Evidence map›Paper›PMID 34625802›Full record

ArticleAnnals of work exposures and health2022

Adapting Decision Rules to Estimate Occupational Metalworking Fluid Exposure in a Case-Control Study of Bladder Cancer in Spain.

Pabitra R Josse, Stella Koutros, Adonina Tardon, Nathaniel Rothman, Debra T Silverman, Melissa C Friesen

Abstract read
In one paragraph

Article in Annals of work exposures and health, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
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

6 authors.

Pabitra R JosseOccupational and Environmental Epidemiology Branch, Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, MD, USA.
Stella KoutrosOccupational and Environmental Epidemiology Branch, Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, MD, USA.ORCID 0000-0001-5294-5485
Adonina TardonDepartment of preventive medicine, University of Oviedo, Health Research Institute of Asturias, ISPA and CIBERESP, Oviedo, Spain.
Nathaniel RothmanOccupational and Environmental Epidemiology Branch, Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, MD, USA.
Debra T SilvermanOccupational and Environmental Epidemiology Branch, Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, MD, USA.
Melissa C FriesenOccupational and Environmental Epidemiology Branch, Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, MD, USA.

Funding

Molecular Epidemiology Studies of Occupational and Environmental ExposuresZIACP010121 · NCI · DIVISION OF CANCER EPIDEMIOLOGY AND GENETICS · PI ROTHMAN, NATHANIEL · 2009 to 2025
$23.5M
STUDIES OF OCCUPATIONAL CANCER--MOLECULAR EPIDEMIOLOGYZ01CP010121 · NCI · DIVISION OF CANCER EPIDEMIOLOGY AND GENETICS · PI ROTHMAN, NATHANIEL · 1997 to 2008
$4.4M
INVESTIGATIONS OF ENVIRONMENTAL EXPOSURES AND CANCERZ01CP010125 · NCI · DIVISION OF CANCER EPIDEMIOLOGY AND GENETICS · PI CANTOR, KENNETH · 1996 to 2008
$108k
Intramural NIH HHS Z01 CP010125NCI NIH HHS Z01 CP010121
6 · The paper itself

Abstract

objectivesWe adapted previously developed decision rules from the New England Bladder Cancer Study (NEBCS) to assign occupational exposure to straight, soluble, and synthetic metalworking fluids (MWFs) to participants of the Spanish Bladder Cancer Study (SBCS).

methodsThe SBCS and NEBCS are case-control studies that used the same lifetime occupational history and job module questionnaires. We adapted published decision rules from the NEBCS that linked questionnaire responses to estimates of the probability (<5, ≥5 to <50, ≥50 to <100, and 100%), frequency (in h week-1), and intensity (in mg m-3) of exposure to each of the three broad classes of MWFs to assign exposure to 10 182 reported jobs in the SBCS. The decision rules used the participant's module responses to MWF questions wherever possible. We then used these SBCS module responses to calculate job-, industry-, and time-specific patterns in the prevalence and frequency of MWF exposure. These estimates replaced the NEBCS-specific estimates in decision rules applied to jobs without MWF module responses. Intensity estimates were predicted using a previously developed statistical model that used the decade, industry (three categories), operation (grinding versus machining), and MWF type extracted from the SBCS questionnaire responses. We also developed new decision rules to assess mineral oil exposure from non-machining sources (possibly exposed versus not exposed). The decision rules for MWF and mineral oil identified questionnaire response patterns that required job-by-job expert review.

resultsTo assign MWF exposure, we applied decision rules that incorporated participant's responses and job group patterns for 99% of the jobs and conducted expert review of the remaining 1% (145) jobs. Overall, 14% of the jobs were assessed as having ≥5% probability of exposure to at least one of the three MWFs. Probability of exposure of ≥50% to soluble, straight, and synthetic MWFs was identified in 2.5, 1.7, and 0.5% of the jobs, respectively. To assign mineral oil from non-machining sources, we used module responses for 49% of jobs, a job-exposure matrix for 41% of jobs, and expert review for the remaining 10%. We identified 24% of jobs as possibly exposed to mineral oil from non-machining sources.

conclusionsWe demonstrated that we could adapt existing decision rules to assess exposure in a new population by deriving population-specific job group patterns.

Indexed as

Occupational ExposureUrinary Bladder NeoplasmsCase-Control StudiesFemaleHumansMaleMineral OilSpainMineral Oilbladder cancercase–control studyexposure assessmentmetalworking fluidsoccupational exposures

Identifiers

PMID34625802
PMCPMC8922194

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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.