Evidence map›Paper›PMID 22882896›Full record

ArticleRisk analysis : an official publication of the Society for Risk Analysis2012

Chapter 8: The FHCRC lung cancer model.

William D Hazelton, Jihyoun Jeon, Rafael Meza, Suresh H Moolgavkar

Open access · bronzeAbstract read
In one paragraph

Article in Risk analysis : an official publication of the Society for Risk Analysis, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers.

0numbers the graph read from it
0cells of the map it votes in
18citing papers in PubMed
1.2field-weighted citation impact, top 21% 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

18 citing papers in PubMed, 25 citations in OpenAlex.

  1. Article
  2. Review
  3. Article
  4. A Scoping Review on Calibration Methods for Cancer Simulation Models.Medical decision making : an international journal of the Society for Medical Decision Making · 2025
    Article
  5. Article
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  9. Article
  10. Article
  11. Article
  12. Article
  13. Comparison of Smoking History Patterns Among African American and White Cohorts in the United States Born 1890 to 1990.Nicotine & tobacco research : official journal of the Society for Research on Nicotine and Tobacco · 2016
    Article
  14. Chapter 12: Yale lung cancer model.Risk analysis : an official publication of the Society for Risk Analysis · 2012
    Article
  15. Chapter 13: CISNET lung models: comparison of model assumptions and model structures.Risk analysis : an official publication of the Society for Risk Analysis · 2012
    Article
  16. Chapter 6: Lung cancer in never smokers: epidemiology and risk prediction models.Risk analysis : an official publication of the Society for Risk Analysis · 2012
    Article
  17. Chapter 5: Actual and counterfactual smoking prevalence rates in the U.S. population via microsimulation.Risk analysis : an official publication of the Society for Risk Analysis · 2012
    Article
  18. Chapter 4: Development of the counterfactual smoking histories used to assess the effects of tobacco control.Risk analysis : an official publication of the Society for Risk Analysis · 2012
    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

4 authors at 1 institution in 1 country.

William D HazeltonFred Hutchinson Cancer Research Center, Public Health Science Division, 1100 Fairview Avenue North, Seattle, WA 98109, USA. hazelton@fhcrc.org
Jihyoun Jeon
Rafael Meza
Suresh H Moolgavkar
Fred Hutch Cancer Center · US

Funding

Comparative Modeling of Lung Cancer Control PoliciesU01CA152956 · NCI · MASSACHUSETTS GENERAL HOSPITAL · PI DE KONING, HARRY J, KONG, CHUNG YIN · 2010 to 2014
$7.4M
Lung Cancer in the U.S.: Trends and PreventionU01CA097415 · NCI · FRED HUTCHINSON CANCER RESEARCH CENTER · PI MOOLGAVKAR, SURESH H · 2002 to 2009
$1.8M
NCI NIH HHS U01 CA097415NCI NIH HHS U01 CA152956NCI NIH HHS UO1 CA097415NCI NIH HHS UO1 CA152956
6 · The paper itself

Abstract

As a member of the Cancer Intervention and Surveillance Modeling Network (CISNET), the lung cancer (LC) group at Fred Hutchinson Cancer Research Center (FHCRC) developed a model for evaluating U.S. lung cancer mortality trends and the impact of changing tobacco consumption. Model components include a biologically based two-stage clonal expansion (TSCE) model; a smoking simulator to generate smoking histories and other cause mortality; and adjustments for period and birth cohort to improve calibration to U.S. LC mortality. The TSCE model was first calibrated to five substantial cohorts: British doctors, American Cancer Society CPS-I and CPS-II, Health Professionals' Follow-Up Study (HPFS), and Nurses' Health Study (NHS). The NHS and HPFS cohorts included the most detailed smoking histories and were chosen to represent the effects of smoking on U.S. LC mortality. The calibrated TSCE model and smoking simulator were used to simulate U.S. LC mortality. Further adjustments were necessary to account for unknown factors. This provided excellent fits between simulated and observed U.S. LC mortality for ages 30-84 and calendar years 1975-2000. The FHCRC LC model may be used to study the effects of public health information on U.S. LC trends and the impact of tobacco control policy. For example, we estimated that over 500,000 males and 200,000 females avoided LC death between 1975 and 2000 due to increasing awareness since the mid 1950s of the harmful effects of smoking. We estimated that 1.1 million male and 0.6 million female LC deaths were avoidable if smokers quit smoking in 1965.

Indexed as

AdultAgedAged, 80 and overCalibrationCohort StudiesDisease ProgressionFemaleHealth EducationHumansLung NeoplasmsMaleMiddle AgedModels, StatisticalModels, TheoreticalPublic HealthSmoking

Identifiers

PMID22882896
PMCPMC3475418
OpenAlexW1885546850

What OpenQuestion holds

Textmetadata
LicenceTDM
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.