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Xiaobu Ye Sidney Kimmel Cancer Center, Biostatistics and Clinical Trials

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. Talk Outline. How are we doing?

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Xiaobu Ye Sidney Kimmel Cancer Center, Biostatistics and Clinical Trials

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  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 treatmentor 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 O’Quigley 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 3+3 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 includingdose-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

  12. Trials used mCRM method • 9-AMINO-20(s)-CAMPTOTHECIN • Pyraxoloacridin • Irinotecan (CPT-11) • Karenitecin • BMS-247550 • TMZ+BSI-201

  13. Modified CRMby 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

  18. 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.jhmi.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 investigator’s 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 PI’s 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

  23. Example Table Provided in a Protocol Currently, a reported safe dose from an on-going phase I trial in solid tumors is XX.

  24. 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

  26. Initial Dose

  27. Second Dose

  28. Final Dose

  29. 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 <date> to obtain the next testing dose, dose level 2, for the group2. The new dose was reviewed by the central office on <date>.

  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

  32. 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 3+3 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

  38. 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)

  39. 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)

  40. 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

  41. Can we capture the complex information we need to define a best dose and deliver it through a simple platform for general usage?

  42. Is this A Challenge?

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