Cancer Medicine (Apr 2020)

Nomogram for predicting overall survival in stage II‐III colorectal cancer

  • Jungang Liu,
  • Xiaoliang Huang,
  • Wenkang Yang,
  • Chan Li,
  • Zhengtian Li,
  • Chuqiao Zhang,
  • Shaomei Chen,
  • Guo Wu,
  • Weishun Xie,
  • Chunyin Wei,
  • Chao Tian,
  • Lingxu Huang,
  • Franco Jeen,
  • Xianwei Mo,
  • Weizhong Tang

DOI
https://doi.org/10.1002/cam4.2896
Journal volume & issue
Vol. 9, no. 7
pp. 2363 – 2371

Abstract

Read online

Abstract Purpose The overall survival (OS) of patients diagnosed with stage II‐III colorectal cancer (CRC) can vary greatly, even between patients with the same tumor stage. We aimed to design a nomogram to predict OS in resected, stage II‐III CRC and stratify patients with CRC into different risk groups. Patients and Methods Based on data from 873 patients with CRC, we used univariate Cox regression analysis to select the significant prognostic features, which were subjected to the least absolute shrinkage and selection operator (LASSO) regression algorithm for feature selection. Cross‐validation was used to confirm suitable tuning parameters (λ) for LASSO logistic regression. Then, the nomogram was used to estimate 3‐ and 5‐year OS based on the multivariable Cox regression model. The survival curves of the two groups were produced using the Kaplan‐Meier method. Risk group stratification was performed to assess the predictive capacity of the nomogram. Results Preoperative mean platelet volume, preoperative platelet distribution width, monocytes, and postoperative adjuvant chemotherapy were identified as independent prognostic factors by LASSO regression and integrated for the construction of the nomogram. The nomogram provided good discrimination, with C‐indices of 0.67 and 0.69 for the training and validation sets, respectively. Calibration plots illustrated excellent agreement between the nomogram predictions and actual observations for 3‐ and 5‐year OS. Moreover, a significant difference in OS was shown between patients stratified into different risk groups (P < .001). Conclusion We constructed and validated an original predictive nomogram for OS in patients with CRC after surgery, facilitating physicians to appraise the individual survival of postoperative patients accurately and identify high‐risk patients who need more aggressive treatment and follow‐up strategies.

Keywords