Are the measures actually measuring the same thing?

For example, does a score of 0 in Method 1 match a score of 1 in Method 2, and a score of 1 match a score of 12?

If so, you can take exp(beta*12), where beta is the regression coeffieient from your logistic regression for Method 2. That would essentially give you the odds ratio not for a single step increase (1 to 2, 2 to 3, etc.) but the odds ratio for an increase from one end of the scale to the other.

If instead say a 0 in Method 1 is probably closer to a 2 in Method 2, and a score of 1 is more like a 10, then you'd multiply by 10-2 = 8 instead of 12.

That should get you a more comparable interval. There are other methods you can try as well, depending on the distribution of Method 2's scores. This retains much of the information from Method 2 while still providing something approaching a like-with-like comparison.

Are the measures actually measuring the same thing?

For example, does a score of 0 in Method 1 match a score of 1 in Method 2, and a score of 1 match a score of 12?

If so, you can take exp(beta*12), where beta is the regression coefficient from your logistic regression for Method 2. That would essentially give you the odds ratio not for a single step increase (1 to 2, 2 to 3, etc.) but the odds ratio for an increase from one end of the scale to the other.

If instead say a 0 in Method 1 is probably closer to a 2 in Method 2, and a score of 1 is more like a 10, then you'd multiply by 10-2 = 8 instead of 12.

That should get you a more comparable interval. There are other methods you can try as well, depending on the distribution of Method 2's scores. This retains much of the information from Method 2 while still providing something approaching a like-with-like comparison.