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Validation of a prediction model for long-term outcome of aphasia after stroke

BACKGROUND: About 30% of stroke patients suffer from aphasia. As aphasia strongly affects daily life, most patients request a prediction of outcome of their language function. Prognostic models provide predictions of outcome, but external validation is essential before models can be used in clinical...

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Autores principales: Nouwens, Femke, Visch-Brink, Evy G., El Hachioui, Hanane, Lingsma, Hester F., van de Sandt-Koenderman, Mieke W. M. E., Dippel, Diederik W. J., Koudstaal, Peter J., de Lau, Lonneke M. L.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6191997/
https://www.ncbi.nlm.nih.gov/pubmed/30322381
http://dx.doi.org/10.1186/s12883-018-1174-5
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author Nouwens, Femke
Visch-Brink, Evy G.
El Hachioui, Hanane
Lingsma, Hester F.
van de Sandt-Koenderman, Mieke W. M. E.
Dippel, Diederik W. J.
Koudstaal, Peter J.
de Lau, Lonneke M. L.
author_facet Nouwens, Femke
Visch-Brink, Evy G.
El Hachioui, Hanane
Lingsma, Hester F.
van de Sandt-Koenderman, Mieke W. M. E.
Dippel, Diederik W. J.
Koudstaal, Peter J.
de Lau, Lonneke M. L.
author_sort Nouwens, Femke
collection PubMed
description BACKGROUND: About 30% of stroke patients suffer from aphasia. As aphasia strongly affects daily life, most patients request a prediction of outcome of their language function. Prognostic models provide predictions of outcome, but external validation is essential before models can be used in clinical practice. We aim to externally validate the prognostic model from the Sequential Prognostic Evaluation of Aphasia after stroKe (SPEAK-model) for predicting the long-term outcome of aphasia caused by stroke. METHODS: We used data from the Rotterdam Aphasia Therapy Study – 3 (RATS-3), a multicenter RCT with inclusion criteria similar to SPEAK, an observational prospective study. Baseline assessment in SPEAK was four days after stroke and in RATS-3 eight days. Outcome of the SPEAK-model was the Aphasia Severity Rating Scale (ASRS) at 1 year, dichotomized into good (ASRS-score of 4 or 5) and poor outcome (ASRS-score < 4). In RATS-3, ASRS-scores at one year were not available, but we could use six month ASRS-scores as outcome. Model performance was assessed with calibration and discrimination. RESULTS: We included 131 stroke patients with first-ever aphasia. At six months, 86 of 124 (68%) had a good outcome, whereas the model predicted 88%. Discrimination of the model was good with an area under the receiver operation characteristic curve of 0.87 (95%CI: 0.81–0.94), but calibration was unsatisfactory. The model overestimated the probability of good outcome (calibration-in-the-large α = − 1.98) and the effect of the predictors was weaker in the validation data than in the derivation data (calibration slope β = 0.88). We therefore recalibrated the model to predict good outcome at six months. CONCLUSION: The original model, renamed SPEAK-12, has good discriminative properties, but needs further external validation. After additional external validation, the updated SPEAK-model, SPEAK-6, may be used in daily practice to discriminate between patients with good and patients with poor outcome of aphasia at six months after stroke. TRIAL REGISTRATION: RATS-3 was registered on January 13th 2012 in the Netherlands Trial Register: NTR3271. SPEAK was not listed in a trial registry. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s12883-018-1174-5) contains supplementary material, which is available to authorized users.
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spelling pubmed-61919972018-10-23 Validation of a prediction model for long-term outcome of aphasia after stroke Nouwens, Femke Visch-Brink, Evy G. El Hachioui, Hanane Lingsma, Hester F. van de Sandt-Koenderman, Mieke W. M. E. Dippel, Diederik W. J. Koudstaal, Peter J. de Lau, Lonneke M. L. BMC Neurol Research Article BACKGROUND: About 30% of stroke patients suffer from aphasia. As aphasia strongly affects daily life, most patients request a prediction of outcome of their language function. Prognostic models provide predictions of outcome, but external validation is essential before models can be used in clinical practice. We aim to externally validate the prognostic model from the Sequential Prognostic Evaluation of Aphasia after stroKe (SPEAK-model) for predicting the long-term outcome of aphasia caused by stroke. METHODS: We used data from the Rotterdam Aphasia Therapy Study – 3 (RATS-3), a multicenter RCT with inclusion criteria similar to SPEAK, an observational prospective study. Baseline assessment in SPEAK was four days after stroke and in RATS-3 eight days. Outcome of the SPEAK-model was the Aphasia Severity Rating Scale (ASRS) at 1 year, dichotomized into good (ASRS-score of 4 or 5) and poor outcome (ASRS-score < 4). In RATS-3, ASRS-scores at one year were not available, but we could use six month ASRS-scores as outcome. Model performance was assessed with calibration and discrimination. RESULTS: We included 131 stroke patients with first-ever aphasia. At six months, 86 of 124 (68%) had a good outcome, whereas the model predicted 88%. Discrimination of the model was good with an area under the receiver operation characteristic curve of 0.87 (95%CI: 0.81–0.94), but calibration was unsatisfactory. The model overestimated the probability of good outcome (calibration-in-the-large α = − 1.98) and the effect of the predictors was weaker in the validation data than in the derivation data (calibration slope β = 0.88). We therefore recalibrated the model to predict good outcome at six months. CONCLUSION: The original model, renamed SPEAK-12, has good discriminative properties, but needs further external validation. After additional external validation, the updated SPEAK-model, SPEAK-6, may be used in daily practice to discriminate between patients with good and patients with poor outcome of aphasia at six months after stroke. TRIAL REGISTRATION: RATS-3 was registered on January 13th 2012 in the Netherlands Trial Register: NTR3271. SPEAK was not listed in a trial registry. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s12883-018-1174-5) contains supplementary material, which is available to authorized users. BioMed Central 2018-10-15 /pmc/articles/PMC6191997/ /pubmed/30322381 http://dx.doi.org/10.1186/s12883-018-1174-5 Text en © The Author(s). 2018 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
spellingShingle Research Article
Nouwens, Femke
Visch-Brink, Evy G.
El Hachioui, Hanane
Lingsma, Hester F.
van de Sandt-Koenderman, Mieke W. M. E.
Dippel, Diederik W. J.
Koudstaal, Peter J.
de Lau, Lonneke M. L.
Validation of a prediction model for long-term outcome of aphasia after stroke
title Validation of a prediction model for long-term outcome of aphasia after stroke
title_full Validation of a prediction model for long-term outcome of aphasia after stroke
title_fullStr Validation of a prediction model for long-term outcome of aphasia after stroke
title_full_unstemmed Validation of a prediction model for long-term outcome of aphasia after stroke
title_short Validation of a prediction model for long-term outcome of aphasia after stroke
title_sort validation of a prediction model for long-term outcome of aphasia after stroke
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6191997/
https://www.ncbi.nlm.nih.gov/pubmed/30322381
http://dx.doi.org/10.1186/s12883-018-1174-5
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