Evidence map›Paper›PMID 26090590›Full record

Trial reportScientific reports2015

Prediction models and risk assessment for silicosis using a retrospective cohort study among workers exposed to silica in China.

Lap Ah Tse, Juncheng Dai, Minghui Chen, Yuewei Liu, Hao Zhang, Tze Wai Wong, Chi Chiu Leung, Hans Kromhout, Evert Meijer, Su Liu and 4 more

Open access · goldAbstract readClinical Trial
PubMed Full text at PMC Publisher
In one paragraph

Trial report in Scientific reports, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers.

0numbers the graph read from it
0cells of the map it votes in
19citing papers in PubMed
3.1field-weighted citation impact, top 8% 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

19 citing papers in PubMed, 47 citations in OpenAlex.

  1. Article
  2. Review
  3. A rare case of silicosis with hepatitis B infection.Annals of medicine and surgery (2012) · 2022
    Article
  4. Epidemiology of silicosis reported to the central register of occupational diseases over last 20 years in Poland.International journal of occupational medicine and environmental health · 2022
    Article
  5. Article
  6. Article
  7. Article
  8. Article
  9. Article
  10. Article
  11. The epidemiology of idiopathic pulmonary fibrosis and interstitial lung diseases at risk of a progressive-fibrosing phenotype.European respiratory review : an official journal of the European Respiratory Society · 2018
    Review
  12. Article
  13. HO-1 protects smokers exposed to artificial stone dust for pulmonary function tests deterioration.Sarcoidosis, vasculitis, and diffuse lung diseases : official journal of WASOG · 2018
    Article
  14. Article
  15. Article
  16. Article
  17. Article
  18. Article
  19. 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

14 authors at 4 institutions in 2 countries.

Lap Ah TseDivision of Occupational and Environmental Health, JC School of Public Health and Primary Care, the Chinese University of Hong Kong, HKSAR, China.
Juncheng Dai1] Division of Occupational and Environmental Health, JC School of Public Health and Primary Care, the Chinese University of Hong Kong, HKSAR, China [2] Department of Epidemiology and Biostatistics, Collaborative Innovation Center of Cancer Medicine, School of Public Health, Nanjing Medical University, Nanjing, China.
Minghui ChenDivision of Occupational and Environmental Health, JC School of Public Health and Primary Care, the Chinese University of Hong Kong, HKSAR, China.
Yuewei LiuDepartment of Occupational &Environmental Health and MOE Key lab of Environmental and Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
Hao ZhangDepartment of Occupational &Environmental Health and MOE Key lab of Environmental and Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
Tze Wai WongDivision of Occupational and Environmental Health, JC School of Public Health and Primary Care, the Chinese University of Hong Kong, HKSAR, China.
Chi Chiu LeungPneumoconiosis Clinic, Department of Health, HKSAR, China.
Hans KromhoutInstitute for Risk Assessment Sciences, Utrecht University, Netherlands.
Evert MeijerPneumoconiosis Clinic, Department of Health, HKSAR, China.
Su LiuDivision of Occupational and Environmental Health, JC School of Public Health and Primary Care, the Chinese University of Hong Kong, HKSAR, China.
Feng WangDivision of Occupational and Environmental Health, JC School of Public Health and Primary Care, the Chinese University of Hong Kong, HKSAR, China.
Ignatius Tak-sun Yu1] Division of Occupational and Environmental Health, JC School of Public Health and Primary Care, the Chinese University of Hong Kong, HKSAR, China [2] Hong Kong Academy of Occupational and Environmental Health.
Hongbing ShenDepartment of Epidemiology and Biostatistics, Collaborative Innovation Center of Cancer Medicine, School of Public Health, Nanjing Medical University, Nanjing, China.
Weihong ChenDepartment of Occupational &Environmental Health and MOE Key lab of Environmental and Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
Chinese University of Hong Kong · CNHuazhong University of Science and Technology · CNNanjing Medical University · CNUtrecht University · NL

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This study aims to develop a prognostic risk prediction model for the development of silicosis among workers exposed to silica dust in China. The prediction model was performed by using retrospective cohort of 3,492 workers exposed to silica in an iron ore, with 33 years of follow-up. We developed a risk score system using a linear combination of the predictors weighted by the LASSO penalized Cox regression coefficients. The model's predictive accuracy was evaluated using time-dependent ROC curves. Six predictors were selected into the final prediction model (age at entry of the cohort, mean concentration of respirable silica, net years of dust exposure, smoking, illiteracy, and no. of jobs). We classified workers into three risk groups according to the quartile (Q1, Q3) of risk score; 203 (23.28%) incident silicosis cases were derived from the high risk group (risk score ≥ 5.91), whilst only 4 (0.46%) cases were from the low risk group (risk score < 3.97). The score system was regarded as accurate given the range of AUCs (83-96%). This study developed a unique score system with a good internal validity, which provides scientific guidance to the clinicians to identify high-risk workers, thus has important cost efficient implications.

Indexed as

Biobehavioral SciencesAdultAge FactorsChinaFemaleFollow-Up StudiesHumansMaleOccupational ExposurePredictive Value of TestsRetrospective StudiesRisk FactorsSilicon DioxideSilicosisSilicon Dioxide

Identifiers

PMID26090590
PMCPMC4473532
OpenAlexW2343496494

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

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.