Literature DB >> 12754719

Age-conditional probabilities of developing cancer.

Michael P Fay1, Ruth Pfeiffer, Kathleen A Cronin, Chenxiong Le, Eric J Feuer.   

Abstract

We propose an estimator of the probability of developing a disease in a given age range, conditional on never having developed the disease prior to the beginning of the age range. Our estimator improves the one described by Wun, Merrill and Feuer ( Lifetime Data Analysis 1998; 4, 169-186) that is currently used by the U.S. National Cancer Institute for the SEER Cancer Statistics Review. Both estimators use cross-sectional disease rates and provide an interpretation of these rates in terms of the age-conditional probability of developing disease in a hypothetical cohort. The difficulty of this problem is that rates are not available per person-years alive and disease free, but only per person-years alive. Wun et al. used ad hoc methods to handle this problem which did not properly account for competing risks, did not provide a measure of variability, and only allowed age ranges using prespecified 5-year age intervals. Here we solve the problem under a unified competing risks framework, which allows the calculation of the age-conditional probabilities for any age range. We generalize gamma confidence intervals to apply to our new statistic. Although our new method provides estimates which are numerically similar to that of Wun et al., this paper provides a comprehensive theoretical basis for estimation and inference about the age-conditional probability of developing a disease.

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Year:  2003        PMID: 12754719      PMCID: PMC1475950          DOI: 10.1002/sim.1428

Source DB:  PubMed          Journal:  Stat Med        ISSN: 0277-6715            Impact factor:   2.373


  3 in total

1.  Confidence intervals for directly standardized rates: a method based on the gamma distribution.

Authors:  M P Fay; E J Feuer
Journal:  Stat Med       Date:  1997-04-15       Impact factor: 2.373

2.  The natural variability of vital rates and associated statistics.

Authors:  D R Brillinger
Journal:  Biometrics       Date:  1986-12       Impact factor: 2.571

3.  Estimating lifetime and age-conditional probabilities of developing cancer.

Authors:  L M Wun; R M Merrill; E J Feuer
Journal:  Lifetime Data Anal       Date:  1998       Impact factor: 1.588

  3 in total
  37 in total

1.  Improved population-based probability of developing cancer when direct estimates of the cancer-free population are available.

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Journal:  Lifetime Data Anal       Date:  2012-03-20       Impact factor: 1.588

2.  German cancer statistics 2004.

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Journal:  BMC Cancer       Date:  2010-02-22       Impact factor: 4.430

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4.  Being 'at-risk' for developing cancer: cognitive representations and psychological outcomes.

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Journal:  J Behav Med       Date:  2008-09-19

Review 5.  CBTRUS Statistical Report: Primary Brain and Other Central Nervous System Tumors Diagnosed in the United States in 2011-2015.

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Journal:  Neuro Oncol       Date:  2018-10-01       Impact factor: 12.300

Review 6.  Hereditary pancreatic cancer: molecular bases and their application in diagnosis and clinical management: a guideline of the TTD group.

Authors:  P Pérez Segura; C Guillén Ponce; T Ramón Y Cajal; R Serrano Blanch; E Aranda
Journal:  Clin Transl Oncol       Date:  2012-07-19       Impact factor: 3.405

Review 7.  Systematic review: surveillance for breast cancer in women treated with chest radiation for childhood, adolescent, or young adult cancer.

Authors:  Tara O Henderson; Alison Amsterdam; Smita Bhatia; Melissa M Hudson; Anna T Meadows; Joseph P Neglia; Lisa R Diller; Louis S Constine; Robert A Smith; Martin C Mahoney; Elizabeth A Morris; Leslie L Montgomery; Wendy Landier; Stephanie M Smith; Leslie L Robison; Kevin C Oeffinger
Journal:  Ann Intern Med       Date:  2010-04-06       Impact factor: 25.391

8.  Risk of ESRD in the United States.

Authors:  Patrick Albertus; Hal Morgenstern; Bruce Robinson; Rajiv Saran
Journal:  Am J Kidney Dis       Date:  2016-08-28       Impact factor: 8.860

9.  Polygenic susceptibility to prostate and breast cancer: implications for personalised screening.

Authors:  N Pashayan; S W Duffy; S Chowdhury; T Dent; H Burton; D E Neal; D F Easton; R Eeles; P Pharoah
Journal:  Br J Cancer       Date:  2011-04-05       Impact factor: 7.640

10.  Using lifetime risk estimates in personal genomic profiles: estimation of uncertainty.

Authors:  Quanhe Yang; W Dana Flanders; Ramal Moonesinghe; John P A Ioannidis; Idris Guessous; Muin J Khoury
Journal:  Am J Hum Genet       Date:  2009-12       Impact factor: 11.025

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