Evidence map›Paper›PMID 31557690›Full record

ReviewCurrent opinion in immunology2019

Autoimmune complications of cancer immunotherapy.

Kavita M Dhodapkar

Abstract readReview
In one paragraph

Review in Current opinion in immunology, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing 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

7 citing papers in PubMed.

  1. Article
  2. Review
  3. Article
  4. Autoimmune Responses in Oncology: Causes and Significance.International journal of molecular sciences · 2021
    Review
  5. Industry and MASCC-an opportunity not to be missed.Supportive care in cancer : official journal of the Multinational Association of Supportive Care in Cancer · 2021
    Article
  6. Review
  7. Article
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

1 author.

Kavita M DhodapkarEmory University and Children's Healthcare of Atlanta, Atlanta, GA, United States. Electronic address: kavita.dhodapkar@emory.edu.

Funding

HARNESSING HOST RESPONSE TO PREVENT MYELOMAR35CA197603 · NCI · YALE UNIVERSITY · PI DHODAPKAR, MADHAV V · 2016 to 2022
$5.8M
B cells in autoimmunity following checkpoint blockade therapyR01CA238471 · NCI · EMORY UNIVERSITY · PI DHODAPKAR, KAVITA MADHAV, SANZ, IGNACIO E. · 2019 to 2023
$2.3M
B cell depletion to prevent autoimmunityR01AR077926 · NIAMS · EMORY UNIVERSITY · PI DHODAPKAR, KAVITA MADHAV, SANZ, IGNACIO E. · 2020 to 2023
$1.6M
NCI NIH HHS R01 CA238471NCI NIH HHS R35 CA197603NIAMS NIH HHS R01 AR077926
6 · The paper itself

Abstract

Immunotherapy of cancer with blockade of inhibitory immune checkpoints and adoptive cell therapies have led to impressive clinical responses in several cancers. However, with increasing utilization of these therapies, immune-related adverse events have emerged as a major obstacle. Herein I discuss recent insights into the immunobiology of these toxicities. Deeper understanding of the underlying pathogenic mechanisms, cellular and molecular pathways involved, similarities and differences with spontaneous autoimmunity, and identification of clinically relevant predictive biomarkers is needed to develop optimal approaches to prevent and treat these toxicities, without compromising the therapeutic benefit from these immune therapies. These events may also provide a unique window into mechanisms underlying spontaneous autoimmunity.

Indexed as

AutoimmunityAnimalsAntineoplastic Agents, ImmunologicalAutoimmune DiseasesBiomarkers, TumorDisease Models, AnimalDisease SusceptibilityHumansImmunotherapy, AdoptiveMolecular Targeted TherapyNeoplasmsRisk FactorsAntineoplastic Agents, ImmunologicalBiomarkers, Tumor

Identifiers

PMID31557690
PMCPMC7968474

What OpenQuestion holds

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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.