Prognostic nomogram for colorectal cancer patients with multi-organ metastases: a Surveillance, Epidemiology, and End Results program database analysis

Abstract

Background: A nomogram that integrates risk models and clinical characteristics can accurately predict the prognosis of individual patients. We aimed to identify the prognostic factors and establish nomograms for predicting overall survival (OS) and cause-specific survival (CSS) in patients with multi-organ metastatic colorectal cancer (CRC).

Methods: Demographic and clinical information on multi-organ metastases from 2010 to 2019 were extracted from the Surveillance, Epidemiology, and End Results (SEER) Program. Univariate and multivariate Cox analyses were used to identify independent prognostic factors that were used to develop nomograms to predict CSS and OS, and to assess the concordance index (C-index), area under the curve (AUC), and calibration curve.

Results: The patients were randomly assigned to the training and validation groups at a 7:3 ratio. A Cox proportional hazards model was conducted for CRC patients to identify independent prognostic factors, including age, sex, tumor size, metastases, degree of differentiation, stage T, stage N, primary and metastasis surgery. The competing risk models employed by Fine and Gray were used to identify the risk factors for CRC. Death from other causes was treated as a competing event, and Cox models were used to identify the factors for death to identify the independent factors of CSS. By incorporating the corresponding independent prognostic factors, we established prognostic nomograms for OS and CSS. Finally, we used the C-index, ROC curve, and calibration plots to assess the utility of the nomogram.

Conclusions: Using the SEER database, we constructed a predictive model for CRC patients with multi-organ metastases. Nomograms provide clinicians with 1-, 3-, and 5-year OS and CSS predictions for CRC, allowing them to formulate appropriate treatment plans.

Keywords: Colorectal cancer; Multi-organ metastases; Nomogram; Prognosis; Surveillance, Epidemiology and End Results.

Fig. 1

The inclusion flowchart of recruited colorectal cancer patients with multi-organ metastases

Fig. 2

Survival curve of CC patients with multi-organ metastasis by age (A), Grade (B), metastasis (C), Sex (D), tumor size (E), stage T (F), stage N (G), Surg prim (H) and surg dis site (I). CC colorectal cancer

Fig. 3

Forest plot of all variables with hazard ratios in CC patients with multi-organ metastasis with OS (A) and CSS (B). CC colorectal cancer, OS overall survival, CSS cancer-specific survival. Age: 1 < 77 years, 2 ≥ 77 years; sex: 1 Male, 2 Female; size: 1 < 36 mm,  ≥  36 mm; Grade: 1 Grade I, 2 Grade II; 3 Grade III, 4 Grade IV; Histype: 1 Adenocarcinomas, 2 cystic, mucinous and serous neoplasms, 3 squamous, 4 Other; Metastases: 1 Liver + Lung, 2 Liver + Bone, 3 Liver + Brain, 4 Lung + Bone, 5 Lung + Brain, 6 Bone + Brain, 7 Liver + Lung + Bone, 8 Liver + Lung + Brain, 9 Liver + Bone + Brain, 10 Lung + Bone + Brain, 11 Liver + Lung + Bone + Brain; T: Stage T: 1 T1, 2 T2, 3 T3, 4 T4; N:Stage N:0 N0, 1 N1, 2 N2, 3 N3; SurgP: Surg prim site: 1 Yes, 2 No; SurgO: Surg dis site: 1 yes; 2 No

Fig. 4

Establishment of nomograms regarding both OS (A) and CSS (B). OS overall survival, CSS cancer-specific survival

Fig. 5

ROC of nomogram using OS of the training group (A–C) and the validation group (D–F) in 1-, 3- and 5-year. TP true positive, FP false positive, ROC receiver operating characteristic, OS overall survival

Fig. 6

Evaluation of calibration plots based on OS of the training group (A–C) and the validation group (D–F) in 1-, 3- and 5-year. OS overall survival