Preoperative nomogram to predict survival following colorectal cancer liver metastasis simultaneous resection

A nomogram for predicting colorectal cancer liver metastasis using circulating tumor cells from the first drainage vein

PURPOSE

To use circulating tumor cells (CTC) from the first drainage vein (FDV) of the primary lesion and other clinically relevant parameters to construct a nomogram for predicting liver metastasis in colorectal cancer (CRC) patients, and to provide a theoretical basis for clinical diagnosis and treatment.

METHODS

Information from 343 CRC patients was collected and a database was established. Multivariate logistic analysis was used to identify independent factors for colorectal cancer liver metastasis(mCRC) and nomograms were constructed. Receiver operating characteristic curves(ROC), calibration plots, and decision curve analysis (DCA) were used to assess discrimination, agreement with actual risk, and the clinical utility of the prediction model, respectively.

RESULT

CTC levels in FDV were significantly higher in patients with liver metastasis than in those without liver metastasis. Logistic multivariate analysis showed that vascular invasion, T stage, carcinoembryonic antigen (CEA), CA19-9, and CTC could be used as predictors to construct nomograms. The nomograms showed good discriminatory ability in predicting mCRC, with area under the curve (AUC) values of 0.871 [95 % CI: 0.817-0.924) and 0.891 (95 % CI: 0.817-0.964) for the training and validation sets, respectively.] The calibration curves of both the training and validation sets showed that the model was effective in predicting the probability of mCRC. DCA was used to evaluate this predictive model and showed good net clinical benefit.

CONCLUSION

We developed and validated a nomogram model based on the combination of CTC in the FDV with other clinical parameters to better predict the occurrence of mCRC.

Meta-analysis of the prognostic value of serum carcinoembryonic antigen in patients with colorectal cancer liver metastases after hepatectomy

OBJECTIVES

Carcinoembryonic antigen (CEA) is a broad-spectrum tumor marker for differential diagnosis, monitoring, and response assessment of a variety of malignancies. This meta-analysis was aimed at evaluating whether serum CEA could predict the prognosis in patients with colorectal cancer liver metastasis (CRCLM) before and after liver resection (LR).

METHODS

PubMed, Embase, Cochrane, and Web of Science were systematically searched to retrieve literature, with a search cutoff date of 27 February 2023. Articles were strictly screened for inclusion according to pre-specified inclusion and exclusion criteria. Data were pooled and analyzed using Stata 16.0.

RESULTS

This meta-analysis included 36 studies involving a total of 11 143 CRCLM patients. The results showed that a high pre-LR serum CEA level was correlated with poor overall survival (OS: HR = 1.61, 95% CI = 1.49-1.75, P  < 0.001) and recurrence-free survival (RFS: HR = 1.27, 95% CI = 1.11-1.45, P  < 0.001) in CRCLM patients. A high post-LR serum CEA level predicted poor overall survival (OS: HR = 2.66, 95% CI = 2.10-3.38, P  < 0.001).

CONCLUSION

High preoperative and postoperative serum CEA levels in patients with CRCLM were significantly associated with poor prognosis, independent of treatment modality, mode of analysis, case origin, and cutoff value classification.

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

Colorectal liver metastasis (CRLM) is a disease entity that warrants special attention due to its high frequency and potential curability. Identification of "high-risk" patients is increasingly popular for risk stratification and personalization of the management pathway. Traditional regression-based methods have been used to derive prediction models for these patients, and lately, focus has shifted to artificial intelligence-based models, with employment of variable supervised and unsupervised techniques. Multiple endpoints, like overall survival (OS), disease-free survival (DFS) and development or recurrence of postoperative complications have all been used as outcomes in these studies. This review provides an extensive overview of available clinical prediction models focusing on the prognosis of CRLM and highlights the different predictor types incorporated in each model. An overview of the modelling strategies and the outcomes chosen is provided. Specific patient and treatment characteristics included in the models are discussed in detail. Model development and validation methods are presented and critically appraised, and model performance is assessed within a proposed framework.

Prognostic role of serum carcinoembryonic antigen in patients receiving liver resection for colorectal cancer liver metastasis: A meta-analysis

BACKGROUND

Carcinoembryonic antigen (CEA) is a broad-spectrum tumor marker for differential diagnosis, monitoring, and response assessment of a variety of malignancies.

AIM

To evaluate whether serum CEA could predict the prognosis in patients with colorectal cancer liver metastasis (CRCLM) before and after liver resection (LR).

METHODS

PubMed, Embase, Cochrane, and Web of Science were systematically searched to retrieve literature, with a search cut-off date of February 27, 2023. Articles were strictly screened for inclusion according to pre-specified inclusion and exclusion criteria. Data were pooled and analyzed using Stata 16.0.

RESULTS

This meta-analysis included 36 studies involving a total of 11143 CRCLM patients. The results showed that a high pre-LR serum CEA level was correlated with poor overall survival (OS) [hazard ratio (HR) = 1.61, 95% confidence interval (CI): 1.49-1.75, P < 0.001] and recurrence-free survival (HR = 1.27, 95%CI: 1.11-1.45, P < 0.001) in CRCLM patients. A high post-LR serum CEA level predicted poor OS (HR = 2.66, 95%CI: 2.10-3.38, P < 0.001). A comparison by treatment modality, analysis modality, patient source, and cutoff-value showed that overall, high preoperative and postoperative serum CEA levels remained correlated with a poor prognosis.

CONCLUSION

This study concluded that high pre-LR and post-LR serum CEA levels were significantly correlated with a poor prognosis in CRCLM patients.

Real-World Results of Raltitrexed Combined with S-1 and Bevacizumab in Heavily Pretreated Metastatic Colorectal Cancer

Purpose

Treatment options for refractory metastatic colorectal cancer (CRC) are scarce. This retrospective study aimed to evaluate the efficacy and safety of raltitrexed combined with S-1 and bevacizumab in patients with heavily pretreated metastatic CRC in a clinical real-world setting.

Patients and Methods

Records of patients with metastatic CRC refractory to standard therapies who initiated raltitrexed plus S-1 and bevacizumab from October 2017 to December 2021 were retrospectively reviewed at our institution. The study endpoints included median overall survival (OS), overall response rate (ORR), progression-free survival (PFS), disease control rate (DCR), and adverse events (AEs).

Results

Forty-four patients with metastatic CRC, who had previously undergone standard chemotherapy received the regimen comprising raltitrexed plus S-1 and bevacizumab. As of March 2022, the median follow-up was 23.2 months (95% confidence interval 15.8-30.6). The median OS and median PFS were 13.5 (95% CI 9.9-17.1) and 4.7 months (95% CI 3.6-5.8), respectively, with a 16-week PFS rate of 60.9%. Among 43 patients with measurable lesions, the ORR and DCR were 7.0% (3/43) and 65.1% (28/43), respectively. Patients without peritoneal metastases (P = 0.003, hazard ratio 0.160, 95% CI 0.048-0.531), lower carcinoembryonic antigen level (≤42.8 ng/mL) (P = 0.039, HR 0.382, 95% CI 0.153-0.952), and no previous treatment with both vascular endothelial growth factor inhibitors (VEGF) and S-1 (P = 0.020, HR 0.215, 95% CI 0.059-0.785) had better OS. The incidence of any grade of treatment-related AEs was 88.6%, most of which were mild to moderate, and no treatment-related deaths occurred.

Conclusion

Raltitrexed combined with S-1 and bevacizumab shows promising antitumor activity and safety and could be an alternative for patients with metastatic CRC who are refractory or intolerant to standard therapy.

Predicting metachronous liver metastasis in patients with colorectal cancer: development and assessment of a new nomogram

Background

We aimed to develop and validate a nomogram model, which could predict metachronous liver metastasis in colorectal cancer within two years after diagnosis.

Methods

A retrospective study was performed on colorectal cancer patients who were admitted to Beijing Shijitan Hospital from January 1, 2016 to June 30, 2019. The least absolute shrinkage and selection operator (LASSO) regression model was used to optimize feature selection for susceptibility to metachronous liver metastasis in colorectal cancer. Multivariable logistic regression analysis was applied to establish a predictive model through incorporating features selected in the LASSO regression model. C-index, receiver operating characteristic (ROC) curve, calibration plot, and decision curve analysis (DCA) were employed to assess discrimination, distinctiveness, consistency with actual occurrence risk, and clinical utility of candidate predictive model. Internal validation was assessed with bootstrapping method.

Results

Predictors contained in candidate prediction nomogram included age, CEA, vascular invasion, T stage, N stage, family history of cancer, and KRAS mutation. This model displayed good discrimination with a C-index of 0.787 (95% confidence interval: 0.728–0.846) and good calibration, whereas area under the ROC curve (AUC) of 0.786. Internal validation obtained C-index of 0.786, and AUC of validation cohort is 0.784. Based on DCA, with threshold probability range from 1 to 60%; this predictive model might identify colorectal cancer metachronous liver metastasis to achieve a net clinical benefit.

Conclusion

We have developed and validated a prognostic nomogram with good discriminative and high accuracy to predict metachronous liver metastasis in CRC patients.