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Predicting tumor response to TACE plus lenvatinib and PD-1 inhibitors for unresectable HCC: A multicenter observational study.

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European journal of radiology 📖 저널 OA 7.7% 2022: 0/1 OA 2023: 0/2 OA 2024: 0/4 OA 2025: 1/40 OA 2026: 8/67 OA 2022~2026 2025 Vol.192() p. 112401
Retraction 확인
출처

PICO 자동 추출 (휴리스틱, conf 3/4)

유사 논문
P · Population 대상 환자/모집단
환자: uHCC who received TLP treatment were divided into training (n = 107), internal validation (n = 46), and external validation (n = 52) cohorts
I · Intervention 중재 / 시술
TLP treatment were divided into training (n = 107), internal validation (n = 46), and external validation (n = 52) cohorts
C · Comparison 대조 / 비교
추출되지 않음
O · Outcome 결과 / 결론
Stratification of patients into objective responders and non-responders via the EAPTT model revealed statistically significant progression-free survival and overall survival differences between the two groups. [CONCLUSION] The EAPTT model may enable precise stratification of the efficacy of patients with uHCC receiving TLP treatment, serving to assist in identifying the optimal candidates.

Deng LW, Xie QY, Peng B, Zhao Y, Liu B, Feng SF

📝 환자 설명용 한 줄

[OBJECTIVES] Preoperatively identifying patients with unresectable hepatocellular carcinoma (uHCC) who are likely to achieve an objective response to the treatment regimen of transarterial chemoemboli

🔬 핵심 임상 통계 (초록에서 자동 추출 — 원문 검증 권장)
  • 표본수 (n) 107

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↓ .bib ↓ .ris
APA Deng LW, Xie QY, et al. (2025). Predicting tumor response to TACE plus lenvatinib and PD-1 inhibitors for unresectable HCC: A multicenter observational study.. European journal of radiology, 192, 112401. https://doi.org/10.1016/j.ejrad.2025.112401
MLA Deng LW, et al.. "Predicting tumor response to TACE plus lenvatinib and PD-1 inhibitors for unresectable HCC: A multicenter observational study.." European journal of radiology, vol. 192, 2025, pp. 112401.
PMID 40911988 ↗

Abstract

[OBJECTIVES] Preoperatively identifying patients with unresectable hepatocellular carcinoma (uHCC) who are likely to achieve an objective response to the treatment regimen of transarterial chemoembolization (TACE) plus lenvatinib and programmed death-1 inhibitors (TLP) remains challenging. We aimed to develop and validate a predictive model for tumor response to TLP treatment in patients with uHCC.

[MATERIALS AND METHODS] Patients with uHCC who received TLP treatment were divided into training (n = 107), internal validation (n = 46), and external validation (n = 52) cohorts. A nomogram model was developed based on the clinical variables of the training cohort using multivariate logistic regression. The performance of this nomogram model was evaluated using the area under the curve (AUC) and calibration curves, and its performance was compared with that of other predictive models.

[RESULTS] The Eastern Cooperative Oncology Group performance status, albumin-bilirubin grade, platelet-to-lymphocyte ratio, tumor distribution, and total bilirubin were identified as independent predictors of objective response. These variables were incorporated to develop the EAPTT model. The AUCs of the EAPTT model were 0.84, 0.90, and 0.85 in the training, internal validation, and external validation cohorts, respectively-statistical analysis via the DeLong test showed that these AUCs were significantly higher than those of the other seven predictive models. Stratification of patients into objective responders and non-responders via the EAPTT model revealed statistically significant progression-free survival and overall survival differences between the two groups.

[CONCLUSION] The EAPTT model may enable precise stratification of the efficacy of patients with uHCC receiving TLP treatment, serving to assist in identifying the optimal candidates.

🏷️ 키워드 / MeSH 📖 같은 키워드 OA만

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🏷️ 같은 키워드 · 무료전문 — 이 논문 MeSH/keyword 기반