Abstract: FR-PO1140
Variation in the Number Needed to Screen for Undiagnosed CKD: Implications for Targeted Screening Strategies
Session Information
- CKD: Screening, Diagnosis, Serum and Urine Biomarkers, and Scoring Indices
November 07, 2025 | Location: Exhibit Hall, Convention Center
Abstract Time: 10:00 AM - 12:00 PM
Category: CKD (Non-Dialysis)
- 2301 CKD (Non-Dialysis): Epidemiology, Risk Factors, and Prevention
Authors
- Lee, Lydia Yejin, Boehringer Ingelheim Pharmaceuticals Inc, Ridgefield, Connecticut, United States
- Bowie, Alexa C, Broadstreet HEOR, Vancouver, British Columbia, Canada
- Szabo, Shelagh, Broadstreet HEOR, Vancouver, British Columbia, Canada
- Sun, Rosie, Broadstreet HEOR, Vancouver, British Columbia, Canada
- Bengtson, Lindsay GS, Boehringer Ingelheim Pharmaceuticals Inc, Ridgefield, Connecticut, United States
Background
Undiagnosed chronic kidney disease (CKD) is highly prevalent, with up to 90% of affected individuals remaining undiagnosed. This study aimed to estimate the number needed to screen (NNS) to identify one case of undiagnosed CKD based on risk factors.
Methods
US adults with ≥1 eGFR or SCr (G-stage) finding from 01OCT2016 to 01JUL2023 were identified in Optum® Market Clarity™. Those with polycystic kidney disease, renal dialysis or transplant were excluded. Individuals were classified as ‘diagnosed CKD’, ‘indeterminate’, ‘undiagnosed CKD’ and ‘no CKD’ by lab (eGFR and uACR) and diagnosis using a validated CKD algorithm; analyses focused on the undiagnosed (lab evidence of CKD but no diagnosis) and no CKD (no lab evidence or diagnosis). Index was defined as the most recent G-stage finding. Sociodemographic and clinical covariates were ascertained 1 year prior to index. Associations between covariates and undiagnosed CKD were assessed using logistic regression. NNS was estimated as the reciprocal of the absolute risk reduction between the proportion with undiagnosed and no CKD among covariate combinations.
Results
Individuals with undiagnosed CKD (n = 126,355) and no CKD (n = 281,712) were included. Covariates strongly associated with undiagnosed CKD included past acute kidney injury (AKI), dyslipidemia, hypertension (HTN), type 2 diabetes mellitus (T2DM), heart failure (HF), and atrial fibrillation (AF). Estimated NNS was lowest for dyslipidemia (NNS = 3) and HTN (NNS = 3); suggesting targeted screening in these populations may identify up to 87% of undiagnosed CKD cases. Estimated NNS for other clinical conditions was higher (T2DM: 7, HF: 21, AF: 12, AKI: 65); 30% of those with undiagnosed CKD had either T2DM or HF.
Conclusion
Based on NNS, individuals with dyslipidemia and HTN represent additional high-risk populations for undiagnosed CKD that would benefit from screening. NNS was lowest for dyslipidemia and HTN, potentially due to pre-existing CKD screening priorities within other high-risk groups such as T2DM and HF. Given the progressive nature of CKD, early identification by risk stratification and targeted screening may enable optimal intervention. Implementing targeted screening strategies in high-risk populations may be a relatively low-cost solution to reduce the burden of CKD.
Funding
- Commercial Support – Boehringer Ingelheim Pharmaceuticals Inc.