Journal of Shandong University (Health Sciences) ›› 2025, Vol. 63 ›› Issue (5): 101-110.doi: 10.6040/j.issn.1671-7554.0.2024.0531

• Public Health & Preventive Medicine • Previous Articles     Next Articles

Dynamic prediction model for the colorectal cancer patients prognosis based on MFPC-Cox

DU Xue1,2, LI Chunxia1,2, LIU Yunxia1,2, ZHANG Tao1,2   

  1. 1. Department of Biostatistics, School of Public Health, Cheeloo College of Medicine, Shandong University, Jinan 250012, Shandong, China;
    2. Institute for Medical Dataology, Shandong University, Jinan 250002, Shandong, China
  • Published:2025-05-07

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Abstract: Objective To evaluated the utility of repeated measurements of carcinoembryonic antigen(CEA)and carbohydrate antigen 19-9(CA19-9)in improving the prognosis of colorectal cancer(CRC)patients, and to predict dynamically the future longitudinal trajectories of CEA and CA19-9, as well as the survival probability. Methods CRC patients who underwent radical resection at Yunnan Cancer Hospital between January 2011 and December 2018 were selected as the study subjects. Based on the clinical data and perioperative longitudinal measurements of CEA and CA19-9 in patients, multivariate functional principal component analysis(MFPCA)was used to extract the trajectory features of longitudinal CEA and CA19-9 measurements within 12 months postoperatively. The corresponding multivariate functional principal component scores were incorporated as covariates into the Cox proportional hazards model to construct a MFPC-Cox dynamic prediction model for the colorectal cancer patients prognosis. The predictive performance of models was quantitatively assessed by the time-varying area under the curve(AUC)and Brier score(BS), and compared with a static prediction model that only considered baseline information. Results The first seven principal components were selected to describe their longitudinal characteristics in the MFPCA of CEA and CA19-9. Compared to the static model, the dynamic prediction model increased the AUC of the 60-month postoperative survival rate from 0.727 to 0.787 and reduced the BS from 0.077 to 0.072. The accuracy of the model prediction improved significantly with the inclusion of aforementioned longitudinal biomarker measurements. Conclusion After considering the perioperative longitudinal measurements of CEA and CA19-9, the prognostic model for CRC based on the MFPC-Cox has high accuracy and can update the risk at each follow-up visit, enabling dynamic prediction. It is recommended to repeatedly measure CEA and CA19-9 during the postoperative follow-up of CRC patients.

Key words: Colorectal cancer, Serum tumor markers, MFPC-Cox model, Dynamic prediction, Prognosis

CLC Number: 

  • R735.3
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