Using missing data methods in genetic studies with missing mutation status

Because of current techniques of determining gene mutation, investigators a re now interested in estimating the odds ratio between genetic status (muta tion, no mutation) and an outcome variable such as disease cell type (A, B) . In this paper we consider the mutation of the RAS genetic family. To dete rmine if the genes have mutated, investigators look at five specific locati ons on the RAS gene. RAS mutated is a mutation in at least one of the five gene locations and RAS non-mutated is no mutation in any of the five locati ons. Owing to limited time and financial resources, one cannot obtain a com plete genetic evaluation of all five locations on the gene for all patients . We propose the use of maximum likelihood (ML) with a 2(6) multinomial dis tribution formed by cross-classifying the binary mutation status at five lo cations by binary disease cell type. This ML method includes all patients r egardless of completeness of data, treats the locations not evaluated as mi ssing data, and uses the EM algorithm to estimate the odds ratio between ge netic mutation status and the disease type. We compare the ML method to com plete case estimates, and a method used by clinical investigators, which ex cludes patients with data on less than five locations who have no mutations on these sites. Copyright (C) 1999 John Wiley & Sons, Ltd.