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Estimating age conditional probability of developing disease from surveillance data

Fay, Pfeiffer, Cronin, Le, and Feuer (Statistics in Medicine 2003; 22; 1837–1848) developed a formula to calculate the age-conditional probability of developing a disease for the first time (ACPDvD) for a hypothetical cohort. The novelty of the formula of Fay et al (2003) is that one need not know t...

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Autor principal: Fay, Michael P
Formato: Texto
Lenguaje:English
Publicado: BioMed Central 2004
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC517510/
https://www.ncbi.nlm.nih.gov/pubmed/15279675
http://dx.doi.org/10.1186/1478-7954-2-6
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author Fay, Michael P
author_facet Fay, Michael P
author_sort Fay, Michael P
collection PubMed
description Fay, Pfeiffer, Cronin, Le, and Feuer (Statistics in Medicine 2003; 22; 1837–1848) developed a formula to calculate the age-conditional probability of developing a disease for the first time (ACPDvD) for a hypothetical cohort. The novelty of the formula of Fay et al (2003) is that one need not know the rates of first incidence of disease per person-years alive and disease-free, but may input the rates of first incidence per person-years alive only. Similarly the formula uses rates of death from disease and death from other causes per person-years alive. The rates per person-years alive are much easier to estimate than per person-years alive and disease-free. Fay et al (2003) used simple piecewise constant models for all three rate functions which have constant rates within each age group. In this paper, we detail a method for estimating rate functions which does not have jumps at the beginning of age groupings, and need not be constant within age groupings. We call this method the mid-age group joinpoint (MAJ) model for the rates. The drawback of the MAJ model is that numerical integration must be used to estimate the resulting ACPDvD. To increase computational speed, we offer a piecewise approximation to the MAJ model, which we call the piecewise mid-age group joinpoint (PMAJ) model. The PMAJ model for the rates input into the formula for ACPDvD described in Fay et al (2003) is the current method used in the freely available DevCan software made available by the National Cancer Institute.
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spelling pubmed-5175102004-09-17 Estimating age conditional probability of developing disease from surveillance data Fay, Michael P Popul Health Metr Research Fay, Pfeiffer, Cronin, Le, and Feuer (Statistics in Medicine 2003; 22; 1837–1848) developed a formula to calculate the age-conditional probability of developing a disease for the first time (ACPDvD) for a hypothetical cohort. The novelty of the formula of Fay et al (2003) is that one need not know the rates of first incidence of disease per person-years alive and disease-free, but may input the rates of first incidence per person-years alive only. Similarly the formula uses rates of death from disease and death from other causes per person-years alive. The rates per person-years alive are much easier to estimate than per person-years alive and disease-free. Fay et al (2003) used simple piecewise constant models for all three rate functions which have constant rates within each age group. In this paper, we detail a method for estimating rate functions which does not have jumps at the beginning of age groupings, and need not be constant within age groupings. We call this method the mid-age group joinpoint (MAJ) model for the rates. The drawback of the MAJ model is that numerical integration must be used to estimate the resulting ACPDvD. To increase computational speed, we offer a piecewise approximation to the MAJ model, which we call the piecewise mid-age group joinpoint (PMAJ) model. The PMAJ model for the rates input into the formula for ACPDvD described in Fay et al (2003) is the current method used in the freely available DevCan software made available by the National Cancer Institute. BioMed Central 2004-07-27 /pmc/articles/PMC517510/ /pubmed/15279675 http://dx.doi.org/10.1186/1478-7954-2-6 Text en Copyright © 2004 Fay; licensee BioMed Central Ltd. http://creativecommons.org/licenses/by/2.0 This is an open-access article distributed under the terms of the Creative Commons Attribution License ( (http://creativecommons.org/licenses/by/2.0) ), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Research
Fay, Michael P
Estimating age conditional probability of developing disease from surveillance data
title Estimating age conditional probability of developing disease from surveillance data
title_full Estimating age conditional probability of developing disease from surveillance data
title_fullStr Estimating age conditional probability of developing disease from surveillance data
title_full_unstemmed Estimating age conditional probability of developing disease from surveillance data
title_short Estimating age conditional probability of developing disease from surveillance data
title_sort estimating age conditional probability of developing disease from surveillance data
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC517510/
https://www.ncbi.nlm.nih.gov/pubmed/15279675
http://dx.doi.org/10.1186/1478-7954-2-6
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