Evidence map›Paper›PMID 38349446›Full record

ArticleInternational journal of hematology2024

Chimeric antigen receptor T-cell therapy after COVID-19 in refractory high-grade B-cell lymphoma.

Kenta Hayashino, Keisuke Seike, Kanako Fujiwara, Kaho Kondo, Chisato Matsubara, Toshiki Terao, Wataru Kitamura, Chihiro Kamoi, Hideaki Fujiwara, Noboru Asada and 6 more

Open access · hybridAbstract readCase Reports
In one paragraph

Article in International journal of hematology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
0.8field-weighted citation impact, top 25% 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

2 citing papers in PubMed, 3 citations in OpenAlex.

  1. Article
  2. Review
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

16 authors at 1 institution in 1 country.

Kenta HayashinoDepartment of Hematology and Oncology, Okayama University Hospital, 2-5-1 Shikata, Okayama-shi, Okayama, Japan.
Keisuke SeikeDepartment of Hematology and Oncology, Okayama University Hospital, 2-5-1 Shikata, Okayama-shi, Okayama, Japan. pq2k5tsg@okayama-u.ac.jp.ORCID http://orcid.org/0000-0002-3484-0265
Kanako FujiwaraDepartment of Hematology and Oncology, Okayama University Hospital, 2-5-1 Shikata, Okayama-shi, Okayama, Japan.
Kaho KondoDepartment of Hematology and Oncology, Okayama University Hospital, 2-5-1 Shikata, Okayama-shi, Okayama, Japan.
Chisato MatsubaraDepartment of Hematology and Oncology, Okayama University Hospital, 2-5-1 Shikata, Okayama-shi, Okayama, Japan.
Toshiki TeraoDepartment of Hematology and Oncology, Okayama University Hospital, 2-5-1 Shikata, Okayama-shi, Okayama, Japan.
Wataru KitamuraDepartment of Hematology and Oncology, Okayama University Hospital, 2-5-1 Shikata, Okayama-shi, Okayama, Japan.
Chihiro KamoiDivision of Blood Transfusion, Okayama University Hospital, 2-5-1 Shikata, Okayama-shi, Okayama, Japan.
Hideaki FujiwaraDepartment of Hematology and Oncology, Okayama University Hospital, 2-5-1 Shikata, Okayama-shi, Okayama, Japan.
Noboru AsadaDepartment of Hematology and Oncology, Okayama University Hospital, 2-5-1 Shikata, Okayama-shi, Okayama, Japan.
Hisakazu NishimoriDepartment of Hematology and Oncology, Okayama University Hospital, 2-5-1 Shikata, Okayama-shi, Okayama, Japan.
Daisuke EnnishiCenter for Comprehensive Genomic Medicine, Okayama University Hospital, 2-5-1 Shikata, Okayama-shi, Okayama, Japan.
Keiko FujiiDivision of Clinical Laboratory, Okayama University Hospital, 2-5-1 Shikata, Okayama-shi, Okayama, Japan.
Nobuharu FujiiDivision of Blood Transfusion, Okayama University Hospital, 2-5-1 Shikata, Okayama-shi, Okayama, Japan.
Ken-Ichi MatsuokaDepartment of Hematology and Oncology, Okayama University Hospital, 2-5-1 Shikata, Okayama-shi, Okayama, Japan.
Yoshinobu MaedaDepartment of Hematology and Oncology, Okayama University Hospital, 2-5-1 Shikata, Okayama-shi, Okayama, Japan.
Okayama University Hospital · JP

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Although chimeric antigen receptor T-cell (CAR-T) therapies have dramatically improved the outcomes of relapsed/refractory B-cell malignancies, recipients suffer from severe humoral immunodeficiencies. Furthermore, patients with coronavirus disease 2019 (COVID-19) have a poor prognosis, as noted in several case reports of recipients who had COVID-19 before the infusion. We report the case of a 70-year-old woman who developed COVID-19 immediately before CAR-T therapy for high-grade B-cell lymphoma. She received Tixagevimab-Cilgavimab chemotherapy and radiation therapy but never achieved remission. She was transferred to our hospital for CAR-T therapy, but developed COVID-19. Her symptoms were mild and she was treated with long-term molnupiravir. On day 28 post-infection, lymphodepleting chemotherapy was restarted after a negative polymerase chain reaction (PCR) test was confirmed. The patient did not experience recurrence of COVID-19 symptoms or severe cytokine release syndrome. Based on the analysis and comparison of the previous reports with this case, we believe that CAR-T therapy should be postponed until a negative PCR test is confirmed. In addition, Tixagevimab-Cilgavimab and long term direct-acting antiviral agent treatment can be effective prophylaxis for severe COVID-19 and shortening the duration of infection.

Indexed as

COVID-19Hepatitis C, ChronicLymphoma, Large B-Cell, DiffuseReceptors, Chimeric AntigenAgedAntigens, CD19Antiviral AgentsCell- and Tissue-Based TherapyFemaleHumansImmunotherapy, AdoptiveAntigens, CD19Antiviral AgentsReceptors, Chimeric AntigenCAR-T-cell therapyCOVID-19LymphomaMolnupiravir

Identifiers

PMID38349446
PMCPMC10960909
OpenAlexW4391781953

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.