Improving Quality of Trials through the MRC Network of Hubs for Trials Methodology Research Professor Lucinda (Cindy) Billingham Professor of Biostatistics Director, MRC Midland Hub for Trials Methodology Research Biostatistics Lead, Cancer Research UK Clinical Trials Unit University of Birmingham NIHR Statistical Meeting, London February 13 th 2012

Agenda Explain structure, objectives and activity of: –Network of MRC Hubs for Trials Methodology Research (HTMR) –MRC Midland Hub for Trials Methodology Research (MHTMR) Examples of Methodology Research –Query from clinical research community: crossing survival curves –MRC initiated topic: stratified medicine –Working with a CTU: rare diseases

Why Do We Need Funding for Trials Methodology Research? Clinical Trials Units Design, conduct and analyse trials Evidence synthesis from trials Identify methodological problem Methodology review – identify a solution Methodology research and development Not Directly Funded

MRC / NIHR Initiative

HTMR Network All-Ireland Hub led by Professor Mike Clarke Dr Adrian Mander

1. Promoting high quality collaborative methodological research, both between Hubs and with other groups, nationally and internationally 2. Providing methodological advice to the clinical trials community 3. Encouraging the implementation of the most effective and appropriate methodological practice, for example by providing education and training 4. Working with stakeholders, in particular to agree on shared priorities for research and guidance Network Objectives

What Do the Hubs Do? Research Programme Develop existing expertise Develop new research themes identified by trials community Collaborative, practical use to the trials community Training Programme Train the experts of the future Provide training for current practitioners Advice, Support and Dissemination Function Advice facility for trial practitioners Make knowledge accessible to the trials community Provide core of expertise in trials methodology Make UK a leader in trials methodology Hubs will become self sufficient

Structure of the Midland Hub (MHTMR) University of Birmingham College of Medical and Dental Sciences School of Cancer Sciences Cancer Research UK Clinical Trials Unit Billingham, Johnson, Wheatley (Stocken) Birmingham Clinical Trials Unit Ives School of Health and Population Sciences Primary Care Clinical Sciences Unit Calvert, Wilson (Draper) Public Health, Epidemiology and Biostatistics Unit Lilford, Deeks, Zeegers Riley (Girling) Health Economics Unit Coast (Al-Janabi, Barton) Director: Prof Lucinda Billingham Deputy Director: Dr Richard Riley

MHTMR Hub Resources Director (60%)Day-to-day management; support and mentorship to RFs and PhD students; ensure successful delivery Hub programme; networking 10 Hub InvestigatorsSupervision and development of research projects and contributions to training and advisory service 3 Research FellowsMethodological research projects Project grant applications Provision and coordination of advice facility Training and support to PhD students 1 Senior Administrator Support Director, Investigators, Research Fellows Support training programme and PhD students Organise Hub meetings and events 5 PhD StudentsMethodological development Plus other affiliated RFs and PhD students

Users Change Clinical Practice Established expertise New areas Clinical Trial Pathway for Research Phase I, II, III Add-on translational studies

Network: Working Groups Trial recruitment group Outcomes group Evidence synthesis group Trial conduct group Adaptive design group (Stratified medicine group)

HTMR Network Funds for Small Projects Proposals for methodological research and workshops in all areas relating to trials –Organising a research workshop –Organising training/educational workshops –Knowledge exchange visits for pilot/feasibility work –Systematic review of methodology –Methodological guidelines development Short-term <12 months, max £50k Lead applicant based at one of the Hubs, involve researchers from at least 2 of the Hubs, additional investigators from outside Hub encouraged 4 times per year: next is March 26 th 2012 Application on

Core Outcome Measures in Effectiveness Trials (COMET) Database of Resource-Use Data Collection Instruments for Trial-based Health Economic Evaluations (DIRUM) Methodology for Trials of Radiotherapy Interventions CONSORT Extension on Quality of Life Reporting Standards Research Exchange Visits for Improving Multi-Arm, Multi- Stage Clinical Trials Trial Monitoring – Towards Best Practice Central Statistical Monitoring IPD Meta-analysis Guidelines for Reporting Biases HTMR Funded Collaborative Methodological Research

MHTMR: Research Themes 1) QoL evaluation for clinical and health economic assessment Outcome measures; evaluating costs PhD: Capability as an outcome measure (Tom Keeley; Coast, Al-Janabi) 2) Discovery and evaluation of diagnostic, prognostic and predictive biomarkers Stratified medicine; statistical modelling; analysis of multiple serial biomarkers; design and analysis of proteomic studies PhD (MHTMR): Stratified medicine: methods for evaluating predictive biomarkers (Kinga Malottki; Billingham, Deeks, Riley) PhD: Use of flexible parametric modelling in prognosis research (Kym Snell; Riley, Stocken, Billingham) 3) Methods to obtain reliable conclusions and involve users Phase I/II trials; complex interventions (specifically radiotherapy); rare diseases/ paediatrics; complex time-to-event data ; trial conduct PhD: Electronic participant information sheets (Helen Kirkby; Wilson, Draper, Calvert) 4) Bayesian methods in trialsPhD: Bayesian methods for design and analysis of clinical trials (Danielle Burke; Billingham, Girling) 5) E-trials 6) Systematic reviews for clinical and health economic evaluation Systematic review of biomarkers, decision modelling PhD: evidence synthesis for risk prediction (Ikhlaaq Ahmed; Deeks, Riley) PhD (Maths): meta-analysis of prognostic factors (Ghada; Deeks,Riley) PhD (NIHR): allocation of cancer resources to maximise health benefits (Lazaros Andronis; Billingham, Barton) 7) Education in trial methodology

Training Schemes Provided by Hubs 5 PhD Studentships MSc courses MSc dissertation projects Experts of the futureCurrent practitioners CPD Courses Best practice New methodology Via existing mechanisms Regular seminars One-off symposia Annual one-day meeting Network: Workshops Annual Meeting Sponsored speakers/events at major meetings UK Clinical Trials Methodology Conference Example: Nov 17 th 2011 QoL Assessment in Cancer Research (MHTMR/CRCTU/ECMC at UoB)

Workshops Hosted by Network Using Existing Data in Trial DesignUsing Existing Data in Trial Design Biologic Therapies in Inflammatory Joint Diseases- Models for Decision MakingBiologic Therapies in Inflammatory Joint Diseases- Models for Decision Making Routinely collected medical data - Use in clinical trials The use of ICECAP measures in clinical trials and economic evaluationThe use of ICECAP measures in clinical trials and economic evaluation Handling Missing Outcome Data Accrual and Recruitment in Paediatric Trials Complex Interventions Ordinal Outcome Data Core Outcome Measures for Effectiveness Trials (COMET) Recruitment in Surgical Trials Diagnostic Evaluation in Stratified Medicine - joint workshop with Efficacy and Mechanism Evaluation program (EME)Diagnostic Evaluation in Stratified Medicine - joint workshop with Efficacy and Mechanism Evaluation program (EME)

Advice Function HTMR Network Regional Hub Hub with relevant specialist expertise CTU: design, conduct and analysis of trials RDS: designing research studies Specialist expertise external to HTMR Network In-house research Systematic Reviewers Pharmaceutical Industry In-house research MAST

Methodology Advisory Service for Trials (MAST) Advice provided by individual Hubs through Network ‘Non-standard’ methodological problems –E.g. Adaptive trial designs, incorporating qualitative research, analysis with missing data For statisticians and trialists working within the registered Clinical Trials Units and Research Design Services in the UK Fill out the MAST Query Form and to and the query will be directed to the appropriate Hub

Example of Methodological Issue in the Clinical Research Community GefitinibGem/Cis N Event (96.2%) (94.6%) HR (95%CI) = (0.641 to 1.031), P=0.044 Median PFS 4 month PFS (%) 6 month PFS (%) 1 year PFS (%) 2 year PFS (%) 6.1 m m First-SIGNAL (Jin Soo Lee et al): PFS in never smoking adeno NSCLC ‘PFS was better in gefitinib arm’

Methodology Review: Aims To identify the different methods that have been proposed for crossing survival curves To determine if these methods are available using standard software and if not consider developing code To investigate how they operate under different circumstances To make recommendations regarding best practice

Example of MRC initiated topic: ‘Stratified Medicine’ Recent term: 15 hits on PubMed Association for the British Pharmaceutical Industry (ABPI) white paper 2009 –‘the ability to classify individuals into subpopulations that differ in their susceptibility to a particular disease or their response to a specific treatment’ Trusheim et al (Nature Reviews Drug Discovery 2007) –‘In stratified medicine, a patient can be found to be similar to a cohort that has historically exhibited a differential therapeutic response using a biomarker that has been correlated to a differential response’ Other terms –Diagnostic biomarkers, prognostic biomarkers, predictive biomarkers (e.g. Cancer Research UK) –‘Patient Segmenting’ –Biomarker classifiers

Biomarker Classifiers for Stratified Medicine Biomarkers Classifier+ Classifier- Mathematical Function (weights, cut-points) DNA, RNA, proteins … Predict to benefit Predict to NOT benefit Classifier needs to be: quick, cheap, reliable, reproducible, high sensitivity and specificity Example: HER2 status for herceptin treatment in breast cancer

Trial Designs Assessing Application of Biomarkers in Clinical Practice Discovery Development Validation Application Change Clinical Practice Randomised Clinical Trial 1) Stratified Trial Design a) Stratified Assessment Design b) Targeted Trial Design c) Treatment-Marker Interaction Design 2)Marker-Based Strategy Design Sargent DJ et al JCO 2005; Simon R Clin Cancer Research 2008; (plus many more!) Freidlin et al JNCI 2010; Research Hypothesis: there is a validated biomarker classifier that accurately identifies patients who are highly likely to gain survival time from a marker-based treatment (M-Trt)

Measure Biomarkers Classifier +Classifier - RANDOMISE M-TrtControl M-Trt RANDOMISE Stratified Trial Design Marker-Based Strategy Design RANDOMISE Marker-based treatment strategyStandard Care Classifier+Classifier- Standard Care Measure Biomarkers M-Trt

Stratified Medicine: Evidence of the Need for Information Provision on Methodology 2 nd Late Phase Trials Forum, London, June 2008 International Lung Cancer Conference Liverpool, July 2008 NCRI Cancer Conference, Birmingham, October 2008 First International Workshop on Thoracic Oncology, Turin, April 2009 CRUK/ECMC Biomarker Roadmap Meeting, Leeds, April rd Late Phase Clinical Trials Forum (multimodality setting), London, June 2009 World Conference on Lung Cancer, San Francisco, July 2009 International Society for Clinical Biostatistics, Prague, August 2009 Critical Issues in Lung Cancer Research: The Swedish Approach and the International Standards, Stockholm, February 2010 European Congress: Perspectives in Lung Cancer, Amsterdam, March 2010 National Lung Cancer Partnership 2010 Annual Meeting, Chicago, June 2010 Trial Designs to Assess Biomarkers in Clinical Practice Research activity for publication How sensitivity and specificity of a biomarker affects statistical power Review the evidence behind the stratified medicine decisions

Example of MHTMR Working with CTUs: Trials in Rare Diseases Randomised Phase III trials are the optimal method for establishing best patient care Patients with rare diseases have the same right to evidence based treatment as those with common diseases Phase III trials in rare diseases will never be large enough to determine best practice with adequate certainty Trials in rare diseases are not a worthwhile investment due to high cost-utility

Lilford’s Proposal Lilford R, Thornton JG, Braunholtz D Clinical trials and rare diseases: a way out of a conundrum BMJ 1995 Ethics of small clinical trials –Small well designed study better than no study –Contribute to a pool of knowledge Proposes an alternative view to clinical trials: –Carry out a trial NOT to gain a definitive answer but to change the level of uncertainty Bayesian perspective is useful in these circumstances Make use of all knowledge, results from non- randomised studies should not be discarded p ( treatment effect lies in a particular range | data, prior ) p-value = p ( data | no treatment effect )

Example: Bayesian Analysis of Trial Data with No Prior Information - Data: HR=0.8, d=50 P(HR<1)=0.78 Posterior probability distribution for True HR

What about Incorporating Prior Information? Aim: Combine all current evidence into a single prior probability distribution for the treatment effect Systematic review of literature and identify relevant studies Obtain HR from each study (actually log HR) Weight the different studies according to: –Pertinence: how close is the information to that we wish to obtain –Validity: quality of the study –Precision: depends on number of events Combine the log HR and weights Tan S-B, Dear KBG, Bruzzi, P, Machin D Strategy for randomised clinical trials in rare cancers BMJ 2003 –Propose methodology for representing existing evidence as prior distribution Tan S-B, Wee J, Wong H-B, Machin D Can external and subjective information ever be used to reduce the size of randomised controlled trials? Contemporary Clinical Trials 2008 –Illustrate the methodology on nasopharyngeal carcinoma example Application to merkel cell carcinoma: Lucinda Billingham, Kinga Malottki, Mark Pritchard, Jerry Marsden, Neil Steven

Rare Diseases: Summary Small trial, ideally randomised, is better than no trial Existing evidence is important in this setting Bayesian approach enables: –small trials to be regarded as reducing the uncertainty in estimation of a treatment effect –probability statements about treatment effects which may be more useful in small studies –‘cumulative learning’ which facilitates adaptive trial designs –inclusion of prior information which maximises the utility of the evidence Inclusion of prior is controversial - evidence synthesis needs to provide a believable prior

MHTMR Working with CTUs International Rare Cancers Initiative –National Cancer Research Institute (NCRI), –Cancer Research UK –National Cancer Institute (NCI in USA) –European Organisation in Research of Treatment for Cancer (EORTC) 8 rare cancers selected for trials Aim: develop first phase III trial ever in penile cancer –Institute for Cancer Research CTU, Sutton Statistician: Dr Emma Hall –MHTMR: Methodology Advisors –Potential Collaboration: M.D. Anderson Cancer Centre Statisticians - Professor Peter Thall

Hub Network: Stakeholder Meetings Arthritis Research UK British Heart Foundation Cancer Research UK Health Technology Assessment Programme Medicines and Healthcare products Regulatory Agency NIHR Comprehensive Clinical Research Network Wellcome Trust Association of the British Pharmaceutical Industry Cochrane Collaboration Statisticians in the Pharmaceutical Industry Registered clinical trials units National Institute for Health and Clinical Excellence National Ethics Research Service

How can the Hub Network support the NIHR Statisticians? Senior Administrator for Hub and PA to Director: Karen Biddle,