Evidence map›Paper›PMID 35927466›Full record

ArticleEuropean radiology2023

Quantitative CT evaluation after two cycles of induction chemotherapy to predict prognosis of patients with locally advanced oesophageal squamous cell carcinoma before undergoing definitive chemoradiotherapy/radiotherapy.

Shuo Yan, Yan-Jie Shi, Chang Liu, Xiao-Ting Li, Bo Zhao, Yi-Yuan Wei, Lin Shen, Zhi-Hao Lu, Ying-Shi Sun

Open access · hybridAbstract read
In one paragraph

Article in European radiology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
0.7field-weighted citation impact, top 31% 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

2 citing papers in PubMed, 3 citations in OpenAlex.

  1. Article
  2. Article
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 1 institution in 2 countries.

Shuo YanKey Laboratory of Carcinogenesis and Translational Research (Ministry of Education/ Beijing), Department of Radiology, Peking University Cancer Hospital & Institute, No. 52, Fucheng Road, Hai Dian District, Beijing, 100142, China.
Yan-Jie ShiKey Laboratory of Carcinogenesis and Translational Research (Ministry of Education/ Beijing), Department of Radiology, Peking University Cancer Hospital & Institute, No. 52, Fucheng Road, Hai Dian District, Beijing, 100142, China.
Chang LiuKey Laboratory of Carcinogenesis and Translational Research (Ministry of Education/ Beijing), Early Drug Development Center, Peking University Cancer Hospital & Institute, No. 52, Fucheng Road, Haidian District, Beijing, 100142, China.
Xiao-Ting LiKey Laboratory of Carcinogenesis and Translational Research (Ministry of Education/ Beijing), Department of Radiology, Peking University Cancer Hospital & Institute, No. 52, Fucheng Road, Hai Dian District, Beijing, 100142, China.
Bo ZhaoKey Laboratory of Carcinogenesis and Translational Research (Ministry of Education/ Beijing), Department of Radiology, Peking University Cancer Hospital & Institute, No. 52, Fucheng Road, Hai Dian District, Beijing, 100142, China.
Yi-Yuan WeiKey Laboratory of Carcinogenesis and Translational Research (Ministry of Education/ Beijing), Department of Radiology, Peking University Cancer Hospital & Institute, No. 52, Fucheng Road, Hai Dian District, Beijing, 100142, China.
Lin ShenKey Laboratory of Carcinogenesis and Translational Research (Ministry of Education/ Beijing), Early Drug Development Center, Peking University Cancer Hospital & Institute, No. 52, Fucheng Road, Haidian District, Beijing, 100142, China.
Zhi-Hao LuDepartment of Gastrointestinal Oncology, Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education/Beijing), Peking University Cancer Hospital & Institute, No. 52 Fu-Cheng Road, Hai-Dian District, Beijing, 100142, China. pppeirain@126.com.
Ying-Shi SunKey Laboratory of Carcinogenesis and Translational Research (Ministry of Education/ Beijing), Department of Radiology, Peking University Cancer Hospital & Institute, No. 52, Fucheng Road, Hai Dian District, Beijing, 100142, China. sys27@163.com.ORCID http://orcid.org/0000-0001-9424-1910
Peking University · CN

Funding

Beijing Hospitals Authority Ascent Plan Grant No. 20191103Beijing Municipal Administration of Hospitals Clinical Medicine Development of Special Funding Support Grant No. ZYLX201803Beijing Municipal Administration of Hospitals Incubating Program Grant No. PX2020046Beijing Natural Science Foundation Grant No. Z200015National Natural Science Foundation of China Grant Nos. 91959116 and 81971584
6 · The paper itself

Abstract

objectiveTo investigate the performance of quantitative CT analysis in predicting the prognosis of patients with locally advanced oesophageal squamous cell carcinoma (ESCC) after two cycles of induction chemotherapy before definitive chemoradiotherapy/radiotherapy.

methodsA total of 110 patients with locally advanced ESCC were retrospectively analysed. Baseline chest CT and CT after two cycles of induction chemotherapy were analysed. A multivariate Cox proportional-hazard regression model was used to identify independent prognostic markers for survival analysis. Then, a CT scoring system was established. Time-dependent receiver operating characteristic (ROC) curve analysis and the Kaplan-Meier method were employed for analysing the prognostic value of the CT scoring system.

resultsBody mass index, treatment strategy, change ratios of thickness (ΔTH

conclusionQuantitative CT analysis after two cycles of induction chemotherapy could predict the outcome of locally advanced ESCC patients treated with definitive chemoradiotherapy/radiotherapy. The CT scoring system could contribute to the development of an appropriate strategy for patients with locally advanced ESCC. KEY POINTS: • Quantitative CT evaluation after two cycles of induction chemotherapy can predict the long-term outcome of locally advanced oesophageal cancer treated with definitive chemoradiotherapy/radiotherapy. • A CT scoring system provides valuable imaging support for indicating the prognosis at the early stage of therapy. • Quantitative CT evaluation can assist clinicians in personalising treatment plans.

Indexed as

Esophageal NeoplasmsEsophageal Squamous Cell CarcinomaChemoradiotherapyHumansInduction ChemotherapyPrognosisRetrospective StudiesTomography, X-Ray ComputedOesophageal squamous cell carcinomaPrognosisResponse Evaluation Criteria in Solid TumoursTomography, X-ray computed

Identifiers

PMID35927466
PMCPMC9755097
OpenAlexW4289783316

What OpenQuestion holds

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LicenceCC BY
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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.