Hyperaldosteronism is characterized by the excessive release of aldosterone hormone into the blood and the resulting rise in blood pressure. This disorder is a common cause of secondary hypertension, and often patients are initially misdiagnosed as hypertensive. The cause of hyperaldosteronism is the key factor for determining the treatment approach. Surgical treatment is an option for primary hyperaldosteronism. Where surgical excision is not appropriate or needs to be supplemented, pharmacotherapy is indicated and a polypharmacy treatment approach is frequently adopted. Numerous drug treatments are available, including aldosterone antagonists, renin-angiotensin-aldosterone system (RAAS) inhibitors, calcium channel blockers, and beta blockers. The hyperaldosteronism Treatment Algorithm provides insights into prescribing patterns among many treatment options.
- What patient shares do key therapy drug classes garner by line of therapy in newly diagnosed hyperaldosteronism patients? What are the quarterly trends in prescribing among recentlytreated and newly diagnosed hyperaldosteronism patients?
- How are aldosterone antagonists integrated into the treatment algorithm?
- What proportion of hyperaldosteronism patients receive drug therapy within one year of diagnosis, and how quickly? What percentage of patients progress to later lines of therapy within one year of diagnosis?
- What percentage of hyperaldosteronism patients are treated with monotherapy versus combination therapy? What are the most widely used combination therapies?
- What are the compliance and persistency rates among drug-treated patients with hyperaldosteronism?
Treatment Algorithms: Claims Data Analysis provides detailed analysis of brand usage across different lines of therapy using real-world, patient-level claims data, so you can accurately assess your source of business and quantify areas of opportunity for increasing your brand share.
Key drugs: angiotensin-converting enzyme inhibitors, aldosterone antagonists, angiotensin II receptor blockers, adrenergic receptor blockers, calcium channel blockers, diuretics, direct renin inhibitors, corticosteroids.
Key analysis provided:
- Brand 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 flow charts.
- Detailed, Expanded Analysis: Hyperaldosteronism: Treatment Algorithms: Claims Data Analysis (US)
- Treatment Algorithms - Claims Data Analysis - Hyperaldosteronism - PPT [August 2018]
Author(s): Rameshwar Prajapati, Ph.D., M.S. (Pharm.)
Rameshwar Prajapati, (Pharm.), is an Associate Analyst in Decision Resources Group’s cardiovascular, metabolic, renal, and hematologic disorders team, focusing primarily on metabolic and renal diseases. In this role, his main function is to perform primary and secondary research across the team’s range of therapeutic indications and provide insights and assessments for related pharmaceutical ; Rameshwar holds a bachelor’s degree in pharmacy from Dr. Gour University, Sagar, India. He obtained his master’s and doctorate degree in pharmacoinformatics from the National Institute of Pharmaceutical Education and Research, Nagar, India. Rameshwar also received a German Academic Exchange Service (DAAD) fellowship to conduct his research on P-glycoprotein at the University of Bonn, ;