Glaucoma | Treatment Algorithms: Claims Data Analysis | US | 2019

Drug treatment of glaucoma focuses on reducing / controlling IOP and preserving visual function. Given the availability of therapies from several drug classes (e.g., PGAs, beta blockers, FDCs), multiple factors (e.g., efficacy, safety / tolerability, patient convenience and compliance, cost) determine the treatment approach. Even with multiple generic therapies available, branded therapies (e.g., Allergan’s Lumigan and Combigan, Novartis’s Travatan Z) still play an important role in glaucoma treatment. Given the continued use of branded therapies and the entry of new agents to the market (e.g., Bausch + Lomb’s Vyzulta, Aerie Pharmaceuticals’ Rhopressa), it is essential to understand physicians’ actual prescribing behavior for glaucoma.

QUESTIONS ANSWERED

• What percentage of glaucoma 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 patient share do key therapies, including newer-to-market agents Vyzulta and Rhopressa, garner by line of therapy in newly diagnosed glaucoma patients?
• What key drug classes and brands compete for share among recently treated patients? What are the quarterly trends in prescribing for these patients?
• What percentage of glaucoma 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 with glaucoma?

CONTENT HIGHLIGHTS

Geography: United States

Real-world data: Longitudinal patient-level claims data analysis

Key drugs covered: Lumigan, Travatan Z, Combigan, Cosopt PF, Simbrinza, Alphagan P, Azopt, Vyzulta, Rhopressa, latanoprost, timolol maleate

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.

PRODUCT DESCRIPTION

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.