Evidence map›Paper›PMID 39113705›Full record

ReviewInternational journal of biological sciences2024

Using Combination therapy to overcome diverse challenges of Immune Checkpoint Inhibitors treatment.

Racheli Birnboim-Perach, Itai Benhar

Abstract readReview
In one paragraph

Review in International journal of biological sciences, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 30 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
30citing papers in PubMed, 1 pooled it
–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

30 citing papers in PubMed, 1 synthesis or guideline pooled it.

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  15. Zebrafish as a Model for Translational Immuno-Oncology.Journal of personalized medicine · 2025
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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

2 authors.

Racheli Birnboim-PerachDepartment of Molecular Microbiology and Biotechnology, The Shmunis School of Biomedicine and Cancer Research, The George S. Wise Faculty of Life Sciences, Tel-Aviv University, Tel-Aviv 69978, Israel.
Itai BenharDepartment of Molecular Microbiology and Biotechnology, The Shmunis School of Biomedicine and Cancer Research, The George S. Wise Faculty of Life Sciences, Tel-Aviv University, Tel-Aviv 69978, Israel.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Immune checkpoint inhibitors (ICIs) have heralded a new era in immunotherapy, representing a pivotal breakthrough in cancer treatment. Their impact is profound, with ICIs standing as some of the most prescribed anticancer therapies today. Notably, their ability to induce long-term remission even after treatment cessation provides genuine hope for achieving durable cures. However, despite these strides, challenges persist in the landscape of oncology, including resistance phenomena, immune-related adverse events, and suboptimal response rates. In response to these challenges, combination therapy emerges as a promising approach, poised to enhance treatment outcomes and address limitations inherent to single-agent ICI therapy. By synergistically targeting multiple pathways, combination therapy holds the potential to augment therapeutic efficacy while mitigating toxicity and impeding the emergence of resistance mechanisms. Understanding the intricacies underlying resistance development and adverse events is paramount in devising novel and refined combination strategies. A timeline showing FDA approvals of ICIs combination is shown in

Indexed as

Immune Checkpoint InhibitorsImmunotherapyNeoplasmsAntineoplastic Combined Chemotherapy ProtocolsCombined Modality TherapyHumansImmune Checkpoint Inhibitors

Identifiers

PMID39113705
PMCPMC11302893

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.