Predicting treatment benefit in multiple myeloma through simulation of alternative treatment effects

Selection of the right cancer treatment is still a challenge. Here, the authors introduce a framework to analyze treatment benefits, using the idea that patients with similar genetic tumor profiles receiving different treatments can be used to model their responses to the alternative treatment.

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Autores principales:	Joske Ubels, Pieter Sonneveld, Erik H. van Beers, Annemiek Broijl, Martin H. van Vliet, Jeroen de Ridder
Formato:	article
Lenguaje:	EN
Publicado:	Nature Portfolio 2018
Materias:	Science Q
Acceso en línea:	https://doaj.org/article/bc84203d4d9b4efaa0dbb9de2ebf654a
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spelling	oai:doaj.org-article:bc84203d4d9b4efaa0dbb9de2ebf654a2021-12-02T16:56:54ZPredicting treatment benefit in multiple myeloma through simulation of alternative treatment effects10.1038/s41467-018-05348-52041-1723https://doaj.org/article/bc84203d4d9b4efaa0dbb9de2ebf654a2018-07-01T00:00:00Zhttps://doi.org/10.1038/s41467-018-05348-5https://doaj.org/toc/2041-1723Selection of the right cancer treatment is still a challenge. Here, the authors introduce a framework to analyze treatment benefits, using the idea that patients with similar genetic tumor profiles receiving different treatments can be used to model their responses to the alternative treatment.Joske UbelsPieter SonneveldErik H. van BeersAnnemiek BroijlMartin H. van VlietJeroen de RidderNature PortfolioarticleScienceQENNature Communications, Vol 9, Iss 1, Pp 1-10 (2018)
institution	DOAJ
collection	DOAJ
language	EN
topic	Science Q
spellingShingle	Science Q Joske Ubels Pieter Sonneveld Erik H. van Beers Annemiek Broijl Martin H. van Vliet Jeroen de Ridder Predicting treatment benefit in multiple myeloma through simulation of alternative treatment effects
description	Selection of the right cancer treatment is still a challenge. Here, the authors introduce a framework to analyze treatment benefits, using the idea that patients with similar genetic tumor profiles receiving different treatments can be used to model their responses to the alternative treatment.
format	article
author	Joske Ubels Pieter Sonneveld Erik H. van Beers Annemiek Broijl Martin H. van Vliet Jeroen de Ridder
author_facet	Joske Ubels Pieter Sonneveld Erik H. van Beers Annemiek Broijl Martin H. van Vliet Jeroen de Ridder
author_sort	Joske Ubels
title	Predicting treatment benefit in multiple myeloma through simulation of alternative treatment effects
title_short	Predicting treatment benefit in multiple myeloma through simulation of alternative treatment effects
title_full	Predicting treatment benefit in multiple myeloma through simulation of alternative treatment effects
title_fullStr	Predicting treatment benefit in multiple myeloma through simulation of alternative treatment effects
title_full_unstemmed	Predicting treatment benefit in multiple myeloma through simulation of alternative treatment effects
title_sort	predicting treatment benefit in multiple myeloma through simulation of alternative treatment effects
publisher	Nature Portfolio
publishDate	2018
url	https://doaj.org/article/bc84203d4d9b4efaa0dbb9de2ebf654a
work_keys_str_mv	AT joskeubels predictingtreatmentbenefitinmultiplemyelomathroughsimulationofalternativetreatmenteffects AT pietersonneveld predictingtreatmentbenefitinmultiplemyelomathroughsimulationofalternativetreatmenteffects AT erikhvanbeers predictingtreatmentbenefitinmultiplemyelomathroughsimulationofalternativetreatmenteffects AT annemiekbroijl predictingtreatmentbenefitinmultiplemyelomathroughsimulationofalternativetreatmenteffects AT martinhvanvliet predictingtreatmentbenefitinmultiplemyelomathroughsimulationofalternativetreatmenteffects AT jeroenderidder predictingtreatmentbenefitinmultiplemyelomathroughsimulationofalternativetreatmenteffects
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Predicting treatment benefit in multiple myeloma through simulation of alternative treatment effects

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