The value of complete blood count for the prognosis analysis of preoperative esophageal squamous cell carcinoma

Abstract

Objective: To investigate the predictive value of preoperative complete blood count for the survival of patients with esophageal squamous cell carcinoma.

Methods: A total of 1587 patients with pathologically confirmed esophageal squamous cell carcinoma who underwent esophagectomy in the Cancer Hospital Affiliated to Xinjiang Medical University from January 2010 to December 2019 were collected by retrospective study. A total of 359 patients were as the validation cohort from January 2015 to December 2016, and the remaining 1228 patients were as the training cohort. The relevant clinical data were collected by the medical record system, and the patients were followed up by the hospital medical record follow-up system. The follow-up outcome was patient death. The survival time of all patients was obtained. The Cox proportional hazards regression model and nomogram were established to predict the survival prognosis of esophageal squamous cell carcinoma by the index, their cut-off values obtained the training cohort by the ROC curve. The Kaplan-Meier survival curve was established to express the overall survival rate. The 3-year and 5-year calibration curves and C-index were used to determine the accuracy and discrimination of the prognostic model. The decision curve analysis was used to predict the potential of clinical application. Finally, the validation cohort was used to verify the results of the training cohort.

Results: The cut-off values of NLR, NMR, LMR, RDW and PDW in complete blood count of the training cohort were 3.29, 12.77, 2.95, 15.05 and 13.65%, respectively. All indicators were divided into high and low groups according to cut-off values. Univariate Cox regression analysis model showed that age (≥ 60), NLR (≥3.29), LMR (< 2.95), RDW (≥15.05%) and PDW (≥13.65%) were risk factors for the prognosis of esophageal squamous cell carcinoma; multivariate Cox regression analysis model showed that age (≥ 60), NLR (≥3.29) and LMR (< 2.95) were independent risk factors for esophageal squamous cell carcinoma. Kaplan-Meier curve indicated that age < 60, NLR < 3.52 and LMR ≥ 2.95 groups had higher overall survival (p < 0.05). The 3-year calibration curve indicated that its predictive probability overestimate the actual probability. 5-year calibration curve indicated that its predictive probability was consistent with the actual probability. 5 c-index was 0.730 and 0.737, respectively, indicating that the prognostic model had high accuracy and discrimination. The decision curve analysis indicated good potential for clinical application. The validation cohort also proved the validity of the prognostic model.

Conclusion: NLR and LMR results in complete blood count results can be used to predict the survival prognosis of patients with preoperative esophageal squamous cell carcinoma.

Fig. 1

ROC curve of CBC index based on training cohort. NOTE: NLR:neutrophil to lymphocyte ratio;NMR:neutrophil to monocyte ratio;LMR:lymphocyte to monocyte ratio;RDW: red blood cell distribution width;PDW: blood cell distribution width

Fig. 2

Kaplan Meier survival curve for the indicators of significance. NOTE: NLR:neutrophil to lymphocyte ratio;LMR:lymphocyte to monocyte ratio

Fig. 3

Evaluation of nomogram of CBC index in the patients with esophageal squamous cell cancer after esophagectomy. NOTE: To use the nomogram, the value attributed to an individual patient is located on each variable axis, and a line is drawn upwards to determine the number of points received for each variable value. The sum of these numbers is located on the total points axis, and a line is drawn downward to the survival axis to determine the likelihood of 3- or 5-year survival. NLR:neutrophil to lymphocyte ratio;LMR:lymphocyte to monocyte ratio

Fig. 4

Performance validation for predicting 3-year and 5-year survival in the training cohort. NOTE: Calibration curve by nomogram, Pathological stage for 3-year (A) and 5-year (B) OS in the training cohort, Time-dependent receiver operating characteristic (ROC) curves by nomogram, Pathological stage for 3-year (C) and 5-year (D) OS in the training cohort. Decision curve analyses by nomogram, Pathological stage for 3-year (E) and 5-year (F) OS in the training cohort

Fig. 5

Performance validation for predicting 3-year and 5-year survival in the validation cohort. NOTE: Calibration curve by nomogram, Pathological stage for 3-year (A) and 5-year (B) OS in the validation cohort, Time-dependent receiver operating characteristic (ROC) curves by nomogram, Pathological stage for 3-year (C) and 5-year (D) OS in the validation cohort. Decision curve analyses by nomogram, Pathological stage for 3-year (E) and 5-year (F) OS in the validation cohort