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Record W3167211705 · doi:10.1111/bjd.20571

COVID‐19 outcomes in patients with autoimmune blistering disease

2021· letter· en· W3167211705 on OpenAlexfundno aff
Erica Hwang, Mary M. Tomayko

Bibliographic record

VenueBritish Journal of Dermatology · 2021
Typeletter
Languageen
FieldMedicine
TopicAutoimmune Bullous Skin Diseases
Canadian institutionsnot available
FundersNational Heart, Lung, and Blood InstituteGaldermaRegeneron PharmaceuticalsCelgeneSanofiValeant Pharmaceuticals InternationalPfizer
KeywordsCoronavirus disease 2019 (COVID-19)RituximabMedicinePandemic2019-20 coronavirus outbreakSevere acute respiratory syndrome coronavirus 2 (SARS-CoV-2)HydroxychloroquinePopulationDiseaseAutoimmune diseaseImmunologyIntensive care medicineInfectious disease (medical specialty)Internal medicineVirologyAntibodyEnvironmental health

Abstract

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Dear Editor, Autoimmune blistering diseases (AIBD) are often treated with immunosuppressive medications, including rituximab, yet the implications of these approaches during the COVID‐19 pandemic are not fully understood. COVID‐19 outcome studies in patients with AIBD are limited by small sample sizes and interpretation complicated by advanced age and comorbidities common in this population. On the one hand, although a diagnosis of bullous pemphigoid (BP) alone may present a higher risk of death from COVID‐19 disease,1 a review of published case reports2 and a population‐based cohort study1 of patients with AIBD who had confirmed SARS‐CoV‐2 infection (16 and 36 patients, respectively), suggested that immunomodulatory treatments do not increase risks of contracting COVID‐19 or of poor outcomes. On the other hand, a study of 17 patients with AIBD who had documented SARS‐CoV‐2 infection found increased risk of hospitalization with more recent rituximab treatment,3 suggesting that the risks of treatment, especially with rituximab, deserve further investigation. Indeed, an increased risk of death has been observed among rheumatology patients on rituximab.4–6 To provide clarity on the risk of treating AIBD with immunosuppressive therapies, particularly rituximab, during the pandemic, we assembled and analysed outcomes in a cohort treated in our US institution. We performed an institutional review board‐approved retrospective search of the electronic health record for patients with diagnoses of pemphigoid or pemphigus and conducted a chart review of those who had SARS‐CoV‐2 infection confirmed by polymerase chain reaction between 1 February 2020 and 1 July 2020. Additionally, we contacted patients with AIBD followed in our academic tertiary care clinic and reviewed the history of those diagnosed with COVID‐19. Of 19 patients with AIBD identified, 11 patients had BP, one had ocular cicatricial pemphigoid, four had pemphigus vulgaris (PV), and three had pemphigus foliaceus. Clinical findings are summarized in Table 1. Characteristics and COVID‐19 outcomes of patients with autoimmune blistering diseases (AIBD) who contracted COVID‐19 BP, bullous pemphigoid; COPD, chronic obstructive pulmonary disease; DCN, doxycycline; F, female; M, male; MCN, minocycline; MMF, mycophenolate mofetil; MTX, methotrexate; OCP, ocular cicatricial pemphigoid; PF, pemphigus foliaceous; pred, prednisone; PV, pemphigus vulgaris; RTX, rituximab; TCS, topical corticosteroids. aTreated with azithromycin in her skilled nursing facility at the beginning of the pandemic; btreated with remdesivir, convalescent plasma, admitted to intensive care and ventilated; cmanaged as high risk with decadron and bamlanivimab owing to recent rituximab infusion; dadmitted to intensive care; ehospital course complicated by embolic stroke, deep vein thrombosis, pulmonary embolism; frecovered but BP flared, entered hospice care months later; gtreated with tocilizumab and supplemental oxygen. Characteristics and COVID‐19 outcomes of patients with autoimmune blistering diseases (AIBD) who contracted COVID‐19 BP, bullous pemphigoid; COPD, chronic obstructive pulmonary disease; DCN, doxycycline; F, female; M, male; MCN, minocycline; MMF, mycophenolate mofetil; MTX, methotrexate; OCP, ocular cicatricial pemphigoid; PF, pemphigus foliaceous; pred, prednisone; PV, pemphigus vulgaris; RTX, rituximab; TCS, topical corticosteroids. aTreated with azithromycin in her skilled nursing facility at the beginning of the pandemic; btreated with remdesivir, convalescent plasma, admitted to intensive care and ventilated; cmanaged as high risk with decadron and bamlanivimab owing to recent rituximab infusion; dadmitted to intensive care; ehospital course complicated by embolic stroke, deep vein thrombosis, pulmonary embolism; frecovered but BP flared, entered hospice care months later; gtreated with tocilizumab and supplemental oxygen. In our cohort, the only patients who succumbed to COVID‐19 were treated with rituximab. Although three patients who received rituximab ≥ 6 months prior recovered without intervention, two of three who received rituximab ≤ 5 months prior to COVID‐19 diagnosis died. One was a 74‐year‐old man with PV and hypertension on prednisone 40 mg daily who received rituximab 2 months prior to COVID‐19 diagnosis; he was treated with remdesivir, convalescent plasma and mechanical ventilation. The other was an 82‐year‐old woman with BP, dementia, chronic obstructive lung disease and hypertension, all of which are independent risk factors for poor outcome, who received rituximab 4 months prior to COVID‐19 diagnosis. She was treated with azithromycin at the beginning of the pandemic in her skilled nursing facility before succumbing. A 65‐year‐old man with PV and obesity on mycophenolate mofetil who received rituximab 5 months prior was treated with decadron and bamlanivimab and recovered without hospitalization. Altogether, six patients were treated with rituximab, three with mycophenolate mofetil, five with methotrexate (each alone or in combination with prednisone), and five with topical steroids alone or in combination with tetracycline antibiotics. All five patients treated with topical corticosteroid/tetracycline recovered. Two required hospitalization – a 99‐year‐old woman who had a BP flare after recovery and entered hospice care soon thereafter and a 102‐year‐old woman with BP treated with tocilizumab and supplemental oxygen. The five patients in the methotrexate group recovered at home. The three patients treated with mycophenolate mofetil recovered, one after intensive care unit admission, tocilizumab, high‐dose steroids and ventilation, and one after a hospital course complicated by embolic stroke, deep vein thrombosis and pulmonary embolism. The recovery of 17 of 19 patients with AIBD who had documented SARS‐CoV‐2 infection in our single institution cohort, despite advanced age and comorbidities, is reassuring. The two deaths were in individuals treated with rituximab < 6 months before infection, suggesting that recent rituximab therapy may increase risk of poor outcomes. These findings complement observations of decreased hospitalization rates of infected patients with AIBD with increasing intervals post rituximab3 and a 4·04‐fold increase in death among rheumatology patients on rituximab,4 and likely reflect the kinetics of B cell reconstitution following depletion.7 Thus, our data provide specific rational supporting expert guidelines to weigh the risks of rituximab relative to other immunosuppressive therapies for AIBD during this pandemic.8 Although larger datasets are needed, our observations suggest that patients on rituximab be counselled about the increased risks for poor COVID‐19 outcomes. Patients should␣be vaccinated prior to therapy when possible, and dermatologists should consider confirming response with SARS‐CoV‐2 spike protein IgG serologies. Finally, the observations in this cohort, although small, provide rationale for the immediate use of COVID‐19 monoclonal antibodies such as bamlanivimab, etesevimab, casirivimab and imdevimab after SARS‐CoV‐2 detection in dermatology patients treated with rituximab in the previous 6 months. Erica Hwang: Conceptualization (supporting); Data curation (supporting); Formal analysis (supporting); Funding acquisition (supporting); Investigation (supporting); Methodology (supporting); Project administration (supporting); Resources (supporting); Software (equal); Supervision (supporting); Validation (supporting); Visualization (equal); Writing‐original draft (lead); Writing‐review & editing (supporting). Mary M Tomayko: Conceptualization (lead); Data curation (lead); Formal analysis (lead); Funding acquisition (lead); Investigation (lead); Methodology (equal); Project administration (equal); Resources (lead); Software (equal); Supervision (lead); Validation (lead); Visualization (equal); Writing‐original draft (supporting); Writing‐review & editing (lead). Funding sources: E.H. was supported by NIH/NHLBI training grant T35HL007649. Conflicts of interest: the authors declare they have no conflicts of interest. Data availability: the data that support the findings of this study are available on request from the corresponding author. The data are not publicly available owing to privacy or ethical restrictions.

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How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.009
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Case report · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.003
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.009
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0030.002
Insufficient payload (model declined to judge)0.0030.001

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 head0.012
GPT teacher head0.250
Teacher spread0.238 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designCase report
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".

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Citations4
Published2021
Admission routes1
Has abstractyes

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