Email Alert | RSS

Journal of Peking University (Health Sciences) ›› 2023, Vol. 55 ›› Issue (1): 149-155. doi: 10.19723/j.issn.1671-167X.2023.01.023

Previous Articles     Next Articles

Pre-operative prognostic nutritional index as a predictive factor for prognosis in non-metastatic renal cell carcinoma treated with surgery

Quan ZHANG,Hai-feng SONG,Bing-lei MA,Zhe-nan ZHANG,Chao-hui ZHOU,Ao-lin LI,Jun LIU,Lei LIANG,Shi-yu ZHU,Qian ZHANG*()   

  1. Department of Urology, Peking University First Hospital; Institute of Urology, Peking University; National Urological Cancer Center, Beijing 100034, China
  • Received:2020-06-12 Online:2023-02-18 Published:2023-01-31
  • Contact: Qian ZHANG E-mail:zhangqianbjmu@126.com

RICH HTML

   

PDF (PC)

Abstract:

Objective: To evaluate the implications of the prognostic nutrition index (PNI) in non-metastatic renal cell carcinoma (RCC) patients treated with surgery and to compare it with other hematological biomarkers, including neutrophil to lymphocyte ratio (NLR), platelet to lymphocyte ratio (PLR), and systemic immune inflammation index (SII). Methods: A cohort of 328 non-metastatic RCC patients who received surgical treatment between 2010 and 2012 at Peking University First Hospital was analyzed retrospectively. Receiver operating characteristic (ROC) curve analysis was used to determine the optimal cutoff values of the hematological biomarkers. The Youden index was maximum for PNI was value of 47.3. So we divided the patients into two groups (PNI≤ 47. 3 and >47. 3) for further analysis. Categorical variables [age, gender, body mass index (BMI), surgery type, histological subtype, necrosis, pathological T stage and tumor grade] were compared using the Chi-square test and Student' s t test. The association of the biomarkers with overall survival (OS) and disease-free survival (DFS) was analyzed using Kaplan-Meier methods with log-rank test, followed by multivariate Cox proportional hazards model. Results: According to the maximum Youden index of ROC curve, the best cut-off value of PNI is 47. 3. Low level of PNI was significantly associated with older age, lower BMI and higher tumor pathological T stage (P < 0.05). Kaplan-Meier univariate analysis showed that lower PNI was significantly correlated with poor OS and DFS (P < 0.05). In addition, older age, lower BMI, tumor necrosis, higher tumor pathological T stage and Fuhrman grade were significantly correlated with poor OS (P < 0.05). Cox multivariate analysis showed that among the four hematological indexes, only PNI was an independent factor significantly associated with OS, whether as a continuous variable (HR=0.9, 95%CI=0.828-0.978, P=0.013) or a classified variable (HR=2.397, 95%CI=1.061-5.418, P=0.036). Conclusion: Low PNI was a significant predictor for advanced pathological T stage, decreased OS, or DFS in non-metastatic RCC patients treated with surgery. In addition, PNI was superior to the other hematological biomar-kers as a useful tool for predicting prognosis of RCC in our study. It should be externally validated in future research before the PNI can be used widely as a predictor of RCC patients undergoing nephrectomy.

Key words: Prognostic nutrition index, Renal cell carcinoma, Nephrectomy, Prognosis

CLC Number: 

  • R737.11

Figure 1

ROC curve for PNI, NLR, SII, and PLR PNI, prognostic nutritional index; NLR, neutrophil to lymphocyte ratio; PLR, platelet to lymphocyte ratio; SII, systemic immune inflammation index; ROC, receiver operating characteristic."

Table 1

The AUC, optimal cut-off values for PNI, NLR, SII, and PLR"

Items PNI NLR SII PLR
AUC 0.751 0.737 0.729 0.719
95%CI 0.700-0.796 0.685-0.784 0.678-0.776 0.667-0.767
P value < 0.000 1 < 0.000 1 < 0.000 1 < 0.000 1
Sensitivity/% 72.5 70.0 70.0 67.5
Specificity/% 67.36 72.57 67.71 67.36
Cut-off value ≤47.30 >2.52 >489.80 >131.25

Table 2

Associations of clinicopathological features with different groups of PNI, NLR, SII, and PLR in renal cell carcinoma patients underwent surgery"

Variable PNI NLR SII PLR
≤47.30 (n = 123) >47.30 (n=205) P ≤2.52 (n =220) >2.52 (n= 108) P ≤489.80 (n=206) >489.80 (n = 122) P ≤131.25 (n=207) >131.25 (n = 121) P
Age/years 60.11 ±11.93 53.89 ±13.51 < 0.001 54.78 ±13.98 59. 18 ±11.19 0.005 55.78 ±13.65 56.98 ±12.63 0.432 55.67 ±13.15 57.18 ±13.47 0.319
BMI 23.76 ±3.08 25.54 ±3.40 < 0.001 25.24 ±3.46 24. 12 ±3. 13 0.005 25.17 ±3.46 24.38 ±3.21 0.041 25.47 ±3.44 23.84 ±3.05 < 0.001
Gender 0.802 0.500 0.281 < 0.001
  Male 86 (37.1) 146 (62.9) 153 (65.9) 79 (34.1) 150 (64.7) 82 (35.3) 160 (69.0) 72 (31.0)
  Female 37 (38.5) 59 (61.5) 67 (69.8) 29 (30.2) 56 (58.3) 40 (41.7) 47 (49.0) 49 (51.0)
Surgery 0.060 0.003 0.001 0.005
  PN 25 (29.1) 61 (70.9) 69 (80.2) 17 (19.8) 67 (77.9) 19 (22.1) 65 (75.6) 21 (24.4)
  RN 98 (40.5) 144 (59.5) 151 (62.4) 91 (37.6) 139 (57.4) 103 (42.6) 142 (58.7) 100 (41.3)
Histopalhology 0.723 0.561 0.745 0.708
  Clear cell 105 (37.9) 172 (62.1) 184 (66.4) 93 (33.6) 175 (63.2) 102 (36.8) 176 (63.5) 101 (36.5)
  No dear cell 18 (35.3) 33 (64.7) 36 (70.6) 15 (29.4) 31 (60.8) 20 (39.2) 31 (60.8) 20 (39.2)
Necrosis 0.628 0.096 0.013 0.005
  Yes 93 (36.6) 161 (63.4) 176 (69.3) 78 (30.7) 169 (66.5) 85 (33.5) 171 (67.3) 83 (32.7)
  No 29 (39.7) 44 (60.3) 43 (58.9) 30 (41.1) 37 (50.7) 36 (49.3) 36 (49.3) 37 (50.7)
pT stage < 0.001 < 0.001 < 0.001 < 0.001
  pT1-2 77 (30.4) 176 (69.6) 192 (75.9) 61 (24.1) 175 (69.2) 78 (30.8) 179 (70.8) 74 (29.2)
  pT3-4 46 (61.3) 29 (38.7) 28 (37.3) 47 (62.7) 31 (41.3) 44 (58.7) 28 (37.3) 121 (62.7)
Fuhnnan grade 0.327 0.002 0.002 0.001
  G1-2 106 (36.6) 184 (63.4) 203 (70.0) 87 (20.0) 191 (65.9) 99 (34.1) 192 (66.2) 98 (33.8)
  G3-4 17 (44.7) 21 (55.3) 17 (44.7) 21 (55.3) 15 (39.5) 23 (60.5) 15 (39.5) 23 (60.5)

Figure 2

Kaplan-Meier curves of OS(A) and DFS(B) in renal cell carcinoma patients underwent surgery based on the PNI OS, overall survival; DFS, disease free survival; PNI, prognostic nutritional index."

Table 3

Univariate and multivariate analyses of clinicopathological parameters and the biomarkers to predict OS in non-metastatic renal cell carcinoma patients underwent surgery"

VariableOS
Univariate Multivariate Multivariate
HR (95%CI) P HR (95%CI) P HR (95%CI) P
Age (continuous) 1.035 (1.009-1.062) 0.007 1.022 (0.994-1.052) 0.124 1.026 (0.997-1.055) 0.080
Gender (female) 0.797 (0.390-1.631) 0.534
BMI (continuous) 0.854 (0.773-0.944) 0.002 0.961 (0.864-1.069) 0.465 0.948 (0.854-1.053) 0.322
Surgery method 0.028 0.801 0.829
  PN 1 1 1
  RN 2.852 (1.117-7.285) 0.871 (0.296-2.558) 0.890 (0.308-2.570)
Histopathology (no clear cell) 2.018 (0.959-4.245) 0.064 2.065 (0.920-4.637) 0.079 2.708 (1.236-5.933) 0.013
Necrosis (yes) 4.071 (2.188-7.575) < 0.001 1.673 (0.735-3.807) 0.220 2.143 (0.935-4.910) 0.072
pT stage < 0.001 0.052 0.221
  pT1-2 1 1 1
  pT3-4 5.611 (2.995-10.512) 2.130 (0.993-4.571) 1.625 (0.747-3.533)
Fuhrman grade < 0.001 0.010 0.044
  G1-2 1 1 1
  G3-4 6.668 (3.559-12.493) < 0.001 3.150 (1.323-7.500) 2.363 (1.024-5.454)
PNI (continuous) 0.831 (0.785-0.879) < 0.001 0.900 (0.828-0.978) 0.013
NLR (continuous) 1.204 (1.108-1.309) < 0.001 0.765 (0.568-1.032) 0.080
SII (continuous) 1.001 (1.001-1.001) < 0.001 1.000 (0.999-1.001) 0.790
PLR (continuous) 1.005 (1.003-1.006) < 0.001 1.007 (1.001-1.014) 0.025
PNI (≤47.30) 5.252 (2.619-10.529) < 0.001 2.397 (1.061-5.418) 0.036
NLR (>2.52) 5.383 (2.735-10.593) < 0.001 1.797 (0.660-4.895) 0.252
SII (>489.80) 4.525 (2.299-8.906) < 0.001 1.587 (0.527-4.780) 0.412
PLR (>131.25) 4.390 (2.263-8.516) < 0.001 1.140 (0.451-2.879) 0.782
1 Siegel RL , Miller KD , Jemal A . Cancer statistics, 2015[J]. CA Cancer J Clin, 2015, 65 (1): 5- 29.
doi: 10.3322/caac.21254
2 Janzen NK , Kim HL , Figlin RA , et al. Surveillance after radical or partial nephrectomy for localized renal cell carcinoma and management of recurrent disease[J]. Urol Clin North Am, 2003, 30 (4): 843- 852.
doi: 10.1016/S0094-0143(03)00056-9
3 Chrom P , Stec R , Bodnar L , et al. Incorporating neutrophil-to-lymphocyte ratio and platelet-to-lymphocyte ratio in place of neutrophil count and platelet count improves prognostic accuracy of the International Metastatic Renal Cell Carcinoma Database Consortium model[J]. Cancer Res Treat, 2018, 50 (1): 103- 110.
doi: 10.4143/crt.2017.033
4 Bazzi WM , Tin AL , Sjoberg DD , et al. The prognostic utility of preoperative neutrophil-to-lymphocyte ratio in localized clear cell renal cell carcinoma[J]. Can J Urol, 2016, 23 (1): 8151- 8154.
5 Hu K , Lou L , Ye J , et al. Prognostic role of the neutrophil-lymphocyte ratio in renal cell carcinoma: A meta-analysis[J]. BMJ Open, 2015, 5 (4): 6404- 6415.
6 Jagdev SP , Gregory W , Vasudev NS , et al. Improving the accuracy of pre-operative survival prediction in renal cell carcinoma with C-reactive protein[J]. Br J Cancer, 2010, 103 (11): 1649- 1656.
doi: 10.1038/sj.bjc.6605973
7 Onodera T , Goseki N , Kosaki G . Prognostic nutritional index in gastrointestinal surgery of malnourished cancer patients[J]. Nihon Geka Gakkai Zasshi, 1984, 85 (9): 1001- 1005.
8 Borda A , Borda F , Vila J , et al. Predictive pre-treatment value of the prognostic nutritional index on survival in gastric carcinoma[J]. An Sist Sanit Navar, 2016, 39 (2): 227- 235.
doi: 10.23938/ASSN.0271
9 Nozoe T , Ninomiya M , Maeda T , et al. Prognostic nutritional index: A tool to predict the biological aggressiveness of gastric carcinoma[J]. Surg Today, 2010, 40 (5): 440- 443.
doi: 10.1007/s00595-009-4065-y
10 Nozoe T , Kohno M , Iguchi T , et al. The prognostic nutritional index can be a prognostic indicator in colorectal carcinoma[J]. Surg Today, 2012, 42 (6): 532- 535.
doi: 10.1007/s00595-011-0061-0
11 Peng D , Gong YQ , Hao H , et al. Preoperative prognostic nutritional index is a significant predictor of survival with bladder cancer after radical cystectomy: A retrospective study[J]. BMC Cancer, 2017, 17 (1): 391- 399.
doi: 10.1186/s12885-017-3372-8
12 Xue W , Tan P , Xu H , et al. Impact of the preoperative prognostic nutritional index on survival outcomes in upper tract urothelial carcinomas[J]. Cancer Med, 2019, 8 (6): 2971- 2978.
doi: 10.1002/cam4.2161
13 Cui J , Chen S , Bo Q , et al. Preoperative prognostic nutritional index and nomogram predicting recurrence-free survival in patients with primary non-muscle-invasive bladder cancer without carcinoma in situ[J]. Onco Targets Ther, 2017, 10 (1): 5541- 5550.
14 Kang M , Chang CT , Sung HH , et al. Prognostic significance of pre- to postoperative dynamics of the prognostic nutritional index for patients with renal cell carcinoma who underwent radical nephrectomy[J]. Ann Surg Oncol, 2017, 24 (13): 4067- 4075.
doi: 10.1245/s10434-017-6065-2
15 Jeon HG , Choi DK , Sung HH , et al. Preoperative prognostic nutritional index is a significant predictor of survival in renal cell carcinoma patients undergoing nephrectomy[J]. Ann Surg Oncol, 2016, 23 (1): 321- 327.
doi: 10.1245/s10434-015-4614-0
16 Kang HW , Seo SP , Kim WT , et al. Low preoperative serum cholesterol level is associated with aggressive pathologic features and poor cancer-specific survival in patients with surgically treated renal cell carcinoma[J]. Int J Clin Oncol, 2018, 23 (1): 142- 150.
doi: 10.1007/s10147-017-1172-4
17 de Martino M , Leitner CV , Seemann C , et al. Preoperative serum cholesterol is an independent prognostic factor for patients with renal cell carcinoma (RCC)[J]. BJU Int, 2015, 115 (3): 397- 404.
doi: 10.1111/bju.12767
18 Chen Z , Shao Y , Wang K , et al. Prognostic role of pretreatment serum albumin in renal cell carcinoma: A systematic review and meta-analysis[J]. Onco Targets Ther, 2016, 9, 6701- 6710.
doi: 10.2147/OTT.S108469
19 Byun SS , Hwang EC , Kang SH , et al. Prognostic significance of preoperative neutrophil-to-lymphocyte ratio in nonmetastatic renal cell carcinoma: A large, multicenter cohort analysis[J]. Biomed Res Int, 2016, 2016, 4148- 4156.
20 Grimes N , Hannan C , Tyson M , et al. The role of neutrophil-lymphocyte ratio as a prognostic indicator in patients undergoing nephrectomy for renal cell carcinoma[J]. Can Urol Assoc J, 2018, 12 (7): E345- E348.
21 Zhou W , Zhang GL . C-reactive protein to albumin ratio predicts the outcome in renal cell carcinoma: A meta-analysis[J]. PLoS One, 2019, 14 (10): 4266- 4277.
22 Wang X , Su S , Guo Y . The clinical use of the platelet to lymphocyte ratio and lymphocyte to monocyte ratio as prognostic factors in renal cell carcinoma: A systematic review and meta-analysis[J]. Oncotarget, 2017, 8 (48): 84506- 84514.
doi: 10.18632/oncotarget.21108
23 Jiang N , Deng JY , Ding XW , et al. Prognostic nutritional index predicts postoperative complications and long-term outcomes of gastric cancer[J]. World J Gastroenterol, 2014, 20 (30): 10537- 10544.
doi: 10.3748/wjg.v20.i30.10537
24 Zheng Y , Bao L , Wang W , et al. Prognostic impact of the controlling nutritional status score following curative nephrectomy for patients with renal cell carcinoma[J]. Medicine (Baltimore), 2018, 97 (49): e13409.
doi: 10.1097/MD.0000000000013409
25 Kanda M , Mizuno A , Tanaka C , et al. Nutritional predictors for postoperative short-term and long-term outcomes of patients with gastric cancer[J]. Medicine (Baltimore), 2016, 95 (24): e3781.
doi: 10.1097/MD.0000000000003781
26 Song Y , Yang Y , Gao P , et al. The preoperative neutrophil to lymphocyte ratio is a superior indicator of prognosis compared with other inflammatory biomarkers in resectable colorectal cancer[J]. BMC Cancer, 2017, 17 (1): 391- 399.
doi: 10.1186/s12885-017-3372-8
27 Hu H , Yao X , Xie X , et al. Prognostic value of preoperative NLR, dNLR, PLR and CRP in surgical renal cell carcinoma patients[J]. World J Urol, 2017, 35 (2): 261- 270.
doi: 10.1007/s00345-016-1864-9
28 Tsujino T , Komura K , Hashimoto T , et al. C-reactive protein-albumin ratio as a prognostic factor in renal cell carcinoma: A data from multi-institutional study in Japan[J]. Urol Oncol, 2019, 37 (11): 812.e1- 812.e8.
29 Lien YC , Hsieh CC , Wu YC , et al. Preoperative serum albumin level is a prognostic indicator for adenocarcinoma of the gastric cardia[J]. J Gastrointest Surg, 2004, 8 (8): 1041- 1048.
doi: 10.1016/j.gassur.2004.09.033
30 Gupta D , Lis CG . Pretreatment serum albumin as a predictor of cancer survival: A systematic review of the epidemiological literature[J]. Nutr J, 2010, 9 (1): 69- 85.
doi: 10.1186/1475-2891-9-69
31 Chandra RK . Nutrition and immunology: From the clinic to cellular biology and back again[J]. Proc Nutr Soc, 1999, 58 (3): 681- 683.
doi: 10.1017/S0029665199000890
32 Alwarawrah Y , Kiernan K , MacIver NJ . Changes in nutritional status impact immune cell metabolism and function[J]. Front Immunol, 2018, 9 (1): 1055- 1069.
33 Tang Y , Liu Z , Liang J , et al. Early post-operative serum albumin level predicts survival after curative nephrectomy for kidney cancer: A retrospective study[J]. BMC Urol, 2018, 18 (1): 111- 118.
doi: 10.1186/s12894-018-0427-3
34 Corcoran AT , Kaffenberger SD , Clark PE , et al. Hypoalbuminaemia is associated with mortality in patients undergoing cytoreductive nephrectomy[J]. BJU Int, 2015, 116 (3): 351- 357.
doi: 10.1111/bju.12897
35 Stone PC , Lund S . Predicting prognosis in patients with advanced cancer[J]. Ann Oncol, 2007, 18 (6): 971- 976.
doi: 10.1093/annonc/mdl343
36 Volpe A , Patard JJ . Prognostic factors in renal cell carcinoma[J]. World J Urol, 2010, 28 (3): 319- 327.
doi: 10.1007/s00345-010-0540-8
[1] Junyong OU,Kunming NI,Lulin MA,Guoliang WANG,Ye YAN,Bin YANG,Gengwu LI,Haodong SONG,Min LU,Jianfei YE,Shudong ZHANG. Prognostic factors of patients with muscle invasive bladder cancer with intermediate-to-high risk prostate cancer [J]. Journal of Peking University (Health Sciences), 2024, 56(4): 582-588.
[2] Kewei CHEN,Zhuo LIU,Shaohui DENG,Fan ZHANG,Jianfei YE,Guoliang WANG,Shudong ZHANG. Clinical diagnosis and treatment of renal angiomyolipoma with inferior vena cava tumor thrombus [J]. Journal of Peking University (Health Sciences), 2024, 56(4): 617-623.
[3] Shuai LIU,Lei LIU,Zhuo LIU,Fan ZHANG,Lulin MA,Xiaojun TIAN,Xiaofei HOU,Guoliang WANG,Lei ZHAO,Shudong ZHANG. Clinical treatment and prognosis of adrenocortical carcinoma with venous tumor thrombus [J]. Journal of Peking University (Health Sciences), 2024, 56(4): 624-630.
[4] Jie YANG,Jieli FENG,Shudong ZHANG,Lulin MA,Qing ZHENG. Clinical effects of transesophageal echocardiography in different surgical methods for nephrectomy combined with Mayo Ⅲ-Ⅳ vena tumor thrombectomy [J]. Journal of Peking University (Health Sciences), 2024, 56(4): 631-635.
[5] Le YU,Shaohui DENG,Fan ZHANG,Ye YAN,Jianfei YE,Shudong ZHANG. Clinicopathological characteristics and prognosis of multilocular cystic renal neoplasm of low malignant potential [J]. Journal of Peking University (Health Sciences), 2024, 56(4): 661-666.
[6] Fan SHU,Yichang HAO,Zhanyi ZHANG,Shaohui DENG,Hongxian ZHANG,Lei LIU,Guoliang WANG,Xiaojun TIAN,Lei ZHAO,Lulin MA,Shudong ZHANG. Functional and oncologic outcomes of partial nephrectomy for cystic renal cell carcinoma: A single-center retrospective study [J]. Journal of Peking University (Health Sciences), 2024, 56(4): 667-672.
[7] Zezhen ZHOU,Shaohui DENG,Ye YAN,Fan ZHANG,Yichang HAO,Liyuan GE,Hongxian ZHANG,Guoliang WANG,Shudong ZHANG. Predicting the 3-year tumor-specific survival in patients with T3a non-metastatic renal cell carcinoma [J]. Journal of Peking University (Health Sciences), 2024, 56(4): 673-679.
[8] Yangyi FANG,Qiang LI,Zhigao HUANG,Min LU,Kai HONG,Shudong ZHANG. Well-differentiated papillary mesothelial tumour of the tunica vaginalis: A case report [J]. Journal of Peking University (Health Sciences), 2024, 56(4): 741-744.
[9] Yuanyuan ZENG,Yun XIE,Daonan CHEN,Ruilan WANG. Related factors of euthyroid sick syndrome in patients with sepsis [J]. Journal of Peking University (Health Sciences), 2024, 56(3): 526-532.
[10] Jian-bin LI,Meng-na LYU,Qiang CHI,Yi-lin PENG,Peng-cheng LIU,Rui WU. Early prediction of severe COVID-19 in patients with Sjögren’s syndrome [J]. Journal of Peking University (Health Sciences), 2023, 55(6): 1007-1012.
[11] Yun-chong LIU,Zong-long WU,Li-yuan GE,Tan DU,Ya-qian WU,Yi-meng SONG,Cheng LIU,Lu-lin MA. Mechanism of nuclear protein 1 in the resistance to axitinib in clear cell renal cell carcinoma [J]. Journal of Peking University (Health Sciences), 2023, 55(5): 781-792.
[12] Huan-rui LIU,Xiang PENG,Sen-lin LI,Xin GOU. Risk modeling based on HER-2 related genes for bladder cancer survival prognosis assessment [J]. Journal of Peking University (Health Sciences), 2023, 55(5): 793-801.
[13] Zi-xuan XUE,Shi-ying TANG,Min QIU,Cheng LIU,Xiao-jun TIAN,Min LU,Jing-han DONG,Lu-lin MA,Shu-dong ZHANG. Clinicopathologic features and prognosis of young renal tumors with tumor thrombus [J]. Journal of Peking University (Health Sciences), 2023, 55(5): 802-811.
[14] Dong LAN,Zhuo LIU,Yu-xuan LI,Guo-liang WANG,Xiao-jun TIAN,Lu-lin MA,Shu-dong ZHANG,Hong-xian ZHANG. Risk factors for massive hemorrhage after radical nephrectomy and removal of venous tumor thrombus [J]. Journal of Peking University (Health Sciences), 2023, 55(5): 825-832.
[15] Min QIU,You-long ZONG,Bin-shuai WANG,Bin YANG,Chu-xiao XU,Zheng-hui SUN,Min LU,Lei ZHAO,Jian LU,Cheng LIU,Xiao-jun TIAN,Lu-lin MA. Treatment outcome of laparoscopic partial nephrectomy in patients with renal tumors of moderate to high complexity [J]. Journal of Peking University (Health Sciences), 2023, 55(5): 833-837.
Viewed
Full text


Abstract

Cited
  Shared   
  Discussed   
No Suggested Reading articles found!
Copyright © Journal of Peking University (Health Sciences), All Rights Reserved.
Powered by Beijing Magtech Co. Ltd