Evidence map›Paper›PMID 39012903›Full record

ArticlePloS one2024

Pre-existing autoimmune disease as a risk factor for immune-related adverse events in cancer patients receiving immune checkpoint inhibitors.

Hidetoshi Sumimoto, Satoshi Noda, Hiroyoshi Koide, Yutaro Douke, Kosuke Sakai, Akihito Nishikawa, Azumi Tomioka, Maki Hori, Hiromi Nakato, Yuri Kimura and 5 more

Abstract read
In one paragraph

Article in PloS one, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers.

0numbers the graph read from it
0cells of the map it votes in
19citing 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

19 citing papers in PubMed.

  1. Review
  2. Article
  3. Article
  4. Review
  5. Review
  6. Article
  7. Review
  8. Article
  9. Review
  10. Review
  11. Article
  12. Article
  13. Article
  14. Review
  15. Article
  16. Article
  17. Article
  18. Article
  19. 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

15 authors.

Hidetoshi SumimotoDepartment of Medical Oncology, Shiga University of Medical Science, Otsu, Shiga, Japan.
Satoshi NodaDepartment of Pharmacy, Shiga University of Medical Science Hospital, Otsu, Shiga, Japan.
Hiroyoshi KoideDepartment of Pharmacy, Shiga University of Medical Science Hospital, Otsu, Shiga, Japan.
Yutaro DoukeDepartment of Pharmacy, Shiga University of Medical Science Hospital, Otsu, Shiga, Japan.
Kosuke SakaiDepartment of Pharmacy, Shiga University of Medical Science Hospital, Otsu, Shiga, Japan.
Akihito NishikawaCancer Center, Shiga University of Medical Science, Otsu, Shiga, Japan.
Azumi TomiokaCancer Center, Shiga University of Medical Science, Otsu, Shiga, Japan.
Maki HoriCancer Center, Shiga University of Medical Science, Otsu, Shiga, Japan.
Hiromi NakatoCancer Center, Shiga University of Medical Science, Otsu, Shiga, Japan.
Yuri KimuraCancer Center, Shiga University of Medical Science, Otsu, Shiga, Japan.
Aya TokudaCancer Center, Shiga University of Medical Science, Otsu, Shiga, Japan.
Atsushi TakanoDepartment of Medical Oncology, Shiga University of Medical Science, Otsu, Shiga, Japan.
Koji TeramotoDepartment of Medical Oncology, Shiga University of Medical Science, Otsu, Shiga, Japan.
Satoshi MurataCancer Center, Shiga University of Medical Science, Otsu, Shiga, Japan.
Yataro DaigoDepartment of Medical Oncology, Shiga University of Medical Science, Otsu, Shiga, Japan.ORCID 0000-0002-0915-3025

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Immune checkpoint inhibitors (ICIs) have been widely used as standard therapies for various cancers. However, in 20-30% of cases, ICIs can lead to immune-related adverse events (irAEs), which sometimes require discontinuation of treatment. Due to the increased risk of irAEs, patients with pre-existing autoimmune diseases (AI) are often advised against receiving ICIs. However, there has not been sufficient objective risk assessment for AI. In our study, we conducted logistic regression analysis to assess the risk of irAEs by analyzing 478 cases that received anti-PD-(L)1 Ab and/or anti-CTLA4 Ab at our hospital between April 3, 2017, and May 24, 2022. Among these cases, 28 (5.9%) had pre-existing AI. We selected several independent factors for analysis: gender, age, performance status (PS), cancer type, type of ICI, type of combined anti-cancer agents, best overall response, and pre-existing AI. The adjusted odds ratio (OR) of AI for irAE occurrence was 2.52 [95% CI: 1.08-5.86] (p = 0.033), and the adjusted OR of AI for ICI discontinuation due to irAE was 3.32 [1.41-7.78] (p = 0.006). Patients with pre-existing AI experienced a significantly shorter irAE-free survival time compared to those without AI (median irAE-free survival: 5.7 months [95% CI: 3.5-7.8] vs 10.4 months [95% CI: 7.9-12.9], respectively, p = 0.035). Frequently observed irAEs in full ICI cohort, such as dermatologic issues (7.5%), pneumonitis (7.1%), hepatitis (4.6%), and hypothyroidism (4.2%), were often accompanied by pre-existing AI. Furthermore, pre-existing AI flared up in 6 cases (37.5% in AI-positive irAE-positive cases). The activity of AI was not related to the occurrence of irAEs. Grade 3 or higher irAEs were observed in 6 out of 20 (30.0%) cases in AI-accompanied patients complicated with irAEs. Although having a complicated AI increases the risk of irAEs, it may not necessarily be a contraindication for ICI treatment if closely monitored. (292<300 characters).

Indexed as

Autoimmune DiseasesImmune Checkpoint InhibitorsNeoplasmsAdultAgedAged, 80 and overCTLA-4 AntigenFemaleHumansMaleMiddle AgedRetrospective StudiesRisk FactorsCTLA-4 AntigenImmune Checkpoint Inhibitors

Identifiers

PMID39012903
PMCPMC11251620

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.