2017 Corrona Advisory Roundtable

2017 Corrona Advisory Roundtable

Friday, December 8th, 2017

2017 Corrona Advisory Roundtable

THE NEW YORK ATHLETIC CLUB
180 Central Park South, New York, NY 10019
December 8th, 2017
8:15 am – 5:15 pm

Generating the Evidence that Payers, PBMs, Caregivers, and Patients Need in Major Autoimmune Diseases: Implications for the Pharmaceutical Industry

With the proliferation and approval of additional biologic and targeted therapies in autoimmune diseases, clinicians, payers, and patients are faced with a dizzying array of therapeutic options. For rational decision-making, it is apparent that head-to-head studies of biologic therapies are ideal and the ‘gold standard’ for evidence-based decision-making.


Autoimmune diseases pose significant challenges to health care and no one entity will solve these alone. The answer lies not just in new clinical advances, but in expanding our collective capability to enhance patient treatment and outcomes through data analytics and evidence-based medicine. Health care has only begun to scratch the surface of the true potential of data analytics. Our discussions must ultimately address solving the barriers to an evidence-based approach.

—Roy A. Beveridge, MD, Senior Vice President & Chief Medical Officer, Humana

However, there is an emerging gap in the evidence generated from RCTs. For example, the majority of clinical trials do not compare biologic drugs against one another, but rather versus either a placebo or single active comparator. Further, many RCTs show similar outcomes across different therapeutic options for autoimmune diseases. For instance, in the treatment of RA we frequently see the same “60-40-20” response rates across ACR 20, 50 and 70 outcomes respectively with all interventions. This situation begs the question of whether we are using the right data sources, and the right measures to capture meaningful differences.

We believe that more attention needs to be:

  • focused on assessing the potential for real world outcomes data to help distinguish meaningful differences that are not readily apparent in randomized controlled trials
  • acknowledging the data gaps and how should they be filled
  • assessing how real world outcomes data can complement data gathered from RCTs