Development and Validation of a Predictive Scoring System for Colorectal Cancer Patients With Liver Metastasis: A Population-Based Study

Lymphovascular invasion affects prognosis of colorectal cancer liver metastasis underwent primary resection: a propensity score matching analysis

BACKGROUND

Lymphovascular invasion (LVI) is associated with poor prognosis in a variety of malignancies; however, its prognostic value has not been fully defined in patients with colorectal cancer with liver metastases (CRCLM). The aim of this study was to investigate the impact of LVI on long-term postoperative recurrence and survival in patients with CRCLM.

METHODS

Clinicopathologic data were retrospectively collected from patients who underwent primary resection for CRCLM at Wuhan Union Hospital from 2013 to 2018. To reduce potential confounders and selection bias, we used propensity score matching (PSM) to compare the clinicopathologic characteristics and long-term prognostic outcomes of patients in the LVI (+) and LVI (-) groups. Cox unifactorial and multifactorial analyses were used to screen relevant factors affecting patient prognosis, and Kaplan-Meier curves were plotted to compare differences in patient overall survival (OS) and disease-free survival (DFS). The predictive power of independent factors on patients' long-term prognosis was assessed using receiver operating characteristic ROC) curves and area under the curve (AUC).

RESULTS

After PSM, 230 patients were enrolled in the study (n = 115 per group). Multifactorial analysis revealed that LVI was an independent prognostic factor for OS and DFS (hazard ratio [HR], 1.424; 95% confidence interval [CI], 1.004-2.022; P = 0.048 and HR, 1.452; 95% CI, 1.020-2.069; p = 0.039, respectively). In the LVI (-) group, postoperative chemotherapy did not significantly improve OS or DFS; however, in the LVI (+) group, those who received chemotherapy had significantly improved OS (HR: 1.593, 95% CI: 1.187 - 2.571; P = 0.044) and DFS (HR: 1.503, 95% CI. 1.033 - 2.422; P = 0.045) compared with patients not treated with chemotherapy. In the LVI (+) group, the AUC for the OS AUROC curves was more favorable compared with after PSM (AUC at 3 years: 0.786 vs. 0.903; AUC at 5 years: 0.744 vs. 0.889). For DFS, the area under the AUROC curve was also better in the LVI (+) subgroup compared with after PSM (AUC at 3 years: 0.825 vs. 0.874; AUC at 5 years: 0.839 vs. 0.863).

CONCLUSIONS

LVI may significantly impact long-term survival and prognosis in patients with CRCLM undergoing primary resection, potentially serving as an independent prognostic factor for OS and DFS. Additionally, postoperative chemotherapy appears to significantly improve the long-term prognosis of patients with LVI (+).

Rapid detection of liver metastasis risk in colorectal cancer patients through blood test indicators

Introduction

Colorectal cancer (CRC) is one of the most common malignancies, with liver metastasis being its most common form of metastasis. The diagnosis of colorectal cancer liver metastasis (CRCLM) mainly relies on imaging techniques and puncture biopsy techniques, but there is no simple and quick early diagnosisof CRCLM.

Methods

This study aims to develop a method for rapidly detecting the risk of liver metastasis in CRC patients through blood test indicators based on machine learning (ML) techniques, thereby improving treatment outcomes. To achieve this, blood test indicators from 246 CRC patients and 256 CRCLM patients were collected and analyzed, including routine blood tests, liver function tests, electrolyte tests, renal function tests, glucose determination, cardiac enzyme profiles, blood lipids, and tumor markers. Six commonly used ML models were used for CRC and CRCLM classification and optimized by using a feature selection strategy.

Results

The results showed that AdaBoost algorithm can achieve the highest accuracy of 89.3% among the six models, which improved to 91.1% after feature selection strategy, resulting with 20 key markers.

Conclusions

The results demonstrate that the combination of machine learning techniques with blood markers is feasible and effective for the rapid diagnosis of CRCLM, significantly im-proving diagnostic ac-curacy and patient prognosis.

Multimodal Management of Colorectal Liver Metastases: State of the Art

Liver is the most common site of colorectal cancer (CRC) metastases. Treatment of CRC liver metastases (CRLM) includes different strategies, prevalently based on the clinical and oncological intent. Valid approaches in liver-limited or liver-prevalent disease include surgery, percutaneous ablative procedures (radiofrequency ablation, microwave ablation), intra-arterial perfusional techniques (chemo-embolization, radio-embolization) as well as stereotactic radiotherapy. Systemic treatments, including chemotherapy, immunotherapy and other biological agents, are the only options for patients with no chance of locoregional approaches. The use of chemotherapy in other settings, such as neoadjuvant, adjuvant or conversion therapy of CRLM, is commonly accepted in the clinical practice, although data from several clinical trials have been mostly inconclusive. The optimal integration of all these strategies, when applicable and clinically indicated, should be ever considered in patients affected by CRLM based on clinical evidence and multidisciplinary experience. Here we revised in detail all the possible therapeutic approaches of CRLM focusing on the current evidences, the studies still in progress and the often contradictory data.

Tumor burden score dictates prognosis of patients with combined hepatocellular cholangiocarcinoma undergoing hepatectomy

BACKGROUND

The prognostic value of the tumor burden score (TBS) in patients with combined hepatocellular-cholangiocarcinoma (cHCC-CCA) remains unknown. This study aimed to investigate the impact of TBS on long-term outcomes after surgery.

METHODS

Patients who underwent radical-intent resection between June 2013 and December 2019 were retrospectively reviewed. Kaplan-Meier curves were used to analyze patient survival, and disease-free survival (DFS) and overall survival (OS) were examined in relation to TBS.

RESULTS

A total of 178 patients were included in this study, with 119 in the training cohort and 59 in the validation cohort. Kaplan-Meier curves showed that TBS was a strong prognostic indicator in patients with cHCC-CCA. Elevated TBS was associated with poorer DFS and OS (both P-value < 0.001) and was identified as an independent prognostic indicator. In addition, the prognostic value of TBS outperformed tumor size and number alone, microvascular invasion, and lymph node invasion. The prognostic significance of TBS was confirmed by the internal validation cohort.

CONCLUSIONS

The present study suggested the significance of tumor morphology in assessing the prognosis of patients with cHCC-CCA who undergoing curative resection. The TBS is a promising prognostic index in patients with cHCC-CCA. Elevated TBS was related to a lower long-term survival rate and was identified as an independent risk factor for poor DFS and OS. Further research is needed to verify our results.

Development and validation of a prognostic scoring system for patients with colorectal cancer hepato-pulmonary metastasis: a retrospective study

BACKGROUND

Hepato-pulmonary metastasis of colorectal cancer (CRC) is a rare disease with poor prognosis. This study aims to establish a highly efficient nomogram model to predict overall survival (OS) and cancer-specific survival (CSS) in patients with colorectal cancer hepato-pulmonary metastasis (CRCHPM).

METHODS

We retrospectively analyzed the data of patients with CRCHPM from SEER database and Wuhan Union Hospital Cancer Center (WUHCC). A total of 1250 CRCHPM patients were randomly assigned to the training, internal validation, and external validation cohorts from 2010 to 2016.Univariate and multivariate cox analysis were performed to identify independent clinicopathological predictors of OS and CSS, and a nomogram was constructed to predict OS and CSS in CRCHPM patients.

RESULTS

A nomogram of OS was constructed based on seven independent predictors of age, degree of differentiation, T stage, chemotherapy, number of lsampled lymph nodes, number of positive lymph nodes, and tumor size. Nomogram showed favorable sensitivity in predicting OS at 1, 3 and 5 years, with area under the receiver operating characteristic curve (AUROC) values of 0.802, 0.759 and 0.752 in the training cohort;0.814, 0.769 and 0.716 in the internal validation cohort;0.778, 0.756 and 0.753 in the external validation cohort, respectively. A nomogram of CSS was constructed based on three independent predictors of T stage, chemotherapy, and tumor size. The AUROC values of 1, 3 and 5 years were 0.709,0.588,0.686 in the training cohort; 0.751, 0.648,0.666 in the internal validation cohort;0.781,0.588,0.645 in the external validation cohort, respectively. Calibration curves, Concordance index (C-index), and decision curve analysis (DCA) results revealed that using our model to predict OS and CSS is more efficient than other single clinicopathological characteristics.

CONCLUSION

A nomogram of OS and CSS based on clinicopathological characteristics can be conveniently used to predict the prognosis of CRCHPM patients.

Nomogram Predicting the Survival of Young-Onset Patients with Colorectal Cancer Liver Metastases

Background: Although the global prevalence of colorectal cancer (CRC) is decreasing, there has been an increase in incidence among young-onset individuals, in whom the disease is associated with specific pathological characteristics, liver metastases, and a poor prognosis. Methods: From 2010 to 2016, 1874 young-onset patients with colorectal cancer liver metastases (CRLM) from the Surveillance, Epidemiology, and End Results (SEER) database were randomly allocated to training and validation cohorts. Multivariate Cox analysis was used to identify independent prognostic variables, and a nomogram was created to predict cancer-specific survival (CSS) and overall survival (OS). Receiver operating characteristic (ROC) curve, C-index, area under the curve (AUC), and calibration curve analyses were used to determine nomogram accuracy and reliability. Results: Factors independently associated with young-onset CRLM CSS included primary tumor location, the degree of differentiation, histology, M stage, N stage, preoperative carcinoembryonic antigen level, and surgery (all p < 0.05). The C-indices of the CSS nomogram for the training and validation sets (compared to TNM stage) were 0.709 and 0.635, and 0.735 and 0.663, respectively. The AUC values for 1-, 3-, and 5-year OS were 0.707, 0.708, and 0.755 in the training cohort and 0.765, 0.735, and 0.737 in the validation cohort, respectively; therefore, the nomogram had high sensitivity, and was superior to TNM staging. The calibration curves for the training and validation sets were relatively consistent. In addition, a similar result was observed with OS. Conclusions: We developed a unique nomogram incorporating clinical and pathological characteristics to predict the survival of young-onset patients with CRLM. This may serve as an early warning system allowing doctors to devise more effective treatment regimens.