Are sporadic colorectal cancers in young patients distinct from those in elderly patients?

AIM: The aim of this study was to compare the clinicopathological and oncological characteristics of sporadic colorectal cancer (CRC) between young and elderly patients without any genetic mutations that cause hereditary CRC. METHOD: In this cross-sectional, retrospective study conducted at three tertiary referral hospitals, we enrolled 1599 patients with CRC who underwent surgery between January 2010 and December 2017, including 157 young patients (age ≤ 40 years; yCRC) and 1442 elderly patients (age ≥ 70 years; eCRC). The clinicopathological and oncological outcomes were compared between the two groups. RESULTS: The median age at diagnosis was 37 years in the yCRC group (range 33.0-39.2 years) and 76 years in the eCRC group (range 72.0-79.0 years). The yCRC group did not present with advanced stages at diagnosis compared with the eCRC group, and the distribution of tumour stages was similar between the two groups. Microsatellite instability (MSI) testing revealed no difference in the frequency of tumours with high MSI (7.8% in yCRC, 5.8% in eCRC), and the frequency of mutations in the KRAS, NRAS and BRAF genes was also similar. The 3-year overall survival was better in the yCRC group than in the eCRC group (97.4% vs. 83.5%, p < 0.001); however, no such difference was observed in cancer-specific survival. CONCLUSION: Genetically proven sporadic CRCs did not differ significantly between young and elderly patients in terms of tumour stage, tumour location and various molecular features. CLINICAL TRIAL REGISTRATION NUMBER: The study was retrospectively registered with Clinical Trials.gov (no. NCT05601609).

Glycemic traits and colorectal cancer survival in a cohort of South Korean patients: A Mendelian randomization analysis.

BACKGROUND: Clinical diabetic traits have been reported to be associated with increased colorectal cancer (CRC) risk in observational studies. Using the Mendelian randomization (MR) analysis method, we examined the causal association between glycemic traits, such as fasting glucose (FG), fasting insulin (FI), and glycosylated hemoglobin A1c (HbA1c), and survival in a cohort of CRC patients. METHODS: We conducted a two-sample MR analysis among a cohort of patients with locally advanced CRC at Seoul National University Hospital. Single-nucleotide polymorphisms robustly associated (p < 5 × 10-8 ) with the three glycemic traits were obtained from the Meta-Analyses of Glucose and Insulin-related traits Consortium, Asian Genetic Epidemiology Network, and Korea Biobank Array. Three-year and 5-year overall survival (OS) and progression-free survival (PFS) were used as outcomes. Survival analysis was conducted using subgroup analysis by cancer stage and subsite in a multivariate Cox proportional hazards model adjusted for age and sex to examine whether glycemic traits affected survival. RESULTS: A total of 509 patients were included in our final analysis. MR analysis showed that HbA1c levels were associated with poor 3-year OS (ß = 4.20, p = 0.02). Sensitivity analyses did not show evidence of any violations of the MR assumptions. In the cancer subgroup analysis of the Cox proportional hazards model, pooled hazard ratios for FG were significantly associated with poor 3-year OS and PFS regardless of cancer stage. FI was not significantly associated with any 3-year survival endpoints. Among Stage III patients, three glycemic traits were significantly associated with both 5-year OS and PFS. Location-specific subgroup analysis showed a significant association between three glycemic traits and 5-year PFS in patients with left-sided colon cancer. FG was associated with poor 3-year survival for colon cancer but not rectal cancer. CONCLUSIONS: Our results suggest that FG and HbA1c could be used to predict prognosis in CRC patients. Lifestyle and/or pharmacological interventions targeting glycemic traits could help improve survival for CRC patients.

Risk Factor Analysis of Lymph Node Metastasis for Rectal Neuroendocrine Tumors: Who Needs a Radical Resection in Rectal Neuroendocrine Tumors Sized 1-2 cm?

BACKGROUND: Rectal neuroendocrine tumors (NETs) have malignant potential, and lymph node (LN) or distant metastases can occur; however, treatment of NETs 1-2 cm in size is controversial. OBJECTIVE: This study aimed to identify predictive factors for LN metastasis and prognostic factors for recurrence of rectal NETs, especially tumors 1‒2 cm in size. METHODS: Between October 2004 and November 2020, 453 patients underwent endoscopic or surgical treatment for rectal NETs in Seoul National University Hospital. The data on these patients were prospectively collected in our database and reviewed retrospectively. In cases of local excision, we evaluated LN metastasis with radiologic imaging, including computed tomography or magnetic resonance imaging before treatment and during the follow-up periods. RESULTS: LN metastasis was observed in 40 patients (8.8%). A higher rate of LN metastasis was observed in larger-sized tumors, advanced T stage, lymphovascular invasion (LVI), perineural invasion (PNI), and high tumor grade. In multivariable analysis, the significant risk factors for LN metastasis were tumor size (1 ≤ size < 2 cm: hazard ratio [HR] 64.07; size ≥2 cm: HR 102.37, p < 0.001) and tumor grade (G2: HR 3.63, p = 0.034; G3: HR 5.09, p = 0.044). In multivariable analysis for tumors 1-2 cm in size, the risk factor for LN metastasis was tumor grade (G2: HR 6.34, p = 0.013). CONCLUSIONS: Tumor grade and size are important predictive factors for LN metastasis. In NETs 2 cm in size, tumor grade is also important for LN metastasis, and radical resection should be considered.

Three-dimensional body composition parameters using automatic volumetric segmentation allow accurate prediction of colorectal cancer outcomes.

BACKGROUND: Parameters obtained from two-dimensional (2D) cross-sectional images have been used to determine body composition. However, data from three-dimensional (3D) volumetric body images reflect real body composition more accurately and may be better predictors of patient outcomes in cancer. This study aimed to assess the 3D parameters and determine the best predictive factors for patient prognosis. METHODS: Patients who underwent surgery for colorectal cancer (CRC) between 2010 and 2016 were included in this study. Preoperative computed tomography images were analysed using an automatic segmentation program. Body composition parameters for muscle, muscle adiposity, subcutaneous fat (SF) and abdominal visceral fat (AVF) were assessed using 2D images at the third lumbar (L3) level and 3D images of the abdominal waist (L1-L5). The cut-off points for each parameter were determined using X-tile software. A Cox proportional hazards regression model was used to identify the association between the parameters and the treatment outcomes, and the relative influence of each parameter was compared using a gradient boosting model. RESULTS: Overall, 499 patients were included in the study. At a median follow-up of 59 months, higher 3D parameters of the abdominal muscles and SF from the abdominal waist were found to be associated with longer overall survival (OS) and disease-free survival (all P < 0.001). Although the 3D parameters of AVF were not related to survival outcomes, patients with a high AVF volume and mass experienced higher rate of postoperative complications than those with low AVF volume (27.4% vs. 18.7%, P = 0.021, for mass; 27.1% vs. 19.0%, P = 0.028, for volume). Low muscle mass and volume (hazard ratio [HR] 1.959, P = 0.016; HR 2.093, P = 0.036, respectively) and low SF mass and volume (HR 1.968, P = 0.008; HR 2.561, P = 0.003, respectively), both in the abdominal waist, were identified as independent prognostic factors for worse OS. Along with muscle mass and volume, SF mass and volume in the abdominal waist were negatively correlated with mortality (all P < 0.001). Both AVF mass and volume in the abdominal waist were positively correlated with postoperative complications (P < 0.05); 3D muscle volume and SF at the abdominal waist were the most influential factors for OS. CONCLUSIONS: 3D volumetric parameters generated using an automatic segmentation program showed higher correlations with the short- and long-term outcomes of patients with CRC than conventional 2D parameters.