Prognostic impact of tumor size on patients with metastatic colorectal cancer: a large SEER-based retrospective cohort study

The role of superior hemorrhoidal vein ectasia in the preoperative staging of rectal cancer

Objective

The prognosis of colorectal cancer has continuously improved in recent years thanks to continuous progress in both the therapeutic and diagnostic fields. The specific objective of this study is to contribute to the diagnostic field through the evaluation of the correlation between superior hemorrhoidal vein (SHV) ectasia detected on computed tomography (CT) and Tumor (T), Node (N), and distant metastasis (M) examination and mesorectal fascia (MRF) invasion in the preoperative staging of rectal cancer.

Methods

Between January 2018 and April 2022, 46 patients with histopathological diagnosis of rectal cancer were retrospectively enrolled, and the diameter of the SHV was evaluated by CT examination. The cutoff value for SHV diameter used is 3.7 mm. The diameter was measured at the level of S2 during portal venous phase after 4× image zoom to reduce the interobserver variability. The parameters evaluated were tumor location, detection of MRF infiltration (defined as the distance < 1 mm between the tumor margins and the fascia), SHV diameter, detection of mesorectal perilesional lymph nodes, and detection of metastasis.

Results

A total of 67.39% (31/46) of patients had SHV ectasia. All patients with MRF infiltration (4/46, 7.14%) presented SHV ectasia (average diameter of 4.4 mm), and SHV was significantly related with the development of liver metastases at the moment of primary staging and during follow-up.

Conclusion

SHV ectasia may be related to metastasis and MRF involvement; therefore, it could become a tool for preoperative staging of rectal cancer.

Correlation between abdominal computed tomography signs and postoperative prognosis for patients with colorectal cancer

BACKGROUND

Patients with different stages of colorectal cancer (CRC) exhibit different abdominal computed tomography (CT) signs. Therefore, the influence of CT signs on CRC prognosis must be determined.

AIM

To observe abdominal CT signs in patients with CRC and analyze the correlation between the CT signs and postoperative prognosis.

METHODS

The clinical history and CT imaging results of 88 patients with CRC who underwent radical surgery at Xingtan Hospital Affiliated to Shunde Hospital of Southern Medical University were retrospectively analyzed. Univariate and multivariate Cox regression analyses were used to explore the independent risk factors for postoperative death in patients with CRC. The three-year survival rate was analyzed using the Kaplan-Meier curve, and the correlation between postoperative survival time and abdominal CT signs in patients with CRC was analyzed using Spearman correlation analysis.

RESULTS

For patients with CRC, the three-year survival rate was 73.86%. The death group exhibited more severe characteristics than the survival group. A multivariate Cox regression model analysis showed that body mass index (BMI), degree of periintestinal infiltration, tumor size, and lymph node CT value were independent factors influencing postoperative death (P < 0.05 for all). Patients with characteristics typical to the death group had a low three-year survival rate (log-rank χ 2 = 66.487, 11.346, 12.500, and 27.672, respectively, P < 0.05 for all). The survival time of CRC patients was negatively correlated with BMI, degree of periintestinal infiltration, tumor size, lymph node CT value, mean tumor long-axis diameter, and mean tumor short-axis diameter (r = -0.559, 0.679, -0.430, -0.585, -0.425, and -0.385, respectively, P < 0.05 for all). BMI was positively correlated with the degree of periintestinal invasion, lymph node CT value, and mean tumor short-axis diameter (r = 0.303, 0.431, and 0.437, respectively, P < 0.05 for all).

CONCLUSION

The degree of periintestinal infiltration, tumor size, and lymph node CT value are crucial for evaluating the prognosis of patients with CRC.

Impact of tumor size on overall survival and cancer-specific survival of early-onset colon and rectal cancer: a retrospective cohort study

PURPOSE

This study aimed to investigate the impact of tumor size on survival in early-onset colon and rectal cancer.

METHODS

Early-onset colon and rectal cancer patients were identified from the Surveillance, Epidemiology, and End Results (SEER) database between 2004 and 2015. Tumor size was analyzed as both continuous and categorical variables. Several statistical techniques, including restricted cubic spline (RCS), Cox proportional hazard model, subgroup analysis, propensity score matching (PSM), and Kaplan-Meier survival analysis, were employed to demonstrate the association between tumor size and overall survival (OS) and cancer-specific survival (CSS) of early-onset colon and rectal cancer.

RESULTS

Seventeen thousand five hundred fifty-one (76.7%) early-onset colon and 5323 (23.3%) rectal cancer patients were included. RCS analysis confirmed a linear association between tumor size and survival. Patients with a tumor size > 5 cm had worse OS and CSS, compared to those with a tumor size ≤ 5 cm for both early-onset colon and rectal cancer. Notably, subgroup analysis showed that a smaller tumor size (≤ 50 mm) was associated with worse survival in stage II early-onset colon cancer, although not statistically significant. After PSM, Kaplan-Meier survival curves showed that the survival of patients with tumor size ≤ 50 mm was better than that of patients with tumor size > 50 mm.

CONCLUSION

Patients with tumors larger than 5 cm were associated with worse survival in early-onset colon and rectal cancer. However, smaller tumor size may indicate a more biologically aggressive phenotype, correlating with poorer survival in stage II early-onset colon cancer.

Prognostic Assessment of Colorectal Cancer Patients after Laparoscopic Surgery: A Comprehensive Evaluation of the Glasgow Prognostic Score and Fibrinogen-to-Prealbumin Ratio

BACKGROUND Previous studies have shown that systemic inflammation and suboptimal nutritional status are associated with poor cancer prognosis. This study aims to investigate the prognostic value of preoperative Glasgow prognostic score (GPS) and fibrinogen-to-prealbumin ratio (FPR) in patients with CRC (colorectal cancer) after laparoscopic surgery. MATERIAL AND METHODS In this study, the clinical data of 112 patients with CRC who underwent laparoscopic surgery were retrospectively analyzed, and the 3-year and 5-year survival rates of these patients were evaluated. In addition, the prognostic role of preoperative FPR and GPS in CRC patients was assessed using X-tile software, Kaplan-Meier analysis, and Cox regression analysis. Receiver operating characteristic (ROC) curves were generated to assess the predictive value of FPR, GPS, and FPR-GPS for the survival of these patients. RESULTS The results revealed a significant negative correlation between high FPR, elevated GPS, and overall survival (OS) in patients with CRC. Univariate and multivariate Cox regression analyses identified GPS (HR=3.207, 95% CI: 1.746~6.126), FPR (HR=2.669, 95% CI: 1.052~6.772), and lymph node metastasis (HR=2.222, 95% CI: 1.199~4.115) as independent prognostic indicators for overall survival. The ROC analysis demonstrated that the prediction based on FPR and GPS outperformed a single indicator in accurately predicting the prognosis of CRC patients. CONCLUSIONS Combining the preoperative FPR with the GPS contributes to accurate prognosis assessment for CRC patients after laparoscopic surgery. Patients exhibiting high FPR and GPS values are associated with a worse prognosis.

Colorectal Cancer: Current Updates and Future Perspectives

Colorectal cancer is a frequent neoplasm in western countries, mainly due to dietary and behavioral factors. Its incidence is growing in developing countries for the westernization of foods and lifestyles. An increased incidence rate is observed in patients under 45 years of age. In recent years, the mortality for CRC is decreased, but this trend is slowing. The mortality rate is reducing in those countries where prevention and treatments have been implemented. The survival is increased to over 65%. This trend reflects earlier detection of CRC through routine clinical examinations and screening, more accurate staging through advances in imaging, improvements in surgical techniques, and advances in chemotherapy and radiation. The most important predictor of survival is the stage at diagnosis. The screening programs are able to reduce incidence and mortality rates of CRC. The aim of this paper is to provide a comprehensive overview of incidence, mortality, and survival rate for CRC.

Development and validation of prognostic nomograms for early-onset colon cancer in different tumor locations: a population-based study

OBJECTIVE

The prevalence of early-onset colon cancer (EOCC) among individuals below the age of 50 has shown a marked upward trend in recent years. The embryology, clinical symptoms, incidence, molecular pathways, and oncologic outcomes differ between right-sided and left-sided colon cancers. However, the differences have not been fully researched in EOCC. Our study aims to develop and validate prognostic nomograms predicting overall survival (OS) and cancer-specific survival (CSS) for EOCC in different tumor locations based on the Surveillance, Epidemiology, and End Results (SEER) database.

METHODS

Using the SEER database, a total of 5,588 patients with EOCC were extracted and divided into development and validation cohorts in a random allocation ratio of 7:3 across three groups. Univariate and multivariate Cox regression analyses were performed to identify independent prognostic factors influencing OS and CSS outcomes. These factors were then utilized to construct nomogram models. The prognostic capabilities of the three models were assessed through various evaluation metrics, including the concordance index (C-index), receiver operating characteristic (ROC) curves, calibration curves, decision curve analysis (DCA), and validation cohorts respectively. Additionally, survival curves of the low- and high-risk groups were calculated using the Kaplan-Meier method together with the log-rank test.

RESULTS

Significant differences in clinical features were observed between right-sided and left-sided EOCCs, particularly in terms of OS (52 months vs 54 months) as demonstrated by Kaplan-Meier curves. Transverse-sided EOCCs exhibited clinical characteristics similar to right-sided EOCCs, suggesting a potential shared tumor microenvironment and therapeutic considerations. Advanced stage, liver metastasis, poor grade, elevated pretreatment carcinoembryonic antigen (CEA) level, chemotherapy, and perineural invasion were identified as independent prognostic factors across all three tumor locations and were incorporated into the nomogram model. Nomograms were constructed to predict the probability of 3- and 5-year OS and CSS. The C-index and calibration plots showed that the established nomograms had good consistency between actual clinical observations and predicted outcomes. ROC curves with calculated area under the curve (AUC) values exceeded 0.8 for all three groups in both the development and validation cohorts, indicating robust predictive performance for OS and CSS. Furthermore, decision curve analysis (DCA) plots revealed a threshold probability range of 0.1 to 0.9, within which the nomogram model exhibited maximum benefit. Kaplan-Meier curves exhibited significant differences between the low- and high-risk groups in EOCC for all three tumor locations in OS and CSS, further validating the prognostic value of the nomogram models.

CONCLUSIONS

We successfully developed three precise nomogram models for EOCCs in different tumor locations, providing valuable support for clinicians in guiding clinical treatments and facilitating further prospective follow-up studies.

Artificial Intelligence to Early Predict Liver Metastases in Patients with Colorectal Cancer: Current Status and Future Prospectives

BACKGROUND

Artificial Intelligence (AI)-based analysis represents an evolving medical field. In the last few decades, several studies have reported the diagnostic efficiency of AI applied to Computed Tomography (CT) and Magnetic Resonance Imaging (MRI) to early detect liver metastases (LM), mainly from colorectal cancer. Despite the increase in information and the development of different procedures in several radiological fields, an accurate method of predicting LM has not yet been found. This review aims to compare the diagnostic efficiency of different AI methods in the literature according to accuracy, sensibility, precision, and recall to identify early LM.

METHODS

A narrative review of the literature was conducted on PubMed. A total of 336 studies were screened.

RESULTS

We selected 17 studies from 2012 to 2022. In total, 14,475 patients were included, and more than 95% were affected by colorectal cancer. The most frequently used imaging tool to early detect LM was found to be CT (58%), while MRI was used in three cases. Four different AI analyses were used: deep learning, radiomics, machine learning, and fuzzy systems in seven (41.18%), five (29.41%), four (23.53%), and one (5.88%) cases, respectively. Four studies achieved an accuracy of more than 90% after MRI and CT scan acquisition, while just two reported a recall rate ≥90% (one method using MRI and CT and one CT).

CONCLUSIONS

Routinely acquired radiological images could be used for AI-based analysis to early detect LM. Simultaneous use of radiomics and machine learning analysis applied to MRI or CT images should be an effective method considering the better results achieved in the clinical scenario.