Personalized Medicine’s Effect on Oncologists’ Treatment Regimens

Report Overview

One aspect of personalized medicine is certain; it is complicated. If you happen to have a highly scientific background, you actually may be able to define the term. However, if you polled five people very familiar with personalized medicine, you should expect to hear five different definitions.

ISR wanted to understand where oncologists stand on the topic of personalized medicine. We interviewed 101 US-based, board-certified oncologists to gather their views on how familiar they are with personalized medicine, how they are treating patients, what tests are being used and which will be used more, and how their patient treatment regimens could evolve in the future.

What you will learn:

• Oncologists’ familiarity with personalized medicine, and perceptions related to hype vs. tangible benefit
• Future predictions for the use and benefits related to personalized medicine in oncology, including potential hurdles to adoption
• Percentage of patients requesting personalized medicine vs. percentage of oncologists suggesting personalized medicine to patients
• Current number of patients treated using genetic tumor profiling vs. oncologists’ predictions for the number in 3 years
• Oncologists’ interest in conducting clinical trials using genetic tumor profiling
• What tests oncologists perform, and how the data are used and stored for use in future clinical trials

Report Contents:

1. Current Landscape

• Oncologist familiarity with personalized medicine
• Current perceptions of hype vs. benefit
• Future perceptions of hype vs. benefit
• Willingness of payers to pay for panel tests

2. Genetic Tests and Patient Care

• Prevalence of patients asking for personalized treatments
• Asking patients about completing a genetic profile
• Hurdles preventing widespread use of personalized medicine
• Predictions for the biggest treatment advancements in five years

3. Clinical Trial Views

• Genetic tumor profiling and clinical trial interest
• Using genetic data to match patients for clinical trials
• Trial protocol: Broad vs. Sub-set indication