Evidence map›Paper›PMID 40666359›Full record

ArticlemedRxiv : the preprint server for health sciences2025

Effect of systemic glucocorticoid immunosuppression timing, dose, and duration on overall survival among immune checkpoint inhibitor recipients: a retrospective multicohort study.

Guihong Wan, Nga Nguyen, Charles Lu, Sara Khattab, Boshen Yan, Munachimso Amadife, Bonnie W Leung, Wenxin Chen, Ahmad Rajeh, Kimberly Tang and 8 more

Abstract readPreprint
In one paragraph

Article in medRxiv : the preprint server for health sciences, 2025. 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.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

18 authors.

Guihong WanDepartment of Dermatology, Massachusetts General Hospital, Harvard Medical School, Boston, MA.ORCID 0000-0003-1100-4018
Nga NguyenDepartment of Dermatology, Massachusetts General Hospital, Harvard Medical School, Boston, MA.ORCID 0000-0003-2935-3603
Charles LuDepartment of Dermatology, Massachusetts General Hospital, Harvard Medical School, Boston, MA.ORCID 0000-0003-3450-1682
Sara KhattabDepartment of Dermatology, Massachusetts General Hospital, Harvard Medical School, Boston, MA.
Boshen YanDepartment of Dermatology, Massachusetts General Hospital, Harvard Medical School, Boston, MA.
Munachimso AmadifeDepartment of Dermatology, Massachusetts General Hospital, Harvard Medical School, Boston, MA.
Bonnie W LeungDepartment of Dermatology, Massachusetts General Hospital, Harvard Medical School, Boston, MA.
Wenxin ChenDepartment of Dermatology, Massachusetts General Hospital, Harvard Medical School, Boston, MA.
Ahmad RajehDepartment of Dermatology, Massachusetts General Hospital, Harvard Medical School, Boston, MA.
Kimberly TangDepartment of Dermatology, Massachusetts General Hospital, Harvard Medical School, Boston, MA.
Christopher ThangDepartment of Dermatology, Massachusetts General Hospital, Harvard Medical School, Boston, MA.
Genevieve BolandDepartment of Dermatology, Massachusetts General Hospital, Harvard Medical School, Boston, MA.
Kerry L ReynoldsDepartment of Medicine, Division of Oncology, Massachusetts General Hospital, Boston, MA.
Kun-Hsing YuDepartment of Biomedical Informatics, Harvard Medical School, Boston, MA.
Alexander GusevDepartment of Medicine, Dana-Farber Cancer Institute, Boston, MA.
Nicole R LeBoeufDepartment of Dermatology, Center for Cutaneous Oncology, Dana-Farber/Brigham Cancer Center, Harvard Medical School, Boston, MA.
Shawn G KwatraDepartment of Dermatology, University of Maryland School of Medicine, Baltimore, MD.
Yevgeniy R SemenovDepartment of Dermatology, Massachusetts General Hospital, Harvard Medical School, Boston, MA.ORCID 0000-0002-7387-3094

Funding

Robust, Generalizable, and Fair Machine Learning Models for BiomedicineR35GM142879 · NIGMS · HARVARD MEDICAL SCHOOL · PI YU, KUN-HSING · 2021 to 2025
$2.4M
Mitigating Hematologic Adverse Events in Patients with Myeloid Malignancies: A Novel Causal Artificial Intelligence ApproachR01HL174679 · NHLBI · HARVARD MEDICAL SCHOOL · PI Kun-Hsing Yu · 2024 to 2026
$2.3M
Predictive modeling of cutaneous immune checkpoint inhibitor toxicitiesK23AR080791 · NIAMS · MASSACHUSETTS GENERAL HOSPITAL · PI Yevgeniy R Semenov · 2023 to 2026
$704k
Explainable Artificial Intelligence for Melanoma Recurrence Prediction via Integrative Modeling of Multiplexed Imaging with Transcriptomics and HistopathologyK99CA286966 · NCI · MASSACHUSETTS GENERAL HOSPITAL · PI WAN, GUIHONG · 2024 to 2025
$352k
NCI NIH HHS K99 CA286966NCI NIH HHS L30 CA264747NHLBI NIH HHS R01 HL174679NIAMS NIH HHS K23 AR080791NIGMS NIH HHS R35 GM142879
6 · The paper itself

Abstract

Background: Systemic immunosuppression (sISP), particularly with glucocorticoids, is commonly used among patients receiving immune checkpoint inhibitor (ICI) therapy. Although recent studies have demonstrated that sISP is associated with poor outcomes in ICI recipients, there is limited information on how the timing, dose, and duration of sISP affect overall survival (OS). This multi-cohort retrospective study aims to address these gaps. Methods: This study included 13,086 ICI recipients from Massachusetts General Hospital, Brigham and Women's Hospital, and Dana-Farber Cancer Institute (MGBD) between May 31, 2015, and October 11, 2021. For independent validation, 26,172 ICI recipients were identified from the TriNetX database between April 30, 2010, and October 11, 2021, using 2:1 propensity score matching. Multivariable survival analyses were conducted with Accelerated Failure Time (AFT) models, reporting Time Ratios (TRs) and 95% Confidence Intervals (CIs), where TR<1 indicates shorter OS. Findings: In the MGBD cohort, sISP within one year of ICI initiation was associated with worse OS compared to patients without sISP via landmark analysis. This association was accentuated among patients receiving sISP closer to ICI initiation, with those receiving sISP within one month of ICI initiation having the worst outcomes (TR: 0.49; 95% CI: 0.44-0.54; p<0.0001). Increased dose and duration of sISP were associated with a greater survival time loss, such that doses beyond 60 mg/day had a 40% survival time loss and durations longer than 7 days were associated with a 35% survival time loss. These findings were independently validated in the TriNetX cohort. Interpretation: Three key factors are associated with significantly worse OS: sISP near ICI initiation, higher sISP dose, and longer sISP duration, regardless of indication. These findings provide clinicians with valuable information to guide sISP management among ICI recipients. Funding: NIH, USA.

Indexed as

immune checkpoint inhibitoroncologyoverall survivalsystemic glucocorticoid immunosuppression

Identifiers

PMID40666359
PMCPMC12262798

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.