I have 5 variables that I've used to calculate a score with. Each variable contributes 0-2 points to the score depending on their value.
I'm interested in whether these predictors better can predict the outcome (disease status) by themselves or if a score of all would predict the outcome better.
The score works very well in a regression model and seems to be able to predict disease status with p=0.003 and a satisfactory confidence interval (CI). The 5 binary variables are also significant but with very large CI. Does this mean that the score has a higher validity than the binary variables on their own?
Also if I run a regression model with all 5 predictors, the R-squared is 0.35 and the model P value is 0.01, with only one of the predictors being significant in the model, though. Is this worth noting in the manuscript? I'm not exactly sure what it means other than that the model itself is good at predicting disease status.