Dose-Response Mixed Models for Repeated Measures – a New Method for Assessment of Dose-Response

• Published in: Pharmaceutical research Vol. 37; no. 8; p. 157
• Main Authors: Wellhagen, Gustaf J., Hamrén, Bengt, Kjellsson, Maria C., Åstrand, Magnus
• Format: Journal Article
• Language: English
• Published: New York Springer US 01.08.2020; Springer; Springer Nature B.V
• Subjects: Albumin; Albumins - metabolism; Analysis; Bias; Biochemistry; Biomarkers; Biomarkers - metabolism; Biomedical and Life Sciences; Biomedical Engineering and Bioengineering; Biomedicine; chronic kidney disease (CKD); Chronic kidney failure; Clinical trials; Computer Simulation; Creatinine; Creatinine - metabolism; Dapagliflozin; Data Interpretation, Statistical; dose-response analysis; dose-response mixed models for repeated measures (DR-MMRM); Dose-Response Relationship, Drug; Drug development; Drug dosages; Humans; Information processing; Kidney diseases; Medical Law; Methods; Mixed models for repeated measures (MMRM); Models, Statistical; Pharmacology/Toxicology; Pharmacy; Proteinuria; Renal Insufficiency, Chronic - drug therapy; Research Paper; Time Factors; Treatment Outcome; Type 2 diabetes; urinary albumin-to-creatinine ratio (UACR); Within-subjects design; dose-response analysis; Mixed models for repeated measures (MMRM); dose-response mixed models for repeated measures (DR-MMRM); chronic kidney disease (CKD); urinary albumin-to-creatinine ratio (UACR)
• ISSN: 0724-8741; 1573-904X; 1573-904X
• DOI: 10.1007/s11095-020-02882-0

Purpose In this paper we investigated a new method for dose-response analysis of longitudinal data in terms of precision and accuracy using simulations. Methods The new method, called Dose-Response Mixed Models for Repeated Measures (DR-MMRM), combines conventional Mixed Models for Repeated Measures (MMRM) and dose-response modeling. Conventional MMRM can be applied for highly variable repeated measure data and is a way to estimate the drug effect at each visit and dose, however without any assumptions regarding the dose-response shape. Dose-response modeling, on the other hand, utilizes information across dose arms and describes the drug effect as a function of dose. Drug development in chronic kidney disease (CKD) is complicated by many factors, primarily by the slow progression of the disease and lack of predictive biomarkers. Recently, new approaches and biomarkers are being explored to improve efficiency in CKD drug development. Proteinuria, i.e. urinary albumin-to-creatinine ratio (UACR) is increasingly used in dose finding trials in patients with CKD. We use proteinuria to illustrate the benefits of DR-MMRM. Results The DR-MMRM had higher precision than conventional MMRM and less bias than a dose-response model on UACR change from baseline to end-of-study (DR-EOS). Conclusions DR-MMRM is a promising method for dose-response analysis.