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http://hdl.handle.net/1942/20858
Title: | Validating predictors of therapeutic success: A causal inference approach | Authors: | ALONSO ABAD, Ariel VAN DER ELST, Wim MOLENBERGHS, Geert |
Issue Date: | 2015 | Source: | Statistical modelling 15(6), p. 619-636 | Abstract: | In personalized medicine medical decisions, practices and/or products are tailored to the individual patient. The idea is to provide the right patient with the right drug at the right dose at the right time. However, our current lack of ability to predict an individual patient’s treatment success for most diseases and conditions is a major challenge to achieve the goal of personalized medicine. In the present work, we argue that many of the techniques often used to evaluate predictors of therapeutic success may not be able to answer the relevant scientific questions and we propose a new validation strategy based on causal inference. The methodology is illustrated using data from a clinical trial in opiate/heroin addiction. The user-friendly R library EffectTreat is provided to carry out the necessary calculations. | Notes: | Address for correspondence: Ariel Abad Alonso, I-BioStat, Kapucijnenvoer 35, blok D, bus 7001, 3000 Leuven, Belgium. E-mail: Ariel.AlonsoAbad@kuleuven.be | Keywords: | causal inference; personalized medicine; prediction of therapeutic success | Document URI: | http://hdl.handle.net/1942/20858 | ISSN: | 1471-082X | e-ISSN: | 1477-0342 | DOI: | 10.1177/1471082X15586286 | ISI #: | 000369699200006 | Category: | A1 | Type: | Journal Contribution | Validations: | ecoom 2017 |
Appears in Collections: | Research publications |
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465.pdf | Peer-reviewed author version | 418.47 kB | Adobe PDF | View/Open |
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