Development of a new nomogram for predicting recurrence in HCC with MVI following curative hepatectomy.
1/5 보강
PICO 자동 추출 (휴리스틱, conf 2/4)
유사 논문P · Population 대상 환자/모집단
환자: microvascular invasion (MVI) carry a high risk of recurrence and poor prognosis
I · Intervention 중재 / 시술
추출되지 않음
C · Comparison 대조 / 비교
추출되지 않음
O · Outcome 결과 / 결론
[CONCLUSION] This study developed a nomogram based on seven independent prognostic factors for RFS of HCC patients with MVI. The model demonstrated favorable predictive performance and may assist clinicians in stratifying recurrence risk and formulating individualized follow-up and treatment strategies.
[BACKGROUND] Hepatocellular carcinoma (HCC) patients with microvascular invasion (MVI) carry a high risk of recurrence and poor prognosis.
APA
Zhang FF, Liu ZH, et al. (2026). Development of a new nomogram for predicting recurrence in HCC with MVI following curative hepatectomy.. International journal of surgery (London, England), 112(2), 3854-3864. https://doi.org/10.1097/JS9.0000000000003626
MLA
Zhang FF, et al.. "Development of a new nomogram for predicting recurrence in HCC with MVI following curative hepatectomy.." International journal of surgery (London, England), vol. 112, no. 2, 2026, pp. 3854-3864.
PMID
41092419 ↗
Abstract 한글 요약
[BACKGROUND] Hepatocellular carcinoma (HCC) patients with microvascular invasion (MVI) carry a high risk of recurrence and poor prognosis. However, few studies have developed models to predict the recurrence in HCC patients with MVI. This study aimed to develop a predictive model for recurrence in HCC patients with MVI, which can aid in postoperative treatment decision-making.
[METHODS] This retrospective study enrolled HCC patients with postoperative pathological confirmation of MVI from two tertiary hospitals between January 2015 and December 2020. Independent prognostic factors for recurrence-free survival (RFS) were identified using random survival forests, followed by Cox regression analyses. A nomogram was developed based on these factors, and its performance was evaluated through internal validation to assess discrimination, calibration, and clinical utility.
[RESULT] A nomogram incorporating seven independent predictors - tumor size, satellite nodules, MVI grade, tumor number, ascites, prothrombin time, and gamma-glutamyl transferase - was developed to estimate RFS in HCC patients with MVI after curative resection. The concordance index (C-index) was 0.700 in the training cohort and 0.675 in the validation cohort. The area under the curve values for 1, 2, and 3 years were consistently high in both cohorts, confirming robust predictive performance. Calibration curves showed good agreement between predicted and observed outcomes. Decision curve analysis indicated clear clinical utility, with the model providing substantial net benefit across a range of threshold probabilities.
[CONCLUSION] This study developed a nomogram based on seven independent prognostic factors for RFS of HCC patients with MVI. The model demonstrated favorable predictive performance and may assist clinicians in stratifying recurrence risk and formulating individualized follow-up and treatment strategies.
[METHODS] This retrospective study enrolled HCC patients with postoperative pathological confirmation of MVI from two tertiary hospitals between January 2015 and December 2020. Independent prognostic factors for recurrence-free survival (RFS) were identified using random survival forests, followed by Cox regression analyses. A nomogram was developed based on these factors, and its performance was evaluated through internal validation to assess discrimination, calibration, and clinical utility.
[RESULT] A nomogram incorporating seven independent predictors - tumor size, satellite nodules, MVI grade, tumor number, ascites, prothrombin time, and gamma-glutamyl transferase - was developed to estimate RFS in HCC patients with MVI after curative resection. The concordance index (C-index) was 0.700 in the training cohort and 0.675 in the validation cohort. The area under the curve values for 1, 2, and 3 years were consistently high in both cohorts, confirming robust predictive performance. Calibration curves showed good agreement between predicted and observed outcomes. Decision curve analysis indicated clear clinical utility, with the model providing substantial net benefit across a range of threshold probabilities.
[CONCLUSION] This study developed a nomogram based on seven independent prognostic factors for RFS of HCC patients with MVI. The model demonstrated favorable predictive performance and may assist clinicians in stratifying recurrence risk and formulating individualized follow-up and treatment strategies.
🏷️ 키워드 / MeSH 📖 같은 키워드 OA만
- Humans
- Nomograms
- Liver Neoplasms
- Carcinoma
- Hepatocellular
- Male
- Hepatectomy
- Female
- Retrospective Studies
- Middle Aged
- Neoplasm Recurrence
- Local
- Aged
- Neoplasm Invasiveness
- Prognosis
- hepatocellular carcinoma (HCC)
- microvascular invasion (MVI)
- nomogram
- random survival forest (RSF)
- univariate and multivariate Cox regression analysis
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