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Title: | Identifying individual predictive factors for treatment efficacy | Authors: | ALONSO ABAD, Ariel VAN DER ELST, Wim SANCHEZ, Lizet Luaces, Patricia MOLENBERGHS, Geert |
Issue Date: | 2022 | Publisher: | WILEY | Source: | BIOMETRICS, 78(1), p. 35-45 | Abstract: | Given the heterogeneous responses to therapy and the high cost of treatments, there is an increasing interest in identifying pretreatment predictors of therapeutic effect. Clearly, the success of such an endeavor will depend on the amount of information that the patient-specific variables convey about the individual causal treatment effect on the response of interest. In the present work, using causal inference and information theory, a strategy is proposed to evaluate individual predictive factors for cancer immunotherapy efficacy. In a first step, the methodology proposes a causal inference model to describe the joint distribution of the pretreatment predictors and the individual causal treatment effect. Further, in a second step, the so-called predictive causal information (PCI), a metric that quantifies the amount of information the pretreatment predictors convey on the individual causal treatment effects, is introduced and its properties are studied. The methodology is applied to identify predictors of therapeutic success for a therapeutic vaccine in advanced lung cancer. A user-friendly R library EffectTreat is provided to carry out the necessary calculations. | Notes: | Alonso, A (corresponding author), Katholieke Univ Leuven, I BioStat, B-3000 Leuven, Belgium. ariel.alonsoabad@kuleuven.be |
Other: | Alonso, A (corresponding author), Katholieke Univ Leuven, I BioStat, B-3000 Leuven, Belgium. ariel.alonsoabad@kuleuven.be | Keywords: | causal inference;multivariate predictors;personalized medicine;prediction of therapeutic success | Document URI: | http://hdl.handle.net/1942/33063 | ISSN: | 0006-341X | e-ISSN: | 1541-0420 | DOI: | 10.1111/biom.13398 | ISI #: | WOS:000591167700001 | Category: | A1 | Type: | Journal Contribution | Validations: | ecoom 2021 |
Appears in Collections: | Research publications |
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Biometrics - 2020 - Alonso - Identifying individual predictive factors for treatment efficacy.pdf Restricted Access | Published version | 265.18 kB | Adobe PDF | View/Open Request a copy |
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