Practical considerations in designing a phase I Time to Event Continual Reassessment Method (TiTE CRM) trial in a grant funded CTU Eleni Frangou 1, Jane Holmes 1, Sharon Love 1, Lang o Odondi 1,2, Claire Hamill 3, Naomi McGregor 3, Maria Hawkins 2 1 Centre for Statistics in Medicine (CSM), NDORMS, The University of Oxford 2 Department of Oncology, The University of Oxford 3 Oncology Clinical Trials Office (OCTO), The University of Oxford 25 th August 2015 36 th ISCB Annual Conference, Utrecht, The Netherlands
Overview Description of the clinical trial Design Time to Event Continual Reassessment Method (TiTE CRM) Set up Communication with the Chief Investigator Familiarisation with the TiTE CRM Statistical Programming Trial Management Costing and Funding Future Steps 2
Description of the clinical trial Phase I, single arm, open-label, multicentre, 2 stage trial in oesophageal cancer Stage A Palliative setting: Radiation and escalating doses of VX970 Stage B Radical setting: Definitive chemoradiotherapy using radiotherapy, in combination with Cisplatin, Capecitabine and escalating doses of VX970 Primary objective in each stage is to determine the safety, toxicity profile and Maximum Tolerated Dose (MTD) The MTD from Stage A will be used to inform the starting dose of Stage B 3
Design of the clinical trial Continual Reassessment Method (CRM) Model-based method for finding the MTD which causes a dose limiting toxicity (DLT) for a specified target toxicity level Larger number of patients are treated on or at adjacent doses of the MTD than the conventional algorithm-based methods A priori a relationship between the dose levels and the toxicity levels is defined namely the Dose Toxicity Curve (DTC) which is re-evaluated every time a new patient is observed Examples of the DTC include the power curve and the logistic model Monotonicity assumption states that toxicity increases with increasing dose and that efficacy also increases with 4
Design of the clinical trial Time to Event Continual Reassessment Method (TiTE-CRM) Modified version of the CRM It accounts for the time to event of possible late onset toxicities by considering a weighted DTC Uses all accumulated information to decide which dose to assign the next patient Results in shorter study duration as it is not necessary for a patient to be observed for the full observation period before recruiting the next patient 5
Communication with the Chief Investigator (CI) Various meetings and email exchanges were required to establish: Timelines Meaningful prior probabilities (skeleton) An adequate number of nested treatment schedules Target toxicity levels for both stages Stopping rules due to success and safety Escalation rules Utilising the data from Stage A for Stage B Simulation results from different scenarios enabled us to make decisions between different options 6
Familiarisation with the TiTE CRM This task consisted of: Literature review Self study Attending seminars and courses Exchanging views and knowledge amongst statisticians Marrying up the expectations of the Chief Investigator and the TiTE CRM design External advice was sought through the Methodology Advisory Service for Trials of the MRC Hubs for Trials Methodology Research 7
Statistical Programming and Simulations Statistical package used: R Programmes were developed independently by two statisticians Executable, simulator and processing programmes developed Existing R functions could not accommodate some trial specific characteristics Pause in recruitment Time-to-toxicity distribution Dose allocation Stopping rules Additional time was allowed for debugging and validating 8
Statistical Programming and Simulations Extensive simulations were performed to assess the behaviour and robustness of the model Data were generated under a number of scenarios reflecting a variety of realistic and extreme cases Each trial was simulated using the actual study s parameters and characteristics The simulation results were used to inform different aspects: Sample Size Trial Duration Power to detect the MTD Stopping due to safety 9
Statistical Programming and Simulations Simulation Example 10
Statistical Programming and Simulations Simulation Example (contd.) 11
Trial Management Protocol development Time delay between idea and protocol development Transition between Stage A and B Dose levels and schedule of events discussions were driven by an ongoing First In Human Phase I study It has received external review and input at a European Cancer Organisation (ECCO) workshop High staff requirements Data input by sites needs to be swift to allow the statisticians to advise on dose Lack of knowledge in advance of when teleconferences will be required to advise on dose escalation Risk associated with the combined trial interventions is high and the trial will require intense central monitoring 12
Costing and Funding The total cost of this trial was estimated to be higher than conventional trials due to The complexity of the design The extra statistical input to design and during the trial Our unit s lack of experience in these methods The estimated trial duration being 4 years once recruitment starts The trial was costed on the basis of both the average duration and number of patients and the maximum duration and number of patients Funding applications were submitted to multiple sources New Agents Committee (NAC), Cancer Research UK Pharmaceutical Company providing the ATR inhibitor Department of Oncology, The University of Oxford, UK 13
Time (%) Set up of the clinical trial Communication with the CI; 10.9 Funding and Finance; 4.9 Trial Management; 10.4 Study Dissemination; 7.1 Trial Design Characteristics; 8.2 Simulations, Results Processing, Debugging; 32.4 Familiarisation with TiTE CRM; 12.5 Statistical Programming; 13.6 Percentages show the statisticians time spent on each aspect of the set up process 14
Future Steps Protocol Statistical Analysis Plan (SAP) Case Report Forms (CRFs) Review Data Management Plan Critical points review Charters Data Monitoring Committee Trial Steering Committee Statistical programmes Statisticians should be at the ready to analyse the available data once there is a new recruit Two independent programmes will be used in addition to the titecrm function in the dfcrm package by Cheung (2013) Trial Master File GREEN LIGHT! 15
Conclusions Significantly more time, man power and resources than an algorithm-based trial were invested during set up We feel we are up to date with the literature and have a good knowledge of existing model-based methodologies Generic CRM and TiTE CRM analysis and simulation programmes have been set up and are ready to use in future trials Having explored the behaviour and performance of this methodology puts us in an advantageous position in designing more CRM and TiTE CRM trials 16
Acknowledgments This work is supported by Cancer Research UK (CRUK) trial number CRUKD/15/011 Vertex Pharmaceuticals University of Oxford CRUK/MRC Oxford Institute for Radiation Oncology Oxford Clinical Trials Research Unit (OCTRU) Oncology Clinical Trials Office (OCTO) Centre for Statistics in Medicine (CSM) Oxford University Hospitals NHS Trust (Churchill Hospital) Leeds Teaching Hospitals NHS Trust University of Leeds NHS Greater Glasgow & Clyde 17
Acknowledgments Chief Investigator: Maria Hawkins Trial Management: Claire Hamill and Naomi McGregor Clinical Trials Unit Statisticians: Jane Holmes, Lang o Odondi and Sharon Love Oncology Trials Director: Tim Maughan 18