How to reduce the colorectal anastomotic leakage? The MIRACLe protocol experience in a cohort in a single high-volume centre

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.

Efficacy of Switching to Adalimumab for Maintenance of Remission Following Induction Therapy with Tacrolimus in Patients with Ulcerative Colitis

BACKGROUND

Tacrolimus (TAC) effectively induces remission in refractory ulcerative colitis (UC). However, TAC therapy usually lasts for 3 months. Although azathioprine (AZA) is often used in maintenance therapy, the relapse rate remains high. Herein, we evaluated the efficacy of adalimumab (ADA) for remission maintenance in patients with UC after induction therapy with TAC.

METHODS

We prospectively enrolled patients with moderate-to-severe UC who achieved clinical remission after 3 months of TAC therapy with endoscopic non-mucosal healing (Cohort A). After TAC discontinuation, the remission maintenance rate up to 1 year after starting ADA therapy was examined. We retrospectively enrolled patients with UC treated with TAC (Cohort B). Among patients in clinical remission after TAC treatment for 3 months, those who received AZA as remission maintenance therapy after TAC discontinuation constituted the AZA group. Patients in Cohort A who received ADA and AZA as remission maintenance therapy after TAC discontinuation constituted the ADA + AZA group. We compared the remission maintenance rates in the AZA and ADA + AZA groups for up to 5 years after TAC discontinuation.

RESULTS

In Cohort A, of the 46 patients with UC treated with TAC, 17 were eligible for analysis after receiving ADA as remission maintenance therapy. A notable 88.2% (15/17) were still in remission 1 year after starting ADA. The ADA + AZA group (n = 16) exhibited a significantly higher relapse-free rate than the AZA group (n = 26) (p < 0.05; log-rank test).

CONCLUSION

switching to ADA for remission maintenance in patients with refractory UC who achieved clinical remission with TAC is clinically useful.

Treatment for T1 colorectal cancers substratified by site and size: "horses for courses"

Background

Owing to advances in diagnostic technology, the diagnosis of T1 colorectal cancers (CRCs) continues to increase. However, the optimal management of T1 CRCs in the Western Hemisphere remains unclear due to limited population-based data directly comparing the efficacy of endoscopic therapy (ET) and surgical resection (SR). The purpose of this study was to report outcome data from a large Western cohort of patients who underwent ET or SR for early CRCs.

Methods

The SEER-18 database was used to identify patients with T1 CRCs diagnosed from 2004 to 2018 treated with ET or SR. Multivariable logistic regression models were employed to identify variables related to lymph node metastasis (LNM). Rates of ET and 1-year relative survival were calculated for each year. Effect of ET or SR on overall survival and cancer-specific survival was compared using Kaplan-Meier method stratified by tumor size and site.

Results

A total of 28,430 T1 CRCs patients were identified from 2004 to 2018 in US, with 22.7% undergoing ET and 77.3% undergoing SR. The incidence of T1 CRCs was 6.15 per 100,000 person-years, with male patients having a higher incidence. Left-sided colon was the most frequent location of tumors. The utilization of ET increased significantly from 2004 to 2018, with no significant change in 1-year relative survival rate. Predictors of LNM were age at diagnosis, sex, race, tumor size, histology, grade, and location. The 5-year relative survival rates were 91.4 and 95.4% for ET and SR, respectively. Subgroup analysis showed that OS and CSS were similar between ET and SR in T1N0M0 left-sided colon cancers with tumors 2 cm or less and in rectal cancers with tumors 1 cm or less.

Conclusion

Our study showed that ET was feasible and safe for patients with left-sided T1N0M0 colon cancers and tumors of 2 cm or less, as well as T1N0M0 rectal cancers and tumors of 1 cm or less. Therefore, the over- and under-use of ET should be avoided by carefully selecting patients based on tumor size and site.

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.