© 2001 by Oxford University Press
Journal of the National Cancer Institute, Vol. 93, No. 7, 534-538,
April 4, 2001
© 2001 Oxford University Press
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Methodology for Treatment Evaluation in Patients With Cancer Metastatic to Bone
Affiliations of authors: R. J. Cook, Department of Statistics and Actuarial Science, University of Waterloo, ON, Canada; P. Major, Hamilton Regional Cancer Centre and Department of Medicine, McMaster University, ON.
Correspondence to: Pierre Major, M.D., Hamilton Regional Cancer Center, 699 Concession St., Hamilton, ON, Canada L8V 5C2.
Background: Patients with cancer metastatic to bone experience several adverse and clinically important skeletal-related events, including pathologic fractures, vertebral compressions with fracture, the need for surgery to treat or prevent fractures, and the need for radiation therapy for the treatment of bone pain. We present appropriate methods for describing and modeling the clinical course of skeletal-related events and comparing treatments for such events. Methods: On the basis of data from a recently completed randomized, placebo-controlled trial involving 380 breast cancer patients with bone metastases, we tested the validity of the "events-per-person-years" method, one of the most commonly used techniques, for the analysis of skeletal-related events. We then used more robust methods of analysis that are based on fewer assumptions, including a random-effects Poisson model, and contrasted the inferences about skeletal-related event rates and treatment effects for the different analytic methods. All statistical tests were two-sided. Results: The events-per-person-years analysis underestimated substantially the variation in the data and is not appropriate to summarize the incidence rate of skeletal-related events. A random-effects Poisson model did provide a valid basis for analyzing such data. Conclusions: The underestimation of variability in data associated with the use of the events-per-person-years analysis leads to unduly narrow confidence intervals for complication rates and inflated false-positive error rates in treatment comparisons. A random-effects Poisson model provides a valid, robust basis for describing the clinical course of bone complications and evaluating treatment effects.
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