Journal of Shanghai Jiao Tong University (Medical Science) ›› 2025, Vol. 45 ›› Issue (3): 324-334.doi: 10.3969/j.issn.1674-8115.2025.03.009

• Clinical research • Previous Articles     Next Articles

Study on prediction model and influencing factors of progression-free survival in colorectal cancer

CHEN Jiaying1,2(), CHU Yimin1,2, PENG Haixia1,2()   

  1. 1.Digestive Endoscopy Center, Shanghai Tongren Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai 200336, China
    2.Shanghai Key Laboratory of Flexible Medical Robotics, Institute of Medical Robotics, Shanghai Tongren Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai 200336, China
  • Received:2024-05-29 Accepted:2024-09-06 Online:2025-03-28 Published:2025-03-28
  • Contact: PENG Haixia E-mail:cjy811976991@163.com;phx1101@shtrhospital.com
  • Supported by:
    Natural Science Foundation of Shanghai(21ZR1058600);Medical-Engineering Cross Research of Shanghai Jiao Tong University(YG2022ZD031);Shanghai Municipal Health Commission Health industry Clinical Research Project(20234Y0016)

Abstract:

Objective ·To explore the risk factors affecting progression-free survival (PFS) in colorectal cancer (CRC) patients and establish a corresponding prognostic prediction model. Methods ·A retrospective cohort study was used for analysis, including 533 patients with surgically resected and pathologically confirmed colorectal adenocarcinoma at Tongren Hospital, Shanghai Jiao Tong University School of Medicine, who were randomly divided into a training set (373 cases) and a validation set (160 cases) in a 7:3 ratio. The included clinical data were analyzed using univariate and multivariate Cox proportional hazards models to explore independent factors affecting postoperative PFS in patients with CRC and to establish a clinical prognostic prediction model based on these factors. The discrimination and calibration of the prediction model were evaluated by using concordance index (C-index), area under the receiver operating characteristic (ROC) curve (AUC), calibration curve, and survival curve. The independent effects of age, gender, and American Joint Committee on Cancer (AJCC) cancer stage on prognosis were assessed using multivariate Cox regression analysis. Results ·Multivariate Cox regression analysis revealed that age, smoking history, liver disease, carbohydrate antigen 724 (CA724), and AJCC stage were independent factors influencing PFS. In the training set, the C-index of the PFS model was 0.69, with AUCs of 0.744 and 0.713 at 3 and 5 years, respectively. In the validation set, the C-index of the PFS model was 0.64, with AUCs of 0.706 and 0.683 at 3 and 5 years, respectively. The calibration curves showed that the prediction of PFS for the training and validation sets were close to the standard curve. The survival curves suggested that the progression rate of patients in the low-risk group was significantly lower than that in the high-risk group. Stratified analysis revealed that among patients aged ≥65 years, age, liver disease, and AJCC clinical stage were independent factors affecting postoperative PFS. Among patients aged <65 years, smoking history, CA724, and AJCC clinical stage were independent factors affecting postoperative PFS. For male patients, age, smoking history, CA724, and AJCC clinical stage were independent factors affecting postoperative PFS, while for female patients, liver disease, CA724, and AJCC clinical staging were independent predictors of postoperative PFS. Among patients with AJCC stage Ⅰ‒Ⅱ, age and smoking history were independent factors affecting postoperative PFS, whereas in those with AJCC stage Ⅲ‒⁠Ⅳ, age, liver disease, and CA724 were independent factors affecting postoperative PFS. Conclusion ·The PFS prognostic model established in this study for CRC patients has good discriminative ability and provides clinicians with an effective risk assessment tool.

Key words: colorectal cancer, progression-free survival, influencing factor, predictive modeling

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