Cancer Research and Treatment

Original Articles

Gastrointestinal cancer

The Persistence of Hypertriglyceridemia and the Risk of Early Onset Colorectal Cancer According to Tumor Subsites: A Nationwide Population-Based Study: Young Hoon Chang, Cheol Min Shin, Kyungdo Han, Jin Hyung Jung, Eun Hyo Jin, Joo Hyun Lim, Seung Joo Kang, Yoon Jin Choi, Hyuk Yoon, Young Soo Park, Nayoung Kim, Dong Ho Lee; Cancer Res Treat. 2024;56(3):825-837. Published online December 20, 2023; DOI: https://doi.org/10.4143/crt.2023.753

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Purpose
The incidence of early-onset colorectal cancer (EoCRC) is increasing worldwide. The association between hypertriglyceridemia (HTG) and EoCRC risk remains unclear.
Materials and Methods
We conducted a nationwide cohort study of 3,340,635 individuals aged 20-49 years who underwent health checkups between 2009 and 2011 under the Korean National Health Insurance Service. HTG was defined as serum triglyceride (TG) level ≥ 150 mg/dL. According to the change in TG status, participants were categorized into persistent normotriglyceridemia (NTG; group 1), NTG to HTG (group 2), HTG to NTG (group 3), and persistent HTG (group 4) groups. The EoCRC incidence was followed up until 2019.
Results
In total, 7,492 EoCRC cases developed after a mean of 6.05 years of follow-up. Group 4 had the highest risk of EoCRC (adjusted hazard ratio [aHR], 1.097; 95% confidence interval [CI], 1.025 to 1.174). While the risk of rectal cancer was significantly increased in groups 3 and 4 (aHR [95% CI], 1.236 [1.076 to 1.419] and 1.175 [1.042-1.325], respectively), no significant risk differences were observed in right colon cancer. In group 4, male sex and diabetes were associated with a further increased risk of EoCRC (aHR [95% CI], 1.149 [1.082 to 1.221] and 1.409 [1.169 to 1.699], respectively). In addition, there was a dose-response relationship between serum TG levels and the risk of EoCRC (p for trends < 0.0001).
Conclusion
Persistent HTG increased the risk of EoCRC, which was significantly higher only for rectal cancer and marginally higher for other colonic subsites.

Citations

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The multifaceted role of agents counteracting metabolic syndrome: A new hope for gastrointestinal cancer therapy
Elena Crecca, Gianfranco Di Giuseppe, Claudia Camplone, Virginia Vigiano Benedetti, Ombretta Melaiu, Teresa Mezza, Chiara Cencioni, Francesco Spallotta
Pharmacology & Therapeutics.2025; 270: 108847. CrossRef
Obesity-Associated Colorectal Cancer
Lucia Gonzalez-Gutierrez, Omar Motiño, Daniel Barriuso, Juan de la Puente-Aldea, Lucia Alvarez-Frutos, Guido Kroemer, Roberto Palacios-Ramirez, Laura Senovilla
International Journal of Molecular Sciences.2024; 25(16): 8836. CrossRef

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Development and Validation of Models to Predict Lymph Node Metastasis in Early Gastric Cancer Using Logistic Regression and Gradient Boosting Machine Methods: Hae Dong Lee, Kyung Han Nam, Cheol Min Shin, Hye Seung Lee, Young Hoon Chang, Hyuk Yoon, Young Soo Park, Nayoung Kim, Dong Ho Lee, Sang-Hoon Ahn, Hyung-Ho Kim; Cancer Res Treat. 2023;55(4):1240-1249. Published online March 21, 2023; DOI: https://doi.org/10.4143/crt.2022.1330

Abstract PDF Supplementary Material PubReader ePub

Purpose
To identify important features of lymph node metastasis (LNM) and develop a prediction model for early gastric cancer (EGC) using a gradient boosting machine (GBM) method.
Materials and Methods
The clinicopathologic data of 2556 patients with EGC who underwent gastrectomy were used as training set and the internal validation set (set 1) at a ratio of 8:2. Additionally, 548 patients with EGC who underwent endoscopic submucosal dissection (ESD) as the initial treatment were included in the external validation set (set 2). The GBM model was constructed, and its performance was compared with that of the Japanese guidelines.
Results
LNM was identified in 12.6% (321/2556) of the gastrectomy group (training set & set 1) and 4.3% (24/548) of the ESD group (set 2). In the GBM analysis, the top five features that most affected LNM were lymphovascular invasion, depth, differentiation, size, and location. The accuracy, sensitivity, specificity, and the area under the receiver operating characteristics of set 1 were 0.566, 0.922, 0.516, and 0.867, while those of set 2 were 0.810, 0.958, 0.803, and 0.944, respectively. When the sensitivity of GBM was adjusted to that of Japanese guidelines (beyond the expanded criteria in set 1 [0.922] and eCuraC-2 in set 2 [0.958]), the specificities of GBM in sets 1 and 2 were 0.516 (95% confidence interval, 0.502-0.523) and 0.803 (0.795-0.805), while those of the Japanese guidelines were 0.502 (0.488-0.509) and 0.788 (0.780-0.790), respectively.
Conclusion
The GBM model showed good performance comparable with the eCura system in predicting LNM risk in EGCs.

Citations

Citations to this article as recorded by

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Amin Zadeh Shirazi, Morteza Tofighi, Alireza Gharavi, Guillermo A. Gomez
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