Evidence map›Paper›PMID 38633444›Full record

ArticleInfectious diseases & clinical microbiology2024

Individualized High Dose Intravenous Anakinra Treatment in Cancer Patients with COVID-19 Associated Cytokine Storm: A Retrospective Controlled Study.

Ramazan Çakmak, Murat Bektaş

Open access · hybridAbstract read
In one paragraph

Article in Infectious diseases & clinical microbiology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact, top 96% 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

0 citing papers in PubMed, 0 citations in OpenAlex.

No citing paper in PubMed yet.

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

2 authors at 1 institution in 1 country.

Ramazan ÇakmakDepartment of Internal Medicine, Division of Endocrinology and Metabolism, İstinye University School of Medicine, İstanbul, Türkiye.ORCID https://orcid.org/0000-0003-3815-7444
Murat BektaşDepartment of Internal Medicine, Division of Rheumatology, Aksaray Training and Research Hospital, Aksaray, Türkiye.ORCID https://orcid.org/0000-0002-1788-3837
Aksaray University · TR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objective: Patients with COVID-19 accompanying cancer have been reported to have higher morbidity and mortality. In this study, we aimed to evaluate the high-dose high intravenous anakinra treatment response and outcome in patients with COVID-19-associated cytokine storm accompanying cancer. Materials and Methods: This retrospective observational study was carried out at a tertiary referral center between September 01, 2021, and February 01, 2022, in Turkey. The study population consisted of two groups: patients receiving high-dose intravenous anakinra and patients treated with standard care. Results: Data from 146 patients in the anakinra group and 114 patients in the control group were analyzed. Malignancy frequency was 11% (n=16) in the anakinra group and 7% (n=8) in the control group. In survival analysis, a significantly lower survival rate was observed in patients with malignancy than those without in the control group (log-rank: Conclusion: In the control group, mortality was higher in patients with malignancy compared to those without malignancy, but not in the anakinra group. Also, mortality was higher in patients receiving SoC compared to anakinra. Intravenous high-dose anakinra treatment is safe and effective in patients with COVID-19 accompanying cancer.

Indexed as

anakinracancerCOVID-19cytokine stormhyperinflammation

Identifiers

PMID38633444
PMCPMC11019726
OpenAlexW4392697956

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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.