: 10.5504%;\"\u003e\n \u003cp\u003e1.85 (1.36\u0026minus;2.51)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.504424778761061%\" valign=\"top\" style=\"width: 4.5047%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"38.64306784660767%\" valign=\"top\" style=\"width: 29.3988%;\"\u003e\n \u003cp\u003eIMDC prognostic group\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.141592920353983%\" valign=\"top\" style=\"width: 21.6935%;\"\u003e\n \u003cp\u003e3.13 (2.47\u0026minus;3.97)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.2094395280236%\" valign=\"top\" style=\"width: 13.3954%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.50147492625369%\" valign=\"top\" style=\"width: 10.5504%;\"\u003e\n \u003cp\u003e2.66 (2.03\u0026minus;3.48)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.504424778761061%\" valign=\"top\" style=\"width: 4.5047%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"38.64306784660767%\" valign=\"top\" style=\"width: 29.3988%;\"\u003e\n \u003cp\u003eNephrectomy (yes vs no)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.141592920353983%\" valign=\"top\" style=\"width: 21.6935%;\"\u003e\n \u003cp\u003e0.40 (0.30\u0026minus;0.54)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.2094395280236%\" valign=\"top\" style=\"width: 13.3954%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.50147492625369%\" valign=\"top\" style=\"width: 10.5504%;\"\u003e\n \u003cp\u003e0.60 (0.43\u0026minus;0.83)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.504424778761061%\" valign=\"top\" style=\"width: 4.5047%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e.002\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"38.64306784660767%\" valign=\"top\" style=\"width: 29.3988%;\"\u003e\n \u003cp\u003eHistology (ccRCC vs nccRCC)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.141592920353983%\" valign=\"top\" style=\"width: 21.6935%;\"\u003e\n \u003cp\u003e1.41 (0.97\u0026minus;2.04)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.2094395280236%\" valign=\"top\" style=\"width: 13.3954%;\"\u003e\n \u003cp\u003e.06\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.50147492625369%\" valign=\"top\" style=\"width: 10.5504%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.504424778761061%\" valign=\"top\" style=\"width: 4.5047%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"38.64306784660767%\" valign=\"top\" style=\"width: 29.3988%;\"\u003e\n \u003cp\u003eSarcomatoid features (yes vs no)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.141592920353983%\" valign=\"top\" style=\"width: 21.6935%;\"\u003e\n \u003cp\u003e1.82 (1.23\u0026minus;2.68)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.2094395280236%\" valign=\"top\" style=\"width: 13.3954%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e.02\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.50147492625369%\" valign=\"top\" style=\"width: 10.5504%;\"\u003e\n \u003cp\u003e1,75 (1.18\u0026minus;2.60)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.504424778761061%\" valign=\"top\" style=\"width: 4.5047%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e.005\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"38.64306784660767%\" valign=\"top\" style=\"width: 29.3988%;\"\u003e\n \u003cp\u003eLung metastases (yes vs no)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.141592920353983%\" valign=\"top\" style=\"width: 21.6935%;\"\u003e\n \u003cp\u003e1.11 (0.82\u0026minus;1.51)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.2094395280236%\" valign=\"top\" style=\"width: 13.3954%;\"\u003e\n \u003cp\u003e.50\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.50147492625369%\" valign=\"top\" style=\"width: 10.5504%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.504424778761061%\" valign=\"top\" style=\"width: 4.5047%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"38.64306784660767%\" valign=\"top\" style=\"width: 29.3988%;\"\u003e\n \u003cp\u003eBone metastases (yes vs no)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.141592920353983%\" valign=\"top\" style=\"width: 21.6935%;\"\u003e\n \u003cp\u003e2.02 (1.52-2.70)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.2094395280236%\" valign=\"top\" style=\"width: 13.3954%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.50147492625369%\" valign=\"top\" style=\"width: 10.5504%;\"\u003e\n \u003cp\u003e1.54 (1.13\u0026minus;2.09)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.504424778761061%\" valign=\"top\" style=\"width: 4.5047%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e.006\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"38.64306784660767%\" valign=\"top\" style=\"width: 29.3988%;\"\u003e\n \u003cp\u003eLiver metastases (yes vs no)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.141592920353983%\" valign=\"top\" style=\"width: 21.6935%;\"\u003e\n \u003cp\u003e1.77 (1.29\u0026minus;2.42)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.2094395280236%\" valign=\"top\" style=\"width: 13.3954%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.50147492625369%\" valign=\"top\" style=\"width: 10.5504%;\"\u003e\n \u003cp\u003e1.44 (1.03\u0026minus;2.01)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.504424778761061%\" valign=\"top\" style=\"width: 4.5047%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e.032\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"38.64306784660767%\" valign=\"top\" style=\"width: 29.3988%;\"\u003e\n \u003cp\u003eBrain metastases (yes vs no)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.141592920353983%\" valign=\"top\" style=\"width: 21.6935%;\"\u003e\n \u003cp\u003e2.05 (1.34\u0026minus;3.16)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.2094395280236%\" valign=\"top\" style=\"width: 13.3954%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.50147492625369%\" valign=\"top\" style=\"width: 10.5504%;\"\u003e\n \u003cp\u003e1.86 (1.17\u0026minus;2.96)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.504424778761061%\" valign=\"top\" style=\"width: 4.5047%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e.009\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"38.64306784660767%\" valign=\"top\" style=\"width: 29.3988%;\"\u003e\n \u003cp\u003eNivolumab/Cabozantinib vs Pembrolizumab/Axitinib\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.141592920353983%\" valign=\"top\" style=\"width: 21.6935%;\"\u003e\n \u003cp\u003e0.87 (0.58\u0026minus;1.31)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.2094395280236%\" valign=\"top\" style=\"width: 13.3954%;\"\u003e\n \u003cp\u003e.51\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.50147492625369%\" valign=\"top\" style=\"width: 10.5504%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.504424778761061%\" valign=\"top\" style=\"width: 4.5047%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"38.64306784660767%\" valign=\"top\" style=\"width: 29.3988%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"61.35693215339233%\" colspan=\"4\" valign=\"top\" style=\"width: 50.9738%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"38.70014771048744%\" rowspan=\"2\" valign=\"top\" style=\"width: 29.3988%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eProgression-Free Survival\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"29.246676514032497%\" colspan=\"2\" valign=\"top\" style=\"width: 35.0889%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eUnivariate Cox Regression\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"32.05317577548006%\" colspan=\"2\" valign=\"top\" style=\"width: 15.055%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eMultivariate Cox regression\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"29.567307692307693%\" valign=\"top\" style=\"width: 21.6935%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eHR (95%CI)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.26923076923077%\" valign=\"top\" style=\"width: 13.3954%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003ep-value\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"33.41346153846154%\" valign=\"top\" style=\"width: 10.5504%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eHR (95%CI)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.75%\" valign=\"top\" style=\"width: 4.5047%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003ep-value\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"38.64306784660767%\" valign=\"top\" style=\"width: 29.3988%;\"\u003e\n \u003cp\u003eGender (females vs males)\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.141592920353983%\" valign=\"top\" style=\"width: 21.6935%;\"\u003e\n \u003cp\u003e1.25 (0.98\u0026minus;1.59)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.2094395280236%\" valign=\"top\" style=\"width: 13.3954%;\"\u003e\n \u003cp\u003e.07\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.50147492625369%\" valign=\"top\" style=\"width: 10.5504%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.504424778761061%\" valign=\"top\" style=\"width: 4.5047%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"38.64306784660767%\" valign=\"top\" style=\"width: 29.3988%;\"\u003e\n \u003cp\u003eAge (\u0026ge;65y vs \u0026lt;65y)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.141592920353983%\" valign=\"top\" style=\"width: 21.6935%;\"\u003e\n \u003cp\u003e1.05 (0.84\u0026minus;1.31)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.2094395280236%\" valign=\"top\" style=\"width: 13.3954%;\"\u003e\n \u003cp\u003e.68\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.50147492625369%\" valign=\"top\" style=\"width: 10.5504%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.504424778761061%\" valign=\"top\" style=\"width: 4.5047%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"38.64306784660767%\" valign=\"top\" style=\"width: 29.3988%;\"\u003e\n \u003cp\u003eIMDC prognostic group\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.141592920353983%\" valign=\"top\" style=\"width: 21.6935%;\"\u003e\n \u003cp\u003e1.78 (1.52\u0026minus;2.10)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.2094395280236%\" valign=\"top\" style=\"width: 13.3954%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.50147492625369%\" valign=\"top\" style=\"width: 10.5504%;\"\u003e\n \u003cp\u003e1.54 (1.27\u0026minus;1.86)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.504424778761061%\" valign=\"top\" style=\"width: 4.5047%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"38.64306784660767%\" valign=\"top\" style=\"width: 29.3988%;\"\u003e\n \u003cp\u003eNephrectomy (yes vs no)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.141592920353983%\" valign=\"top\" style=\"width: 21.6935%;\"\u003e\n \u003cp\u003e0.51 (0.41\u0026minus;0.64)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.2094395280236%\" valign=\"top\" style=\"width: 13.3954%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.50147492625369%\" valign=\"top\" style=\"width: 10.5504%;\"\u003e\n \u003cp\u003e0.63 (0.49\u0026minus;0.81)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.504424778761061%\" valign=\"top\" style=\"width: 4.5047%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"38.64306784660767%\" valign=\"top\" style=\"width: 29.3988%;\"\u003e\n \u003cp\u003eHistology (ccRCC vs nccRCC)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.141592920353983%\" valign=\"top\" style=\"width: 21.6935%;\"\u003e\n \u003cp\u003e1.40 (1.06\u0026minus;1.85)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.2094395280236%\" valign=\"top\" style=\"width: 13.3954%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e.01\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.50147492625369%\" valign=\"top\" style=\"width: 10.5504%;\"\u003e\n \u003cp\u003e1.14 (0.85\u0026minus;1.52)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.504424778761061%\" valign=\"top\" style=\"width: 4.5047%;\"\u003e\n \u003cp\u003e.38\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"38.64306784660767%\" valign=\"top\" style=\"width: 29.3988%;\"\u003e\n \u003cp\u003eSarcomatoid features (yes vs no)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.141592920353983%\" valign=\"top\" style=\"width: 21.6935%;\"\u003e\n \u003cp\u003e1.59 (1.16\u0026minus;2.18)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.2094395280236%\" valign=\"top\" style=\"width: 13.3954%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e.004\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.50147492625369%\" valign=\"top\" style=\"width: 10.5504%;\"\u003e\n \u003cp\u003e1.53 (1.11\u0026minus;2.11)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.504424778761061%\" valign=\"top\" style=\"width: 4.5047%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e.008\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"38.64306784660767%\" valign=\"top\" style=\"width: 29.3988%;\"\u003e\n \u003cp\u003eLung metastases (yes vs no)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.141592920353983%\" valign=\"top\" style=\"width: 21.6935%;\"\u003e\n \u003cp\u003e1.13 (0.83\u0026minus;1.54)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.2094395280236%\" valign=\"top\" style=\"width: 13.3954%;\"\u003e\n \u003cp\u003e.43\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.50147492625369%\" valign=\"top\" style=\"width: 10.5504%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.504424778761061%\" valign=\"top\" style=\"width: 4.5047%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"38.64306784660767%\" valign=\"top\" style=\"width: 29.3988%;\"\u003e\n \u003cp\u003eBone metastases (yes vs no)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.141592920353983%\" valign=\"top\" style=\"width: 21.6935%;\"\u003e\n \u003cp\u003e1.67 (1.33\u0026minus;2.08)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.2094395280236%\" valign=\"top\" style=\"width: 13.3954%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.50147492625369%\" valign=\"top\" style=\"width: 10.5504%;\"\u003e\n \u003cp\u003e1.36 (1.08\u0026minus;1.72)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.504424778761061%\" valign=\"top\" style=\"width: 4.5047%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e.01\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"38.64306784660767%\" valign=\"top\" style=\"width: 29.3988%;\"\u003e\n \u003cp\u003eLiver metastases (yes vs no)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.141592920353983%\" valign=\"top\" style=\"width: 21.6935%;\"\u003e\n \u003cp\u003e1.49 (1.16\u0026minus;1.92)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.2094395280236%\" valign=\"top\" style=\"width: 13.3954%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e.002\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.50147492625369%\" valign=\"top\" style=\"width: 10.5504%;\"\u003e\n \u003cp\u003e1.36 (1.04\u0026minus;1.78)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.504424778761061%\" valign=\"top\" style=\"width: 4.5047%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e.02\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"38.64306784660767%\" valign=\"top\" style=\"width: 29.3988%;\"\u003e\n \u003cp\u003eBrain metastases (yes vs no)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.141592920353983%\" valign=\"top\" style=\"width: 21.6935%;\"\u003e\n \u003cp\u003e1.76 (1.24\u0026minus;2.49)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.2094395280236%\" valign=\"top\" style=\"width: 13.3954%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.50147492625369%\" valign=\"top\" style=\"width: 10.5504%;\"\u003e\n \u003cp\u003e1.48 (1.02\u0026minus;2.15)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.504424778761061%\" valign=\"top\" style=\"width: 4.5047%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e.03\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"38.64306784660767%\" valign=\"top\" style=\"width: 29.3988%;\"\u003e\n \u003cp\u003eNivolumab/Cabozantinib vs Pembrolizumab/Axitinib\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.141592920353983%\" valign=\"top\" style=\"width: 21.6935%;\"\u003e\n \u003cp\u003e0.60 (0.43\u0026minus;0.84)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.2094395280236%\" valign=\"top\" style=\"width: 13.3954%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e.003\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.50147492625369%\" valign=\"top\" style=\"width: 10.5504%;\"\u003e\n \u003cp\u003e0.53 (0.37\u0026minus;0.74)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.504424778761061%\" valign=\"top\" style=\"width: 4.5047%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"100%\" colspan=\"5\" valign=\"top\" style=\"width: 79.6613%;\"\u003e\n \u003cp\u003eccRCC = clear cell Renal Cell Carcinoma; IMDC = International Metastatic RCC Database Consortium; nccRCC = non-clear cell Renal Cell Carcinoma\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"cancer-immunology-immunotherapy","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"ciim","sideBox":"Learn more about [Cancer Immunology, Immunotherapy](http://link.springer.com/journal/262)","snPcode":"262","submissionUrl":"https://submission.nature.com/new-submission/262/3","title":"Cancer Immunology, Immunotherapy","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"ARON-1 study, axitinib plus pembrolizumab, cabozantinib plus nivolumab, immune-oncology combinations","lastPublishedDoi":"10.21203/rs.3.rs-4125332/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4125332/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e \u003cp\u003eThe optimal first-line therapy for metastatic renal cell carcinoma (mRCC) remains uncertain, despite recent advancements in immune-based combinations. This retrospective study compares the effectiveness of pembrolizumab plus axitinib (PA) and nivolumab plus cabozantinib (NC) as first-line treatments for mRCC in a real-world setting.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003ePatient data were collected from 55 centres across 16 countries, encompassing individuals diagnosed with mRCC receiving first-line treatment with PA or NC between January 2016 and October 2023. Clinical and tumour features and treatment responses were recorded. The primary endpoints were overall response rate (ORR), overall survival (OS), progression-free survival (PFS), and time to second progression. Statistical analyses included Kaplan-Meier survival estimates, Cox proportional hazard models, and chi-square tests.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eA total of 760 patients with a median age of 64 years (range, 29\u0026ndash;88) were included. Of them, 607 received PA, and only 153 NC. Median OS was 55.7 months and not reached (NR) for PA and NC, respectively (P\u0026thinsp;=\u0026thinsp;.51), while median PFS was longer with NC (27.6 months) than for PA (16.2 months, P\u0026thinsp;=\u0026thinsp;.003). Subgroup analysis suggested a PFS benefits for NC in male, younger patients, intermediate-risk group, clear cell histology, and lung involvement, as well as ORR favoured NC in good risk patients. Multivariate analysis identified first-line therapy as a significant factor associated with PFS.\u003c/p\u003e\u003ch2\u003eConclusions\u003c/h2\u003e \u003cp\u003eIn this certainly biased retrospective comparison, NC demonstrated superior ORR and longer PFS compared to PA in mRCC. These findings underscore the importance of considering individual patient characteristics and risk profiles when selecting first-line therapy for mRCC.\u003c/p\u003e","manuscriptTitle":"Pembrolizumab-axitinib versus nivolumab-cabozantinib as first-line therapy in patients with metastatic renal cell carcinoma: a retrospective real-world comparison (ARON-1)","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-03-21 19:27:19","doi":"10.21203/rs.3.rs-4125332/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2025-03-29T22:56:24+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2024-09-16T19:11:55+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"100602596782276704967746912452879682570","date":"2024-08-27T19:43:26+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"61841485238646745367714399244113342856","date":"2024-08-27T19:42:57+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"279637942035831364603283143603350192136","date":"2024-08-25T21:13:09+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"c314ff30-bc7e-4807-b93b-3c4f8e9633bb","date":"2024-03-19T16:17:49+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2024-03-19T16:00:44+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2024-03-19T13:32:43+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2024-03-19T13:32:43+00:00","index":"","fulltext":""},{"type":"submitted","content":"Cancer Immunology, Immunotherapy","date":"2024-03-18T18:25:41+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"cancer-immunology-immunotherapy","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"ciim","sideBox":"Learn more about [Cancer Immunology, Immunotherapy](http://link.springer.com/journal/262)","snPcode":"262","submissionUrl":"https://submission.nature.com/new-submission/262/3","title":"Cancer Immunology, Immunotherapy","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"b67afde1-2ee1-4e72-8ce8-a50332fceaad","owner":[],"postedDate":"March 21st, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2025-06-02T16:01:39+00:00","versionOfRecord":{"articleIdentity":"rs-4125332","link":"https://doi.org/10.1007/s00262-025-04043-x","journal":{"identity":"cancer-immunology-immunotherapy","isVorOnly":false,"title":"Cancer Immunology, Immunotherapy"},"publishedOn":"2025-05-27 15:57:03","publishedOnDateReadable":"May 27th, 2025"},"versionCreatedAt":"2024-03-21 19:27:19","video":"","vorDoi":"10.1007/s00262-025-04043-x","vorDoiUrl":"https://doi.org/10.1007/s00262-025-04043-x","workflowStages":[]},"version":"v1","identity":"rs-4125332","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4125332","identity":"rs-4125332","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}