Sobhani Navid, D'Angelo Alberto, Pittacolo Matteo, Mondani Giuseppina, Generali Daniele
Department of Cancer Biology, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA.
Department of Medicine, Northern General Hospital, Sheffield S5 7AT, UK.
Cancers (Basel). 2024 Sep 5;16(17):3089. doi: 10.3390/cancers16173089.
The medical research field has been tremendously galvanized to improve the prediction of therapy efficacy by the revolution in artificial intelligence (AI). An earnest desire to find better ways to predict the effectiveness of therapy with the use of AI has propelled the evolution of new models in which it can become more applicable in clinical settings such as breast cancer detection. However, in some instances, the U.S. Food and Drug Administration was obliged to back some previously approved inaccurate models for AI-based prognostic models because they eventually produce inaccurate prognoses for specific patients who might be at risk of heart failure. In light of instances in which the medical research community has often evolved some unrealistic expectations regarding the advances in AI and its potential use for medical purposes, implementing standard procedures for AI-based cancer models is critical. Specifically, models would have to meet some general parameters for standardization, transparency of their logistic modules, and avoidance of algorithm biases. In this review, we summarize the current knowledge about AI-based prognostic methods and describe how they may be used in the future for predicting antibody-drug conjugate efficacy in cancer patients. We also summarize the findings of recent late-phase clinical trials using these conjugates for cancer therapy.
人工智能（AI）的革命极大地推动了医学研究领域，以改善对治疗效果的预测。人们热切希望找到更好的方法，利用AI预测治疗效果，这推动了新模型的发展，使其在乳腺癌检测等临床环境中更具适用性。然而，在某些情况下，美国食品药品监督管理局不得不支持一些先前批准的基于AI的预后模型的不准确模型，因为它们最终会对可能有心力衰竭风险的特定患者产生不准确的预后。鉴于医学研究界常常对AI的进展及其在医学目的上的潜在用途抱有一些不切实际的期望，为基于AI的癌症模型实施标准程序至关重要。具体而言，模型必须满足一些标准化的一般参数、其逻辑模块的透明度以及避免算法偏差。在本综述中，我们总结了关于基于AI的预后方法的当前知识，并描述了它们未来如何用于预测癌症患者中抗体药物偶联物的疗效。我们还总结了最近使用这些偶联物进行癌症治疗的晚期临床试验的结果。
