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炎症性肠病(IBD)患者新冠病毒病(COVID-19)不良结局多变量预测模型的开发与验证

Development and validation of multivariable prediction models for adverse COVID-19 outcomes in IBD patients.

作者信息

Sperger John, Shah Kushal S, Lu Minxin, Zhang Xian, Ungaro Ryan C, Brenner Erica J, Agrawal Manasi, Colombel Jean-Frederic, Kappelman Michael D, Kosorok Michael R

机构信息

Department of Biostatistics, University of North Carolina, Chapel Hill, NC.

Division of Pediatric Gastroenterology, Department of Pediatrics, University of North Carolina, Chapel Hill, NC.

出版信息

medRxiv. 2021 Jan 20:2021.01.15.21249889. doi: 10.1101/2021.01.15.21249889.

DOI:10.1101/2021.01.15.21249889
PMID:33501455
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC7836127/
Abstract

IMPORTANCE

Risk calculators can facilitate shared medical decision-making . Demographics, comorbidities, medication use, geographic region, and other factors may increase the risk for COVID-19-related complications among patients with IBD .

OBJECTIVES

Develop an individualized prognostic risk prediction tool for predicting the probability of adverse COVID-19 outcomes in patients with IBD.

DESIGN SETTING AND PARTICIPANTS

This study developed and validated prognostic penalized logistic regression models using reports to Surveillance Epidemiology of Coronavirus Under Research Exclusion for Inflammatory Bowel Disease (SECURE-IBD) from March-October 2020. Model development was done using a training data set (85% of cases reported March 13 - September 15, 2020), and model validation was conducted using a test data set (the remaining 15% of cases plus all cases reported September 16-October 20, 2020).

MAIN OUTCOMES AND MEASURES

COVID-19 related:Hospitalization+: composite outcome of hospitalization, ICU admission, mechanical ventilation, or deathICU+: composite outcome of ICU admission, mechanical ventilation, or deathDeathWe assessed the resulting models' discrimination using the area under the curve (AUC) of the receiver-operator characteristic (ROC) curves and reported the corresponding 95% confidence intervals (CIs).

RESULTS

We included 2709 cases from 59 countries (mean age 41.2 years [s.d. 18], 50.2% male). A total of 633 (24%) were hospitalized, 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 AUC (95% CI) of 0.79 (0.75, 0.83) for Hospitalization+, 0.88 (0.82, 0.95) for ICU+, and 0.94 (0.89, 0.99) for Death. Age, comorbidities, corticosteroid use, and male gender were associated with higher risk of death, while use of biologic therapies was associated with a lower risk.

CONCLUSIONS AND RELEVANCE

Prognostic models can effectively predict who is at higher risk for COVID-19-related adverse outcomes in a population of IBD patients. 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 IBD patients. The tool numerically and visually summarizes the patient's probabilities of adverse outcomes and associated CIs. Helping physicians identify their highest-risk patients will be important in the coming months as cases rise in the US and worldwide. This tool can also serve as a model for risk stratification in other chronic diseases.

KEY POINTS

How well can a multivariable risk model predict the risk of hospitalization, intensive care unit (ICU) stay, or death due to COVID-19 in patients with inflammatory bowel disease (IBD)? Multivariable prediction models developed using data from an international voluntary registry of IBD patients and available for use online ( https://covidibd.org/ ) have very good discrimination for predicting hospitalization (Test set AUC 0.79) and excellent discrimination for ICU admission (Test set AUC 0.88) and death (Test set AUC 0.94). The models were developed with a training sample of 2009 cases and validated in an independent test sample of 700 cases comprised of a random sub-sample of cases and all cases entered in the registry during a one-month period after model development. This risk prediction model may serve as an effective tool for healthcare providers to facilitate conversations about COVID-19-related risks with IBD patients.

摘要

重要性

风险计算器有助于共同的医疗决策。人口统计学、合并症、药物使用、地理区域及其他因素可能增加炎症性肠病(IBD)患者发生与COVID-19相关并发症的风险。

目的

开发一种个性化的预后风险预测工具,以预测IBD患者出现不良COVID-19结局的概率。

设计、设置和参与者:本研究使用2020年3月至10月向炎症性肠病研究排除冠状病毒监测流行病学(SECURE-IBD)报告的数据,开发并验证了预后惩罚逻辑回归模型。模型开发使用训练数据集(2020年3月13日至9月15日报告病例的85%),模型验证使用测试数据集(其余15%的病例加上2020年9月16日至10月20日报告的所有病例)。

主要结局和指标

与COVID-19相关的:住院+:住院、入住重症监护病房(ICU)、机械通气或死亡的复合结局;ICU+:入住ICU、机械通气或死亡的复合结局;死亡。我们使用受试者工作特征(ROC)曲线的曲线下面积(AUC)评估所得模型的区分度,并报告相应的95%置信区间(CI)。

结果

我们纳入了来自59个国家的2709例病例(平均年龄41.2岁[标准差18],50.2%为男性)。共有633例(24%)住院,137例(5%)入住ICU或接受插管,69例(3%)死亡。2009例患者构成训练集,700例构成测试集。模型显示出良好的区分度,测试集AUC(95%CI)对于住院+为0.79(0.75,0.83),对于ICU+为0.88(0.82,0.95),对于死亡为0.94(0.89,0.99)。年龄、合并症、使用皮质类固醇以及男性性别与较高的死亡风险相关,而使用生物疗法与较低风险相关。

结论及相关性

预后模型可有效预测IBD患者群体中哪些人发生与COVID-19相关不良结局的风险更高。医疗保健提供者可使用免费在线风险计算器(https://covidibd.org/covid-19-risk-calculator/),以促进与IBD患者讨论COVID-19相关风险。该工具以数字和直观方式总结患者出现不良结局的概率及相关CI。随着美国及全球病例数上升,在未来几个月帮助医生识别最高风险患者将很重要。该工具也可作为其他慢性病风险分层的模型。

关键点

多变量风险模型在预测炎症性肠病(IBD)患者因COVID-19住院、入住重症监护病房(ICU)或死亡风险方面效果如何?使用来自IBD患者国际自愿登记处数据开发并可在线使用(https://covidibd.org/)的多变量预测模型,在预测住院方面具有很好的区分度(测试集AUC 0.79),在预测入住ICU方面具有良好的区分度(测试集AUC

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ff4b/7836127/d6c83ea65019/nihpp-2021.01.15.21249889-f0003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ff4b/7836127/4a971dd693f6/nihpp-2021.01.15.21249889-f0001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ff4b/7836127/857a1344532d/nihpp-2021.01.15.21249889-f0002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ff4b/7836127/d6c83ea65019/nihpp-2021.01.15.21249889-f0003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ff4b/7836127/4a971dd693f6/nihpp-2021.01.15.21249889-f0001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ff4b/7836127/857a1344532d/nihpp-2021.01.15.21249889-f0002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ff4b/7836127/d6c83ea65019/nihpp-2021.01.15.21249889-f0003.jpg

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