Evidence map›Paper›PMID 33163952›Full record

ArticleThe Lancet. Digital health2020

A prognostic model for overall survival of patients with early-stage non-small cell lung cancer: a multicentre, retrospective study.

Cheng Lu, Kaustav Bera, Xiangxue Wang, Prateek Prasanna, Jun Xu, Andrew Janowczyk, Niha Beig, Michael Yang, Pingfu Fu, James Lewis and 7 more

Open access · goldAbstract readMulticenter Study
In one paragraph

Article in The Lancet. Digital health, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 53 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
53citing papers in PubMed, 2 pooled it
4.8field-weighted citation impact, top 4% 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

53 citing papers in PubMed, 2 syntheses or guidelines pooled it, 79 citations in OpenAlex.

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  7. A Computational Pathology Model to Predict Docetaxel Benefit in Localized High-Risk and Metastatic Prostate Cancer.Clinical cancer research : an official journal of the American Association for Cancer Research · 2026
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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 12 institutions in 3 countries.

Cheng LuDepartment of Biomedical Engineering, Case Western Reserve University, Cleveland, OH, USA.
Kaustav BeraDepartment of Biomedical Engineering, Case Western Reserve University, Cleveland, OH, USA.
Xiangxue WangDepartment of Biomedical Engineering, Case Western Reserve University, Cleveland, OH, USA.
Prateek PrasannaDepartment of Biomedical Informatics, Stony Brook University, New York.
Jun XuJiangsu Key Laboratory of Big Data Analysis Technique, Nanjing University of Information Science and Technology, Nanjing, China.
Andrew JanowczykDepartment of Biomedical Engineering, Case Western Reserve University, Cleveland, OH, USA; Precision Oncology Center, Lausanne University Hospital, Lausanne, Switzerland.
Niha BeigDepartment of Biomedical Engineering, Case Western Reserve University, Cleveland, OH, USA.
Michael YangUniversity of Colorado Anschutz Medical Campus, Aurora, CO, USA.
Pingfu FuDepartment of Population and Quantitative Health Sciences, Case Western Reserve University, Cleveland, OH, USA.
James LewisDepartment of Pathology, Microbiology, and Immunology, Vanderbilt University Medical Center, Nashville, TN, USA.
Humberto ChoiDepartment of Pulmonary Medicine, Cleveland Clinic, Cleveland, OH, USA.
Ralph A SchmidDivision of General Thoracic Surgery, Inselspital University Hospital Bern, Bern, Switzerland.
Sabina BerezowskaThe Institute of Pathology, University of Bern, Bern, Switzerland.
Kurt SchalperDepartment of Pathology, Yale University School of Medicine, New Haven, CT, USA.
David RimmDepartment of Pathology, Yale University School of Medicine, New Haven, CT, USA.
Vamsidhar VelchetiPerlmutter Cancer Center, New York University, NY, USA.
Anant MadabhushiDepartment of Biomedical Engineering, Case Western Reserve University, Cleveland, OH, USA; Louis Stokes Cleveland Veterans Administration Medical Center, Cleveland, OH, USA.
Case Western Reserve University · USYale University · USCleveland Clinic · USLouis Stokes Cleveland VA Medical Center · USNanjing University of Information Science and Technology · CNNew York University · USStony Brook University · USUniversity Hospital of Bern · CHUniversity of Bern · CHUniversity of Colorado Anschutz Medical Campus · USUniversity of Lausanne · CHVanderbilt University Medical Center · US

Funding

Yale Clinical and Translational Science Award (U Component)UL1TR001863 · NCATS · YALE UNIVERSITY · PI John H. Krystal, LUCILA OHNO-MACHADO · 2016 to 2026
$102.9M
Yale SPORE in Lung Cancer (YSILC): The Biology and Personalized Treatment of Lung CancerP50CA196530 · NCI · YALE UNIVERSITY · PI Shuangge Ma · 2015 to 2026
$31.1M
Oral Cavity Quantitative Histomorphometric Risk Classifier (OHbIC) in Oral Cavity Squamous Cell Carcinoma (OC-SCC)R01CA249992 · NCI · EMORY UNIVERSITY · PI LEWIS, JAMES, MADABHUSHI, ANANT · 2021 to 2025
$3.2M
Computerized histologic image predictor of cancer outcomeR01CA202752 · NCI · CASE WESTERN RESERVE UNIVERSITY · PI FELDMAN, MICHAEL D, GANESAN, SHRIDAR · 2016 to 2020
$3.1M
Quantitative Histomorphometric Risk Classifier (QuHbIC) in HPV + Oropharyngeal CarcinomaR01CA220581 · NCI · CASE WESTERN RESERVE UNIVERSITY · PI KOYFMAN, SHLOMO, LEWIS, JAMES · 2018 to 2023
$3.1M
Computerized Histologic Risk Predictor (CHiRP) for Early Stage Lung CancersR01CA216579 · NCI · EMORY UNIVERSITY · PI FU, PINGFU, LLOYD, MARK · 2018 to 2023
$3.1M
MR Fingerprinting and Computerized Decision Support for Prostate CancerR01CA208236 · NCI · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI GULANI, VIKAS, PONSKY, LEE EVAN · 2017 to 2022
$3.0M
Pathology Image Informatics Platform for visualization, analysis and managementU24CA199374 · NCI · CASE WESTERN RESERVE UNIVERSITY · PI GURCAN, METIN NAFI, MADABHUSHI, ANANT · 2015 to 2019
$2.9M
RadxTools for assessing tumor treatment response on imagingU01CA248226 · NCI · CASE WESTERN RESERVE UNIVERSITY · PI TIWARI, PALLAVI, VISWANATH, SATISH EASWAR · 2020 to 2022
$1.4M
HistoTools: A suite of digital pathology tools for quality control, annotation and dataset identificationU01CA239055 · NCI · CASE WESTERN RESERVE UNIVERSITY · PI JANOWCZYK, ANDREW ROBERT, MADABHUSHI, ANANT · 2019 to 2022
$1.0M
A Study to Validate and Improve an Automated Image Analysis Algorithm to Detect Tuberculosis in Sputum Smear SlidesR43EB028736 · NIBIB · DIASCOPIC, LLC · PI MADABHUSHI, ANANT, SERIF, CARY · 2019 to 2019
$225k
BIOMEDICAL ENGINEERING RESEARCH FACILITIESC06RR012463 · NCRR · CASE WESTERN RESERVE UNIVERSITY · PI KUTINA, KENNETH L · 1997 to 1997
–
BLRD VA I01 BX004121BLRD VA IK6 BX006185NCATS NIH HHS UL1 TR001863NCI NIH HHS P50 CA196530NCI NIH HHS R01 CA202752NCI NIH HHS R01 CA208236NCI NIH HHS R01 CA216579NCI NIH HHS R01 CA220581NCI NIH HHS R01 CA249992NCI NIH HHS U01 CA239055NCI NIH HHS U01 CA248226NCI NIH HHS U24 CA199374NCRR NIH HHS C06 RR012463NIBIB NIH HHS R43 EB028736
6 · The paper itself

Abstract

Background: Intratumoural heterogeneity has been previously shown to be related to clonal evolution and genetic instability and associated with tumour progression. Phenotypically, it is reflected in the diversity of appearance and morphology within cell populations. Computer-extracted features relating to tumour cellular diversity on routine tissue images might correlate with outcome. This study investigated the prognostic ability of computer-extracted features of tumour cellular diversity (CellDiv) from haematoxylin and eosin (H&E)-stained histology images of non-small cell lung carcinomas (NSCLCs). Methods: In this multicentre, retrospective study, we included 1057 patients with early-stage NSCLC with corresponding diagnostic histology slides and overall survival information from four different centres. CellDiv features quantifying local cellular morphological diversity from H&E-stained histology images were extracted from the tumour epithelium region. A Cox proportional hazards model based on CellDiv was used to construct risk scores for lung adenocarcinoma (LUAD; 270 patients) and lung squamous cell carcinoma (LUSC; 216 patients) separately using data from two of the cohorts, and was validated in the two remaining independent cohorts (comprising 236 patients with LUAD and 335 patients with LUSC). We used multivariable Cox regression analysis to examine the predictive ability of CellDiv features for 5-year overall survival, controlling for the effects of clinical and pathological parameters. We did a gene set enrichment and Gene Ontology analysis on 405 patients to identify associations with differentially expressed biological pathways implicated in lung cancer pathogenesis. Findings: For prognosis of patients with early-stage LUSC, the CellDiv LUSC model included 11 discriminative CellDiv features, whereas for patients with early-stage LUAD, the model included 23 features. In the independent validation cohorts, patients predicted to be at a higher risk by the univariable CellDiv model had significantly worse 5-year overall survival (hazard ratio 1·48 [95% CI 1·06-2·08]; p=0·022 for The Cancer Genome Atlas [TCGA] LUSC group, 2·24 [1·04-4·80]; p=0·039 for the University of Bern LUSC group, and 1·62 [1·15-2·30]; p=0·0058 for the TCGA LUAD group). The identified CellDiv features were also found to be strongly associated with apoptotic signalling and cell differentiation pathways. Interpretation: CellDiv features were strongly prognostic of 5-year overall survival in patients with early-stage NSCLC and also associated with apoptotic signalling and cell differentiation pathways. The CellDiv-based risk stratification model could potentially help to determine which patients with early-stage NSCLC might receive added benefit from adjuvant therapy. Funding: National Institue of Health and US Department of Defense.

Indexed as

Survival AnalysisAgedCarcinoma, Non-Small-Cell LungDatabases, FactualFemaleHumansMaleMiddle AgedNeoplasm StagingPrognosisProportional Hazards ModelsRetrospective Studies

Identifiers

PMID33163952
PMCPMC7646741
OpenAlexW3092855556

What OpenQuestion holds

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LicenceCC BY-NC-ND
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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.