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Article

Preoperative Cancer Inflammation Prognostic Index as a Superior Predictor of Short- and Long-Term Outcomes in Patients with Stage I–III Colorectal Cancer after Curative Surgery

by
Jeng-Fu You
1,
Yu-Jen Hsu
1,
Yih-Jong Chern
1,
Ching-Chung Cheng
1,
Bor-Kang Jong
1,
Chun-Kai Liao
1,
Pao-Shiu Hsieh
1,
Hung-Chih Hsu
2 and
Wen-Sy Tsai
1,*
1
Division of Colon and Rectal Surgery, Department of Surgery, Chang Gung Memorial Hospital at Linkou, College of Medicine, Chang Gung University, Taoyuan 33305, Taiwan
2
Division of Hematology-Oncology, Chang Gung Memorial Hospital at Linkou, College of Medicine, Chang Gung University, Taoyuan 33305, Taiwan
*
Author to whom correspondence should be addressed.
Cancers 2022, 14(24), 6232; https://doi.org/10.3390/cancers14246232
Submission received: 14 November 2022 / Revised: 13 December 2022 / Accepted: 14 December 2022 / Published: 17 December 2022
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Abstract

:

Simple Summary

Inflammatory reactions may lead to systemic inflammation and cancer growth. Some inflammatory indicators are effective predictors of colorectal cancer in ordinary clinical practice. The objective of this study is to evaluate the utility of a novel cancer-inflammation prognostic index (CIPI) marker derived from multiplying carcinoembryonic antigen by the neutrophil-to-lymphocyte ratio value obtained for non-metastatic colorectal cancer. Patients who underwent radical resection for stage I to stage III primary colorectal cancer between January 1995 and December 2018 were included in this study for further investigation. The group with a high CIPI had considerably lower relapse-free survival and overall survival rates, as well as a greater incidence of recurrence. Both univariate and multivariate analyses found that a high CIPI was an independent prognostic factor for survival analysis. This research is the first to demonstrate that CIPI is an independent factor that can be used to predict the outcome of colorectal cancer.

Abstract

Inflammatory reactions play a crucial role in cancer progression and may contribute to systemic inflammation. In routine clinical practice, some inflammatory biomarkers can be utilized as valuable predictors for colorectal cancer (CRC). This study aims to determine the usefulness of a novel cancer-inflammation prognostic index (CIPI) marker derived from calculating carcinoembryonic antigen (CEA) multiplied by the neutrophil-to-lymphocyte ratio (NLR) values established for non-metastatic CRCs. Between January 1995 and December 2018, 12,092 patients were diagnosed with stage I to III primary CRC and had radical resection—they were all included in this study for further investigation. There were 5996 (49.6%) patients in the low-CIPI group and 6096 (50.4%) patients in the high-CIPI group according to the cutoff value of 8. For long-term outcomes, the high-CIPI group had a significantly higher incidence of recurrence (30.6% vs. 16.0%, p < 0.001) and worse relapse-free survival (RFS) and overall survival (OS) rates (p < 0.001). High CIPI was an independent prognostic factor for RFS and OS in univariate and multivariate analyses. This research is the first to document the independent significance of CIPI as a prognostic factor for CRC. To ensure that it works, this CIPI needs to be tested on more CRC prediction models.

1. Introduction

The tumor microenvironment is complex, containing cells with various properties; inflammatory cells are considered, generally, critical to the tumor microenvironment [1,2]. Inflammatory responses play an essential role in cancer evolution and progression and are possibly involved in systemic inflammation [3,4]. There is growing evidence that inflammatory markers are closely related to poor prognosis in colorectal cancer (CRC) [5,6,7,8]. One well-known marker of systemic inflammation is serum C-reactive protein (CRP) level [9,10]. Several studies have elucidated that high-CRP levels are associated with poorer survival in CRC patients and could be used as a prognostic biomarker [11,12,13,14,15]. In addition, combinations of parameters have been widely utilized to predict CRC outcomes, including neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), lymphocyte-to-monocyte ratio (LMR), Glasgow prognostic score (GPS), prognostic nutritional index (PNI), and geriatric nutritional risk index (GNRI). These biomarkers can be used as valuable predictors in daily clinical work [16].
Carcinoembryonic antigen (CEA) is a glycoprotein and is currently the most widely implemented tumor marker in CRC patients. The primary role of this tumor marker is to detect recurrence as early as possible during follow-up visits after curative surgery for CRC [17,18,19]. The sensitivity of serum values of CEA at diagnosis is usually low because serum CEA levels can be within the normal range in patients with CRC. Several studies have analyzed the association between high preoperative serum levels of CEA and poorer prognosis [20,21,22]. Evidence suggests that patients with elevated serum levels of preoperative CEA may have a higher recurrence rate than patients with normal levels prior to the operation [23,24,25].
A new prognostic index, defined as the cancer-inflammation prognostic index (CIPI), based on CEA and NLR, was recently introduced as a promising novel prognostic marker for metastatic CRC patients treated with regorafenib [26,27]. To our knowledge, CIPI has never been utilized as a prognostic marker in non-metastatic CRC after curative resection. In theory, predicting prognosis after radical surgery for CRC involves evaluation of the interaction between patient- and tumor-related factors. Thus, it is reasonable to suggest the use of CIPI as a simultaneous surrogate for tumor- and immune-related markers. Therefore, in the present study, we investigate the prognostic significance of CIPI in patients with non-metastatic CRC after curative surgery.
This study was designed to explore the value of a novel marker, CIPI, by calculating CEA multiplied by NLR values developed for non-metastatic CRCs. To our knowledge, no previous analysis has assessed the significance of CIPI in non-metastatic CRC after curative resection. Therefore, we examine the prognostic value of CIPI to indicate recurrence risk and survival outcomes in patients with stage I–III CRC after radical resection in a real-world dataset.

2. Materials and Methods

2.1. Data Collection and Study Design

This retrospective study examined the records of a database from the Colorectal Section Tumor Registry of Chang Gung Memorial Hospital. The institutional review board approved this study (IRB No. 201601428B0).
The inclusion criteria were as follows: histologically confirmed colorectal adenocarcinoma and complete clinical, laboratory, imaging, and follow-up data. The exclusion criteria included: emergency operation, non-curative resection, and missing CEA or NLR data.
Database variables included age, sex, body mass index (BMI), underlying disease, preoperative routine serological test, and tumor-related variables. We collected laboratory data within one week prior to patients undergoing surgery. According to the 8th edition of Cancer Staging, all patients in this study were staged.

2.2. Cancer-Inflammation Prognostic Index (CIPI)

CIPI is calculated as CEA (mg/L) × NLR, where NLR denotes the neutrophil-to-lymphocyte counts ratio. The receiver operating characteristic (ROC) curve was used to assess the ability of CIPI to classify disease status. The optimal cutoff value of CIPI for tumor recurrence was determined by ROC curve analysis according to the Youden index.

2.3. Measurement Outcomes

Measurement outcomes included short-term postoperative complications and long-term survival. Postoperative complications were defined as complications that occurred within 30 days of surgery. Postoperative mortality was defined as death that occurred within 30 days of surgery. Long-term outcomes were evaluated using relapse-free survival (RFS) and overall survival (OS). The first recurrence was defined as the first date when local recurrence or distant metastases were confirmed by histology of biopsy specimens, additional surgery, or radiological studies. RFS was defined as the interval between cancer resection and the first recurrence, death, or the final follow-up date. OS was defined as the interval between cancer resection and death or the date of the last follow-up.

2.4. Statistics

All analyses were conducted using SPSS Statistics, version 24.0 (IBM Corp, Armonk, NY, USA). Clinicopathological characteristics with categorical variables were presented as frequencies and proportions and were compared using the chi-squared test. Continuous variables were expressed as means and standard deviations and were analyzed using the Student t-test. RFS, OS, and time-to-event probabilities were determined and plotted using the Kaplan–Meier method. Differences were estimated using the log-rank test. Univariate and multivariate analyses of independent factors for RFS and OS were performed using the Cox proportional hazards regression analysis. We incorporated all variables with p < 0.05 from the univariate regression analysis into a multivariate Cox proportional hazards regression model to investigate the explanatory variables further. A p-value < 0.05 was considered statistically significant.

3. Results

Between January 1995 and December 2018, 13,954 patients with stage I to III primary CRC who had received radical resection were included in the study. Of these 13,954 patients, 104, 382, and 1376 were excluded because they had a non-curative resection, missing CEA data, and missing NLR data, respectively. The remaining 12,092 patients were included.

3.1. The CIPI Cutoff Level

The ROC curve that demarcates the predictivity of CIPI and five-year RFS is illustrated for the whole cohort of patients. As shown in Figure 1a, the area under the curve (AUC) was 0.658 (95% CI: 0.648–0.669; p = 0.001). Estimation using the Youden index showed that the recommended cutoff value of preoperative CIPI for evaluating five-year RFS was 8.351, with a sensitivity of 0.659 and a specificity of 0.585. To simplify grouping and application, we determined a recommended cutoff value of 8.0 for CIPI, with a sensitivity of 0.67 and a specificity of 0.569 for further study.
The CIPI value of all patients ranged from 0.3 to 10,909.4, with a mean value of 43.2 ± 224.5 and a median value of 8.1. The mean and 5% trimmed values of CIPI were 75.4 and 32.4, respectively, for patients with recurrence or mortality within five years; these values were 29.1 and 12.5 for those without recurrence or mortality within five years. The median CIPI value for patients with recurrence or mortality within five years was 13.7; this value was 6.5 for those without recurrence or mortality within five years (Figure 1b).

3.2. CIPI and Clinicopathological Features

There were 5996 (49.6%) patients in the low-CIPI group and 6096 (50.4%) patients in the high-CIPI group. Table 1 shows the relationships between CIPI and clinicopathological characteristics.
For the baseline clinical data, patients with high-CIPI were usually older (64.94 ± 13.12 vs. 62.10 ± 12.67 years, p < 0.001), more likely male (58.7% vs. 54.5%, p < 0.001), and had a lower BMI (<25 kg/m2: 67.4% vs. 59.3%, p < 0.001). For underlying medical illnesses, the high-CIPI group had a higher proportion of diabetes mellitus (18.9% vs. 14.1%, p < 0.001) and chronic renal disease (9.8% vs. 4.8%, p < 0.001) than the low-CIPI group. However, patients with a history of hepatitis had lower CIPI levels (4.3% vs. 5.4%, p = 0.006).
Regarding tumor-related characteristics, there was no significant difference between the high- and low-CIPI groups in terms of tumor location. However, the high-CIPI group had a more advanced tumor stage (p < 0.001), including T stage (p < 0.001), N stage (p < 0.001), histologic type (p < 0.001) and histologic differentiation (p < 0.001). CIPI was also associated with obstruction (p < 0.001), perforation (p < 0.001), and preoperative laboratory values, including hemoglobin (p < 0.001) and albumin (p < 0.001) levels.

3.3. CIPI and Short- and Long-Term Outcomes

Details of the association between CIPI and short- and long-term outcomes are presented in Table 2. For short-term outcomes, the preoperative high-CIPI group had a higher postoperative 30-day morbidity and mortality than the low-CIPI group, both p < 0.001.
For long-term outcomes, the high-CIPI group had a significantly higher incidence of recurrence (30.6% vs. 16.0%, p < 0.001) and worse RFS and OS (p < 0.001). The three-year, five-year, and 10-year RFS rates were 81.5%, 77.3%, and 68.2%, respectively, in the low-CIPI group and 61.8%, 56.2%, and 45.5%, respectively, in the high-CIPI group (p < 0.001). Similarly, OS followed the same trend of worse survival rates in the high-CIPI group compared to the low-CIPI group considering three-year, five-year, and 10-year survival.

3.4. CIPI and Survival Analyses According to Tumor Stage

In all patients with TNM stage I to III CRC, the high-CIPI group had lower RFS and OS rates than the low-CIPI group (p < 0.001), as displayed in Figure 2. These patients were divided into three subgroups according to their TNM stage: stage I (n = 2527), stage II (n = 4471), and stage III (n = 5094).
In TNM stage I patients, the estimated 10-year RFS rates of the low-CIPI and high-CIPI groups were 79.9% and 56.6%, respectively (p < 0.001). In the TNM stage II group, the estimated 10-year RFS rates of the low-CIPI and high-CIPI groups were 68.1% and 51.8%, respectively (p < 0.001). In the stage III group, the estimated 10-year RFS rates of the low-CIPI and high-CIPI groups were 58.3% and 37.6%, respectively (p < 0.001). The results of the OS analyses of each TNM stage are also presented in Figure 2. Patients in the high-CIPI group had lower OS at each tumor stage than those in the low-CIPI group (p < 0.001).

3.5. Univariate and Multivariate Analysis of RFS and OS

Detailed univariate and multivariate analysis results for RFS are listed in Table 3.
For the univariate analysis, age, gender, BMI, hypertension, cardiovascular disease, diabetes mellitus, hepatitis, chronic renal disease, tumor location, TNM stage, pT status, pN status, histologic type, histologic grade, obstruction, perforation, hemoglobin level, albumin level, and CIPI were significantly associated with RFS.
The multivariate analysis showed that age ≥ 65 years (HR: 1.59, p < 0.001), male sex (HR: 1.252, p < 0.001), hypertension (HR: 1.131, p < 0.001), cardiovascular disease (HR: 1.26, p < 0.001), diabetes mellitus (HR: 1.147, p = 0.001), chronic renal disease (HR: 1.447, p < 0.001), rectum (HR: 1.493, p < 0.001), pT2 (HR: 1.45, p < 0.001), pT3 (HR: 1.841, p < 0.001), pT4 (HR: 2.542, p < 0.001), pN1 (HR: 1.46, p < 0.001), pN2 (HR: 2.421, p < 0.001), signet ring cell adenocarcinoma (HR: 1.452, p = 0.016), obstruction (HR: 1.276, p < 0.001), hemoglobin ≥ 10 g/dL (HR: 0.873, p < 0.001), albumin ≥ 3.5 g/dL (HR: 0.658, p < 0.001), and CIPI ≥ 8 (HR: 1.478, p < 0.001) were independent prognostic factors for RFS.
The specific univariate and multivariate analysis results of OS are presented in Table 4, showing a considerable similarity with RFS.

3.6. Subgroup Analyses of Survival Based on CIPI

Figure 3 illustrates the subgroup analysis to investigate whether the effect of clinicopathological variables on survival changed according to CIPI level. Patients in the high-CIPI group invariably had poorer RFS and OS than those in the low-CIPI group, except those with signet ring cell adenocarcinoma (RFS: HR 1.749, CI 0.948–3.224, p = 0.074; OS: HR 1.714, CI 0.928–3.166, p = 0.085). When stratified by pathological stage, HR values of the high-CIPI group for RFS and OS were higher in stage I than in stages II and III compared to the low-CIPI group.

4. Discussion

To the best of our knowledge, this is the first study to demonstrate an association between CIPI and the prognosis of non-metastatic CRC following curative resection. Our data suggest that the CIPI is a promising new prediction tool for CRC patients following curative resection based on CEA and NLR. The predictive value of CIPI is significant across all tumor stages and outperformed other serum marker indicators in predicting tumor recurrence and survival outcomes. In particular, CIPI is more significant for predicting the recurrence and survival outcome, especially in stage I colorectal cancer after surgery. Theoretically, determining the prognosis of CRC after radical surgery necessitates the examination of factors related to the patient and the tumor. CIPI serves as a kind of approximation for tumor- and immune-related indicators.
CEA is a member of the immunoglobulin supergene family expressed in normal mucosa cells with the biological function of cell recognition or adhesion mechanisms [28]. An animal study of CEA knockdown in mice reported a 50% decrease in metastatic ability, which indicated its influence on metastatic progression [29]. The elevation of serum CEA itself may also cause pro-inflammatory cytokines and induce adhesion molecules (E-selectin, ICAM-I, and VCAM), thus leading to the metastasis of CRC [30]. CEA is a helpful tumor marker in colorectal cancer. Its increase has been linked to a worse prognosis for CRC [31,32,33]. However, the optimal cutoff level of CEA elevation applied to predict recurrence is inconsistent under different conditions, and even some benign conditions influence its elevation. Generally, a cutoff level of 5 ng/mL is used to define CEA elevation. However, a preoperative CEA of 10 ng/mL has been advanced as the optimal level for assessing recurrence risk in CRC patients with stage II and III, but not stage I, according to a study of 638 stage I–III CRC patients after curative surgery [34]. Other studies suggest that optimal levels of high risk for recurrence include 6 ng/mL in stage IIA CRC patients who underwent colectomy surgery [35] and 2.5 ng/mL in stage I–III rectal cancer patients who underwent both chemoradiotherapy and surgery [36].
CEA elevation was also found in non-malignant conditions such as cirrhosis, ulcerative colitis, chronic renal failure, hypothyroidism, pancreatitis, and chronic lung disease [37,38,39,40]. Other metabolic and lifestyle factors, such as age, fasting glucose, cigarette smoking, and alcohol consumption, were also found to be associated with CEA elevation [41]. Although the level of CEA elevation engendered by benign factors has rarely reached over 10 ng/mL, a level of below 10, especially 5–10 ng/mL, has some limitations for predicting recurrence.
Inflammation and infection are other biological markers with a negative impact on prognosis. Chronic inflammation increases the risk of developing cancer and is inextricably linked to the immune system [42]. Inflammation and cancer use similar mechanisms; the microenvironment contributes to proliferation and survival of malignant cells, angiogenesis, metastasis, inhibition of adaptive immunity, response to hormones, and chemotherapeutic agents [43]. Neutrophils, lymphocytes, monocytes, and platelets are cellular components of systemic inflammation. Previous research has found that lymphocytes have a significant role in cancer immune surveillance, inhibiting the proliferation of tumor cells, restraining metastasis through cytokine production, and inducing cytotoxic cell death [44]. However, neutrophils, the first recruited effectors of the acute inflammatory response, may inhibit the immune system by suppressing the cytolytic activity of immune cells such as lymphocytes, activated T cells, and natural killer cells. They may also produce proangiogenic factors such as vascular endothelial growth factors, proteases, and chemokines and enhance the adhesion of circulating tumor cells in distant sites [45].
Two different types of scores have been proposed to track the systemic inflammatory response: those based on protein measurement and those based on inflammatory cell counting. Patients with CRC can have their condition predicted by counting these differentiated cells individually or collectively [46,47,48,49,50]. Studies evaluating the relationship between NLR and various cancers have shown that it was a strong prognostic factor [51,52]. In colorectal cancer, elevated NLR was associated with worse outcomes, and it has also been extensively discussed with worse prognosis in multiple treatment subgroups [53,54,55]. In our institution, the predictive value of NLR for CRC was published. According to our data, a high NLR was linked to a higher risk of RFS in colon cancer, but a multivariate analysis showed that it was less crucial in rectal cancer [56,57]. The subgroup analysis of this study revealed that patients in the high-CIPI group invariably had worse RFS and OS than those in the low-CIPI group, except for individuals with signet ring cell adenocarcinoma. Our data indicate that a high CIPI exhibited poor outcomes in both colon and rectal cancer, whereas a high NLR was not associated with poor outcomes in rectal cancer. From our data, CEA plus the inflammation index was found to predict tumor recurrence better than CEA or the inflammation index alone. Combining CEA and NLR may result in more valuable and extensive therapeutic applications for various colorectal cancer prognosis predictions.
This study has several limitations. First, the retrospective design of this study may increase the risk of bias. Second, CIPI values may be missing; for example, in the case of emergency surgery, there may be no CEA data prior to surgery. Third, presence of underlying illness may significantly impact the CIPI value, especially when the body is in an inflammatory state. Fourth, CIPI values are not a fixed, absolute value—in other words, even if the blood test is repeated at a comparable time, the CIPI values may be close but not the same, which will inevitably cause bias. Therefore, it might be reasonable to assume that using a trajectory trend of CIPI values would be more practical than a single-point value.

5. Conclusions

In conclusion, the results of the present study suggest that CIPI can function as an effective and easy-to-use clinical tool for patients with non-metastatic CRC after curative resection. This investigation is the first report to reveal that CIPI is an independent significant prognostic factor for resected CRC. Further studies applying CIPI to various prognostic models of CRC are required to ensure its usefulness.

Author Contributions

J.-F.Y. and W.-S.T. made a substantial contribution to the study’s conception and design. Y.-J.C. and Y.-J.H. assisted in the analysis and interpretation of data. J.-F.Y., Y.-J.C., Y.-J.H. and W.-S.T. participated in drafting the article. B.-K.J., C.-K.L., P.-S.H., C.-C.C. and H.-C.H. contributed to data acquisition and revised the manuscript critically for important intellectual content. All authors have read and agreed to the published version of the manuscript.

Funding

This research received no external funding.

Institutional Review Board Statement

Ethical standards were respected in compliance with the 2013 updated Helsinki Declaration. Institutional review board of Chang Gung Memorial Hospital approval was obtained. (IRB No.201601428B0).

Informed Consent Statement

Informed consent was obtained from patients participating in the present study.

Data Availability Statement

Due to privacy and ethical concerns, data details and how to request access are available from the corresponding author.

Conflicts of Interest

The authors have no conflict of interest.

References

  1. Iyengar, N.M.; Gucalp, A.; Dannenberg, A.J.; Hudis, C.A. Obesity and Cancer Mechanisms: Tumor Microenvironment and Inflammation. J. Clin. Oncol. 2016, 34, 4270–4276. [Google Scholar] [CrossRef] [PubMed]
  2. Balkwill, F.; Charles, K.A.; Mantovani, A. Smoldering and polarized inflammation in the initiation and promotion of malignant disease. Cancer Cell 2005, 7, 211–217. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  3. Murata, M. Inflammation and cancer. Environ. Health Prev Med. 2018, 23, 50. [Google Scholar] [CrossRef] [Green Version]
  4. Singh, N.; Baby, D.; Rajguru, J.P.; Patil, P.B.; Thakkannavar, S.S.; Pujari, V.B. Inflammation and cancer. Ann. Afr. Med. 2019, 18, 121–126. [Google Scholar] [CrossRef]
  5. Lucas, C.; Barnich, N.; Nguyen, H.T.T. Microbiota, Inflammation and Colorectal Cancer. Int. J. Mol. Sci. 2017, 18, 1310. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  6. Tuomisto, A.E.; Mäkinen, M.J.; Väyrynen, J.P. Systemic inflammation in colorectal cancer: Underlying factors, effects, and prognostic significance. World J. Gastroenterol. 2019, 25, 4383–4404. [Google Scholar] [CrossRef] [PubMed]
  7. Lichtenstern, C.R.; Ngu, R.K.; Shalapour, S.; Karin, M. Immunotherapy, Inflammation and Colorectal Cancer. Cells 2020, 9, 618. [Google Scholar] [CrossRef] [Green Version]
  8. Yamamoto, T.; Kawada, K.; Obama, K. Inflammation-Related Biomarkers for the Prediction of Prognosis in Colorectal Cancer Patients. Int. J. Mol. Sci. 2021, 22, 8002. [Google Scholar] [CrossRef]
  9. Moutachakkir, M.; Hanchi, A.L.; Baraou, A.; Boukhira, A.; Chellak, S. Immunoanalytical characteristics of C-reactive protein and high sensitivity C-reactive protein. Ann. Biol. Clin. 2017, 75, 225–229. [Google Scholar] [CrossRef]
  10. Sproston, N.R.; Ashworth, J.J. Role of C-Reactive Protein at Sites of Inflammation and Infection. Front. Immunol. 2018, 9, 754. [Google Scholar] [CrossRef]
  11. Pathak, S.; Nunes, Q.; Daniels, I.; Smart, N.J. Is C-reactive protein useful in prognostication for colorectal cancer? A systematic review. Colorectal Dis. 2014, 16, 769–776. [Google Scholar] [CrossRef] [PubMed]
  12. Casadei Gardini, A.; Carloni, S.; Scarpi, E.; Maltoni, P.; Dorizzi, R.M.; Passardi, A.; Frassineti, G.L.; Cortesi, P.; Giannini, M.B.; Marisi, G.; et al. Prognostic role of serum concentrations of high-sensitivity C-reactive protein in patients with metastatic colorectal cancer: Results from the ITACa trial. Oncotarget 2016, 7, 10193–10202. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  13. Fan, Y.; Xiang, S.; Dai, Z.; Zou, C.; Wang, X.; Gao, Z. Prognostic significance of C-reactive protein to albumin ratio in colorectal cancer patients: A meta-analysis. Int. J. Colorectal Dis. 2019, 34, 1105–1111. [Google Scholar] [CrossRef] [PubMed]
  14. Liao, C.-K.; Yu, Y.-L.; Lin, Y.-C.; Hsu, Y.-J.; Chern, Y.-J.; Chiang, J.-M.; You, J.-F. Prognostic value of the C-reactive protein to albumin ratio in colorectal cancer: An updated systematic review and meta-analysis. World J. Surg. Oncol. 2021, 19, 139. [Google Scholar] [CrossRef]
  15. Pan, Y.; Lou, Y.; Wang, L. Prognostic value of C-reactive protein to albumin ratio in metastatic colorectal cancer: A systematic review and meta-analysis. Medicine 2021, 100, e27783. [Google Scholar] [CrossRef]
  16. Mik, M.; Dziki, L.; Berut, M.; Trzcinski, R.; Dziki, A. Neutrophil to Lymphocyte Ratio and C-Reactive Protein as Two Predictive Tools of Anastomotic Leak in Colorectal Cancer Open Surgery. Dig. Surg. 2017, 35, 77–84. [Google Scholar] [CrossRef]
  17. Duffy, M.; Lamerz, R.; Haglund, C.; Nicolini, A.; Kalousova, M.; Holubec, L.; Sturgeon, C. Tumor markers in colorectal cancer, gastric cancer and gastrointestinal stromal cancers: European group on tumor markers 2014 guidelines update. Int. J. Cancer 2013, 134, 2513–2522. [Google Scholar] [CrossRef]
  18. Das, V.; Kalita, J.; Pal, M. Predictive and prognostic biomarkers in colorectal cancer: A systematic review of recent advances and challenges. Biomed. Pharmacother. 2017, 87, 8–19. [Google Scholar] [CrossRef]
  19. Campos-Da-Paz, M.; Dórea, J.G.; Galdino, A.S.; Lacava, Z.G.M.; Santos, M.D.F.M.A. Carcinoembryonic Antigen (CEA) and Hepatic Metastasis in Colorectal Cancer: Update on Biomarker for Clinical and Biotechnological Approaches. Recent Patents Biotechnol. 2018, 12, 269–279. [Google Scholar] [CrossRef]
  20. Kim, J.Y.; Kim, N.K.; Sohn, S.K.; Kim, Y.W.; Kim, K.J.S.; Hur, H.; Min, B.S.; Cho, C.H. Prognostic Value of Postoperative CEA Clearance in Rectal Cancer Patients with High Preoperative CEA Levels. Ann. Surg. Oncol. 2009, 16, 2771–2778. [Google Scholar] [CrossRef]
  21. Treska, V.; Topolcan, O.; Stanislav, K.; Liska, V.; Holubec, L. Preoperative tumor markers as prognostic factors of colorectal liver metastases. Hepatogastroenterology 2009, 56, 317–320. [Google Scholar]
  22. Nesteruk, D.; Rutkowski, A.; Fabisiewicz, S.; Pawlak, J.; Siedlecki, J.A.; Fabisiewicz, A. Evaluation of Prognostic Significance of Circulating Tumor Cells Detection in Rectal Cancer Patients Treated with Preoperative Radiotherapy: Prospectively Collected Material Data. BioMed Res. Int. 2014, 2014, 712827. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  23. Stillwell, A.P.; Ho, Y.-H.; Veitch\ud, C. Systematic Review of Prognostic Factors Related to Overall Survival in Patients with Stage IV Colorectal Cancer and Unresectable Metastases. World J. Surg. 2010, 35, 684–692. [Google Scholar] [CrossRef] [PubMed]
  24. Lu, Y.-Y.; Chen, J.-H.; Chien, C.-R.; Chen, W.T.-L.; Tsai, S.-C.; Lin, W.-Y.; Kao, C.-H. Use of FDG-PET or PET/CT to detect recurrent colorectal cancer in patients with elevated CEA: A systematic review and meta-analysis. Int. J. Colorectal Dis. 2013, 28, 1039–1047. [Google Scholar] [CrossRef] [PubMed]
  25. Cristaudo, A.T.; Jennings, S.B.; Morris, D.L. Comparison of Proportion of Elevated Carcinoembryonic Antigen Levels in Patients With Appendiceal and Colorectal Adenocarcinoma: A Systematic Review and Meta-analysis. Anticancer Res. 2022, 42, 4217–4235. [Google Scholar] [CrossRef] [PubMed]
  26. Su, Y.-L.; Tsai, K.-L.; Chiu, T.-J.; Lin, Y.-M.; Lee, K.-C.; Lu, C.-C.; Chen, H.-H.; Wu, C.-C.; Hsu, H.-C. Development and Validation of a Novel Serum Prognostic Marker for Patients with Metastatic Colorectal Cancer on Regorafenib Treatment. Cancers 2021, 13, 5080. [Google Scholar] [CrossRef]
  27. Horino, T.; Tokunaga, R.; Miyamoto, Y.; Hiyoshi, Y.; Akiyama, T.; Daitoku, N.; Sakamoto, Y.; Yoshida, N.; Baba, H. The advanced lung cancer inflammation index is a novel independent prognosticator in colorectal cancer patients after curative resection. Ann. Gastroenterol. Surg. 2021, 6, 83–91. [Google Scholar] [CrossRef]
  28. Thompson, J.A.; Grunert, F.; Zimmermann, W. Carcinoembryonic antigen gene family: Molecular biology and clinical perspectives. J. Clin. Lab. Anal. 1991, 5, 344–366. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  29. Dallas, M.R.; Liu, G.; Chen, W.; Thomas, S.N.; Wirtz, D.; Huso, D.L.; Konstantopoulos, K. Divergent roles of CD44 and carcinoembryonic antigen in colon cancer metastasis. FASEB J. 2012, 26, 2648–2656. [Google Scholar] [CrossRef] [Green Version]
  30. Alexiou, D.; Karayiannakis, A.; Syrigos, K.; Zbar, A.; Kremmyda, A.; Bramis, I.; Tsigris, C. Serum levels of E-selectin, ICAM-1 and VCAM-1 in colorectal cancer patients: Correlations with clinicopathological features, patient survival and tumour surgery. Eur. J. Cancer 2001, 37, 2392–2397. [Google Scholar] [CrossRef]
  31. Becerra, A.Z.; Probst, C.P.; Tejani, M.A.; Aquina, C.; González, M.G.; Hensley, B.J.; Noyes, K.; Monson, J.R.; Fleming, F. Evaluating the Prognostic Role of Elevated Preoperative Carcinoembryonic Antigen Levels in Colon Cancer Patients: Results from the National Cancer Database. Ann. Surg. Oncol. 2016, 23, 1554–1561. [Google Scholar] [CrossRef]
  32. Thirunavukarasu, P.; Talati, C.; Munjal, S.; Attwood, K.; Edge, S.B.; Francescutti, V. Effect of Incorporation of Pretreatment Serum Carcinoembryonic Antigen Levels Into AJCC Staging for Colon Cancer on 5-Year Survival. JAMA Surg. 2015, 150, 747–755. [Google Scholar] [CrossRef] [PubMed]
  33. Huang, S.H.; Tsai, W.-S.; You, J.-F.; Hung, H.-Y.; Yeh, C.-Y.; Hsieh, P.-S.; Chiang, S.-F.; Lai, C.-C.; Chiang, J.-M.; Tang, R.; et al. Preoperative Carcinoembryonic Antigen as a Poor Prognostic Factor in Stage I–III Colorectal Cancer After Curative-Intent Resection: A Propensity Score Matching Analysis. Ann. Surg. Oncol. 2019, 26, 1685–1694. [Google Scholar] [CrossRef] [PubMed]
  34. Takagawa, R.; Fujii, S.; Ohta, M.; Nagano, Y.; Kunisaki, C.; Yamagishi, S.; Osada, S.; Ichikawa, Y.; Shimada, H. Preoperative Serum Carcinoembryonic Antigen Level as a Predictive Factor of Recurrence After Curative Resection of Colorectal Cancer. Ann. Surg. Oncol. 2008, 15, 3433–3439. [Google Scholar] [CrossRef]
  35. Kim, C.W.; Yoon, Y.S.; Park, I.J.; Lim, S.-B.; Yu, C.S.; Kim, J.C. Elevation of Preoperative s-CEA Concentration in Stage IIA Colorectal Cancer Can Also Be a High Risk Factor for Stage II Patients. Ann. Surg. Oncol. 2013, 20, 2914–2920. [Google Scholar] [CrossRef]
  36. Moreno García, V.; Cejas, P.; Blanco Codesido, M.; Feliu Batlle, J.; de Castro Carpeño, J.; Belda-Iniesta, C.; Barriuso, J.; Sánchez, J.J.; Larrauri, J.; González-Barón, M.; et al. Prognostic value of carcinoembryonic antigen level in rectal cancer treated with neoadjuvant chemoradiotherapy. Int. J. Colorectal. Dis. 2009, 24, 741–748. [Google Scholar] [CrossRef] [PubMed]
  37. Ruibal Morell, A. CEA serum levels in non-neoplastic disease. Int. J. Biol. Markers 1992, 7, 160–166. [Google Scholar] [CrossRef]
  38. Yang, Y.; Xu, M.; Huang, H.; Jiang, X.; Gong, K.; Liu, Y.; Kuang, X.; Yang, X. Serum carcinoembryonic antigen elevation in benign lung diseases. Sci. Rep. 2021, 11, 19044. [Google Scholar] [CrossRef]
  39. Bulut, I.; Arbak, P.; Coskun, A.; Balbay, O.; Annakkaya, A.; Yavuz, O.; Gulcan, E. Comparison of Serum CA 19.9, CA 125 and CEA Levels with Severity of Chronic Obstructive Pulmonary Disease. Med Princ. Pract. 2009, 18, 289–293. [Google Scholar] [CrossRef] [PubMed]
  40. Yamaguchi, S.; Takeuchi, Y.; Arai, K.; Oishi, C.; Norose, T.; Yamochi-Onizuka, T.; Kushima, M.; Ota, H.; Imawari, M. Elevation of carcinoembryonic antigen coinciding with disease activity of ulcerative colitis. Clin. J. Gastroenterol. 2012, 5, 150–154. [Google Scholar] [CrossRef]
  41. Kang, H.Y.; Choe, E.K.; Park, K.J.; Lee, Y. Factors Requiring Adjustment in the Interpretation of Serum Carcinoembryonic Antigen: A Cross-Sectional Study of 18,131 Healthy Nonsmokers. Gastroenterol. Res. Pract. 2017, 2017, 9858931. [Google Scholar] [CrossRef] [PubMed]
  42. Dupré, A.; Malik, H.Z. Inflammation and cancer: What a surgical oncologist should know. Eur. J. Surg. Oncol. 2018, 44, 566–570. [Google Scholar] [CrossRef] [PubMed]
  43. Korniluk, A.; Koper, O.; Kemona, H.; Dymicka-Piekarska, V. From inflammation to cancer. Ir. J. Med. Sci. 2017, 186, 57–62. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  44. Waldman, A.D.; Fritz, J.M.; Lenardo, M.J. A guide to cancer immunotherapy: From T cell basic science to clinical practice. Nat. Rev. Immunol. 2020, 20, 651–668. [Google Scholar] [CrossRef] [PubMed]
  45. Herrero-Cervera, A.; Soehnlein, O.; Kenne, E. Neutrophils in chronic inflammatory diseases. Cell. Mol. Immunol. 2022, 19, 177–191. [Google Scholar] [CrossRef] [PubMed]
  46. Golder, A.M.; McMillan, D.C.; Park, J.H.; Mansouri, D.; Horgan, P.G.; Roxburgh, C.S. The prognostic value of combined measures of the systemic inflammatory response in patients with colon cancer: An analysis of 1700 patients. Br. J. Cancer 2021, 124, 1828–1835. [Google Scholar] [CrossRef]
  47. Hamid, H.K.; Emile, S.H.; Davis, G.N. Prognostic Significance of Lymphocyte-to-Monocyte and Platelet-to-Lymphocyte Ratio in Rectal Cancer: A Systematic Review, Meta-analysis, and Meta-regression. Dis. Colon Rectum 2021, 65, 178–187. [Google Scholar] [CrossRef]
  48. Huang, X.; Huan, Y.; Liu, L.; Ye, Q.; Guo, J.; Yan, B. Preoperative low absolute lymphocyte count to fibrinogen ratio correlated with poor survival in nonmetastatic colorectal cancer. World J. Surg. Oncol. 2022, 20, 309. [Google Scholar] [CrossRef]
  49. Liu, X.-C.; Dai, Y.-L.; Huang, F.; Zhong, Z.-J. Diagnostic Value of Carcinoembryonic Antigen Combined with Multi-Inflammatory Cell Ratios in Colorectal Cancer. Dis. Markers 2022, 2022, 4889616. [Google Scholar] [CrossRef]
  50. Cheng, K.-C.; Lin, Y.-M.; Liu, C.-C.; Wu, K.-L.; Lee, K.-C. High Red Cell Distribution Width Is Associated with Worse Prognosis in Early Colorectal Cancer after Curative Resection: A Propensity-Matched Analysis. Cancers 2022, 14, 945. [Google Scholar] [CrossRef]
  51. Yin, X.; Wu, L.; Yang, H.; Yang, H. Prognostic significance of neutrophil-lymphocyte ratio (NLR) in patients with ovarian cancer: A systematic review and meta-analysis. Medicine 2019, 98, e17475. [Google Scholar] [CrossRef] [PubMed]
  52. Cupp, M.A.; Cariolou, M.; Tzoulaki, I.; Aune, D.; Evangelou, E.; Berlanga-Taylor, A.J. Neutrophil to lymphocyte ratio and cancer prognosis: An umbrella review of systematic reviews and meta-analyses of observational studies. BMC Med. 2020, 18, 360. [Google Scholar] [CrossRef] [PubMed]
  53. Jakubowska, K.; Koda, M.; Kisielewski, W.; Kańczuga-Koda, L.; Grudzińska, M.; Famulski, W. Pre- and postoperative neutrophil and lymphocyte count and neutrophil-to-lymphocyte ratio in patients with colorectal cancer. Mol. Clin. Oncol. 2020, 13, 56. [Google Scholar] [CrossRef]
  54. Mazaki, J.; Katsumata, K.; Kasahara, K.; Tago, T.; Wada, T.; Kuwabara, H.; Enomoto, M.; Ishizaki, T.; Nagakawa, Y.; Tsuchida, A. Neutrophil-to-lymphocyte ratio is a prognostic factor for colon cancer: A propensity score analysis. BMC Cancer 2020, 20, 922. [Google Scholar] [CrossRef]
  55. Dell’Aquila, E.; Cremolini, C.; Zeppola, T.; Lonardi, S.; Bergamo, F.; Masi, G.; Stellato, M.; Marmorino, F.; Schirripa, M.; Urbano, F.; et al. Prognostic and predictive role of neutrophil/lymphocytes ratio in metastatic colorectal cancer: A retrospective analysis of the TRIBE study by GONO. Ann. Oncol. 2018, 29, 924–930. [Google Scholar] [CrossRef] [PubMed]
  56. Hung, H.-Y.; Chen, J.-S.; Yeh, C.Y.; Changchien, C.-R.; Tang, R.; Hsieh, P.-S.; Tasi, W.-S.; You, J.-F.; You, Y.-T.; Fan, C.-W.; et al. Effect of preoperative neutrophil–lymphocyte ratio on the surgical outcomes of stage II colon cancer patients who do not receive adjuvant chemotherapy. Int. J. Colorectal Dis. 2011, 26, 1059–1065. [Google Scholar] [CrossRef] [PubMed]
  57. Chiang, S.F.; Hung, H.Y.; Tang, R.; Changchien, C.R.; Chen, J.S.; You, Y.T.; Chiang, J.M.; Lin, J.R. Can neutrophil-to-lymphocyte ratio predict the survival of colorectal cancer patients who have received curative surgery electively? Int. J. Colorectal Dis. 2012, 27, 1347–1357. [Google Scholar] [CrossRef] [PubMed]
Cancers 14 06232 g001 550
Figure 1. (a) Receiver operating characteristic (ROC) curve analysis of the cancer-inflammation prognostic index (CIPI) for five-year relapse-free survival (RFS) in stage I–III colorectal cancer (CRC). (b) Mean CIPI of patients alive and with recurrence or mortality during five-year follow-up. AUC = area under the curve; CI = confidence interval.
Figure 1. (a) Receiver operating characteristic (ROC) curve analysis of the cancer-inflammation prognostic index (CIPI) for five-year relapse-free survival (RFS) in stage I–III colorectal cancer (CRC). (b) Mean CIPI of patients alive and with recurrence or mortality during five-year follow-up. AUC = area under the curve; CI = confidence interval.
Cancers 14 06232 g001
Cancers 14 06232 g002 550
Figure 2. Kaplan–Meier survival analysis for relapse-free survival (RFS) (a) and overall survival (OS) (b) according to cancer-inflammation prognostic index (CIPI).
Figure 2. Kaplan–Meier survival analysis for relapse-free survival (RFS) (a) and overall survival (OS) (b) according to cancer-inflammation prognostic index (CIPI).
Cancers 14 06232 g002
Cancers 14 06232 g003 550
Figure 3. Subgroup analyses of relapse-free survival and overall survival based on cancer-inflammation prognostic index (CIPI) level.
Figure 3. Subgroup analyses of relapse-free survival and overall survival based on cancer-inflammation prognostic index (CIPI) level.
Cancers 14 06232 g003
Table
Table 1. Demographic characteristics of patients based on the CIPI.
Table 1. Demographic characteristics of patients based on the CIPI.
VariablesCIPI (n = 12,092)p Values
Low < 8
(n = 5996)		High ≥ 8
(n = 6096)
Age, mean ± SD 62.10 ± 12.6764.94 ± 13.12<0.001
Age (years), n (%)
<653331 (55.6)2798 (45.9)<0.001
≥652665 (44.4)3298 (54.1)
Gender, n (%)
Male 3267 (54.5)3581 (58.7)<0.001
Female2729 (45.5)2515 (41.3)
Body mass index, kg/m2, n (%)
<253509 (59.3)3970 (67.4)<0.001
≥252407 (40.7)1916 (32.6)
missing80210
Underlying illness, n (%)
Hypertension 1978 (33.0)2045 (33.5)0.493
Cardiovascular disease511 (8.5)550 (9.0)0.376
Diabetes mellitus843 (14.1)1153 (18.9)<0.001
Peptic ulcer disease447 (7.5)458 (7.5)0.993
Hepatitis 326 (5.4)263 (4.3)0.006
Chronic renal disease282 (4.8)586 (9.8)<0.001
Tumor location, n (%)
Colon3440 (57.4)3411 (56.0)0.119
Rectum2556 (42.6)2685 (44.0)
Tumor stage, n (%)
Stage I1870 (31.2)657 (10.8)<0.001
Stage II1972 (32.9)2499 (41.0)
Stage III2154 (35.9)2940 (48.2)
pT status, n (%)
T11129 (18.8)276 (4.5)<0.001
T21094 (18.2)518 (8.5)
T32842 (47.4)3097 (50.8)
T4931 (15.5)22.5 (36.2)
pN status, n (%)
N03842 (64.1)3153 (51.7)<0.001
N11394 (23.2)1738 (28.5)
N2760 (12.7)1205 (19.8)
Histologic type, n (%)
Adenocarcinoma 5733 (95.6)5611 (92.0)<0.001
Mucinous adenocarcinoma238 (4.0)432 (7.1)
Signet ring cell adenocarcinoma25 (0.4)53 (0.9)
Histologic grade, n (%)
Well differentiated1063 (17.7)767 (12.6)<0.001
Moderate differentiated4515 (75.3)4814 (79.0)
Poor differentiated362 (6.0)498 (8.2)
Unclassified 56 (0.9)17 (0.3)
Operative finding
Obstruction312 (5.2)814 (13.4)<0.001
Perforation70 (1.2)314 (5.2)<0.001
Preoperative laboratory values, n (%)
Hemoglobin (g/dL)
<10743 (12.4)1429 (23.5)<0.001
≥105247 (87.6)4663 (76.5)
missing64
Albumin (g/dL)
<3.5303 (5.1)1065 (17.9)<0.001
≥3.55630 (94.9)4891 (82.1)
missing63140
Table
Table 2. Association of CIPI with short- and long-term outcome.
Table 2. Association of CIPI with short- and long-term outcome.
VariablesCIPI (n = 12,092)p Values
Low < 8
(n = 5996)		High ≥ 8
(n = 6096)
Short-term postoperative outcome, n (%)
30-day morbidity660 (11.0)1032 (16.9)<0.001
30-day mortality14 (0.2)73 (1.2)<0.001
Long-term outcome, n (survival%)
Recurrence961 (16.0)1865 (30.6)<0.001
three-year RFS4956 (81.5)3958 (61.8)<0.001
three-year OS5372 (88.4)4704 (72.0)<0.001
five-year RFS4149 (77.3)3243 (56.2)<0.001
five-year OS4462 (82.9)3660 (62.7)<0.001
10-year RFS2226 (68.2)1892 (45.5)<0.001
10-year OS2312 (71.5)2023 (49.1)<0.001
CIPI = cancer-inflammation prognostic index; RFS = relapse-free survival; OS = overall survival.
Table
Table 3. Univariate and multivariate Cox proportional hazards regression analyses of prognostic factors for relapse-free survival.
Table 3. Univariate and multivariate Cox proportional hazards regression analyses of prognostic factors for relapse-free survival.
CharacteristicsUnivariateMultivariate
HR95% CIp ValuesHR95% CIp Values
Age
<651 1
≥651.8141.711–1.923<0.0011.591.49–1.696<0.001
Gender
Female 1 1
Male1.2511.180–1.326<0.0011.2521.176–1.333<0.001
Body mass index
<251 1
≥250.8770.825–0.933<0.0010.9370.877–1.0010.053
Underlying illness
Hypertension 1.2291.163–1.299<0.0011.1311.060–1.206<0.001
Cardiovascular1.3811.282–1.488<0.0011.261.150–1.381<0.001
Diabetes mellitus1.331.238–1.428<0.0011.1471.060–1.2420.001
Peptic ulcer1.0530.958–1.1580.282
Hepatitis 0.8020.697–0.9240.0020.9450.821–1.0870.427
Renal disease2.0061.835–2.193<0.0011.4471.308–1.599<0.001
Tumor location
Colon1 1
Rectum1.311.237–1.386<0.0011.4931.401–1.591<0.001
Tumor stage
Stage I1
Stage II1.8211.653–2.006<0.001
Stage III3.0082.743–3.300<0.001
pT status
T11 1
T21.8181.550–2.132<0.0011.451.221–1.721<0.001
T32.8232.463–3.236<0.0011.8411.577–2.148<0.001
T44.4183.846–5.076<0.0012.5422.165–2.986<0.001
pN status
N01 1
N11.6021.498–1.714<0.0011.461.357–1.572<0.001
N22.7772.587–2.980<0.0012.4212.236–2.621<0.001
Histologic type
Adenocarcinoma 1 1
Mucinous1.2081.075–1.3570.0010.9780.856–1.1170.740
Signet ring cell2.6212.004–3.428<0.0011.4521.071–1.9680.016
Histologic grade
Well1 1
Moderate1.371.256–1.494<0.0010.9660.875–1.0660.488
Poor1.7431.535–1.980<0.0011.0140.876–1.1750.848
Operative finding
Obstruction1.7781.632–1.936<0.0011.2761.159–1.404<0.001
Perforation1.7691.540–2.033<0.0011.1450.980–1.3370.087
Preoperative values
Hemoglobin
<101 1
≥100.6570.614–0.703<0.0010.8730.807–0.945<0.001
Albumin
<3.51 1
≥3.50.4710.438–0.508<0.0010.6580.601–0.720<0.001
CIPI
<81 1
≥82.1782.052–2.312<0.0011.4781.383–1.579<0.001
CIPI = cancer-inflammation prognostic index.
Table
Table 4. Univariate and multivariate Cox proportional hazards regression analyses of prognostic factors for overall survival.
Table 4. Univariate and multivariate Cox proportional hazards regression analyses of prognostic factors for overall survival.
CharacteristicsUnivariateMultivariate
HR95% CIp ValuesHR95% CIp Values
Age
<651 1
≥652.2532.114–2.401<0.0011.9581.825–2.097<0.001
Gender
Female 1 1
Male1.2821.205–1.364<0.0011.2861.204–1.375<0.001
Body mass index
<251 1
≥250.8340.781–0.890<0.0010.8890.829–0.9530.001
Underlying illness
Hypertension 1.3531.271–1.439<0.0011.1891.107–1.277<0.001
Cardiovascular1.6481.502–1.807<0.0011.3451.219–1.485<0.001
Diabetes mellitus1.4341.330–1.546<0.0011.1851.092–1.285<0.001
Peptic ulcer1.1140.998–1.2440.053
Hepatitis 0.7750.662–0.9060.0010.9590.813–1.1300.616
Renal disease2.3592.153–2.585<0.0011.5871.435–1.755<0.001
Tumor location
Colon1 1
Rectum1.2671.193–1.346<0.0011.4911.395–1.594<0.001
Tumor stage
Stage I1
Stage II1.7041.539–1.887<0.001
Stage III2.7172.466–2.994<0.001
pT status
T11 1
T21.6751.419–1.977<0.0011.31.089–1.5510.004
T32.4332.112–2.803<0.0011.5241.300–1.785<0.001
T43.9773.446–4.591<0.0012.1931.860–2.586<0.001
pN status
N01 1
N11.5041.399–1.617<0.0011.3921.288–1.504<0.001
N22.6122.424–2.815<0.0012.3812.192–2.587<0.001
Histologic type
Adenocarcinoma 1 1
Mucinous1.1921.053–1.3490.0010.9540.830–1.0960.504
Signet ring cell3.1432.396–4.122<0.0011.8391.360–2.486<0.001
Histologic grade
Well1 1
Moderate1.2911.178–1.414<0.0010.9510.859–1.0530.334
Poor1.7261.510–1.974<0.0011.0550.906–1.2290.488
Operative finding
Obstruction1.7841.630–1.953<0.0011.2581.136–1.393<0.001
Perforation1.8111.567–2.093<0.0011.1310.962–1.3310.136
Preoperative values
Hemoglobin
<101 1
≥100.6170.575–0.663<0.0010.8550.788–0.929<0.001
Albumin
<3.51 1
≥3.50.4060.376–0.439<0.0010.5890.538–0.646<0.001
CIPI
<81 1
≥82.2622.121–2.411<0.0011.5031.400–1.613<0.001
CIPI = cancer-inflammation prognostic index.
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You, J.-F.; Hsu, Y.-J.; Chern, Y.-J.; Cheng, C.-C.; Jong, B.-K.; Liao, C.-K.; Hsieh, P.-S.; Hsu, H.-C.; Tsai, W.-S. Preoperative Cancer Inflammation Prognostic Index as a Superior Predictor of Short- and Long-Term Outcomes in Patients with Stage I–III Colorectal Cancer after Curative Surgery. Cancers 2022, 14, 6232. https://doi.org/10.3390/cancers14246232

AMA Style

You J-F, Hsu Y-J, Chern Y-J, Cheng C-C, Jong B-K, Liao C-K, Hsieh P-S, Hsu H-C, Tsai W-S. Preoperative Cancer Inflammation Prognostic Index as a Superior Predictor of Short- and Long-Term Outcomes in Patients with Stage I–III Colorectal Cancer after Curative Surgery. Cancers. 2022; 14(24):6232. https://doi.org/10.3390/cancers14246232

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You, Jeng-Fu, Yu-Jen Hsu, Yih-Jong Chern, Ching-Chung Cheng, Bor-Kang Jong, Chun-Kai Liao, Pao-Shiu Hsieh, Hung-Chih Hsu, and Wen-Sy Tsai. 2022. "Preoperative Cancer Inflammation Prognostic Index as a Superior Predictor of Short- and Long-Term Outcomes in Patients with Stage I–III Colorectal Cancer after Curative Surgery" Cancers 14, no. 24: 6232. https://doi.org/10.3390/cancers14246232

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