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

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

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.

Keywords: IPDfromKM-Shiny method; indirect comparisons; overall survival; patient data reconstruction; progression free survival.

Publication types

  • Review

Grants and funding

This research received no external funding.