Evidence map›Paper›PMID 38136336›Full record

ArticleCancers2023

AI-Based Risk Score from Tumour-Infiltrating Lymphocyte Predicts Locoregional-Free Survival in Nasopharyngeal Carcinoma.

Made Satria Wibawa, Jia-Yu Zhou, Ruoyu Wang, Ying-Ying Huang, Zejiang Zhan, Xi Chen, Xing Lv, Lawrence S Young, Nasir Rajpoot

Registry-linked trialOpen access · goldAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Cancers, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT06829147 (Development and Validation of a Deep Learning Model for Diagnosing Lymph Node Metastasis in Nasopharyngeal Carcinoma Using Histologic Whole Slide Images and Time-dependent Magnetic Resonance Images), which is not on this map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
1.8field-weighted citation impact, top 14% 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.

NCT06829147 recruitingnot on this mapstarted 2024, after this paper: background citation

Development and Validation of a Deep Learning Model for Diagnosing Lymph Node Metastasis in Nasopharyngeal Carcinoma Using Histologic Whole Slide Images and Time-dependent Magnetic Resonance Images

TypeobservationalSponsorSun Yat-sen UniversityRan2024 to 2026Enrolled500ConditionsNasopharyngeal Cancinoma (NPC), Lymph Node Metastasis
3 · Its place in the literature

Who cites it

6 citing papers in PubMed, 8 citations in OpenAlex.

  1. Article
  2. Review
  3. Review
  4. Review
  5. Article
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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

9 authors at 3 institutions in 2 countries.

Made Satria WibawaTissue Image Analytics Centre, Department of Computer Science, University of Warwick, Coventry CV4 7AL, UK.ORCID 0000-0001-5098-1714
Jia-Yu ZhouState Key Laboratory of Oncology in South China, Guangdong Key Laboratory of Nasopharyngeal Carcinoma Diagnosis and Therapy, Guangdong Provincial Clinical Research Center for Cancer, Sun Yat-Sen University Cancer Center, Guangzhou 510060, China.
Ruoyu WangTissue Image Analytics Centre, Department of Computer Science, University of Warwick, Coventry CV4 7AL, UK.
Ying-Ying HuangState Key Laboratory of Oncology in South China, Guangdong Key Laboratory of Nasopharyngeal Carcinoma Diagnosis and Therapy, Guangdong Provincial Clinical Research Center for Cancer, Sun Yat-Sen University Cancer Center, Guangzhou 510060, China.
Zejiang ZhanState Key Laboratory of Oncology in South China, Guangdong Key Laboratory of Nasopharyngeal Carcinoma Diagnosis and Therapy, Guangdong Provincial Clinical Research Center for Cancer, Sun Yat-Sen University Cancer Center, Guangzhou 510060, China.
Xi ChenState Key Laboratory of Oncology in South China, Guangdong Key Laboratory of Nasopharyngeal Carcinoma Diagnosis and Therapy, Guangdong Provincial Clinical Research Center for Cancer, Sun Yat-Sen University Cancer Center, Guangzhou 510060, China.ORCID 0000-0002-8259-9509
Xing LvState Key Laboratory of Oncology in South China, Guangdong Key Laboratory of Nasopharyngeal Carcinoma Diagnosis and Therapy, Guangdong Provincial Clinical Research Center for Cancer, Sun Yat-Sen University Cancer Center, Guangzhou 510060, China.
Lawrence S YoungWarwick Medical School, University of Warwick, Coventry CV4 7AL, UK.ORCID 0000-0003-3919-4298
Nasir RajpootTissue Image Analytics Centre, Department of Computer Science, University of Warwick, Coventry CV4 7AL, UK.ORCID 0000-0002-4706-1308
Sun Yat-sen University · CNUniversity of Warwick · GBTuring Institute · GB

Funding

Lembaga Pengelola Dana Pendidikan S-575/LPDP.4/2020
6 · The paper itself

Abstract

backgroundLocoregional recurrence of nasopharyngeal carcinoma (NPC) occurs in 10% to 50% of cases following primary treatment. However, the current main prognostic markers for NPC, both stage and plasma Epstein-Barr virus DNA, are not sensitive to locoregional recurrence.

methodsWe gathered 385 whole-slide images (WSIs) from haematoxylin and eosin (H&E)-stained NPC sections (

resultsBased on Kaplan-Meier analysis, the proposed methods were able to stratify low- and high-risk NPC cases in a validation set of locoregional recurrence with a statically significant result (

conclusionThe proposed novel digital markers could potentially be utilised to assist treatment decisions in cases of NPC.

Indexed as

artificial intelligencecomputational pathologylocoregional recurrencenasopharyngeal carcinomatumour-infiltrating lymphocytes

Identifiers

PMID38136336
PMCPMC10742296
OpenAlexW4389545702

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

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.