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Development and validation of a multivariable risk prediction model for serious infection in patients with psoriasis receiving systemic therapy
BACKGROUND: Patients with psoriasis are often concerned about the risk of serious infection associated with systemic psoriasis treatments. OBJECTIVES: To develop and externally validate a prediction model for serious infection in patients with psoriasis within 1 year of starting systemic therapies....
Autores principales: | , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
John Wiley and Sons Inc.
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6850093/ https://www.ncbi.nlm.nih.gov/pubmed/30430546 http://dx.doi.org/10.1111/bjd.17421 |
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author | Yiu, Z.Z.N. Sorbe, C. Lunt, M. Rustenbach, S.J. Kühl, L. Augustin, M. Mason, K.J. Ashcroft, D.M. Griffiths, C.E.M. Warren, R.B. |
author_facet | Yiu, Z.Z.N. Sorbe, C. Lunt, M. Rustenbach, S.J. Kühl, L. Augustin, M. Mason, K.J. Ashcroft, D.M. Griffiths, C.E.M. Warren, R.B. |
author_sort | Yiu, Z.Z.N. |
collection | PubMed |
description | BACKGROUND: Patients with psoriasis are often concerned about the risk of serious infection associated with systemic psoriasis treatments. OBJECTIVES: To develop and externally validate a prediction model for serious infection in patients with psoriasis within 1 year of starting systemic therapies. METHODS: The risk prediction model was developed using the British Association of Dermatologists Biologic Interventions Register (BADBIR), and the German Psoriasis Registry PsoBest was used as the validation dataset. Model discrimination and calibration were assessed internally and externally using the C‐statistic, the calibration slope and the calibration in the large. RESULTS: Overall 175 (1·7%) out of 10 033 participants from BADBIR and 41 (1·7%) out of 2423 participants from PsoBest developed a serious infection within 1 year of therapy initiation. Selected predictors in a multiple logistic regression model included nine baseline covariates, and starting infliximab was the strongest predictor. Evaluation of model performance showed a bootstrap optimism‐corrected C‐statistic of 0·64 [95% confidence interval (CI) 0·60–0·69], calibration in the large of 0·02 (95% CI −0·14 to 0·17) and a calibration slope of 0·88 (95% CI 0·70–1·07), while external validation performance was poor, with C‐statistic 0·52 (95% CI 0·42–0·62), calibration in the large 0·06 (95% CI −0·25 to 0·37) and calibration slope 0·36 (95% CI −0·24 to 0·97). CONCLUSIONS: We present the first results of the development of a multivariable prediction model. This model may help patients and dermatologists in the U.K. and the Republic of Ireland to identify modifiable risk factors and inform therapy choice in a shared decision‐making process. |
format | Online Article Text |
id | pubmed-6850093 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | John Wiley and Sons Inc. |
record_format | MEDLINE/PubMed |
spelling | pubmed-68500932019-11-15 Development and validation of a multivariable risk prediction model for serious infection in patients with psoriasis receiving systemic therapy Yiu, Z.Z.N. Sorbe, C. Lunt, M. Rustenbach, S.J. Kühl, L. Augustin, M. Mason, K.J. Ashcroft, D.M. Griffiths, C.E.M. Warren, R.B. Br J Dermatol Original Articles BACKGROUND: Patients with psoriasis are often concerned about the risk of serious infection associated with systemic psoriasis treatments. OBJECTIVES: To develop and externally validate a prediction model for serious infection in patients with psoriasis within 1 year of starting systemic therapies. METHODS: The risk prediction model was developed using the British Association of Dermatologists Biologic Interventions Register (BADBIR), and the German Psoriasis Registry PsoBest was used as the validation dataset. Model discrimination and calibration were assessed internally and externally using the C‐statistic, the calibration slope and the calibration in the large. RESULTS: Overall 175 (1·7%) out of 10 033 participants from BADBIR and 41 (1·7%) out of 2423 participants from PsoBest developed a serious infection within 1 year of therapy initiation. Selected predictors in a multiple logistic regression model included nine baseline covariates, and starting infliximab was the strongest predictor. Evaluation of model performance showed a bootstrap optimism‐corrected C‐statistic of 0·64 [95% confidence interval (CI) 0·60–0·69], calibration in the large of 0·02 (95% CI −0·14 to 0·17) and a calibration slope of 0·88 (95% CI 0·70–1·07), while external validation performance was poor, with C‐statistic 0·52 (95% CI 0·42–0·62), calibration in the large 0·06 (95% CI −0·25 to 0·37) and calibration slope 0·36 (95% CI −0·24 to 0·97). CONCLUSIONS: We present the first results of the development of a multivariable prediction model. This model may help patients and dermatologists in the U.K. and the Republic of Ireland to identify modifiable risk factors and inform therapy choice in a shared decision‐making process. John Wiley and Sons Inc. 2019-01-15 2019-04 /pmc/articles/PMC6850093/ /pubmed/30430546 http://dx.doi.org/10.1111/bjd.17421 Text en © 2018 The Authors. British Journal of Dermatology published by John Wiley & Sons Ltd on behalf of British Association of Dermatologists This is an open access article under the terms of the http://creativecommons.org/licenses/by/4.0/ License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Original Articles Yiu, Z.Z.N. Sorbe, C. Lunt, M. Rustenbach, S.J. Kühl, L. Augustin, M. Mason, K.J. Ashcroft, D.M. Griffiths, C.E.M. Warren, R.B. Development and validation of a multivariable risk prediction model for serious infection in patients with psoriasis receiving systemic therapy |
title | Development and validation of a multivariable risk prediction model for serious infection in patients with psoriasis receiving systemic therapy |
title_full | Development and validation of a multivariable risk prediction model for serious infection in patients with psoriasis receiving systemic therapy |
title_fullStr | Development and validation of a multivariable risk prediction model for serious infection in patients with psoriasis receiving systemic therapy |
title_full_unstemmed | Development and validation of a multivariable risk prediction model for serious infection in patients with psoriasis receiving systemic therapy |
title_short | Development and validation of a multivariable risk prediction model for serious infection in patients with psoriasis receiving systemic therapy |
title_sort | development and validation of a multivariable risk prediction model for serious infection in patients with psoriasis receiving systemic therapy |
topic | Original Articles |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6850093/ https://www.ncbi.nlm.nih.gov/pubmed/30430546 http://dx.doi.org/10.1111/bjd.17421 |
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