Combining longitudinal studies of PSA

Lurdes Y.T. Inoue, Ruth Etzioni, Elizabeth H. Slate, Christopher Morrell, David F. Penson

Research output: Contribution to journalArticle

30 Citations (Scopus)

Abstract

Prostate-specific antigen (PSA) is a biomarker commonly used to screen for prostate cancer. Several studies have examined PSA growth rates prior to prostate cancer diagnosis. However, the resulting estimates are highly variable. In this article we propose a non-linear Bayesian hierarchical model to combine longitudinal data on PSA growth from three different studies. Our model enables novel investigations into patterns of PSA growth that were previously impossible due to sample size limitations. The goals of our analysis are twofold: first, to characterize growth rates of PSA accounting for differences when combining data from different studies; second, to investigate the impact of clinical covariates such as advanced disease and unfavorable histology on PSA growth rates.

Original languageEnglish (US)
Pages (from-to)483-500
Number of pages18
JournalBiostatistics
Volume5
Issue number3
DOIs
StatePublished - Jul 1 2004
Externally publishedYes

Fingerprint

Longitudinal Study
Prostate-Specific Antigen
Longitudinal Studies
Prostate Cancer
Bayesian Hierarchical Model
Growth
Histology
Biomarkers
Longitudinal Data
Covariates
Prostatic Neoplasms
Sample Size
Estimate
Longitudinal study
Prostate cancer
Model

Keywords

  • Bayesian hierarchical model
  • Interval-censored data
  • Longitudinal data
  • Meta-analysis
  • Prostate-specific antigen (PSA)

ASJC Scopus subject areas

  • Statistics and Probability
  • Medicine(all)
  • Statistics, Probability and Uncertainty

Cite this

Inoue, L. Y. T., Etzioni, R., Slate, E. H., Morrell, C., & Penson, D. F. (2004). Combining longitudinal studies of PSA. Biostatistics, 5(3), 483-500. https://doi.org/10.1093/biostatistics/kxh003

Combining longitudinal studies of PSA. / Inoue, Lurdes Y.T.; Etzioni, Ruth; Slate, Elizabeth H.; Morrell, Christopher; Penson, David F.

In: Biostatistics, Vol. 5, No. 3, 01.07.2004, p. 483-500.

Research output: Contribution to journalArticle

Inoue, LYT, Etzioni, R, Slate, EH, Morrell, C & Penson, DF 2004, 'Combining longitudinal studies of PSA', Biostatistics, vol. 5, no. 3, pp. 483-500. https://doi.org/10.1093/biostatistics/kxh003
Inoue LYT, Etzioni R, Slate EH, Morrell C, Penson DF. Combining longitudinal studies of PSA. Biostatistics. 2004 Jul 1;5(3):483-500. https://doi.org/10.1093/biostatistics/kxh003
Inoue, Lurdes Y.T. ; Etzioni, Ruth ; Slate, Elizabeth H. ; Morrell, Christopher ; Penson, David F. / Combining longitudinal studies of PSA. In: Biostatistics. 2004 ; Vol. 5, No. 3. pp. 483-500.
@article{89e3a024caec4225a5e20583c5d78526,
title = "Combining longitudinal studies of PSA",
abstract = "Prostate-specific antigen (PSA) is a biomarker commonly used to screen for prostate cancer. Several studies have examined PSA growth rates prior to prostate cancer diagnosis. However, the resulting estimates are highly variable. In this article we propose a non-linear Bayesian hierarchical model to combine longitudinal data on PSA growth from three different studies. Our model enables novel investigations into patterns of PSA growth that were previously impossible due to sample size limitations. The goals of our analysis are twofold: first, to characterize growth rates of PSA accounting for differences when combining data from different studies; second, to investigate the impact of clinical covariates such as advanced disease and unfavorable histology on PSA growth rates.",
keywords = "Bayesian hierarchical model, Interval-censored data, Longitudinal data, Meta-analysis, Prostate-specific antigen (PSA)",
author = "Inoue, {Lurdes Y.T.} and Ruth Etzioni and Slate, {Elizabeth H.} and Christopher Morrell and Penson, {David F.}",
year = "2004",
month = "7",
day = "1",
doi = "10.1093/biostatistics/kxh003",
language = "English (US)",
volume = "5",
pages = "483--500",
journal = "Biostatistics",
issn = "1465-4644",
publisher = "Oxford University Press",
number = "3",

}

TY - JOUR

T1 - Combining longitudinal studies of PSA

AU - Inoue, Lurdes Y.T.

AU - Etzioni, Ruth

AU - Slate, Elizabeth H.

AU - Morrell, Christopher

AU - Penson, David F.

PY - 2004/7/1

Y1 - 2004/7/1

N2 - Prostate-specific antigen (PSA) is a biomarker commonly used to screen for prostate cancer. Several studies have examined PSA growth rates prior to prostate cancer diagnosis. However, the resulting estimates are highly variable. In this article we propose a non-linear Bayesian hierarchical model to combine longitudinal data on PSA growth from three different studies. Our model enables novel investigations into patterns of PSA growth that were previously impossible due to sample size limitations. The goals of our analysis are twofold: first, to characterize growth rates of PSA accounting for differences when combining data from different studies; second, to investigate the impact of clinical covariates such as advanced disease and unfavorable histology on PSA growth rates.

AB - Prostate-specific antigen (PSA) is a biomarker commonly used to screen for prostate cancer. Several studies have examined PSA growth rates prior to prostate cancer diagnosis. However, the resulting estimates are highly variable. In this article we propose a non-linear Bayesian hierarchical model to combine longitudinal data on PSA growth from three different studies. Our model enables novel investigations into patterns of PSA growth that were previously impossible due to sample size limitations. The goals of our analysis are twofold: first, to characterize growth rates of PSA accounting for differences when combining data from different studies; second, to investigate the impact of clinical covariates such as advanced disease and unfavorable histology on PSA growth rates.

KW - Bayesian hierarchical model

KW - Interval-censored data

KW - Longitudinal data

KW - Meta-analysis

KW - Prostate-specific antigen (PSA)

UR - http://www.scopus.com/inward/record.url?scp=21644490251&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=21644490251&partnerID=8YFLogxK

U2 - 10.1093/biostatistics/kxh003

DO - 10.1093/biostatistics/kxh003

M3 - Article

C2 - 15208207

AN - SCOPUS:21644490251

VL - 5

SP - 483

EP - 500

JO - Biostatistics

JF - Biostatistics

SN - 1465-4644

IS - 3

ER -