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Record W4200112797 · doi:10.1016/j.annonc.2021.12.006

COVID-19 vaccination and breakthrough infections in patients with cancer

2021· article· en· W4200112797 on OpenAlexaff
Andrew Schmidt, Chris Labaki, Chih–Yuan Hsu, Ziad Bakouny, Nino Balanchivadze, Stephanie Berg, Sibel Blau, Ahmad Daher, Talal El Zarif, Christopher R. Friese, Elizabeth A. Griffiths, Jessica E. Hawley, Brandon Hayes‐Lattin, Vidhya Karivedu, Tahir Latif, Blanche H. Mavromatis, Rana R. McKay, Gayathri Nagaraj, Ryan H. Nguyen, Orestis A. Panagiotou, Andrew J. Portuguese, Matthew Puc, Míriam Santos Dutra, Brett Schroeder, Astha Thakkar, Elizabeth Wulff‐Burchfield, Sanjay Mishra, Dimitrios Farmakiotis, Yu Shyr, Jeremy L. Warner, Toni K. Choueiri, Nathan Duma, Petros Grivas, Gilberto Lopes, Corrie Painter, Solange Peters, Brian I. Rini, Dimpy P. Shah, Michael Thompson

Bibliographic record

VenueAnnals of Oncology · 2021
Typearticle
Languageen
FieldMedicine
TopicCOVID-19 and healthcare impacts
Canadian institutionsJewish General Hospital
FundersNational Center for Advancing Translational SciencesNational Cancer InstituteNational Institutes of Health
KeywordsMedicineVaccinationCancerImmunologyMalignancyIntensive care medicineInternal medicine

Abstract

fetched live from OpenAlex

•Patients with cancer who develop breakthrough COVID-19 following full vaccination remain susceptible to severe outcomes.•Hematologic malignancies are over-represented among vaccinated patients with cancer who develop breakthrough COVID-19.•Vaccination of close contacts, masking, boosters, and social distancing are needed to protect patients with cancer. BackgroundVaccination is an important preventive health measure to protect against symptomatic and severe COVID-19. Impaired immunity secondary to an underlying malignancy or recent receipt of antineoplastic systemic therapies can result in less robust antibody titers following vaccination and possible risk of breakthrough infection. As clinical trials evaluating COVID-19 vaccines largely excluded patients with a history of cancer and those on active immunosuppression (including chemotherapy), limited evidence is available to inform the clinical efficacy of COVID-19 vaccination across the spectrum of patients with cancer.Patients and methodsWe describe the clinical features of patients with cancer who developed symptomatic COVID-19 following vaccination and compare weighted outcomes with those of contemporary unvaccinated patients, after adjustment for confounders, using data from the multi-institutional COVID-19 and Cancer Consortium (CCC19).ResultsPatients with cancer who develop COVID-19 following vaccination have substantial comorbidities and can present with severe and even lethal infection. Patients harboring hematologic malignancies are over-represented among vaccinated patients with cancer who develop symptomatic COVID-19.ConclusionsVaccination against COVID-19 remains an essential strategy in protecting vulnerable populations, including patients with cancer. Patients with cancer who develop breakthrough infection despite full vaccination, however, remain at risk of severe outcomes. A multilayered public health mitigation approach that includes vaccination of close contacts, boosters, social distancing, and mask-wearing should be continued for the foreseeable future. Vaccination is an important preventive health measure to protect against symptomatic and severe COVID-19. Impaired immunity secondary to an underlying malignancy or recent receipt of antineoplastic systemic therapies can result in less robust antibody titers following vaccination and possible risk of breakthrough infection. As clinical trials evaluating COVID-19 vaccines largely excluded patients with a history of cancer and those on active immunosuppression (including chemotherapy), limited evidence is available to inform the clinical efficacy of COVID-19 vaccination across the spectrum of patients with cancer. We describe the clinical features of patients with cancer who developed symptomatic COVID-19 following vaccination and compare weighted outcomes with those of contemporary unvaccinated patients, after adjustment for confounders, using data from the multi-institutional COVID-19 and Cancer Consortium (CCC19). Patients with cancer who develop COVID-19 following vaccination have substantial comorbidities and can present with severe and even lethal infection. Patients harboring hematologic malignancies are over-represented among vaccinated patients with cancer who develop symptomatic COVID-19. Vaccination against COVID-19 remains an essential strategy in protecting vulnerable populations, including patients with cancer. Patients with cancer who develop breakthrough infection despite full vaccination, however, remain at risk of severe outcomes. A multilayered public health mitigation approach that includes vaccination of close contacts, boosters, social distancing, and mask-wearing should be continued for the foreseeable future.

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 score0.074
Threshold uncertainty score0.647

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 head0.125
GPT teacher head0.494
Teacher spread0.369 · 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".

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Citations102
Published2021
Admission routes1
Has abstractyes

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