A Prospective Non-Interventional Study Using a Multi-Modal Prognostic Test (Ataraxis) for Evaluating the Clinical Integration in Early-Stage Invasive Breast Cancer
概览
- 阶段
- 不适用
- 状态
- 尚未招募
- 发起方
- Young-Joon Kang
- 入组人数
- 150
- 主要终点
- Stage 1 - Feasibility: Clinical Workflow Compatibility Score
概览
简要总结
This study evaluates the real-world clinical workflow integration of a previously developed artificial intelligence (AI) prognostic test in breast cancer patients receiving neoadjuvant chemotherapy, and validates its accuracy in predicting treatment response.
The Ataraxis AI test analyzes digitized images of tumor biopsy slides combined with basic clinical information (age, tumor stage, hormone receptor status) to generate a risk score. Prior studies showed the AI test can predict cancer recurrence with accuracy comparable to or better than existing genomic tests.
The study has two stages:
- Stage 1 (30 patients): Assess whether the AI test can be practically integrated into routine clinical workflow, including ease of use, report clarity, and time requirements.
- Stage 2 (70-120 additional patients): Validate the accuracy of AI-predicted pathological complete response (pCR) rates against actual surgical outcomes.
This study uses a blinded design where treating physicians remain blinded to AI results until post-surgical pCR assessment. AI analysis is performed by the research coordinator in collaboration with Ataraxis. After pCR evaluation, AI results are disclosed and physicians complete surveys assessing hypothetical treatment changes. This design eliminates AI influence on treatment decisions and ensures independent validation.
Participants are adults with Stage I-III breast cancer planned for neoadjuvant chemotherapy. The study involves no additional procedures beyond standard care except for completing surveys about the AI test experience.
研究设计
- 研究类型
- Observational
- 观察模型
- Cohort
- 时间视角
- Prospective
入排标准
- 年龄范围
- 18 Years 至 —（Adult, Older Adult）
- 性别
- Female
- 接受健康志愿者
- 否
入选标准
- •Histologically confirmed Stage I-III invasive breast cancer
- •Planned for neoadjuvant chemotherapy
- •H\&E-stained slides available from core needle biopsy
- •Age 18 years or older
- •Able to provide written informed consent
排除标准
- •Metastatic breast cancer (Stage IV)
- •Not a candidate for neoadjuvant chemotherapy
- •H\&E slides not obtainable from core needle biopsy
- •Unable to provide informed consent
结局指标
主要结局
Stage 1 - Feasibility: Clinical Workflow Compatibility Score
时间窗: Within 4 weeks after surgery following NAC completion (approximately 5-7 months per participant)
Mean score on 5-point Likert scale assessing AI system integration into existing clinical workflow, including ease of use, report comprehensibility, credibility, and time burden. Higher scores indicate better compatibility.
pCR Prediction: pCR Prediction Accuracy (AUC-ROC)
时间窗: Within 4 weeks after surgery following NAC completion (approximately 5-7 months per participant)
Area under the receiver operating characteristic curve for AI-predicted pCR probability versus actual pathological complete response status (defined as ypT0/is ypN0).
次要结局
- Hypothetical Treatment Change Rate(After AI result disclosure following surgery (approximately 5-7 months per participant))
- Correlation Between AI Score and Established Prognostic Factors(Within 4 weeks after surgery following NAC completion (approximately 5-7 months per participant))
- Subtype-specific pCR Prediction Accuracy(Within 4 weeks after surgery following NAC completion (approximately 5-7 months per participant))
- Sensitivity and Specificity of pCR Prediction(Within 4 weeks after surgery following NAC completion (approximately 5-7 months per participant))
- AI Test Processing Time(Within 2 weeks after enrollment)
研究者
Young-Joon Kang
Assistant Professor
Incheon St.Mary's Hospital