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Идёт набор NCT07702708

Pre-Treatment DCE-MRI AI Models Predict Neoadjuvant Chemotherapy Response in HR+/HER2- Breast Cancer

— Наблюдательное HR+/HER2- Breast Cancer Breast Neoplasms

Ориентир для пациента и семьи

Простыми словами

Автоматическая сводка по структурированным данным реестра. Она помогает сориентироваться, но не заменяет официальный протокол или оценку врача.

Что изучают
В протоколе указаны: Pre-treatment DCE-MRI-based AI model.
Кому может быть актуально
Состояния в реестре: HR+/HER2- Breast Cancer, Breast Neoplasms. Базовые параметры: от 18 лет · Женщины.
Что важно проверить
Возраст, диагноз и пол — только базовые ориентиры. Предыдущее лечение, анализы и другие обязательные условия указаны ниже в критериях участия.
Где проводится
Китай
Следующий шаг
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Официальное название

A Multicenter Prospective Observational Cohort Study: Predicting Neoadjuvant Chemotherapy Response Using Pre-Treatment DCE-MRI-Based AI Models in HR+/HER2- Breast Cancer

Обзор

This study is a multicenter, prospective, observational cohort study to evaluate the predictive performance of pre-treatment DCE-MRI-based artificial intelligence (AI) models for neoadjuvant chemotherapy benefit in HR+/HER2- breast cancer. The study plans to enroll eligible HR+/HER2- breast cancer patients receiving routine standard neoadjuvant chemotherapy and stratify participants into high-benefit and low-benefit subgroups via the established AI model based on baseline breast DCE-MRI images. All enrolled patients will undergo systematic collection of baseline clinical-pathological data, pre-treatment DCE-MRI scans, neoadjuvant chemotherapy regimens, postoperative residual cancer burden (RCB) classification, objective response rate (ORR), and long-term survival endpoints including disease-free survival (DFS) and overall survival (OS). The primary objective compares the rate of RCB 0-1 between AI-defined high-benefit patients and published historical control data; secondary analyses compare ORR, RCB 0-1 proportion, DFS and OS between AI-stratified high-benefit and low-benefit subgroups to comprehensively verify the clinical value of this imaging AI model for individualized neoadjuvant chemotherapy selection.

Вмешательства

  • Диагностический тест Pre-treatment DCE-MRI-based AI model
    Preoperative dynamic contrast-enhanced MRI images are input into an artificial intelligence prediction model to stratify HR+/HER2- breast cancer patients into high and low neoadjuvant chemotherapy benefit subgroups.

Первичные конечные точки

  • Incidence of Residual Cancer Burden (RCB) 0-1 [Срок оценки: After completion of neoadjuvant chemotherapy and definitive surgery (approximately 3-6 months after enrollment)]
Вторичные конечные точки (5)
  • Objective response rate (ORR) of AI-defined high neoadjuvant chemotherapy benefit group [Срок оценки: Imaging assessment after completion of neoadjuvant chemotherapy and prior to surgery]
  • Between-subgroup differences in RCB 0-1 rate [Срок оценки: RCB classification obtained after definitive surgical resection, approximately 3-6 months after enrollment]
  • Between-subgroup differences in objective response rate (ORR) [Срок оценки: ORR imaging assessment after neoadjuvant chemotherapy before surgery]
  • Disease-free survival (DFS) between high and low chemotherapy benefit subgroups [Срок оценки: From the date of surgery until the first recurrence, metastasis, or death, whichever came first, assessed up to 60 months]
  • Overall survival (OS) between high and low chemotherapy benefit subgroups [Срок оценки: From the date of surgery until death from any cause, assessed up to 60 months]

Критерии участия

Критерии включения

  • Female patients aged ≥ 18 years old.
  • Histopathologically confirmed invasive breast carcinoma.
  • Hormone receptor positive (ER and/or PR ≥1%), HER2-negative status (IHC 0-1+, or IHC 2+ with negative FISH result).
  • Clinical stage II-III breast cancer per the 8th AJCC staging system, with clinical indication for neoadjuvant chemotherapy or primary surgery.
  • Standard pre-treatment breast DCE-MRI performed before neoadjuvant chemotherapy, with image quality eligible for AI model analysis.
  • ECOG performance status 0 or 1; adequate function of major vital organs to tolerate planned clinical treatment.
  • Voluntary participation with written informed consent obtained.

Критерии исключения

  • Prior systemic anti-tumor therapy for breast cancer other than planned neoadjuvant chemotherapy.
  • Inflammatory breast cancer or distant metastatic disease (M1).
  • Concurrent active malignant tumors of other origins.
  • Contraindications to MRI examination or unqualified MRI images that cannot support model analysis.
  • Severe comorbidities incompatible with neoadjuvant chemotherapy or surgical resection.
  • Any other conditions judged ineligible for enrollment by the investigator.

Критерии приведены из реестра в оригинале (на английском). Окончательную оценку соответствия проводит исследовательский центр.

Здоровые добровольцы: Нет

Дизайн исследования

Модель наблюдения
Когортное

Центры проведения

Китай · 5 центров
  • Fujian Cancer Hospital — Фучжоу
  • Fujian Provincial Hospital — Фучжоу
  • The Second Affiliated Hospital of Fujian Medical University — Quanzhou
  • Ningde First Hospital — Ningde
  • Sanming Second Hospital — Sanming

Идентификаторы

NCT: NCT07702708 · K2026-219-01

Первоисточники (государственные реестры)

Открыть это исследование на ClinicalTrials.gov ↗