Treatment sequencing of metastatic colorectal cancer based on primary tumor location

Primary site and treatment impact in unresectable metastatic colorectal cancer

INTRODUCTION

Colorectal cancer is a heterogenous disease, with various clinical and molecular subtypes related to the primary site (left versus right colon) of the original tumour. Primary colon tumour side is both a prognostic and predictive marker in metastatic colorectal cancer.

AREAS COVERED

There is an increasing body of evidence for how primary site may impact treatment decisions in metastatic colorectal cancer. We reviewed the evidence for its prognostic and predictive value.

EXPERT OPINION

Primary site is a prognostic marker in metastatic colorectal cancer, with right colon tumours being associated with more aggressive disease behaviour and poorer outcomes. Primary site also appears to predict for outcomes to various treatments, in particular anti-EGFR antibodies. As our understanding and testing of the molecular and biological differences within colorectal cancer increases beyond primary site, this should be integrated into the current treatment algorithm to ensure an individualised patient-centred approach to care.

Establishment and validation of a prognostic nomogram for patients with early-onset stage I–II colon cancer

Background

The aims of this study were to establish and validate a nomogram model for predicting the survival of patients with early-onset stage I–II colon cancer (CC).

Methods

Data of eligible patients enrolled from 2012 to 2015 were extracted from the Surveillance, Epidemiology, and End Results (SEER) database. Patients were randomly allocated to training and validation groups in a 7:3 ratio. Significant prognostic factors were identified by univariate and multivariate analysis and a nomogram model constructed. The predictive performance of the nomogram was evaluated by the concordance index (C-index), calibration plots, and decision curve analysis.

Results

Our study cohort comprised 3528 early-onset CC patients with stage I–II disease, 2469 of whom were allocated to the training cohort and 1059 to the validation cohort. Race, age, marital status, tumor grade, tumor size, tumor stage (T stage), and chemotherapy were considered the significant predictor by univariate analysis. Race, marital status, and T stage were found to be independent prognostic factors by multivariate analysis. The C-indexes of the nomogram were 0.724 and 0.692 in the training and validation cohorts, respectively. Likewise, the calibration plots showed good agreement regarding the probability of 3- and 5-year observed and nomogram-predicted overall survival in the training group. Decision curve analysis showed that the nomogram model was clinically practical and effective. Moreover, applying the nomogram enabled dividing of the patients into two cohorts with different risk scores. The low-risk group thus created had a better survival than the high-risk group.

Conclusions

We developed and validated a meaningful prognostic nomogram model for patients with early-onset stage I–II CC that clinicians can use to make better decisions for individual patients.