Evidence map›Paper›PMID 24581169›Full record

ArticleZhongguo fei ai za zhi = Chinese journal of lung cancer2014

[Survey and analysis of awareness of lung cancer prevention and control in a LDCT lung cancer screening project in Tianjin Dagang Oilfield of China].

Guanhua Ren, Jianfei Ye, Yaguang Fan, Jing Wang, Zhijuan Sun, Hui Jia, Xinxin Du, Chaohua Hou, Ying Wang, Yongcheng Zhao and 1 more

Abstract read
In one paragraph

Article in Zhongguo fei ai za zhi = Chinese journal of lung cancer, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed, 1 pooled it
–field-weighted citation impact
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

6 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Article
  3. Article
  4. Article
  5. [Progress of Lung Cancer Screening with Low Dose Helical Computed Tomography].Zhongguo fei ai za zhi = Chinese journal of lung cancer · 2020
    Review
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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

11 authors.

Guanhua RenPeking Union Medical College & Institute of radiation medicine, Chinese Academy of Medical Science, Tianjin 300192, China.
Jianfei YeDepartment of Thoracic Surgery, Dagang Oil Field General Hospital, Tianjin 300280, China.
Yaguang FanTianjin Key Laboratory of Lung cancer Metastasis and Tumor Microenvironment, Tianjin Lung cancer Institute, Tianjin Medical University General Hospital, Tianjin 300052, China.
Jing WangTianjin Key Laboratory of Lung cancer Metastasis and Tumor Microenvironment, Tianjin Lung cancer Institute, Tianjin Medical University General Hospital, Tianjin 300052, China.
Zhijuan SunDepartment of Thoracic Surgery, Dagang Oil Field General Hospital, Tianjin 300280, China.
Hui JiaDepartment of Thoracic Surgery, Dagang Oil Field General Hospital, Tianjin 300280, China.
Xinxin DuTianjin Key Laboratory of Lung cancer Metastasis and Tumor Microenvironment, Tianjin Lung cancer Institute, Tianjin Medical University General Hospital, Tianjin 300052, China.
Chaohua HouDepartment of Thoracic Surgery, Dagang Oil Field General Hospital, Tianjin 300280, China.
Ying WangDepartment of Radiology, Tianjin Medical University General Hospital, Tianjin 300052, China.
Yongcheng ZhaoPeking Union Medical College & Institute of radiation medicine, Chinese Academy of Medical Science, Tianjin 300192, China.
Qinghua ZhouTianjin Key Laboratory of Lung cancer Metastasis and Tumor Microenvironment, Tianjin Lung cancer Institute, Tianjin Medical University General Hospital, Tianjin 300052, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

BACKGROUND AND

objectiveIt has been proven that increase of the awareness level of lung cancer prevention and control could enhance participation of lung cancer screening of lung cancer high risk group. The aim of this study is to investigate the awareness level of lung cancer prevention and control and the effect of individual characteristics on lung cancer awareness, and to provide evidence for comprehensive lung cancer prevention in high risk areas of lung cancer.

methodsStaffs of Tianjin Dagang Oil Field who participate low dose CT (LDCT) lung cancer screening by cluster sampling or according to voluntary principle were surveyed, data of lung cancer awareness were collected by questionnaire.

resultsA total of 1,633 valid questionnaires were collected. The average age of respondents was 60.08±6.58. Most participants were males (82.2%) while female only accounted for 17.8%. The proportions of awareness about lung cancer in China, risk factors, screening methods and the knowledge of health examination were 64.5%, 77.1%, 43.7%, 49.6% respectively. Result of multiple logistic regression analysis showed that education level, smoking (pack-year), age, prior tuberculosis were the influencing factors of lung cancer awareness with adjusted Ors for education and age level as of 0.567 (95%CI: 0.439-0.733) and 1.373 (95%CI: 1.084-1.739) respectively. 80.3% of the participants can accept health examination once a year, while the ability to pay the medical expenses was not high. The influencing factors of health examination willingness were gender, age, income, the knowledge of lung cancer.

conclusionsEducation level and smoking affect the awareness of lung cancer prevention and control, health education for lung cancer should be conducted especially in population with low education level. Comprehensive lung cancer control in high risk areas should combined lung cancer screening, tobacco control and health education.

Indexed as

AwarenessAgedChinaEarly Detection of CancerFemaleHumansLung NeoplasmsMaleMiddle AgedSurveys and QuestionnairesTomography, X-Ray Computed

Identifiers

PMID24581169
PMCPMC6000055

What OpenQuestion holds

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LicenceCC BY
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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.