A methodology to assess the population size and estimate the needed resources for new licensed medications by combining clinical and administrative databases: The example of glycated haemoglobin in type 2 diabetes

To retrieve values of albuminuria to define the size of CKD patients eligible to SGLT-2Is: An explorative analysis using a primary care database

PURPOSE

To address missingness of albuminuria values, which establish the eligibility to SGLT-2Is for patients with CKD, using the multiple imputation (MI) method.

METHODS

We selected patients aged 18 or older and diagnosed with CKD in a primary care database. Those with severe CKD and/or previously treated with SGLT-2Is were excluded. Then, we collected all available information on albuminuria within 90 days the measure of GFR. A value of albumin-creatinine ratio (ACR) ranging 200-5000 mg/g or otherwise was the response variable on which we ran MI. Using logistic regression, odds ratios (OR) and related 95% confidence intervals (CI) were estimated for each covariate toward the response variable for both full and imputed dataset.

RESULTS

The determinants showed consistent estimates between the full and imputed datasets as demonstrated by the overlaps of the CIs and the similar point estimates. As expected, there were some exceptions, such as diabetes (OR of 1.2 vs. 0.5) and use of diabetic medications (OR of 1.0 vs. 2.1) and/or statins (OR of 1.1 vs. 1.8).

CONCLUSIONS

Besides being a reminder for GPs to prescribe and register albuminuria in certain patients' categories, these determinants might be translated into an operational algorithm to input ACR values in administrative data sources. Scenarios for the reimbursement criteria regulating SGLT-2Is to treat CKD would be therefore simulated on more inferable estimates.