Student or educator? Sign up with your school email and get 6 months of Pro free.
CoChat
Sign Up
Cited by 802

The DOI matches its Crossref record; 21 of the 21 references it cites were found in a registry or an index.

Treatment of the Immune-Related Adverse Effects of Immune Checkpoint Inhibitors: A Review

Friedman, Claire F., Proverbs-Singh, Tracy A., Postow, Michael A.·2016·JAMA Oncology
DOI 10.1001/jamaoncol.2016.1051
Open this paper in CoChat — free account

Abstract

IMPORTANCE: The development of immune checkpoint inhibitors targeting cytotoxic T-lymphocyte antigen 4 (CTLA-4) and programmed cell death-1 (PD-1) has significantly improved the treatment of a variety of cancers and led to US Food and Drug Administration approvals for patients with a variety of malignant neoplasms. Immune checkpoint inhibitors enhance antitumor immunity by blocking negative regulators of T-cell function that exist both on immune cells and on tumor cells. Although these agents can lead to remarkable responses, their use can also be associated with unique immune-related adverse effects (irAEs). OBSERVATIONS: In general, use of PD-1 inhibitors such as nivolumab and pembrolizumab has a lower incidence of irAEs compared with those that block CTLA-4 such as ipilimumab. The combination of nivolumab and ipilimumab has a higher rate of irAEs than either approach as monotherapy. Consensus guidelines regarding the treatment of the most common irAEs including rash, colitis, hepatitis, endocrinopathies, and pneumonitis have been established. The mainstay of irAE treatment consists of immunosuppression with corticosteroids or other immunosuppressant agents such as infliximab; most irAEs will resolve with appropriate management. CONCLUSIONS AND RELEVANCE: The clinical use of immune checkpoint inhibitors is expanding rapidly. Oncology practitioners will therefore be required to recognize and manage irAEs in a growing patient population. Early recognition and treatment are essential to prevent patient morbidity and mortality, and adherence to established algorithms is recommended.

Overview

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.1001/jamaoncol.2016.1051

Cites

21 of 21 references verified0 citation errors · 0 not checkable

Statistics

Verification

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Citations

Cites

Show all 21 references

Cited by

Metadata

Authors
Friedman, C. F., Proverbs-Singh, T. A., & Postow, M. A.
Venue
JAMA Oncology
Publisher
American Medical Association (AMA)
Published
2016-10-01
Volume
2
Issue
10
Pages
1346
ISSN
2374-2437 (ISSN-L)
DOI
10.1001/jamaoncol.2016.1051
OpenAlex
W2473218705
Cited by
802
References
21
FWCI
41.88
Type
journal article
Language
en
Open access
closed

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review

Data sources

Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.