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

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.

Personalizing prognostic prediction in early-onset Colorectal Cancer

“…External validation is an indispensable step which integrates the nomogram into the different study population [39]. External validation could detect the generalizability of the survival nomogram and ultimately avoid poor goodness-of-fit [40]. The survival nomogram obtained an acceptable predictive performance in RHWU validation set, indicating that our nomogram possessed favorable generalizability.…”

Prediction of cancer-specific survival and overall survival in middle-aged and older patients with rectal adenocarcinoma using a nomogram model

“…Most previous studies presenting prediction models for colorectal cancer-related survival had limited samples and included data from a single center. The included predictors were limited, or the evaluation indicators were not easy to obtain, greatly limiting the clinical application of these models [ 9 , 10 ]. In addition, the study endpoint was limited to a single prediction of CSS or OS for some studies [ 11 , 12 ], and few studies have been constructed to predict both.…”

A Combined Epithelial Mesenchymal Transformation and DNA Repair Gene Panel in Colorectal Cancer With Prognostic and Therapeutic Implication

“…5-fluorouracil (5-Fu) based chemotherapy is commonly used in convention chemotherapy of CRC ( 36 ). The 5-Fu resistance is partially induced by EMT via the Akt gene or mediated by Twist, miR-200c, miR-141 ( 26 , 34 ). Besides, down-regulation of EMT-related miR-200c and miR-141 could induced resistance to oxaliplatin, which is one of the most common drugs in CRC chemotherapy ( 37 ).…”

“…The regression coefficients estimated by LASSO are sparse and many components are exactly zero. Thus, LASSO automatically deletes unnecessary covariates ( 25 , 26 ). 10-fold cross validation was used to confirm the suitable tuning parameter (λ) for LASSO regression.…”