Fors Martha Maria, Viada Carmen Elena, Gonzalez Paloma
Universidad de las Américas, Granados E14-592, Quito, Ecuador.
Rev Recent Clin Trials. 2017;12(1):3-7. doi: 10.2174/1574887111666160916144658.
Recursive Partitioning Analysis (RPA) is a very flexible non parametric algorithm that allows classification of individuals according to certain criteria, particularly in clinical trials, the method is used to predict response to treatment or classify individuals according to prognostic factors.
In this paper we examine how often RPA is used in clinical trials and in meta-analysis.
We reviewed abstracts published between 1990 and 2016, and extracted data regarding clinical trial phase, year of publication, type of treatment, medical indication and main evaluated endpoints.
One hundred and eighty three studies were identified; of these 43 were meta-analyses and 23 were clinical trials. Most of the studies were published between 2011 and 2016, for both clinical trials and meta-analyses of randomized clinical trials. The prediction of overall survival and progression free survival were the outcomes most evaluated, at 43.5% and 51.2% respectively. Regarding the use of RPA in clinical trials, the brain was the most common site studied, while for meta-analytic studies, other cancer sites were also studied. The combination of chemotherapy and radiation was seen frequently in clinical trials.
Recursive partitioning analysis is a very easy technique to use, and it could be a very powerful tool to predict response in different subgroups of patients, although it is not widely used in clinical trials.
递归划分分析（RPA）是一种非常灵活的非参数算法，可根据特定标准对个体进行分类，特别是在临床试验中，该方法用于预测治疗反应或根据预后因素对个体进行分类。
在本文中，我们研究了RPA在临床试验和荟萃分析中的使用频率。
我们回顾了1990年至2016年发表的摘要，并提取了有关临床试验阶段、发表年份、治疗类型、医学适应症和主要评估终点的数据。
共识别出183项研究；其中43项为荟萃分析，23项为临床试验。大多数研究发表于2011年至2016年之间，涉及临床试验和随机临床试验的荟萃分析。总生存期和无进展生存期的预测是评估最多的结局，分别为43.5%和51.2%。关于RPA在临床试验中的应用，脑部是研究最常见的部位，而在荟萃分析研究中，也研究了其他癌症部位。化疗和放疗的联合在临床试验中很常见。
递归划分分析是一种非常易于使用的技术，尽管它在临床试验中未被广泛应用，但它可能是预测不同患者亚组反应的非常强大的工具。
