Statistical Issues Involved in Medical Device Postmarketing Surveillance
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STATISTICAL ISSUES INVOLVED IN MEDICAL DEVICE POSTMARKETING SURVEILLANCE* CHANGS. LAO,PHD Mathematical Statistician, Division of Biostatistics, Office of Surveillance and Biometrics. Center for Devices and Radiological Health, Food and Drug Administration, Rockville, Maryland
This paper describes several statistical methods for analyzing medical device reports received by the Food and Drug Administration. The nonparametric regressions (polynomial, loess, kernel smooth, and cubic spline smoothing) are used as exploratory tools to evaluate trends in adverse event reports. Several statistical models, including simple Poisson, mixed binornial/Poisson, zero-truncated Poisson, and the negative binomial (compound Poisson), are used to monitor and to determine the upper 95% threshold values for reported adverse events during the study period. The hip implant injury data and the intravenous tube total (sum of death, device malfunction, and injury) data are used to illustrate our model fitting procedures. In this paper; only the numerator data (medical device adverse events), not the denominator data (medical device usage), are available in our statistical analysis. The possible effects of marketing time and other factors, which may be available in adverse drug reactions, are not available and are not considered for medical device adverse events in this pape,: Key Words: Medical device reports; Model fitting; Trend analysis; Monitoring; Threshold cutoff point
INTRODUCTION
premarket approval and clearance. Due to limited sample size and duration of the studIN 1976, THE UNITED STATES Food, ies, however, these premarket approval studDrug, and Cosmetic Act required that manu- ies may not be able to detect uncommon and facturers of medical and radiation-emitting unexpected adverse events. devices conduct scientifically validated analIn 1984, the United States Food and Drug yses and studies, including reasonably de- Administration (FDA) required manufactursigned clinical trials, to demonstrate the ers of medical and radiation-emitting devices safety and effectiveness of their products for to submit reports of events that reasonably suggest that a medical device has caused or may have caused or contributed to the death, Reprint address: Chang S. Lao, PhD, Mathematical serious injury, or serious illness of a patient, Statistician, Division of Biostatistics, Office of S w e i l - and device malfunctions whose recurrence lance and Biometrics, HFZ-542, Center for Devices and would likely result in death, serious injury, Radiological Health, Food and Drug Administration, or serious illness of a patient. There are gen1350 Piccard Drive. Rockville, MD 20850. erally two major programs to receive medical *The views expressed are those of the author, and device reports (MDRs) from various reportnot necessarily those of the FDA. 483
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