Elevated Neutrophil-to-Lymphocyte Ratio in Perioperative Periods is Suggestive of Poor Prognosis in Patients with Colorectal Cancer

Construction and validation of a nomogram for predicting disease-free survival after radical resection of rectal cancer using perioperative inflammatory indicators

Background

Colorectal cancer is a common digestive tract malignancy that seriously affects patients' quality of life and survival time. Surgery is the main treatment modality, but postoperative prognosis varies greatly. This study sought to explore the impact of perioperative inflammatory indicators on disease-free survival (DFS) in patients after radical resection of rectal cancer and to construct a nomogram for clinical reference.

Methods

A retrospective analysis was performed on 304 primary rectal adenocarcinoma patients who underwent laparoscopic radical resection of rectal cancer at the Affiliated Hospital of Xuzhou Medical University from May 1, 2018 to September 30, 2020. The patients were divided into a training set (n=213) and a validation set (n=91) at a ratio of 7:3. The cut-off values of each inflammatory indicator based on the receiver operating characteristic (ROC) curve were determined and each indicator was divided into high and low groups. The least absolute shrinkage and selection operator (LASSO)-Cox regression model was used to analyze the independent risk factors affecting DFS, and a nomogram was established. The model was internally validated using the validation set, and the discrimination, calibration, and clinical application value of the nomogram were evaluated using ROC curve, calibration curve, and clinical decision curve analysis (DCA).

Results

Tumor-node-metastasis (TNM) stage III, neural invasion, preoperative neutrophil-to-lymphocyte ratio (NLR) ≥1.995, postoperative systemic immune-inflammation index (SII) ≥451.05, and Δpan-immune-inflammation value (ΔPIV) ≥144.36 (P<0.05) were independent factors for predicting the 3-year DFS of patients after rectal cancer surgery. The area under the ROC curve (AUC) of the nomogram was 0.811 [95% confidence interval (CI): 0.778-0.889] in the training set and 0.808 (95% CI: 0.785-0.942) in the validation set. The nomogram showed good calibration, indicating good consistency between predicted and actual risks. DCA demonstrated the clinical utility of the nomogram.

Conclusions

The nomogram constructed based on TNM stage III, neural invasion, preoperative NLR ≥1.995, postoperative SII ≥451.05, and ΔPIV ≥144.36 can predict the risk of 3-year DFS in patients undergoing curative surgery for rectal cancer, enabling strict postoperative follow-up and timely adjuvant treatment for high-risk patients.

The neutrophil-to-lymphocyte ratio as a new prognostic factor in cancers: a narrative review

The increasing incidence of cancer globally has highlighted the significance of early diagnosis and improvement of treatment strategies. In the 19th century, a connection was made between inflammation and cancer, with inflammation recognized as a malignancy hallmark. The neutrophil-to-lymphocyte ratio (NLR), calculated from a complete blood count, is a simple and accessible biomarker of inflammation status. NLR has also been proven to be a prognostic factor for various medical conditions, including mortality classification in cardiac patients, infectious diseases, postoperative complications, and inflammatory states. In this narrative review, we aim to assess the prognostic potential of NLR in cancer. We will review recent studies that have evaluated the association between NLR and various malignancies. The results of this review will help to further understand the role of NLR in cancer prognosis and inform future research directions. With the increasing incidence of cancer, it is important to identify reliable and accessible prognostic markers to improve patient outcomes. The study of NLR in cancer may provide valuable insights into the development and progression of cancer and inform clinical decision-making.

Prognostic value of preoperative immune-nutritional scoring systems in remnant gastric cancer patients undergoing surgery

BACKGROUND

Remnant gastric cancer (GC) is defined as GC that occurs five years or more after gastrectomy. Systematically evaluating the preoperative immune and nutritional status of patients and analyzing its prognostic impact on postoperative remnant gastric cancer (RGC) patients are crucial. A simple scoring system that combines multiple immune or nutritional indicators to identify nutritional or immune status before surgery is necessary.

AIM

To evaluate the value of preoperative immune-nutritional scoring systems in predicting the prognosis of patients with RGC.

METHODS

The clinical data of 54 patients with RGC were collected and analyzed retrospectively. Prognostic nutritional index (PNI), controlled nutritional status (CONUT), and Naples prognostic score (NPS) were calculated by preoperative blood indicators, including absolute lymphocyte count, lymphocyte to monocyte ratio, neutrophil to lymphocyte ratio, serum albumin, and serum total cholesterol. Patients with RGC were divided into groups according to the immune-nutritional risk. The relationship between the three preoperative immune-nutritional scores and clinical characteristics was analyzed. Cox regression and Kaplan–Meier analysis was performed to analyze the difference in overall survival (OS) rate between various immune-nutritional score groups.

RESULTS

The median age of this cohort was 70.5 years (ranging from 39 to 87 years). No significant correlation was found between most pathological features and immune-nutritional status (P > 0.05). Patients with a PNI score < 45, CONUT score or NPS score ≥ 3 were considered to be at high immune-nutritional risk. The areas under the receiver operating characteristic curves of PNI, CONUT, and NPS systems for predicting postoperative survival were 0.611 [95% confidence interval (CI): 0.460–0.763; P = 0.161], 0.635 (95%CI: 0.485–0.784; P = 0.090), and 0.707 (95%CI: 0.566–0.848; P = 0.009), respectively. Cox regression analysis showed that the three immune-nutritional scoring systems were significantly correlated with OS (PNI: P = 0.002; CONUT: P = 0.039; NPS: P < 0.001). Survival analysis revealed a significant difference in OS between different immune-nutritional groups (PNI: 75 mo vs 42 mo, P = 0.001; CONUT: 69 mo vs 48 mo, P = 0.033; NPS: 77 mo vs 40 mo, P < 0.001).

CONCLUSION

These preoperative immune-nutritional scores are reliable multidimensional prognostic scoring systems for predicting the prognosis of patients with RGC, in which the NPS system has relatively effective predictive performance.

Increased neutrophil-to-lymphocyte ratio is associated with unfavorable functional outcomes in acute pontine infarction

BACKGROUND

The neutrophil-to-lymphocyte ratio (NLR) is positively associated with unfavorable outcomes in patients with cerebral infarction. This study aimed to investigate the relationship between the NLR and the short-term clinical outcome of acute pontine infarction.

METHODS

Patients with acute pontine infarction were consecutively included. Clinical and laboratory data were collected. All patients were followed up at 3 months using modified Rankin Scale (mRS) scores. An unfavorable outcome was defined as an mRS score ≥ 3. Receiver operating characteristic (ROC) curve analysis was used to calculate the optimal cutoff values for patients with acute pontine infarction. risk factors can be predictive factors for an unfavorable outcome after acute pontine infarction.

RESULTS

Two hundred fifty-six patients with acute pontine infarction were included in this study. The NLR was significantly higher in the unfavorable outcome group than in the favorable outcome group (P < 0.05). Additionally, the infarct size was significantly higher in the high NLR tertile group than in the low NLR tertile group (P < 0.05). Multivariate logistic regression analysis revealed that the baseline National Institutes of Health Stroke Scale (NIHSS) score, NLR, platelet count, and fasting blood glucose (FBG) level were significantly associated with unfavorable outcomes 3 months after acute pontine infarction. The optimal cutoff value of the NLR for predicting the 3-month outcome of acute pontine infarction was 3.055. The negative and positive predictive values of NLR were 85.7% and 61.3%, respectively, and the sensitivity and specificity of NLR were 69.2% and 80.9%.

CONCLUSIONS

We found that the NLR may be an independent predictive factor for the outcome of acute pontine infarction.

The Clinical Impact of Combining Neutrophil-to-Lymphocyte Ratio with Sarcopenia for Improved Discrimination of Progression-Free Survival in Patients with Colorectal Cancer

This study aimed to evaluate the clinical impact of combined sarcopenia and inflammation classification (CSIC) in patients with colorectal cancer (CRC). The skeletal muscle index (SMI) and neutrophil-to-lymphocyte ratio (NLR) were measured in 1270 patients who underwent surgery between January 2005 and April 2014. A Cox proportional hazards model was used to evaluate the correlation of sarcopenia, NLR, and CSIC, with progression-free survival (PFS). The integrated area under the curve (iAUC) was used to compare the discriminatory performance of each model. Using the cut-off values for SMI suggested by Martin et al. and for an NLR of 2.26, the CSIC was defined as follows: nonsarcopenia with low NLR (group 1), nonsarcopenia with high NLR (group 2), sarcopenia with low NLR (group 3), and sarcopenia with high NLR (group 4). Sarcopenia alone was not statistically significant. Multivariate analysis identified that CSIC (group 4 vs. group 1; hazard ratio (HR), 1.726; 95% CI, 1.130–2.634; p = 0.011) and NLR (HR, 1.600; 95% CI, 1.203–2.128; p = 0.001) were independently associated with PFS. The CSIC improved the prediction accuracy of PFS compared with NLR (iAUC mean difference = 0.011; 95% CI, 0.0018–0.028). In conclusion, the combination of sarcopenia and NLR could improve prognostic accuracy, and thus compensate for the limitation of sarcopenia.

The Efficacy of Different Inflammatory Markers for the Prognosis of Patients with Malignant Tumors

Background

Inflammation is considered essential in cancer progression, as it affects the nutritional status and prognosis of patients. In this study, we aim to analyze the efficacy of various inflammatory markers in predicting prognosis in cancer patients.

Methods

Patients with malignant tumor were included as primary and validation cohort. Basic clinical information, anthropometric indicators, body composition analysis, and serological indicators were recorded. After proposing the optimal thresholds by time-dependent receiver operating characteristic (ROC), univariate and multivariate Cox regression analyses were performed to analyze the association between inflammatory markers and overall survival (OS). A nomogram was established to develop a scored-inflammatory marker system. Eight inflammatory models based on combinations of inflammatory markers were assessed. Cox regression analysis was used to analyze the relationship of each inflammatory model and mortality of participants. Then, subanalysis of specific tumor types was conducted by Cox regression. Logistic regression models were used to analyze the relationship between different inflammatory models and malnutrition.

Results

Univariate and multivariate Cox regression analyses indicated that pack-years of cigarette smoking, C-reactive protein (CRP), and systemic immune-inflammation index (SII) were related to the OS of cancer patients. A nomogram was constructed to develop a scored-inflammatory marker system. Among the eight inflammatory models, patients in model A had worst prognosis compared with patients in other models. Subanalysis next showed lung cancer, breast cancer and digestive system neoplasms patients in model A suffered the worst prognosis. Logistic regression indicated that model A was also with predictive value for malnutrition.

Conclusion

A scored-inflammatory marker system was established to predict the OS of cancer patients. The inflammatory models established in this study can be used to predict prognosis, as well as cancer-related malnutrition. Inflammatory model A suffered the worst OS and was with the predictive efficacy for malnutrition.