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Record W4400118846 · doi:10.1016/j.vaccine.2024.06.041

COVID-19 vaccine immunogenicity and safety surrounding fourth and subsequent vaccine doses in patients with hematologic malignancies

2024· article· en· W4400118846 on OpenAlexaffabout
Sita Bhella, Allison M. Wilkin, Katrina Hueniken, Abi Vijenthira, Michaël Sébag, Peng Wang, Lisa K. Hicks, Annette E. Hay, Sarit Assouline, Graeme Fraser, Amaris Balitsky, Joy Mangel, Carolyn Owen, Anthony Reiman, Laurie H. Sehn, Heather J. Sutherland, Tinghua Zhang, Corey Arnold, Tamara Leite, Erinn McCarthy, Curtis Cooper, Marc‐André Langlois, C. Arianne Buchan

Bibliographic record

VenueVaccine · 2024
Typearticle
Languageen
FieldMedicine
TopicSARS-CoV-2 and COVID-19 Research
Canadian institutionsUniversity of British ColumbiaSaint John Regional HospitalVancouver General HospitalPrincess Margaret Cancer CentreUniversity of CalgarySt. Michael's HospitalJewish General HospitalMcMaster UniversityQueen's UniversityUniversity of TorontoWestern UniversityUniversity of AlbertaUniversity of OttawaMcGill University Health CentreOttawa Hospital
Fundersnot available
KeywordsImmunogenicityMedicineAntibodyVaccinationImmune systemImmunologyHematologic malignancyInternal medicineVirology

Abstract

fetched live from OpenAlex

BACKGROUND: Immune response to COVID-19 vaccine is diminished in patients with hematologic malignancy. There is limited data regarding response to vaccine doses in these patients. PURPOSE: To quantify the humoral immune response engendered by 4th and subsequent doses of SARS-CoV-2 vaccination as measured by anti-Spike (anti-S) antibody levels, based on dried blood spot (DBS) testing, in patients with hematologic malignancies. Anti-S binds to the spike protein of the SARS-CoV-2 virus and is indicative of vaccine immunogenicity. METHODS: We conducted a prospective study of hematologic malignancies between August 2021 and January 2023 at 12 sites across Canada. Participants were followed longitudinally and submitted finger-prick DBS cards at set intervals associated with vaccination. Samples were processed via high throughput ELISA assay to detect serum antibodies against nucleocapsid (N) and spike (S) proteins. RESULTS: We obtained 3071 samples on 790 unique patients. Of these, 372 unique participants with 1840 samples had anti-S results available post-4th, 5th or 6th COVID-19 vaccine dose and were included for analysis. Three hundred thirty-three patients of the 372 participants submitted a DBS sample post 4th dose. Of these, 257 patients (77.2%) had a positive anti-S antibody. A total of 198 patients had paired samples pre- and post-dose 4, of which 59 (29.7%) had a negative anti-S antibody pre-dose 4. Of these, 20 (33.4%) developed positive anti-S antibody post-dose 4. One hundred forty-nine patients submitted a DBS sample post-dose 5. Of these, 135 patients (90.6%) had positive anti-S antibody. A total of 52 had paired samples pre- and post-dose 5. Six (8.7%) had a negative anti-S antibody pre-dose 5, of which two (33.3%) developed positive anti-S antibody post-dose 5. Of these 372 patients, 123 (34%) reported COVID-19 infection and 4 (1%) had a COVID-19 related hospitalization. There were no reported deaths from COVID-19. CONCLUSIONS: This prospective cohort study showed that humoral immune response improved with subsequent doses of COVID-19 vaccines.

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 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)0.000
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.021
Threshold uncertainty score0.042

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
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)0.0010.000

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 head0.028
GPT teacher head0.311
Teacher spread0.283 · 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 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

Citations7
Published2024
Admission routes2
Has abstractyes

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