Do tumor localization, microsatellite instability and mismatch repair deficiency have an impact on the prognosis of colorectal cancer?

Factors Affecting Recurrence and Survival in Stage IIA Colon Cancer Patients

INTRODUCTION

Our study delves into the intricate interplay of risk factors and the strategic selection of adjuvant therapy, scrutinizing their influence on recurrence and survival outcomes in stage IIA (T3N0M0) colon cancer patients.

MATERIALS AND METHODS

The study examined the medical records of patients who underwent surgery for stage IIA colon cancer. Identification of stage IIA (pT3N0M0) colon cancer involved a comprehensive review of postoperative clinical records and histological reports. Parameters such as demographic data, tumor characteristics, microsatellite instability status, tumor locations, recurrence risk factors, preoperative carcinoembryonic antigen levels, and adjuvant treatments were systematically evaluated.

RESULTS

In our study involving 220 patients, 138 were male (62.7%), with a median age of 62 years and a median body mass index of 25.1 kg/m2. In the patient group without risk factors, no statistically significant difference was detected in disease-free survival (DFS) rates between those who received treatment and those who did not (p = 0.546). DFS rates of patients with >1 risk factor were statistically significantly lower than those with a single risk factor (p = 0.017). In patients with >1 risk factor, the DFS of those who did not receive adjuvant treatment was significantly lower than those who received adjuvant treatment (p < 0.001). In the patient group with recurrence, when adjuvant treatments were considered, recurrence was significantly higher in the group receiving capecitabine (p = 0.01).

CONCLUSION

The decision for adjuvant chemotherapy in stage IIA colon cancer patients involves careful consideration of various parameters and risk factors. The evolving landscape of research may refine recommendations, ensuring optimal treatment outcomes while minimizing unnecessary toxicity.

An integrative clinical and CT-based tumoral/peritumoral radiomics nomogram to predict the microsatellite instability in rectal carcinoma

BACKGROUND

Microsatellite instability (MSI) is detected in approximately 15% of colorectal carcinoma (CRC) patients, which has emerged as a predictor of patient response to adjuvant chemotherapy. Rectal carcinoma (RC) is the most common type of CRC. Therefore, prediction of MSI status of RC is significant for personalized medication. The purpose of this article was to develop an integrative model that combines clinical characteristics and computed tomography-based (CT-based) tumoral/peritumoral radiomics to predict the MSI status in RC.

METHODS

A cohort of 788 RCs with 97 high-MSI status (MSI-H) and 691 microsatellite stable status (MSS) were enrolled between January 2015 and January 2021 in this retrospective study. Clinical characteristics were recorded, and CT-based tumoral/peritumoral radiomic features were calculated after segmenting volume of interests. The patients were randomly divided into training and validation sets in a 7:3 proportion. Logistic models of single tumoral radiomics (LM-tRadio), peritumoral radiomics (LM-ptRadio), and combined tumoral/peritumoral radiomics (LM-Radio) were constructed to distinguish MSI-H from MSS, and a relevant radiomic score was calculated. An integrative nomogram (LM-Nomo) was developed, including significant clinical characteristics and CT-based tumoral/peritumoral radiomics. The area under receiver operator curve (AUC) was calculated to evaluate the efficacy of prediction.

RESULTS

The AUCs of LM-Radio were 0.785 (95%CI 0.732-0.837) in the training set and were 0.628 (95%CI 0.528-0.723) in the validation set, which were higher than those of LM-tRadio and LM-ptRadio. The AUCs of single LM-ptRadio were slightly higher than those of LM-tRadio (0.724 vs. 0.708 in the training set, 0.613 vs. 0.602 in the validation set). The LM-Nomo containing carcinoembryonic antigen (CEA), hypertension, and CT-based tumoral/peritumoral radiomic score showed the highest AUCs of 0.796 (95%CI 0.748-0.843) in the training set and 0.679 (95%CI 0.588-0.771) in the validation set in predicting the MSI-H status of RC.

CONCLUSION

The AUCs of LM-ptRadio were slightly higher than LM-tRadio to evaluate the MSI-H status of RC. The LM-Nomo, which includes significant clinical characteristics and CT-based tumoral/peritumoral radiomics score, demonstrated the best performance in predicting MSI-H status of RC.