ninary logistic regression - poor models

[dfva]

Hi all!

I am fairly novice in SPSS binary regression. I would like to carry out an
analysis on the following topic:
- I want to predict a medical event (this is the heart failure)
I have the following predictors: age, gender, the existence of 12 different
diseases for each patient (e.g diabetes mellitus) and cumulative doses for
42 drugs - so each patient can I describe with 58 variables. The existence
variables have 'yes' and 'no' values, the cumulative drugs are variables
with continuous values.

I know that age has effect on the dependent variable, and probably some
other variables has also affect on the dependent variable, but it is
unknown.

I would like to determine the effect of each variable.

I tried to put all variables in the covariates box, but it gave me very poor
model.
Then I tried it in 3 step: in the first step age and gender, and in the
second step the diseases, and in the third step the drugs. It resulted in
very poor model as well.
Then I though I will test only one drog, and I put in the first step age and
gender, and in the second step only one drug. The model was again very poor.
In all cases Rˇ2 values are under 0,1.  

In my sample the occurrence is only 10,1 percent.
If I make ROC analysis it shows very bad curve - fast straight across.

Could somebody help me, how can I solve this problem? Is binary logistic
regression a good method for this problem? Even if the model is very poor???
Can I evaluate the p values for poor models or not???

Thank you!
Agnes



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