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CT radiomics-based intratumoral and intertumoral heterogeneity indicators for prognosis prediction in gastric cancer patients receiving neoadjuvant chemotherapy.

1/5 보강
European radiology 📖 저널 OA 29.4% 2022: 1/4 OA 2023: 0/7 OA 2024: 2/11 OA 2025: 18/71 OA 2026: 57/165 OA 2022~2026 2025 Vol.35(8) p. 4448-4460
Retraction 확인
출처

PICO 자동 추출 (휴리스틱, conf 2/4)

유사 논문
P · Population 대상 환자/모집단
환자: lower baseline ITHscore had better prognoses (p < 0
I · Intervention 중재 / 시술
추출되지 않음
C · Comparison 대조 / 비교
추출되지 않음
O · Outcome 결과 / 결론
The Pre-SPM model, integrating both, independently predicts patient outcomes. Clinical relevance Pre-SPM enhances prognosis prediction by quantifying intratumoral and intertumoral heterogeneity, potentially guiding more personalized and effective treatment strategies for patients with LAGC.

Li J, Li Z, Wang Y, Li Y, Zhang J, Li Z, Tang L

📝 환자 설명용 한 줄

[OBJECTIVES] CT-based intratumoral and intertumoral heterogeneity indicators were integrated to develop a prognostic model for locally advanced gastric cancer (LAGC) patients undergoing neoadjuvant ch

🔬 핵심 임상 통계 (초록에서 자동 추출 — 원문 검증 권장)
  • p-value p < 0.001

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↓ .bib ↓ .ris
APA Li J, Li Z, et al. (2025). CT radiomics-based intratumoral and intertumoral heterogeneity indicators for prognosis prediction in gastric cancer patients receiving neoadjuvant chemotherapy.. European radiology, 35(8), 4448-4460. https://doi.org/10.1007/s00330-025-11430-6
MLA Li J, et al.. "CT radiomics-based intratumoral and intertumoral heterogeneity indicators for prognosis prediction in gastric cancer patients receiving neoadjuvant chemotherapy.." European radiology, vol. 35, no. 8, 2025, pp. 4448-4460.
PMID 39953151 ↗

Abstract

[OBJECTIVES] CT-based intratumoral and intertumoral heterogeneity indicators were integrated to develop a prognostic model for locally advanced gastric cancer (LAGC) patients undergoing neoadjuvant chemotherapy (NACT).

[METHODS] This retrospective study included 568 LAGC patients treated with NACT from two hospitals. The intratumor heterogeneity score (ITHscore) was developed to quantify the intratumoral heterogeneity of LAGCs on CT; intertumoral heterogeneity was characterized by combining the primary tumor (PT) and lymph node (LN) sizes on CT. CT indicators were measured on baseline and posttreatment CT scans; the reduction rates (%Δ) were calculated. The overall survival (OS) of all patients was recorded. Cox regression analysis was used to construct a preoperative survival prediction model (Pre-SPM) based on the baseline indicators and %Δ indicators. The predictive performance of Pre-SPM for OS was assessed. The clinicopathological data, including the ypTNM stage, were also collected to evaluate their impact on OS.

[RESULTS] Patients with lower baseline ITHscore had better prognoses (p < 0.001). Approximately 13.01% of patients exhibited contradictory changes in PT and LN sizes. Cox regression analysis selected the baseline ITHscore, baseline PT area, %ΔPT, and %ΔLN to establish the Pre-SPM. In the external validation cohort, the c-index of Pre-SPM for predicting OS was 0.72, while the AUC for predicting 5-year OS was 0.73. After adjusting for the influence of clinicopathological features, including the ypTNM stage, Pre-SPM remained an independent prognostic factor.

[CONCLUSION] The Pre-SPM model, combining intratumoral heterogeneity and intertumoral heterogeneity, has the potential to predict the OS of LAGC patients receiving NACT.

[KEY POINTS] Question Increased tumor heterogeneity in LAGC affects prognosis, but effective non-invasive CT methods for assessing intratumoral and intertumoral heterogeneity are lacking. Findings ITHscore indicates intratumoral heterogeneity, while changes in PT and LN sizes reflect intertumoral heterogeneity. The Pre-SPM model, integrating both, independently predicts patient outcomes. Clinical relevance Pre-SPM enhances prognosis prediction by quantifying intratumoral and intertumoral heterogeneity, potentially guiding more personalized and effective treatment strategies for patients with LAGC.

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