Evolution of Colorectal Cancer Trends and Treatment Outcomes: A Comprehensive Retrospective Analysis (2019-2023) in West Kazakhstan

Imanbayev, Nauryzbay; Iztleuov, Yerbolat; Koishybaev, Arip; Kereyeva, Nurgul; Tulyaeva, Anar; Zholmukhamedova, Dinara; Zharylgapov, Azamat

doi:10.31557/APJCP.2024.25.8.2773

Evolution of Colorectal Cancer Trends and Treatment Outcomes: A Comprehensive Retrospective Analysis (2019-2023) in West Kazakhstan

Document Type : Research Articles

Authors

¹ Department of oncology, West Kazakhstan Marat Ospanov Medical University, Aktobe, Kazakhstan.

² Department of Radiologists of the NJSC ZKMU named after M. Ospanov, MC NCJSC Marat Ospanov Western-Kazakhstan Medical University, Kazakhstan.

³ Department of Oncology of the NJSC ZKMU named after M. Ospanov MC NCJSC Marat Ospanov Western-Kazakhstan Medical University, Kazakhstan.

⁴ Department of Oncology, MC NCJSC Marat Ospanov Western-Kazakhstan Medical University, Kazakhstan.

10.31557/APJCP.2024.25.8.2773

Abstract

Objective: To determine the demographic and clinical characteristics of individuals diagnosed with colorectal cancer. Methods: A retrospective study was conducted on 650 patients diagnosed with colorectal cancer in West Kazakhstan from 2019 to 2023. Statistical analysis was performed to explore the relationships between various factors and outcomes, using significance tests and regression techniques. Results: The study included 650 colorectal cancer patients, with 59.7% males and 40.3% females. Age distribution showed 63.1% between 24-65 years and 36.9% over 65, with no gender-based age differences. Nationality significantly influenced patient composition (63.8% Kazakh, 36.2% Russian, P=0.03). KRAS mutations (76.0% negative) and tumor morphology (40% adenocarcinoma, P=0.02) displayed varied associations. Univariate logistic regression revealed links between demographic/clinical factors and cancer outcomes. Multivariate analysis emphasized age, stage of cancer, expansion, involvement of lymphatic and metastasis in cancer progression. Nomogram predictive modeling incorporated gender, tumor form, stage, and infiltration. Evaluation in a validation cohort showed good differentiation (AUC=0.6293) and calibration. The findings provide insights into colorectal cancer demographics, progression, treatment, and mortality, aiding personalized interventions. Conclusion: this study reveals critical insights into demographics, treatment, and prognosis. Emphasizing the complexity of CRC, the study highlights age, gender, and tumor characteristics’ impact on progression and mortality. A developed nomogram model offers clinicians a practical tool for personalized treatment decisions, enhancing prognosis discussions with patients.

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