Evidence map›Paper›PMID 16401279›Full record

ArticleBiometrics2005

MLE and Bayesian inference of age-dependent sensitivity and transition probability in periodic screening.

Dongfeng Wu, Gary L Rosner, Lyle Broemeling

Abstract read
In one paragraph

Article in Biometrics, 2005. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
21citing 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

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

  1. Pooled it
  2. Trial
  3. Article
  4. Article
  5. Article
  6. When to initiate cancer screening exam?Statistics and its interface · 2022
    Article
  7. Article
  8. Article
  9. Article
  10. Article
  11. Article
  12. A Bayesian nonlinear mixed-effects disease progression model.Journal of biometrics & biostatistics · 2015
    Article
  13. Bayesian lead time estimation for the Johns Hopkins Lung Project data.Journal of epidemiology and global health · 2013
    Article
  14. Article
  15. Sojourn time and lead time projection in lung cancer screening.Lung cancer (Amsterdam, Netherlands) · 2011
    Article
  16. Article
  17. Article
  18. Article
  19. Article
  20. 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

3 authors.

Dongfeng WuDepartment of Mathematics and Statistics, Mississippi State University, Mississippi State, 39762, USA. dwu@math.msstate.edu
Gary L Rosner
Lyle Broemeling

Funding

STATISTICAL METHODS FOR BREAST CANCER SCREENING STUDIESR01CA079466 · NCI · UNIVERSITY OF TX MD ANDERSON CAN CTR · PI SHEN, YU · 1999 to 2014
$1.5M
Statistical Inference for Lead Time in Cancer ScreeningR03CA115012 · NCI · MISSISSIPPI STATE UNIVERSITY · PI WU, DONGFENG · 2005 to 2006
$136k
NCI NIH HHS CA-79466NCI NIH HHS R01 CA079466NCI NIH HHS R03 CA115012
6 · The paper itself

Abstract

This article extends previous probability models for periodic breast cancer screening examinations. The specific aim is to provide statistical inference for age dependence of sensitivity and the transition probability from the disease free to the preclinical state. The setting is a periodic screening program in which a cohort of initially asymptomatic women undergo a sequence of breast cancer screening exams. We use age as a covariate in the estimation of screening sensitivity and the transition probability simultaneously, both from a frequentist point of view and within a Bayesian framework. We apply our method to the Health Insurance Plan of Greater New York study of female breast cancer and give age-dependent sensitivity and transition probability density estimates. The inferential methodology we develop is also applicable when analyzing studies of modalities for early detection of other types of progressive chronic diseases.

Indexed as

Bayes TheoremLikelihood FunctionsAdultAge FactorsBreast NeoplasmsFemaleHumansMammographyMass ScreeningMiddle AgedSensitivity and Specificity

Identifiers

PMID16401279
PMCPMC1540406

What OpenQuestion holds

Textmetadata
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.