Evidence map›Paper›PMID 37693493›Full record

ArticlemedRxiv : the preprint server for health sciences2023

Pre-Existing Inflammatory Disease Predicts Cutaneous Immunotherapy Toxicity Development: A Multi-Institutional Cohort Study.

Guihong Wan, Nga Nguyen, Bonnie W Leung, Hannah Rashdan, Kimberly Tang, Katie Roster, Michael R Collier, Pearl O Ugwu-Dike, Neel S Raval, Nora A Alexander and 10 more

Open access · greenAbstract readPreprint
In one paragraph

Article in medRxiv : the preprint server for health sciences, 2023. 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
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, 1 citations in OpenAlex.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

20 authors at 4 institutions in 1 country.

Guihong Wan
Nga Nguyen
Bonnie W Leung
Hannah Rashdan
Kimberly Tang
Katie Roster
Michael R Collier
Pearl O Ugwu-Dike
Neel S Raval
Nora A Alexander
Ruple Jairath
Jordan Phillipps
Munachimso Amadife
Shijia Zhang
Alexander Gusev
Steven T Chen
Kerry L Reynolds
Nicole R LeBoeuf
Shawn G Kwatra
Yevgeniy R Semenov
Massachusetts General Hospital · USDana-Farber Cancer Institute · USHarvard University · USJohns Hopkins University · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Relationships between pre-existing inflammatory diseases (pIDs) and cutaneous immune-related adverse events (cirAEs) have not been well-studied. This study is to investigate associations between pIDs and cirAEs among immune-checkpoint inhibitor (ICI) recipients at the Mass General Brigham healthcare system. Methods: Electronic health records were reviewed to ascertain cirAE status. Patients' pID status was determined using International Classification of Diseases (ICD) codes. Cox proportional hazard, logistic regression, and linear regression models were performed. Results: Among 3607 ICI recipients, 1354 had pIDs, and 672 developed cirAEs. After covariate adjustments, patients with cutaneous pIDs (HR:1.56, p<0.001) or both cutaneous and non-cutaneous pIDs (HR:1.76, p<0.001) had increased cirAE risk in contrast to patients with non-cutaneous pIDs alone (HR:1.01, p=0.9). In adjusted ordinal logistic regression modeling, cutaneous pIDs (OR:1.55, p<0.0001) and the presence of both cutaneous pIDs and non-cutaneous pIDs (OR:1.71, p=0.002) were associated with increased cirAE severity. The time to cirAE onset was different between the cutaneous pID group and the non-cutaneous pID group (Mean: 98 vs. 146 days, p=0.021; Beta: -0.11, p=0.033). Conclusions: ICI recipients with cutaneous pIDs should have increased clinical monitoring due to their increased risk of cirAE development, severity, and earlier onset.

Identifiers

PMID37693493
PMCPMC10491283
OpenAlexW4386293458

What OpenQuestion holds

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Registered trials

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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.