BMC Cancer (Jun 2023)

Cancer-specific survival in patients with cholangiocarcinoma after radical surgery: a Novel, dynamic nomogram based on clinicopathological features and serum markers

  • Shurui Zhou,
  • Yue Zhao,
  • Yanzong Lu,
  • Weiling Liang,
  • Jianmin Ruan,
  • Lijun Lin,
  • Haoming Lin,
  • Kaihong Huang

DOI
https://doi.org/10.1186/s12885-023-11040-9
Journal volume & issue
Vol. 23, no. 1
pp. 1 – 13

Abstract

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Abstract Background This study aims to (1) identify preoperative testing-based characteristics associated with enhanced prognosis and survival for cholangiocarcinoma patients, and (2)create a distinctive nomogram to anticipate each patient’s cancer-specific survival (CSS). Methods Retrospective analysis was performed on 197 CCA patients who underwent radical surgery at Sun Yat-sen Memorial Hospital; they were divided into a 131-person “training cohort” and a 66-person “internal validation cohort.“ The prognostic nomogram was created following a preliminary Cox proportional hazard regression search for independent factors influencing the patients’ CSS. Its applicable domain was examined via an external validation cohort, which included 235 patients from the Sun Yat-sen University Cancer Center. Results The median follow-up period for the 131 patients in the training group was 49.3 months (range, 9.3 to 133.9 months). One-, three-, and five-year CSS rates were 68.7%, 24.5%, and 9.2%, respectively, with the median CSS length being 27.4 months (range: 1.4 to 125.2 months). PLT, CEA, AFP, tumor location, differentiation, lymph node metastasis, chemotherapy, and TNM stage were determined to be independent risk factors for CCA patients by univariate and multivariate Cox proportional hazard regression analysis. We were able to accurately predict postoperative CSS after incorporating all of these characteristics into a nomogram. The AJCC’s 8th edition staging method’s C-indices were statistically substantially (P < 0.001) lower than the nomogram’s C-indices (0.84, 0.77, and 0.74 in the training, internal and external validation cohorts respectively). Conclusions A realistic and useful model for clinical decision-making and the optimization of therapy is presented as a nomogram that includes serum markers and clinicopathologic features for predicting postoperative survival in cholangiocarcinoma.

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