A nomogram for disease recurrence following radical resection surgery for colorectal cancer in a Hong Kong tertiary hospital : use of preoperative and postoperative circulating inflammatory markers for prediction of colorectal cancer patient prognosis

Abstract

Colorectal cancer (CRC) is the most commonly diagnosed and the second most common cause of cancer-related death in Hong Kong. Most patients die from tumour relapse or metastatic disease. Radical resection is the main treatment method for stage I-III of CRC. There are currently many approaches to the prediction of the risk of cancer recurrence or metastasis, yet a practical prediction model is still under investigation.

Inflammation can induce proliferation, progression, and metastasis of cancer cells. Inflammatory indicators could be detected even before a tumour begins to grow. The use of inflammatory variables could serve as an earlier marker for prediction of CRC postoperative outcomes.

This study was conducted to evaluate the utility of preoperative and postoperative neutrophil to lymphocyte ratio (NLR), platelet to lymphocyte ratio (PLR), and other inflammatory variables for the prediction of postoperative recurrence risk in patients with CRC. A nomogram was constructed for daily use in clinical practice.

A nested case-control study was performed. A database search was performed to identify CRC patients who underwent potentially curative surgery at the Department of Surgery of The University of Hong Kong; patient records were retrospectively reviewed. Follow-up data for these patients were retrieved from electrical medical records within Hong Kong’s public hospital network; at least 60 months of follow up data were retrieved for each patient (except for early death cases). The preoperative parameters were measured within two weeks before surgery and the postoperative parameters were measured at the first visit after leaving the hospital. Univariate analysis was used to select independent variables for the prediction model. The prediction model was built based on inflammation-related data.

Based on our data, a set of candidate predictors were selected, including cancer staging data, preoperative NLR, preoperative red blood cell distribution width (RDW), preoperative prognostic nutritional index (PNI), postoperative RDW, and proximal margin for potential inclusion in the prognostic model. A nomogram was built based on the survival model using these variables.

The present study used nomogram analysis to establish a system for predicting the survival of CRC patients. These inflammatory markers such as NLR, RDW and PNI are inexpensive to assess, readily available and reliable biomarkers for the prediction of survival in patients with CRC.