MétaCan
Menu
Back to cohort
Record W3112543907 · doi:10.1093/ibd/izaa303

Characteristics and Outcomes of IBD Patients with COVID-19 on Tofacitinib Therapy in the SECURE-IBD Registry

2020· article· en· W3112543907 on OpenAlexfundno aff
Manasi Agrawal, Erica J. Brenner, Xian Zhang, Irene Modesto, John Woolcott, Ryan C. Ungaro, Jean‐Frédéric Colombel, Michael D. Kappelman

Bibliographic record

VenueInflammatory Bowel Diseases · 2020
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicInflammatory Bowel Disease
Canadian institutionsnot available
FundersNational Center for Advancing Translational SciencesGenentechAbbVieLeona M. and Harry B. Helmsley Charitable TrustPfizerNational Institute of Diabetes and Digestive and Kidney DiseasesBristol-Myers Squibb CanadaBoehringer IngelheimEli Lilly and Company
KeywordsTofacitinibMedicineCoronavirus disease 2019 (COVID-19)Ulcerative colitisInflammatory bowel diseaseInflammatory Bowel DiseasesSevere acute respiratory syndrome coronavirus 2 (SARS-CoV-2)2019-20 coronavirus outbreakVirologyImmunologyInternal medicineRheumatoid arthritisDisease

Abstract

fetched live from OpenAlex

The coronavirus disease 2019 (COVID-19) pandemic due to the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has led to unprecedented loss of life and health on a global scale.1 COVID-19 outcomes are more severe among those with comorbid conditions,1 which raises concerns for patients with inflammatory bowel disease (IBD), especially given the increased infection risk with immunosuppression used for IBD therapy. Tofacitinib is a Janus kinase inhibitor (JAKi) approved for the treatment of ulcerative colitis (UC)2 and other immune-mediated diseases. Tofacitinib is associated with higher risk of herpes zoster (HZ) infection.2 Although HZ is a DNA virus, little is known regarding risks and outcomes of RNA viral infections such as SARS-CoV-2 with JAKi. Type 1 interferons, central to anti-SARS-CoV-2 activity and induced by the JAK-STAT pathway, were found to be impaired in severe COVID-19 in some studies and conversely upregulated in others, possibly reflecting heterogeneity in COVID-19 severity.3 Emerging data in non-IBD patients suggest that JAKi may blunt the cytokine storm that characterizes severe COVID-19 and potentially improve outcomes.4 In fact, a number of JAKi such as tofacitinib, baricitinib and ruxolitinib are being studied in clinical trials for COVID-19 treatment. Moreover, hospitalized COVID-19 patients are at a greater risk of thromboembolic events. This is important because findings from an interim analysis of a rheumatoid arthritis study for tofacitinib in older patients with ≥1 cardiovascular risk factor, alongside data from other JAKi clinical programs, suggest a higher risk of venous thromboembolic events.5 Emerging data on COVID-19 outcomes in patients with immune-mediated diseases treated with JAKi do not indicate worse outcomes compared with other immunosuppressive therapies; prior studies have been limited by very small sample sizes of fewer than 10 patients.6–9 To address this critical knowledge gap, we analyzed characteristics and outcomes of tofacitinib-treated IBD patients with COVID-19 compared with those on other medications in a global registry. The Surveillance Epidemiology of Coronavirus Under Research Exclusion for Inflammatory Bowel Disease (SECURE-IBD) is a global, web-based, collaborative registry established in March 2020 to understand COVID-19 outcomes in IBD patients, including the impact of immunosuppression.6 The collection and categorization of data have been reported previously.6 Using data reported though September 2020, we compared characteristics and COVID-19 outcomes of IBD patients on tofacitinib and those on other medications. We determined the proportion of patients with severe COVID-19, defined as a composite of intensive care unit (ICU) admission, mechanical ventilation, and/or death. In June 2020, we addended the SECURE-IBD data collection form to include questions pertaining to thrombotic complications. We compared the proportion of patients with thrombotic complications who were on tofacitinib with those on other IBD therapies. We performed bivariate analyses using χ 2 or Fisher exact test for categorial variables and Wilcoxon rank-sum or t test for continuous variables. P values ≤0.05 were considered statistically significant for all analyses. SAS version 9.3 (SAS Institute, Cary, North Carolina) was used for data preparation and analyses. As SECURE-IBD collects only de-identified data, the UNC-Chapel Hill Office for Human Research Ethics has determined that the storage and analysis of de-identified data for this project does not constitute human subjects research. Of 2326 patients who were on ≥1 IBD medication in the SECURE-IBD registry, 37 (1.6%) were treated with tofacitinib; 17 (45.9%) and 20 (54.1%) patients were on ≥20 and <20 mg total daily dose of tofacitinib, respectively. Baseline demographic and clinical characteristics of patients on tofacitinib compared with those on other medications are reported in the Table 1. Thirty (81.1%) patients in the tofacitinib group had UC compared with 946 (41.3%) patients on other IBD medications (P < 0.001). Significantly fewer patients were in remission in the tofacitinib group compared with those on other medications (32.4% vs 55.8%, P = 0.03). All other baseline demographic and clinical characteristics were comparable between the 2 groups. Demographic and Clinical Characteristics of IBD Patients on Tofacitinib Compared With Other IBD Therapies in the SECURE-IBD Registry aUnless otherwise specified, percentages do not include missing values or “unknown.” For all characteristics, unless noted above, less than 4% of data were missing and unknown, respectively, for each category. bPercentages and n from each subcategory may not add up to the exact number of total reported cases due to missing values and/or non-mutually exclusive variables. cP-values for tests comparing variables between tofacitinib and other medications groups dBy physician global assessment (PGA) at time of COVID-19 infection *Statistically significant association. Abbreviations: CAD, coronary artery disease; COPD, chronic obstructive pulmonary disease. Demographic and Clinical Characteristics of IBD Patients on Tofacitinib Compared With Other IBD Therapies in the SECURE-IBD Registry aUnless otherwise specified, percentages do not include missing values or “unknown.” For all characteristics, unless noted above, less than 4% of data were missing and unknown, respectively, for each category. bPercentages and n from each subcategory may not add up to the exact number of total reported cases due to missing values and/or non-mutually exclusive variables. cP-values for tests comparing variables between tofacitinib and other medications groups dBy physician global assessment (PGA) at time of COVID-19 infection *Statistically significant association. Abbreviations: CAD, coronary artery disease; COPD, chronic obstructive pulmonary disease. With respect to COVID-19 outcomes, there were no significant differences between tofacitinib-treated patients and other patients in the occurrence of hospitalization (21.6% vs 23.3%), admission to the ICU (5.4% vs 4.5%), and severe COVID-19 (6.2% in both groups, Table 2). In the subgroup of patients on tofacitinib for whom information on thrombotic events were available (n = 19), none experienced a thrombotic event. Among those on other IBD medications, thrombotic events occurred in 9 of 1270 (0.7%). COVID-19 Outcomes Among IBD Patients on Tofacitinib Compared With Other IBD Therapies in the SECURE-IBD Registry aIncludes composite of ICU admission, mechanical ventilation, and death. COVID-19 Outcomes Among IBD Patients on Tofacitinib Compared With Other IBD Therapies in the SECURE-IBD Registry aIncludes composite of ICU admission, mechanical ventilation, and death. We describe characteristics and outcomes of COVID-19 in 37 patients with IBD treated with tofacitinib compared with other medications in the SECURE-IBD registry. Overall, we found no difference in COVID-19 outcomes between the 2 groups. Our findings are consistent with previous descriptive reports of patients on JAKi for UC and other immune-mediated disease; although in each of these studies, COVID-19 outcomes are reported jointly among the few patients on JAKi along with other immunosuppression.6–9 In a case report of a 33-year-old woman with UC on tofacitinib, respiratory symptoms resolved in 5 days, and the patient recovered completely in 2 weeks with no change to tofacitinib treatment.10 In addition, although patients with COVID-19 may experience thrombotic complications, and tofacitinib at the higher dose has been associated with venous thromboembolism,5 none of the tofacitinib-treated patients in SECURE-IBD experienced thrombotic complications. Overall, these early data should be viewed as cautiously reassuring to patients and providers while we await larger studies and more granular analyses to parse out the impact of JAKi on COVID-19 outcomes. Strengths of this study include the use of a large, international registry of adult and pediatric IBD patients with diverse characteristics and outcomes. Limitations include the small number of patients on tofacitinib and even fewer outcomes precluding adjusted analyses; however, most demographic and clinical characteristics were comparable between tofacitinib-treated and other IBD patients. The only notable differences were the higher proportion of tofacitinib-treated patients with UC and active IBD. This is likely due to the real-world use of tofacitinib in moderate-severely active UC refractory to tumor necrosis factor antagonists.2 There are also risks of reporting bias and missing data in this voluntary registry. In summary, in our descriptive analysis, characteristics and COVID-19 outcomes among IBD patients on tofacitinib were comparable to those on other IBD medications. Future larger studies of patients on tofacitinib are needed to understand clinical implications. Data Availability: The data underlying this article are available in the article and in its online supplementary material. Author Contribution: MA contributed to the study concept and design, interpretation of data, drafting of manuscript, and critical revision of the manuscript for important intellectual content. EJB and RCU contributed to the study concept and design, acquisition of data, interpretation of data, and critical revision of the manuscript for important intellectual content. XZ contributed to the acquisition, analysis, and interpretation of data. IM contributed to the study concept and design and critical revision of the manuscript for important intellectual content. JW contributed to the drafting of manuscript and critical revision of the manuscript for important intellectual content. JFC contributed to the study concept and design, interpretation of data, and critical revision of the manuscript for important intellectual content. MDK contributed to the study concept and design, interpretation of data, and critical revision of the manuscript for important intellectual content. Supported by: This work was funded by the Helmsley Charitable Trust (2003–04445), National Center for Advancing Translational Sciences (UL1TR002489), a T32DK007634 (EJB), and a K23KD111995-01A1 (RCU). Additional funding provided by Pfizer, Takeda Pharmaceutical Company, Janssen Biotech., AbbVie Inc., Eli Lilly and Company, Genentech, Boehringer Ingelheim, Bristol Myers Squibb, Celtrion, and Arenapharm. The current analysis did not receive any direct funding from Pfizer. Conflicts of Interest: MA receives research support from the Dickler Family Fund, New York Community Trust, and the Helmsley Charitable Trust Fund for SECURE-IBD. EJB is supported by an Institutional Training Grant from the National Institutes of Health (T32DK007634). XZ reports no conflict of interest. IM and JW are employees and shareholders of Pfizer Inc. RCU has served as a consultant and/or advisory board member for Eli Lilly, Janssen, Pfizer, and Takeda; he has received research support from AbbVie, Boehringer Ingelheim, and Pfizer; he is supported by a Career Development Award from the National Institutes of Health (K23KD111995‐01A1). JFC reports receiving research grants from AbbVie, Janssen Pharmaceuticals, and Takeda; receiving payment for lectures from AbbVie, Amgen, Allergan, Inc. Ferring Pharmaceuticals, Shire, and Takeda; receiving consulting fees from AbbVie, Amgen, Arena Pharmaceuticals, Boehringer Ingelheim, Celgene Corporation, Celltrion, Eli Lilly, Enterome, Ferring Pharmaceuticals, Genentech, Janssen Pharmaceuticals, Landos, Ipsen, Medimmune, Merck, Novartis, Pfizer, Shire, Takeda, Tigenix, and Viela bio; and holding stock options in Intestinal Biotech Development and Genfit. MDK has consulted for Abbvie, Janssen, Pfizer, and Takeda, is a shareholder in Johnson & Johnson, and has received research support from Pfizer, Takeda, Janssen, Abbvie, Lilly, Genentech, Boehringer Ingelheim, Bristol Myers Squibb, Celtrion, and Arenapharm. The corresponding author confirms on behalf of all authors that there have been no involvements that might raise the question of bias in the work reported or in the conclusions, implications, or opinions stated.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.005
Threshold uncertainty score0.888

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.011
GPT teacher head0.243
Teacher spread0.232 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations57
Published2020
Admission routes1
Has abstractyes

Explore more

Same venueInflammatory Bowel DiseasesSame topicInflammatory Bowel DiseaseFrench-language works237,207