Title: Charge
1Charge
- Can one apply a Bayesian analysis where the a
priori data comes from an adult patient
population and the new data comes from a
pediatric population? - Dr. S. Hirschfeld, Halloween, 2001
2What Can Bayesian Methods Do For Us?
- FDA ODAC, Pediatric Subcommittee
- November 28, 2001
- Steven Goodman, MD, PhD
- Oncology Biostatistics
- Johns Hopkins University
3What are Bayesian Methods?
- Methods based on Bayes theorem
a.k.a. Bayes factor
4What are Bayesian Methods?
- Approaches that combine information of
different types. - Provide a formal way to make statistical
inferences from a clinical trial, incorporating
prior knowledge. - A calculus of uncertainty.
- A calculus of belief.
- A calculus of evidence.
5In what settings have Bayesian designs/analyses
been used?
- Pharmacokinetics
- Phase I - CRM
- Phase II - Thall/Simon
- Phase III - Spiegelhalter, Parmar, many others
- Meta-analysis
6 of Bayes Articles in Medical Journals
7What Bayesian Methods Cannot Do
- They cannot tell us, in the absence of empirical
or biological information, how alike children
and adults are, and how relevant adult
information is for children.
8The Charge, Redux
- Can one apply a Bayesian analysis where the a
priori data comes from an adult patient
population and the new data comes from a
pediatric population? - Yes, but only if one makes an a priori judgment
about how relevant the information from adults is
for children.
9What information comes from adults?
- Pharmacokinetics
- Pharmacogenomics
- Dose - Toxicity relationship
- Types of toxicity
- Frequency of toxicity / MTD
- Efficacy
- Covariate effects on all of above.
- Uncertainty in all of above.
10What allows extrapolation to children?
- Empirical comparisons
- Knowledge of mechanism
- Known adult-child biologic and clinical
properties of analgous drugs. - Known sensitivity of children to specific
toxicities.
11How is prior information represented?
- Probability distributions on key parameters,
expressing our best guess and degree of
uncertainty. - Key parameters
- MTD
- Response / Survival rate
- Toxicity rate
- Shape/slope of dose-toxicity curve
- Pharmacokinetic parameters
12Bayesian Representation of Prior Knowledge
13Another view of prior information
- Prior probability distributions are
mathematically equivalent to information from N
prior individuals. - Made-up data.
14Even weak knowledge Subjects not needed
- Confidence that cure rate lies within a 40 range
(e.g. 20 -gt 60) corresponds to 25 patients
worth of experimental information. - Confidence that cure rate lies within a 20 range
(e.g. 20 -gt 40) corresponds to 100 patients
worth of experimental information.
15What do these methods do for us?
- Properly account for uncertainty/ knowledge in
both previous and current experimental data. - Minimize the amount of information necessary from
the current experiment - of value only if
priors are reasonably accurate. - Promote research treatments that reflect, as
closely as possible, our best guess about what
would be best for the child based on all prior
information. - Allow flexibility in design, because all Bayesian
designs can be adaptive, i.e. responsive to
accumulating data.
16What do these methods do for us? (cont.
- Encourage extremely valuable discussions about
prior knowledge and uncertainty, and about goals
of study. e.g. toxicity target in CRM. - Most standard approaches, used flexibly and
with common sense, can become operationally
indistinguishable from Bayesian ones, but this
often requires more ad-hocery, and lack of
theoretical foundation.
17Charge
- Can one apply a Bayesian analysis where the a
priori data comes from an adult patient
population and the new data comes from a
pediatric population? -
18Final Answer
- Yes, but only if the adult data is deemed
relevant or informative. - More empirical studies of this relevance need to
be conducted, and ongoing. - This may require incorporating additional
endpoints and measurements into both adult and
pediatric trials to facilitate this comparison.