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Practical Implementation of CRM in Real Clinical Settings for Oncology Dose-Finding Trials Xiaobu Ye 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 l How are we doing? l What might be the reasons? l Talk Outline l How are we doing? l What might be the reasons? l What could we do to help? l Are there more challenges ahead ?

Goal of Dose-Finding Trial in Oncology Dose-finding trials in oncology are a broad class 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.

Two Types of Drugs of Interest l l Cytotoxic agents (toxicity) A higher therapeutic Two Types of Drugs of Interest l l 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

Type of Measurements Used in Dose-Finding Trials l l l Toxicity Pharmacokinetics Pharmacodynamics Biomarker Type of Measurements Used in Dose-Finding Trials l l l Toxicity Pharmacokinetics Pharmacodynamics Biomarker Imaging

Model-based Approach for Dose-Finding Trial Definition of Dose-response relationship The relationships among dose, drug 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-E 4 Model-based approaches are generally under some assumptions l The true dose-response relationship has a biological form; l A mathematical model could mimic observation if empirical data were collected; and l 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)

Popularity = Reality From 1991 -2006, among 1, 235 phase I oncology trials in 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; l Clinicians are satisfied with having sufficient assurance that the selected dose is reasonably safe and desire for simplicity of trial execution; l Regulatory agency has the primary concern for the safety of using human subjects for testing without pre-specified dose. l

Special Characteristics of Model-based Approach Compared to Simple 3+3 Design l l l l Special Characteristics of Model-based Approach Compared to Simple 3+3 Design l l l l 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

How Statisticians Deal with the Challenge To identify the necessary steps that ease the 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.

Example New Approaches to Brain Tumor Therapy NABTT-Consortium has been funded by the NCI Example New Approaches to Brain Tumor Therapy NABTT-Consortium has been funded by the NCI since 1994 for therapeutic studies of central nervous system malignancies Member Institutions Cleveland Clinic Emory University Henry Ford Hospital Johns Hopkins University Massachusetts General Hospital Primary goal of the consortium is to improve therapeutic outcome for adults with primary brain tumors. Moffitt Cancer Center NCI Neuro-Oncology Program University of Alabama at Birmingham University of Pennsylvania Wake Forest University

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

Trials used m. CRM method l l l 9 -AMINO-20(s)-CAMPTOTHECIN Pyraxoloacridin Irinotecan (CPT-11) Karenitecin Trials used m. CRM method l l l 9 -AMINO-20(s)-CAMPTOTHECIN Pyraxoloacridin Irinotecan (CPT-11) Karenitecin BMS-247550 TMZ+BSI-201

Modified CRM by Dr. Steven Piantadois The main points in modification of CRM used Modified CRM by Dr. Steven Piantadois The main points in modification of CRM used in the NABTT : 1. A simple probability model, assuming a true dose-toxicity response is a logistic curve, to guide data interpolation:

Assumed Underline Dose-Toxicity Function Assumed Underline Dose-Toxicity Function

Modified CRM The log-likelihood function for binomial outcomes and logistic dose response: The best Modified CRM The log-likelihood function for binomial outcomes and logistic dose response: The best estimated dose is obtained by using prespecified target toxicity rate and empirical data to fit the logistic function through maximum likelihood estimates of Beta and d 50.

Modified CRM 2. Use three patients at each dose to stabilize estimates 3. Use Modified CRM 2. Use three patients at each dose to stabilize estimates 3. Use investigator clinical knowledge in the form of data to make the process easier to understand 4. 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)

The Computer Program User Interface sp The Computer Program User Interface sp

Initiating the CRM Requires Information from: l l Observations of patients Quantitative specification of Initiating the CRM Requires Information from: l l Observations of patients Quantitative specification of a model Assumed probability distribution for the model parameters Clinical knowledge formalized as “data”

Software Website Current website: http: //www. cancerbiostats. onc. jhmi. edu/softw are. cfm Potential future Software Website Current website: http: //www. cancerbiostats. onc. jhmi. edu/softw are. cfm Potential future website: http: //www. csmc. edu/15108. html

Planning Stage 1 working with investigators The goal is to simplify and ease investigator’s Planning Stage 1 working with investigators The goal is to simplify and ease investigator’s participation l l l l 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

Issues Requiring PI’s Confirmation l l l l l Using CRM method (Giving a Issues Requiring PI’s Confirmation l l l l l Using CRM method (Giving a demo to investigator 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

Planning Stage 2. working with regulatory agency (CTEP) The goal is to get approval 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 l l l To provide documentation of theoretical elements of using the modelbased 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

Example Table Provided in a Protocol CRM cycle 1 CRM cycle 2 Toxicities Next Example Table Provided in a Protocol CRM cycle 1 CRM cycle 2 Toxicities Next Dose 0/3 7. 5 0/3 8. 7 1/3 7. 5 2/3 6. 3 3/3 5. 7 0/3 6. 2 1/3 5. 0 2/3 3. 2 3/3 Re-evaluate the starting dose 1/3 2/3 5. 1 2. 3 This dose is below the d 10 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.

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

Required Information to Run the Model l l l Quantified clinical intuition about drug Required Information to Run the Model l l l 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

Initial Dose Initial Dose

Second Dose Second Dose

Final Dose Final Dose

Cautions during the Execution Period l l l Subjectivity in toxicity grading and attribution Cautions during the Execution Period l l l 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)

A Partial Operational Report X number of patients were treated on dose level 1. 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 to obtain the next testing dose, dose level 2, for the group 2. The new dose was reviewed by the central office on .

Reporting Stage Information should be provided in the statistical report: l l l l Reporting Stage Information should be provided in the statistical report: l l l l 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

Limitations l l Current mathematical model used to describe the dose and toxicity relationship Limitations l l 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.

Popularity = Implementation The three parties in the challenging reality: l l l Clinical Popularity = Implementation The three parties in the challenging reality: l l l 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)

More Challenges ahead in Oncology Dose-Finding Trials What are we looking for in a 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

Challenges: 1. Model Selection l l Cytotoxic anticancer drugs: the optimal dose has usually Challenges: 1. Model Selection l l 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).

Challenges: 1. Model Selection Mathematical models commonly used to fit dose-toxicity relationship for cytotoxic 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

Challenges: 1. Model Selection Challenges: 1. Model Selection

Challenges: 2. Endpoint Selection l l l Toxicity PK guided dose escalation is based Challenges: 2. Endpoint Selection l l l 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. Hung 2009)

Challenges: 2. Endpoint Selection The optimal biological dose based on a therapeutic end point 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)

Challenges: 3. Joint Effect from Combined Regimes l l l Combination of two cytotoxic Challenges: 3. Joint Effect from Combined Regimes l l l Combination of two cytotoxic agents Combination of one cytotoxic agent and another a target agent Combination of two target agents

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

Is this A Challenge ? Is this A Challenge ?