Evidence map›Paper›PMID 37675597›Full record

ArticleThoracic cancer2023

Artificial intelligence-powered spatial analysis of tumor-infiltrating lymphocytes as a biomarker in locally advanced unresectable thymic epithelial neoplasm: A single-center, retrospective, longitudinal cohort study.

Dong Hyun Kim, Yoojoo Lim, Sukjun Kim, Chan-Young Ock, Jeonghwan Youk, Miso Kim, Tae Min Kim, Dong-Wan Kim, Hak Jae Kim, Jiwon Koh and 4 more

Open access · goldAbstract read
In one paragraph

Article in Thoracic cancer, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
1.6field-weighted citation impact, top 15% 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

6 citing papers in PubMed, 8 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

14 authors at 2 institutions in 1 country.

Dong Hyun KimDepartment of Internal Medicine, Seoul National University Hospital, Seoul, Republic of Korea.ORCID 0000-0002-0369-5763
Yoojoo LimLunit, Seoul, Republic of Korea.
Sukjun KimLunit, Seoul, Republic of Korea.
Chan-Young OckLunit, Seoul, Republic of Korea.
Jeonghwan YoukDepartment of Internal Medicine, Seoul National University Hospital, Seoul, Republic of Korea.
Miso KimDepartment of Internal Medicine, Seoul National University Hospital, Seoul, Republic of Korea.
Tae Min KimDepartment of Internal Medicine, Seoul National University Hospital, Seoul, Republic of Korea.
Dong-Wan KimDepartment of Internal Medicine, Seoul National University Hospital, Seoul, Republic of Korea.ORCID 0000-0001-5124-7132
Hak Jae KimDepartment of Radiation Oncology, Seoul National University Hospital, Seoul, Republic of Korea.ORCID 0000-0003-3602-2263
Jiwon KohDepartment of Pathology, Seoul National University Hospital, Seoul, Republic of Korea.
Kyeong Cheon JungDepartment of Pathology, Seoul National University Hospital, Seoul, Republic of Korea.
Kwon Joong NaDepartment of Thoracic and Cardiovascular Surgery, Seoul National University Hospital, Seoul, Republic of Korea.
Chang Hyun KangDepartment of Thoracic and Cardiovascular Surgery, Seoul National University Hospital, Seoul, Republic of Korea.
Bhumsuk KeamDepartment of Internal Medicine, Seoul National University Hospital, Seoul, Republic of Korea.ORCID 0000-0001-8196-4247
Seoul National University · KRSeoul National University Hospital · KR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThymic epithelial tumors (TET) are rare malignancies and lack well-defined biomarkers for neoadjuvant therapy. This study aimed to evaluate the clinical utility of artificial intelligence (AI)-powered tumor-infiltrating lymphocyte (TIL) analysis in TET.

methodsPatients initially diagnosed with unresectable thymoma or thymic carcinoma who underwent neoadjuvant therapy between January 2004 and December 2021 formed our study population. Hematoxylin and eosin-stained sections from the initial biopsy and surgery were analyzed using an AI-powered spatial TIL analyzer. Intratumoral TIL (iTIL) and stromal TIL (sTIL) were quantified and their immune phenotype (IP) was identified.

resultsThirty-five patients were included in this study. The proportion of patients with partial response to neoadjuvant therapy was higher in the group with nondesert IP in preneoadjuvant biopsy (63.6% vs. 17.6%, p = 0.038). A significant increase in both iTIL (median 22.18/mm

conclusionsNondesert IP in initial biopsy was associated with a better response to neoadjuvant therapy. Increased infiltration of both iTIL and sTIL in surgical specimens were associated with longer OS in patients with TET who underwent resection followed by neoadjuvant therapy.

Indexed as

Lymphocytes, Tumor-InfiltratingNeoplasms, Glandular and EpithelialArtificial IntelligenceBiomarkersHumansLongitudinal StudiesPrognosisRetrospective StudiesBiomarkersartificial intelligence-analysisthymic epithelial tumortumor-infiltrating lymphocyte

Identifiers

PMID37675597
PMCPMC10599973
OpenAlexW4386506817

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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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.