BMC Cancer (Feb 2024)

Impact of preoperative white blood cell count on outcomes in different stage colorectal cancer patients undergoing surgical resection: a single-institution retrospective cohort study

  • Bei Wang,
  • Dandan Ling,
  • Lihong Li,
  • Jun Zhang,
  • Jianghui Xu

DOI
https://doi.org/10.1186/s12885-024-11983-7
Journal volume & issue
Vol. 24, no. 1
pp. 1 – 10

Abstract

Read online

Abstract Purpose To explore the association between preoperative WBC count and the long-term survival outcomes and clinical outcomes in different stage patients who underwent surgical resection for colorectal cancer (CRC). Patients and methods A cohort of 8121 Chinese patients who underwent surgical resection for CRC from January 1, 2008 to December 31, 2014 were enrolled as part of the retrospective cohort were retrospectively analyzed. Based on that the preoperative WBC optimal cut-off value was 7*109/L (7,000/µL), the high preoperative WBC group and the low preoperative WBC group was defined. Inverse probability of treatment weighting (IPTW) using the propensity score was used to reduce confounding. The impact of preoperative WBC count on overall survival (OS) and disease-free survival (DFS) was investigated using the Kaplan-Meier method and Univariate Cox proportional hazards models in different stage subgroup respectively. Results After IPTW, the clinical characters in the high preoperative WBC count group and the low preoperative WBC count group were balanced. Kaplan-Meier analysis showed that the 5-year OS rate were significantly lower in the high preoperative WBC count group overall, in stage II and IV. The 5-year DFS rate was significantly lower overall, in stage II and III in the high preoperative WBC count group. High preoperative WBC count was associated with poorer OS overall in stage II and stage IV. Conclusions This study suggests that preoperative WBC count is an independent risk factor for survival in patients undergoing colorectal surgery and may need to consider the stage of cancer when applied to predict long-term adverse outcome prognosis.

Keywords