Abstract Background and Aims Estimating prevalence and incidence of chronic kidney disease (CKD) based on claims data often underlies bias and limitations due to uncertainty of diagnostic validity. We investigated CKD prevalence and incidence over time using data from a community-dwelling cohort of individuals aged 70+ linked to individual claims data. We assessed the diagnostic validity of the claims-based compared with the eGFR-based CKD definition. Method We assessed CKD prevalence and incidence in two data sources: 1) eGFR values of participants aged 70+ (n = 2,069) of the Berlin Initiative Study (BIS), including five biennial study visits from 2009-2019, and 2) claims data of BIS participants matched on person-level. Using eGFR, we defined CKD prevalence as eGFR <60 ml/min/1.73m² calculated with the creatinine-based CKD-EPI (2009) equation. For each study visit, prevalent CKD cases were considered as incident if eGFR was ≥60 ml/min/1.73m² in the respective previous study visit. In claims data, in- and outpatient ICD-10 diagnoses (N18.3, N18.4, N18.5, N18.8, N18.9, N19) in the year preceding and/or following the study visit date were used to determine CKD prevalence. Incidence was defined as prevalent cases without a diagnosis in the year preceding the first CKD diagnosis. The denominator for incidence was defined as all persons at risk, i.e., who were not prevalent in a respective previous study visit and still under observation. We assessed the diagnostic validity of claims-based CKD prevalence and incidence using eGFR data as a reference. Analyses were stratified by sex. Results Between 2009 and 2019, CKD prevalence increased from 0.42 to 0.51 based on eGFR and from 0.30 to 0.43 based on claims data. Incidence varied between 0.16–0.22 using eGFR and 0.07–0.13 using BIS claims data. There was no clear time trend for incidence in any data source. Diagnostic validity of claims-based CKD prevalence and incidence detection is displayed in Table 1. Sensitivity for prevalence increased while other indicators remained stable over time. Detection of incident cases showed lower sensitivity (0.18–0.30 vs. 0.58–0.70) and PPVs (0.40–0.60 vs. 0.79–0.83) compared to prevalence, respectively. Prevalence and incidence based on claims data were slightly higher in males compared to females (Figure 1). Conclusion Using the eGFR-based or claims-based definition of CKD we found an increase in prevalence between 2009 and 2019. This might be due to the introduction of the KDIGO guidelines in 2012. During the same time, CKD incidence rates were stable. Comparing the claims-based with eGFR-based CKD definition, we found a sensitivity of 0.58-0.70 for prevalence and 0.18-0.30 for incidence, indicating that there is a risk of underdetection of CKD when using solely claims data, in particular for incident cases.