MEDICAL DIAGNOSTIC DECISION RULES BASED ON MUTUALLY DEPENDENT DIAGNOSTIC FACTORS

There are numerous situations in which clinicians are not free to choo se informative and independent factors (tests) in the solution of thei r diagnostic or prognostic problems. It is vital to use a combination of several mutually dependent factors in such cases. The paper develop s a Bayesian approach to the creation of diagnostic and prognostic rul es based on mutually dependent factors. Following the work of Philosop hov (Philosophov, Medical Decision Making, 15, 264-275, 1995), we dist inguish between true factor values and factor estimates-the result of factor measurement by means of an imperfect medical instrument (techno logy). A constructive solution of the problem is achieved by introduci ng the concept of clinical variants of a disease-a set of possible for ms of disease, each of which is described by a specific combination of prognostic and other relevant factors. The appropriate use of mutuall y dependent factors can yield gains in decision efficiency, even in th e simplest case of two binary factors. The gain achieved can increase with the number of factors used and variety of factor values. An examp le based on real clinical material illustrates the approach and the ga ins it can achieve. (C) 1997 Elsevier Science Ltd.