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一种用于成人转移性非小细胞肺癌的自动治疗线算法:使用盲法人工病历审查的验证研究

An Automated Line-of-Therapy Algorithm for Adults With Metastatic Non-Small Cell Lung Cancer: Validation Study Using Blinded Manual Chart Review.

作者信息

Meng Weilin, Mosesso Kelly M, Lane Kathleen A, Roberts Anna R, Griffith Ashley, Ou Wanmei, Dexter Paul R

机构信息

Center for Observational and Real-World Evidence, Merck & Co, Inc, Kenilworth, NJ, United States.

Department of Biostatistics and Health Data Science, Indiana University School of Medicine, Indianapolis, IN, United States.

出版信息

JMIR Med Inform. 2021 Oct 12;9(10):e29017. doi: 10.2196/29017.

Abstract

BACKGROUND

Extraction of line-of-therapy (LOT) information from electronic health record and claims data is essential for determining longitudinal changes in systemic anticancer therapy in real-world clinical settings.

OBJECTIVE

The aim of this retrospective cohort analysis is to validate and refine our previously described open-source LOT algorithm by comparing the output of the algorithm with results obtained through blinded manual chart review.

METHODS

We used structured electronic health record data and clinical documents to identify 500 adult patients treated for metastatic non-small cell lung cancer with systemic anticancer therapy from 2011 to mid-2018; we assigned patients to training (n=350) and test (n=150) cohorts, randomly divided proportional to the overall ratio of simple:complex cases (n=254:246). Simple cases were patients who received one LOT and no maintenance therapy; complex cases were patients who received more than one LOT and/or maintenance therapy. Algorithmic changes were performed using the training cohort data, after which the refined algorithm was evaluated against the test cohort.

RESULTS

For simple cases, 16 instances of discordance between the LOT algorithm and chart review prerefinement were reduced to 8 instances postrefinement; in the test cohort, there was no discordance between algorithm and chart review. For complex cases, algorithm refinement reduced the discordance from 68 to 62 instances, with 37 instances in the test cohort. The percentage agreement between LOT algorithm output and chart review for patients who received one LOT was 89% prerefinement, 93% postrefinement, and 93% for the test cohort, whereas the likelihood of precise matching between algorithm output and chart review decreased with an increasing number of unique regimens. Several areas of discordance that arose from differing definitions of LOTs and maintenance therapy could not be objectively resolved because of a lack of precise definitions in the medical literature.

CONCLUSIONS

Our findings identify common sources of discordance between the LOT algorithm and clinician documentation, providing the possibility of targeted algorithm refinement.

摘要

背景

从电子健康记录和理赔数据中提取治疗线(LOT)信息对于确定真实临床环境中全身抗癌治疗的纵向变化至关重要。

目的

这项回顾性队列分析的目的是通过将算法输出与通过盲法人工病历审查获得的结果进行比较,来验证和完善我们之前描述的开源LOT算法。

方法

我们使用结构化电子健康记录数据和临床文档,识别出2011年至2018年年中接受全身抗癌治疗的500例转移性非小细胞肺癌成年患者;我们将患者分为训练组(n = 350)和测试组(n = 150),按照简单病例与复杂病例的总体比例(n = 254:246)随机分配。简单病例为接受一种治疗线且未接受维持治疗的患者;复杂病例为接受一种以上治疗线和/或维持治疗的患者。使用训练组数据进行算法更改,然后针对测试组评估优化后的算法。

结果

对于简单病例,治疗线算法与病历审查在优化前的不一致情况有16例,优化后减少至8例;在测试组中,算法与病历审查之间没有不一致情况。对于复杂病例,算法优化使不一致情况从68例减少至62例,测试组中有37例。接受一种治疗线的患者中,治疗线算法输出与病历审查之间的一致性百分比在优化前为89%,优化后为93%,测试组为93%,而算法输出与病历审查之间精确匹配的可能性随着独特治疗方案数量的增加而降低。由于医学文献中缺乏精确的定义,治疗线和维持治疗不同定义产生的几个不一致领域无法客观解决。

结论

我们的研究结果确定了治疗线算法与临床医生记录之间不一致的常见来源,为有针对性的算法优化提供了可能性。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ba69/8548977/9f57f1fd8066/medinform_v9i10e29017_fig1.jpg

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