Mixed-effects regression models for studying the natural history of prostate disease

J. D. Pearson, C. H. Morrell, P. K. Landis, H Ballentine Carter, L. J. Brant

Research output: Contribution to journalArticle

Abstract

Although prostate cancer and benign prostatic hyperplasia are major health problems in U.S. men, little is known about the early stages of the natural history of prostate disease. A molecular biomarker called prostate specific antigen (PSA), together with a unique longitudinal bank of frozen serum, now allows a historic prospective study of changes in PSA levels for decades prior to the diagnosis of prostate disease. Linear mixed-effects regression models were used to test whether rates of change in PSA were different in men with and without prostate disease. In addition, since the prostate cancer cases developed their tumours at different (and unknown) times during their periods of follow-up, a piece-wise non-linear mixed-effects regression model was used to estimate the time when rapid increases in PSA were first observable beyond the background level of PSA change. These methods have a wide range of applications in biomedical research utilizing repeated measures data such as pharmacokinetic studies, crossover trials, growth and development studies, aging studies, and disease detection.

Original languageEnglish (US)
Pages (from-to)587-601
Number of pages15
JournalStatistics in Medicine
Volume13
Issue number5-7
StatePublished - 1994

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Mixed Effects
Prostate-Specific Antigen
Natural History
Prostate
Regression Model
Prostate Cancer
Crossover Trial
Prostatic Neoplasms
Measure Data
Repeated Measures
Rate of change
Pharmacokinetics
Biomarkers
Nonlinear Effects
Prostatic Hyperplasia
Tumor
Health
Growth and Development
Cross-Over Studies
Biomedical Research

ASJC Scopus subject areas

  • Epidemiology

Cite this

Pearson, J. D., Morrell, C. H., Landis, P. K., Carter, H. B., & Brant, L. J. (1994). Mixed-effects regression models for studying the natural history of prostate disease. Statistics in Medicine, 13(5-7), 587-601.

Mixed-effects regression models for studying the natural history of prostate disease. / Pearson, J. D.; Morrell, C. H.; Landis, P. K.; Carter, H Ballentine; Brant, L. J.

In: Statistics in Medicine, Vol. 13, No. 5-7, 1994, p. 587-601.

Research output: Contribution to journalArticle

Pearson, JD, Morrell, CH, Landis, PK, Carter, HB & Brant, LJ 1994, 'Mixed-effects regression models for studying the natural history of prostate disease', Statistics in Medicine, vol. 13, no. 5-7, pp. 587-601.
Pearson, J. D. ; Morrell, C. H. ; Landis, P. K. ; Carter, H Ballentine ; Brant, L. J. / Mixed-effects regression models for studying the natural history of prostate disease. In: Statistics in Medicine. 1994 ; Vol. 13, No. 5-7. pp. 587-601.
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