Jin LJ, Chen WB, Zhang XY, Bai J, Zhao HC, Wang ZY. Analysis of factors potentially predicting prognosis of colorectal cancer.
World J Gastrointest Oncol 2019;
11:1206-1217. [PMID:
31908725 PMCID:
PMC6937433 DOI:
10.4251/wjgo.v11.i12.1206]
[Citation(s) in RCA: 12] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/11/2019] [Revised: 08/05/2019] [Accepted: 08/26/2019] [Indexed: 02/05/2023] Open
Abstract
BACKGROUND
Accurate assessment of the prognosis after colorectal cancer surgery is of great significance in patients with colorectal cancer. However, there is no systematic analysis of factors affecting the prognosis of colorectal cancer currently.
AIM
To systematically analyze the influence of clinical data and serological and histological indicators on the prognosis of patients with colorectal cancer, and to explore the indicators that can accurately assess the prognosis of patients with colorectal cancer.
METHODS
A total of 374 patients with colorectal cancer were enrolled. The clinical data, tumor-node-metastasis (TNM) stage, and Dukes stage were recorded. All patients received examinations including carcinoembryonic antigen (CEA), carbohydrate antigen 199, C-reactive protein, albumin, D-dimer, and fibrinogen as well as routine blood tests one week before surgery. The tumor location, size, depth of invasion, lymph node metastasis, and distant metastasis were recorded during surgery. The pathological tissue typing and expression of proliferating cell nuclear antigen (PCNA) and p53 were observed. All patients were followed for 3 years, and patients with endpoint events were defined as a poor prognosis group, and the remaining patients were defined as a good prognosis group. The differences in clinical data, serology, and histology were analyzed between the two groups. Multivariate COX regression was used to analyze the independent influencing factors for the prognosis of colorectal cancer. The receiver operating characteristic curve was used to evaluate the predictive value of each of the independent influencing factors and their combination for the prognosis of colorectal cancer.
RESULTS
The follow-up outcomes showed that 81 patients were in the good prognosis group and 274 patients in the poor prognosis group. The TNM stage, PCNA, Glasgow prognostic score (GPS), neutrophil-lymphocyte ratio (NLR), C-reactive protein/albumin ratio (CAR), D-dimer, and CEA were independent influencing factors for the prognosis of colorectal cancer (P = 0.000). NLR had the highest predictive power for colorectal cancer prognosis [area under the receiver operating characteristic curve (AUC) = 0.925], followed by D-dimer (AUC = 0.879) and GPS (AUC = 0.872). The accuracy of the combination of all indicators in predicting the prognosis of colorectal cancer was the highest (AUC = 0.973), which was significantly higher than that of any of the indicators alone (P < 0.05). The sensitivity and specificity of the combination were 92.59% and 90.51%, respectively.
CONCLUSION
The independent influence factors for the prognosis of colorectal cancer include TNM stage, PCNA, GPS, NLR, CAR, D-dimer, and CEA. The combined assessment of the independent factors is the most accurate predictor of the prognosis after colorectal cancer surgery.
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