Evidence map›Paper›PMID 37268978›Full record

ReviewBiomarker research2023

Potential non-invasive biomarkers in tumor immune checkpoint inhibitor therapy: response and prognosis prediction.

Ruixia Song, Fengsen Liu, Yu Ping, Yi Zhang, Liping Wang

Abstract readReview
PubMed Full text at PMC Publisher
In one paragraph

Review in Biomarker research, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.

0numbers the graph read from it
0cells of the map it votes in
14citing 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

14 citing papers in PubMed.

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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

5 authors.

Ruixia Song *Biotherapy Center and Cancer Center, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan, China.
Fengsen Liu *Biotherapy Center and Cancer Center, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan, China.
Yu PingBiotherapy Center and Cancer Center, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan, China.
Yi ZhangBiotherapy Center and Cancer Center, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan, China. yizhang@zzu.edu.cn.
Liping WangDepartment of Oncology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan, China. wlp@zzu.edu.cn.

Funding

Henan Provincial Medical Science and Technology Research Plan Pro-vincial and Ministerial Joint Construction Project SBGJ202101010Henan Provincial Science and Technology Research Project 222102310052National Natural Science Foundation of China 81872410National Natural Science Foundation of China 82102869National Natural Science Foundation of China 91942314the Central Funds Guiding the Local Science and Technology Devel-opment of Henan Province Z20221343036
6 · The paper itself

Abstract

Immune checkpoint inhibitors (ICIs) have dramatically enhanced the treatment outcomes for diverse malignancies. Yet, only 15-60% of patients respond significantly. Therefore, accurate responder identification and timely ICI administration are critical issues in tumor ICI therapy. Recent rapid developments at the intersection of oncology, immunology, biology, and computer science have provided an abundance of predictive biomarkers for ICI efficacy. These biomarkers can be invasive or non-invasive, depending on the specific sample collection method. Compared with invasive markers, a host of non-invasive markers have been confirmed to have superior availability and accuracy in ICI efficacy prediction. Considering the outstanding advantages of dynamic monitoring of the immunotherapy response and the potential for widespread clinical application, we review the recent research in this field with the aim of contributing to the identification of patients who may derive the greatest benefit from ICI therapy.

Indexed as

BiomarkersCancerImmune checkpoint inhibitorsPrognosisTreatment outcome

Identifiers

PMID37268978
PMCPMC10236604

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.