1. What’s Beyond Poolability: Exchangability
Roseann White, MA
Director Pragmatic Clinical Trial Statistics
Duke Clinical Research Institute

2. Acknowledgements Dawn Bardot, VP Tecnologies, MDIC
Dan Schwartz, PM, MDIC
Tarek Haddad, Ph.D., Director, MDT

3. Disclosure Statement of Financial Interest
Within the past 12 months, I or my spouse/partner have had a financial interest/arrangement or affiliation with the organization(s) listed below.
Affiliation/Financial Relationship
Company
Employee
Consulting Fees/Honoraria
Other Financial Benefit
Duke Clinical Research Institute
Claret
Abbott, Abbvie

4. “Um,” my son muttered sheepishly, “I’d rather have the real ones.”
My 8th-grade–bound son has long coveted classic Converse low-tops. Last week, we found a pair of lookalikes on sale for $15.
“Um,” my son muttered sheepishly, “I’d rather have the real ones.”
“.. they look … exactly the same.”
“Not exactly,” he explained. “These” [referring to the Converse low-tops], “have a label.”
From the Santa Barbara Independent newspaper, July 21, 2011 by Starshine Roshell

5. Exchangability: outcomes from persons from two sources can be explained by deterministic characteristics and random error
UNC and Duke University Basketball Teams are exchangeable
2015 UNC won 33 out of 40 games, i.e. 85%
2015 Duke University won 25 out of 36 games, i.e. 70%

6. What do we want to look at to assess exchangeability
Trial Design: inclusion/exclusion criteria, primary endpoint, ……..
Geography
Device
Definitions of the outcomes, key baseline characteristics,…….
Quality of the Data: monitoring level , adjudication, …….
Follow-up: same schedule of follow-up visits, same kind of follow-up visits, …….
Your statistician can assist
but the clinician/clinical trial
scientist is the final
judge of exchangability

7. Completely Exchangeable  Completely Separate

8. Comparing Historical Data to your Current Data
100%
Completely Exchangeable (poolable): any differences between in outcomes between the can be adjusted for by deterministic characteristics
Partial/Conditional: average outcomes for persons from historical and current data, after adjusting for deterministic characteristics, arise from a common distribution
Completely Separate: we ignore the historical information except in how it might help us understand designing a study from “scratch” 0%

9. Why do we want to know exchangability?
Historical
Historical
Historical
Current
Current
Current

10. To determine the discount function one needs to balance:
Creating the Discount Function: Collaborative Effort between Statistician and Clinical Scientist
To determine the discount function one needs to balance:
Type I error: False Hope
Type II error: Missed opportunity
Bias: Smallest clinical meaningful shift in outcomes

11. “Past is prologue”
William Shakepeare
(a literary Bayesian)