Vision for Clinical Trials and Clinical Trials Units in the Future - PowerPoint Presentation

1. Vision for Clinical Trials and Clinical Trials Units in the FutureProfessor Julia BrownLeeds Institute of Clinical Trials Research, University of Leeds

2. IntroductionFirst clinical trial in 1747, James LindClinical trials are gold standard for the evaluation of new treatments/interventions in health care Provide evidence to improve clinical serviceLead to improved patient outcomes

3. BackgroundINDUSTRYClinical Trials ResearchInfrastructure in the NHSAcademic FundersPatients/publicSignificant investment in clinical trials research infrastructure and clinical trial funding over last decade

4. BackgroundINDUSTRYFUNDERSClinical Trials ResearchInfrastructure in the NHSAcademic FundersClinical Trials UnitsPatients/public

5. Clinical Trials UnitGrant prepStudy hypothesisStudy DesignSample SizeFeasibilityOutcomes/outcome developmentCostingsProtocol DevelopmentCase report FormsDatabase designRandomisationApprovalsContract negotiationSponsor liaisonStudy CentresTrial/data managementCoordinationAdverse event managementRandomisationMonitoringTrial meetingsQuality assuranceStatistical analysis planStatistical monitoringProgramming and analysisFunder ReportsData interpretationDMEC reportsTrial Steering Committee reportsAdvice and consultingScientific writing

6. To collaborate with clinical investigators in the successful design, development, set-up, conduct, management and analysis of clinical trials.“Clinical Trials Units are central to our vision of expanding clinical trials in this country". Professor Dame Sally C Davies, Chief Medical Officer & Chief Scientific Adviser, Department of HealthRole of the CTU – Summary:

7. Limitations of Clinical Trials Clinical trials can take many years:Lengthy process to plan, fund and set-up new trialsIncreasing survival times mean more patients, long recruitment periods and longer follow-up timesRegulatory challengesRapidly changing drug development environmentSimple trials focusing on one or two treatments still dominateApproximately 80% of registered trials 2010-2012 simple 2 arm designExpensive Emerging evidence rarely incorporated into ongoing trialsTrial outcomes less relevant by time of reportingSlow investigation of promising new therapiesClinical trials alone rarely change practice, especially if simple experimental vs control design

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10. What’s next?Streamline processesCoordination of trialsCollaborationNot reinventing wheelBust bureaucracyRisk adapted approachesBetter data captureMaximise information gained from trialsEfficient designBetter prediction of successful treatmentsPrecision medicineMultiple treatmentsRolling designsData sharing

11. Coordination of Clinical Trials

12. UKCRC CTU Registration SystemCTU Core competencies Track record of coordinating multicentre clinical trials from design through to publication, as evidenced by publication in peer reviewed journalEstablished multidisciplinary teamQuality assurance systemsRobust and secure IT Robust statistical inputRegular review (3-5 years) by International Peer Review Panel

13. UKCRC CTU Registration System

14. Network of 49 UKCRC Registered CTUs

15. UKCRC Registered CTU Network AimsDevelop and embed the CTU Registration Process as a recognised standard for high quality clinical trials researchMaintain a cohesive network of high quality CTUsMaintain a visible profile to facilitate access to and integration of UKCRC Registered CTUs with key stakeholders, in particular research funders (including industry), research networks, regulators, and investigatorsInfluence 2018 EU Directive UpdateBREXIT!

16. UKCRC Registered CTU Network AimsEnhance capacity and capability by continuing to support and promote the development of collaborative solutions to CTU issuesTask and finish groupsIndustry collaborationCostings and infrastructure fundingEfficient trial conductPatient public involvementInsuranceData sharingOperational GroupsStatisticsInformation SystemsQuality AssuranceRoll out risk adapted procedures

17. Better data captureRemote data capture/mobile technologyPatient reported outcomesReport UKReal-time Electronic Patient Outcome ReporTing of adverse events in UK cancer trials (REPORT-UK) EprimeReal time Electronic Patient Outcome Reporting of adverse events in early phase trialsReal time monitoring (apps, wearable devices)Sensium patch - Vital signs monitoring post-operation

18. Better Data CaptureUse of Routine dataBenefitsIdentification of patientsAssess feasibilityAdapt conductEnable follow-upAid interpretationCost reductionChallenges/concernsDifficulty accessing and extracting dataLack of uniformityPoor data quality, completeness and accuracyComplicated models required for evidence synthesis with many (sometimes untestable) assumptionsCook J, Collins G. The rise of big clinical databases BJS 2015 102(2) 93-101

19. The SHIFT trial(Self Harm Intervention: Family Therapy)‘A pragmatic, randomised, controlled trial, comparing family therapy with treatment as usual for young people seen after second or subsequent episodes of self-harm’Individually randomised 1:1 between Family Therapy and Treatment As Usual832 young people from 30+ centres (CAMHS) across England (Yorkshire, Greater Manchester, London). Young people and their primary care-giver are followed up by trial Researchers via:face-to-face meetings collection of clinical outcome data

20. Primary outcomePrimary outcome: Repetition of self-harm leading to hospital attendance within 18 months of randomisationObjective rather than subjectiveCan be obtained from hospital records even if contact has been lost with participantsSHIFT researchers visit hospitals in ‘SHIFT areas’ to manually interrogate local medical records

21. Challenges to the collection of primary outcome dataResource intensiveDifferential frequency of access between researchersHospital attendance episodes may be missedDifferent search processes for different hospitals (paper vs electronic)Lack of data linkage within Trusts – between A&E and Admissions Various obstacles and levels of access to different hospital trusts Approvals obtained from 25/33 Trusts identified for SHIFTData accessed from hospitals within ~ 22 Trusts

22. Benefits of data collection utilising Hospital Episode StatisticsIf reliable data can be obtained, benefits to the SHIFT trial include: Regular, fast, England-wide data retrieval from a central sourceAvoidance of potentially biased data collection Save on researcher resources

23. Hospital Episode Statistics Datafor the SHIFT trialObtained HES data for 487 participants Data requested from the A&E and Admissions datasets We decided that a change to the method of primary outcome data collection may be instigated after considering:% episodes coded appropriately as self-harm episodes% required data items retrieved for each episodeData quality & completeness by Hospital - to ensure recommendations can be made at both study and site level

24. Reported hospital episodesfor SHIFT participants N = 1897 Episodes receivedN = 516Within time period(335 A&E and 181 Admission)N = 458Emergency related(332 A&E and 126 Admission)N = 341Separate hospital attendances(222 A&E, 98 A&E and Admission, 21 Admission only)

25. Comparison of reported hospitalepisodes for SHIFT participantsEpisodes missed by the researcher:20 A&E episodes missed (9%)8 A&E and Admission episodes missed (8%) 12 Admission only episodes missed (57%)Three episodes missed by HES* 29 episodes identified from hospitals we had not planned to search   ResearcherEpisode reportedEpisode not reportedTotalHospital searchedHospital not searchedHES Episode reported136 (39.5%)40165*341 (99.1%) Episode not reported3 3  Total139(40.4%)205344(100%)

26. Comparison of Self-harm related hospital episodes       ResearcherSH Non-SHEpisode not reportedTotal H E S SH  24037  61Non-SH   02346  69Unknown type  1574122  211Episode not reported033  Total  39100 205 344Unable to classify 211 episodes from the HSCIC data > 60% 39% Admissions data unknown - ICD classifications75% A&E data unknown - 8 patient group classificationsNo conflicting episodes

27. ConclusionOutcome: continued collection of primary outcome data via this method every 6 months plus targeted researcher searchingDevelopment of data search algorithm and data manipulation intensive taskIncorporate a pilot download to test searches and understand dataRequires a multidisciplinary team to develop and interpretAdvantages for the SHIFT trial outweigh disadvantagesStatistics time increased by 3-4 weeks per downloadMore comprehensive and accurate trial outcome dataReduced cost of data collectionResearch time substantially reducedData management time reduced

28. Maximise information from RCTsEfficient early phase designs CTIMPsNeed for more accurate prediction of effective treatments to move to large scale evaluationIn oncology only 37% of phase III trials identify successful treatmentMore sophisticated statistical designs Complex interventionsSince 2010 only 30% of phase III NIHR HTA trials identified a successful complex interventionCurrent Complex Intervention guidance: doesn’t include assessment efficacy in feasibility and pilot studiesNeed for more evaluation of efficacy in development pathway

29. Maximise information from RCTsAdapting phase II CTIMP trial ideas to the feasibility/pilot setting could help in assessing efficacy, thereby increasing the success rate of phase III trials of complex interventions.Major challenges to such adaptation include allowing for multi component interventions, multiple endpoints, multilevel data.Bayesian approaches being investigatedStat Methods Med Res. 2016 Jun;25(3):997-1009. Statistical challenges in assessing potential efficacy of complex interventions in pilot or feasibility studies. Wilson DT1, Walwyn RE2, Brown J2, Farrin AJ2, Brown SR2

30. Maximise information from RCTsPrecision MedicineBiomarker driven designs (Focus4)

31. Maximise information from RCTsMultiple questions within a trial Access for patients to more promising therapies within trials Trials outcomes remain relevant Greater chance of a successful outcome from the trial Faster adoption of successful therapies into practice Reduced overall patient numbers, trial costs and resources

32. Phase II Phase III IAIBICIDC Randomisation (1:1:1:1:2)  Randomisation (1:1:1) Analysis (≥50% reduction in area at 4 weeks)  Analysis (time to complete healing (by 52 weeks))N=54N=54N=54N=54N=108N=166 (+112)N=166 (+112)N=220 (+112)Numbers in () indicate number of additional patients recruited in Phase IIIMaximise information from RCTs: MIDFUT Multi-arm Multi stage trial design

33. Adding an ARM : FLAIRFCRIRRandomise 1:1Phase III Trial of IR vs FCR4 year recruitment and 4 year follow-upSurvival AssessmentNewly diagnosed patients with CLLRandomised to:FCR (current standard)IR (Ibrutinib + Rituximab) Cohen DR, Todd S, Gregory WM, & Brown JM (2015). Adding a treatment arm to an ongoing clinical trial: a review of methodology and practice. Trials, 16(1), 179.

34. Adding an Arm : FLAIR+ FCRIRRandomise 1:1Phase III Trial of IR vs FCR4 year recruitment and 4 year follow-upRandomise 1:1:nTime = 18 monthsPhase II Trial assessing IVOutcome expected in 2017I+VResponse AssessmentIV acceptableSurvival AssessmentShould we:Wait for the phase II I+V outcome, but delay the phase III trial in IR? Start the trial with IR now, but deny I+V a timely investigation?

35. Adding an Arm : FLAIR+Planning needed for I+V addition: obtain funding and approvals; implement amendments. Logistics complicated due to unknown outcomes and timings for the phase II trial.FLAIR+ in 3 stages. Control patients not recruited concurrently (within same stage) not used within primary comparisons Savings in timelines over 2 separate trials or delay in initial trialTrial StageIIIIIIFCR (N=566)N=189N=188N=189IR (N=377)N=189N=188 I+V (N=377) N=188N=189Time18 months18 months12 monthsTotal months183648

36. Rolling Trials : Myeloma TrialVery complicated phase III, factorial trial asking a number of questions Myeloma XI (Intensive Pathway) 2-arm trial 1:1 N=1509 CTD vs RCD

37. Rolling Trials : Myeloma TrialVery complicated phase III, factorial trial asking a number of questionsCCRD arm added to induction randomisation Myeloma XI (Intensive Pathway) Myeloma XI+ 2-arm trial 1:1 N=1509 3-arm trial 1:1:2 N=1000 CTD vs RCD CCRD vs CTD/RCD

38. Rolling Trials : Myeloma TrialAdvantages of this design amendment:New treatment addressed without waiting for original trial outcomes: compared to both existing treatments at 2:1 allocationInferior existing treatment can be droppedCentres are in place and recruitment already has momentumIntensive pathway recruited >40 patients/month from 100 centres; completed recruitment a year ahead of schedule. Total planned recruitment period only extended by 1 year overallReduced set-up times: amendments rather than new applications; faster MHRA, ethics, R&D and endorsement approvals, industry contracts2½ year set-up time has been eliminated! Cost savings over a new trial: protocol and approvals only require amendments; database exists; trial management procedures in place; staff employed and trained

39. Rolling or adaptive Trials : ChallengesCan be difficult to implement: Planning amendment with uncertainties: - Timing of implementation unknown - Funding applications prior to availability of early phase data - Contracts (possibly negotiating with multiple pharmaceutical companies)Statistical considerations:Type I and II error rate controlMultiple testing adjustmentsHandling of non-concurrent control dataNot impossible to overcome, but careful planning is needed!Adding a treatment arm to an ongoing clinical trial: a review of methodology and practiceDena R Cohen, Susan Todd, Walter M Gregory and Julia M Brown Trials (2015) 16:179Recommendations on multiple testing adjustment in multi-arm trials with a shared control groupDena R Howard, Julia M Brown, Susan Todd and Walter M Gregory Statistical Methods in Medical Research (on line)

40. Maximise information from clinical trialsResponsible Data sharingEnhances transparencyFosters development and testing of new hypothesesAvoids unnecessary repetition‘Knowledge is power and the stakes are too high to hold back scientific information that could be used to answer new questions or guard against biased reporting of results’. Senator Elizabeth Warren

41. Maximise information from clinical trialsResponsible Data sharing : ChallengesProtecting rights of patients, investigators, sponsors, fundersRequires up front planningLogistics of long term database access

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43. Overall messagesClinical trials continue to raise difficult design, conduct and analysis questionsTechnological and clinical advancesMove towards multi arm, dynamic trial design, conduct and analysis Increasing collaboration and changes requiredCoordination of trialsData sharing Requires a willingness to question long held beliefs about how clinical trials are performedFuture is bright