Xiaobu Ye

1
Practical Implementation of CRM in Real Clinical
Settings for Oncology
Dose-Finding Trials

• Xiaobu Ye
• Sidney Kimmel Cancer Center, Biostatistics and
  Clinical Trials
• Johns Hopkins University School of Medicine

2
Talk Outline

• How are we doing?
• What might be the reasons?
• What could we do to help?
• Are there more challenges ahead ?

3
Goal of Dose-Finding Trial in Oncology

• Dose-finding trials in oncology are a broad class
  of clinical experiments to determine an optimal
  dose (MTD or OBD) of drug for cancer related
  treatment or prevention.

4
Two Types of Drugs of Interest

• Cytotoxic agents (toxicity)
• A higher therapeutic index for most cytotoxic
  drugs is obtained using a higher dose which
  yields higher side-effects
• Molecular target agents (mechanism of action)
• Toxicity
• Biological activities which are assumed to be
  associated with the clinical outcome of interests

5
Type of Measurements Used in Dose-Finding Trials

• Toxicity
• Pharmacokinetics
• Pharmacodynamics
• Biomarker
• Imaging

6
Model-based Approach for Dose-Finding Trial

• Definition of Dose-response relationship
• The relationships among dose, drug
  concentration in blood, and clinical response
  (effectiveness and undesirable effects). ICH-E4
• Model-based approaches are generally under some
  assumptions
• The true dose-response relationship has a
  biological form
• A mathematical model could mimic observation if
  empirical data were collected and
• A model could capture and represent biological
  knowledge.
• CRM is one of the model-based approaches of
  dose-finding methods in oncology drug
  development, and was first proposed by OQuigley
  et al (Biometrics, 1990)

7
Popularity Reality

• From 1991-2006, among 1,235 phase I oncology
  trials in US, only 20 (1.6) were identified
  using model based approach (A. Rogatko et al
  2007)
• There are three parties involved that created the
  reality
• Statisticians develop sophisticated model-based
  approaches and desire for accuracy and precision
  in estimates
• Clinicians are satisfied with having sufficient
  assurance that the selected dose is reasonably
  safe and desire for simplicity of trial
  execution
• Regulatory agency has the primary concern for the
  safety of using human subjects for testing
  without pre-specified dose.

8
Special Characteristics of Model-based Approach
Compared to Simple 33 Design

• complex
• no assumption of actual dose used
• no assumption of response
• no assumption of cohort size
• not intuitive
• use clinical inference throughout trial
• need statistical expert
• have to use computer program

9
How Statisticians Deal with the Challenge

• To identify the necessary steps that ease the
  adaption of CRM into clinical practice (focus on
  simplicity for clinicians and safety for
  regulatory agency)
• Planning stage
• Working with investigators
• Working with regulatory agency (CTEP)
• Execution stage
• Toxicity grading and modeling
• working with investigators
• Conclusion stage
• detailed written documentation of
  model-based
• dose selection process.

10
Example New Approaches to Brain Tumor Therapy
Member Institutions Cleveland Clinic Emory
University Henry Ford Hospital Johns Hopkins
University Massachusetts General
Hospital Moffitt Cancer Center NCI
Neuro-Oncology Program University of Alabama
at Birmingham University of Pennsylvania Wake
Forest University

• NABTT-Consortium has been funded by the NCI since
  1994 for therapeutic studies of central nervous
  system malignancies
• Primary goal of the consortium is to improve the
  therapeutic outcome for adults with primary brain
  tumors.

11
Example NABTT

• The main task is early anti-cancer drug screen
• including dose-finding and safety / efficacy
  clinical trials
• All NABTT trials
• Approved by CTEP and local IRBs
• Involve multiple institutions
• phase I trial designs were either rule-based or
  model-based (modified CRM)
• single agent or combination agents

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Trials used mCRM method

• 9-AMINO-20(s)-CAMPTOTHECIN
• Pyraxoloacridin
• Irinotecan (CPT-11)
• Karenitecin
• BMS-247550
• TMZBSI-201

13
Modified CRM by Dr.Steven Piantadois

• The main points in modification of CRM used in
  the NABTT
• A simple probability model, assuming a true
  dose-toxicity response is a logistic curve, to
  guide data interpolation

14
Assumed Underline Dose-Toxicity Function
15
Modified CRM

• The log-likelihood function for binomial outcomes
  and logistic dose response
• The best estimated dose is obtained by using
  pre-specified target toxicity rate and empirical
  data to fit the logistic function through maximum
  likelihood estimates of Beta and d50.

16
Modified CRM

• Use three patients at each dose to stabilize
  estimates
• Use investigator clinical knowledge in the form
  of data to make the process easier to understand
  
• A flexible computer program to facilitate
  calculation with an intuitive user interface to
  guide through the dose-finding process
• Reference Piantadosi et al Practical
  implementation of a modified continual
  reassessment method for dose-finding trials,
  Cancer Chemother Pharmacol (1998)

17
The Computer Program User Interface
sp
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Initiating the CRM Requires Information from

• Observations of patients
• Quantitative specification of a model
• Assumed probability distribution for the model
  parameters
• Clinical knowledge formalized as data

19
Software Website

• Current website http//www.cancerbiostats.onc.jhm
  i.edu/software.cfm
• Potential future website
• http//www.csmc.edu/15108.html

20
Planning Stage

• 1 working with investigators
• The goal is to simplify and ease investigators
  participation
• Prior knowledge in study drug including
  biological mechanism, side-effect, PD, PK, and
  drug half-life etc. from preclinical , or health
  volunteers or other type of cancer that had been
  studied
• Type of toxic (side-effects) and its severity by
  dose level
• Formulate a mathematical model that capture the
  dose and response relationship
• Model specification with a range of a prior
  initial lower dose to the lethal dose
• Modeling the dose-finding trial with several
  different scenarios
• Conceptualizing the definition of dose-limiting
  toxicity ( this definition may vary according to
  different types of cancer)
• preparing protocol documentation with dose
  escalation or de-escalation rule, procedure and
  the stopping rule for declare a MTD
• Scheduling a 30-60 minute meeting with PI when
  all information is ready

21
Issues Requiring PIs Confirmation

• Using CRM method (Giving a demo to investigator
  for future dose-finding trial with several
  different scenarios)
• Number of patients per dose cohort
• Initial prior dose and toxicity used in the model
• Choice of initial testing dose
• Definition of dose limiting toxicity
• Duration of the treatment
• Toxicity evaluation period
• Dose escalation or de-escalation rule, procedure
  and the stopping rule for declare MTD
• Documentation of the first meeting with both
  investigator and statistician signatures
• Protocol preparation after the initial meeting

22
Planning Stage

• 2. working with regulatory agency (CTEP)
• The goal is to get approval of an algorithm
  rather than a set of pre-specified doses and
  demonstrate it is safe to perform a dose-find
  trial in human subjects using the algorithm
• To provide documentation of theoretical elements
  of using the model-based approach and include it
  in the clinical protocol
• To provide clinical references (rationale) for
  initial data (prior) used in the model
• To limit the uncertainty about unspecified
  testing doses by providing several steps of
  potential dose escalation and de-escalation
  scenarios using the model predicted results in
  the protocol
• Clearly defined stopping rule (stop when
  estimated targeting dose become sufficient
  accurate)
• To define an upper boundary of does increment to
  an adjacent cohort
• If it is possible, to do a real-time demo with
  CTEP biostatisticians

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Example Table Provided in a Protocol
CRM cycle 1 CRM cycle 2
Toxicities Next Dose Toxicities Next Dose
0/3 7.5 0/3 8.7
1/3 7.5
2/3 6.3
3/3 5.7
1/3 5.1 0/3 6.2
1/3 5.0
2/3 3.2
3/3 Re-evaluate the starting dose
2/3 2.3 This dose is below the d10 and will not be considered as a testing dose
Currently, a reported safe dose from an on-going
phase I trial in solid tumors is XX.
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Execution Stage

• Statisticians could help
• Study toxicity report
• Working with investigator using patient data to
  fit the model and estimate next dose for testing
• Prepare an operational report for each dose
  cohort including type, severity, and frequency of
  the toxicity used to fit the model for dose
  estimation

25
Required Information to Run the Model

• Quantified clinical intuition about drug behavior
  at higher and lower doses
• Target toxicity rate ( assuming a highest
  therapeutic index within tolerable side-effect)
• Dose
• number of patients
• r (number of responses (toxicity))
• Weight

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Initial Dose
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Second Dose
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Final Dose
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Cautions during the Execution Period

• Subjectivity in toxicity grading and attribution
• External drug information becomes available
  during the trial
• Clinical judgment versus model prediction
• Decision rule to declare an MTD ( avoid
  split-hair issues )
• Predetermined number of iterations ( revisit
  model specification if estimates do not converge
  after a predetermined number of steps)

30
A Partial Operational Report

• X number of patients were treated on dose level
  1. Two patients had grade 4 thrombosis during
  first cycle of the treatment. One thrombosis was
  attributed to drug A with possible relationship
  given by the treating physician and it was deemed
  as a DLT based on pre-specified criteria. The
  other case of thrombosis was attributed as
  unlikely to either drug A or drug B given by a
  different treating physician. Due to this
  attribution, this case of thrombosis will be
  weighted as zero with respect to treatment
  related toxicity in estimation of next testing
  dose by CRM method.
• The toxicity profile is attached to this report.
  Dr. X and statistician Y run the CRM model on
  ltdategt to obtain the next testing dose, dose
  level 2, for the group2. The new dose was
  reviewed by the central office on ltdategt.

31
Reporting Stage

• Information should be provided in the statistical
  report
• The type of mathematical model used to guide data
  interpolation
• Rationale for the target toxicity rate (
  clinically and biologically)
• Dosing steps
• Number of patients per dose cohort ( enrolled and
  actually used for fitting dose-response model)
• Major deviation in toxicity attribution which had
  effect on estimating the best dose
• Overall model fitting with cumulative data from
  all cohorts being tested
• Clear description on decision of the best dose
  based on estimation convergence with sufficient
  accuracy
• Percent of patients treated by dose above the
  best dose

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Limitations

• Current mathematical model used to describe the
  dose and toxicity relationship is based on
  cytotoxic agents. It does not necessarily fit new
  paradigm of target agents.
• The fraction of increment of the dose works only
  best for agent with a continuous dose such as
  given through IV, not for discrete dose ranges,
  such as by tablets.

33
Popularity Implementation

• The three parties in the challenging reality
• Clinical investigators to understand CRM and use
  the method in their dose-find trial
• NCI statisticians to confidently accept that the
  model-based approach is more efficient than and
  as safe as conventional 33 design
• Statisticians to implement the method in general
  use with simple execution procedure and safety
  boundary for over dosing control (development and
  implement)

34
More Challenges ahead in Oncology Dose-Finding
Trials

• What are we looking for in a dose-finding
  trial?
• A dose that has higher therapeutic effect for
  a medical condition and with tolerable
  side-effects

35
Challenges 1. Model Selection

• Cytotoxic anticancer drugs the optimal dose has
  usually been defined as the maximum tolerated
  dose (MTD). This toxicity-based dosing approach
  is under the assumption that the mechanisms of
  action of the toxic and therapeutic effects are
  the same.
• Molecular target based drugs the dose-effect
  relationship is likely to be a biological rather
  than a toxicity. Without induction of acute
  cellular damage, they are likely to be
  cytostatic. Most molecularly targeted drugs are
  expected to be more selective and less toxic than
  conventional cytotoxic drugs (E. Fox 2002).

36
Challenges 1. Model Selection

• Mathematical models commonly used to fit
  dose-toxicity relationship for cytotoxic drugs
  are not necessarily suitable for describing the
  relationship of dose-biological activities unless
  the dose-biological function is similar to the
  relationship of dose-toxicity

37
Challenges 1. Model Selection
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Challenges 2. Endpoint Selection

• Toxicity
• PK guided dose escalation is based on
  extracellular drug delivery (plasma
  concentrations). it dose not have direct
  indication of drug uptake at a specific tumor
  site. It also requires real-time PK.
• PD using biomarker as a therapeutic endpoint
  requires sequential tumor biopsies.
• Biomarkers require well defined appropriate
  measure of achieved target effect and reliable
  assay given a small cohort size
• Imaging (functional imaging) quantifies the level
  of target function in vivo.
• Multiple endpoints (toxicity and biological
  activity) (P.Hung2009)

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Challenges 2. Endpoint Selection

• The optimal biological dose based on a
  therapeutic end point
• The assays used to measure the biological effect
  need to be stabilized (sensitivity and
  variability assessment) and validated prior to
  the initiation of the phase I trial (E. Fox
  2002).
• These surrogate measures must be validated and
  correlated with the effect of the drug on the
  target in the tumor prior to using them as
  primary end points in clinical trials (KA.
  Gelmon, 1999)

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Challenges 3. Joint Effect from Combined Regimes

• Combination of two cytotoxic agents
• Combination of one cytotoxic agent and another a
  target agent
• Combination of two target agents

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Can we capture the complex information we need to
define a best dose and deliver it through a
simple platform for general usage?
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• Is this A
• Challenge ?

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