Purpose: Previous studies have demonstrated that the serum creatinine level and skeletal muscle index (SMI) (correlated with the overall survival [OS] of patients with colorectal cancer [CRC]). However, the combined significance of these 2 factors is not fully understood. The goal of this study was to investigate the prognostic potential of the combination of these two factors in patients with CRC. Methods: The patients were categorized into subgroups based on preoperative serum creatinine level, with a cut-off value of 1.01 mg/dL for males and 0.80 mg/dL for females. The patients were further categorized into 4 groups based on SMI. Data were analyzed using the Cox proportional hazards model and Harrell’s concordance index (C-index). Results: Poor 5-year OS was observed in patients with high SMI and high serum creatinine levels (hazard ratio [HR]=1.676, 95% confidence interval [CI]=1.110–2.529, P=0.013), low SMI and low serum creatinine levels (HR=1.916, 95% CI=1.249–2.938, P=0.002), and low SMI and high serum creatinine levels (HR=2.172, 95% CI=1.279–3.687, P=0.004) compared to those of patients with high SMI and low serum creatinine levels. Grouping patients based on both SMI and serum creatinine levels led to improved prognostic stratification (C-index, 0.626; 95% CI=0.587–0.666) compared to grouping based on SMI (CI difference=0.062, 95% CI=0.031–0.103, P=0.0011) or serum creatinine (CI difference=0.043, 95% CI=0.017–0.081, P=0.0072) alone. Conclusion Incorporating both SMI and serum creatinine levels enhances the prognostic stratification for 5-year OS in patients with CRC, surpassing the prognostic power of grouping solely based on SMI or creatinine.

Purpose: Compared with extracorporeal anastomosis (ECA), intracorporeal anastomosis (ICA) is expected to provide some benefits, including a shorter operation time and less intraoperative bleeding. Nevertheless, the benefits of ICA have mainly been evaluated in nonrandomized studies. Owing to the recent update of randomized controlled trials (RCTs) for minimally invasive surgery (MIS) of right hemicolectomy (RHC), the need to measure the actual effect by synthesizing the outcomes of these studies has emerged. Methods: We performed a comprehensive search of the PubMed, Embase, and Cochrane databases (from inception to January 30, 2023) for studies that applied ICA and ECA for RHC with MIS. We included 7 RCTs. The operation time, intraoperative blood loss, conversion rate, length of incision, and postoperative outcomes such as ileus, anastomosis leakage, length of hospitalization, and postoperative pain were compared between ICA and ECA. Results: A total of 740 patients were included in the study. Among them, 377 and 373 underwent ICA and ECA, respectively.There were significant differences in age (P = 0.003) and incision type (P < 0.001) between ICA and ECA. ICA was associated with a significantly longer operation time (P = 0.033). Although the postoperative pain associated with ICA was significantly lower than that associated with ECA on postoperative day 2 (POD 2) (P = 0.003), it was not different on POD 3 between the groups. Other perioperative outcomes were similar between the 2 groups. Conclusion In this meta-analysis, ICA did not significantly improve short-term outcomes compared to ECA; other advantages to overcome ICA’s longer operation time are not clear.

Traditionally, cancer treatment has focused on the stages of the disease; however, recent studies have highlighted the importance of considering the overall health status of patients in the prognosis of cancer. Loss of skeletal muscle, known as sarcopenia, has been found to significantly affect outcomes in many different types of cancers, including colorectal cancer. In this review, we discuss the guidelines for diagnosing sarcopenia, with a specific focus on CT-based assessments. Many groups worldwide, including those in Europe and Asia, have introduced their own diagnostic guidelines for sarcopenia. Seemingly similar yet subtle discrepancies, particularly in the cutoff values used, limit the use of these guidelines in the general population, warranting a more universal guideline. Although CT-based measurements, such as skeletal muscle index and radiodensity, have shown promise in predicting outcomes, the lack of standardized values in these measurements hinders their universal adoption. To overcome these limitations, innovative approaches are being developed to assess changes in muscle mass trajectories and introduce new indices, such as skeletal and appendicular muscle gauges. Additionally, machine learning models have shown superior performance in predicting sarcopenic status, providing an alternative to CT-based diagnosis, particularly after surgery. CT has tremendous benefits and a significant role in visually as well as quantitatively retrieving information on patient body composition. In order to compensate for the limitation of standard cutoff value, 3-dimensional analysis of the CT, artificial intelligence-based body composition analysis, as well as machine learning algorithms for data interpretation and analysis have been proposed and are being utilized. In conclusion, despite the varying definitions of sarcopenia, CT-based measurements coupled with machine-learning models are promising for evaluating patients with cancer. Standardization efforts can improve diagnostic accuracy, reduce the reliance on CT examinations, and make sarcopenia assessments more accessible in clinical settings.

Purpose: Albumin-bilirubin (ALBI) score is a well-known prognostic factor for various diseases, including colorectal cancer (CRC). However, little is known about the significance of postoperative ALBI score changes in patients with CRC. Materials and Methods: A total of 723 patients who underwent surgery were enrolled. Preoperative ALBI (ALBI-pre) and postoperative ALBI (ALBI-post) scores were divided into low and high score groups. ALBI-trend was defined as a combination of four groups comprising the low and high ALBI-pre and ALBI-post score groups. Kaplan-Meier survival curves were used to compare the overall survival (OS) between the different ALBI groups. The Cox proportional hazards model was used to examine the independent relevant factors of OS. Stratification performance was compared between the different ALBI groupings using Harrell’s concordance index (C-index). Results: ALBI-pre, ALBI-post, and ALBI-trend score groups were significant prognostic factors of OS in the univariable analysis. However, multivariable analysis showed that ALBI-trend was an independent prognostic factor while ALBI-pre and ALBI-post were not. The C-index of ALBI-trend (0.622; 95% confidence interval [CI], 0.587 to 0.655) was higher than that of ALBI-pre (0.589; 95% CI, 0.557 to 0.621; bootstrap mean difference, 0.033; 95% CI, 0.013 to 0.057) and ALBI-post (0.575; 95% CI, 0.545 to 0.605; bootstrap mean difference, 0.047; 95% CI, 0.024 to 0.074). Conclusion Combining ALBI-pre and ALBI-post scores is an independent prognostic factor of OS and shows superior predictive power compared to ALBI-pre or ALBI-post alone in patients with CRC.

Objective: Dysphagia is a common clinical condition characterized by difficulty in swallowing. It is sub-classified into oropharyngeal dysphagia, which refers to problems in the mouth and pharynx, and esophageal dysphagia, which refers to problems in the esophageal body and esophagogastric junction. Dysphagia can have a significant negative impact one’s physical health and quality of life as its severity increases. Therefore, proper assessment and management of dysphagia are critical for improving swallowing function and preventing complications. Thus a guideline was developed to provide evidence-based recommendations for assessment and management in patients with dysphagia. Methods: Nineteen key questions on dysphagia were developed. These questions dealt with various aspects of problems related to dysphagia, including assessment, management, and complications. A literature search for relevant articles was conducted using Pubmed, Embase, the Cochrane Library, and one domestic database of KoreaMed, until April 2021. The level of evidence and recommendation grade were established according to the Grading of Recommendation Assessment, Development and Evaluation methodology. Results: Early screening and assessment of videofluoroscopic swallowing were recommended for assessing the presence of dysphagia. Therapeutic methods, such as tongue and pharyngeal muscle strengthening exercises and neuromuscular electrical stimulation with swallowing therapy, were effective in improving swallowing function and quality of life in patients with dysphagia. Nutritional intervention and an oral care program were also recommended. Conclusion This guideline presents recommendations for the assessment and management of patients with oropharyngeal dysphagia, including rehabilitative strategies.

OBJECTIVES: We estimated the population prevalence of antibodies to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), including unreported infections, through a Korea Seroprevalence Study of Monitoring of SARS-CoV-2 Antibody Retention and Transmission (K-SEROSMART) in 258 communities throughout Korea. METHODS: In August 2022, a survey was conducted among 10,000 household members aged 5 years and older, in households selected through two stage probability random sampling. During face-to-face household interviews, participants self-reported their health status, COVID-19 diagnosis and vaccination history, and general characteristics. Subsequently, participants visited a community health center or medical clinic for blood sampling. Blood samples were analyzed for the presence of antibodies to spike proteins (anti-S) and antibodies to nucleocapsid proteins (anti-N) SARS-CoV-2 proteins using an electrochemiluminescence immunoassay. To estimate the population prevalence, the PROC SURVEYMEANS statistical procedure was employed, with weighting to reflect demographic data from July 2022. RESULTS: In total, 9,945 individuals from 5,041 households were surveyed across 258 communities, representing all basic local governments in Korea. The overall population-adjusted prevalence rates of anti-S and anti-N were 97.6% and 57.1%, respectively. Since the Korea Disease Control and Prevention Agency has reported a cumulative incidence of confirmed cases of 37.8% through July 31, 2022, the proportion of unreported infections among all COVID-19 infection was suggested to be 33.9%. CONCLUSIONS The K-SEROSMART represents the first nationwide, community-based seroepidemiologic survey of COVID-19, confirming that most individuals possess antibodies to SARS-CoV-2 and that a significant number of unreported cases existed. Furthermore, this study lays the foundation for a surveillance system to continuously monitor transmission at the community level and the response to COVID-19.

Purpose: We investigated the feasibility of preoperative 18F-fluorodeoxyglucose (FDG) positron emission tomography (PET)/ computed tomography (CT) radiomics with machine learning to predict microsatellite instability (MSI) status in colorectal cancer (CRC) patients. Materials and Methods: Altogether, 233 patients with CRC who underwent preoperative FDG PET/CT were enrolled and divided into training (n=139) and test (n=94) sets. A PET-based radiomics signature (rad_score) was established to predict the MSI status in patients with CRC. The predictive ability of the rad_score was evaluated using the area under the receiver operating characteristic curve (AUROC) in the test set. A logistic regression model was used to determine whether the rad_score was an independent predictor of MSI status in CRC. The predictive performance of rad_score was compared with conventional PET parameters. Results: The incidence of MSI-high was 15 (10.8%) and 10 (10.6%) in the training and test sets, respectively. The rad_score was constructed based on the two radiomic features and showed similar AUROC values for predicting MSI status in the training and test sets (0.815 and 0.867, respectively; p=0.490). Logistic regression analysis revealed that the rad_score was an independent predictor of MSI status in the training set. The rad_score performed better than metabolic tumor volume when assessed using the AUROC (0.867 vs. 0.794, p=0.015). Conclusion Our predictive model incorporating PET radiomic features successfully identified the MSI status of CRC, and it also showed better performance than the conventional PET image parameters.

Purpose: Machine learning (ML) is a strong candidate for making accurate predictions, as we can use large amount of data with powerful computational algorithms. We developed a ML based model to predict survival of patients with colorectal cancer (CRC) using data from two independent datasets. Materials and Methods: A total of 364,316 and 1,572 CRC patients were included from the Surveillance, Epidemiology, and End Results (SEER) and a Korean dataset, respectively. As SEER combines data from 18 cancer registries, internal validation was done using 18-Fold-Cross-Validation then external validation was performed by testing the trained model on the Korean dataset. Performance was evaluated using area under the receiver operating characteristic curve (AUROC), sensitivity and positive predictive values. Results: Clinicopathological characteristics were significantly different between the two datasets and the SEER showed a significant lower 5-year survival rate compared to the Korean dataset (60.1% vs. 75.3%, p < 0.001). The ML-based model using the Light gradient boosting algorithm achieved a better performance in predicting 5-year-survival compared to American Joint Committee on Cancer stage (AUROC, 0.804 vs. 0.736; p < 0.001). The most important features which influenced model performance were age, number of examined lymph nodes, and tumor size. Sensitivity and positive predictive values of predicting 5-year-survival for classes including dead or alive were reported as 68.14%, 77.51% and 49.88%, 88.1% respectively in the validation set. Survival probability can be checked using the web-based survival predictor (http://colorectalcancer.pythonanywhere.com). Conclusion ML-based model achieved a much better performance compared to staging in individualized estimation of survival of patients with CRC.

Purpose: This study aimed to investigate the clinicopathologic features and survival in patients with both breast cancer (BrC) and colorectal cancer (CRC). Methods: Between 1996 and 2019, patients who were diagnosed with both BrC and CRC were evaluated retrospectively. Patients with distant metastasis, palliative resection, and previous cancer histories except for BrCs or CRCs were excluded. Altogether, 105 patients were divided into the B=C group (n=21), B-first group (n=40), and C-first group (n=44) according to the definition of synchronous and metachronous cancers. The clinicopathologic features and overall survival were evaluated. Results: TNM stages and histologic types were comparable among the 3 groups (P=0.434). The interval of diagnosis was 67.1±40.4 and 59.3±47.2 months in the B- and C-first groups, respectively. The incidence of adjuvant chemotherapy in the B-first group was 57.5%, which was higher than the B=C and C-first groups (P<0.001). The estrogen receptor, progesterone receptor, Ki-67, and HER-2 molecular markers were not significantly different among the groups. The overall survival of the B-first group showed lower survival rates than the C-first group (P=0.039). In the logistic regression, HER-2 status (hazard ratio [HR], 11.9; P=0.032) and lymph node metastasis of CRC (HR, 5.8; P=0.036) were prognostic factors affecting overall survival. Conclusion B-first group had poorer survival outcomes than the C-first group in patients with the metachronous BrC and CRC. HER2 positivity and CRC lymph node metastasis may be prognostic factors that affect overall survival in these patients. The findings support that a colorectal cancer screening program should be included during BrC surveillance.

Purpose: The role of tumor-infiltrating lymphocytes (TILs) in predicting lymph node metastasis (LNM) in patients with T1 colorectal cancer (CRC) remains unclear. Furthermore, clinical utility of a machine learning–based approach has not been widely studied. Materials and Methods: Immunohistochemistry for TILs against CD3, CD8, and forkhead box P3 in both center and invasive margin of the tumor were performed using surgically resected T1 CRC slides. Three hundred and sixteen patients were enrolled and categorized into training (n=221) and validation (n=95) sets via random sampling. Using clinicopathologic variables including TILs, the least absolute shrinkage and selection operator (LASSO) regression model was applied for variable selection and predictive signature building in the training set. The predictive accuracy of our model and the Japanese criteria were compared using area under the receiver operating characteristic (AUROC), net reclassification improvement (NRI)/integrated discrimination improvement (IDI), and decision curve analysis (DCA) in the validation set. Results: LNM was detected in 29 (13.1%) and 12 (12.6%) patients in training and validation sets, respectively. Nine variables were selected and used to generate the LASSO model. Its performance was similar in training and validation sets (AUROC, 0.795 vs. 0.765; p=0.747). In the validation set, the LASSO model showed better outcomes in predicting LNM than Japanese criteria, as measured by AUROC (0.765 vs. 0.518, p=0.003) and NRI (0.447, p=0.039)/IDI (0.121, p=0.034). DCA showed positive net benefits in using our model. Conclusion Our LASSO model incorporating histopathologic parameters and TILs showed superior performance compared to conventional Japanese criteria in predicting LNM in patients with T1 CRC.