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Abstract: PO0498

Healthcare Resource Utilisation and Costs of CKD According to the 2012 KDIGO CKD Classification: A Report from the DISCOVER CKD Retrospective Cohort

Session Information

Category: CKD (Non-Dialysis)

  • 2101 CKD (Non-Dialysis): Epidemiology, Risk Factors, and Prevention

Authors

  • Garcia Sanchez, Juan Jose, AstraZeneca, Cambridge, United Kingdom
  • Carrero, Juan Jesus, Karolinska Institutet, Stockholm, Stockholm, Sweden
  • Kumar, Supriya R., AstraZeneca, Gaithersburg, Maryland, United States
  • L Heerspink, Hiddo Jan, Rijksuniversiteit Groningen, Groningen, Groningen, Netherlands
  • James, Glen, AstraZeneca, Cambridge, United Kingdom
  • Nolan, Stephen, AstraZeneca, Cambridge, United Kingdom
  • Carolyn, Lam Su ping, National Heart Centre Singapore, Singapore, Singapore
  • Chen, Hungta (tony), AstraZeneca, Gaithersburg, Maryland, United States
  • Abdul Sultan, Alyshah, AstraZeneca, Cambridge, United Kingdom
  • Pollock, Carol A., Royal North Shore Hospital, St Leonards, New South Wales, Australia
  • Pecoits-Filho, Roberto, Pontificia Universidade Catolica do Parana Escola de Medicina Campus Londrina, Londrina, PR, Brazil
Background

The DAPA-CKD trial finished early due to overwhelming efficacy. Real-world data reporting healthcare resource utilization (HCRU) and cost associated with CKD categorized according to the 2012 KDIGO recommendations are scarce. We assessed HCRU and costs in a “DAPA-CKD-like population” (eGFR 25-75ml/min/1.73m2 and UACR 200-5000mg/g) compared to patients categorized according to KDIGO 2012 recommendations.

Methods

DISCOVER CKD is an observational study in patients with CKD, data was extracted using the integrated Limited Claims and Electronic Health Record data. Patients were aged ≥18 years, with ≥1 UACR measure and two eGFR measures of 0-75ml/min/1.73m2 recorded at least 90 days apart between January 2008 and September 2018. Index date was 2nd eGFR. We calculated total and annualized number of encounters and estimated annualized per-patient and total costs. Incidence rates per 100 person-years (PY) were estimated for outpatient and hospitalization events.

Results

Preliminarily, 6270 patients met the KDIGO 2012 definition (mean[SD] age 64.0(10.9) years, 51.0% female) and 383 patients met the DAPA-CKD-like criteria (mean[SD] age 64.0(11.9) years, 38.9% female). The rate of hospitalizations almost doubled for the DAPA-CKD-like population vs the KDIGO 2012 defined population (Rate 100-PY[95CI] 59.0[53.7-64.8] vs 26.4[25.5-27.3]) and length of stay was also higher (Mean[SD] 6.5[9.4] vs 5.4[6.6] days). The DAPA-CKD-like population incurred substantially higher annualized per patient hospitalization costs (mean[SD] USD39782[78572] vs USD25717[60019]); Figure 1.

Conclusion

This analysis demonstrated that the DAPA-CKD-like population is associated with a higher HCRU and cost burden. These results highlight the need for innovative therapies to improve patient outcomes in this population.

Funding

  • Commercial Support –