Case-control study on uveal melanoma (RIFA): rational and design

Andrea Schmidt-Pokrzywniak¹ , Karl-Heinz Jöckel¹ , Norbert Bornfeld² and Andreas Stang³

¹Institute of Medical Informatics, Biometry and Epidemiology, University Hospital, University of Duisburg-Essen, Hufelandstr. 55, 45122 Essen, Germany

²Division of Ophthalmology, University Hospital, University of Duisburg-Essen, Hufelandstr. 55, 45122 Essen, Germany

³Institute of Medical Epidemiology, Biometry and Informatics, Medical Faculty, Martin-Luther-University Halle-Wittenberg, Magdeburgerstr. 27, 06097 Halle, Germany

author email corresponding author email

BMC Ophthalmology 2004, 4:11doi:10.1186/1471-2415-4-11


Published:	19 August 2004

Abstract

Background

Although a rare disease, uveal melanoma is the most common primary intraocular malignancy in adults, with an incidence rate of up to 1.0 per 100,000 persons per year in Europe. Only a few consistent risk factors have been identified for this disease. We present the study design of an ongoing incident case-control study on uveal melanoma (acronym: RIFA study) that focuses on radiofrequency radiation as transmitted by radio sets and wireless telephones, occupational risk factors, phenotypical characteristics, and UV radiation.

Methods/Design

We conduct a case-control study to identify the role of different exposures in the development of uveal melanoma. The cases of uveal melanoma were identified at the Division of Ophthalmology, University of Essen, a referral centre for tumours of the eye. We recruit three control groups: population controls, controls sampled from those ophthalmologists who referred cases to the Division of Ophthalmology, University of Duisburg-Essen, and sibling controls. For each case the controls are matched on sex and age (five year groups), except for sibling controls. The data are collected from the study participants by short self-administered questionnaire and by telephone interview. During and at the end of the field phase, the data are quality-checked.

To estimate the effect of exposures on uveal melanoma risk, we will use conditional logistic regression that accounts for the matching factors and allows to control for potential confounding.