Evidence map›Paper›PMID 28692191›Full record

ArticleAmerican journal of industrial medicine2017

Capture and coding of industry and occupation measures: Findings from eight National Program of Cancer Registries states.

MaryBeth B Freeman, Lori A Pollack, Judy R Rees, Christopher J Johnson, Randi K Rycroft, David L Rousseau, Mei-Chin Hsieh, enhancement of NPCR for comparative effectiveness research team

Abstract read
In one paragraph

Article in American journal of industrial medicine, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
11citing 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

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

  1. The quality of social determinants data in the electronic health record: a systematic review.Journal of the American Medical Informatics Association : JAMIA · 2021
    Pooled it
  2. Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. Laying the Foundation for a Mesothelioma Patient Registry: Development of Data Collection Tools.International journal of environmental research and public health · 2023
    Article
  8. Article
  9. Demographic considerations in analyzing decedents by usual occupation.American journal of industrial medicine · 2020
    Article
  10. Article
  11. 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

8 authors.

MaryBeth B FreemanCancer Surveillance Branch, Division of Cancer Prevention and Control, National Center for Chronic Disease Prevention and Health Promotion, Centers for Disease Control and Prevention, Atlanta, Georgia.ORCID http://orcid.org/0000-0002-7709-3749
Lori A PollackCancer Surveillance Branch, Division of Cancer Prevention and Control, National Center for Chronic Disease Prevention and Health Promotion, Centers for Disease Control and Prevention, Atlanta, Georgia.
Judy R ReesNew Hampshire State Cancer Registry and the Geisel School of Medicine at Dartmouth, Department of Epidemiology, Hanover, New Hampshire.
Christopher J JohnsonCancer Data Registry of Idaho, Boise, Idaho.
Randi K RycroftColorado Central Cancer Registry, Denver, Colorado.
David L RousseauRhode Island Cancer Registry, Providence, Rhode Island.
Mei-Chin HsiehLouisiana Tumor Registry and Epidemiology Program, School of Public Health, Louisiana State University Health Sciences Center, New Orleans, Louisiana.
enhancement of NPCR for comparative effectiveness research team

Funding

PROJECT CONSISTS OF THE NAT'L COMPREHENSIVE CANCER CONTROL PROG, NAT'L PROG FOR CU58DP000792 · DP · ALASKA STATE DEPARTMENT OF HLTH-SOC SVCS · PI ALLELY, KATHY · 2007 to 2011
$15.8M
Intramural CDC HHS CC999999NCCDPHP CDC HHS U58 DP000792
6 · The paper itself

Abstract

backgroundAlthough data on industry and occupation (I&O) are important for understanding cancer risks, obtaining standardized data is challenging. This study describes the capture of specific I&O text and the ability of a web-based tool to translate text into standardized codes.

methodsData on 62 525 cancers cases received from eight National Program of Cancer Registries (NPCR) states were submitted to a web-based coding tool developed by the National Institute for Occupational Safety and Health for translation into standardized I&O codes. We determined the percentage of sufficiently analyzable codes generated by the tool.

resultsUsing the web-based coding tool on data obtained from chart abstraction, the NPCR cancer registries achieved between 48% and 75% autocoding, but only 12-57% sufficiently analyzable codes.

conclusionsThe ability to explore associations between work-related exposures and cancer is limited by current capture and coding of I&O data. Increased training of providers and registrars, as well as software enhancements, will improve the utility of I&O data.

Indexed as

SoftwareData CollectionHumansNeoplasmsOccupational DiseasesOccupationsRegistriesUnited StatescancerindustryNIOCCSNPCRoccupation

Identifiers

PMID28692191
PMCPMC5769461

What OpenQuestion holds

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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.