Each year in the United States, thousands of patients suffering from end-stage renal disease undergo a kidney transplant. To prevent rejection and maintain the new kidney’s functionality, these patients must remain on immunosuppressive regimens for the duration of their life. However, these powerful agents come with considerable risks on top of their important benefits. This report examines how key immunosuppressive agents are used in induction and maintenance regimens to prevent kidney transplant rejection.
- What patient shares do key therapies and brands garner by line of therapy in the induction and maintenance phases? What are the quarterly trends in prescribing among induction-and maintenance-phase patients?
- How have different immunosuppressive agents been integrated into the treatment algorithm, and what is their source of business?
- What percentage of kidney transplant patients switch to a different therapy after initiation and how quickly?
- What percentage of kidney transplant patients are treated with monotherapy versus combination therapy? What are the most commonly used combinations?
- What are the product-level compliance and persistency rates among drug-treated patients?
Treatment Algorithms: Claims Data Analysis provides detailed, quantitative analysis of the treatment journey and brand usage across lines of therapy and overall using real-world, patient-level claims data so that marketers can accurately assess their source of business, benchmark usage against competitors, and quantify areas of opportunity for their marketed or emerging brand.
GEOGRAPHY: United States
REAL WORLD DATA: Longitudinal patient-level claims data analysis
KEY DRUGS COVERED: Nulojix, Imuran, CellCept, Myfortic, Prograf, Astagraf XL, Envarsus XR, Neoral, Sandimmune, Rapamune, Zortress, Thymoglobulin, Atgam, Simulect
KEY ANALYSIS PROVIDED: Brand/therapy usage across longitudinal patient sample; Newly diagnosed patient analysis; Treatment initiation and progression; Line of therapy analysis; Combination therapy analysis; Source of business for recently treated patients; Persistency and compliance analysis; Product-level patient flowcharts
- Detailed, Expanded Analysis - Treatment Algorithms - Claims Data Analysis (US)
- Treatment Algorithms: Claims Data Analysis | Kidney Transplant | US | March 2020
Author(s): Rohit Bansal, MS (Pharm.)
Rohit joined Decision Resources Group (DRG)’s Cardiovascular, Metabolic, Renal, and Hematologic Disorders team in April 2019. His current focus includes non-alcoholic steatohepatitis (NASH), glomerulonephritis, and renal anemia. Prior to joining DRG, Rohit worked as analyst helping pharmaceutical clients address their business questions across various therapeutic areas. Rohit’s postgraduate research centred on molecular dynamics. His work included computer-aided drug design software that involved studying the effect of pharmaceutical excipients on the reabsorption of drug molecules from cancer cells leading to drug resistance.