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01.12.2017 | Research article | Ausgabe 1/2017 Open Access

BMC Cancer 1/2017

Preoperative Prognostic Nutritional Index is a Significant Predictor of Survival with Bladder Cancer after Radical Cystectomy: a retrospective study

Zeitschrift:
BMC Cancer > Ausgabe 1/2017
Autoren:
Ding Peng, Yan-qing Gong, Han Hao, Zhi-song He, Xue-song Li, Cui-jian Zhang, Li-qun Zhou
Abbreviations
PNI
Prognostic nutritional index
OS
Overall survival
PFS
Progression free survival
MIBC
Muscle-invasive bladder cancer
NMIBC
Non-muscle invasive bladder cancer
IQR
Interquartile range
ASA
American Society of Anesthesiologists
ROC
Receiver operating characteristic
AUC
Area under the receiver operating characteristic curve

Background

Radical cystectomy is the standard treatment for localized muscle-invasive bladder cancer (MIBC) and non-muscle invasive bladder cancer (NMIBC) unresponsive to intravesical therapy [1, 2]. Despite the advances in surgical skills and chemotherapy, the 5-year survival with all bladder cancer is 77.9% and only 33.0% and 5.4% for regional and distant disease [3]. Therefore, prognostic factors for bladder cancer are needed for treatment decision making and postoperative monitoring.
Several preoperative hematological parameters have been reported as prognostic biomarkers for bladder cancer. Prognostic indicators suggested have been based on albumin and C-reactive protein levels and platelet and blood count, such as neutrophil/lymphocyte ratio [NLR], platelet/lymphocyte ratio (PLR) and lymphocyte/monocyte ratio (LMR) [48]. In addition, prognostic nutritional index (PNI), which combines nutrition and inflammation status, has been found to predict outcomes in various cancers [914]. However, no study has evaluated the prognostic value of PNI in bladder cancer.
This study aimed to explore the prognostic significance of preoperative PNI in bladder cancer patients after radical cystectomy and compare the prognostic ability of inflammation-based indices.

Methods

We retrospectively reviewed the medical data for 571 consecutive bladder cancer patients who underwent radical cystectomy between 2006 and 2012 in Peking University First Hospital. We excluded 55 patients with non-bladder cancer, were lost to follow-up or had a history of disease that could affect blood cell lines. Therefore, we analyzed data for 516 patients. Clinicopathological data including gender, age, smoking status, history of Diabetes Mellitus, hypertension, heart and cerebrovascular disease, histology type, operation style (open or laparoscopic), American Society of Anesthesiologists (ASA) grade, postoperative complications (including prolonged ileus, fever, wound infection, wound dehiscence, gastrointestinal bleeding, cardiac arrhythmia, myocardial infarction, urinary leakage, pneumonia and death), pathological lymph-node status, pathological T stage and differential grade were obtained from the medical database. Histological subtype was diagnosed by at least 2 experienced pathologists on the basis of the 1973 WHO criteria, and TNM staging was assessed by the American Joint Committee on Cancer cancer staging system (7th edition, 2010). Hematological factors including preoperative hemoglobin and albumin levels and complete blood counts were collected within 3 days before surgery. This study was approved by the Institutional Review Board of Peking University First Hospital.

Statistical analysis

The endpoint of the study was overall survival (OS), calculated from the day of surgery to the time of all-caused death, and progression-free survival (PFS), as the period from the date of surgery to the time of disease recurrence, metastasis or death. All continuous data are shown as median (interquartile range [IQR]). PNI was calculated as albumin level (g/L) + 5 × lymphocyte count (109/L), PLR as platelet/lymphocyte ratio, NLR as neutrophil/lymphocyte count, and LMR as lymphocyte/monocyte count. Receiver operating characteristic (ROC) curve analysis was used to compare the prognostic ability of each indicator for each OS and PFS event according to the area under the ROC curve (AUC) and to determine the best cutoff points. For each prognostic factor, patients were divided into 2 groups according to cutoffs. The Kaplan–Meier survival method were used to draw OS and PFS curves. Univariate analysis involved the log-rank test. Factors significant on univariate analysis were included in Cox proportional-hazards multivariate models, estimating hazard ratios (HRs) and 95% CIs. The association of clinicopathological characteristics and PNI or NLR was tested by Mann–Whitney U-test. Statistical significance was considered with two-sided p < 0.05. All statistical analyses involved use of SPSS v21.0 (IBM Inc. Chicago, IL, USA).

Results

A total of 516 patients (median age 66 years, IQR 57–73; 80 females [15.5%]) were included in this study. The median follow-up was 37 months (IQR 20–56). At the end of follow-up, 164 (31.8%) patients had died from any cause and 188 (36.4%) showed disease progression. The clinicopathological characteristics of all patients are shown in Table 1. The tumor stage of all patients was T1 for 162 (31.4%), T2 for 161 (31.2%), T3 for 105 (20.3%), and T4 for 88 (17.1%). The 3- and 5-year OS was 75.3% and 69% and PFS was 63.7% and 59.7%. Median NLR was 2.34 (IQR 1.74–3.49), PLR: 133.8 (98.22–180.22), LMR: 4.37 (3.30–5.72), PNI: 47.8 (44.66–51.58).
Table 1
Baseline clinicopathological characteristics of patients with bladder cancer
Characteristics
Total n = 516
Age, years, median (IQR)
66 (35–91)
Female sex, n (%)
80 (15.5%)
Histology type, n (%)
 
 UC
488 (94.6%)
 NUC
28 (5.4%)
Pathological grade, n (%)
 
 2
131 (25.4%)
 3
385 (74.6%)
Smoking history
161 (31.2%)
Diabetes Mellitus
56 (10.9%)
Hypertension
149 (28.9%)
Heart disease
55 (10.7%)
Cerebrovascular disease
17 (3.3%)
pT stage, n (%)
 
 1
162 (31.4%)
 2
161 (31.2%)
 3
105 (20.3%)
 4
88 (17.1%)
pN status, n (%)
 
 negative
81 (15.7%)
 positive
435 (84.3%)
ASA grade, n (%)
 
 1&2
436 (84.5%)
 3&4
80 (15.5%)
Surgery style
 
 open
409 (79.3%)
 laparoscopic
107 (20.7%)
Postoperative complications
 
 present
73 (8.3%)
 absent
443 (91.7%)
Anemia
 
 present
144 (27.9%)
 absent
372 (72.1%)
Hypoalbuminemia
 
 present
74 (14.3%)
 absent
442 (85.7%)
NLR, median (IQR)
2.34 (1.74–3.49)
PLR, median (IQR)
133.8 (98.22–180.22)
LMR, median (IQR)
4.37 (3.30–5.72)
PNI, median (IQR)
47.8 (44.66–51.58)
UC urothelial carcinoma, NUC non-urothelial carcinoma, ASA American Society of Anesthesiologists, PNI prognostic nutritional index, NLR neutrophil-lymphocyte ratio, PLR platelet-lymphocyte ratio, LMR lymphocyte-monocyte ratio, IQR, interquartile range
The AUC value was greater for PNI than the other 3 factors for estimating OS and PFS (Fig. 1). We determined the cutoff values for the 4 factors for OS and PFS by calculating the maximum Youden index (OS: PNI-46.025, NLR-2.303, PLR-136.125, LMR-4.099; PFS: PNI-47.20, NLR-2.288, PLR-135.247, LMR-4.099). Then patients were divided into low- and high-risk groups according to the ratios.
On univariate analysis, significant indicators for both OS and PFS were older age (>65 years), high tumor grade, pT2 or greater, positive lymph node status, history of heart and cerebrovascular disease, high ASA grade, hypoalbuminemia, anemia, postoperative complications and the 4 indicators (PNI, PLR, NLR, LMR) (Table 2). As compared with high PNI, low PNI was associated with worse OS and PFS (Fig. 2).
Table 2
Univariate and multivariate analyses of prognostic factors for overall survival and progression-free survival
Variable
Univariate
Multivariate
P value
HR (95% CI)
P Value
Overall survival
   
 Age (>65 vs. ≤65)
<0.001
1.615 (1.116–2.337)
0.011
 Gender (male vs. female)
0.264
  
 Histology type (NUC vs. UC)
0.363
  
 Pathological grade (3 vs. 2)
<0.001
  
 pT (pT2 or greater vs. pT1)
<0.001
2.796 (1.700–4.598)
<0.001
 pN status (positive vs. negative)
<0.001
1.682 (1.141–2.480)
0.009
 Smoking history
0.937
  
 Hypertension
0.480
  
 Diabetes Mellitus
0.534
  
 Heart disease
0.018
  
 Cerebrovascular disease
0.032
  
 ASA grade (3&4 vs. 1&2)
<0.001
1.641 (1.113–2.418)
0.012
 Hypoalbuminemia
<0.001
  
 Anemia
<0.001
  
 Postoperative complications
0.003
1.607 (1.076–2.400)
0.020
 PNI (low vs. high)
<0.001
1.668 (1.147–2.425)
0.007
 PLR (high vs. low)
<0.001
  
 NLR (high vs. low)
<0.001
1.416 (1.094–2.016)
0.014
 LMR (low vs. high)
<0.001
  
Progression-free survival
   
 Age (>65 vs. ≤65)
<0.001
  
 Gender (male vs. female)
0.304
  
 Histology type (NUC vs. UC)
0.683
  
 Pathological grade (3 vs. 2)
<0.001
  
 pT (pT2 or greater vs. pT1)
<0.001
2.560 (1.677–3.906)
<0.001
 pN status (positive vs. negative)
<0.001
1.871 (1.306–2.680)
0.001
 Smoking history
0.952
  
 Hypertension
0.604
  
 Diabetes Mellitus
0.681
  
 Heart disease
0.012
  
 Cerebrovascular disease
0.033
  
 ASA grade (3&4 vs. 1&2)
<0.001
1.561 (1.086–2.243)
0.016
 Hypoalbuminemia
<0.001
  
 Anemia
<0.001
  
 Postoperative complications
0.004
  
 PNI (low vs. high)
<0.001
1.680 (1.092–2.005)
0.011
 PLR (high vs. low)
<0.001
  
 NLR (high vs. low)
<0.001
1.550 (1.140–2.388)
0.008
 LMR (low vs. high)
<0.001
  
UC urothelial carcinoma, NUC non-urothelial carcinoma, ASA American Society of Anesthesiologists, PNI prognostic nutritional index, NLR neutrophil-lymphocyte ratio, PLR platelet-lymphocyte ratio, LMR lymphocyte-monocyte ratio
Significant values are in bold
Thus, these variables were included in a Cox proportional-hazards model. Independent risk factors for OS were older age (>65 years; HR = 1.615, 95% CI:1.116–2.337, P = 0.011), pT2 or greater (HR = 2.796, 95% CI:1.700–4.598, P < 0.001), positive lymph node status (HR = 1.682, 95% CI:1.141–2.480, P = 0.009), high ASA grade (HR = 1.641, 95% CI:1.113–2.418, P = 0.012), postoperative complications (HR = 1.607, 95% CI: 1.076–2.400, P = 0.020),low PNI (HR = 1.668, 95% CI: 1.147–2.425, P = 0.007) and high NLR (HR = 1.416, 95% CI:1.094–2.016, P = 0.0149). For PFS, independent risk factors were pT2 or greater (HR = 2.560, 95% CI:1.677–3.906, P < 0.001), positive lymph node status (HR = 1.871, 95% CI:1.306–2.680, P = 0.001), high ASA grade (HR = 1.561, 95% CI:1.086–2.243, P = 0.016), low PNI (HR = 1.680, 95% CI:1.092–2.005, P = 0.015) and high NLR (HR = 1.550, 95% CI:1.140–2.388, P = 0.008).
Inflammatory status may be affected by disease stage. Therefore, we classified patients into 3 groups by pathological stage (Fig. 3). OS was shorter for patients with low than high PNI with all stages (stage 1: P = 0.042, stage 2: P = 0.002, stages 3 and 4: P = 0.012). However, PFS was shorter for patients with low PNI only with stage 1 or 2 disease (stage 1: P = 0.014, stage 2: P = 0.001, stages 3 and 4: P = 0.141).
We then assessed PNI and NLR for patients with different clinicopathological characteristics. Low PNI was associated with older age (>65 years), pT2 or greater, high ASA grade and anemia (Table 3). Meanwhile, elevated NLR level was associated with older age (>65 years), high grade and ASA grade, pT2 or greater, positive lymph node status, cerebrovascular disease and anemia.
Table 3
Relationship between clinicopathological characteristics and PNI or NLR
Variable
N
PNI
P value
NLR
P value
Gender
  
0.068
 
0.406
 male
436
48.05 (44.95–51.75)
 
2.39 (1.77–3.47)
 
 female
80
46.90 (43.87–50.05)
 
2.21 (1.59–3.97)
 
Age, years
  
<0.001
 
<0.001
  > 65
278
46.92 (43.33–49.68)
 
2.61 (1.95–3.91)
 
  ≤ 65
238
49.62 (46.25–53.22)
 
2.15 (1.68–2.92)
 
Histology type
  
0.396
 
0.667
 UC
488
47.80 (44.65–51.55)
 
2.33 (1.76–3.49)
 
 NUC
28
48.95 (46.15–53.05)
 
2.67 (1.66–3.54)
 
Pathological grade
  
0.086
 
0.048
 2
131
48.65 (45.25–52)
 
2.24 (1.70–2.90)
 
 3
385
47.65 (44.52–51.15)
 
2.43 (1.76–3.73)
 
T stage
  
<0.001
 
<0.001
 pT2 or greater
354
47.35 (44.05–50.65)
 
2.52 (1.90–3.93)
 
 pT1
162
49.00 (46.20–52.97)
 
2.06 (1.63–2.68)
 
N status
  
0.250
 
0.041
 negative
435
48.00 (44.90–51.65)
 
2.29 (1.71–3.42)
 
 positive
81
47.10 (43.87–51.02)
 
2.50 (1.99–3.96)
 
Smoking
  
0.109
 
0.524
 no
355
47.55 (44.40–51.57)
 
2.39 (1.72–3.64)
 
 yes
161
48.70 (45.42–51.60)
 
2.33 (1.81–3.17)
 
Diabetes Mellitus
  
0.948
 
0.179
 no
460
47.8 (44.75–51.60)
 
2.32 (1.73–3.44)
 
 yes
56
48 (44.50–51.28)
 
2.72 (1.81–3.99)
 
Hypertension
  
0.862
 
0.067
 no
367
47.80 (44.75–51.65)
 
2.27 (1.71–3.19)
 
 yes
149
48.02 (44.57–51.15)
 
2.50 (1.82–3.75)
 
Heart disease
  
0.177
 
0.516
 no
461
47.97 (44.90–51.65)
 
2.31 (1.73–3.53)
 
 yes
55
47.22 (43.70–50.56)
 
2.48 (1.78–3.09)
 
Cerebrovascular disease
  
0.277
 
0.045
 no
499
47.95 (44.71–51.6)
 
2.32 (1.72–3.44)
 
 yes
17
47.10 (42.77–49.10)
 
2.69 (2.22–4.04)
 
Surgery style
  
0.278
 
0.806
 open
409
47.95 (44.9051.75)
 
2.37 (1.73–3.65)
 
 laparoscopic
107
47.60 (44.2051.25)
 
2.28 (1.80–3.20)
 
Postoperative complications
  
0.129
 
0.730
 no
443
48.00 (45.05–51.55)
 
2.33 (1.76–3.47)
 
 yes
73
46.35 (43.75–51.78)
 
2.37 (1.59–3.61)
 
ASA grade
  
<0.001
 
0.031
 1&2
436
48.05 (45.25–51.90)
 
2.30 (1.725–3.21)
 
 3&4
80
46.00 (42.50–49.37)
 
2.53 (2.05–3.99)
 
Anemia
  
<0.001
 
<0.001
 no
372
49.07 (46.502.93)
 
2.23 (1.69–2.96)
 
 yes
144
44.55 (40.90–47.38)
 
3.01 (2.00–4.42)
 
UC urothelial carcinoma, NUC non-urothelial carcinoma, ASA American Society of Anesthesiologists, PNI prognostic nutritional index, NLR neutrophil-lymphocyte ratio, PLR platelet-lymphocyte ratio, LMR lymphocyte-monocyte ratio
Significant values are in bold

Discussion

Inflammation-based ratios are representative biomarkers of host inflammation response that predict the prognosis of cancer. In this study, we assessed the prognostic value of PNI and compared the prognostic ability of inflammation-based indices in bladder cancer patients who underwent radical cystectomy. By univariate and multivariate analyses, we found that PNI and NLR as prognostic and independent risk factors for both OS and PFS.
Immune cells play an important role in tumorigenesis, development and metastasis. Neutrophils can interact with tumor cells and secrete cytokines and chemokines which could promote tumor proliferation, angiogenesis and metastasis [15]. For example, neutrophils could secrete vascular endothelial growth factor (VEGF) into the circulation and VEGF is essential for tumor angiogenesis, metastasis and drug resistance. On the other hand, the role of lymphocytes is mainly through the tumor immune surveillance and tumor cell clearance to inhibit the tumorigenesis and development. In addition, neutrophils in the tumor microenvironment could also interact with lymphocytes and reduce the antitumor effects of activated T cells and natural killer (NK) cells [16, 17]. Therefore, an elevated NLR represent a neutrophilia and lymphocytopenia, which reflected the imbalance in the immune response. As a simple systemic inflammation response marker, NLR has been recommended associated with worse recurrence-free, disease-specific, and overall survival in patients with bladder cancer [18]. In the present study, NLR was independent risk factor for OS and PFS for bladder cancer patients and this is consistent with previous studies.
In addition to inflammation response, nutrition status is another important prognostic impact for cancer patients. Hypoalbuminemia has been demonstrated associated with cancer recurrence and decreased OS in bladder cancer patients after RC [19, 20]. Moreover, increasing evidence indicated that hypoalbuminemia in cancer patients is related with inflammatory imbalance as well as cancer cachexia. Lambert et al. [19] evaluated 187 bladder cancer patients and found 31(16.5%) patients were in the low-albumin cohort(albumin <3.5 g/dL). The OS was lower in low-albumin group than those with normal albumin and the complication rates were also higher in the group with low albumin. Djaladat et al. [20] reported 197 patients (13.4%) from a 1964 bladder cancer patients cohort had a low albumin level (<3.5 g/dL). In multivariable analysis for OS and RFS, low albumin remained independently associated with decreased OS and RFS. In our study, we observed 74 (13.66%) patients with albumin <3.5 g/dL and hypoalbuminemia was predictor for OS and PFS in univariate analysis. Those findings support the importance of albumin level in prognosis for bladder cancer.
PNI was first created by Onodera et al. to evaluate the inflammation and nutrition status of patients after gastrointestinal surgery [21]. Because PNI is calculated by serum albumin and lymphocyte count, decreased PNI represents hypoalbuminemia and decreased lymphocyte count, both responsible for worse outcomes in cancer patients. Since then, it has been a predictor of survival in several solid tumors including colorectal, breast, oesophageal, hepatocellular, renal and lung cancer [911, 13]. Ryuma Tokunaga et al. [22] compared the systemic inflmmatory and nutritional scores for colorectal cancer patients after curative resection and found PNI was a better predictive score than NLR, PLR and CRP.
Several studies also have compared inflammation-based ratios to find a good marker for bladder cancer and NLR or LMR was reported as the best [7, 23, 24]. These results differing from ours may be due to differences in patient characteristics and populations. In our study, NLR but not LMR remained an independent factor of survival on multivariate analysis, which may support the significance of NLR. In addition, these studies did not include PNI, a comprehensive and easily measured indicator. Therefore, we investigated PNI in the prognosis of bladder cancer and found it as a predictor of OS and PFS.
Our study has some limitations. First, this was a retrospective observational study and the inherent retrospective and nonrandomized nature may have led to selection bias. Second, we did not measure blood cell counts at regular intervals after radical cystectomy and could not explore the predictive value of the change in inflammation-based biomarkers pre- and post-radical cystectomy. Finally, this study was a single, tertiary-care institution study and our findings require well-controlled and multiple-institution studies for external validation.

Conclusion

Both PNI and NLR are independent risk factors for OS and PFS. PNI may be an additional easily measured biomarker for stratifying risk preoperatively for bladder cancer patients who undergo radical cystectomy.

Acknowledgements

Not applicable.

Authors’ contribution

LZ, CZ, DP, and YG conceived and designed project. HH, XL, ZH, DP and YG collected data. DP and YG analyzed the data. DP, CZ, YG and LZ wrote the manuscript. All authors read and approved the final manuscript.

Funding

This work was supported by the National Natural Science Foundation of China (Grant Number: 81372746 and 81672546).

Availability of data and materials

The data and charts involved in this article are available from the corresponding author if there are reasonable reasons.

Competing interests

All authors in this article declare that they have no competing interests.

Consent for publication

Not applicable.

Ethics approval and consent to participate

Written informed consents for their information to be stored and used in the hospital database were obtained prior to data collection and the study was approved by the ethics committee of Peking University First Hospital. The study was conducted in accordance with the Declaration of Helsinki to protect the personal data.

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