Evidence map›Paper›PMID 34196388›Full record

ArticleBritish journal of haematology2021

Humoral response rate and predictors of response to BNT162b2 mRNA COVID19 vaccine in patients with multiple myeloma.

Irit Avivi, Roi Balaban, Tamir Shragai, Gabi Sheffer, Miguel Morales, Anat Aharon, Noa Lowenton-Spier, Svetlana Trestman, Chava Perry, Noam Benyamini and 7 more

Open access · bronzeAbstract read
In one paragraph

Article in British journal of haematology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 55 papers, 12 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
55citing papers in PubMed, 12 pooled it
10.4field-weighted citation impact, top 1% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

55 citing papers in PubMed, 12 syntheses or guidelines pooled it, 74 citations in OpenAlex.

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  10. Immunological and clinical efficacy of COVID-19 vaccines in immunocompromised populations: a systematic review.Clinical microbiology and infection : the official publication of the European Society of Clinical Microbiology and Infectious Diseases · 2022
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

17 authors at 2 institutions in 1 country.

Irit AviviDepartment of Hematology, Tel Aviv Sourasky Medical Center, Tel Aviv, Israel.ORCID 0000-0001-8663-444X
Roi BalabanDepartment of Hematology, Tel Aviv Sourasky Medical Center, Tel Aviv, Israel.
Tamir ShragaiDepartment of Hematology, Tel Aviv Sourasky Medical Center, Tel Aviv, Israel.ORCID 0000-0002-3741-689X
Gabi ShefferDepartment of Hematology, Tel Aviv Sourasky Medical Center, Tel Aviv, Israel.
Miguel MoralesDepartment of Hematology, Tel Aviv Sourasky Medical Center, Tel Aviv, Israel.
Anat AharonDepartment of Hematology, Tel Aviv Sourasky Medical Center, Tel Aviv, Israel.
Noa Lowenton-SpierDepartment of Hematology, Tel Aviv Sourasky Medical Center, Tel Aviv, Israel.
Svetlana TrestmanDepartment of Hematology, Tel Aviv Sourasky Medical Center, Tel Aviv, Israel.
Chava PerryDepartment of Hematology, Tel Aviv Sourasky Medical Center, Tel Aviv, Israel.
Noam BenyaminiDepartment of Hematology, Tel Aviv Sourasky Medical Center, Tel Aviv, Israel.
Moshe MittelmanDepartment of Hematology, Tel Aviv Sourasky Medical Center, Tel Aviv, Israel.
Yaara TabibDepartment of Hematology, Tel Aviv Sourasky Medical Center, Tel Aviv, Israel.
Tali Bar LevDepartment of Hematology, Tel Aviv Sourasky Medical Center, Tel Aviv, Israel.
Mor ZavaroDepartment of Hematology, Tel Aviv Sourasky Medical Center, Tel Aviv, Israel.
Yair HerishanuDepartment of Hematology, Tel Aviv Sourasky Medical Center, Tel Aviv, Israel.
Efrat LuttwakDepartment of Hematology, Tel Aviv Sourasky Medical Center, Tel Aviv, Israel.
Yael C CohenDepartment of Hematology, Tel Aviv Sourasky Medical Center, Tel Aviv, Israel.ORCID 0000-0002-9061-7287
Tel Aviv University · ILTel Aviv Sourasky Medical Center · IL

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Multiple myeloma (MM) patients are at excess risk for clinically significant COVID19 infection. BNT162b2 mRNA COVID19 (BNT162b2) vaccine provides effective protection against COVID19 for the general population, yet its effect in MM patients may be compromised due to disease and therapy-related factors and was not yet evaluated. This single-centre prospective study included MM patients tested for serological response 14-21 days post second vaccine. Vaccinated healthy volunteers served as controls. In all, 171 MM patients, median age 70 (38-94) were included; 159 active MM and 12 smouldering myeloma (SMM). Seropositive response rate (median titer) was 76% (91 U/ml) in active MM patients vs 98% (992 U/ml) in the 64 controls (P < 0·0001), and 100% (822 U/ml) in SMM patients. Multivariate analysis revealed older age (P = 0·009), exposure to ≥4 novel anti-myeloma drugs (P = 0·02) and hypogammaglobulinaemia (P = 0·002) were associated with lower response rates. None of the novel agents significantly decreased response rate, whereas daratumumab trended towards reduced response (P = 0·08). Adverse events occurred in 53% and 55% of the MM patients and controls, respectively, all transient grade 1-2. In conclusion, BNT162b2 vaccine was safe and provided a high seropositivity rate in MM patients, independent of treatment type. Older, hypogammaglobulinaemic and heavily pretreated patients had lower response rates.

Indexed as

AdultAgammaglobulinemiaAgedAged, 80 and overAntibodies, MonoclonalBNT162 VaccineCase-Control StudiesCOVID-19COVID-19 VaccinesFemaleHumansImmunity, HumoralMaleMiddle AgedMultiple MyelomaMultivariate AnalysisAntibodies, MonoclonalBNT162 VaccineCOVID-19 Vaccinesdaratumumabantibody responseBNT162b2COVID19 vaccinemultiple myeloma

Identifiers

PMID34196388
PMCPMC8444771
OpenAlexW3176755586

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.