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. 2024 Dec 18:16:1835-1849.
doi: 10.2147/CMAR.S489960. eCollection 2024.

Development and Validation of Nomograms to Predict the Overall Survival and Progression-Free Survival in Patients with Advanced Unresectable Intrahepatic Cholangiocarcinoma

Affiliations

Development and Validation of Nomograms to Predict the Overall Survival and Progression-Free Survival in Patients with Advanced Unresectable Intrahepatic Cholangiocarcinoma

Feng Xian et al. Cancer Manag Res. .

Abstract

Purpose: This study aimed to develop and validate clinical nomograms for predicting progression-free survival (PFS) and overall survival (OS) in unresectable ICC patients.

Patients and methods: Patients with ICC between 1 January 2018 and 31 May 2023 were selected and randomized into a training set and an internal validation set as a 7:3 ratio. Data analysis and modeling were conducted through R software. The univariate and multivariate Cox regression models were used to analyze the prognosis factors affecting OS and PFS. Survival analysis was conducted using the Kaplan-Meier (KM) method, and comparisons were made using the Log rank test. Then, two nomogram models were constructed to predict OS and PFS, respectively. The nomogram was evaluated and calibrated using the Harrell's C-index, receiver operating characteristic curve (ROC), and calibration plots, and the decision curve analysis (DCA) was conducted to assess its clinical utility.

Results: A total of 110 patients were enrolled in this study, with 77 to the training set and 33 to the validation set. In the entire population, the OS rates at 6 and 12 months were 75.5% and 35.5%, respectively, while the PFS rates at 6 and 12 months were 47.3% and 20%, respectively. Cox regression analyses showed that ECOG, Tumor volume, HBsAg and AFP were the prognosis factors of OS, and the predictors in the model of PFS included Gender, Stage of tumor, CDC20 expression and AFP. The nomograms were constructed based on the predictors above. The C-index for predicting OS was 0.802 (0.755, 0.849) in the training set, 0.813 (0.764, 0.862) in the internal validation set; the C-index for predicting PFS was 0.658 (0.568, 0.748) in the training set, and 0.795 (0.705, 0.885) in the internal validation set. Finally, calibration curves and DCA indicated that two nomograms showed favorable performance.

Conclusion: Two practical and effective prognostic nomograms were developed to assist clinicians in evaluating OS and PFS in patients with unresectable ICC.

Keywords: intrahepatic cholangiocarcinoma; nomogram; overall survival; prognostic model; progression-free survival.

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Conflict of interest statement

The authors declare no conflicts of interest.

Figures

Figure 1
Figure 1
Consort diagram of patient data selection process.
Figure 2
Figure 2
Kaplan-Meier survival curves for overall survival. (A) and progression-free survival, (B) in the total cohort.
Figure 3
Figure 3
The Kaplan–Meier curves of clinicopathological factors affecting OS and PFS based on multivariate analyses. (A-D) the survival curves of OS-related prognostic factors, (E-H) the survival curves of PFS-related prognostic factors.
Figure 4
Figure 4
Nomogram for predicting overall survival (OS) in intrahepatic cholangiocarcinoma.
Figure 5
Figure 5
Nomogram for predicting survival for ICC patients with different PFS.
Figure 6
Figure 6
The ROC curves of nomogram predicting OS and PFS in intrahepatic cholangiocarcinoma. ROC curves of the 6 months and 12 months OS in the training set (A) and in the validation set (B), and the curves of 6 and 12 months PFS in the training set (C) and in the validation set (D).
Figure 7
Figure 7
The DCA curves of nomogram predicting OS and PFS in intrahepatic cholangiocarcinoma. DCA curves of the 6 (A) and 12 months (B) OS in the training set and the 6 (C) and 12 months (D) OS in the validation set, and the curves of 6 (E) and 12 months (F) PFS in the training set and the 6 (G) and 12 months (H) PFS in the validation set.
Figure 8
Figure 8
The calibration curves of nomogram predicting OS and PFS in intrahepatic cholangiocarcinoma. (A and B) Calibration curves of the 6- and 12-month OS in the training set, (C and D) Calibration curves of the 6- and 12-month OS in the validation set, (E and F) Calibration curves of the 6- and 12-month PFS in the training set, (G and H) Calibration curves of the 6- and 12-month OS in the validation set.

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