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Korean J Urol Oncol > Volume 17(3); 2019 > Article
Choi, Kim, Sung, Jeon, Jeong, Jeon, Lee, Choi, Kang, and Seo: Prognostic Significance of Systemic Inflammatory Response in Patients with Synchronous and Metachronous Metastatic Renal Cell Carcinoma Receiving First-Line Tyrosine Kinase Inhibitors



To determine whether systemic inflammatory response (SIR), particularly platelet-lymphocyte ratio (PLR) and neutrophil-lymphocyte ratio (NLR), has different prognostic role between patients with metastatic renal cell carcinoma (mRCC) receiving first-line tyrosine kinase inhibitors (TKI).

Materials and Methods

We retrospectively reviewed 547 patients with mRCC who were diagnosed and treated with a first-line TKI between 2007 and 2015. The primary endpoint was overall survival (OS) and secondary endpoint was progression-free survival (PFS). We evaluated differences in survival outcomes according to SIR and identified predictors of OS and PFS.


In synchronous mRCC, patients with a higher PLR had significantly worse OS and PFS. Moreover, a higher NLR was also associated with both worse OS and PFS in these patients. However, PLR was not associated with either OS or PFS in metachronous mRCC patients. While metachronous mRCC patients with a higher NLR had worse OS compared to those with lower NLR, there was no difference in PFS according to the status of NLR. On multivariate analysis, PLR was identified as predictive factor for OS (hazard ratio [HR], 1.55) as well as PFS (HR, 1.39) in patients with synchronous mRCC, but not in patients with metachronous mRCC. Additionally, higher NLR was also remained as predictive factor of both OS (HR, 1.83) and PFS (HR, 1.57) in patients with synchronous mRCC.


Our study indicates that simple biomarkers of SIR, particularly PLR and NLR, can be more useful predictors of survival outcomes in patients with synchronous mRCC rather than metachronous mRCC.


The treatment of metastatic renal cell carcinoma (mRCC) has evolved continuously over the last 2 decades as evidenced by an increase in the 5-year survival rate of advanced mRCC over time (from 7.3% to 12.3%).1 Targeted therapy with tyrosine kinase inhibitor (TKI) has been the standard of systemic treatment for patients with mRCC for more than 10 years. In mRCC patients with clear cell histology, sunitinib or pazopanib is recommended as first-line therapy after tissue sampling. Otherwise, sunitinib, cabo-zantinib or everolimus is recommended in nonclear cell histology patients.
Recently, immunotherapy by using immune checkpoint inhibitor has been received a great interest as a novel drug for mRCC. Nivolumab, a programmed death 1 checkpoint inhibitor, has proved that it is more effective than ever-olimus with advanced RCC patients in CheckMate 025 study. Furthermore, in CheckMate 214 study, nivolumab plus ipilimumab have significantly higher overall survival and objective response rates than sunitinib in same patient population.3 The effects of many immuno-oncology agent have been demonstrated,4,5 and it is apparent that these agents leading a paradigm shift in systemic therapy for mRCC.
As such, the treatment of mRCC continues to develop, optimal treatment for these patients is still obstacle due to the lack of useful biomarker. Although treatment response assessment has been calculated by abdominal and chest computed tomography (CT) or bone scan, the evaluation method for indeterminate lesion is not yet known.
Blood markers of systemic inflammatory response (SIR) such as platelet-lymphocyte ratio (PLR) and neu-trophil-lymphocyte radio (NLR) are suggested as prognostic factors in patients with various type of malignancy. Among many SIR markers, an elevated NLR is a strong indicator of poor prognosis in patients with prostate cancer, bladder cancer, and RCC.912 Also, an elevated PLR is associated with poor oncological outcomes in cancer patients.13,14 Considering the emerging role of immune-onco-logic drugs in mRCC, SIR can be a simple and valuable biomarker.
Metastatic RCC is classified as either synchronous or metachronous. However, according to our knowledge, there is no report on different prognostic role of SIR between these 2 types of mRCC. Here, we aimed to determine whether PLR and NLR are prognostic factors of survival outcomes in mRCC who received first-line TKI. In particular, we focused on the different prognostic roles of these biomarkers between synchronous and metachronous mRCC patients.


1. Study Population

We retrospectively reviewed the clinical data of 547 patients with mRCC. Among these patients, 59 patients with no values for NLR and PLR before treatment and 11 patients using the mTOR inhibitors were excluded from the study. We finally analyzed 261 synchronous and 216 metachronous mRCC patients who were treated with first-line systemic TKI between 2007 and 2015. The Institutional Review Board of Samsung Medical Center approved this study (IRB No. SMC 2019-01-165).

2. Study Design

We reviewed the presence of distant metastasis at the time of RCC diagnosis to classify synchronous and meta-chronous mRCC. Synchronous mRCC refers to metastatic disease present at the time of RCC diagnosis. Metachronous mRCC refers to cases where a nephrectomy is performed for primary RCC removal, and metastatic disease is identified on follow-up study.
We reviewed various clinical factors, including age at time of metastasis-diagnosis, age at the time of treatment initiation, sex, the presence of hypertension and diabetes mellitus, body mass index (kg/m), number of metastatic sites, pathologic T stage, Fuhrman nuclear grade, type of first-line TKI, and the International Metastatic Renal Cell Carcinoma Database criteria for mRCC prognosis. All patients had full image staging by CT of the chest, abdomen, and pelvis. The pathological staging and subtype of RCC samples were determined using the American Joint Committee on Cancer TNM system and the Heidelberg recommendations.
Total blood sampling was performed for hematological testing prior to TKI treatment. NLR was calculated as the ratio of absolute neutrophil count to absolute lymphocyte count measured in peripheral blood. PLR was measured in the same manner as the ratio of platelet count to absolute lymphocyte count. Cutoff values of PLR and NLR were divided based on the median value of the population. Pretreatment PLR and NLR cutoff values were 110.5 and 1.9, respectively, for synchronous mRCC. With respect to metachronous mRCC, the PLR and NLR cutoff values were 90.4 and 1.5, respectively.

3. Statistical Analysis

The primary endpoint of the current study was overall survival (OS), defined as the time from initiation of targeted therapy to time of death. Progression-free survival (PFS) was used as a secondary endpoint, and it was defined as time between initiation of targeted therapy to progression, cessation of treatment, or death. Kaplan-Meier curve analysis and log-rank tests were used to compare survival outcomes between groups. Multivariate Cox regression hazard ratio model was used to identify the predictive factors of OS. All descriptive data are presented as the median with interquartile range or percentage (%) of events. Student t-test was used to compare continuous variables and the chi-square test was used to compare categorical variables. Data were analyzed with IBM SPSS Statistics ver. 23.0 (IBM Co., Armonk, NY, USA) and GraphPad Prism software (GraphPad Software Inc., San Diego, CA, USA). All statistical tests were 2 sided, and statistical significance was defined as p<0.05.


Baseline demographics are presented in Table 1. Patient with synchronous mRCC tended to be younger at the time of TKI treatment. With respect to pathological status, there was no difference in the histology of the 2 groups. The most common pathological T stage was T3 (65.4%) in the synchronous population and T1 (42.9%) in the metachro-nous population. There were more cases of Fuhrman high-grade disease in the synchronous population compared to the metachronous population (94.0% vs. 73.6%, respectively).
Table 1.
Baseline clinical characteristics
Characteristic Synchronous (n=261) Metachronous (n=216) p-value
mRCC-diagnosed age (yr) 57.0 (50.0–65.0) 60.0 (53.0–68.0) 0.060
mRCC-treatment age (yr) 57.0 (50.0–66.0) 61.0 (54.0–69.0) 0.021
Sex     0.910
  Male 205 (78.5) 170 (79.4)  
  Female 55 (21.2) 44 (20.6)  
Hypertension 106 (41.2) 95 (44.6) 0.512
Diabetes mellitus 39 (14.9) 47 (21.8) 0.057
Body mass index (kg/m2)     0.155
  > 25 199 (78.3) 148 (72.2)  
  ≤ 25 55 (21.7) 57 (27.8)  
Clinical T stage     < 0.001
  ≤ cT2 104 (39.8) 121 (56.0)  
  ≥ cT3 142 (54.4) 64 (29.6)  
Surgery type     < 0.001
  No or unknown 89 (34.1) 26 (12.0)  
  Radical nephrectomy 168 (64.4) 177 (81.9)  
  Partial nephrectomy 4 (1.5) 13 (6.0)  
Pathology status      
  Pathologic T stage     < 0.001
    T1 28 (15.1) 91 (42.9)  
    T2 24 (13.0) 45 (21.2)  
    T3 121 (65.4) 76 (35.8)  
    T4 12 (6.5) 0 (0)  
  Histology     0.333
    Clear cell 165 (92.2) 196 (89.5)  
    Papillary 13 (7.3) 17 (7.8)  
    Chromophobe 1 (0.6) 6 (2.7)  
  Fuhrman grade     < 0.001
    Low 11 (6.0) 55 (26.4)  
    High 172 (94.0) 153 (73.6)  
No. of metastasis     0.053
  Single 106 (40.6) 107 (49.5)  
  Multiple 155 (59.4) 109 (50.5)  
Tyrosine kinase inhibitor types     0.472
  Sunitinib 149 (57.3) 129 (60.3)  
  Sorafenib 31 (11.9) 25 (11.7)  
  Pazopanib 73 (28.1) 56 (26.2)  
Complete blood counts      
  WBC (/µL) 5,590 (4,295–7,680) 5,740 (4,353–7,438) 0.805
  Hemoglobin (g/dL) 12.6 (10.8–13.9) 13.4 (11.9–14.8) < 0.001
  Platelet (×103/µL) 183.0 (126.0–261.5) 175.0 (122.5–231.3) 0.143
  Neutrophil (/µL) 2,950 (1,940–4,735) 3,036 (1,875–4,260) 0.466
  Lymphocyte (/µL) 1,570 (1,101–2,201) 1,889 (1,437–2,400) < 0.001

Values are presented as median (interquartile range) or number (%). mRCC: metastatic renal cell carcinoma, WBC: white blood cell.

In the overall mRCC population, patients with a higher PLR exhibited poorer OS and PFS outcomes compared to those with a lower PLR (Fig. 1). Likewise, a higher NLR was associated with worse OS and PFS in the overall mRCC population. Interestingly, patients with a higher PLR showed significantly worse and PFS outcomes than those with a lower PLR in the synchronous mRCC population (Fig. 2). In these population, a higher NLR also associated with worse OS and PFS rates. Conversely, there were no differences in terms of OS and PFS outcomes according to the status of PLR in the metachronous mRCC population (Fig. 3). Additionally, there was no difference in PFS according to the status of NLR. A higher NLR was only associated with poorer OS outcomes in patients with metachro-nous mRCC.
Fig. 1.
Overall survival and progression-free survival in overall metastatic renal cell carcinoma patients stratified by median platelet-lymphocyte ratio (PLR) (A, B) and neutrophil-lymphocyte ratio (NLR) (C, D).
Fig. 2.
Overall survival and progression-free survival in synchronous metastatic renal cell carcinoma patients stratified by median platelet-lymphocyte ratio (PLR) (A, B) and neutrophil-lymphocyte ratio (NLR) (C, D).
Fig. 3.
Overall survival and progression-free survival in metachronous metastatic renal cell carcinoma patients stratified by medianplatelet-lymphocyte ratio (PLR) (A, B) and neutrophil-lymphocyte ratio (NLR) (C, D).
In multivariate Cox regression analysis, NLR and PLR are verified as the predicator of OS (Table 2, Supplementary Table 1) and the PFS (Supplementary Tables 2, 3) in synchronous mRCC population. But in metachronous population, PLR was not act as a predicator in neither OS (Table 3) nor PFS (Supplemental Table 4). NLR wasn't predicator in PFS (Supplementary Table 5), but remained as predictive factor of OS (Supplementary Table 6).
Table 2.
PLR – risk factor for OS with synchronous mRCC
Variable Univariate
HR (95% CI) p-value HR (95% CI) p-value
Age (yr)        
  < 65 Reference      
  ≥ 65 1.326 (0.946–1.861) 0.102    
  Male Reference      
  Female 1.114 (0.765–1.622) 0.573    
BMI (kg/m2)        
  < 25 Reference      
  ≥ 25 0.549 (0.361–0.836) 0.005 0.610 (0.385–0.967) 0.036
IMDC criteria        
  Intermediate Reference   Reference  
  Poor 1.967 (1.402–2.759) < 0.001 1.668 (1.150–2.418) 0.007
Clinical T stage        
  ≤ cT2 Reference      
  ≥ cT3 1.092 (0.799–1.492) 0.581    
Cytoreductive nephrectomy   < 0.001   0.007
  None Reference   Reference  
  Radical 0.456 (0.334–0.623) < 0.001 0.570 (0.399–0.816) 0.002
  Partial 0.222 (0.031–1.603) 0.136 0.353 (0.048–2.598) 0.306
Multiple metastasis        
  Single Reference      
  Multiple 1.529 (1.122–2.083) 0.007    
  < 110.5 Reference   Reference  
  ≥ 110.5 1.985 (1.470–2.679) < 0.001 1.556 (1.112–2.179) 0.010

PLR: platelet-lymphocyte ratio, OS: overall survival, mRCC: metastatic renal cell carcinoma, HR: hazard ratio, CI: confidence interval, BMI: body mass index, IMDC: International Metastatic Renal Cell Carcinoma Database.

Table 3.
PLR – risk factor for OS with metachronous mRCC
Variable Univariate
HR (95% CI) p-value HR (95% CI) p-value
Age (yr)        
  < 65 Reference      
  ≥ 65 1.050 (0.698–1.577) 0.816    
  Male Reference      
  Female 0.741 (0.440–1.250) 0.262    
BMI (kg/m2)        
  < 25 Reference      
  ≥ 25 0.848 (0.521–1.381) 0.508    
IMDC criteria   0.312   0.034
  Favorable Reference   Reference  
  Intermediate 1.234 (0.830–1.833) 0.299 1.725 (1.087–2.738) 0.021
  Poor 2.183 (0.669–7.115) 0.195 2.760 (0.829–9.197) 0.098
Clinical T stage        
  ≤ cT2 Reference      
  ≥ cT3 1.334 (0.881–2.020) 0.174    
Grade   0.334    
  1 Reference      
  2 1.426 (0.875–2.324) 0.155    
  3 1.159 (0.569–2.361) 0.685    
  Clear cell Reference      
  Nonclear cell 1.208 (0.583–2.501) 0.611    
Multiple metastasis        
  Single Reference   Reference  
  Multiple 1.527 (1.026–2.272) 0.037 1.470 (0.939–2.300) 0.092
  < 90.4 Reference      
  ≥ 90.4 1.283 (0.872–1.886) 0.206    

PLR: platelet-lymphocyte ratio, OS: overall survival, mRCC: metastatic renal cell carcinoma, HR: hazard ratio, CI: confidence interval, BMI: body mass index, IMDC: International Metastatic Renal Cell Carcinoma Database.


Szendi et al. 16 made the initial report of synchronous and metachronous RCC metastasis in 1959, and since then many studies have been conducted to compare these 2 forms of disease. The biology and outcomes of synchronous and metachronous mRCC are different.17 Considering that SIR is a prognostic factor that reflects interactions between tumor and host, it is reasonable to expect that the role of SIR differs between synchronous and metachronous mRCC.
To the best of our knowledge, we reported for the first time that there were different prognostic roles of 2 SIR markers (PLR and NLR) between synchronous and meta-chronous mRCC patients receiving a first-line TKI. The prognostic significance of pretreatment PLR and NLR status was more significant in synchronous mRCC compared to metachronous mRCC. In addition, patients with increased NLR and PLR had a significantly poorer prognosis compared to those with lower NLR or PLR.
Recently, NLR and PLR which are markers of host inflammation have gained attention as prognostic markers in mRCC.18 There are relatively few reports on the relationship between PLR and RCC; however, it is well known that PLR is prognostic in several types of cancer such as large B-cell lymphoma, breast cancer, and colon cancer.19,20 In addition, reports indicate that NLR is related to metachronous metastasis of pancreatic cancer, lymph node metastasis of breast cancer, and peritoneal metastasis of gastric cancer.21,22
We found that NLR can predict OS outcomes regardless of synchronous or metachronous type mRCC; however, the same was not true for PLR. Specifically, we found that PLR was not predictive of outcomes in metachronous mRCC patients. In other words, while NLR remained a significant independent predictor of OS, PLR failed to serve as a prognostic factor for OS and PFS in patients with metachronous mRCC. Templeton et al.18 showed that the proportion of immune cells in the blood is of prognostic value, and that early decline of NLR after targeted therapy is associated with favorable outcomes. Similarly, Zhang et al. showed that pretreatment NLR may be an independent prognostic factor in mRCC patients receiving targeted therapy. In our study, pretreatment lymphocytes were higher in metachronous mRCC. As a result of our literature search, there was no paper that reported relationship between metastasis or prognosis with lymphocytes alone. But many reports suggested that ratio with lymphocyte with various substances such as neutrophil, platelet, lactate dehydrogenase, or monocyte were cancer prognostic factor.24
One of the key findings of our study was that SIR markers were useful in synchronous mRCC patients but were of limited use in metachronous patients. Synchronous mRCC tumors are widespread in the short term and likely stimulate more interactions between the host and the tumor.25 In this way, there may be more opportunities for SIR markers to be meaningful, as the action of tumor infiltrating lymphocytes is expected to be more vigorous.
There is some evidence in the literature to suggest that synchronous and metachronous tumors have different characteristics. First, the prognosis of metachronous tumors are better than that of synchronous tumors.15 Second, Zheng et al. showed different mutational patterns between synchronous and metachronous liver metastases of colorectal cancer. Third, a systematic review of colorectal cancer studies identified significant differences in expression of molecular markers between synchronous and metachronous metastases.27 We believe that the immune system plays a role in the differences between synchronous and metachro-nous disease. Unfortunately, in our search of the literature, we did not identify any reviews or studies focusing on the biological differences between synchronous and metachro-nous mRCC.
In this study, cytoreductive nephrectomy was an independent predictor for OS and PFS in synchronous mRCC. These results are contrary to CARMENA trial, but CAR-MENA trial only contains MSKCC (Memorial Sloan Kettering Cancer Center) intermediate- and poor-risk patients. Also, unlike usual real-world settings, 43% were poor-risk patients in this study.28 Careful patient selection is more appropriate than complete abandon for cytoreductive nephrectomy.29
There were some limitations to this study. First, our study had a retrospective nature with potential of selection and classification bias. In addition, while the purpose of this study was to investigate the relationship between SIR and outcomes in synchronous and metachronous mRCC, it is difficult to make firm conclusions from a single blood test measurement prior to starting TKI treatment. Third, in some cases of metachronous RCC patients, the results of previous treatment and biopsy results were unclear. Thus, due to this limitation, we conducted the risk analysis of cytoreductive nephrectomy in only synchronous RCC patient. Finally, we only tested blood samples to evaluate PLR and NLR as markers of SIR, rather than concurrently assess for tumor inflating cells in pathologic slides. Despite these drawbacks, our study describes for the first time the different prognostic power of the SIR markers PLR and NLR between synchronous and metachronous mRCC. The importance of SIR is expected to increase in the era of immune-oncology, and it can be useful to apply SIR markers according to synchronous and metachronous mRCC disease in appropriate clinical settings.


In summary, we found that SIR such as PLR and NLR have different prognostic value in synchronous and meta-chronous mRCC patients who were treated with first-line TKI. In particular, SIRs were more useful in synchronous mRCC population. Our study provides valuable information regarding the ability to predict survival outcomes in different types of mRCC by using well-known SIR markers.

Conflict of Interest


The authors claim no conflicts of interest.


Supplementary Tables 1–6 can be found via https://doi.org/10.22465/kjuo.2019.17.3.150.

Supplementary Table 1.

NLR - risk factor for OS with synchronous mRCC

Supplementary Table 2.

PLR - risk factor for PFS with synchronous mRCC

Supplementary Table 3.

NLR - risk factor for PFS with synchronous mRCC

Supplementary Table 4.

PLR - risk factor for PFS with metachronous mRCC

Supplementary Table 5.

NLR - risk factor for PFS with metachronous mRCC

Supplementary Table 6.

NLR - risk factor for OS with metachronous mRCC


This study was funded by a research grant from the National Research Foundation (NRF) of Korea, funded by the Ministry of Science and ICT (2018M3A9H1078336). This research was also supported by a grant from the Korea Health Technology R&D Project through the Korea Health Industry Development Institute (KHIDI), funded by the Ministry of Health & Welfare, Republic of Korea (HI17C0025).


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