Predictive impact of the inflammation‐based indices in colorectal cancer patients with adjuvant chemotherapy

Abstract

Increasing evidences reported that cancer‐triggered inflammation was associated with survival prognosis from colorectal cancer (CRC). However, the comprehensive effects of inflammatory‐based coNLR‐PLR that combines neutrophil‐to‐lymphocyte ratio (NLR) and platelet‐to‐lymphocyte ratio (PLR) rarely remain to be determined during chemotherapy. We retrospectively analyzed clinical data and baseline laboratory parameters from 153 colorectal cancer patients who underwent palliative adjuvant chemotherapy between January 2009 to January 2012. Receiver operating characteristic (ROC) curves and linear regression analyzed the predictive ability of NLR, and PLR for calculating the score of coNLR‐PLR. Overall survival (OS) and recurrence‐free survival (RFS) rates were estimated using the Kaplan‐Meier method and analyzed by the Cox proportional hazards model in univariate and multivariate analysis. The optimal cut‐off value of NLR and PLR was 2.24 and 186 by the ROC analysis. Kaplan‐Meier method showed that patients with high coNLR‐PLR score was associated with poorer OS and RFS (all P < .05). In univariate and multivariate analysis, it obtained that the coNLR‐PLR severed as a strong independent prognostic factor for OS and RFS (all P < .05). These results highlight that coNLR‐PLR index severed as a strong predictor of prognosis biomarker in CRC patients receiving adjuvant chemotherapy. Furthermore, its assessment could contribute to accurately predicting prognosis after chemotherapy in clinical practice.

Prognostic significance of the neutrophil-to-lymphocyte and platelet-to-lymphocyte ratio in patients with metastatic gastric cancer

“…In our study we did not count the NLR of the healthy population, but we refer to Professor Tao's study and think that the NLR of the healthy population is 0.62 to 1.64, and the PLR of the healthy population is 45.81 to 108.33. [ 11 ] As summarized in Table 1 , an increased NLR level was significantly associated with age ( P = .008), liver metastases ( P < .001), H pylori infection ( P = .008), peritoneal metastasis ( P = .003). The PLR was associated with liver metastasis ( P = .021), sex ( P = .048), and with H pylori infection ( P = .008), which was not associated with age, HER-2, CA-199 level, metastatic sites, and left cervical lymph node metastases.…”

Prognostic Value of an Inflammation-Related Index in 6,865 Chinese Patients With Postoperative Digestive Tract Cancers: The FIESTA Study

“…Although the integration of NLR and PLR as a composite biomarker has been widely investigated, comparisons between the results of different studies are difficult due to diverse cutting points selected (38, 45). For instance, Tao and colleagues found a strong predictive effect for combined NLR-PLR index in 153 patients with CRC who received adjuvant chemotherapy (46). Feng et al also found that INP was an independent prognostic marker in patients with EC without neoadjuvant or adjuvant treatment (47).…”

Lymphocyte-to-monocyte ratio effectively predicts survival outcome of patients with obstructive colorectal cancer

“…On the other hand, increasing monocytes and lymphatic cells would enhance the resistance against tumor invasion[11]. Increasing evidence shows that an elevated neutrophil-to-lymphocyte ratio (NLR) is closely related to a poor prognosis in ovarian cancer, cholangiocarcinoma, and elective colorectal cancer (CRC)[12-14]. The overexpression of circulating derived NLR, an effective biomarker for the diagnosis of early pancreatic cancer[15], was accompanied by increasing distal organ invasion in metastatic CRC[16].…”

“…An elevated preoperative lymphocyte-to-monocyte ratio (LMR), as a superior existing biomarker, was positively correlated with the survival outcomes of patients with resectable CRC and presented better overall survival[17]. Other inflammatory indexes, such as the platelet-to-lymphocyte ratio (PLR)[14] and systemic immune inflammation index (SII)[18], have also been studied in the exploration of optimal predictive models for tumor recurrence.…”