Evaluate Cutpoints: Adaptable continuous data distribution system for determining survival in Kaplan-Meier estimator
Evaluate Cutpoints: Adaptable continuous data distribution system for determining survival in Kaplan-Meier estimator
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DOI：
10.1016/j.cmpb.2019.05.023
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发表时间：
2019-08-01
影响因子：
6.1
通讯作者：
Bednarek, Andrzej K.
中科院分区：
文献类型：
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作者：
Ogluszka, Magdalena;Orzechowska, Magdalena;Bednarek, Andrzej K.
背景和目的：越来越多的转录和代谢组学分化的证据诱导了许多研究，这些研究在疾病进展、治疗或影响细胞和组织代谢的许多不同因素的影响的背景下分析了这种分化。特别是，癌症研究人员正在寻找新的生物标志物，可以作为一个诊断/预后因素和其进一步的对应关系，关于临床效果。由于对涉及临床或流行病学数据（基因表达、生物标志物、生化参数等）的连续变量的二分法的使用的兴趣日益增加，存在对截止点确定工具的大量需求，同时缺乏提供基于连续和二元变量的患者分层的软件。因此，我们开发了“Evaluate Cutpoints”应用程序，提供广泛的统计和图形方法，用于截断点优化，使人群分层为两组或三组。方法：应用程序基于R语言，包括软件包算法，如survival，survMisc，OptimalCutpoints，maxstat，Rolr，ggplot 2，GGally和plotly，提供Kaplan-Meier图和ROC曲线，并确定截断点。通过对乳腺癌队列雌激素、孕激素和人表皮生长因子2受体的实例分析，说明了Evaluate Cutpoints的所有功能。通过ROC曲线确定ESR 1、PGR和ERBB 2表达与其免疫组化状态相关的截断点（截断点分别为1301.253、243.35、11434.438;敏感性分别为94%、85%、64%;特异性分别为93%、86%、91%）。通过无病生存分析，我们根据ESR 1、PGR和ERBB 2的表达将患者分为两组和三组。示例算法cutp显示，降低ESR 1和ERBB 2的表达更有利（HR = 2.07，p = 0.0412; HR = 2.79，p = 0.0777），而PGR表达升高与预后较好相关。（HR = 0.192，p = 0.0115）。结论：这项工作提出了应用程序Evaluate Cutpoints，可在www.example.com免费下载http://wnbikp.umed.lodz.pl/Evaluate-Cutpoints/。目前，许多软件被用来分割连续变量，如Cutoff Tile和X-Tile，它们提供了不同的算法。与它们不同的是，评估临界点不仅允许根据连续变量和二元变量将人群二分为组，而且还可以分层为三组以及手动选择临界点，从而防止潜在的信息丢失。(C)2019年，任作家。由爱思唯尔公司出版
Background and Objective: Growing evidence of transcriptional and metabolomic differentiation induced many studies which analyze such differentiation in context of outcome of disease progression, treatment or influence of many different factors affecting cellular and tissue metabolism. Particularly, cancer researchers are looking for new biomarkers that can serve as a diagnostic/prognostic factor and its further corresponding relationship regarding clinical effects. As a result of the increasing interest in use of dichotomization of continuous variables involving clinical or epidemiological data (gene expression, biomarkers, biochemical parameters, etc.) there is a large demand for cutoff point determination tools with simultaneous lack of software offering stratification of patients based on continuous and binary variables. Therefore, we developed "Evaluate Cutpoints" application offering wide set of statistical and graphical methods for cutpoint optimization enabling stratification of population into two or three groups.Methods: Application is based on R language including algorithms of packages such as survival, survMisc, OptimalCutpoints, maxstat, Rolr, ggplot2, GGally and plotly offering Kaplan-Meier plots and ROC curves with cutoff point determination.Results: All capabilities of Evaluate Cutpoints were illustrated with example analysis of estrogen, progesterone and human epidermal growth factor 2 receptors in breast cancer cohort. Through ROC curve the cutoff points were established for expression of ESR1, PGR and ERBB2 in correlation with their immunohistochemical status (cutoff: 1301.253, 243.35, 11,434.438, respectively; sensitivity: 94%, 85%, 64%, respectively; specificity: 93%, 86%, 91%, respectively). Through disease-free survival analysis we divided patients into two and three groups regarding expression of ESR1, PGR and ERBB2. Example algorithm cutp showed that lowered expression of ESR1 and ERBB2 was more favorable (HR = 2.07, p = 0.0412; HR = 2.79, p = 0.0777, respectively), whereas heightened PGR expression was correlated with better prognosis (HR = 0.192, p = 0.0115).Conclusions: This work presents application Evaluate Cutpoints that is freely available to download at http://wnbikp.umed.lodz.pl/Evaluate-Cutpoints/. Currently,many softwares are used to split continuous variables such as Cutoff Finder and X-Tile, which offer distinct algorithms. Unlike them, Evaluate Cutpoints allows not only dichotomization of populations into groups according to continuous variables and binary variables, but also stratification into three groups as well as manual selection of cutoff point thus preventing potential loss of information. (C) 2019 The Authors. Published by Elsevier B.V.