The Efficiency of Concomitant Antibiotic Usage On Survival Outcomes of Nivolumab-Treated Metastatic Renal Cell Carcinoma Patients: A Multicenter Experience

The Efficiency of Concomitant Antibiotic Usage On Survival Outcomes of Nivolumab-Treated Metastatic Renal Cell Carcinoma Patients: A Multicenter Experience | 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 The Efficiency of Concomitant Antibiotic Usage On Survival Outcomes of Nivolumab-Treated Metastatic Renal Cell Carcinoma Patients: A Multicenter Experience Muzaffer Uğraklı, Mehmet Zahid Koçak, Selin Uğraklı, Gülhan Dinç, and 10 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6066659/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Aim: Immunotherapy has brought a new perspective to cancer treatments. However, the response of patients to the novel drug is heterogeneous. It is essential to reveal the factors that may affect the outcomes. It was aimed to evaluate the effect of antibiotherapy (Abx) on overall survival (OS) and progression-free survival (PFS) in patients with metastatic renal cell carcinoma (mRCC) receiving second-line nivolumab treatment. Method: The study is a multicentre, retrospective, multicentre design that included patients with metastatic renal cell carcinoma who used nivolumab in second-line treatment. One hundred and two patients with mRCC were divided into two groups according to whether they used Abx with nivolumab: concurrent Abx users and non-users. Overall survival (OS) and progression-free survival (PFS) were compared between the groups with and without concurrent Abx. Results: Of the 102 patients included in the study, 67 (65.7%) of the patients did not receive Abx treatment, while 35 (34.3%) of the patients used Abx. Quinolones were the most commonly used Abx group (57.2 %). This was followed by beta-lactams Abx (42.8%). Median PFS was 9.4 (4.4-14.4) months in non-Abx users and 6.7 (5.9-7.5) months in Abx users (p=0.04). mOS was 29.8 (23.6-35.9) months in non-Abx users and 22.04 (16.4-27.7) months in Abx users (p=0.96). Conclusion: Concurrent Abx usage in mRCC patients treated with nivolumab negatively affects immunotherapy efficacy and treatment response. Clinicians should be cautious about the concomitant use of immunotherapy and Abx in such patients. renal cell carcinoma nivolumab antibiotherapy survival dysbiosis Figures Figure 1 Figure 2 Introduction Renal cell carcinoma (RCC) is derived from the renal cortex and constitutes almost 90% of primary renal malignancies[ 1 ]. RCC consists of various subtypes with particular histopathological and genetic features. Three main histologic types are generally encountered in RCC cases. In order of frequency, these are clear-cell (ccRCC; 70–80%), papillary (pRCC; 10–15%), and chromophobe types (4–5%)[ 1 , 2 ]. Various treatments can be applied in different histologic types of RCC cases. However, ccRCC, the most common histologic type, has a poor prognosis with distant organ metastases reaching up to 40% and 5-year survival is estimated to be 10%[ 3 ]. RCC is a highly vascularized and immunogenic tumor. For this reason, various therapies have been applied to increase antitumor immunity by non-specifically targeting cytokines (such as Interferon-alpha, and interleukin-2). The invention of targeted therapies with anti-angiogenic effect (“blocking vascular endothelial growth factor [VEGF] receptor, Platelet-derived growth factor receptors [PDGF-R] and c-kit) and immunotherapies, which are promising treatment options even in advanced RCC cases, have been developed[ 1 , 4 ]. Nivolumab, an anti-programmed cell death-1(PD-1) antibody, effectively disrupts the interaction between PD-1 and its ligands, PD-L1 and PD-L2, offering a promising therapeutic option for patients with metastatic renal cell carcinoma (mRCC)[ 5 ]. However, the heterogeneity of treatment responses in patients treated with this novel immune checkpoint inhibitor (ICI) immunotherapy and the poor clinical responses detected in some patients have led researchers to reveal the factors that may affect the efficacy of the drug. The gut microbiota consists of commensal bacteria and other microorganisms (archaea, fungi, protozoa, viruses) that inhabit the epithelial barriers of the host. The gut microbiota has critical roles in maintaining various host functions such as metabolism, intestinal homeostasis, inflammation, and immunomodulation[ 6 ]. Moreover, the intestinal microbiome influences drug pharmacokinetics, antitumoral efficiency, and side effects at several grades. Evidence from many preclinical and clinical studies also suggests that the gut microbiota has also an important role in cancer immunotherapy efficacy and modulation of emerging drug toxicity[ 6 , 7 ]. Recent results from several studies have demonstrated the role of gut microbiota content in patients' clinical response to cancer immunotherapy. Accordingly, the composition of the microbiome suggests that it contains different profiles between patients responsive and non-responsive to ICIs across groups and countries. Distinct gut microbial species are capable of inducing or suppressing antitumor immunity. In addition, existing studies have shown that the use of antibiotics (Abx) immediately before or after the start of ICIs may result in poor clinical outcomes due to leading to gut dysbiosis[ 8 – 10 ]. Nevertheless, Abx use is occasionally critical and inevitable in cancer patient groups. The number of studies with heterogeneous clinical responses, limited sample size, and single-center experiences are increasing in publications on this subject. This multi-center study was planned to investigate the effect of Abx use on treatment response in patients receiving ICI treatment with a diagnosis of mRCC. Methods Inclusion criteria patients over 18 years of age, diagnosed with mRCC, receiving TKI or mTOR inhibitors treatment in the first-line treatment followed by nivolumab treatment in the second-line treatment, not receiving steroid treatment or using 10 mg for more than seven days, those who received nivolumab in a series other than second-line treatment, and patients receiving concomitant anti-epileptic and anti-inflammatory treatment. A total of 115 mRCC patients from four centers received Nivolumab in second-line treatment between 2016 and 2023 were included in this study. Four patients were excluded from the study due to high-dose steroid use (> 10mg daily) and 9 patients were excluded due to missing data. Finally, 102 patients were analyzed in the study (Fig. 1 ). Patients' data were retrospectively obtained from hospital file records, electronic databases, prescription systems, and national health system networks. Nivolumab was given at 3 mg/kg every 2 weeks in all patients. The median follow-up was 24.15 months. The study was approved by the local ethics committee (Ethics Committee Number:2023/4155). The patient population was divided into two groups: patients who used oral or intravenous Abx for at least 7 days while on Nivolumab and those who did not. 15 patients had used beta-lactam group Abx and 20 patients had used quinolone group Abx. Clinicopathological characteristics of the patient population, Abx type, metastatic status at diagnosis, number of metastatic sites, primary tumor surgery, International Metastatic Renal Cell Carcinoma Database Consortium (IMDC) risk score, best response to Nivolumab, side effects of nivolumab, tyrosine kinase inhibitor (TKI) use before nivolumab, type of TKI, overall survival (OS) and progression-free survival (PFS) were compared between patients with and without Abx use during nivolumab treatment. Statistical Analysis: The chi-square test and Fisher exact test were used to compare categorical variables between groups. OS was defined as the time from the date of diagnosis until death from any cause. PFS was defined as the time from the start of treatment until disease progression. Survival curves were obtained by the Kaplan-Meier method and evaluated by log-rank test. Cox regression analysis was performed to determine the risk factors for OS and PFS in patient groups. Data were analyzed with SPSS software version 15.0 (SPSS Inc., Chicago, IL, USA). The significance level was set as p < 0.05. Results Of the 102 patients included in the study, 67 (65.7%) did not receive Abx treatment, while 35 (34.3%) of the patients used Abx. Quinolones were the most commonly used Abx group (57.2%). This was followed by beta-lactam Abx (42.8%). Among those Abx non-users, 51 (76.1%) were ccRCC and 16 (23.9%) were non-ccRCC, while 32 (91.4%) of those Abx users were ccRCC and 3 (7.6%) were non-ccRCC (p = 0.17). According to the IMDC risk score, 18 (26.9%) of non-Abx users were in the favorable, 28 (41.8%) in the intermediate, and 21 (31.3%) in the poor risk group. Of those who used Abx, 11 (31.4%) were in the favorable, 15 (42.9%) in the intermediate, and 9 (25.7%) in the poor risk group according to the IMDC risk score. There was no statistical difference between Abx users and non-users according to IMDC risk score (p = 0.81). According to the IMDC score, mPFS was 13.8 (95%CI:12.6–15.1) months in the favorable group, 7.6 (95%CI:5.1–10.2) months in the intermediate group, and 5.2 (95%CI:3.8–6.6) months in the poor group (p = 0.03). mOS were 28.3 (95%CI:26.7–29.9) months in the favorable group, 24.1 (95%CI:22.4–25.8) months in the intermediate group, and 28.5 (95%CI:14.2–42.8) months in the poor group (p = 0.9). Surgery to the primary tumor (No vs Yes), Number of metastatic sites (1 vs ≥ 2), Metastasis at diagnosis (No vs Yes), TKI treatment before Nivolumab (No vs Yes), TKI type (Pazopanib. Sunitinib, Axitinib, and Cabozantinib), Age (< 65 vs ≥ 65), Gender (Female vs Male), BMI ( 0.05 for all, Table 1 ). Table 1 Clinical features of the study participants with antibiotic use and non-use during nivolumab treatment All participants Antibiotic non-use Antibiotic use p Age (n) < 65 67 (65.7%) 43 (64.2%) 24 (68.6%) 0.65 ≥ 65 35 (34.3%) 24 (35.2%) 11 (31.4%) Gender (n) Female 27 (26.5%) 20 (29.1%) 7 (20%) 0.28 Male 75 (73.5%) 47 (70.1%) 28 (80%) BMI (n) < 25 kg/m 2 33 (32.4%) 22 (32.8%) 11 (31.4%) 0.88 ≥ 25 kg/m 2 69 (67.6%) 45 (67.2%) 24 (68.6%) ECOG-PS (n) 0 62 (60.8%) 41 (61.2%) 21 (60%) 0.9 1 40 (39.2%) 26 (38.8%) 14 (40%) IMDC score (n) Favorable 29 (28.4%) 18 (26.9%) 11 (31.4%) 0.81 Intermediate 43 (42.2%) 28 (41.8%) 15 (42.9%) Poor 30 (29.4%) 21 (31.3%) 9 (25.7%) Subtypes of RCC (n) Clear cell 83 (81.4%) 51 (76.1%) 32 (91.4%) 0.17 Non-clear cell 19 (18.6%) 16 (23.9%) 3 (7.6%) Surgery to primary tumor (n) No 27 (26.5%) 19 (28.4%) 8 (22.9%) 0.55 Yes 75 (73.5%) 48 (71.6%) 27 (77.1%) Number of metastatic sites (n) 1 39 (38.2%) 26 (38.8%) 13 (37.1%) 0.87 ≥ 2 63 (61.8%) 41 (61.2%) 22 (62.9%) Metastasis at diagnosis (n) No 44 (43.1%) 24 (35.8%) 20 (57.1%) 0.06 Yes 58 (56.9%) 43 (64.2%) 15 (42.9%) TKI treatment before Nivolumab No 3 (2.9%) 3 (4.5%) 0 (0%) 0.2 Yes 99 (97.1%) 64 (95.5%) 35 (100%) TKI type Pazopanib 39 (38.2%) 24 (35.8%) 15 (42.9%) 0.6 Sunitinib 57 (54.3%) 28 (56.7%) 19 (54.3%) Axitinib 3 (2.9%) 2 (3%) 1 (2.9%) Cabozantinib 3 (2.9%) 3 (4.5%) 0 (%) Abbreviations: Body Mass Index (BMI), Eastern Cooperative Oncology Group Performance Status (ECOG-PS), International Metastatic Renal Cell Carcinoma Database Consortium Risk Score (IMDC score), Tyrosine kinase inhibitor (TKİ). mPFS was 9.4 (4.4–14.4) months in non-Abx users and 6.7 (5.9–7.5) months in Abx users (p = 0.04). mOS was 29.8 (23.6–35.9) months in non-Abx users and 22.04 (16.4–27.7) months in Abx users (p = 0.96) (Fig. 2 ). There was no difference in PFS (beta-lactam group vs quinolone group mPFS: 7.03 [5.4–8.5] months vs 6.03 [4.14–8.60] months, p = 0.5) and OS (beta-lactam group vs quinolone group mOS: 20 [17.3–22.6] months vs 31.3 [23.9–58.6] months, p = 0.06). In the study, risk factors for PFS and OS were evaluated by multivariate and univariate analysis. Non-use of Abx was determined as a good risk factor for PFS (Non-use vs Use = HR: 0.63, 95%Cl: 0.40–0.98, p = 0.04) (Table 2 ). Abx use was not found to be a risk factor for OS (Non-use vs Use = HR: 1.00, 95%Cl: 0.77–1.31, p = 0.96) (Table 2 ). In addition, IMDC score and best response to nivolumab for PFS, IMDC score, best response to nivolumab, and metastasis at diagnosis were found to be independent risk factors for OS (Table 2 ). Table 2: Univariate analyses and multivariate analyses of the risk factors for PFS and OS Univariate analysis Multivariate analysis Progression-free survival HR 95% CI p HR 95% CI p Antibiotic use Non-use vs Use 0.63 0.40-0.98 0.04 0.96 0.64-1.47 0.2 IMDC score Favorable Reference 0.05 Reference 0.036 Intermediate 1.81 1.56-9.17 0.03 1.91 1.04-3.49 0.035 Poor 1.97 1.27-7.78 0.02 2.30 1.19-4.44 0.013 Best response to nivolumab Complete Reference <0.001 Reference <0.001 Partial 2.36 0.31-17.7 0.4 2.07 0.27-6.01 0.48 Stable 6.40 0.87-4.76 0.06 5.85 0.76-9.41 0.08 Progression 5.71 1.71-9.44 0.013 4.58 1.65-12.58 0.014 Number of metastatic sites ≥2 vs 1 0.90 0.57-1.42 0.65 - - - Metastasis at diagnosis No vs Yes 0.80 0.64-1.1 0.06 - - - Surgery to primary tumor (n) No vs Yes 1.26 0.97-1.62 0.07 - - - Univariate analysis Multivariate analysis Overall survival HR 95% CI p HR 95% CI p Antibiotic use Non-use vs Use 1.00 0.77-1.31 0.96 - - - IMDC score Favorable Reference 0.15 Reference 0.46 Intermediate 1.70 0.83-3.48 0.14 1.55 0.70-3.45 0.28 Poor 2.11 1.10-4.46 0.4 1.64 0.72-3.69 0.23 Best response to nivolumab Complete Reference 0.001 Reference 0.001 Partial 0.58 0.13-2.62 0.48 0.62 0.12-2.90 0.54 Stable 0.80 0.18-3.47 0.76 0.85 0.18-3.88 0.83 Progression 2.29 0.53-9.85 0.26 2.50 0.56-11.14 0.22 Number of metastatic sites ≥2 vs 1 1.35 0.80-2.28 0.25 - - - Metastasis at diagnosis No vs Yes 0.54 0.32-0.91 0.023 0.96 0.25-2.24 0.11 Surgery to primary tumor (n) No vs Yes 0.94 0.56-1.59 0.84 - - - Abbreviations Confidence Interval (CI), Hazard Ratio (HR), International Metastatic Renal Cell Carcinoma Database Consortium Risk Score (IMDC score), Overall survival (OS), Progression free survival (PFS) Hypothyroidism (5 [14.3%]), dermatitis (2 [5.7%]), increased transaminases (1 [2.9%]), pneumonitis (1 [2.9%]), and fatigue (1 [2.9%]) were observed in patients who used Abx during nivolumab treatment. Hypothyroidism (8 [11.9%]), dermatitis (4 [6%]), diarrhea (1 [1.5%]), and fatigue (1 [1.5%]) side effects were observed in non-Abx users during nivolumab treatment. There was no significant difference in the incidence of side effects between Abx users (13 [37.1%] with side effects and 22 [62.9%] without side effects) and non-users (46 [68.6%] with side effects and 21 [31.4%] without side effects) (p = 0.24). Discussions In many countries, as in our country, immunotherapy treatments are difficult to access in the first-line setting (due to reimbursement, licensing, and clinical practice rules for TKIs in the first-line setting) and are used in the second-line or subsequent-line treatment. In our study, mPFS was lower with concurrent Abx use in patients receiving nivolumab in the second-line treatment of mRCC. PFS was found to be a statistically significant worse risk factor with concurrent Abx use. IMDC score and best response to nivolumab for PFS, IMDC score, best response to nivolumab, and metastasis at diagnosis were found to be independent risk factors for OS. There was no statistical difference in the degree of any side effect, primary tumor surgery, number of metastatic sites, tyrosine kinase inhibitor types used before nivolumab treatment, age, gender, body mass index, ECOG score, and Abx types. In recent years, factors affecting OS and PFS have been emphasized in the use of immunotherapy. One of the most emphasized factors is the gut microbiota in the gastrointestinal system. The effect of intestinal flora on the body's immune system and immune system diseases caused by disruption of intestinal flora and its negative effects have been frequently discussed in many diseases in recent years[ 9 – 12 ]. It is emphasized in publications that the body's immune system is negatively affected as a result of the increase in harmful bacteria ( C. hathewayi , E. rectale , )[ 13 ] as a result of fecal microbiota analyses and that the immune response can be increased by increasing the variety of immunostimulatory bacteria ( Akkermansia muciniphila, Bifidobacterium longum, Bacteroides fragilis, Enterococcus hirae type 13144, Bifidobacterium adolescentis, Barnesiella intestinihominis ) with probiotic supplements[ 14 – 17 ]. Some metabolites produced by intestinal bacteria, such as short-chain fatty acids and inosine, increase the therapeutic effects of ICIs by activating CD8 + T cells[ 18 ]. Inosinin produced by Akkermansia muciniphila activates T cells, as a result of the decrease in the amount of inosinin after the use of Abx, the microbiome balance is disrupted, leading to a decrease in treatment efficacy[ 19 ]. Hagihara M et al conducted a randomized trial to investigate the effects of CBM588 (a butyrate-producing non-pathogenic strain of Clostridium butyricum , believed to restore healthy microbiota through increasing interleukin-17A-producing T cells and CD4[+] cells in the lamina propria). This study randomized patients to receive nivolumab and ipilimumab with (n = 19) or without (n = 19) CBM588. mPFS was greater in the nivolumab-ipilimumab plus CBM588 arm compared to the nivolumab-ipilimumab alone arm (12.7 vs 2.5 months, HR 0.15, p < 0.001) [ 20 ]. In preclinical laboratory studies, diminished quantity and capacity of immune cells as a result of dysbiosis caused by antibiotic usage have been reported. Recently, clinical investigations evaluating the usage of immunotherapy and Abx as regards to survival of patients have increased. Derosa L et al.[ 9 ] included 106 patients with mRCC receiving PD-(L)1 mono therapy. Patients with Abx had shorter PFS and OS than those without Abx (mPFS, 1.9 months vs 7.4 months, P < 0.01; mOS, 17.3 months vs 30.6 months, P < 0.03). In another phase 2 study by Derosa L. et al[ 21 ], 707 patients were included and 104 patients used Abx. ORR was found to be 15.1% in Abx users and 21.1% in non-users. The mOS was 13.0 months versus 25.0 months and mPFS was 2.6 months versus 3.8 months in Abx users and non-users, respectively. The study by Lalani AA et al.[ 22 ] included 146 patients who received ICI in the first series and subsequent series, 31 of whom received Abx. For patients treated with ICI who also received systemic Abx compared with non-receiver, ORR was lower (12.9% vs. 34.8%, p = 0.026), PFS was shorter (p = 0.007) and OS was worse (p = 0.270). Katsurayama N et al[ 23 ]. included patients receiving ICI in the first-line treatment phase. Of 128 mRCC patients, 30 (23%) received Abx. Abx-treated patients exhibited shorter mPFS and mOS compared to those who did not receive Abx (median mPFS: 4.9 vs. 16.1 months, p < 0.0001 mOS: 20.8 vs. 49.0 months, p = 0.0034). In similar studies by Routy et al.[ 12 ], Tinsley N et al.[ 8 ], Ueda K et al.[ 24 ], and Kulkarni AA et al.[ 25 ], worsening in both OS and PSF was found in patients using Abx with ICI. DC Guven et al[ 26 ]. evaluated the use of immunotherapy in the second series, 93 patients were included, and 31 patients were on Abx and ICI. The ORR was lower in Abx users compared to non-users (24.1% vs. 50%, P = 0.023). There was a statistically significant difference in PFS, p = 0.004, and OS, p = 0.018 in Abx users compared to non-users. Buti S et al.[ 27 ] study, 305 patients with mRCC receiving ICI combination therapy in first-line treatment were included and scoring was performed according to Abx, steroid and proton pump inhibitors (PPI) (Abx 1 point, PPI 1 point, steroid 2 points). The 12-month mOS (73% vs. 44% (P < 0.0001) and mPFS were 11.6 months and 4.8 months for patients belonging to the favorable group (score 0–1) and unfavorable group (score 2–4), respectively (P = 0.002). In our study, 102 patients were included in the study, 35 of whom used ICI plus Abx. The mPFS was 6.7 months and 9.4 months (p = 0.04), mOS was 22.04 months and 29.8 months (p = 0.96) in ICI plus Abx users and non-users, respectively. In our study, unlike other studies[ 8 , 9 , 12 , 21 – 25 , 27 ], the patient group who received only nivolumab in the second-line treatment after the first series of TKI in mRCC were included, patients who received only one type of Abx and patients who received Abx treatment together with ICI (those who received Abx before and after ICI were not included) were included. Another difference in our study was that the Abx used were different. In other studies[ 8 , 9 , 12 , 21 – 27 ], beta-lactam Abx was used more, but in our study, the most commonly used Abx group was Quinolones (57.2%) followed by beta-lactam Abx (42.8%). In other studies, studies[ 8 , 9 , 12 , 21 – 27 ], a significant difference was found in both OS and PFS in patients who used Abx together with ICI, but in our study, there was a statistically significant difference in PFS, but no statistically significant difference was found in OS. The limitations of our study were that the patient population was relatively small, Abx diversity was low and it was a retrospective study. The patient groups with and without concomitant Abx use were following our current practice and it was a multi-center study. In conclusion, concurrent Abx use in mRCC patients treated with nivolumab negatively affects immunotherapy efficacy and treatment response. Clinicians should be cautious about the concomitant use of immunotherapy and Abx in such patients. Declarations Author contribution Concept — MU, MZK and MA. Design — MU and MA. Supervision — all authors. Data collection and/or processing — all authors. Analysis and/or interpretation — MZK and MA. Literature search —TBG, MÇ and GD. Writing — MU, SU, MZK, MKE,MA and MA. Critical reviews — all authors. Data availability Data will be provided by the corresponding author. Ethics approval This research was conducted ethically in accordance with the World Medical Association Helsinki Declaration. All patients had to give informed consent before participating in our sensitive study. Ethics approval was obtained from -------------------------- Medical Faculty, ----, ----- (Ethics Committee Number: 2023/4155). Informed consent Because the study was designed retrospectively, no informed consent was obtained from the patients. Conflict of interest The authors declare no competing interests. Funding None References Ljungberg B, Albiges L, Abu-Ghanem Y, et al. 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Microbiome-derived inosine modulates response to checkpoint inhibitor immunotherapy. Science . 2020;369(6510):1481-1489. https://doi.org/10.1126/science.abc3421 Hagihara M, Kuroki Y, Ariyoshi T, et al. Clostridium butyricum Modulates the Microbiome to Protect Intestinal Barrier Function in Mice with Antibiotic-Induced Dysbiosis. iScience . 2020;23(1):100772. https://doi.org/10.1016/j.isci.2019.100772 L. Derosa, C. Alves Costa Silva, C. Dalban, 657MO Antibiotic (ATB) therapy and outcome from nivolumab (N) in metastatic renal cell carcinoma (mRCC) patients (pts): Results of the GETUG-AFU 26 NIVOREN multicentric phase II study, Annals of Oncology, Volume 32, Supplement 5, 2021, Page S681. Lalani AA, Xie W, Braun DA, et al. Effect of Antibiotic Use on Outcomes with Systemic Therapies in Metastatic Renal Cell Carcinoma. Eur Urol Oncol . 2020;3(3):372-381.https://doi.org/10.1016/j.euo.2019.09.001 Katsurayama N, Ishihara H, Ishiyama R, et al. Prognostic Impact of the Administration of Antibiotics and Proton Pump Inhibitors in Immune Checkpoint Inhibitor Combination Therapy for Advanced Renal Cell Carcinoma. Cancer Diagn Progn . 2024;4(4):496-502. https://doi.org/10.21873/cdp.10354 Ueda K, Yonekura S, Ogasawara N, et al. The Impact of Antibiotics on Prognosis of Metastatic Renal Cell Carcinoma in Japanese Patients Treated With Immune Checkpoint Inhibitors. Anticancer Res . 2019;39(11):6265-6271. https://doi.org/10.21873/anticanres.13836 Kulkarni AA, Ebadi M, Zhang S, et al. Comparative analysis of antibiotic exposure association with clinical outcomes of chemotherapy versus immunotherapy across three tumour types. ESMO Open . 2020;5(5):e000803. https://doi.org/10.1136/esmoopen-2020-000803 Guven DC, Acar R, Yekeduz E, et al. The association between antibiotic use and survival in renal cell carcinoma patients treated with immunotherapy: a multi-center study. Curr Probl Cancer . 2021;45(6):100760. https://doi.org/10.1016/j.currproblcancer.2021.100760 Buti S, Basso U, Giannarelli D, et al. Concomitant Drugs Prognostic Score in Patients With Metastatic Renal Cell Carcinoma Receiving Ipilimumab and Nivolumab in the Compassionate Use Program in Italy: Brief Communication. J Immunother . 2023;46(1):22-26. https://doi.org/10.1097/CJI.0000000000000446 Additional Declarations No competing interests reported. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-6066659","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":423270208,"identity":"9966fed0-5cd8-4351-85a4-8d51e4919ac9","order_by":0,"name":"Muzaffer 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University","correspondingAuthor":false,"prefix":"","firstName":"Melek","middleName":"Karakurt","lastName":"Eryılmaz","suffix":""},{"id":423270232,"identity":"24914ec5-55be-46f0-980c-2c9a80cd6f5d","order_by":9,"name":"Murat Araz","email":"","orcid":"","institution":"Necmettin Erbakan University","correspondingAuthor":false,"prefix":"","firstName":"Murat","middleName":"","lastName":"Araz","suffix":""},{"id":423270233,"identity":"835ebc80-eb61-4198-a15c-f8ad39e7a358","order_by":10,"name":"Çağlayan Geredeli","email":"","orcid":"","institution":"Istinye University","correspondingAuthor":false,"prefix":"","firstName":"Çağlayan","middleName":"","lastName":"Geredeli","suffix":""},{"id":423270234,"identity":"60ce054d-4c76-4891-b899-71a159b07cc0","order_by":11,"name":"Ali Murat Tatlı","email":"","orcid":"","institution":"Akdeniz University","correspondingAuthor":false,"prefix":"","firstName":"Ali","middleName":"Murat","lastName":"Tatlı","suffix":""},{"id":423270235,"identity":"178f8b7a-ba18-47dc-b646-7aabae986caa","order_by":12,"name":"Orhan Önder Eren","email":"","orcid":"","institution":"Selçuk University","correspondingAuthor":false,"prefix":"","firstName":"Orhan","middleName":"Önder","lastName":"Eren","suffix":""},{"id":423270236,"identity":"b0f47c9f-32fd-4c44-b464-ccdbc75df03a","order_by":13,"name":"Mehmet Artaç","email":"","orcid":"","institution":"Necmettin Erbakan University","correspondingAuthor":false,"prefix":"","firstName":"Mehmet","middleName":"","lastName":"Artaç","suffix":""}],"badges":[],"createdAt":"2025-02-19 19:38:26","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-6066659/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6066659/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":78248718,"identity":"5d99c754-0a68-485f-aa8b-cba88cd4ca62","added_by":"auto","created_at":"2025-03-11 09:39:26","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":241498,"visible":true,"origin":"","legend":"\u003cp\u003eFlow chart of study participants\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-6066659/v1/ce548a6020a26dba18a30ea3.png"},{"id":78250852,"identity":"d8cf96b6-9e51-42b5-8721-6be3946c9456","added_by":"auto","created_at":"2025-03-11 09:55:26","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":246828,"visible":true,"origin":"","legend":"\u003cp\u003eKaplan-Meier curves of progression-free survival (mPFS) and overall survival (mOS) with antibiotic use during nivolumab treatment in metastatic renal cell carcinoma\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-6066659/v1/634a6ac19aa0d67d87a61ff1.png"},{"id":78251714,"identity":"260ec05a-2837-4910-ad86-ba0f6b79c6e3","added_by":"auto","created_at":"2025-03-11 10:03:28","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1357258,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6066659/v1/acfa5515-30c1-4402-b561-1c1080423395.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"The Efficiency of Concomitant Antibiotic Usage On Survival Outcomes of Nivolumab-Treated Metastatic Renal Cell Carcinoma Patients: A Multicenter Experience","fulltext":[{"header":"Introduction","content":"\u003cp\u003eRenal cell carcinoma (RCC) is derived from the renal cortex and constitutes almost 90% of primary renal malignancies[\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. RCC consists of various subtypes with particular histopathological and genetic features. Three main histologic types are generally encountered in RCC cases. In order of frequency, these are clear-cell (ccRCC; 70\u0026ndash;80%), papillary (pRCC; 10\u0026ndash;15%), and chromophobe types (4\u0026ndash;5%)[\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. Various treatments can be applied in different histologic types of RCC cases. However, ccRCC, the most common histologic type, has a poor prognosis with distant organ metastases reaching up to 40% and 5-year survival is estimated to be 10%[\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. RCC is a highly vascularized and immunogenic tumor. For this reason, various therapies have been applied to increase antitumor immunity by non-specifically targeting cytokines (such as Interferon-alpha, and interleukin-2). The invention of targeted therapies with anti-angiogenic effect (\u0026ldquo;blocking vascular endothelial growth factor [VEGF] receptor, Platelet-derived growth factor receptors [PDGF-R] and c-kit) and immunotherapies, which are promising treatment options even in advanced RCC cases, have been developed[\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eNivolumab, an anti-programmed cell death-1(PD-1) antibody, effectively disrupts the interaction between PD-1 and its ligands, PD-L1 and PD-L2, offering a promising therapeutic option for patients with metastatic renal cell carcinoma (mRCC)[\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. However, the heterogeneity of treatment responses in patients treated with this novel immune checkpoint inhibitor (ICI) immunotherapy and the poor clinical responses detected in some patients have led researchers to reveal the factors that may affect the efficacy of the drug.\u003c/p\u003e \u003cp\u003eThe gut microbiota consists of commensal bacteria and other microorganisms (archaea, fungi, protozoa, viruses) that inhabit the epithelial barriers of the host. The gut microbiota has critical roles in maintaining various host functions such as metabolism, intestinal homeostasis, inflammation, and immunomodulation[\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. Moreover, the intestinal microbiome influences drug pharmacokinetics, antitumoral efficiency, and side effects at several grades. Evidence from many preclinical and clinical studies also suggests that the gut microbiota has also an important role in cancer immunotherapy efficacy and modulation of emerging drug toxicity[\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. Recent results from several studies have demonstrated the role of gut microbiota content in patients' clinical response to cancer immunotherapy. Accordingly, the composition of the microbiome suggests that it contains different profiles between patients responsive and non-responsive to ICIs across groups and countries. Distinct gut microbial species are capable of inducing or suppressing antitumor immunity. In addition, existing studies have shown that the use of antibiotics (Abx) immediately before or after the start of ICIs may result in poor clinical outcomes due to leading to gut dysbiosis[\u003cspan additionalcitationids=\"CR9\" citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. Nevertheless, Abx use is occasionally critical and inevitable in cancer patient groups. The number of studies with heterogeneous clinical responses, limited sample size, and single-center experiences are increasing in publications on this subject.\u003c/p\u003e \u003cp\u003eThis multi-center study was planned to investigate the effect of Abx use on treatment response in patients receiving ICI treatment with a diagnosis of mRCC.\u003c/p\u003e"},{"header":"Methods","content":"\u003cp\u003eInclusion criteria patients over 18 years of age, diagnosed with mRCC, receiving TKI or mTOR inhibitors treatment in the first-line treatment followed by nivolumab treatment in the second-line treatment, not receiving steroid treatment or using\u0026thinsp;\u0026lt;\u0026thinsp;10 mg steroid treatment for a maximum of seven days were included. Exclusion criteria were those who used steroids for a long time and \u0026gt;\u0026thinsp;10 mg for more than seven days, those who received nivolumab in a series other than second-line treatment, and patients receiving concomitant anti-epileptic and anti-inflammatory treatment.\u003c/p\u003e \u003cp\u003eA total of 115 mRCC patients from four centers received Nivolumab in second-line treatment between 2016 and 2023 were included in this study. Four patients were excluded from the study due to high-dose steroid use (\u0026gt;\u0026thinsp;10mg daily) and 9 patients were excluded due to missing data. Finally, 102 patients were analyzed in the study (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). Patients' data were retrospectively obtained from hospital file records, electronic databases, prescription systems, and national health system networks. Nivolumab was given at 3 mg/kg every 2 weeks in all patients. The median follow-up was 24.15 months. The study was approved by the local ethics committee (Ethics Committee Number:2023/4155).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eThe patient population was divided into two groups: patients who used oral or intravenous Abx for at least 7 days while on Nivolumab and those who did not. 15 patients had used beta-lactam group Abx and 20 patients had used quinolone group Abx. Clinicopathological characteristics of the patient population, Abx type, metastatic status at diagnosis, number of metastatic sites, primary tumor surgery, International Metastatic Renal Cell Carcinoma Database Consortium (IMDC) risk score, best response to Nivolumab, side effects of nivolumab, tyrosine kinase inhibitor (TKI) use before nivolumab, type of TKI, overall survival (OS) and progression-free survival (PFS) were compared between patients with and without Abx use during nivolumab treatment.\u003c/p\u003e \u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eStatistical Analysis:\u003c/h2\u003e \u003cp\u003eThe chi-square test and Fisher exact test were used to compare categorical variables between groups. OS was defined as the time from the date of diagnosis until death from any cause. PFS was defined as the time from the start of treatment until disease progression. Survival curves were obtained by the Kaplan-Meier method and evaluated by log-rank test. Cox regression analysis was performed to determine the risk factors for OS and PFS in patient groups. Data were analyzed with SPSS software version 15.0 (SPSS Inc., Chicago, IL, USA). The significance level was set as p\u0026thinsp;\u0026lt;\u0026thinsp;0.05.\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cp\u003eOf the 102 patients included in the study, 67 (65.7%) did not receive Abx treatment, while 35 (34.3%) of the patients used Abx. Quinolones were the most commonly used Abx group (57.2%). This was followed by beta-lactam Abx (42.8%). Among those Abx non-users, 51 (76.1%) were ccRCC and 16 (23.9%) were non-ccRCC, while 32 (91.4%) of those Abx users were ccRCC and 3 (7.6%) were non-ccRCC (p\u0026thinsp;=\u0026thinsp;0.17). According to the IMDC risk score, 18 (26.9%) of non-Abx users were in the favorable, 28 (41.8%) in the intermediate, and 21 (31.3%) in the poor risk group. Of those who used Abx, 11 (31.4%) were in the favorable, 15 (42.9%) in the intermediate, and 9 (25.7%) in the poor risk group according to the IMDC risk score. There was no statistical difference between Abx users and non-users according to IMDC risk score (p\u0026thinsp;=\u0026thinsp;0.81). According to the IMDC score, mPFS was 13.8 (95%CI:12.6\u0026ndash;15.1) months in the favorable group, 7.6 (95%CI:5.1\u0026ndash;10.2) months in the intermediate group, and 5.2 (95%CI:3.8\u0026ndash;6.6) months in the poor group (p\u0026thinsp;=\u0026thinsp;0.03). mOS were 28.3 (95%CI:26.7\u0026ndash;29.9) months in the favorable group, 24.1 (95%CI:22.4\u0026ndash;25.8) months in the intermediate group, and 28.5 (95%CI:14.2\u0026ndash;42.8) months in the poor group (p\u0026thinsp;=\u0026thinsp;0.9). Surgery to the primary tumor (No vs Yes), Number of metastatic sites (1 vs\u0026thinsp;\u0026ge;\u0026thinsp;2), Metastasis at diagnosis (No vs Yes), TKI treatment before Nivolumab (No vs Yes), TKI type (Pazopanib. Sunitinib, Axitinib, and Cabozantinib), Age (\u0026lt;\u0026thinsp;65 vs\u0026thinsp;\u0026ge;\u0026thinsp;65), Gender (Female vs Male), BMI (\u0026lt;\u0026thinsp;25 kg/m2 vs\u0026thinsp;\u0026ge;\u0026thinsp;25 kg/m2) and ECOG-PS (0 vs 1) were not statistically significantly different between Abx users and non-users (p\u0026thinsp;\u0026gt;\u0026thinsp;0.05 for all, Table \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e). \u0026nbsp;\u003c/p\u003e\n\u003ctable id=\"Tab1\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eClinical features of the study participants with antibiotic use and non-use during nivolumab treatment\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\u0026nbsp;\u003c/th\u003e\n \u003cth align=\"left\"\u003e\u0026nbsp;\u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eAll participants\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eAntibiotic non-use\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eAntibiotic use\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003ep\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003e\u003cstrong\u003eAge (n)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;65\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e67 (65.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e43 (64.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e24 (68.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" rowspan=\"2\"\u003e\n \u003cp\u003e0.65\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026ge;\u0026thinsp;65\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e35 (34.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e24 (35.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e11 (31.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003e\u003cstrong\u003eGender (n)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eFemale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e27 (26.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e20 (29.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e7 (20%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" rowspan=\"2\"\u003e\n \u003cp\u003e0.28\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e75 (73.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e47 (70.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e28 (80%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003e\u003cstrong\u003eBMI (n)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;25 kg/m\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e33 (32.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e22 (32.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e11 (31.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" rowspan=\"2\"\u003e\n \u003cp\u003e0.88\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026ge;\u0026thinsp;25 kg/m\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e69 (67.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e45 (67.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e24 (68.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003e\u003cstrong\u003eECOG-PS (n)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e62 (60.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e41 (61.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e21 (60%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" rowspan=\"2\"\u003e\n \u003cp\u003e0.9\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e40 (39.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e26 (38.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e14 (40%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" rowspan=\"3\"\u003e\n \u003cp\u003e\u003cstrong\u003eIMDC score (n)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eFavorable\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e29 (28.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e18 (26.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e11 (31.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" rowspan=\"3\"\u003e\n \u003cp\u003e0.81\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eIntermediate\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e43 (42.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e28 (41.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e15 (42.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePoor\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e30 (29.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e21 (31.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e9 (25.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003e\u003cstrong\u003eSubtypes of RCC (n)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eClear cell\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e83 (81.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e51 (76.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e32 (91.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" rowspan=\"2\"\u003e\n \u003cp\u003e0.17\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNon-clear cell\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e19 (18.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e16 (23.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3 (7.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003e\u003cstrong\u003eSurgery to primary tumor (n)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e27 (26.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e19 (28.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e8 (22.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" rowspan=\"2\"\u003e\n \u003cp\u003e0.55\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e75 (73.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e48 (71.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e27 (77.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003e\u003cstrong\u003eNumber of metastatic sites (n)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e39 (38.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e26 (38.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e13 (37.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" rowspan=\"2\"\u003e\n \u003cp\u003e0.87\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026ge;\u0026thinsp;2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e63 (61.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e41 (61.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e22 (62.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003e\u003cstrong\u003eMetastasis at diagnosis (n)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e44 (43.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e24 (35.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e20 (57.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" rowspan=\"2\"\u003e\n \u003cp\u003e0.06\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e58 (56.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e43 (64.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e15 (42.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003e\u003cstrong\u003eTKI treatment before Nivolumab\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e3 (2.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3 (4.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0 (0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" rowspan=\"2\"\u003e\n \u003cp\u003e0.2\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e99 (97.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e64 (95.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e35 (100%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" rowspan=\"4\"\u003e\n \u003cp\u003e\u003cstrong\u003eTKI type\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePazopanib\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e39 (38.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e24 (35.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e15 (42.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" rowspan=\"4\"\u003e\n \u003cp\u003e0.6\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSunitinib\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e57 (54.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e28 (56.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e19 (54.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAxitinib\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e3 (2.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2 (3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1 (2.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCabozantinib\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e3 (2.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3 (4.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0 (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAbbreviations:\u0026nbsp;\u003c/strong\u003eBody Mass Index (BMI), Eastern Cooperative Oncology Group Performance Status (ECOG-PS), International Metastatic Renal Cell Carcinoma Database Consortium Risk Score (IMDC score), Tyrosine kinase inhibitor (TKİ).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003emPFS was 9.4 (4.4\u0026ndash;14.4) months in non-Abx users and 6.7 (5.9\u0026ndash;7.5) months in Abx users (p\u0026thinsp;=\u0026thinsp;0.04). mOS was 29.8 (23.6\u0026ndash;35.9) months in non-Abx users and 22.04 (16.4\u0026ndash;27.7) months in Abx users (p\u0026thinsp;=\u0026thinsp;0.96) (Fig. \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e). There was no difference in PFS (beta-lactam group vs quinolone group mPFS: 7.03 [5.4\u0026ndash;8.5] months vs 6.03 [4.14\u0026ndash;8.60] months, p\u0026thinsp;=\u0026thinsp;0.5) and OS (beta-lactam group vs quinolone group mOS: 20 [17.3\u0026ndash;22.6] months vs 31.3 [23.9\u0026ndash;58.6] months, p\u0026thinsp;=\u0026thinsp;0.06). In the study, risk factors for PFS and OS were evaluated by multivariate and univariate analysis. Non-use of Abx was determined as a good risk factor for PFS (Non-use vs Use\u0026thinsp;=\u0026thinsp;HR: 0.63, 95%Cl: 0.40\u0026ndash;0.98, p\u0026thinsp;=\u0026thinsp;0.04) (Table \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e). Abx use was not found to be a risk factor for OS (Non-use vs Use\u0026thinsp;=\u0026thinsp;HR: 1.00, 95%Cl: 0.77\u0026ndash;1.31, p\u0026thinsp;=\u0026thinsp;0.96) (Table \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e). In addition, IMDC score and best response to nivolumab for PFS, IMDC score, best response to nivolumab, and metastasis at diagnosis were found to be independent risk factors for OS (Table \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e\u003cstrong\u003e).\u003c/strong\u003e\u003c/p\u003e\n\u003cdiv align=\"left\" class=\"colspec\"\u003e\u003cstrong\u003eTable 2: Univariate analyses and multivariate analyses of the risk factors for PFS and OS\u003c/strong\u003e\u003c/div\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"650\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 92px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 97px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"3\" valign=\"top\" style=\"width: 227px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eUnivariate analysis\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"3\" valign=\"top\" style=\"width: 234px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eMultivariate analysis\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 189px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eProgression-free survival\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 54px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eHR\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 95px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e95% CI\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003e\u003cstrong\u003ep\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eHR\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 94px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e95% CI\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\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 valign=\"top\" style=\"width: 92px;\"\u003e\n \u003cp\u003eAntibiotic use\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 97px;\"\u003e\n \u003cp\u003eNon-use vs Use\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 54px;\"\u003e\n \u003cp\u003e0.63\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 95px;\"\u003e\n \u003cp\u003e0.40-0.98\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003e0.04\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e0.96\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 94px;\"\u003e\n \u003cp\u003e0.64-1.47\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e0.2\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"3\" valign=\"top\" style=\"width: 92px;\"\u003e\n \u003cp\u003eIMDC score\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 97px;\"\u003e\n \u003cp\u003eFavorable\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 149px;\"\u003e\n \u003cp\u003eReference\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003e0.05\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 170px;\"\u003e\n \u003cp\u003eReference\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e0.036\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 97px;\"\u003e\n \u003cp\u003eIntermediate\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 54px;\"\u003e\n \u003cp\u003e1.81\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 95px;\"\u003e\n \u003cp\u003e1.56-9.17\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003e0.03\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e1.91\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 94px;\"\u003e\n \u003cp\u003e1.04-3.49\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e0.035\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 97px;\"\u003e\n \u003cp\u003ePoor\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 54px;\"\u003e\n \u003cp\u003e1.97\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 95px;\"\u003e\n \u003cp\u003e1.27-7.78\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003e0.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e2.30\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 94px;\"\u003e\n \u003cp\u003e1.19-4.44\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e0.013\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"4\" valign=\"top\" style=\"width: 92px;\"\u003e\n \u003cp\u003eBest response to nivolumab\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 97px;\"\u003e\n \u003cp\u003eComplete\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 149px;\"\u003e\n \u003cp\u003eReference\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 170px;\"\u003e\n \u003cp\u003eReference\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 97px;\"\u003e\n \u003cp\u003ePartial\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 54px;\"\u003e\n \u003cp\u003e2.36\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 95px;\"\u003e\n \u003cp\u003e0.31-17.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003e0.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e2.07\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 94px;\"\u003e\n \u003cp\u003e0.27-6.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e0.48\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 97px;\"\u003e\n \u003cp\u003eStable\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 54px;\"\u003e\n \u003cp\u003e6.40\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 95px;\"\u003e\n \u003cp\u003e0.87-4.76\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003e0.06\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e5.85\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 94px;\"\u003e\n \u003cp\u003e0.76-9.41\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e0.08\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 97px;\"\u003e\n \u003cp\u003eProgression\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 54px;\"\u003e\n \u003cp\u003e5.71\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 95px;\"\u003e\n \u003cp\u003e1.71-9.44\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003e0.013\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e4.58\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 94px;\"\u003e\n \u003cp\u003e1.65-12.58\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e0.014\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 92px;\"\u003e\n \u003cp\u003eNumber of metastatic sites\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 97px;\"\u003e\n \u003cp\u003e\u0026ge;2 vs 1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 54px;\"\u003e\n \u003cp\u003e0.90\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 95px;\"\u003e\n \u003cp\u003e0.57-1.42\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003e0.65\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 94px;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 92px;\"\u003e\n \u003cp\u003eMetastasis at diagnosis\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 97px;\"\u003e\n \u003cp\u003eNo vs Yes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 54px;\"\u003e\n \u003cp\u003e0.80\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 95px;\"\u003e\n \u003cp\u003e0.64-1.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003e0.06\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 94px;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 92px;\"\u003e\n \u003cp\u003eSurgery to primary tumor (n)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 97px;\"\u003e\n \u003cp\u003eNo vs Yes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 54px;\"\u003e\n \u003cp\u003e1.26\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 95px;\"\u003e\n \u003cp\u003e0.97-1.62\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003e0.07\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 94px;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 92px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 97px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"3\" valign=\"top\" style=\"width: 227px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eUnivariate analysis\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"3\" valign=\"top\" style=\"width: 234px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eMultivariate analysis\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 189px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eOverall survival\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 54px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eHR\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 95px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e95% CI\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003e\u003cstrong\u003ep\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eHR\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 94px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e95% CI\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\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 valign=\"top\" style=\"width: 92px;\"\u003e\n \u003cp\u003eAntibiotic use\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 97px;\"\u003e\n \u003cp\u003eNon-use vs Use\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 54px;\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 95px;\"\u003e\n \u003cp\u003e0.77-1.31\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003e0.96\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 94px;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"3\" valign=\"top\" style=\"width: 92px;\"\u003e\n \u003cp\u003eIMDC score\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 97px;\"\u003e\n \u003cp\u003eFavorable\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 149px;\"\u003e\n \u003cp\u003eReference\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003e0.15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 170px;\"\u003e\n \u003cp\u003eReference\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e0.46\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 97px;\"\u003e\n \u003cp\u003eIntermediate\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 54px;\"\u003e\n \u003cp\u003e1.70\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 95px;\"\u003e\n \u003cp\u003e0.83-3.48\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003e0.14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e1.55\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 94px;\"\u003e\n \u003cp\u003e0.70-3.45\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e0.28\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 97px;\"\u003e\n \u003cp\u003ePoor\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 54px;\"\u003e\n \u003cp\u003e2.11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 95px;\"\u003e\n \u003cp\u003e1.10-4.46\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003e0.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e1.64\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 94px;\"\u003e\n \u003cp\u003e0.72-3.69\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e0.23\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"4\" valign=\"top\" style=\"width: 92px;\"\u003e\n \u003cp\u003eBest response to nivolumab\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 97px;\"\u003e\n \u003cp\u003eComplete\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 149px;\"\u003e\n \u003cp\u003eReference\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003e0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 170px;\"\u003e\n \u003cp\u003eReference\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 97px;\"\u003e\n \u003cp\u003ePartial\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 54px;\"\u003e\n \u003cp\u003e0.58\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 95px;\"\u003e\n \u003cp\u003e0.13-2.62\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003e0.48\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e0.62\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 94px;\"\u003e\n \u003cp\u003e0.12-2.90\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e0.54\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 97px;\"\u003e\n \u003cp\u003eStable\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 54px;\"\u003e\n \u003cp\u003e0.80\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 95px;\"\u003e\n \u003cp\u003e0.18-3.47\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003e0.76\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e0.85\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 94px;\"\u003e\n \u003cp\u003e0.18-3.88\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e0.83\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 97px;\"\u003e\n \u003cp\u003eProgression\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 54px;\"\u003e\n \u003cp\u003e2.29\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 95px;\"\u003e\n \u003cp\u003e0.53-9.85\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003e0.26\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e2.50\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 94px;\"\u003e\n \u003cp\u003e0.56-11.14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e0.22\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 92px;\"\u003e\n \u003cp\u003eNumber of metastatic sites\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 97px;\"\u003e\n \u003cp\u003e\u0026ge;2 vs 1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 54px;\"\u003e\n \u003cp\u003e1.35\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 95px;\"\u003e\n \u003cp\u003e0.80-2.28\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003e0.25\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 94px;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 92px;\"\u003e\n \u003cp\u003eMetastasis at diagnosis\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 97px;\"\u003e\n \u003cp\u003eNo vs Yes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 54px;\"\u003e\n \u003cp\u003e0.54\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 95px;\"\u003e\n \u003cp\u003e0.32-0.91\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003e0.023\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e0.96\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 94px;\"\u003e\n \u003cp\u003e0.25-2.24\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e0.11\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 92px;\"\u003e\n \u003cp\u003eSurgery to primary tumor (n)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 97px;\"\u003e\n \u003cp\u003eNo vs Yes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 54px;\"\u003e\n \u003cp\u003e0.94\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 95px;\"\u003e\n \u003cp\u003e0.56-1.59\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003e0.84\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 94px;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cdiv align=\"left\" class=\"colspec\"\u003e\u003cbr\u003e\u003c/div\u003e\n\u003cdiv align=\"left\" class=\"colspec\"\u003eAbbreviations Confidence Interval (CI), Hazard Ratio (HR), International Metastatic Renal Cell Carcinoma Database Consortium Risk Score (IMDC score), Overall survival (OS), Progression free survival (PFS)\u003c/div\u003e\n\u003cp\u003e\u003c/p\u003e\n\u003cp\u003eHypothyroidism (5 [14.3%]), dermatitis (2 [5.7%]), increased transaminases (1 [2.9%]), pneumonitis (1 [2.9%]), and fatigue (1 [2.9%]) were observed in patients who used Abx during nivolumab treatment. Hypothyroidism (8 [11.9%]), dermatitis (4 [6%]), diarrhea (1 [1.5%]), and fatigue (1 [1.5%]) side effects were observed in non-Abx users during nivolumab treatment. There was no significant difference in the incidence of side effects between Abx users (13 [37.1%] with side effects and 22 [62.9%] without side effects) and non-users (46 [68.6%] with side effects and 21 [31.4%] without side effects) (p\u0026thinsp;=\u0026thinsp;0.24).\u003c/p\u003e"},{"header":"Discussions","content":"\u003cp\u003eIn many countries, as in our country, immunotherapy treatments are difficult to access in the first-line setting (due to reimbursement, licensing, and clinical practice rules for TKIs in the first-line setting) and are used in the second-line or subsequent-line treatment.\u003c/p\u003e \u003cp\u003eIn our study, mPFS was lower with concurrent Abx use in patients receiving nivolumab in the second-line treatment of mRCC. PFS was found to be a statistically significant worse risk factor with concurrent Abx use. IMDC score and best response to nivolumab for PFS, IMDC score, best response to nivolumab, and metastasis at diagnosis were found to be independent risk factors for OS. There was no statistical difference in the degree of any side effect, primary tumor surgery, number of metastatic sites, tyrosine kinase inhibitor types used before nivolumab treatment, age, gender, body mass index, ECOG score, and Abx types.\u003c/p\u003e \u003cp\u003eIn recent years, factors affecting OS and PFS have been emphasized in the use of immunotherapy. One of the most emphasized factors is the gut microbiota in the gastrointestinal system. The effect of intestinal flora on the body's immune system and immune system diseases caused by disruption of intestinal flora and its negative effects have been frequently discussed in many diseases in recent years[\u003cspan additionalcitationids=\"CR10 CR11\" citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. It is emphasized in publications that the body's immune system is negatively affected as a result of the increase in harmful bacteria (\u003cem\u003eC. hathewayi\u003c/em\u003e, \u003cem\u003eE. rectale\u003c/em\u003e, )[\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e] as a result of fecal microbiota analyses and that the immune response can be increased by increasing the variety of immunostimulatory bacteria (\u003cem\u003eAkkermansia muciniphila, Bifidobacterium longum, Bacteroides fragilis, Enterococcus hirae\u003c/em\u003e type 13144, \u003cem\u003eBifidobacterium adolescentis, Barnesiella intestinihominis\u003c/em\u003e) with probiotic supplements[\u003cspan additionalcitationids=\"CR15 CR16\" citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]. Some metabolites produced by intestinal bacteria, such as short-chain fatty acids and inosine, increase the therapeutic effects of ICIs by activating CD8\u0026thinsp;+\u0026thinsp;T cells[\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]. Inosinin produced by \u003cem\u003eAkkermansia muciniphila\u003c/em\u003e activates T cells, as a result of the decrease in the amount of inosinin after the use of Abx, the microbiome balance is disrupted, leading to a decrease in treatment efficacy[\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]. Hagihara M et al conducted a randomized trial to investigate the effects of CBM588 (a butyrate-producing non-pathogenic strain of \u003cem\u003eClostridium butyricum\u003c/em\u003e, believed to restore healthy microbiota through increasing interleukin-17A-producing T cells and CD4[+] cells in the lamina propria). This study randomized patients to receive nivolumab and ipilimumab with (n\u0026thinsp;=\u0026thinsp;19) or without (n\u0026thinsp;=\u0026thinsp;19) CBM588. mPFS was greater in the nivolumab-ipilimumab plus CBM588 arm compared to the nivolumab-ipilimumab alone arm (12.7 vs 2.5 months, HR 0.15, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001) [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eIn preclinical laboratory studies, diminished quantity and capacity of immune cells as a result of dysbiosis caused by antibiotic usage have been reported. Recently, clinical investigations evaluating the usage of immunotherapy and Abx as regards to survival of patients have increased. Derosa L et al.[\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e] included 106 patients with mRCC receiving PD-(L)1 mono therapy. Patients with Abx had shorter PFS and OS than those without Abx (mPFS, 1.9 months vs 7.4 months, P\u0026thinsp;\u0026lt;\u0026thinsp;0.01; mOS, 17.3 months vs 30.6 months, P\u0026thinsp;\u0026lt;\u0026thinsp;0.03). In another phase 2 study by Derosa L. et al[\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e], 707 patients were included and 104 patients used Abx. ORR was found to be 15.1% in Abx users and 21.1% in non-users. The mOS was 13.0 months versus 25.0 months and mPFS was 2.6 months versus 3.8 months in Abx users and non-users, respectively. The study by Lalani AA et al.[\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e] included 146 patients who received ICI in the first series and subsequent series, 31 of whom received Abx. For patients treated with ICI who also received systemic Abx compared with non-receiver, ORR was lower (12.9% vs. 34.8%, p\u0026thinsp;=\u0026thinsp;0.026), PFS was shorter (p\u0026thinsp;=\u0026thinsp;0.007) and OS was worse (p\u0026thinsp;=\u0026thinsp;0.270). Katsurayama N et al[\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]. included patients receiving ICI in the first-line treatment phase. Of 128 mRCC patients, 30 (23%) received Abx. Abx-treated patients exhibited shorter mPFS and mOS compared to those who did not receive Abx (median mPFS: 4.9 vs. 16.1 months, p\u0026thinsp;\u0026lt;\u0026thinsp;0.0001 mOS: 20.8 vs. 49.0 months, p\u0026thinsp;=\u0026thinsp;0.0034). In similar studies by Routy et al.[\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e], Tinsley N et al.[\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e], Ueda K et al.[\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e], and Kulkarni AA et al.[\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e], worsening in both OS and PSF was found in patients using Abx with ICI. DC Guven et al[\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]. evaluated the use of immunotherapy in the second series, 93 patients were included, and 31 patients were on Abx and ICI. The ORR was lower in Abx users compared to non-users (24.1% vs. 50%, P\u0026thinsp;=\u0026thinsp;0.023). There was a statistically significant difference in PFS, p\u0026thinsp;=\u0026thinsp;0.004, and OS, p\u0026thinsp;=\u0026thinsp;0.018 in Abx users compared to non-users. Buti S et al.[\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e] study, 305 patients with mRCC receiving ICI combination therapy in first-line treatment were included and scoring was performed according to Abx, steroid and proton pump inhibitors (PPI) (Abx 1 point, PPI 1 point, steroid 2 points). The 12-month mOS (73% vs. 44% (P\u0026thinsp;\u0026lt;\u0026thinsp;0.0001) and mPFS were 11.6 months and 4.8 months for patients belonging to the favorable group (score 0\u0026ndash;1) and unfavorable group (score 2\u0026ndash;4), respectively (P\u0026thinsp;=\u0026thinsp;0.002). In our study, 102 patients were included in the study, 35 of whom used ICI plus Abx. The mPFS was 6.7 months and 9.4 months (p\u0026thinsp;=\u0026thinsp;0.04), mOS was 22.04 months and 29.8 months (p\u0026thinsp;=\u0026thinsp;0.96) in ICI plus Abx users and non-users, respectively.\u003c/p\u003e \u003cp\u003eIn our study, unlike other studies[\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e, \u003cspan additionalcitationids=\"CR22 CR23 CR24\" citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e, \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e], the patient group who received only nivolumab in the second-line treatment after the first series of TKI in mRCC were included, patients who received only one type of Abx and patients who received Abx treatment together with ICI (those who received Abx before and after ICI were not included) were included. Another difference in our study was that the Abx used were different. In other studies[\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e, \u003cspan additionalcitationids=\"CR22 CR23 CR24 CR25 CR26\" citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e], beta-lactam Abx was used more, but in our study, the most commonly used Abx group was Quinolones (57.2%) followed by beta-lactam Abx (42.8%). In other studies, studies[\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e, \u003cspan additionalcitationids=\"CR22 CR23 CR24 CR25 CR26\" citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e], a significant difference was found in both OS and PFS in patients who used Abx together with ICI, but in our study, there was a statistically significant difference in PFS, but no statistically significant difference was found in OS.\u003c/p\u003e \u003cp\u003eThe limitations of our study were that the patient population was relatively small, Abx diversity was low and it was a retrospective study. The patient groups with and without concomitant Abx use were following our current practice and it was a multi-center study.\u003c/p\u003e \u003cp\u003eIn conclusion, concurrent Abx use in mRCC patients treated with nivolumab negatively affects immunotherapy efficacy and treatment response. Clinicians should be cautious about the concomitant use of immunotherapy and Abx in such patients.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAuthor contribution\u003c/strong\u003e Concept \u0026mdash; MU, MZK and MA. Design \u0026mdash; MU and MA. Supervision \u0026mdash; all authors. Data collection and/or processing \u0026mdash; all authors. Analysis and/or interpretation \u0026mdash; MZK and MA. Literature search \u0026mdash;TBG, M\u0026Ccedil; and GD. Writing \u0026mdash; MU, SU, MZK, MKE,MA and MA. Critical reviews \u0026mdash; all authors.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData availability\u003c/strong\u003e Data will be provided by the corresponding author.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics approval\u003c/strong\u003e This research was conducted ethically in accordance with the World Medical Association Helsinki Declaration. All patients had to give informed consent before participating in our sensitive study. Ethics approval was obtained from -------------------------- Medical Faculty, ----, ----- (Ethics Committee Number: 2023/4155).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eInformed consent\u003c/strong\u003e Because the study was designed retrospectively, no informed consent was obtained from the patients.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConflict of interest\u003c/strong\u003e The authors declare no competing interests.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e None\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n \u003cli\u003eLjungberg B, Albiges L, Abu-Ghanem Y, et al. European Association of Urology Guidelines on Renal Cell Carcinoma: The 2019 Update. \u003cem\u003eEur Urol\u003c/em\u003e. 2019;75(5):799-810. https://doi.org/10.1016/j.eururo.2019.02.011 \u003c/li\u003e\n \u003cli\u003eHumphrey PA, Moch H, Cubilla AL, Ulbright TM, Reuter VE. 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Gut microbiota influence immunotherapy responses: mechanisms and therapeutic strategies. \u003cem\u003eJ Hematol Oncol\u003c/em\u003e. 2022;15(1):47. https://doi.org/10.1186/s13045-022-01273-9\u003c/li\u003e\n \u003cli\u003eMager LF, Burkhard R, Pett N, et al. Microbiome-derived inosine modulates response to checkpoint inhibitor immunotherapy. \u003cem\u003eScience\u003c/em\u003e. 2020;369(6510):1481-1489. https://doi.org/10.1126/science.abc3421\u003c/li\u003e\n \u003cli\u003eHagihara M, Kuroki Y, Ariyoshi T, et al. Clostridium butyricum Modulates the Microbiome to Protect Intestinal Barrier Function in Mice with Antibiotic-Induced Dysbiosis. \u003cem\u003eiScience\u003c/em\u003e. 2020;23(1):100772. https://doi.org/10.1016/j.isci.2019.100772\u003c/li\u003e\n \u003cli\u003eL. Derosa, C. Alves Costa Silva, C. Dalban, 657MO Antibiotic (ATB) therapy and outcome from nivolumab (N) in metastatic renal cell carcinoma (mRCC) patients (pts): Results of the GETUG-AFU 26 NIVOREN multicentric phase II study, Annals of Oncology, Volume 32, Supplement 5, 2021, Page S681.\u003c/li\u003e\n \u003cli\u003eLalani AA, Xie W, Braun DA, et al. Effect of Antibiotic Use on Outcomes with Systemic Therapies in Metastatic Renal Cell Carcinoma. \u003cem\u003eEur Urol Oncol\u003c/em\u003e. 2020;3(3):372-381.https://doi.org/10.1016/j.euo.2019.09.001\u003c/li\u003e\n \u003cli\u003eKatsurayama N, Ishihara H, Ishiyama R, et al. Prognostic Impact of the Administration of Antibiotics and Proton Pump Inhibitors in Immune Checkpoint Inhibitor Combination Therapy for Advanced Renal Cell Carcinoma. \u003cem\u003eCancer Diagn Progn\u003c/em\u003e. 2024;4(4):496-502. https://doi.org/10.21873/cdp.10354\u003c/li\u003e\n \u003cli\u003eUeda K, Yonekura S, Ogasawara N, et al. 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Concomitant Drugs Prognostic Score in Patients With Metastatic Renal Cell Carcinoma Receiving Ipilimumab and Nivolumab in the Compassionate Use Program in Italy: Brief Communication. \u003cem\u003eJ Immunother\u003c/em\u003e. 2023;46(1):22-26. https://doi.org/10.1097/CJI.0000000000000446\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"renal cell carcinoma, nivolumab, antibiotherapy, survival, dysbiosis","lastPublishedDoi":"10.21203/rs.3.rs-6066659/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6066659/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eAim:\u003c/strong\u003e Immunotherapy has brought a new perspective to cancer treatments. However, the response of patients to the novel drug is heterogeneous. It is essential to reveal the factors that may affect the outcomes. It was aimed to evaluate the effect of antibiotherapy (Abx) on overall survival (OS) and progression-free survival (PFS) in patients with metastatic renal cell carcinoma (mRCC) receiving second-line nivolumab treatment.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethod:\u003c/strong\u003e The study is a multicentre, retrospective, multicentre design that included patients with metastatic renal cell carcinoma who used nivolumab in second-line treatment. One hundred and two patients with mRCC were divided into two groups according to whether they used Abx with nivolumab: concurrent Abx users and non-users. Overall survival (OS) and progression-free survival (PFS) were compared between the groups with and without concurrent Abx.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults: \u003c/strong\u003eOf the 102 patients included in the study, 67 (65.7%) of the patients did not receive Abx treatment, while 35 (34.3%) of the patients used Abx. Quinolones were the most commonly used Abx group (57.2 %). This was followed by beta-lactams Abx (42.8%). Median PFS was 9.4 (4.4-14.4) months in non-Abx users and 6.7 (5.9-7.5) months in Abx users (p=0.04). mOS was 29.8 (23.6-35.9) months in non-Abx users and 22.04 (16.4-27.7) months in Abx users (p=0.96).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusion: \u003c/strong\u003eConcurrent Abx usage in mRCC patients treated with nivolumab negatively affects immunotherapy efficacy and treatment response. Clinicians should be cautious about the concomitant use of immunotherapy and Abx in such patients.\u003c/p\u003e","manuscriptTitle":"The Efficiency of Concomitant Antibiotic Usage On Survival Outcomes of Nivolumab-Treated Metastatic Renal Cell Carcinoma Patients: A Multicenter Experience","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-03-11 09:39:21","doi":"10.21203/rs.3.rs-6066659/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"2a62a065-47f0-4903-b3f4-67c3b87458b3","owner":[],"postedDate":"March 11th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2025-03-11T09:39:23+00:00","versionOfRecord":[],"versionCreatedAt":"2025-03-11 09:39:21","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-6066659","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6066659","identity":"rs-6066659","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}