Methods for Feature Selection in Down-Selection of Vaccine Regimens Based on Multivariate Immune Response Endpoints
Autor: | Ying Huang, Aliasghar Tarkhan |
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Jazyk: | angličtina |
Rok vydání: | 2020 |
Předmět: |
0301 basic medicine
Statistics and Probability Importance weight Feature selection Bioinformatics 01 natural sciences Biochemistry Genetics and Molecular Biology (miscellaneous) Article Down-selection 010104 statistics & probability 03 medical and health sciences Measurement error Medicine 0101 mathematics HIV vaccine Selection (genetic algorithm) business.industry Vaccine trial Correlation Clinical trial Vaccination Regimen 030104 developmental biology Clinical research business |
Zdroj: | Statistics in Biosciences |
ISSN: | 1867-1772 1867-1764 |
Popis: | In clinical trials, it is often of interest to compare and order several candidate regimens based on multiple endpoints. For example, in HIV vaccine development, immune response profiles induced by vaccination are key for selecting vaccine regimens to advance to efficacy evaluation. Motivated by the need to rank and choose a few vaccine regimens based on their immunogenicity in phase I trials, Huang et al. (Biostatistics 18(2):230–243, 2017) proposed a ranking/filtering/selection algorithm that down-selects vaccine regimens to satisfy the superiority and non-redundancy criteria, based on multiple immune response endpoints. In practice, many candidate immune response endpoints can be correlated with each other. An important question that remains to be addressed is how to choose a parsimonious set of the available immune response endpoints to effectively compare regimens. In this paper, we propose novel algorithms for selecting immune response endpoints to be used in regimen down-selection, based on importance weights assigned to individual endpoints and their correlation structure. We show through extensive simulation studies that pre-selection of endpoints can substantially improve performance of the subsequent regimen down-selection process. The application of the proposed method is demonstrated using a real example in HIV vaccine research, although the methods are also applicable in general to clinical research for dimension reduction when comparing regimens based on multiple candidate endpoints. Electronic supplementary material The online version of this article (10.1007/s12561-020-09275-2) contains supplementary material, which is available to authorized users. |
Databáze: | OpenAIRE |
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