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Record W4408225561 · doi:10.2196/70522

The Fire Fighter Cancer Cohort Study: Protocol for a Longitudinal Occupational Cohort Study

2025· article· en· W4408225561 on OpenAlexvenueno aff
Jefferey L. Burgess, Shawn C. Beitel, Miriam M. Calkins, Melissa Furlong, Paola Louzado‐Feliciano, Jamie Gabriel, Casey Grant, Jaclyn M. Goodrich, Judith M. Graber, Olivia Healy, James Hollister, J. Margaret Hughes, Sara A. Jahnke, Krystal Kern, Frank A Leeb, Alberto J. Caban‐Martinez, Alexander C. Mayer, Cynthia Porter, Sreenivasan Ranganathan, Heather M. Stapleton, Natasha Schaefer Solle, Christine Toennis, Derek J. Urwin, Michelle Valenti, John Gulotta

Bibliographic record

VenueJMIR Research Protocols · 2025
Typearticle
Languageen
FieldHealth Professions
TopicOccupational Health and Performance
Canadian institutionsnot available
FundersNational Institute of Environmental Health Sciences
KeywordsPreprintCohortMedicineCohort studyProtocol (science)GerontologyEnvironmental healthComputer scienceAlternative medicine

Abstract

fetched live from OpenAlex

BACKGROUND: Firefighters are at an increased risk of cancer and other health conditions compared with the general population. However, the specific exposures and mechanisms contributing to these risks are not fully understood. This information is critical to formulate and test protective interventions. OBJECTIVE: The purpose of the Fire Fighter Cancer Cohort Study (FFCCS) is to conduct community-engaged research with the fire service to advance the evaluation and reduction of firefighter exposures, along with understanding and mitigating effects leading to an increased risk of cancer and other health conditions. This involves establishing a long-term (>30 years) firefighter multicenter prospective cohort study. METHODS: The structure of the FFCCS includes a fire service oversight and planning board to provide guidance and foster communication between researchers and fire organizations; a data coordinating center overseeing survey data collection and data management; an exposure assessment center working with quantitative exposure data to construct a firefighter job exposure matrix; and a biomarker analysis center, including a biorepository. Together, the centers evaluate the association between firefighter exposures and toxic health effects. Firefighter research liaisons are involved in all phases of the research. The FFCCS research design primarily uses a set of core and project-specific survey questions accompanied by a collection of biological samples (blood and urine) for the analysis of biomarkers of exposure and effect. Data and samples are collected upon entry into the study, with subsequent collection after eligible exposures, and at intervals (eg, 1-2 years) after enrollment. FFCCS data collection and analysis have been developed to evaluate unique exposures for specific firefighter groups; cancer risks; and end points in addition to cancer, such as reproductive outcomes. Recruitment is carried out with coordination from partnering fire departments and eligible participants, including active career and volunteer firefighters in the United States. RESULTS: The FFCCS protocol development was first funded by the US Federal Emergency Management Agency in 2016, with enrollment beginning in February 2018. As of September 2024, >6200 participants from >275 departments across 31 states have enrolled, including recruit and incumbent firefighters. Biological samples have been analyzed for measures of exposure and effect. Specific groups enrolled in the FFCCS include career and volunteer structural firefighters, women firefighters, trainers, fire investigators, wildland firefighters, firefighters responding to wildland-urban interface fires, and airport firefighters. Peer-reviewed published results include measurement of exposures and the toxic effects of firefighting exposure. Whenever possible, research results are provided back to individual participants. CONCLUSIONS: The FFCCS is a unique, community-engaged, multicenter prospective cohort study focused on the fire service. Study results contribute to the evaluation of exposures, effects, and preventive interventions across multiple sectors of the US fire service, with broad implications nationally. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/70522.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.011
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Protocol · Consensus signal: Protocol
Teacher disagreement score0.195
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0110.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0070.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.002
Insufficient payload (model declined to judge)0.0010.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.494
GPT teacher head0.722
Teacher spread0.228 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designObservational
Domainnot available
GenreProtocol

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations10
Published2025
Admission routes1
Has abstractyes

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