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应用KM-Shiny方法的个体参与者数据（IPD）比较针对同一疾病状况的新型治疗方法的疗效：14项分析报告

Application of the IPDfromKM-Shiny Method to Compare the Efficacy of Novel Treatments Aimed at the Same Disease Condition: A Report of 14 Analyses.

作者信息

Messori Andrea, Damuzzo Vera, Rivano Melania, Cancanelli Luca, Di Spazio Lorenzo, Ossato Andrea, Chiumente Marco, Mengato Daniele

机构信息

Unità di HTA, Regione Toscana, 50139 Firenze, Italy.

Dipartimento Politiche del Farmaco, Azienda ULSS 2 Marca Trevigiana, 31100 Treviso, Italy.

出版信息

Cancers (Basel). 2023 Mar 7;15(6):1633. doi: 10.3390/cancers15061633.

DOI:10.3390/cancers15061633
PMID:36980518
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC10046165/
Abstract

In the area of evidence-based medicine, the IPDfromKM-Shiny method is an innovative method of survival analysis, midway between artificial intelligence and advanced statistics. Its main characteristic is that an original software investigates the Kaplan-Meier graphs of trials so that individual-patient data are reconstructed. These reconstructed patients represent a new form of original clinical material. The typical objective of investigations based on this method is to analyze the available evidence, especially in oncology, to perform indirect comparisons, and determine the place in therapy of individual agents. This review examined the most recent applications of the IPDfromKM-Shiny method, in which a new web-based software-published in 2021-was used. Reported here are 14 analyses, mostly focused on oncological treatments. Indirect comparisons were based on overall survival or progression free survival. Each of these analyses provided original information to compare treatments with one another and select the most appropriate depending on patient characteristics. These analyses can also be useful to assess equivalence from a regulatory viewpoint. All investigations stressed the importance of heterogeneity to better interpret the evidence generated by IPDfromKM-Shiny investigations. In conclusion, these investigations showed that the reconstruction of individual patient data through this online tool is a promising new method for analyzing trials based on survival endpoints. This new approach deserves further investigation, particularly in the area of indirect comparisons.

摘要

在循证医学领域，基于KM-Shiny方法的个体患者数据（IPD）是一种生存分析的创新方法，介于人工智能和高级统计学之间。其主要特点是通过一款原创软件研究试验的 Kaplan-Meier 图，从而重建个体患者数据。这些重建后的患者代表了一种新形式的原始临床资料。基于该方法的研究的典型目标是分析现有证据，尤其是在肿瘤学领域，进行间接比较，并确定个体药物在治疗中的地位。本综述考察了基于KM-Shiny方法的最新应用，其中使用了2021年发布的一款新的基于网络的软件。这里报告了14项分析，大多聚焦于肿瘤治疗。间接比较基于总生存期或无进展生存期。这些分析中的每一项都提供了原始信息，以便相互比较治疗方法，并根据患者特征选择最合适的方法。这些分析从监管角度评估等效性也可能有用。所有研究都强调了异质性对于更好地解释基于KM-Shiny方法的研究所产生证据的重要性。总之，这些研究表明，通过这个在线工具重建个体患者数据是一种基于生存终点分析试验的有前景的新方法。这种新方法值得进一步研究，尤其是在间接比较领域。

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