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Obesity/Overweight | Current Treatment | Detailed, Expanded Analysis (US): Treatment Algorithms: Claims Data Analysis

Obesity/Overweight | Current Treatment | Detailed, Expanded Analysis (US): Treatment Algorithms: Claims Data Analysis

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Obesity is a significant public health concern in the United States. The body of evidence highlighting the physical and economic impact of obesity on society is growing steadily. The most frequently used first-line therapy remains generic phentermine, a drug that has been on the U.S. market for decades. However, since 2012, a number of novel branded drugs have entered the market. Approved agents include Novo Nordisk’s Saxenda (liraglutide), Vivus’ Qsymia (phentermine/topiramate), Eisai’s Belviq (lorcaserin), and Nalpropion Pharmaceuticals’ Contrave (naltrexone/bupropion). This report provides important insights into how prescription weight-loss agents are being incorporated into the treatment paradigm for obesity and how the practice is evolving.


  • What patient shares do key therapies and brands garner by line of therapy in newly diagnosed obese/overweight patients? What are the quarterly trends in prescribing among recently treated and newly diagnosed patients?
  • How has Saxenda been integrated into the treatment algorithm, and what is its source of business?
  • What percentage of obese/overweight patients receive drug therapy within one year of diagnosis, and how quickly do they receive it? What percentage of patients progress to later lines of therapy within one year of diagnosis?
  • What percentage of obese/overweight patients are treated with monotherapy versus combination therapy? What are the most common combinations?
  • What are the product-level compliance and persistency rates among drug-treated patients?


United States


Longitudinal patient-level claims data analysis


Saxenda, Qsymia, Belviq, Contrave, Xenical, phentermine


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 flowchart


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.

Table of contents

  • Detailed, Expanded Analysis (US): Treatment Algorithms: Claims Data Analysis
    • Obesity - Treatment Algorithms - Claims Data Analysis - US - May 2019

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  • Pub Date: April 2019
  • 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, ;

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