Department of oncology, West Kazakhstan Marat Ospanov Medical University, Aktobe, Kazakhstan.
Department of Radiologists of the NJSC ZKMU named after M. Ospanov, MC NCJSC Marat Ospanov Western-Kazakhstan Medical University, Kazakhstan.
Asian Pac J Cancer Prev. 2024 Aug 1;25(8):2773-2785. doi: 10.31557/APJCP.2024.25.8.2773.
To determine the demographic and clinical characteristics of individuals diagnosed with colorectal cancer.
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.
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.
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.
确定诊断为结直肠癌患者的人口统计学和临床特征。
对 2019 年至 2023 年在哈萨克斯坦西部诊断为结直肠癌的 650 名患者进行了回顾性研究。使用显著性检验和回归技术对各种因素与结果之间的关系进行了统计分析。
该研究纳入了 650 例结直肠癌患者,其中男性占 59.7%,女性占 40.3%。年龄分布显示 63.1%的患者年龄在 24-65 岁之间,36.9%的患者年龄超过 65 岁,且无性别差异。民族显著影响患者构成(63.8%哈萨克族,36.2%俄罗斯族,P=0.03)。KRAS 突变(76.0%阴性)和肿瘤形态(40%腺癌,P=0.02)显示出不同的关联。单因素逻辑回归显示,人口统计学/临床因素与癌症结果之间存在联系。多因素分析强调了年龄、癌症分期、扩散、淋巴浸润和转移与癌症进展的关系。列线图预测模型纳入了性别、肿瘤形态、分期和浸润。在验证队列中的评估显示出良好的区分度(AUC=0.6293)和校准。这些发现为结直肠癌的人口统计学、进展、治疗和死亡率提供了深入了解,有助于个性化干预。
本研究揭示了结直肠癌患者的人口统计学、治疗和预后的关键见解。强调了结直肠癌的复杂性,研究突出了年龄、性别和肿瘤特征对进展和死亡率的影响。开发的列线图模型为临床医生提供了个性化治疗决策的实用工具,增强了与患者进行预后讨论的能力。