Comparing two screening methods for albuminuria in the general population

The Thomas study (Towards HOMe-based Albuminuria Screening): A prospective, randomized study investigating two strategies for early detection and treatment of chronic kidney disease

Presented at ERA congress in Paris, France by Ronald Gansevoort (Groningen, The Netherlands)

Introduction and methods

Background

Chronic kidney disease (CDK) is often detected late, when eGFR is already impaired, resulting in a late start of preventive treatment. Early stage of CKD are defined by albuminuria, which is the strongest risk factor for CKD progression.

Aim of the study

To investigate the value of screening the general population for albuminuria to early identify people with CKD.

Methods

The study consisted of 3 phases: home-based screening, elaborate screening and implementation of care. In the home-based, phase 1, 15.072 individuals from the general population of 45-80 years were invited to participate in the study. They were randomized to the classical method of screening (using a urine collection tube) or to an e-Health method (App- and dipstick-based). If albuminuria test was positive (ACR>3 mg/mmoL), subjects were asked to do a confirmation test. If albuminuria was confirmed, subjects were invited for an elaborate screening visit at the central screening facility to measure traditional risk factor for CKD and CVD. In case of abnormalities, subjects were referred to a GP for treatment.

Study endpoints

Endpoints of the study were participation rate, yield to detect high albuminuria and risk factors for renal and CVD progression, and Implementation of care

Main results

• Participation rate was 59% for the classical method and 44% for the eHealth method.
• In the classical method group, 5.3% of subjects had a first positive test and 3.3% confirmed high albuminuria. In the e-Health method group, the first test was positive in 13.3% of subjects and 5.1% had confirmed high albuminuria.
• At the elaborate screening with a gold standard method for albuminuria testing, albuminuria was confirmed in 91% of subjects in the classical method group, and only in 37% in the e-Health app group. The e-Health app method had a good sensitivity of 98.1%, but a low specificity of 67.9%, which is too low to be used for population screening.
• When looking at traditional risk factors at elaborate screening of subjects with albuminuria, 62% in the classical method group were newly diagnosed with albuminuria, and 38% had known albuminuria. Also in this group, they were new diagnoses of lower eGFR (22%), high blood pressure (35%), high cholesterol (25%) and type 2 diabetes (20%).
• 90% of subjects with elevated albuminuria had risk factors and was referred to their GP (49% with newly diagnosed risk factors and 55% with known risk factors).
• Of the referred patients, 57% of subjects actually visited their GP.

Conclusions

For the classical method, participation rate was high, the yield of finding subjects with elevated albuminuria and new or poorly controlled CKD and CV risk factors was good, and implementation of care was acceptable, but there is room for improvement. For the e-Health method, participation rate was relatively lower and false positive rate was too high.

Gansevoort ended his presentation by saying that screening the general population for albuminuria should be considered, and that confirmation in controlled studies showing efficacy of screening vs. no screening on hard endpoints (like CV events) is needed. He shared the news that they received funding to perform such a trial in the Netherlands.

- Our reporting is based on the information provided at the ERA congress 2022 -