1. The Cardiovascular Literature-Based Risk Algorithm (CALIBRA): Predicting Cardiovascular Events in Patients With Non-Dialysis Dependent Chronic Kidney Disease.
- Author
-
Neri L, Lonati C, Titapiccolo JI, Nadal J, Meiselbach H, Schmid M, Baerthlein B, Tschulena U, Schneider MP, Schultheiss UT, Barbieri C, Moore C, Steppan S, Eckardt KU, Stuard S, and Bellocchio F
- Abstract
Background and Objectives: Cardiovascular (CV) disease is the main cause of morbidity and mortality in patients suffering from chronic kidney disease (CKD). Although it is widely recognized that CV risk assessment represents an essential prerequisite for clinical management, existing prognostic models appear not to be entirely adequate for CKD patients. We derived a literature-based, naïve-bayes model predicting the yearly risk of CV hospitalizations among patients suffering from CKD, referred as the CArdiovascular, LIterature-Based, Risk Algorithm (CALIBRA)., Methods: CALIBRA incorporates 31 variables including traditional and CKD-specific risk factors. It was validated in two independent CKD populations: the FMC NephroCare cohort (European Clinical Database, EuCliD
® ) and the German Chronic Kidney Disease (GCKD) study prospective cohort. CALIBRA performance was evaluated by c-statistics and calibration charts. In addition, CALIBRA discrimination was compared with that of three validated tools currently used for CV prediction in CKD, namely the Framingham Heart Study (FHS) risk score, the atherosclerotic cardiovascular disease risk score (ASCVD), and the Individual Data Analysis of Antihypertensive Intervention Trials (INDANA) calculator. Superiority was defined as a ΔAUC>0.05., Results: CALIBRA showed good discrimination in both the EuCliD® medical registry (AUC 0.79, 95%CI 0.76-0.81) and the GCKD cohort (AUC 0.73, 95%CI 0.70-0.76). CALIBRA demonstrated improved accuracy compared to the benchmark models in EuCliD® (FHS: ΔAUC=-0.22, p<0.001; ASCVD: ΔAUC=-0.17, p<0.001; INDANA: ΔAUC=-0.14, p<0.001) and GCKD (FHS: ΔAUC=-0.16, p<0.001; ASCVD: ΔAUC=-0.12, p<0.001; INDANA: ΔAUC=-0.04, p<0.001) populations. Accuracy of the CALIBRA score was stable also for patients showing missing variables., Conclusion: CALIBRA provides accurate and robust stratification of CKD patients according to CV risk and allows score calculations with improved accuracy compared to established CV risk scores also in real-world clinical cohorts with considerable missingness rates. Our results support the generalizability of CALIBRA across different CKD populations and clinical settings., Competing Interests: LN, JT, FB, SoS, StS, CM, CB, and UT are full time employees at Fresenius Medical Care. CL provided medical writing services on behalf of Fresenius Medical Care. HM reports grants from KfH Foundation of Preventive Medicine, and grants from German ministry of Education and Research. MatS reports grants from Fresenius Medical Care during the conduct of the study. BB reports grants from the Federal Ministry of Education and Research (Bundesministerium für Bildung und Forschung (www.bmbf.de), FKZ 01ER 0804, 01ER 0818, 01ER 0819, 01ER 0820 und 01ER 0821), and grants from Foundation for Preventive Medicine of the KfH (Kuratorium für Heimdialyse und Nierentransplantation e.V.–Stiftung Präventivmedizin; www.kfh-stiftung-praeventivmedizin.de). MarS reports grants from Fresenius Medical Care outside the submitted work. K-UE reports grants from: Astra Zeneca, Bayer, Fresenius Medical Care, Vifor, and Amgen during the conduct of the study, personal fees from Akebia, Astellas, Astra Zeneca, Bayer, and Boehringer Ingelheim, and grants from Genzyme, Shire, and Vifor outside the submitted work. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2022 Neri, Lonati, Titapiccolo, Nadal, Meiselbach, Schmid, Baerthlein, Tschulena, Schneider, Schultheiss, Barbieri, Moore, Steppan, Eckardt, Stuard and Bellocchio.)- Published
- 2022
- Full Text
- View/download PDF