Evidence map›Paper›PMID 22705252›Full record

ArticleMathematical biosciences2012

Longitudinal multistage model for lung cancer incidence, mortality, and CT detected indolent and aggressive cancers.

William D Hazelton, Gary Goodman, William N Rom, Melvyn Tockman, Mark Thornquist, Suresh Moolgavkar, Joel L Weissfeld, Ziding Feng

Open access · greenAbstract read
In one paragraph

Article in Mathematical biosciences, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed, 1 pooled it
1.0field-weighted citation impact, top 22% 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

7 citing papers in PubMed, 1 synthesis or guideline pooled it, 14 citations in OpenAlex.

  1. Pooled it
  2. Article
  3. Natural history models for lung Cancer: A scoping review.Lung cancer (Amsterdam, Netherlands) · 2025
    Article
  4. Current Evidence for a Lung Cancer Screening Program.Portuguese journal of public health · 2024
    Review
  5. Article
  6. Article
  7. Lung cancer screening with low-dose computed tomography.Radiologic clinics of North America · 2014
    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 at 4 institutions in 1 country.

William D HazeltonFred Hutchinson Cancer Research Center, Public Health Sciences Division, 1100 Fairview Avenue North, Box 19024, Seattle, WA 98109, USA. hazelton@fhcrc.org
Gary Goodman
William N Rom
Melvyn Tockman
Mark Thornquist
Suresh Moolgavkar
Joel L Weissfeld
Ziding Feng
Fred Hutch Cancer Center · USMoffitt Cancer Center · USNew York University · USUniversity of Pittsburgh · US

Funding

Vitamin D3 Modulation of Inflammation and Lung Cancer RiskP50CA090440 · NCI · UNIVERSITY OF PITTSBURGH AT PITTSBURGH · PI DACIC, SANJA · 2001 to 2015
$34.6M
INTEGRATED DEVELOPMENT OF NOVEL MOLECULAR MARKERSU01CA084986 · NCI · JOHNS HOPKINS UNIVERSITY · PI SIDRANSKY, DAVID · 1999 to 2014
$33.8M
EDRN--DATA MANAGEMENT AND COORDINATING CENTERU01CA086368 · NCI · FRED HUTCHINSON CANCER RESEARCH CENTER · PI FENG, ZIDING · 2000 to 2010
$16.9M
NYU Lung Cancer Biomarker CenterU01CA086137 · NCI · NEW YORK UNIVERSITY SCHOOL OF MEDICINE · PI ROM, WILLIAM N · 2000 to 2015
$15.3M
THE CAROTENE AND RETINOL EFFICACY TRIAL (CARET)U01CA063673 · NCI · FRED HUTCHINSON CANCER RESEARCH CENTER · PI GOODMAN, GARY E · 1994 to 2006
$13.0M
Comparative Modeling of Lung Cancer Control PoliciesU01CA152956 · NCI · MASSACHUSETTS GENERAL HOSPITAL · PI DE KONING, HARRY J, KONG, CHUNG YIN · 2010 to 2014
$7.4M
Modeling Colon Cancer, Intervention and PreventionR01CA107028 · NCI · FRED HUTCHINSON CANCER RESEARCH CENTER · PI LUEBECK, GEORG E. · 2005 to 2013
$2.1M
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 5U01CA086137NCI NIH HHS P50 CA090440NCI NIH HHS P50 CA90440NCI NIH HHS R01 CA107028NCI NIH HHS U01 CA063673NCI NIH HHS U01 CA084986NCI NIH HHS U01 CA086137NCI NIH HHS U01 CA086368NCI NIH HHS U01 CA097415NCI NIH HHS U01CA097415NCI NIH HHS U01 CA152956NCI NIH HHS U01 CA63673NCI NIH HHS UO1 CA084986NCI NIH HHS UO1 CA097415NCI NIH HHS UO1 CA152956NCI NIH HHS UO1 CA86368
6 · The paper itself

Abstract

It is currently not known whether most lung cancers detected by computerized tomography (CT) screening are aggressive and likely to be fatal if left untreated, or if a sizable fraction are indolent and unlikely to cause death during the natural lifetime of the individual. We developed a longitudinal biologically-based model of the relationship between individual smoking histories and the probability for lung cancer incidence, CT screen detection, lung cancer mortality, and other-cause mortality. The longitudinal model relates these different outcomes to an underlying lung cancer disease pathway and an effective other-cause mortality pathway, which are both influenced by the individual smoking history. The longitudinal analysis provides additional information over that available if these outcomes were analyzed separately, including testing if the number of CT detected and histologically-confirmed lung cancers is consistent with the expected number of lung cancers "in the pipeline". We assume indolent nodules undergo Gompertz growth and are detectable by CT, but do not grow large enough to contribute significantly to symptom-based lung cancer incidence or mortality. Likelihood-based model calibration was done jointly to data from 6878 heavy smokers without asbestos exposure in the control (placebo) arm of the Carotene and Retinol Efficacy Trial (CARET); and to 3,642 heavy smokers with comparable smoking histories in the Pittsburgh Lung Screening Study (PLuSS), a single-arm prospective trial of low-dose spiral CT screening for diagnosis of lung cancer. Model calibration was checked using data from two other single-arm prospective CT screening trials, the New York University Lung Cancer Biomarker Center (NYU) (n=1,021), and Moffitt Cancer Center (Moffitt) cohorts (n=677). In the PLuSS cohort, we estimate that at the end of year 2, after the baseline and first annual CT exam, that 33.0 (26.9, 36.9)% of diagnosed lung cancers among females and 7.0 (4.9,11.7)% among males were overdiagnosed due to being indolent cancers. At the end of the PLuSS study, with maximum follow-up of 5.8 years, we estimate that due to early detection by CT and limited follow-up, an additional 2.2 (2.0,2.4)% of all diagnosed cancers among females and 7.1 (6.7,8.0)% among males would not have been diagnosed in the absence of CT screening. We also find a higher apparent cure rate for lung cancer among CARET females than males, consistent with the larger indolent fraction of CT detected and histologically confirmed lung cancers among PLuSS females. This suggests that there are significant gender differences in the aggressiveness of lung cancer. Females may have an inherently higher proportion of indolent lung cancers than males, or aggressive lung cancers may be brought into check by the immune system more frequently among females than males.

Indexed as

Models, StatisticalFemaleHumansIncidenceLongitudinal StudiesLung NeoplasmsMaleMass ScreeningMiddle AgedNew YorkPennsylvaniaSex FactorsSmokingTomography, X-Ray Computed

Identifiers

PMID22705252
PMCPMC3412888
OpenAlexW1995901688

What OpenQuestion holds

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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.