Evidence map›Paper›PMID 36189291›Full record

ArticleFrontiers in immunology2022

TMBcat: A multi-endpoint

Yixuan Wang, Xin Lai, Jiayin Wang, Ying Xu, Xuanping Zhang, Xiaoyan Zhu, Yuqian Liu, Yang Shao, Li Zhang, Wenfeng Fang

Abstract read
In one paragraph

Article in Frontiers in immunology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
13citing 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

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

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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

10 authors.

Yixuan WangSchool of Computer Science and Technology, Xi'an Jiaotong University, Xi'an, China.
Xin LaiSchool of Computer Science and Technology, Xi'an Jiaotong University, Xi'an, China.
Jiayin WangSchool of Computer Science and Technology, Xi'an Jiaotong University, Xi'an, China.
Ying XuSchool of Computer Science and Technology, Xi'an Jiaotong University, Xi'an, China.
Xuanping ZhangSchool of Computer Science and Technology, Xi'an Jiaotong University, Xi'an, China.
Xiaoyan ZhuSchool of Computer Science and Technology, Xi'an Jiaotong University, Xi'an, China.
Yuqian LiuSchool of Computer Science and Technology, Xi'an Jiaotong University, Xi'an, China.
Yang ShaoMedical Department, Nanjing Geneseeq Technology Inc., Nanjing, China.
Li ZhangState Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Sun Yat-sen University Cancer Center, Guangzhou, China.
Wenfeng FangState Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Sun Yat-sen University Cancer Center, Guangzhou, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Tumor mutation burden (TMB) is a widely recognized stratification biomarker for predicting the efficacy of immunotherapy; however, the number and universal definition of the categorizing thresholds remain debatable due to the multifaceted nature of efficacy and the imprecision of TMB measurements. We proposed a minimal joint

Indexed as

Carcinoma, Non-Small-Cell LungLung NeoplasmsBiomarkers, TumorHumansMutationRetrospective StudiesBiomarkers, Tumorbetween-group differencecategorization thresholdsimmunotherapyjoint efficacyminimal p-valuetumor mutation burden

Identifiers

PMID36189291
PMCPMC9523486

What OpenQuestion holds

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LicenceCC BY
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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.