Evidence map›Paper›PMID 30643941›Full record

ArticleEuropean radiology2019

Development and validation of a prognostic index for efficacy evaluation and prognosis of first-line chemotherapy in stage III-IV lung squamous cell carcinoma.

Jiangdian Song, Jie Tian, Lina Zhang, Xiujuan Qu, Wei Qian, Bin Zheng, Lina Zhang, Jia Zhao, Meng Niu, Mu Zhou and 3 more

Registry-linked trialAbstract read
In one paragraph

Article in European radiology, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT04577105 (Risk Factors, Prognosis and Findings by Computed Tomography in Patients Infected by COVID-19 and Its Association With Severity.), which is not on this map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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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.

NCT04577105 completednot on this mapstarted 2020, after this paper: background citation

Risk Factors, Prognosis and Findings by Computed Tomography in Patients Infected by COVID-19 and Its Association With Severity.

TypeobservationalSponsorInstituto Nacional de Cardiologia Ignacio ChavezRan2020 to 2020Enrolled233ConditionsCovid19, ARDS, Pneumonia, Viral, Computed TomographyArmsSimple chest tomography
3 · Its place in the literature

Who cites it

3 citing papers in PubMed.

  1. Article
  2. Article
  3. Review
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

13 authors.

Jiangdian SongSchool of Medical Informatics, China Medical University, Shenyang, Liaoning, China.
Jie TianCAS Key Laboratory of Molecular Imaging, Institute of Automation, Chinese Academy of Sciences, Beijing, China.
Lina ZhangDepartment of Medical Oncology, The First Hospital of China Medical University, Shenyang, 110001, Liaoning, China.
Xiujuan QuDepartment of Medical Oncology, The First Hospital of China Medical University, Shenyang, 110001, Liaoning, China.
Wei QianCollege of Engineering, University of Texas, El Paso, TX, USA.
Bin ZhengSino-Dutch Biomedical Engineering School, Northeastern University, Shenyang, Liaoning, China.
Lina ZhangDepartment of Radiology, The First Hospital of China Medical University, Shenyang, Liaoning, China.
Jia ZhaoDepartment of Medical Oncology, The First Hospital of China Medical University, Shenyang, 110001, Liaoning, China.
Meng NiuDepartment interventional therapy, The First Hospital of China Medical University, Shenyang, Liaoning, China.
Mu ZhouArtificial Intelligence in Medicine and Imaging (AIMI) Center, Department of Radiology, Stanford University, San Francisco, CA, USA.
Lei CuiSchool of Medical Informatics, China Medical University, Shenyang, Liaoning, China.
Yunpeng LiuDepartment of Medical Oncology, The First Hospital of China Medical University, Shenyang, 110001, Liaoning, China. ypliu@cmu.edu.cn.
Mingfang ZhaoDepartment of Medical Oncology, The First Hospital of China Medical University, Shenyang, 110001, Liaoning, China. mfzhao@cmu.edu.cn.

Funding

China Postdoctoral Science Foundation 2018M630310National Key R&D Program of China 2016YFC1303800
6 · The paper itself

Abstract

objectivesTo establish a pre-therapy prognostic index model (PIM) of the first-line chemotherapy aiming to achieve accurate prediction of time to progression (TTP) and overall survival among the patients diagnosed with locally advanced (stage III) or distant metastasis (stage IV) lung squamous cell carcinoma (LSCC).

methodsNinety-six LSCC patients treated with first-line chemotherapy were retrospectively enrolled to build the model. Fourteen epidermal growth factor receptor (EGFR)-mutant LSCC patients treated with first-line EGFR-tyrosine kinase inhibitor (TKI) therapy were enrolled for validation dataset. From CT images, 56,000 phenotype features were initially computed. PIM was constructed by integrating a CT phenotype signature selected by the least absolute shrinkage and selection operator and the significant blood-based biomarkers selected by multivariate Cox regression. PIM was then compared with other four prognostic models constructed by the CT phenotype signature, clinical factors, post-therapy tumor response, and Glasgow Prognostic Score.

resultsThe signature includes eight optimal features extracted from co-occurrence, run length, and Gabor features. By using PIM, chemotherapy efficacy of patients categorized in the low-risk, intermediate-risk, and high-risk progression subgroups (median TTP = 7.2 months, 3.4 months, and 1.8 months, respectively) was significantly different (p < 0.0001, log-rank test). Chemotherapy efficacy of the low-risk progression subgroup was comparable with EGFR-TKI therapy (p = 0.835, log-rank test). Prognostic prediction of chemotherapy efficacy by PIM was significantly higher than other models (p < 0.05, z test).

conclusionThe study demonstrated that the PIM yielded significantly higher performance to identify individual stage III-IV LSCC patients who can potentially benefit most from first-line chemotherapy, and predict the risk of failure from chemotherapy for individual patients. KEY POINTS: • TTP and OS of first-line chemotherapy in individual stage III-IV LSCC patients could be predicted by pre-therapy blood-based biomarkers and image-based signatures. • Risk status of pre-therapy indicators affected the efficacy of first-line chemotherapy in stage III-IV LSCC patients. • Those stage III-IV LSCC patients who were able to achieve similar efficacy to EGFR-TKI therapy through chemotherapy were identified.

Indexed as

Neoplasm StagingAgedCarcinoma, Non-Small-Cell LungCarcinoma, Squamous CellErbB ReceptorsFemaleGefitinibHumansLung NeoplasmsMaleMultidetector Computed TomographyPrognosisProtein Kinase InhibitorsReproducibility of ResultsRetrospective StudiesEGFR protein, humanErbB ReceptorsGefitinibProtein Kinase InhibitorsBiomarkersCarcinomaPrognosisSquamous cellTumor

Identifiers

PMID30643941
PMCPMC6443600

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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.