This Article Full Text Full Text (PDF) Purchase Article View Shopping Cart Alert me when this article is cited Alert me if a correction is posted Services Email this article to a colleague Similar articles in this journal Similar articles in PubMed Alert me to new issues of the journal Save to my personal folders Download to citation manager Rights & Permissions Citing Articles Citing Articles via HighWire Citing Articles via Google Scholar Google Scholar Articles by Taylor, J. M.G. Articles by Sandler, H. M. Search for Related Content PubMed PubMed Citation Articles by Taylor, J. M.G. Articles by Sandler, H. M. Social Bookmarking                            What's this?

Individualized Predictions of Disease Progression Following Radiation Therapy for Prostate Cancer

From the Departments of Biostatistics and Radiation Oncology, University of Michigan, Ann Arbor, MI; and the Department of Biostatistics, Indiana University School of Medicine, Indianapolis, IN

Address reprint requests to Jeremy M.G. Taylor, PhD, Department of Biostatistics, University of Michigan, 1420 Washington Heights, Ann Arbor, MI 48109; e-mail: jmgt{at}umich.edu

PURPOSE: Following treatment for localized prostate cancer, men are monitored with serial prostate-specific antigen (PSA) measurements. Refining the predictive value of post-treatment PSA determinations may add to clinical management, and we have developed a model that predicts future PSA values and the time to future clinical recurrence for individual patients.

PATIENTS AND METHODS: Data from 934 patients treated between 1987 and 2000 were used to develop a comprehensive statistical model to fit the clinical recurrence events and patterns of PSA data. A logistic model was used for the probability of cure, mixed models were used for serial PSA measurements, and a proportional hazards model was used for recurrences. Data available through February 2001 were fit to the model, and data collected between February 2001 and September 2003 were used for validation.

RESULTS: T-stage, baseline PSA, and radiotherapy dosage are all associated with probability of cure. The risk of clinical recurrence in those not cured is strongly affected by the slope of PSA values. We show how the model can be used for individual monitoring of disease progression. For each patient the model predicts, based on baseline characteristics and all post-treatment PSA values, the probability of future clinical recurrences and future PSA values. The model accurately predicts risk of recurrence and future PSA values in the validation data set.

CONCLUSION: This predictive information on future PSA values and the risk of clinical relapse for each individual patient, which can be updated with each additional PSA value, may prove useful to patients and physicians in determining post-treatment salvage strategies.

Supported by the National Institutes of Health grants P30 CA46592 and P50 CA069568.

Authors’ disclosures of potential conflicts of interest are found at the end of this article.

CiteULike    Complore    Connotea    Del.icio.us    Digg    Facebook    Reddit    Technorati    Twitter    What's this?

This article has been cited by other articles:

				C. Proust-Lima and J. M. G. Taylor Development and validation of a dynamic prognostic tool for prostate cancer recurrence using repeated measures of posttreatment PSA: a joint modeling approach Biostat., July 1, 2009; 10(3): 535 - 549. [Abstract] [Full Text] [PDF]

				J. M.G. Taylor, D. P. Ankerst, and R. R. Andridge Validation of Biomarker-Based Risk Prediction Models Clin. Cancer Res., October 1, 2008; 14(19): 5977 - 5983. [Abstract] [Full Text] [PDF]

				C. A. Bellera, J. A. Hanley, L. Joseph, and P. C. Albertsen Detecting Trends in Noisy Data Series: Application to Biomarker Series Am. J. Epidemiol., May 1, 2008; 167(9): 1130 - 1139. [Abstract] [Full Text] [PDF]

				L. A. Worley, M. D. Onken, E. Person, D. Robirds, J. Branson, D. H. Char, A. Perry, and J. W. Harbour Transcriptomic versus Chromosomal Prognostic Markers and Clinical Outcome in Uveal Melanoma Clin. Cancer Res., March 1, 2007; 13(5): 1466 - 1471. [Abstract] [Full Text] [PDF]