Syarifuddin Erwin, Raharjo Warsinggih, Masadah Rina, Lusikooy Ronald Erasio, Cangara M Husni, Zainuddin Andi Alfian, Mulyawan Made, Aryanti Citra
Division of Digestive Surgery, Department of Surgery, Hasanuddin University, Makassar, Indonesia.
Department of Pathology, Hasanuddin University, Makassar, Indonesia.
Asian Pac J Cancer Prev. 2025 Apr 1;26(4):1365-1370. doi: 10.31557/APJCP.2025.26.4.1365.
A prognostic model is essential for postoperative treatment planning, follow-up strategies, and aiding physicians in communicating survival rates to patients. Recent studies suggest that platelet indices may serve as valuable prognostic markers. This study aims to develop and validate a nomogram incorporating platelet indices to predict survival outcomes in CRC patients.
This prospective cohort study included subjects diagnosed with CRC between 2019 and 2024 at Wahidin Sudirohusodo Hospital, Makassar. Subjects were randomly divided into training and validation sets. Demographic data (age, gender), clinical data (tumor invasion [T], node [N], metastases [M], tumor location, histological grading, history of surgery, chemotherapy, ileus or peritonitis), and platelet indices were collected. Independent prognostic factors were determined using the Cox regression model in SPSS 25.0. Nomogram development and validation were conducted using the "rms" (Regression Modeling Strategies) and "survival" packages in R Studio.
Thirteen prognostic factors, including gender, tumor location, T, N, M, histological grade, history of ileus or peritonitis, history of tumor resection, history of chemotherapy, and platelet indices, significantly impacted CRC survival. A nomogram was constructed with a C-index of 0.9 in the training set and 0.91 in the validation set.
A prognostic survival nomogram for Indonesian CRC patients was developed and validated, enabling predictions of CRC survival probabilities.
预后模型对于术后治疗规划、随访策略以及帮助医生向患者传达生存率至关重要。最近的研究表明,血小板指标可能是有价值的预后标志物。本研究旨在开发并验证一个纳入血小板指标的列线图,以预测结直肠癌(CRC)患者的生存结局。
这项前瞻性队列研究纳入了2019年至2024年期间在马卡萨的瓦希丁·苏迪罗胡索多医院被诊断为CRC的患者。将患者随机分为训练集和验证集。收集人口统计学数据(年龄、性别)、临床数据(肿瘤浸润程度[T]、淋巴结转移情况[N]、远处转移情况[M]、肿瘤位置、组织学分级、手术史、化疗史、肠梗阻或腹膜炎史)以及血小板指标。使用SPSS 25.0中的Cox回归模型确定独立预后因素。使用R Studio中的“rms”(回归建模策略)和“survival”软件包进行列线图的开发和验证。
13个预后因素,包括性别、肿瘤位置、T、N、M、组织学分级、肠梗阻或腹膜炎史、肿瘤切除史、化疗史以及血小板指标,对CRC生存有显著影响。构建的列线图在训练集中的C指数为0.9,在验证集中为0.91。
开发并验证了一个针对印度尼西亚CRC患者的预后生存列线图,能够预测CRC的生存概率。