Adjust for age and Charlson Comorbidity Index in a regression model

[abo7aneen]

Dear Professor and colleagues,

I have a logistic regression model and want to adjust for age, sex, and the Charlson comorbidities index (acknowledging its shortcomings) as indicators of comorbidities. However, one component of CCI is age. I am concerned about collinearity (adjusting age while it is one component of CCI). Should I drop the age from the model?

Thank you

[James_Stanley]

Frank has commented on issues with Charlson elsewhere (see links below, it sounds like you’ve already read these). There are certainly better options, and they tend to draw on the same data sources so there isn’t necessarily much overhead in applying a more modern variant.

To address your question specifically, inclusion of age as a weight component in the Charlson index score is going to be blunt. When we have worked in this space, we purposefully did not include age when developing those indices (edit for clarification: we did adjust for age when developing the condition-specific weightings for the indices, but it was not a weighted component of the index score), instead allowing analysts to separately include age as a separate predictor in the analytical models. This means that one can use these morbidity indices while allowing for better separate control of confounding by age – for example, accounting for age using restricted cubic splines in the modelling, as well as including your other (co)morbidity index using such splines.

I think that if one were constrained to use a (co)morbidity index that included age as a weighted component of a total score, then you could still include age as a separate adjustment variable. I don’t think there would be problematic collinearity, since the morbidity index will most likely be driven mostly by other components, and I would expect better adjustment for confounding by including age adjustment in a suitable functional form (again, because age as included in a weighted score would not be able to capture any nuanced relationship of age to outcome ). I’d be interested in hearing others thoughts on this.

A couple of links below on issues with Charlson for other readers:

Charlson Comorbidity Index or Something Better?

I am doing a study on comparing the healthcare utilization of two types of epilepsy patients. I’m using Cox Proportional Hazard models and I’d like to include comorbidity in the covariates. I’ve seen other papers similar to our study use Charlson Comorbidity Index, but I’ve read that Elixhauser’s is better. I assume there are other useful indices out there as well. My dataset already has the comorbidities used in the Charlson Comorbidity Index. However, we have access to the patient data if …

Comorbidity adjustment in regression: score versus individual components

Comorbidity scores (such as Charlson and Elixhauser) are widely used to adjust for the patients’ comorbidities in observational studies. They’re usually based on regressing the outcome on several, often dozens of comorbidities on a large historical cohort and then publishing the coefficients in some form. I think many aspects can be questioned about using such scores, but now lets focus on one single issue: if the components of the score are available individually in our study (i.e. we have the…

[f2harrell]

I really like the strategy you use, and the thought that even though it’s not optimal to include age inside a comorbidity index there is little harm in using an index that does include it while also adjusting for age separately (hopefully nonlinearly).

[abo7aneen]

Thank you for your help and support