Survival nomograms for simultaneous resection of primary and hepatic lesions without neoadjuvant chemotherapy in patients with resectable colorectal liver metastasis

Abstract

BackgroundNo well‐performing nomogram has been developed specifically to predict individual‐patient cancer‐specific survival (CSS) and overall survival (OS) among patients with resectable colorectal liver metastasis (CRLM) who undergo simultaneous resection of primary and hepatic lesions without neoadjuvant chemotherapy (NAC). We aim to investigate the prognosis of patients with resectable CRLM undergoing simultaneous resection of primary and hepatic lesions without NAC.MethodsData of patients with CRLM in the Surveillance, Epidemiology and End Results Program (cohort, n = 225) were collected as the training set, and data of patients with CRLM treated at the National Cancer Center (cohort, n = 180) were collected as the validation set. The prognostic value of the clinicopathological parameters in the training cohort was assessed using Kaplan‒Meier curves and univariate and multivariate Cox proportional hazards models, and OS and CSS nomograms integrated with the prognostic variables were constructed. Calibration analyses, receiver operating characteristic (ROC) curves, and decision curve analyses (DCAs) were then performed to evaluate the performance of the nomograms.ResultsThere was no collinearity among the collected variables. Three factors were associated with OS and CSS: the pretreatment carcinoembryonic antigen (CEA) concentration, pathologic N (pN) stage, and adjuvant chemotherapy (each p < 0.05). OS and CSS nomograms were constructed using these three parameters. The calibration plots revealed favorable agreement between the predicted and observed outcomes. The areas under the ROC curves were approximately 0.7. The DCA plots revealed that both nomograms had satisfactory clinical benefits. The ROC curves and DCAs also confirmed that the nomogram surpassed the tumor, node, and metastasis staging system.ConclusionThe herein‐described nomograms containing the pretreatment CEA concentration, pN stage, and adjuvant chemotherapy may be effective models for predicting postoperative survival in patients with CRLM.

Clinical Prediction Models for Prognosis of Colorectal Liver Metastases: A Comprehensive Review of Regression-Based and Machine Learning Models

“…Six recent Asian studies focused on patients undergoing simultaneous resections of the primary and metastatic tumours [37,[51][52][53]72,82]. Outcomes studied included OS [53,82], CSS [82], PFS [37,51], recurrence [37,72], serious postoperative complications [52] and presence of lymph node (LN) metastases [51].…”

“…Six recent Asian studies focused on patients undergoing simultaneous resections of the primary and metastatic tumours [37,[51][52][53]72,82]. Outcomes studied included OS [53,82], CSS [82], PFS [37,51], recurrence [37,72], serious postoperative complications [52] and presence of lymph node (LN) metastases [51]. The latter was unique as an outcome of choice since a positive primary LN status is a strong predictor of poor outcomes in CRLM patients in many studies.…”

“…The latter was unique as an outcome of choice since a positive primary LN status is a strong predictor of poor outcomes in CRLM patients in many studies. All models were based on regression-based techniques, and notably, two of the studies performed a decision curve analysis (DCA) [72,82]. In the study by Deng et al, clinical utility was found in only a narrow range of risk thresholds [72], while Jiang et al demonstrated superior net benefit of their model compared to AJCC stage [82].…”