Modeling grade progression in an active surveillance study.

Modeling grade progression in an active surveillance study.
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DOI:
10.1002/sim.6003
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发表时间:
2014-03-15
影响因子:
2
通讯作者:
Etzioni, Ruth
Etzioni, Ruth
中科院分区:
医学3区
文献类型:
--
作者:
Inoue, Lurdes Y. T.;Trock, Bruce J.;Partin, Alan W.;Carter, Herbert B.;Etzioni, Ruth

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Prostate cancer grade, assessed with the Gleason score, describes how abnormal the tumor tissue and cells appear and it is an important prognostic indicator of disease progression. Whether prostate tumors change grade is a question that has implications for screening and treatment. Empirical data on tumor grade over time have become available from men biopsied regularly as part of active surveillance (AS). However, biopsy grade is subject to misclassification. In this article we develop a model that allows for estimation of the time of grade change while accounting for the misclassification error from biopsy grade. We use misclassification rates from studies of prostate cancer biopsies followed by radical prostatectomy. Estimation of the transition times from true low-grade to high-grade disease is conducted within a Bayesian framework. We apply our model to serial observations on biopsy grade among 627 cases enrolled in a cohort of AS patients at Johns Hopkins University who were biopsied annually and referred to treatment if there was any evidence of disease progression on biopsy. We consider different prior distributions for the time to true grade progression. The estimated likelihood of grade progression within 10 years of study entry ranges from 12% to 24% depending on the prior. We conclude that knowledge of rates of grade misclassification allows for determination of true grade progression rates among men with serial biopsies on AS. While our results are sensitive to prior specifications they indicate that in a non-trivial fraction of the patient population, tumor grade can progress.
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