Haas Kyle, Morton Stuart, Gupta Simone, Mahoui Malika
Indiana University-Purdue University Indianapolis (IUPUI), Indianapolis, IN, USA.
Eli Lilly and Company, Indianapolis, IN, USA.
AMIA Jt Summits Transl Sci Proc. 2019 May 6;2019:398-406. eCollection 2019.
Non-small-cell lung cancer (NSCLC) is one of the most prevalent types of lung cancer and continues to have an ominous five year survival rate. Considerable work has been accomplished in analyzing the viability of the treatments offered to NSCLC patients; however, while many of these treatments have performed better over populations of diagnosed NSCLC patients, a specific treatment may not be the most effective therapy for a given patient. Coupling both patient similarity metrics using the Gower similarity metric and prior treatment knowledge, we were able to demonstrate how patient analytics can complement clinical efforts in recommending the next best treatment. Our retrospective and exploratory results indicate that a majority of patients are not recommended the best surviving therapy once they require a new therapy. This investigation lays the groundwork for treatment recommendation using analytics, but more investigation is required to analyze patient outcomes beyond survival.
非小细胞肺癌（NSCLC）是最常见的肺癌类型之一，其五年生存率仍然不容乐观。在分析为NSCLC患者提供的治疗方案的可行性方面已经取得了相当多的成果；然而，虽然这些治疗方法在已确诊的NSCLC患者群体中表现较好，但特定的治疗方法可能并非对特定患者最有效的疗法。通过使用高尔相似度度量结合患者相似性指标和先前的治疗知识，我们能够证明患者分析如何能够在推荐最佳后续治疗方面辅助临床工作。我们的回顾性和探索性结果表明，一旦大多数患者需要新的治疗，他们并未被推荐使用最有利于生存的疗法。这项研究为使用分析方法进行治疗推荐奠定了基础，但还需要更多研究来分析生存以外的患者预后情况。
