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. 2022 Feb 28:10:848716.
doi: 10.3389/fpubh.2022.848716. eCollection 2022.

Development and Validation of a Nomogram to Predict Cancer-Specific Survival for Middle-Aged Patients With Early-Stage Hepatocellular Carcinoma

Chong Wen  1   2 , Jie Tang  3 , Hao Luo  1
Affiliations

Development and Validation of a Nomogram to Predict Cancer-Specific Survival for Middle-Aged Patients With Early-Stage Hepatocellular Carcinoma

Chong Wen et al. Front Public Health. .

Abstract

Background: Hepatocellular carcinoma is a common cause of death in middle-aged patients. We aimed to construct a new nomogram to predict cancer-specific survival (CSS) in middle-aged patients with hepatocellular carcinoma at an early stage.

Method: We collected clinicopathological information on early middle-aged patients with hepatocellular carcinoma from the SEER database. Univariate and multivariate Cox regression models were used to screen the independent risk factors for prognosis. These risk factors were used to construct predictions of CSS in patients with hepatocellular carcinoma. Consistency index (C- index), calibration curve, area under the receiver operating curve (AUC) were used. A decision analysis curve (DCA) was used to evaluate the clinical utility of the predictive model.

Results: A total of 6,286 patients with hepatocellular carcinoma in early middle age were enrolled. Univariate and multivariate Cox regression analysis showed that sex, marriage, race, histological tumor grade, T stage, surgery, chemotherapy, AFP, and tumor size were independent risk factors for prognosis. All independent risk factors were included in the nomogram to predict CSS at 1-, 3-, and 5-years in early middle age patients with hepatocellular carcinoma. In the training cohort and validation cohort, the C-index of the prediction model was 0.728 (95%CI: 0.716-0.740) and 0.733 (95%CI: 0.715-0.751), respectively. The calibration curve showed that the predicted value of the prediction model is highly consistent with the observed value. AUC also suggested that the model has good discrimination. DCA suggested that the nomogram had better predictive power than T staging.

Conclusion: We constructed a new nomogram to predict CSS in middle-aged patients with early-stage hepatocellular carcinoma. This prediction model has good accuracy and reliability, which can help patients and doctors to judge prognosis and make clinical decisions.

Keywords: SEER; cancer-specific survival; hepatocellular carcinoma; middle-aged patients; nomogram.

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Conflict of interest statement

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Figures

Figure 1
Figure 1
Flow chart of patient screening.
Figure 2
Figure 2
The nomogram of CSS in middle-aged patients with HCC at 1-, 3-, and 5-year.
Figure 3
Figure 3
Calibration curve of the nomogram. (A) Calibration curves of 1-, 3-, and 5-year CSS in training cohort; (B) calibration curves of 1-, 3-, and 5-year CSS in the validation cohort.
Figure 4
Figure 4
AUC for predicting 1-, 3-, and 5-year CSS in training cohort (A) and validation cohort (B).
Figure 5
Figure 5
DCA of the nomogram in training cohort (A) and validation cohort (B). The Y-axis represents a net benefit, and the X-axis represents threshold probability. The green line means no patients died, and the dark green line means all patients died. When the threshold probability is between 0 and 75%, the net benefit of the model exceeds all deaths or none.
Figure 6
Figure 6
Kaplan-Meier curves of patients in the low-risk and high-risk groups in training cohort (A) and validation cohort (B).
Figure 7
Figure 7
Kaplan-Meier curves of patients with different surgical procedures in the low-risk group (A) and high-risk group (B).
See this image and copyright information in PMC

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