Evidence map›Paper›PMID 39854167›Full record

ArticleACR open rheumatology2025

Prevalence of Autoimmune Diseases in Patients Treated With Immune Checkpoint Inhibitors: An Epidemiological Study Using A Global Network of Health Care Organizations.

Pushti Khandwala, Devashish Desai, Arthur Lau

Abstract read
In one paragraph

Article in ACR open rheumatology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
–field-weighted citation impact
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

4 citing papers in PubMed.

  1. Review
  2. Article
  3. Review
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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

3 authors.

Pushti KhandwalaJefferson Einstein Philadelphia Hospital, Philadelphia, Pennsylvania.ORCID https://orcid.org/0000-0003-4304-0785
Devashish DesaiSUNY Upstate Medical University, Syracuse, New York.
Arthur LauJefferson Einstein Philadelphia Hospital, Philadelphia, Pennsylvania.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveEvaluate prevalence of new onset autoimmune conditions (ACs) after commencement of immune checkpoint inhibitors (ICIs).

methodsThis retrospective observational study was done using TriNetX. Patients with neoplasm for which ICIs were approved were stratified into two groups based on ICI use. Multivariate Cox proportional hazard models and Kaplan Meier method were used to assess risk of developing ACs among the groups. Subgroup analysis was done to evaluate risk of ACs in patients receiving cytotoxic T-lymphocyte-associated protein 4 inhibitor (CTLA4i) versus program cell death protein 1 inhibitor (PD1i) and program death ligand 1 inhibitor (PDL1i) inhibitors and combination treatment (CT) (CTLA4 + PD1i/PDL1i) versus PD1i/PDL1i.

resultsPatients who received ICIs (2.03% of total population) were younger (68.7 ± 12.6 vs 71.8 ± 13.9; P < 0.001), predominantly male (54% vs 41%; P < 0.0001), and White (68% vs 58%; P < 0.0001), had lower odds of developing systemic lupus erythematosus (SLE) (0.366% vs 0.437%, odds ratio [OR] 0.837; P = 0.0005) and systemic sclerosis (0.108% vs 0.135%, OR 0.796; P = 0.0151), and had higher odds of developing rheumatoid arthritis (RA) (2.194% vs 1.752%, OR 1.258; P < 0.0001 with hazard ratio 1.746; P < 0.0001). There was no significant difference in developing vasculitis, dermatopolymyositis, and psoriatic arthritis when compared to patients who did not receive ICIs. The prevalence of ACs remained true after propensity score matching, except that there was no difference compared with the prevalence of SLE (0.37% [n = 391] vs 0.393% n = 415], OR 0.942 [0.82-1.082]; P = 0.3970).

conclusionPatients receiving ICIs have an increased risk of developing ACs, especially RA. There needs to be a high index of suspicion and awareness about ACs for prescribers of ICIs.

Identifiers

PMID39854167
PMCPMC11760991

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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.