Real-World Predictors of Response to Immunotherapy in Metastatic Renal Cell Carcinoma: The Emerging Role of the Urologist in Immuno-Oncology

Introduction

Cancer treatment has evolved over recent decades from approaches primarily targeting tumor cells to strategies that also modulate the tumor microenvironment and host immune response.¹ This paradigm shift has enabled the development of therapies such as immune checkpoint inhibitors, which act by reshaping the interaction between cancer cells and their surrounding immune milieu.²

Immune checkpoint inhibitors (ICIs) have transformed the therapeutic landscape of mRCC by achieving durable responses in selected patients and redefining survival expectations.^3,4 The incorporation of immunotherapy—either as monotherapy or in combination regimens—has shifted clinical decision-making paradigms, with urologists increasingly taking a leading role in systemic treatment selection by participating in multidisciplinary tumor boards, identifying candidates for immunotherapy based on clinical and surgical factors, and coordinating treatment sequencing and follow-up.

Despite these advances, responses to ICIs remain highly variable, and robust biomarkers to identify patients most likely to benefit are still lacking. The absence of validated predictive and prognostic tools limits precision in treatment sequencing, particularly in real-world experiences, where detailed characterization is feasible but statistical power remains limited. Data from Spanish or Iberian cohorts evaluating prognostic models in immunotherapy-treated mRCC remain particularly scarce.

Several prognostic models have been proposed to stratify mRCC patients and guide systemic therapy choice. The IMDC score, based on clinical and laboratory parameters—performance status, time from diagnosis to treatment, hemoglobin, calcium, neutrophil, and platelet counts— remains the most widely used and validated tool.^5,6 However, its predictive ability may be limited in the immunotherapy era. The Meet–URO score, recently validated in large retrospective series,⁷ builds upon the IMDC model by incorporating the same clinical and laboratory parameters while additionally including bone metastases and lymphocyte count to refine prognostic stratification. Similarly, the FAN score integrates inflammatory and nutritional biomarkers—namely the fibrosis-4 (Fib-4) index, albumin-bilirubin (ALBI) score, and neutrophil-to-lymphocyte ratio (NLR)—reflecting host–tumor interactions and correlating with survival outcomes in ICI-treated RCC.^8,9 However, direct comparisons among IMDC, Meet-URO, and FAN score remain scarce, particularly in smaller or regional cohorts with real-world data.

Beyond composite scores, peripheral blood biomarkers such as the neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), and eosinophil percentage have shown variable prognostic utility in solid tumors, including RCC.^10–12 Their accessibility makes them attractive for early risk stratification and treatment monitoring, although their prognostic role in ICI-treated mRCC remains to be clarified.

Furthermore, the relevance of cytoreductive nephrectomy (CN) in the immunotherapy era continues to be debated. While recent studies suggest a survival benefit in selected patients,^13–15 prospective validation remains limited.

In this context, we hypothesize that integrating established prognostic scores (IMDC, Meet-URO, and FAN score) and cytoreductive nephrectomy, along with clinical features and early treatment-related analytic biomarkers, could improve the prediction of survival outcomes in mRCC patients treated with ICIs. Given the limited sample size, comparisons between prognostic models were considered exploratory.

This study aimed to evaluate clinical and pathological predictors, prognostic scoring systems, and peripheral blood biomarkers associated with treatment response, progression-free survival (PFS), and overall survival (OS) in a real-world Spanish cohort. Specifically, we sought to:

1. Compare baseline characteristics across different immunotherapy regimens;
2. Assess the prognostic impact of cytoreductive nephrectomy;
3. Validate and compare the discriminative capacity of IMDC, Meet-URO, and FAN scores;
4. Explore the association between early-treatment biomarkers—NLR, PLR, and eosinophil percentage—and survival outcomes.

By addressing this gap, we aim to contribute real-world evidence from a Spanish cohort to support individualized treatment strategies and refine prognostic assessment in the evolving immunotherapy era of mRCC.

Material and Methods

Study Design and Population

We conducted a retrospective, single-center cohort study, including consecutive patients with metastatic renal cell carcinoma (mRCC) who received immune checkpoint inhibitor (ICI)-based therapy between January 2019 and March 2024. Eligible patients had histologically confirmed RCC and measurable metastatic disease, and received ICI either as first-line combination therapy—nivolumab plus ipilimumab or pembrolizumab plus axitinib—or as ≥2nd-line nivolumab monotherapy. Cytoreductive nephrectomy, when performed, was carried out prior to ICI initiation, while histological diagnosis in non-surgical patients was established by biopsy. Patients with incomplete clinical records or a follow-up shorter than one month after ICI initiation were excluded. The data cutoff date for follow-up was July 31, 2025.

Data Collection and Variables

Demographic, clinical, and pathological data were retrieved from electronic medical records. Baseline variables included age, sex, Eastern Cooperative Oncology Group (ECOG) performance status, timing of metastases (synchronous versus metachronous), metastatic sites, prior cytoreductive nephrectomy (defined as surgical removal of the primary renal tumor in the presence of metastatic disease), histologic subtype, Fuhrman grade, presence of sarcomatoid features, TNM stage, and prognostic classification according to the International Metastatic RCC Database Consortium (IMDC). Laboratory parameters recorded at baseline and at one month after treatment initiation included neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), and eosinophil percentage.

Tumor progression was assessed using Response Evaluation Criteria in Solid Tumors (RECIST) version 1.1,¹⁶ based on radiologic imaging and clinical evaluation. Prognostic scores evaluated comprised IMDC, Meet-URO, and FAN score, calculated according to their original definitions. For subgroup analyses, IMDC favorable-risk patients and Meet-URO group 1 were excluded, as these groups largely overlap and their excellent prognosis provides limited additional discriminatory value for assessing the performance of prognostic models, consistent with the methodology adopted in the original Meet-URO validation studies. Their inclusion may dilute the ability of the model to distinguish clinically meaningful risk differences among intermediate and poor-risk patients.

Regarding the inflammatory and nutritional biomarkers (NLR, PLR, eosinophil percentage), initial attempts to establish optimal cutoff points for pre- and post-treatment NLR, PLR, and eosinophils through area under the receiver operating characteristic curve (ROC) analysis revealed poor discriminatory power, likely due to the limited sample size and reduced statistical power. Therefore, cutoff points were adopted from the existing literature: NLR cutoff was set at 2.44 and PLR at 181, based on the work of Pacholczak-Madej et al,¹¹ who derived these thresholds via ROC analysis averaging optimal points across three different time points (baseline, 3 months post-treatment, and pre-progression). The eosinophil percentage cutoff was established at 3%, with categories <3% and ≥3%, as reported by Tasaki et al¹² No patients experienced progression or death within the first month after ICI initiation; therefore, all included patients were evaluable for post-treatment biomarker analyses at this timepoint, minimizing the risk of immortal time bias.

Endpoints

The primary endpoints were overall survival (OS), defined as the time from ICI therapy initiation to death from any cause, and progression-free survival (PFS), defined as the time from ICI initiation to documented radiologic or clinical progression or death, whichever occurred first. Secondary objectives included identifying clinical, pathological, and laboratory predictors of OS and PFS.

Statistical Analysis

Baseline characteristics were compared between treatment groups (first-line pembrolizumab–axitinib, first-line nivolumab–ipilimumab, second-line nivolumab, and third-line nivolumab) using the Monte Carlo exact test (derived from the chi-square test) for categorical variables and the Kruskal–Wallis test for continuous variables. Survival analyses were performed using the Kaplan–Meier method, with the Log rank test employed for univariable comparisons. Hazard ratios (HRs) and 95% confidence intervals (CIs) were estimated using Cox proportional hazards regression models.

Multivariable Cox models were constructed using a stepwise approach, including variables with established clinical relevance and those with a univariable p-value <0.10. Given the limited number of events, the number of variables included in multivariable models was restricted to avoid overfitting. The proportional hazards assumption was assessed using graphical inspection of log-minus-log survival plots. These analyses were considered exploratory and no formal assessment of model assumptions or internal validation was performed.

Statistical significance was set at p<0.05 (two-tailed). All statistical analyses were conducted using SPSS Statistics version 25.0 (IBM Corp., Armonk, NY, USA).

Ethics Statement

The study was conducted in accordance with the Declaration of Helsinki and approved by the local institutional ethics committee. The requirement for informed consent was waived due to the retrospective nature of the analysis and anonymization of patient data.

Results

Patient Characteristics

A total of 32 patients with metastatic renal cell carcinoma (mRCC) treated with immune checkpoint inhibitors (ICIs) between January 2019 and March 2024 were included in this study. The median follow-up was 14.0 months (95% CI, 0.0–29.15). No patients were lost to follow-up; at the time of data cutoff, 15 patients had died and 17 remained under active follow-up. Among them, 15 patients (46.9%) received first-line nivolumab–ipilimumab, 3 (9.4%) received first-line pembrolizumab–axitinib, 13 (40.6%) received second-line nivolumab, and 1 patient (3.1%) received third-line nivolumab. The median age at treatment initiation was 64 years (interquartile range (IQR) 58–69), with a predominance of males (23/32; 72%). Clear-cell histology was observed in 31 patients (96.9%), sarcomatoid features in 6 (18.8%), and cytoreductive nephrectomy (CN) had been performed in 25 patients (78.1%). The majority of patients were classified as intermediate risk by the IMDC criteria (24/32; 75%) and had synchronous metastases at diagnosis (23/32; 72%). Baseline demographic, clinical, pathological, and laboratory variables were balanced across treatment groups, with no statistically significant differences detected (all p>0.05 by Monte Carlo exact chi-square or Kruskal–Wallis tests) (Table 1).

Table 1 Baseline Clinical, Pathological, and Laboratory Characteristics of Patients with Metastatic Renal Cell Carcinoma Treated with Immunotherapy, Stratified by Treatment Régimen

Impact of Cytoreductive Nephrectomy

CN was significantly associated with improved survival outcomes. In univariable Cox regression analysis, patients without CN had a markedly increased risk of disease progression (hazard ratio (HR) 3.72; 95% confidence interval (CI) 1.15–12.02; p=0.028) and death (HR 4.03; 95% CI 1.14–14.19; p=0.030) compared to those who underwent CN. Consistently, Kaplan–Meier estimates demonstrated that median progression-free survival (PFS) was significantly longer in patients with CN (9 months) than those without (3 months; log-rank p=0.015). Similarly, median overall survival (OS) was 21 months versus 3 months favoring the CN group (log-rank p=0.020) (Table 2 and Figure 1).

Table 2 Progression-Free and Overall Survival According to Cytoreductive Nephrectomy, Sex, and Presence of Synchronous Metastases in Patients with Metastatic Renal Cell Carcinoma Treated with Immunotherapy

Figure 1 Kaplan–Meier curves and number-at-risk tables for progression-free survival (left; (A)) and for overall survival (right; (B)) in metastatic renal carcinoma (mRCC) patients receiving immunotherapy, stratified by cytoreductive nephrectomy status.

Other Clinical Predictors

Female sex (9/32; 28%) and absence of synchronous metastases (9/32; 28%) were associated with trends toward longer OS, though these associations did not reach statistical significance in Cox models (both p=0.113). However, significant differences were observed in log-rank survival comparisons: median OS was 39 months in females versus 9 months in males (p=0.005), and 39 months in patients with metachronous metastases versus 9 months in those with synchronous metastases (p=0.005). No statistically significant associations were observed between survival and age, histologic subtype, presence of sarcomatoid features, or metastatic sites, though nonsignificant trends were noted. (Table 2)

Treatment Line and Survival Outcomes

Patients were grouped into first-line (treatment-naïve) and ≥2nd-line (pretreated) settings to explore potential differences between clinically distinct populations. Patients receiving first-line ICI therapy (n=18) had a median PFS of 9 months compared to 5 months for those receiving second- or third-line therapy (n=14), but this difference was not statistically significant (p=0.684). Similarly, median OS was 11 months versus 21 months for first-line versus later-line therapy groups, respectively (p=0.451). (Table 3). These findings suggest that, within the limitations of this cohort, treatment line did not significantly impact survival outcomes.

Table 3 Progression-Free and Overall Survival According to Line of Treatment in Patients with Metastatic Renal Cell Carcinoma Treated with Immunotherapy

Prognostic Scoring Systems

The IMDC risk classification did not significantly stratify OS (p=0.792) or PFS (p=0.830) in this cohort. The apparent longer survival observed in the IMDC poor-risk group compared to the intermediate-risk group is likely explained by the small sample size and the predominance of intermediate-risk patients, leading to subgroup imbalance. Conversely, the Meet-URO score significantly discriminated OS (p=0.043), with median OS ranging from 21 months in group 3 to only 1–2 months in groups 4 and 5. This observation, although based on a small cohort, suggests potential added value of Meet-URO in the immunotherapy setting. Meet-URO’s superior stratification for OS mirrors findings from other cohorts.¹⁶ Consistent with its original design as an OS-predictive model, Meet-URO did not significantly predict PFS in this cohort (p=0.380). The FAN score showed no statistically significant prognostic value for OS (p=0.282) or PFS (p=0.618) (Table 4 and Figure 2).

Table 4 Progression-Free and Overall Survival According to Prognostic Scores (IMDC, MEET-URO, and FANSCORE) in Patients with Metastatic Renal Cell Carcinoma

Figure 2 Kaplan–Meier curves and number-at-risk tables for overall survival (OS) in mRCC patients receiving immunotherapy, stratified by Meet-URO score.

Analytical Biomarkers

One month after treatment initiation, patients with neutrophil-to-lymphocyte ratio (NLR) <2.44 (n=14) exhibited significantly longer PFS compared to those with NLR ≥2.44 (median 17 vs. 7 months; log-rank p=0.014), which is consistent with broader real-world evidence of NLR predictive value.^17,18 In multivariable Cox regression, low NLR remained an independent predictor of longer PFS (HR 0.073; 95% CI 0.006–0.859; p=0.037). Platelet-to-lymphocyte ratio (PLR) <181 showed a non-significant trend toward improved PFS (p=0.051). The eosinophil percentage, dichotomized at 3%, did not demonstrate prognostic significance for either PFS or OS (Table 5 and Figure 3).

Table 5 Prognostic Value of Analytical Biomarkers at One Month After Initiation of Immunotherapy in Patients with Metastatic Renal Cell Carcinoma

Figure 3 Kaplan–Meier curves and number-at-risk tables for progression-free survival according to neutrophil-to-lymphocyte ratio (NLR) measured at 1 month after initiation of immunotherapy. Cut-off value:x 2.44, based on published literature.

Discussion

Our findings support and expand upon previous multicenter studies investigating prognostic factors in mRCC treated with ICIs. In agreement with multicenter real-world data as the one led by Lai et al¹⁹ or Bakouny et al,²⁰ cytoreductive nephrectomy (CN) remained associated with improved survival outcomes, although this association should be interpreted with caution given the potential for confounding by indication, as patients selected for surgery are more likely to have favorable performance status and lower disease burden, reinforcing its relevance in appropriately selected patients even in the ICI era. Similarly, the superior discriminative performance of the Meet–URO score over the IMDC model in our cohort mirrors results from large validations in both ESMO Open⁷ and Clinical Genitourinary Cancer,²¹ confirming Meet–URO’s enhanced prognostic granularity for ICI-treated patients.^22–25 According to the prospective validation, a prospective real-world study is currently ongoing.²⁶

The independent association between low early NLR and prolonged PFS aligns with accumulating evidence from Eur Urol Oncol²⁷ and Urol Oncol,²⁸ suggesting that early dynamic inflammatory changes may reflect effective immune activation and treatment response. This supports its potential role as a pragmatic, cost-effective biomarker in clinical practice, although its findings should be interpreted as exploratory given the limited sample size and lack of statistical power.

Importantly, the strengths of this study include the integration of both clinical and laboratory parameters for risk stratification, while limitations involve the retrospective, single-center design, small sample size, treatment heterogeneity, and potential selection bias, which may reduce the robustness and generalizability of our findings. In particular, the retrospective design precludes causal inference regarding the effect of cytoreductive nephrectomy, and residual confounding cannot be excluded in the absence of propensity-adjusted analyses. Future multicenter validations and machine learning–based approaches could further integrate these parameters for dynamic, individualized prognostication. The incorporation of urologists into multidisciplinary immuno-oncology networks will be critical to translating these advances into improved patient outcomes.

Overall, the combined assessment of cytoreductive nephrectomy and advanced prognostic scores (particularly Meet-URO) may enhance risk stratification and personalization of immunotherapy in mRCC. However, mechanistic immune profiling, including tumor-intrinsic and molecular biomarkers, was not available in this cohort, which limits the ability to fully integrate tumor-immune axis characterization; clinical-inflammatory models therefore remain surrogate and incomplete.²⁹

Conclusion

In this single-center, real-world cohort of 32 patients with metastatic renal cell carcinoma (mRCC) treated with immune checkpoint inhibitors (ICIs), cytoreductive nephrectomy was associated with improved progression-free and overall survival, consistent with multicenter studies in patients treated with tyrosine kinase inhibitors or ICIs, including older adults.¹⁹ The Meet-URO score demonstrated superior prognostic discrimination for overall survival compared to the IMDC classification,^22–25 in line with large real-world analyses reporting higher c-index values.^7,21 An early post-treatment neutrophil-to-lymphocyte ratio (NLR) below 2.44 was associated with longer PFS, supporting the prognostic relevance of dynamic inflammatory biomarkers in the ICI era.^30–34

Overall, cytoreductive nephrectomy, the Meet-URO score, and early on-treatment NLR emerged as the key factors associated with survival outcomes, whereas the FAN score and eosinophil percentage did not provide meaningful prognostic value. Integrating clinical variables, validated prognostic scores, and dynamic biomarkers may offer a pragmatic framework for risk stratification and treatment personalization in mRCC, consistent with current EAU and NCCN guidelines.^35–37

These findings should be considered hypothesis-generating and require validation in larger, independent cohorts. Future multicenter studies and machine learning–based approaches may further refine this multifactorial model and support its integration into urologist-led immuno-oncology care.