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Record W3212269438 · doi:10.1182/blood-2021-149652

COVID-19 Vaccine Response in Patients with Hematologic Malignancy: A Systematic Review and Meta-Analysis

2021· review· en· W3212269438 on OpenAlexaff
Inna Y. Gong, Abi Vijenthira, Stephen Betschel, Lisa K. Hicks, Matthew C. Cheung

Bibliographic record

VenueBlood · 2021
Typereview
Languageen
FieldMedicine
TopicSARS-CoV-2 and COVID-19 Research
Canadian institutionsInstitute for Clinical Evaluative SciencesHealth Sciences CentreSunnybrook Health Science CentreSt. Michael's HospitalPrincess Margaret Cancer CentreUniversity of Toronto
Fundersnot available
KeywordsMedicineHematologic malignancyMalignancyInternal medicineMeta-analysisCancerVaccinationPopulationImmunology

Abstract

fetched live from OpenAlex

Abstract Introduction: Emerging data suggests that seroresponse (SR) in patients with hematologic malignancy following COVID-19 vaccination is likely lower than in patients without blood cancer. The objective of this study was to perform a systematic review and meta-analysis on SR in patients with hematologic malignancy who received COVID-19 vaccination (submitted to PROSPERO for registration). Methods: We searched PubMed and EMBASE from December 1, 2020, to July 22, 2021, to identify studies of SR following COVID-19 vaccine in adult patients with hematologic malignancy (including studies in which patients with hematologic malignancy represented a subset of a broader population). Patients with positive serologic response at baseline (prior to vaccination) or known COVID-19 infection were excluded. The primary outcomes were pooled SR estimates following COVID-19 vaccination in patients with hematologic malignancy, and pooled SR estimates of subgroups based on hematologic malignancy type. Secondary outcomes were pooled relative risk ratio (RR; compared to non-cancer controls) based on dichotomous-effect SR in all patients, and subgroups based on hematologic malignancy type, treatment status, and use of anti-CD20 therapy. Pooled estimates and RR with its associated 95% confidence intervals (CIs) were calculated using MetaXL (EpiGear), and Reference Manager (Cochrane) using random effects model. Results A total of 17 studies comprising 2834 patients with hematologic malignancy from Europe, United Kingdom and North America were included (Figure 1). The pooled estimate for SR was 58% (95% CI 48-67%, I 2 95%), with a RR of 0.53 (95% 0.42-0.66, I 2 94%) when compared to controls (10 studies with comparison group, 1092 hematologic malignancy patients, 830 controls; Figure 2). The pooled estimate for SR varied by type of hematologic malignancy: lymphomas SR 52% (95% CI 36-68%, 7 studies, 832 patients, I 2 94%); chronic lymphocytic leukemia (CLL) SR 42% (95% CI 25-60%, 6 studies, 921 patients, I 2 93%); plasma cell dyscrasias SR 66% (95% CI 47-83%, 8 studies, 611 patients, I 2 95%); myeloproliferative neoplasms (MPNs, including chronic myelogenous leukemia) SR 83% (95% CI 68-95%, 6 studies, 227 patients, I 2 58%); acute leukemia SR 86% (95% CI 77-94%, 2 studies, 67 patients, 46 acute myelogenous leukemia [AML] and 15 acute lymphocytic leukemia], I 2 0%). The RR for SR also varied by type of hematologic malignancy: lymphomas (excluding CLL) RR 0.48 (95% CI 0.34-0.68, 4 studies, 337 patients, I 2 89%); CLL RR 0.37 (95% CI 0.25-0.53, 3 studies, 194 patients, I 2 54%); plasma cell dyscrasias RR 0.73 (95% CI 0.62-0.86, 5 studies, 323 patients, I 2 70%); RR MPN 0.78 (95% CI 0.62-0.99, 3 studies, 199 patients, I 2 90%). The pooled estimate for SR in those receiving treatment was 42% (95% CI 26-58%, 9 studies, 683 patients, I 2 94%). The pooled estimates for SR for those receiving anti-CD20, bruton tyrosine kinase inhibitor (BTKi), or venetoclax were 13% (95% CI 1-32%, 6 studies, 367 patients, I 2 88%), 42% (95% CI 17-71%, 3 studies, 319 patients, I 2 75%), and 20% (95% CI 0-54%, 3 studies, 39 patients, I 2 66%), respectively. The RR for those receiving treatment for their hematologic malignancy compared to those who were not receiving treatment was 0.51 (95% CI 0.37-0.71, 8 studies, 579 patients, I 2 89%; Figure 3). . The RR of patients receiving anti-CD20 therapy compared to non-cancer controls was 0.13 (95% CI 0.02-0.93, 102 patients, I 2 73%). For patients treated with anti-CD20 therapy, the RR of those receiving vaccination within 9-12 months compared to beyond 9-12 months was 0.12 (95% CI 0.06-0.25, 2 studies, 74 patients, I 2 0%; Figure 4). Conclusion: Our systematic review and meta-analysis suggests that patients with hematologic malignancy have a lower SR rate following vaccination compared to controls. Furthermore, SR is variable across different types of hematologic malignancy, with very good response rates seen in patients with myeloid diseases (MPN and AML) and poor response rates seen in lymphoma and CLL. Active treatment, particularly anti-CD20 therapy within 12 months of vaccination, is associated with a particularly low SR following vaccination. Additional studies are needed to understand non-humoral responses to vaccination, and to guide decisions regarding how to optimize vaccine response in patients with blood cancer. We plan to update the systematic review and meta-analysis as more data become available. Figure 1 Figure 1. Disclosures No relevant conflicts of interest to declare.

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)0.013
metaresearch head score (Gemma)0.032
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Meta-analysis · Consensus signal: Meta-analysis
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.015
Threshold uncertainty score0.067

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0130.032
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0150.034
Bibliometrics0.0060.007
Science and technology studies0.0010.001
Scholarly communication0.0030.002
Open science0.0020.001
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0030.000

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 head0.103
GPT teacher head0.397
Teacher spread0.294 · 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 designMeta-analysis
Domainnot available
GenreReview

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

Citations9
Published2021
Admission routes1
Has abstractyes

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