RAR-Based Prognostic Model for Predicting Overall Survival in Hepatitis B Virus-Related Hepatocellular Carcinoma: A Multicenter Study.
코호트
1/5 보강
PICO 자동 추출 (휴리스틱, conf 2/4)
유사 논문P · Population 대상 환자/모집단
1403 patients was divided into training, internal validation, and external validation cohorts.
I · Intervention 중재 / 시술
추출되지 않음
C · Comparison 대조 / 비교
추출되지 않음
O · Outcome 결과 / 결론
An online calculator, deployed via a web-based platform, facilitated convenient mortality risk prediction for these patients. [CONCLUSION] The ratio-based nomogram we developed can accurately predict the survival of patients with hepatitis B virus-related hepatocellular carcinoma, serving as an effective auxiliary tool for clinical personalized treatment and prognostic assessment.
[PURPOSE] Hepatitis B virus-related hepatocellular carcinoma poses a significant global health challenge.
APA
Tan M, Liu Y, et al. (2025). RAR-Based Prognostic Model for Predicting Overall Survival in Hepatitis B Virus-Related Hepatocellular Carcinoma: A Multicenter Study.. Journal of inflammation research, 18, 9159-9170. https://doi.org/10.2147/JIR.S527420
MLA
Tan M, et al.. "RAR-Based Prognostic Model for Predicting Overall Survival in Hepatitis B Virus-Related Hepatocellular Carcinoma: A Multicenter Study.." Journal of inflammation research, vol. 18, 2025, pp. 9159-9170.
PMID
40666379
Abstract
[PURPOSE] Hepatitis B virus-related hepatocellular carcinoma poses a significant global health challenge. This study aimed to develop and validate a novel prognostic nomogram integrating the red blood cell distribution width-to-albumin ratio for predicting patients' overall survival.
[PATIENTS AND METHODS] A retrospective cohort of 1403 patients was divided into training, internal validation, and external validation cohorts. A multivariate Cox regression model selected variables to construct a nomogram and an online calculator, which were subsequently validated.
[RESULTS] The ratio emerged as an independent risk factor for long-term survival (hazard ratio: 5.808, 95% confidence interval: 1.721-19.599). A prognostic nomogram incorporating nine variables based on the ratio was developed. Calibration curves demonstrated high concordance between the predicted and actual 3-year survival rates. Decision curve analysis indicated that the nomogram significantly increased the net benefit of predicting 3-year survival. Based on the area under the receiver operating characteristic curves, the nomogram outperformed traditional models in predicting survival across the three cohorts. Patients were stratified into low-, intermediate-, and high-risk groups based on risk scores calculated from the nomogram. In all cohorts, the median survival time of the high-risk group was significantly shorter than that of the intermediate- and low-risk groups. An online calculator, deployed via a web-based platform, facilitated convenient mortality risk prediction for these patients.
[CONCLUSION] The ratio-based nomogram we developed can accurately predict the survival of patients with hepatitis B virus-related hepatocellular carcinoma, serving as an effective auxiliary tool for clinical personalized treatment and prognostic assessment.
[PATIENTS AND METHODS] A retrospective cohort of 1403 patients was divided into training, internal validation, and external validation cohorts. A multivariate Cox regression model selected variables to construct a nomogram and an online calculator, which were subsequently validated.
[RESULTS] The ratio emerged as an independent risk factor for long-term survival (hazard ratio: 5.808, 95% confidence interval: 1.721-19.599). A prognostic nomogram incorporating nine variables based on the ratio was developed. Calibration curves demonstrated high concordance between the predicted and actual 3-year survival rates. Decision curve analysis indicated that the nomogram significantly increased the net benefit of predicting 3-year survival. Based on the area under the receiver operating characteristic curves, the nomogram outperformed traditional models in predicting survival across the three cohorts. Patients were stratified into low-, intermediate-, and high-risk groups based on risk scores calculated from the nomogram. In all cohorts, the median survival time of the high-risk group was significantly shorter than that of the intermediate- and low-risk groups. An online calculator, deployed via a web-based platform, facilitated convenient mortality risk prediction for these patients.
[CONCLUSION] The ratio-based nomogram we developed can accurately predict the survival of patients with hepatitis B virus-related hepatocellular carcinoma, serving as an effective auxiliary tool for clinical personalized treatment and prognostic assessment.
🏷️ 키워드 / MeSH
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