Advances in Clinical and Experimental Medicine

Title abbreviation: Adv Clin Exp Med
JCR Impact Factor (IF) – 2.1
5-Year Impact Factor – 2.0
Scopus CiteScore – 3.7 (CiteScore Tracker 3.3)
Index Copernicus  – 161.11; MNiSW – 70 pts

ISSN 1899–5276 (print)
ISSN 2451-2680 (online)
Periodicity – monthly

Download original text (EN)

Advances in Clinical and Experimental Medicine

Ahead of print

doi: 10.17219/acem/169495

Publication type: original article

Language: English

License: Creative Commons Attribution 3.0 Unported (CC BY 3.0)

Download citation:

  • BIBTEX (JabRef, Mendeley)
  • RIS (Papers, Reference Manager, RefWorks, Zotero)

Cite as:


Wei H, Wang J, Jiang Z, Liu Y, Jiang S, Hu B. Preoperative prognostic nutritional index associated with anastomotic leakage of colorectal cancer patients after surgery [published online as ahead of print on August 4, 2023]. Adv Clin Exp Med. 2024. doi:10.17219/acem/169495

Preoperative prognostic nutritional index associated with anastomotic leakage in colorectal cancer patients after surgery

Haotang Wei1,A,B,C, Jialei Wang1,B,C,D, Zhengkai Jiang1,E,F, Yu Liu1,B,C,D, Sheng Jiang1,B,C, Bangli Hu2,A,D

1 Department of Gastrointestinal Surgery, Third Affiliated Hospital of Guangxi Medical University, Nanning, China

2 Department of Research, Guangxi Medical University Cancer Hospital, Nanning, China

Graphical abstract


Graphical abstracts

Abstract

Background. Anastomotic leakage (AL) is a severe complication of colorectal cancer (CRC) surgery and is associated with the immune and nutritional status.

Objectives. This study aimed to investigate the role of the prognostic nutritional index (PNI) in AL in CRC patients after surgery.

Materials and methods. A retrospective case–control study was designed in a single center. The clinicopathological features and preoperative laboratory data of 124 CRC patients and 120 non-cancer patients who underwent surgery were collected and examined. Among the CRC patients, 24 had AL.

Results. Nutritional indicators were lower in CRC patients than in non-cancer patients (p < 0.05), but the clinical parameters analysis showed that only metastasis (M) stage, albumin, carcinoembryonic antigen (CEA), CA153, and PNI were associated with AL in CRC after surgery (p < 0.05). Prognostic nutritional index had a moderate predictive value for AL, with an area under the curve (AUC) of 0.625. Using the median value as a cutoff point, a high PNI was associated with a longer survival time in CRC patients (p = 0.033), and AL showed marginal significance (p = 0.048). The nomogram showed that PNI has a better prognostic value than tumor–node–metastasis (TNM) staging in CRC patients who underwent surgery.

Conclusions. Prognostic nutritional index is a useful supplement for predicting AL in CRC patients after colorectal surgery. It also helps predict the prognosis of CRC patients.

Key words: colorectal cancer, anastomotic leakage, prognostic nutritional index

Background

Surgery is a major treatment approach for colorectal cancer (CRC), and anastomotic leakage (AL) is one of the most severe early complications of colorectal surgery, with an incidence rate of 1–30%, depending on the site of anastomosis (rectum > colon).1 Anastomotic leakage causes abdominal infections, sepsis and prolonged hospital stays, and is associated with a high reoperation rate, increased short- and long-term morbidity and mortality rates,2, 3 as well as reduced quality of life. Thus, identifying the risk factors associated with AL after colorectal surgery remains a critical need for doctors.4

The exact etiology of AL remains unclear. Current evidence indicates that AL is a result of multiple factors, including operation time,5 steroidal anti-inflammatory drug use6 and surgical experience.7 In addition, nutritional status,8 inflammation status9 and immune system status10 contribute to the occurrence of AL after colorectal surgery. Several indicators, such as the neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR) and lymphocyte-to-monocyte ratio (LMR), have reportedly been associated with AL.11 In addition, some novel indicators, including the systemic immune-inflammation index (SII),12 prognostic nutritional index (PNI), pan-immune-inflammation value (PIV),13 as well as systemic inflammation response index (SIRI),14 have been reported to be associated with the survival of various cancers.

Given that AL is associated with nutrition, inflammation and immune status, finding indicators that can be incorporated into routine blood examination to predict AL in CRC patients after colorectal surgery can help prevent the occurrence of AL, thus improving treatment efficacy.

Objectives

This study aimed to determine the association of NLR, LMR, PLR, PNI, SII, PIV, SIRI, and PNI with AL in CRC patients after colorectal surgery to identify reliable indicators that predict AL, and explore their association with the survival of CRC patients.

Materials and methods

Data collection

This study has a case–control design. The data were retrospectively collected from CRC patients who underwent surgery between March 2013 and July 2022 at Third Affiliated Hospital of Guangxi Medical University (Nanning, China). The inclusion criteria were as follows: 1) histopathologically validated CRC diagnosis; 2) surgical resection of the primary CRC tumor; and 3) complete clinicopathological and postoperative follow-up data. The exclusion criteria included 1) complications with other primary tumors; 2) complications with severe autoimmune diseases, infectious diseases, blood diseases, or injury; and 3) complications with severe liver or kidney malfunction. We also collected data from 120 non-cancer control patients who underwent abdominal surgery.

Clinical data collection and definitions

Clinicopathological features and preoperative laboratory data were collected from the patient’s electronic medical records, and laboratory data used were collected within 3 days of surgery. As part of the clinicopathological analysis of CRC, data on patient’s age, sex, body mass index (BMI), tumor–node–metastasis (TNM) stage, routine blood tests, liver function tests, and tumor biomarkers were collected. A summary of the surgical information included data on the surgical approach (laparoscopic or open), the operation time and the volume of bleeding that occurred during the surgery. The NLR, LMR, PLR, PNI, SII, PIV, SIRI, and PNI were calculated as previously described.14, 15, 16, 17 Anastomotic leakage was defined based on the statement of the International Study Group of Rectal Cancer,18 in which the integrity of the intestinal wall fails at the anastomosis site, and the communication between the intraintestinal and extraintestinal compartments is established.

Follow-up

The follow-up for patients with CRC after surgery was performed every 3 months for the first 2 years, followed by a 6-month follow-up frequency for the next 2 years. The last follow-up date was July 12, 2022. In this study, overall survival (OS) was defined as the number of years between the date of surgery and the date of death or last follow-up of the patient.

Statistical analyses

The distribution of data was tested using the Shapiro–Wilk test, with a p-value <0.05 indicating a normal distribution. The results are listed in Supplementary Table 1. Student’s t-tests with Welch’s correction were used to compare normally distributed continuous data. Median and interquartile range (IQR) as well as the Mann–Whitney U test were used to compare data that were non-normally distributed. Data from categorical variables are presented as absolute numbers (percentages) and compared using the χ2 test or Fisher’s exact test if the sample size was small (when the expected frequency count in any cell of the table was less than 5). The survival analysis was conducted using the Kaplan–Meier plots and log-rank tests. The predictive advantage was distinguished using the receiver operating characteristic (ROC) and area under the curve (AUC). A value of p < 0.05 was considered statistically significant. All studies were performed with the use of R language (v. 4.1.3; R Foundation for Statistical Computing, Vienna, Austria).

Results

Clinical characteristics of the included participants

A total of 124 CRC patients and 120 non-cancer patients who underwent abdominal surgery were included in the study. Adenocarcinoma was the histological type of all CRCs. The results of variance homogeneity t-tests for patients with and without CRC are listed in Supplementary Table 2. A comparison of clinicopathological and preoperative laboratory data between CRC and non-cancer patients is listed in Table 1. Age, gender and BMI of CRC patients showed little significance between cancer and non-cancer patients (p > 0.05). Blood nutritional indicators, including hemoglobin, albumin, globulin, total protein, and prealbumin levels, were lower in CRC patients than in non-cancer patients (p < 0.05). The levels of tumor biomarkers, including carcinoembryonic antigen (CEA), CA125 and CA199, were significantly higher in CRC patients than in non-cancer patients. Other blood indicators, including PLR, NLR, albumin-to-globulin ratio (AGR), and PNI, were substantially elevated in CRC patients compared to non-cancer patients (p < 0.05).

Patients who exhibited risk factors related to AL underwent surgeries for CRC

The results of the variance homogeneity t-tests between patients with and without AL are presented in Supplementary Table 3. As listed in Table 2, M0 stage and laparoscopic surgery were associated with AL in patients who underwent surgeries for CRC. Patients complicated with AL exhibited low levels of albumin, CEA, CA153, and PNI as compared to patients without AL (p < 0.05). Age, sex, tumor type, tumor location, TNM stage, and other blood indicators were not significantly associated with AL (p > 0.05). Using a ROC curve analysis, we found that albumin, CA153 and PNI had a moderate predictive value for AL, with AUC values of 0.662 (95% confidence interval (95% CI): 0.55–0.76), 0.648 (95% CI: 0.52–0.78) and 0.625 (95% CI: 0.52–0.73), respectively, whereas the predictive value of CEA was low, with an AUC of 0.535 (95% CI: 0.42–0.68) (Figure 1).

Survival analysis of the blood biomarkers and anastomotic leakage in CRC patients

Previous studies have indicated that SII,19 PIV,20 SIRI,21 and PNI22 were associated with the survival of patients with CRC who underwent surgery. In this study, we determined the association of the 4 biomarkers and AL with the survival of patients with CRC. Using the median value as a cutoff point, we found that high PNI was associated with a longer survival time in CRC patients (p = 0.033), and AL was marginally associated with the survival of CRC patients (p = 0.048), while SII, PIV and SIRI did not show an obvious association with the patients’ survival (p > 0.05) (Figure 2).

Association of PNI with clinicopathological features in CRC

Next, we explored the association of PNI with clinicopathological features in CRC patients. As illustrated in Figure 3, PNI was significantly associated with T stage (p = 0.044), but was not associated with sex, cancer type, N stage, M stage, and tumor stage (p > 0.05).

Comparison of the prognostic value of clinical parameters in CRC patients

To compare the prognostic value of clinical features in CRC patients who underwent surgery, the nomogram was prepared after analyzing age, TNM stage, tumor stage, AL, and PNI. As shown in Figure 4, PNI showed a better prognostic value in CRC patients who underwent surgery for 1-, 3- and 5-year survival time as compared to other clinicopathological features such as age, TNM stage, tumor stage, and AL.

Discussion

Due to the high risk of AL in patients after colorectal surgery, this study explored the indicators that could serve as predictive biomarkers for AL. By comparing the data between CRC and non-cancer patients, we found that several blood cell count indicators were increased, while the nutritional status was decreased in CRC patients. Next, we compared the clinicopathological features of CRC patients with and without AL after colorectal surgery, and found that female sex, M stage, albumin, CEA, CA153 and PNI were associated with AL, and albumin, CA153 and PNI had a moderate predictive value for AL, suggesting that these indicators may help screen patients at high risk of AL after colorectal surgery. Subsequently, we explored the association between SII, PIV, SIRI and PNI, and found that high PNI was associated with longer survival time in CRC patients. Moreover, the nomogram showed that PNI had a better prognostic value for 1-, 3- and 5-year survival time compared with other clinicopathological features in CRC patients who underwent surgery. Taken together, these results demonstrate that CRC patients with AL present with lower nutritional status and that PNI could help predict AL. Prognostic nutritional index was associated with the survival of CRC patients and showed a better prognostic value in CRC patients who underwent surgery.

Prognostic nutritional index is calculated based on serum albumin levels and peripheral blood lymphocyte counts, and is an indicator that reflects both the nutritional and immune status of patients.23, 24 Our results showed that patients with AL had lower albumin levels than those without AL, although no significant difference was noted in lymphocyte counts. The role of PNI in predicting AL in gastrointestinal tumors had been reported before. A previous study25 stated that preoperative PNI showed no significant prognostic value for short-term outcomes in patients with AL after cancerous esophagectomy. Another study26 reported that PNI is useful for predicting the onset of postoperative complications (including AL) in patients with esophageal cancer after resection. Recently, a study27 concluded that PNI was a predictor of AL (risk ratio (RR): 0.151; 95% CI: 0.036–0.640) in CRC patients after curative surgery. In this study, we found that, similar to the result of CA153, PNI exhibited a moderate predictive value for AL, but was superior to CEA, suggesting that high PNI and CA153 could help screen patients at risk of AL, but CEA showed little significance in this aspect. However, the number was small, with only 11 patients having an AL; thus, the reliability of PNI in predicting AL needs to be further validated.

After confirming the association between PNI and AL in CRC patients after colorectal surgery, we investigated the prognostic value of PNI in CRC. Prognostic nutritional index has been reported to be associated with the treatment response and survival of various malignant tumors such as CRC,28 breast cancer17 and esophageal cancer,29 suggesting that PNI could be a novel prognostic indicator for patients with cancer. Our results are in line with those of previous studies,30 which confirmed the association of PNI and AL with the survival of CRC patients after colorectal surgery. More importantly, PNI-based nomograms showed better prognostic accuracy than TNM stage, tumor stage and AL, which has not been reported in previous studies, indicating that PNI could act as an auxiliary indicator to predict the prognosis of CRC patients. Moreover, the nomograms revealed that PNI showed a much better predictive accuracy; thus, it could serve as a reliable indicator to estimate the prognosis of CRC patients.

Limitations

The present study has some limitations. First, it had a retrospective design and was a single-center study, which inevitably led to selection bias. Second, even though we retrieved a long period of medical records, the number of ALs was relatively small, and the robustness of the results was undermined. Third, some factors that might affect nutritional status, such as genetics and intestinal microbiota, were not taken into consideration in this study; thus, the reliability of our results might be reduced. Fourth, molecular status, such as microsatellite instability (MSI), is an important prognostic and predictive factor in patients with CRC. However, due to the limited data of our study, we could not analyze the effect of molecular status on AL after surgery. Therefore, our results need to be validated in prospective, larger, multicenter cohorts.

Conclusions

This study demonstrated that preoperative PNI is a useful supplement for predicting AL in CRC patients after colorectal surgery and it also helps predict the prognosis of CRC patients. However, considering the limitations of this study, a larger study is required to validate these results.

Supplementary data

The supplementary materials are available at https://doi.org/10.5281/zenodo.8106981. The package contains the following files:

Supplementary Table 1. Continuous data distribution analysis with Shapiro–Wilk normality test.

Supplementary Table 2. Variance homogeneity t-test results between patients with or without CRC.

Supplementary Table 3. Variance homogeneity t-test results between patients with or without anastomotic leakage.

Tables


Table 1. Clinical characteristics of the included participants

Clinical variables

CRC (n = 124)

Non-cancer (n = 120)

χ2/t/Z-value

p-value

Gender

male

61 (49.2%)

64 (53.3%)

female

63 (50.8%)

56 (46.7%)

Age

63.5 ±13.3

61.4 ±8.45

1.4617

0.145*

BMI

22.1 (19.7–24.7)

22.8 (20.4–24.8)

4684.5

0.328

WBC

6.80 (5.80–8.43)

6.70 (5.50–8.03)

6871

0.302

Hemoglobin

116 (99.8–130)

138 (122–148)

10886

<0.001

Platelet

288 (224–361)

244 (222–279)

5536

0.001

Neutrophil

4.29 (3.29–5.87)

3.53 (2.79–4.70)

5709.5

0.002

Lymphocyte

1.58 (1.06–1.90)

2.01 (1.59–2.45)

10323

<0.001

Monocyte

0.55 (0.43–0.80)

0.60 (0.50–0.75)

7966.5

0.339

Fibrinogen

4.09 (3.45–4.69)

2.95 (2.58–3.40)

2732.5

<0.001

Albumin

36.7 ±4.26

40.5 ±3.80

7.433

<0.001*

Globulin

27.0 (24.9–29.9)

26.0 (23.8–28.2)

6097

0.015

AGR

1.36 (1.21–1.48)

1.52 (1.41–1.74)

10963.5

<0.001

Total protein

63.6 (60.1–68.3)

66.9 (62.9–69.8)

9216

0.001

Prealbumin

182 ±52.5

255 ±62.3

9.860

<0.001*

Ferritin

120 (34.2–258)

171 (69.1–295)

8653.5

0.028

CEA

4.60 (2.29–13.7)

1.75 (1.10–2.82)

3149.5

<0.001

AFP

2.40 (1.80–3.10)

2.25 (1.70–3.00)

6975

0.399

CA125

10.3 (7.50–19.0)

8.62 (6.82–12.6)

5805.5

0.003

CA153

10.4 (6.84–16.2)

10.2 (7.20–14.6)

6910

0.456

CA199

11.9 (6.85–24.8)

8.60 (4.62–12.7)

5561

0.001

PLR

184 (130–270)

126 (95.4–162)

4094

<0.001

NLR

3.02 (1.76–4.71)

1.69 (1.32–2.42)

4632

<0.001

LMR

2.53 (1.82–3.65)

3.32 (2.48–4.35)

9192

0.001

SII

1672 (1098–3001)

1717 (1086–2826)

7252

0.733

PIV

997 (540–2122)

1021 (589–2210)

7767

0.553

SIRI

1.54 (0.94–3.27)

1.05 (0.73–1.96)

5680

0.001

PNI

43.8 (41.5–47.3)

51.5 (47.2–54.3)

11961.5

<0.001

CRC – colorectal cancer; BMI – body mass index; CEA – carcinoembryonic antigen; WBC – white blood cells; NLR – neutrophil-to-lymphocyte ratio; LMR – lymphocyte-to-monocyte ratio; PLR – platelet-to-lymphocyte ratio; SII – systemic immune-inflammation index; PNI – prognostic nutritional index; PIV – pan-immune-inflammation value; SIRI – systemic inflammation response index; * data were compared using Student’s t-test; # data were compared using the χ2 test; the other parameters were compared using the Mann–Whitney U test. AGR – albumin-to-globulin ratio.
Table 2. Risk factors related to anastomotic leakage (AL) for patients who underwent colorectal cancer (CRC) surgery

Clinical variables

Non-AL (n = 100)

AL (n = 24)

χ2/t/Z-value

p-value

Sex

male

53 (53.0%)

8 (33.3%)

2.260

0.133#

female

47 (47.0%)

16 (66.7%)

Age

64.7 ±12.9

58.5 ±13.7

2.031

0.050*

Cancer type

colon cancer

67 (67.0%)

11 (45.8%)

2.864

0.091#

rectal cancer

33 (33.0%)

13 (54.2%)

Tumor location

right side

31 (31.0%)

3 (12.5%)

4.508

0.105#

left side

35 (35.0%)

8 (33.3%)

rectal

34 (34.0%)

13 (54.2%)

Tumor grade

high

8 (8%)

3 (12.5%)

0.790

0.674#

middle

79 (79%)

19 (79.2%)

low

13 (13%)

2 (8.3%)

Surgery type

laparoscope

77 (77.0%)

13 (54.2%)

3.988

0.046#

open

23 (23.0%)

11 (45.8%)

Operation time

180 (159–235)

235 (175–286)

911.5

0.068

Intraoperative bleeding

50.0 (20.0–100)

50.0 (20.0–200)

954.0

0.113

T stage

T1

3 (3.00%)

0 (0.00%)

3.341

0.359#

T2

12 (12.0%)

4 (16.7%)

T3

31 (31.0%)

11 (45.8%)

T4

54 (54.0%)

9 (37.5%)

N stage

N0

45 (45.0%)

12 (50.0%)

0.947

0.977#

N1

32 (32.0%)

8 (33.3%)

N2

20 (20.0%)

4 (16.7%)

NX

3 (3.00%)

0 (0.00%)

M stage

M0

68 (68.0%)

22 (91.7%)

6.117

0.038#

M1

16 (16.0%)

2 (8.33%)

MX

16 (16.0%)

0 (0.00%)

Tumor stage

I

13 (13.0%)

2 (8.33%)

2.356

0.607#

II

30 (30.0%)

11 (45.8%)

III

44 (44.0%)

9 (37.5%)

IV

13 (13.0%)

2 (8.33%)

BMI

21.8 (19.6–24.0)

24.4 (20.6–26.4)

1579.5

0.057

WBC

7.10 (5.97–8.53)

6.10 (5.02–6.85)

1243.5

0.016

Hemoglobin

113 ±24.6

114 ±32.6

0.150

0.882*

Platelet

282 (220–348)

290 (259–374)

1546

0.333

Neutrophil

4.50 (3.53–6.12)

3.34 (2.50–4.90)

1296

0.029

Lymphocyte

1.60 (1.05–1.95)

1.50 (1.24–1.80)

1402.5

0.544

Monocyte

0.57 (0.44–0.80)

0.50 (0.40–0.64)

1166.5

0.199

Fibrinogen

4.12 (3.45–4.65)

4.02 (3.50–5.17)

1570.5

0.832

Albumin

37.1 (33.9–39.7)

35.9 (33.2–37.1)

995.5

0.019

Globulin

26.7 (24.7–29.5)

28.4 (25.4–32.1)

1379.5

0.196

AGR

1.36 (1.24–1.50)

1.31 (1.16–1.45)

1072.5

0.256

Total protein

63.5 (60.0–68.2)

65.6 (60.2–68.6)

1328.5

0.420

Prealbumin

185 ±51.8

171 ±55.1

1.081

0.287*

Ferritin

144 (35.6–277)

70.6 (16.9–193)

1316

0.124

CEA

4.93 (2.30–12.3)

3.40 (2.00–16.7)

1496.5

0.463

AFP

2.50 (1.83–3.11)

2.01 (1.58–2.52)

1269

0.061

CA125

10.8 (7.59–18.7)

9.13 (6.91–27.8)

1551

0.663

CA153

11.4 (7.28–17.0)

8.36 (4.74–12.9)

1320.5

0.026

CA199

12.0 (6.92–26.6)

9.75 (6.70–15.9)

1250

0.446

PLR

179 (128–271)

198 (146–268)

1043

0.321

NLR

3.12 (1.79–4.53)

2.03 (1.58–4.74)

1356

0.324

LMR

2.46 (1.61–3.70)

2.84 (2.31–3.60)

1077.5

0.438

SII

1944 (1121–3097)

1432 (1080–1957)

1404

0.197

PIV

1077 (546–2383)

710 (481–1058)

1446

0.120

SIRI

1.69 (0.97–3.27)

1.12 (0.76–2.07)

1463

0.096

PNI

43.9 (41.7–48.6)

41.4 (40.8–44.5)

1491

0.007

BMI – body mass index; WBC – white blood cells; CEA – carcinoembryonic antigen; NLR – neutrophil-to-lymphocyte ratio; LMR – lymphocyte-to-monocyte ratio; PLR – platelet-to-lymphocyte ratio; SII – systemic immune-inflammation index; PNI – prognostic nutritional index; PIV – pan-immune-inflammation value; SIRI – systemic inflammation response index; * data were compared using Student’s t-test; # data were compared using the χ2 test; other parameters were compared using the Mann–Whitney U test. The values in bold indicated statistically significant change.

Figures


Fig. 1. Predictive value of albumin, carcinoembryonic antigen (CEA), CA153, and prognostic nutritional index (PNI) on anastomotic leakage (AL) in colorectal cancer (CRC) patients after surgery
ROC – receiver operating characteristic; AUC – area under the curve.
Fig. 2. Survival analysis of the blood biomarkers and anastomotic leakage (AL) in colorectal cancer (CRC) patients. A. Carcinoembryonic antigen (CEA); B. Systemic immune-inflammation index (SII); C. Pan-immune-inflammation value (PIV); D. Systemic inflammation response index (SIRI); E. Prognostic nutritional index (PNI); F. AL
Fig. 3. Association of prognostic nutritional index (PNI) with clinicopathological features in colorectal cancer (CRC). Data were compared using the Mann–Whitney U test. The whiskers extend from the box to the minimum and maximum values of the dataset, excluding any outliers. Outliers are data points that fall more than 1.5 times of the interquartile range (IQR) beyond the nearest quartile. They are represented by individual points outside the whiskers
Fig. 4. Comparison of the prognostic value of clinicopathological features for colorectal cancer (CRC) patients. A. Nomogram; B. Calibration curve
SII – systemic immune-inflammation index; PNI – prognostic nutritional index; PIV – pan-immune-inflammation value; SIRI – systemic inflammation response index; OS – overall survival.

References (30)

  1. Foppa C, Ng SC, Montorsi M, Spinelli A. Anastomotic leak in colorectal cancer patients: New insights and perspectives. Eur J Surg Oncol. 2020;46(6):943–954. doi:10.1016/j.ejso.2020.02.027
  2. Hoek VT, Buettner S, Sparreboom CL, et al. A preoperative prediction model for anastomotic leakage after rectal cancer resection based on 13,175 patients. Eur J Surg Oncol. 2022;48(12):2495–2501. doi:10.1016/j.ejso.2022.06.016
  3. Chiarello MM, Fransvea P, Cariati M, Adams NJ, Bianchi V, Brisinda G. Anastomotic leakage in colorectal cancer surgery. Surg Oncol. 2022;40:101708. doi:10.1016/j.suronc.2022.101708
  4. Ishizuka M, Shibuya N, Takagi K, et al. Impact of anastomotic leakage on postoperative survival of patients with colorectal cancer: A meta-analysis using propensity score matching studies. Surg Oncol. 2021;37:101538. doi:10.1016/j.suronc.2021.101538
  5. González-Valverde FM, Vicente-Ruiz M, Gómez-Ramos MJ. Risk factors of anastomotic leakage in colon cancer. Cir Cir. 2019;87(3):347–352. doi:10.24875/CIRU.18000616
  6. Klein M, Gogenur I, Rosenberg J. Postoperative use of non-steroidal anti-inflammatory drugs in patients with anastomotic leakage requiring reoperation after colorectal resection: Cohort study based on prospective data. BMJ. 2012;345:e6166. doi:10.1136/bmj.e6166
  7. Vasiliu ECZ, Zarnescu NO, Costea R, Neagu S. Review of risk factors for anastomotic leakage in colorectal surgery. Chirurgia (Bucur). 2015;110(4):319–326. PMID:26305194.
  8. Yamano T, Yoshimura M, Kobayashi M, et al. Malnutrition in rectal cancer patients receiving preoperative chemoradiotherapy is common and associated with treatment tolerability and anastomotic leakage. Int J Colorectal Dis. 2016;31(4):877–884. doi:10.1007/s00384-016-2507-8
  9. Wu CX, Rao DY, Sang CP, et al. Peripheral blood inflammation indices are effective predictors of anastomotic leakage in elective esophageal surgery. J Gastrointest Oncol. 2021;12(6):2675–2684. doi:10.21037/jgo-21-812
  10. Mauser M, Bartsokas C, Brand M, Plani F. Postoperative CD4 counts predict anastomotic leaks in patients with penetrating abdominal trauma. Injury. 2019;50(1):167–172. doi:10.1016/j.injury.2018.11.028
  11. Paliogiannis P, Deidda S, Maslyankov S, et al. Blood cell count indexes as predictors of anastomotic leakage in elective colorectal surgery: A multicenter study on 1432 patients. World J Surg Oncol. 2020;18(1):89. doi:10.1186/s12957-020-01856-1
  12. Yilmaz H, Yersal Ö. Prognostic significance of novel inflammatory markers in extensive-stage small-cell lung cancer. J Can Res Ther. 2022;18(3):691–696. doi:10.4103/jcrt.jcrt_1937_21
  13. Lin F, Zhang LP, Xie SY, et al. Pan-immune-inflammation value: A new prognostic index in operative breast cancer. Front Oncol. 2022;12:830138. doi:10.3389/fonc.2022.830138
  14. Feng Y, Zhang N, Wang S, et al. Systemic inflammation response index is a predictor of poor survival in locally advanced nasopharyngeal carcinoma: A propensity score matching study. Front Oncol. 2020;10:575417. doi:10.3389/fonc.2020.575417
  15. Özkan U, Gürdoğan M, Öztürk C, et al. Systemic immune-inflammation index: A novel predictor of coronary thrombus burden in patients with non-ST acute coronary syndrome. Medicina (Kaunas). 2022;58(2):143. doi:10.3390/medicina58020143
  16. Zeng R, Liu F, Fang C, et al. PIV and PILE score at baseline predict clinical outcome of Anti-PD-1/PD-L1 inhibitor combined with chemotherapy in extensive-stage small cell lung cancer patients. Front Immunol. 2021;12:724443. doi:10.3389/fimmu.2021.724443
  17. Chen L, Bai P, Kong X, et al. Prognostic nutritional index (PNI) in patients with breast cancer treated with neoadjuvant chemotherapy as a useful prognostic indicator. Front Cell Dev Biol. 2021;9:656741. doi:10.3389/fcell.2021.656741
  18. Rahbari NN, Weitz J, Hohenberger W, et al. Definition and grading of anastomotic leakage following anterior resection of the rectum: A proposal by the International Study Group of Rectal Cancer. Surgery. 2010;147(3):339–351. doi:10.1016/j.surg.2009.10.012
  19. Polk N, Budai B, Hitre E, Patócs A, Mersich T. High neutrophil-to-lymphocyte ratio (NLR) and systemic immune-inflammation index (SII) are markers of longer survival after metastasectomy of patients with liver-only metastasis of rectal cancer. Pathol Oncol Res. 2022;28:1610315. doi:10.3389/pore.2022.1610315
  20. Pérez-Martelo M, González-García A, Vidal-Ínsua Y, et al. Clinical significance of baseline pan-immune-inflammation value and its dynamics in metastatic colorectal cancer patients under first-line chemotherapy. Sci Rep. 2022;12(1):6893. doi:10.1038/s41598-022-10884-8
  21. Yatabe S, Eto K, Haruki K, et al. Signification of systemic immune-inflammation index for prediction of prognosis after resecting in patients with colorectal cancer. Int J Colorectal Dis. 2020;35(8):1549–1555. doi:10.1007/s00384-020-03615-w
  22. Takamizawa Y, Shida D, Boku N, et al. Nutritional and inflammatory measures predict survival of patients with stage IV colorectal cancer. BMC Cancer. 2020;20(1):1092. doi:10.1186/s12885-020-07560-3
  23. Johannet P, Sawyers A, Qian Y, et al. Baseline prognostic nutritional index and changes in pretreatment body mass index associate with immunotherapy response in patients with advanced cancer. J Immunother Cancer. 2020;8(2):e001674. doi:10.1136/jitc-2020-001674
  24. Wang X, Cheng G, Tao R, et al. Clinical characteristics and predictors of permanent stoma in rectal cancer patients underwent anterior resections: The value of preoperative prognostic nutritional index. Int J Clin Oncol. 2020;25(11):1960–1968. doi:10.1007/s10147-020-01743-5
  25. Lai GHA, Deng HY, Song TN, et al. Preoperative prognostic nutritional index shows no significant prognostic value for short-term outcomes of anastomosis-leakage patients after cancerous esophagectomy. Ann Palliat Med. 2019;8(5):698–707. doi:10.21037/apm.2019.11.08
  26. Shimakawa T, Asaka S, Sagawa M, et al. Nutritional screening before surgery for esophageal cancer: Current status and evaluation results [in Japanese]. Gan To Kagaku Ryoho. 2014;41(10):1301–1303. PMID:25335724.
  27. Bailón-Cuadrado M, Pérez-Saborido B, Sánchez-González J, et al. Prognostic nutritional index predicts morbidity after curative surgery for colorectal cancer. Cir Esp (Engl Ed). 2019;97(2):71–80. doi:10.1016/j.ciresp.2018.08.015
  28. Tamai M, Kiuchi J, Kuriu Y, et al. Clinical impact of postoperative prognostic nutritional index in colorectal cancer patients undergoing adjuvant chemotherapy. Am J Cancer Res. 2021;11(10):4947–4955. PMID:34765302.
  29. Kang J, Yang G, Wang D, Lin Y, Wang Q, Luo H. The clinical application value of the prognostic nutritional index for the overall survival prognosis of patients with esophageal cancer: A robust real-world observational study in China. Comput Math Methods Med. 2022;2022:3889588. doi:10.1155/2022/3889588
  30. Xie H, Wei L, Yuan G, Liu M, Tang S, Gan J. Prognostic value of prognostic nutritional index in patients with colorectal cancer undergoing surgical treatment. Front Nutr. 2022;9:794489. doi:10.3389/fnut.2022.794489