用因果模型发现乳腺癌治疗关键影响因素
Guiding Treatment Strategies: The Role of Adjuvant Anti-Her2 Neu Therapy and Skin/Nipple Involvement in Local Recurrence-Free Survival in Breast Cancer Patients
- 基于LiNGAM模型分析观察数据，挖掘治疗与预后间的因果关系
- 辅助抗Her2治疗延长无局部复发生存169天，皮肤/乳头受累缩短351天
- 为高危患者制定个性化治疗方案提供数据支持
本研究采用线性非高斯无环模型（LiNGAM）从杜克大学乳腺癌磁共振数据集的40余项特征中提取人口学、治疗方式、病情状况与预后之间的因果关系。相比传统随机对照试验，该方法利用更广泛的观察数据，提升了结果的普适性。分析显示，辅助抗Her2神经疗法可使无局部复发生存期延长169天，而皮肤或乳头受累则使其缩短351天。这些发现凸显了针对Her2阳性患者使用该疗法的重要性，并提示对高风险人群需采取针对性干预，有助于指导个体化治疗策略。
原文摘要 · Abstract (English)
This study explores how causal inference models, specifically the Linear Non-Gaussian Acyclic Model (LiNGAM), can extract causal relationships between demographic factors, treatments, conditions, and outcomes from observational patient data, enabling insights beyond correlation. Unlike traditional randomized controlled trials (RCTs), which establish causal relationships within narrowly defined populations, our method leverages broader observational data, improving generalizability. Using over 40 features in the Duke MRI Breast Cancer dataset, we found that Adjuvant Anti-Her2 Neu Therapy increased local recurrence-free survival by 169 days, while Skin/Nipple involvement reduced it by 351 days. These findings highlight the therapy's importance for Her2-positive patients and the need for targeted interventions for high-risk cases, informing personalized treatment strategies.
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