Development and validation of multivariable prediction models for adverse COVID-19 outcomes in patients with IBD
© Author(s) (or their employer(s)) 2021. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ..
OBJECTIVES: Develop an individualised prognostic risk prediction tool for predicting the probability of adverse COVID-19 outcomes in patients with inflammatory bowel disease (IBD).
DESIGN AND SETTING: This study developed and validated prognostic penalised logistic regression models using reports to the international Surveillance Epidemiology of Coronavirus Under Research Exclusion for Inflammatory Bowel Disease voluntary registry from March to October 2020. Model development was done using a training data set (85% of cases reported 13 March-15 September 2020), and model validation was conducted using a test data set (the remaining 15% of cases plus all cases reported 16 September-20 October 2020).
PARTICIPANTS: We included 2709 cases from 59 countries (mean age 41.2 years (SD 18), 50.2% male). All submitted cases after removing duplicates were included.
PRIMARY AND SECONDARY OUTCOME MEASURES: COVID-19 related: (1) Hospitalisation+: composite outcome of hospitalisation, ICU admission, mechanical ventilation or death; (2) Intensive Care Unit+ (ICU+): composite outcome of ICU admission, mechanical ventilation or death; (3) Death. We assessed the resulting models' discrimination using the area under the curve of the receiver operator characteristic curves and reported the corresponding 95% CIs.
RESULTS: Of the submitted cases, a total of 633 (24%) were hospitalised, 137 (5%) were admitted to the ICU or intubated and 69 (3%) died. 2009 patients comprised the training set and 700 the test set. The models demonstrated excellent discrimination, with a test set area under the curve (95% CI) of 0.79 (0.75 to 0.83) for Hospitalisation+, 0.88 (0.82 to 0.95) for ICU+ and 0.94 (0.89 to 0.99) for Death. Age, comorbidities, corticosteroid use and male gender were associated with a higher risk of death, while the use of biological therapies was associated with a lower risk.
CONCLUSIONS: Prognostic models can effectively predict who is at higher risk for COVID-19-related adverse outcomes in a population of patients with IBD. A free online risk calculator (https://covidibd.org/covid-19-risk-calculator/) is available for healthcare providers to facilitate discussion of risks due to COVID-19 with patients with IBD.
| Errataetall: | |
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| Medienart: |
E-Artikel |
| Erscheinungsjahr: |
2021 |
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| Erschienen: |
2021 |
| Enthalten in: |
Zur Gesamtaufnahme - volume:11 |
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| Enthalten in: |
BMJ open - 11(2021), 11 vom: 12. Nov., Seite e049740 |
| Sprache: |
Englisch |
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| Beteiligte Personen: |
Sperger, John [VerfasserIn] |
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| Links: |
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| Themen: |
COVID-19 |
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| Anmerkungen: |
Date Completed 17.11.2021 Date Revised 16.02.2024 published: Electronic UpdateOf: medRxiv. 2021 Jan 20;:. - PMID 33501455 Citation Status MEDLINE |
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| doi: |
10.1136/bmjopen-2021-049740 |
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| funding: |
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| Förderinstitution / Projekttitel: |
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| PPN (Katalog-ID): |
NLM333105710 |
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| 100 | 1 | |a Sperger, John |e verfasserin |4 aut | |
| 245 | 1 | 0 | |a Development and validation of multivariable prediction models for adverse COVID-19 outcomes in patients with IBD |
| 264 | 1 | |c 2021 | |
| 336 | |a Text |b txt |2 rdacontent | ||
| 337 | |a ƒaComputermedien |b c |2 rdamedia | ||
| 338 | |a ƒa Online-Ressource |b cr |2 rdacarrier | ||
| 500 | |a Date Completed 17.11.2021 | ||
| 500 | |a Date Revised 16.02.2024 | ||
| 500 | |a published: Electronic | ||
| 500 | |a UpdateOf: medRxiv. 2021 Jan 20;:. - PMID 33501455 | ||
| 500 | |a Citation Status MEDLINE | ||
| 520 | |a © Author(s) (or their employer(s)) 2021. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ. | ||
| 520 | |a OBJECTIVES: Develop an individualised prognostic risk prediction tool for predicting the probability of adverse COVID-19 outcomes in patients with inflammatory bowel disease (IBD) | ||
| 520 | |a DESIGN AND SETTING: This study developed and validated prognostic penalised logistic regression models using reports to the international Surveillance Epidemiology of Coronavirus Under Research Exclusion for Inflammatory Bowel Disease voluntary registry from March to October 2020. Model development was done using a training data set (85% of cases reported 13 March-15 September 2020), and model validation was conducted using a test data set (the remaining 15% of cases plus all cases reported 16 September-20 October 2020) | ||
| 520 | |a PARTICIPANTS: We included 2709 cases from 59 countries (mean age 41.2 years (SD 18), 50.2% male). All submitted cases after removing duplicates were included | ||
| 520 | |a PRIMARY AND SECONDARY OUTCOME MEASURES: COVID-19 related: (1) Hospitalisation+: composite outcome of hospitalisation, ICU admission, mechanical ventilation or death; (2) Intensive Care Unit+ (ICU+): composite outcome of ICU admission, mechanical ventilation or death; (3) Death. We assessed the resulting models' discrimination using the area under the curve of the receiver operator characteristic curves and reported the corresponding 95% CIs | ||
| 520 | |a RESULTS: Of the submitted cases, a total of 633 (24%) were hospitalised, 137 (5%) were admitted to the ICU or intubated and 69 (3%) died. 2009 patients comprised the training set and 700 the test set. The models demonstrated excellent discrimination, with a test set area under the curve (95% CI) of 0.79 (0.75 to 0.83) for Hospitalisation+, 0.88 (0.82 to 0.95) for ICU+ and 0.94 (0.89 to 0.99) for Death. Age, comorbidities, corticosteroid use and male gender were associated with a higher risk of death, while the use of biological therapies was associated with a lower risk | ||
| 520 | |a CONCLUSIONS: Prognostic models can effectively predict who is at higher risk for COVID-19-related adverse outcomes in a population of patients with IBD. A free online risk calculator (https://covidibd.org/covid-19-risk-calculator/) is available for healthcare providers to facilitate discussion of risks due to COVID-19 with patients with IBD | ||
| 650 | 4 | |a Journal Article | |
| 650 | 4 | |a Research Support, N.I.H., Extramural | |
| 650 | 4 | |a Research Support, Non-U.S. Gov't | |
| 650 | 4 | |a COVID-19 | |
| 650 | 4 | |a inflammatory bowel disease | |
| 650 | 4 | |a statistics & research methods | |
| 700 | 1 | |a Shah, Kushal S |e verfasserin |4 aut | |
| 700 | 1 | |a Lu, Minxin |e verfasserin |4 aut | |
| 700 | 1 | |a Zhang, Xian |e verfasserin |4 aut | |
| 700 | 1 | |a Ungaro, Ryan C |e verfasserin |4 aut | |
| 700 | 1 | |a Brenner, Erica J |e verfasserin |4 aut | |
| 700 | 1 | |a Agrawal, Manasi |e verfasserin |4 aut | |
| 700 | 1 | |a Colombel, Jean-Frédéric |e verfasserin |4 aut | |
| 700 | 1 | |a Kappelman, Michael D |e verfasserin |4 aut | |
| 700 | 1 | |a Kosorok, Michael R |e verfasserin |4 aut | |
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