Evidence map›Paper›PMID 37664636›Full record

ArticleiScience2023

Computerized tertiary lymphoid structures density on H&E-images is a prognostic biomarker in resectable lung adenocarcinoma.

Yumeng Wang, Huan Lin, Ningning Yao, Xiaobo Chen, Bingjiang Qiu, Yanfen Cui, Yu Liu, Bingbing Li, Chu Han, Zhenhui Li and 7 more

Open access · goldAbstract read
In one paragraph

Article in iScience, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 31 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
31citing papers in PubMed, 1 pooled it
8.0field-weighted citation impact, top 2% of its field
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

31 citing papers in PubMed, 1 synthesis or guideline pooled it, 31 citations in OpenAlex.

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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

17 authors at 6 institutions in 1 country.

Yumeng WangSchool of Computer Science and Information Security, Guilin University of Electronic Technology, Guilin 541004, China.
Huan LinDepartment of Radiology, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangzhou 510080, China.
Ningning YaoDepartment of Radiobiology, Shanxi Province Cancer Hospital/Shanxi Hospital Affiliated to Cancer Hospital, Chinese Academy of Medical Sciences/Cancer Hospital Affiliated to Shanxi Medical University; Taiyuan 030013, China.
Xiaobo ChenFirst Department of Thoracic Surgery, The Third Affiliated Hospital of Kunming Medical University, Yunnan Cancer Hospital, Yunnan Cancer Center, Kunming 650118, China.
Bingjiang QiuDepartment of Radiology, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangzhou 510080, China.
Yanfen CuiDepartment of Radiology, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangzhou 510080, China.
Yu LiuGuangdong Provincial Key Laboratory of Artificial Intelligence in Medical Image Analysis and Application, Guangzhou 510080, China.
Bingbing LiDepartment of Pathology, Ganzhou Hospital of Guangdong Provincial People's Hospital, Ganzhou Municipal Hospital, 49 Dagong Road, Ganzhou 341000, China.
Chu HanDepartment of Radiology, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangzhou 510080, China.
Zhenhui LiDepartment of Radiology, The Third Affiliated Hospital of Kunming Medical University, Yunnan Cancer Hospital, Yunnan Cancer Center, Kunming 650118, China.
Wei ZhaoDepartment of Radiology, The Second Xiangya Hospital, Central South University, Changsha 410011, China.
Zimin WangSchool of Computer Science and Information Security, Guilin University of Electronic Technology, Guilin 541004, China.
Xipeng PanSchool of Computer Science and Information Security, Guilin University of Electronic Technology, Guilin 541004, China.
Cheng LuSchool of Computer Science and Information Security, Guilin University of Electronic Technology, Guilin 541004, China.
Jun LiuDepartment of Radiology, The Second Xiangya Hospital, Central South University, Changsha 410011, China.
Zhenbing LiuSchool of Computer Science and Information Security, Guilin University of Electronic Technology, Guilin 541004, China.
Zaiyi LiuSchool of Computer Science and Information Security, Guilin University of Electronic Technology, Guilin 541004, China.
Key Laboratory of Guangdong Province · CNCentral South University · CNGuilin University of Electronic Technology · CNKunming Medical University · CNShanxi Medical University · CNGanzhou People's Hospital · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The increased amount of tertiary lymphoid structures (TLSs) is associated with a favorable prognosis in patients with lung adenocarcinoma (LUAD). However, evaluating TLSs manually is an experience-dependent and time-consuming process, which limits its clinical application. In this multi-center study, we developed an automated computational workflow for quantifying the TLS density in the tumor region of routine hematoxylin and eosin (H&E)-stained whole-slide images (WSIs). The association between the computerized TLS density and disease-free survival (DFS) was further explored in 802 patients with resectable LUAD of three cohorts. Additionally, a Cox proportional hazard regression model, incorporating clinicopathological variables and the TLS density, was established to assess its prognostic ability. The computerized TLS density was an independent prognostic biomarker in patients with resectable LUAD. The integration of the TLS density with clinicopathological variables could support individualized clinical decision-making by improving prognostic stratification.

Indexed as

cancercomputational bioinformaticsHealth informatics

Identifiers

PMID37664636
PMCPMC10474456
OpenAlexW4385879577

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.