Systemic Inflammation Response Index is an Independent Prognostic Indicator for Patients with Renal Cell Carcinoma Undergoing Laparoscopic Nephrectomy: A Multi-Institutional Cohort Study.

BACKGROUND: We conducted a multicenter clinical study to examine the prognostic value of the systemic inflammation response index (SIRI) in renal cell carcinoma (RCC) patients.
METHODS: We collected patients who underwent nephrectomy from 2014 to 2019 at three centers (343 in the training group and 100 in the validation group). SIRI was created based on hemoglobin and lymphocyte to monocyte ratio (LMR). Kaplan-Meier curves and receiver operating characteristic (ROC) curves were used to analyze the effect of LMR, hemoglobin and SIRI on overall survival (OS) and cancer-specific survival (CSS) effects.
RESULTS: In both the training and validation groups, SIRI was a better predictor of OS and CSS than LMR and hemoglobin. A total of 192 (56.0%) patients were included in grade 1, 108 (31.5%) in grade 2, and 43 (12.5%) in grade 3 based on SIRI in the training group. Higher SIRI was associated with worse prognosis. Multivariate cox regression analysis showed that SIRI was an independent prognostic risk factor for OS (grade 3 vs grade 1: HR=4.93; 95% CI 2.21-11.00, p < 0.001) and CSS (grade 3 vs grade 1: HR=6.29; 95% CI 2.28-17.39, p < 0.001) in patients with RCC. In addition, SIRI-based prognostic nomograms were able to better predict OS and CSS in RCC patients.
CONCLUSION: SIRI is an independent prognostic factor for patients undergoing laparoscopic nephrectomy for RCC, and a prognostic nomogram covering SIRI can better predict survival of RCC patients.

Introduction

Renal cell carcinoma (RCC), also known as renal cancer, is one of the most common malignancies in the urinary tract, and its incidence has been increasing at a rapid rate of 2% per year over the past two decades.1,2 400,000 new cases and 170,000 deaths of renal cancer were reported worldwide in 2018; approximately 70,000 new cases and 43,000 deaths of renal cancer were reported in China.3,4 Surgery is still the main treatment for RCC, and about 30% of RCC patients have metastases at the time of initial diagnosis, and approximately 25% of patients with localized RCC will develop local recurrence or distant metastases after surgery.5,6 Due to recurrence or distant metastasis, the 5-year survival rate of patients with advanced RCC is extremely low, approximately 5%–10%.7,8

The development of malignant tumors was related to the malignant characteristics of tumor cells, and also related to the tumor microenvironment.9 Studies have confirmed the importance of systemic inflammation and local immune response in the progression of malignant tumors and patient prognosis.10 Inflammatory cells (neutrophils, lymphocytes, monocytes) are an important part of the tumor microenvironment, and their mediated inflammatory responses can promote tumor cell proliferation, angiogenesis, apoptosis, invasion and metastasis, and suppress anti-tumor immunity.11 In addition, combined metrics based on multiple inflammatory cells, such as neutrophil to lymphocyte ratio (NLR), platelet to lymphocyte ratio (PLR) and lymphocyte to monocyte ratio (LMR), have been confirmed to be independently associated with tumor outcome in various cancers.12,13 In addition, preoperative hemoglobin and serum albumin levels have been identified as tumor-related prognostic predictors.14,15

In this study, we aimed to assess the prognostic value of systemic inflammatory biomarkers in patients with RCC. We created a systemic inflammatory response index (SIRI) based on hemoglobin and LMR and evaluated the prognostic ability of SIRI for overall survival (OS) and cancer-specific survival (CSS) in patients undergoing laparoscopic nephrectomy in a multicenter clinical study.

Materials and Methods

Study Design and Patients

In this study, we retrospectively collected clinical data from 590 RCC patients from January 2014 to December 2019 at three centers in Zhongda Hospital Southeast University, Shanghai Tenth People’s Hospital and Shidong Hospital. All patients were pathologically diagnosed with RCC and underwent partial or radical nephrectomy. We excluded patients who received other preoperative anti-cancer treatments, or had other malignancies in combination, or lacked complete medical records or were lost to follow-up. After screening, we excluded 147 patients, and finally 443 patients were included in the study.

Three hundred and forty-three patients from Zhongda Hospital Southeast University were included in the training group, and 100 patients from Shanghai Tenth People’s Hospital and Shidong Hospital were categorized in the validation group. All patients or relatives signed the written informed consent. The methodology of this study followed the criteria outlined in the Declaration of Helsinki (as revised in 2013) and was ethically approved by the Ethics Committees and Institutional Review Boards of all participating institutions.

Clinical Data Collection and Follow-Up

Basic clinical information and laboratory test data for all patients were obtained from the patients’ electronic cases. Included study variables were age, gender, body mass index (BMI, calculated by weight (kg)/height2 (m2)), hypertension, diabetes, cardiovascular disease, smoking, surgery type, laterality, AJCC stage, T stage, N stage, M stage, Fuhrman grade, neutrophils, lymphocytes, monocytes, platelets, albumin and hemoglobin. The patient’s basic clinical information was determined at the date of first diagnosis, and laboratory test data were measured two days prior to surgery or closest to the time of surgery. LMR was defined as lymphocyte to monocyte ratio. OS was calculated from the date of surgical treatment to the date of death or the last follow-up. CSS was calculated from the date of therapeutic resection to the date of death due to RCC.

Statistical Analysis

Continuous data were expressed as mean ± standard deviation (SD) and categorical data were presented as number (%). Continuous variables were analyzed using t-test and categorical variables were analyzed using chi-square test. The cutoff value for hemoglobin has been divided into male (<137 g/L) and female (<116 g/L).16,17 The optimal cutoff values for LMR, albumin, NLR and PLR were determined based on receiver operating characteristic (ROC) curves and patients were divided into high LMR and low LMR groups, high hemoglobin and low hemoglobin group. SIRI was determined based on LMR and hemoglobin. SIRI was defined as follows: high LMR and high hemoglobin patients were included in grade 1, low LMR and low hemoglobin patients were included in grade 3, and the remaining patients were included in grade 2.

Kaplan–Meier curves were used to assess the effects of LMR, hemoglobin and SIRI on OS and CSS. ROC curves, which were calculated using the area under the curve (AUC), were used to compare the predictive ability of LMR, hemoglobin and SIRI on OS and CSS. Univariate and multivariate Cox regressions were used to assess the relationship among SIRI and OS and CSS and to calculate the associated adjusted hazard ratio (aHR) and 95% confidence interval (CI). Based on the results of multivariate Cox regression analysis, we included independent risk factors for OS and CSS in the prognostic nomogram. Statistical analyses for this study were performed using SPSS software (version 26.0) and GraphPad Prism (version 8.3.0), and nomograms were constructed using R software (version 3.6.2). P value <0.05 was considered statistically significant.

Results

According to the ROC curve, the optimal cutoff values for LMR, albumin, NLR and PLR were 3.22, 37.7, 2.88 and 163.13, respectively (). Based on the critical values, we divided the patients into high LMR group (>3.22) and low LMR group (≤3.22), high hemoglobin group and low hemoglobin group. The clinicopathological characteristics of all patients in the training and validation groups are shown in Table 1 and . In the training group, we found that LMR was associated with surgery type, AJCC stage, T stage, M stage and Fuhrman grade, whereas hemoglobin was associated with age, BMI, type of surgery, AJCC stage, TNM stage and Fuhrman grade. In the validation group, LMR was correlated with age, and hemoglobin was correlated with age, gender, BMI, smoking and M stage. In addition, Kaplan–Meier curves showed that high LMR and high hemoglobin were associated with longer OS and CSS in both the training and validation groups (Figure 1 and ).

Table 1

Clinical Characteristics of the Patients According to LMR and Hemoglobin in the Training Group

Characteristic		LMR		P value	Hemoglobin		P value
	All	High Group	Low Group		High Group	Low Group
	Patients	N=271	N=72		N=221	N=122
Age categorized, y				0.873			0.003
≤65	255 (74.3)	202 (74.5)	53 (73.6)		176 (79.6)	79 (64.8)
>65	88 (25.7)	69 (25.5)	19 (26.4)		45 (20.4)	43 (35.2)
Gender				0.876			0.116
Male	226 (65.9)	178 (65.7)	48 (66.7)		139 (62.9)	87 (71.3)
Female	117 (34.1)	93 (34.3)	24 (33.3)		82 (37.1)	35 (28.7)
BMI categorized, kg/m2				0.169			0.011
<25	185 (53.9)	141 (52.0)	44 (61.1)		108 (48.9)	77 (63.1)
≥25	158 (46.1)	130 (48.0)	28 (38.9)		113 (51.1)	45 (36.9)
Hypertension				0.980			0.262
No	191 (55.7)	151 (55.7)	40 (55.6)		128 (57.9)	63 (51.6)
Yes	152 (44.3)	120 (44.3)	32 (44.4)		93 (42.1)	59 (48.4)
Diabetes				0.844			0.863
No	288 (84.0)	227 (83.8)	61 (84.7)		185 (83.7)	103 (84.4)
Yes	55 (16.0)	44 (16.2)	11 (15.3)		36 (16.3)	19 (15.6)
Cardiovascular diseases				0.697			0.659
No	300 (87.5)	238 (87.8)	62 (86.1)		192 (86.9)	108 (88.5)
Yes	43 (12.5)	33 (12.2)	10 (13.9)		29 (13.1)	14 (11.5)
Smoking				0.469			0.601
No	286 (83.4)	228 (84.1)	58 (80.6)		186 (84.2)	100 (82.0)
Yes	57 (16.6)	43 (15.9)	14 (19.4)		35 (15.8)	22 (18.0)
Surgery type				<0.001			<0.001
Partial nephrectomy	187 (54.5)	168 (62.0)	19 (26.4)		148 (67.0)	39 (32.0)
Radical nephrectomy	156 (45.5)	103 (38.0)	53 (73.6)		73 (33.0)	83 (68.0)
Laterality				0.615			0.968
Left	171 (49.9)	134 (49.4)	38 (52.8)		110 (49.8)	61 (50.0)
Right	172 (50.1)	137 (50.6)	34 (47.2)		111 (50.2)	61 (50.0)
AJCC stage				<0.001			<0.001
I	256 (74.6)	220 (81.2)	36 (50.0)		183 (82.8)	73 (59.8)
II	19 (5.5)	10 (3.7)	9 (12.5)		10 (4.5)	9 (7.4)
III	45 (13.1)	29 (10.7)	16 (22.2)		18 (8.1)	27 (22.1)
IV	23 (6.7)	12 (4.4)	11 (15.3)		10 (4.5)	13 (10.7)
T-stage				<0.001			<0.001
T1	260 (75.8)	223 (82.3)	37 (51.4)		185 (83.7)	75 (61.5)
T2	23 (6.7)	13 (4.8)	10 (13.9)		12 (5.4)	11 (9.0)
T3	51 (14.9)	28 (10.3)	23 (31.9)		17 (7.7)	34 (27.9)
T4	9 (2.6)	7 (2.6)	2 (2.8)		7 (3.2)	2 (1.6)
N-stage				0.613			0.010
N0	330 (96.2)	260 (95.9)	70 (97.2)		217 (98.2)	113 (92.6)
N1	13 (3.8)	11 (4.1)	2 (2.8)		4 (1.8)	9 (7.4)
M-stage				<0.001			0.005
M0	327 (95.3)	264 (97.4)	63 (87.5)		216 (97.7)	111 (91.0)
M1	16 (4.7)	7 (2.6)	9 (12.5)		5 (2.3)	11 (9.0)
Fuhrman grade				0.004			0.001
I	55 (16.0)	47 (17.3)	8 (11.1)		44 (19.9)	11 (9.0)
II	216 (63.0)	176 (64.9)	40 (55.6)		136 (61.5)	80 (65.6)
III	64 (18.7)	45 (16.6)	19 (26.4)		40 (18.1)	24 (19.7)
IV	8 (2.3)	3 (1.1)	5 (6.9)		1 (0.5)	7 (5.7)

Abbreviations: LMR, lymphocyte to monocyte ratio; BMI, body mass index; AJCC, American Joint Committee on Cancer.

Figure 1

Kaplan–Meier curves for OS and CSS stratified by LMR and hemoglobin in the training group. (A and C), LMR OS and CSS; (B and D), Hemoglobin OS and CSS.

According to SIRI, the training group 192 (56.0%) patients were included in the grade 1 group, 108 (31.5%) patients in the grade 2 group, and 43 (12.5%) patients in the grade 3 group in (Table 2), and in the validation group 64 (64.0%) patients were included in the grade 1 group, 25 (25.0%) patients in the grade 2 group, and 11 (11%) patients in the grade 3 group (). We found that SIRI was associated with BMI, smoking, surgery type, AJCC stage, T stage, M stage and Fuhrman grade in the training group, while SIRI was associated with age, smoking and M stage in the validation group. Moreover, Kaplan–Meier survival curve analysis showed that low SIRI was associated with better OS and CSS both in the training and validation groups (Figure 2).

Table 2

Baseline Characteristics of the Patients According to SIRI in the Training Group

Characteristic	SIRI			P value
	Grade 1	Grade 2	Grade 3
	No. (%)	No. (%)	No. (%)
All patients	192 (56.0)	108 (31.5)	43 (12.5)
Age, y				0.069
≤65	152 (79.2)	74 (68.5)	29 (67.4)
>65	40 (20.8)	34 (31.5)	14 (32.6)
Gender				0.450
Male	121 (63.0)	75 (69.4)	30 (69.8)
Female	71 (37.0)	33 (30.6)	13 (30.2)
BMI, kg/m2				0.038
<25	94 (49.0)	61 (56.5)	30 (69.8)
≥25	98 (51.0)	47 (43.5)	13 (30.2)
Hypertension				0.464
No	112 (58.3)	55 (50.9)	24 (55.8)
Yes	80 (41.7)	53 (49.1)	19 (44.2)
Diabetes				0.918
No	161 (83.9)	90 (83.3)	37 (86.0)
Yes	31 (16.1)	18 (16.7)	6 (14.0)
Cardiovascular diseases				0.614
No	169 (88.0)	92 (85.2)	39 (90.7)
Yes	23 (12.0)	16 (14.8)	4 (9.3)
Smoking				0.042
No	159 (82.8)	96 (88.9)	31 (72.1)
Yes	33 (17.2)	12 (11.1)	12 (27.9)
Surgery type				<0.001
Partial nephrectomy	134 (69.8)	48 (44.4)	5 (11.6)
Radical nephrectomy	58 (30.2)	60 (55.6)	38 (88.4)
Laterality				0.885
Left	96 (50.0)	55 (50.9)	20 (46.5)
Right	96 (50.0)	53 (49.1)	23 (53.5)
AJCC stage				<0.001
I	165 (85.9)	73 (67.6)	18 (41.9)
II	6 (3.1)	8 (7.4)	5 (11.6)
III	16 (8.3)	15 (13.9)	14 (32.6)
IV	5 (2.6)	12 (11.1)	6 (14.0)
T-stage				<0.001
T1	167 (87.0)	74 (68.5)	19 (44.2)
T2	7 (3.6)	11 (10.2)	5 (11.6)
T3	13 (6.8)	19 (17.6)	19 (44.2)
T4	5 (2.6)	4 (3.7)	0 (0.0)
N-stage				0.152
N0	188 (97.9)	101 (93.5)	41 (95.3)
N1	4 (2.1)	7 (6.5)	2 (4.7)
M-stage				<0.001
M0	190 (99.0)	100 (92.6)	37 (86.0)
M1	2 (1.0)	8 (7.4)	6 (14.0)
Fuhrman grade				<0.001
I	39 (20.3)	13 (12.0)	3 (7.0)
II	119 (62.0)	74 (68.5)	23 (53.5)
III	33 (17.2)	19 (17.6)	12 (27.9)
IV	1 (0.5)	2 (1.9)	5 (11.6)

Abbreviation: SIRI, systemic inflammation response index; BMI, body mass index; AJCC, American Joint Committee on Cancer.

Figure 2

Kaplan–Meier curves for OS and CSS stratified by SIRI. (A and B), SIRI OS and CSS in the training group; (C and D), SIRI OS and CSS in the validation group.

ROC curves were used to assess the prognostic ability of LMR, hemoglobin and SIRI in patients with RCC undergoing laparoscopic nephrectomy (Table 3). We found a higher predictive ability of SIRI for OS (Training set: AUC=0.691, 95% CI 0.603–0.779, p < 0.001; Test set: AUC=0.667, 95% CI 0.504–0.829, p=0.062) and CSS (Training set: AUC=0.683, 95% CI 0.578–0.789, p=0.002; Test set: AUC=0.726, 95% CI 0.559–0.894, p=0.025) than LMR and hemoglobin in both the training and test sets (Figure 3).

Table 3

Analysis of Predictive Accuracy Through the Evaluation of the Area Under the Curve (AUC)

	Overall Survival			Cancer-Specific Survival
	AUC	95% CI	Pvalue	AUC	95% CI	Pvalue
Training Set
SIRI	0.691	0.603–0.779	<0.001	0.683	0.578–0.789	0.002
LMR	0.633	0.537–0.729	0.005	0.627	0.509–0.746	0.028
Hemoglobin	0.642	0.552–0.732	0.003	0.629	0.509–0.746	0.027
Test Set
SIRI	0.667	0.504–0.829	0.062	0.726	0.559–0.894	0.025
LMR	0.534	0.354–0.714	0.703	0.579	0.370–0.787	0.437
Hemoglobin	0.672	0.500–0.845	0.054	0.712	0.526–0.899	0.036

Abbreviation: AUC, area under the curve; CI, confidence interval; OS, overall survival; CSS, cancer-specific survival; LMR, lymphocyte to monocyte ratio; SIRI, systemic inflammation response index.

Figure 3

Comparison of area under ROC curves for LMR, hemoglobin and SIRI in predicting OS and CSS. (A) OS ROC curves in the training group; (B) CSS ROC curves in the training group; (C) OS ROC curves in the validation group; (D) CSS ROC curves in the validation group.

Subsequently, in the training group, we used multivariate Cox regression model to assess the correlation of SIRI with OS and CSS (Table 4). The results showed that SIRI was an independent risk factor for OS (grade 3 vs grade 1: HR=4.93; 95% CI 2.21–11.00, p < 0.001) and CSS (grade 3 vs grade 1: HR=6.29; 95% CI 2.28–17.39, p < 0.001), and that SIRI grade 3 was associated with the worst prognosis. Based on the results of the above multivariate regression analysis, we constructed prognostic nomograms for OS and CSS and validated in the validation group (Figure 4). The results showed that the constructed prognostic nomograms covering SIRI were able to predict 1-year and 3-year OS and CSS readily in both the training and validation groups (Figure 5 and ).

Table 4

Multivariate Analyses of Factors Associated with Overall Survival (OS) and Cancer-Specific Survival (CSS) in the Training Group

Characteristics	Overall Survival		Cancer-Specific Survival
	Hazard Ratio (95% CI)	P value	Hazard Ratio (95% CI)	P value
Age, y
≤65	Reference		Reference
>65	-	0.657		0.402
Gender
Male	Reference		Reference
Female	2.25 (1.14–4.44)	0.020		0.284
BMI, kg/m2
<25	Reference		Reference
≥25	-	0.457		0.497
Hypertension
No	Reference		Reference
Yes	-	0.484	2.95 (1.33–6.54)	0.008
Diabetes
No	Reference		Reference
Yes	-	0.561	-	0.789
Cardiovascular Diseases
No	Reference		Reference
Yes	-	0.577	-	0.633
Smoking
No	Reference		Reference
Yes	-	0.881	-	0.847
Surgery Type
Partial nephrectomy	Reference		Reference
Radical nephrectomy	-	0.183	4.65 (1.51–14.28)	0.007
Laterality
Left	Reference		Reference
Right	-	0.889	-	0.828
AJCC stage
I	Reference		Reference
II	-	0.290	1.13 (0.11–6.88)	0.583
III	-	0.203	2.10 (0.68–6.46)	0.196
IV	-	0.077	11.53 (4.62–28.75)	<0.001
T-stage
T1	Reference		Reference
T2	-	0.794	-	0.033
T3	-	0.297	-	0.491
T4	-	0.162	-	0.310
N-stage
N0	Reference		Reference
N1	-	0.056	-	0.254
M-stage
M0	Reference		Reference
M1	8.39 (3.87–18.19)	<0.001	-	0.338
Fuhrman Grade
I	Reference		Reference
II	-	0.891	-	0.878
III	-	0.936	-	0.870
IV	-	0.029	-	0.189
ALB
	Reference		Reference
		0.155	-	0.125
NLR
	Reference		Reference
		0.709	-	0.359
PLR
	Reference		Reference
		0.233	-	0.874
SIRI
Grade 1	Reference		Reference
Grade 2	1.91 (0.87–4.21)	0.109	1.27 (0.78–5.04)	0.513
Grade 3	4.93 (2.21–11.00)	<0.001	6.29 (2.28–17.39)	<0.001

Abbreviations: OS, overall survival; CSS, cancer-specific survival; CI, confidence interval; BMI, body mass index; AJCC, American Joint Committee on Cancer; SIRI, systemic inflammation response index.

Figure 4

The nomogram predicting 1-year and 3-year OS and CSS rate of RCC patients the training cohort. (A) OS nomogram; (B) CSS nomogram.

Figure 5

Calibration plot of the nomogram for predicting 1-year and 3-year OS and CSS in training cohort. (A) 1-year OS; (B) 1-year CSS; (C) 3-year OS; (D) 3-year CSS.

Discussion

Regarding the predictive indicators of RCC prognosis, the traditional concept is that the stage of the tumor is closely related to the prognosis, and a higher stage often indicates shorter survival.18 Many literatures have reported that tumor diameter, lymph node metastasis status, tumor invasion and other conditions are closely related to RCC prognosis.19 Inflammatory and immune markers in routine blood have also been used to study the correlation with cancer occurrence, progression and outcome.20 Lymphocytes and monocytes in the blood, which are closely related to immunity, have been reported to correlate with the prognosis of a variety of tumors in the body.21 Peripheral blood indicators have more of a preoperative predictive role in malignancies and are useful in guiding treatment options such as the extent of surgery and the choice of postoperative radiotherapy.22

In recent years, there has been a strong interest in the prognostic value of peripheral blood biomarkers in RCC patients, such as PLR and NLR can be used as prognostic predictors of RCC.23,24 A variety of inflammatory and immune cells have been confirmed to participate in the whole process of malignant tumor progression, and the body’s immune response to tumor cells is an important factor in the prognosis of malignant tumors. As an important component of the tumor microenvironment, lymphocytes, which are produced by lymphoid organs, participated in tumor cell genesis and development.25 The presence of peritumor lymphocyte infiltration in patients with RCC is an important independent prognostic marker.26 Lymphocytes are important performers in the body’s immune function, which exert cytotoxic effects directly or secret interleukins and other cytokines to mediate immune responses to inhibit tumor growth and distant metastasis and exert immune surveillance.27 Lymphocytes can play a role in eliminating tumor cells and inhibiting their proliferation and growth through CD4 and CD8 lymphocytes and natural killer cells.28 Since lymphocytes are both an indicator of inflammation and a marker that can determine the prognosis of patients with malignant neoplasms, the relationship between inflammatory response and malignancy is closely linked.

Similarly, monocytes have been reported that they can affect the progression of RCC and are associated with RCC patient poor prognosis.29 Further in the mechanism of monocytes affecting RCC, it was found that monocytes in the tumor microenvironment are stimulated by inflammatory factors to differentiate into tumor-associated macrophages, which can be activated into different subtypes that, in the presence of different subtypes, not only inhibit the growth of tumor cells but also promote their proliferation and metastasis.30 Monocyte count can reflect the tumor microenvironment infiltrating macrophages, and also directly supply energy to cancer cells, promote angiogenesis in cancer foci, and facilitate tumor evasion from immune surveillance and subsequently promote tumor progression.31

LMR is an indicator that integrates lymphocytes and monocytes and provides a more comprehensive picture of the chronic inflammatory state of the body.32 Its diagnostic and prognostic value has been demonstrated in a variety of tumors. The results of a meta-analysis showed that low LMR levels were significantly associated with shorter overall survival, progression-free survival, and tumor-specific survival in non-hematologic malignancies and hematologic malignancies.33

The development of tumor is the outcome of the interaction between the body and the tumor, and the prognosis of tumor patients is not only related to the qualities of the tumor itself, but also to the immune status and nutrition of the patients.34 Hemoglobin, as an important parameter of complete blood count, reflects to some extent the degree of anemia and the nutritional status of the patient’s body. It has been suggested that hemoglobin is closely related to the prognosis of colorectal cancer, gastric cancer, endometrial cancer and many other cancers.35–37

A combination of multiple inflammatory cells has been shown to correlate with the prognosis of various cancers. Based on NLR, PLR and LMR, Ferro et al38 developed prostatic systemic inflammatory markers (PSIM) and found that PSIM was the only independent prognostic variable affecting the probability of adverse pathology in prostate cancer. In addition, the usefulness of inflammation-based SIRI prognostic scores for patients with RCC has been reported. By investigating 161 patients with metastatic RCC who underwent cytoreductive nephrectomy, Gu et al16 found that high SIRI was associated with poorer OS and was an independent prognostic predictor of OS, with aggressive tumor behavior significantly associated. Fukuda et al17 retrospectively analyzed data from 161 patients who underwent cytoreductive nephrectomy for metastatic RCC underwent cytoreductive nephrectomy in 152 patients and found that SIRI predicted survival in patients with RCC. In our study, we performed a multicenter clinical study and found that SIRI better predicted OS and CSS in RCC patients than LMR and hemoglobin, and that SIRI was an independent risk factor for OS and CSS in RCC patients. In addition, we constructed prognostic nomograms for OS and CSS based on SIRI, which could better predict survival of RCC patients.

In speculating the reasons for the poor prognosis of RCC patients in the high SIRI group, we found that patients in the high SIRI group included more cases of AJCC III/IV stage, T3/T4 stage, M1 stage and Fuhrman III/IV grade, which may contribute to the poorer prognosis of patients in the grade 3 group.

This study also has several limitations. First, we did not assess the patient’s quality of life, energy level or postoperative nutritional status. Second, we did not include other treatments in the study, which could also have an impact on the prognosis. Finally, although this is a multicenter study, it was still a retrospective study which requires an expanded sample for prospective study.

Conclusion

In general, we created a biomarker that better reflects systemic inflammation in RCC patients, SIRI. In addition, we found that SIRI was an independent prognostic factor for OS and CSS in RCC patients undergoing laparoscopic nephrectomy and SIRI-based prognostic nomograms were good predictors of survival in RCC patients.