A LOGISTIC-REGRESSION MODEL WHEN SOME EVENTS PRECEDE TREATMENT - THE EFFECT OF THROMBOLYTIC THERAPY FOR ACUTE MYOCARDIAL-INFARCTION ON THE RISK OF CARDIAC-ARREST

When outcomes occur in clinical trials before treatment can be given, neither intent-to-treat nor according-to-protocol analyses give optima l estimates of the treatment effect. A better approach employs a time- dependent variable for treatment. Intent to-treat analyses are conserv ative, biasing against treatment; according-to-protocol analyses bias in favor of treatment. Wie show how to measure the effect of a time-de pendent variable in a logistic regression using person-time intervals as units of measurement and describe appropriate methods for reporting model performance. The method is applied to develop a model to predic t the probability that a patient with a myocardial infarction will hav e a sudden cardiac arrest within 48 hours of presentation to emergency medical services both when treated with thrombolysis and when not tre ated. We use a time-dependent treatment variable because many patients went into cardiac arrest while awaiting treatment. This technique has been programmed into an electrocardiograph for real-time use in an em ergency department. (C) 1997 Elsevier Science Inc.