Evidence map›Paper›PMID 35062901›Full record

ArticleBMC cancer2022

Dietary patterns and severity of symptom with the risk of esophageal squamous cell carcinoma and its histological precursor lesions in China: a multicenter cross-sectional latent class analysis.

Zhaoping Zang, Yong Liu, Jialin Wang, Yuqin Liu, Shaokai Zhang, Yongzhen Zhang, Liwei Zhang, Deli Zhao, Fugang Liu, Lina Chao and 17 more

Open access · goldAbstract readMulticenter Study
In one paragraph

Article in BMC cancer, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.

0numbers the graph read from it
0cells of the map it votes in
12citing papers in PubMed
2.6field-weighted citation impact, top 10% 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

12 citing papers in PubMed, 12 citations in OpenAlex.

  1. Article
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  3. Virulence · 2025
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  6. Role ofWorld journal of gastroenterology · 2024
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  8. Observational
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  11. Improving outcomes in patients with oesophageal cancer.Nature reviews. Clinical oncology · 2023
    Review
  12. 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

27 authors at 13 institutions in 1 country.

Zhaoping Zang *Department of Epidemiology and Health Statistics, School of Public Health, Beijing Municipal Key Laboratory of Clinical Epidemiology, Capital Medical University, Beijing, 100069, China.
Yong Liu *Department of Endoscopy, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100021, China.
Jialin WangShandong Cancer Hospital and Institute, Shandong First Medical University and Shandong Academy of Medical Sciences, Shandong, 250000, China.
Yuqin LiuGansu Provincial Cancer Hospital, Gansu, 730000, China.
Shaokai ZhangDepartment of Cancer Epidemiology and Prevention, The Affiliated Cancer Hospital of Zhengzhou University, Henan Cancer Hospital, Henan, 450008, China.
Yongzhen ZhangDepartment of Epidemiology, Shanxi Cancer Hospital, Shanxi, 030013, China.
Liwei ZhangThe Fourth Hospital of Hebei Medical University, Hebei, 050000, China.
Deli ZhaoFeicheng People's Hospital, Shandong, 271600, China.
Fugang LiuDongping People's Hospital, Shandong, 271500, China.
Lina ChaoDepartment of Epidemiology, Hebi People's Hospital, Henan, 458030, China.
Xinzheng WangYangcheng Cancer Hospital, Shanxi, 048100, China.
Chunli ZhangThe First People's Hospital of Ningyang County, Shandong, 271400, China.
Guohui SongCixian Institute for Cancer Prevention and Control, Hebei, 056500, China.
Zhiyi ZhangGansu Wuwei Cancer Hospital, Gansu, 733000, China.
Youpeng LiMinqin County People's Hospital, Gansu, 733000, China.
Zheng YanLinze County People's Hospital, Gansu, 734200, China.
Yongxiu WenShandan County People's Hospital, Gansu, 734000, China.
Yinyin GeGaotai County People's Hospital, Gansu, 734300, China.
Chen NiuDepartment of Epidemiology and Health Statistics, School of Public Health, Beijing Municipal Key Laboratory of Clinical Epidemiology, Capital Medical University, Beijing, 100069, China.
Wei FengDepartment of Epidemiology and Health Statistics, School of Public Health, Beijing Municipal Key Laboratory of Clinical Epidemiology, Capital Medical University, Beijing, 100069, China.
Rena NakyeyuneDepartment of Epidemiology and Health Statistics, School of Public Health, Beijing Municipal Key Laboratory of Clinical Epidemiology, Capital Medical University, Beijing, 100069, China.
Yi ShenDepartment of Epidemiology and Health Statistics, School of Public Health, Beijing Municipal Key Laboratory of Clinical Epidemiology, Capital Medical University, Beijing, 100069, China.
Yi ShaoDepartment of Epidemiology and Health Statistics, School of Public Health, Beijing Municipal Key Laboratory of Clinical Epidemiology, Capital Medical University, Beijing, 100069, China.
Xiuhua GuoDepartment of Epidemiology and Health Statistics, School of Public Health, Beijing Municipal Key Laboratory of Clinical Epidemiology, Capital Medical University, Beijing, 100069, China.
Aiming YangDepartment of Gastroenterology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences, Beijing, 100730, China. yangaiming@medmail.com.cn.
Fen LiuDepartment of Epidemiology and Health Statistics, School of Public Health, Beijing Municipal Key Laboratory of Clinical Epidemiology, Capital Medical University, Beijing, 100069, China. liufen05@ccmu.edu.cn.
Guiqi WangDepartment of Endoscopy, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100021, China. wangguiq@126.com.
Capital Medical University · CNChinese Academy of Medical Sciences & Peking Union Medical College · CNShanxi Provincial Cancer Hospital · CNFourth Hospital of Hebei Medical University · CNGaozhou People's Hospital · CNJingning County People's Hospital · CNPeking Union Medical College Hospital · CNShandong Tumor Hospital · CNThe First People's Hospital of Guiyang · CNThe People's Hospital of LinXia · CNXian Center for Disease Control and Prevention · CNZhengzhou University · CNZoucheng People's Hospital · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundDietary patterns and symptoms research among Chinese with esophageal squamous cell carcinoma (ESCC) and its precursor lesions is limited, especially as it relates to multiple food consumption and multiple co-occurring symptoms. The aim of our study was to identify the dietary patterns and severity of symptom classes with the risk of esophageal squamous cell carcinoma and its histological precursor lesions, and develop a risk prediction model for different stages of esophageal disease.

methodsWe analyzed data from a multicenter cross-sectional study carried out in ESCC high incidence areas between 2017 and 2018, which included 34,707 individuals aged 40-69 years. Dietary patterns and severity of symptom classes were derived by applying a latent class analysis (LCA). A multiple logistic regression model was used to derive the odds ratio (ORs) and corresponding 95% confidence intervals (CIs) for ESCC and the different stages of esophageal disease according to the dietary patterns and severity of symptom classes identified. We built the risk prediction model by using a nomogram.

resultsWe identified five dietary patterns and three severity of symptom classes. The dietary patterns were classified as follows: "Healthy", "Western", "Lower consumers-combination", "Medium consumers-combination" and "Higher consumers-combination" patterns based on the intake of foods such as red meat, vegetables and fruits. The severity of symptoms was categorized into "Asymptomatic", "Mild symptoms" and "Overt symptoms" classes based on health-related symptoms reported by the participants. Compared to the "Healthy" pattern, the other four patterns were all associated with an increased risk of esophageal disease. Similarly, the other two symptom classes present different degrees of increased risk of esophageal disease compared to the "Asymptomatic". The nomograms reflect the good predictive ability of the model.

conclusionAmong individuals aged 40-69 years in high incidence regions of upper gastrointestinal cancer, the results supplied that subjects with diets rich in livestock and poultry meat and low in fruits and vegetables and subjects with typical symptoms were at increased ESCC risk. The findings highlight the importance of considering food and symptom combinations in cancer risk evaluation.

Indexed as

Severity of Illness IndexAdultAgedChinaCluster AnalysisCross-Sectional StudiesDietDiet SurveysEsophageal NeoplasmsEsophageal Squamous Cell CarcinomaFemaleHumansIncidenceLatent Class AnalysisLogistic ModelsMaleDietary patternsEsophageal squamous cell carcinomaLatent class analysisPrecancerous lesionsSymptom

Identifiers

PMID35062901
PMCPMC8783423
OpenAlexW4220698604

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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.