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Statistical Issues in Trial Reporting: Revised US FDA Regulations. David L DeMets, PhD Department of Biostatistics & Medical Informatics University of Wisconsin-Madison. Topics. 1. Clintrials.gov 2. Adverse Event Reporting 3. T2D Trial Design
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Statistical Issues in Trial Reporting: Revised US FDA Regulations David L DeMets, PhD Department of Biostatistics & Medical Informatics University of Wisconsin-Madison
Topics • 1. Clintrials.gov • 2. Adverse Event Reporting • 3. T2D Trial Design • 4. New Public Access to Data / White House Request
Clinical Trial Registries • For most of the past 50 years, it was difficult to know what trials were being done or had been done • True for NIH & industry sponsored trials • Information was by “word of mouth” • Concerns mostly about negative (ie neutral or harmful) results not being published • Both academia & industry run trials
Clintrials.gov • As a result, clintrials.gov was established • US requires that all trials, regardless of sponsor, be registered (federal, industry, local) • US also requires results of completed trials be registered • Ref: FDA Amendments Act (FDAAA-801) • Sponsor or Principal Investigator are responsible for registration
Clintrials.gov (2) • Eligible for registration • Initiated after Sept 27, 2007 or still ongoing on Dec 26, 2007 • Trials of drugs, biologics & devices • One or more sites in the US • Trials under FDA IND or IDE • There are exclusions • Phase I trials • Small feasibility trials • Non interventional studies
Clintrials.gov(3) • Deadlines for trial registration • Not later than 21 days after first patient • Deadline for trial results • Not later than 12 months after trial completed • NIH must certify compliance for funded trials • Sponsors must certify compliance with their submissions
Clintrials.gov (4) • Penalties for non compliance • Fines • Withholding of grant funding • Compliance track record (informal) • Industry mostly compliant • Academic investigators not fully compliant, as yet • NIH working on procedures
Clintrials.gov (5)Registration • Documents to be registered • “Protocol” • Data Elements • Title & Anacronym • Sponsor • Who is responsible • IRB Review • Data Monitoring Committee? • Oversight Authority (FDA, NIH, IRB?) • ….
Clintrials.gov (6)Results To Be Filed • Similar to a NEJM/JAMA/Lancet paper • Patient Flow • Baseline profile • Outcome measures (primary, secondary) • Adverse events • Statistical Analysis • Start & stop dates • Etc • …..
Clintrials.gov (7)2013 Facts • 140,000 studies registered • 40% US only, 40% Non US Only • 80% Registered Studies Interventional • 78000 Drug or biologic • 28000 Behavioral • 8600 Studies with Results • 8000 interventional (90%)
Public Access to Trial Data • US Congress / White House putting pressure to make trial data available, especially trials funded by government • Allow additional analyses……. • Some sponsors already doing this or working towards that goal • NIH has made some trial data available • Not as easy to do as some think
Clinical Trial Transformation Initiative (CTTI) • Cost of trials increasing dramatically, especially in the US, can’t be sustained • More trials are going off US shore • Need to streamline trials, maintain quality but reduce costs • CTTI is a consortium of NIH, FDA, industry and academia • Initiated by Duke Clinical Research Institute (DCRI) and FDA • Selected projects
CTTI ProjectsTwo early examples • SAE Reports • Copies from a trial shipped to all participating sites • Not unblinded & so not useful to sites • Not required by federal regulations • A costly tradition, not very informative • Use DSMB process • CRF Complete Auditing • Line by line on site auditing by CRA’s • Very costly • Two natural experiments suggest errors in NIH type approach small • GUSTO • Breast Cancer Trial / Montreal Site Fraud
Safety ReportingStandard Coding Systems • Several adverse event coding systems • Often organized by body systems • Subcategorized into events as reported by investigator/patient • Safety committees often review these in tabular form by treatment arms • (AE listings not helpful after awhile)
Serious Adverse Event (SAE) Reporting • Historical approach (report everything) caused regulatory SAE drowning • Many AEs part of disease process • Others common in general population • Not a useful or efficient approach • March 2011, FDA altered safety reporting rules – New IND Rule • Challenge to distinguish between common AEs in population and those associated with treatment
SAE Reporting (2) • Goal: reduce the number of uninformative SAE case reports submitted • New IND rule: • Report only Serious, Unexpected Suspected Adverse Reactions (SUSARs) • Suspected adverse reaction: reasonable possibility of causality, suggestive evidence • Places responsibility on sponsor to determine SUSAR rather than investigator
SAE Reporting (3) • May be a SUSAR if • (A) A single occurrence of an uncommon but strongly causal association AE (eg Stevens-Johnson syndrome) • (B) One or more occurrences of event not commonly associated with drug, biologic • (C) An aggregate analysis of a specific event in a CT (concurrent or historical) observed more frequently on drug than control
SAE Reporting (4) • Sponsors should develop a global “firewalled” safety committee • Aggregate analysis of total data on investigational product • SAEs, relevant lab data • Aggregate analysis • A meta-analysis from completed studies • In special cases, unmasked data from ongoing trials • No adjustment for multiplicity needed • Likely to identify false positives
SAE Reporting (5) • Requires sponsors to develop process to unblind cases but • Avoid unblinding of study team • Maintain integrity of data and trial • Review ongoing and completed trials • Compare Suspected Adverse Reactions between drug and control
AE Reporting (6) • Sponsors working to develop Standard Operating Procedures (SOPs) to deal with the new IND Rule • Too early to tell how successful new process is • Probably moving in the right direction but …….
Type II Diabetes (T2D) New Paradigm • Some celebrated cases of Type II diabetes drugs (eg rosiglitazone) had increased CV risk (CV Death, MI, Stroke) • A new paradigm for approval of diabetes drug issued by FDA • Assume new drug lowers HbA1c • A two step process • Rule out CV RR of 1.8 for initial approval • Rule out CV RR of 1.3 for final approval
T2D Paradigm (2)Rationale • Rule out excess CV events/1000 pt yrs • Rule out if : RR Upper 97.5% CI < 1.8, RR Upper 97.5% CI <1.3 • To rule out RR of 1.8 • 120 events needed • To rule out RR of 1.3 • 600 events needed • 6000 patient 5 year trial • Estimated CV RR < 1.1
T2D Paradigm (3)Two Scenarios • Twoseparate trials • First trial rules out CV RR of 1.8, drug submitted for approval • Second trial designed then to rule out CV RR of 1.3 • Failure of second trial, or failure to do second trial could result in removal • One single trial • When trial rules out CV RR of 1.8, submit data for regulatory approval • Continue trial to rule out CV RR of 1.3
T2D Paradigm (4)Issues • Two trial approach • First scenario of two separate trials pose no logistical, ethical problems • Participants in second trial may be different • One trial approach • When CV RR of 1.8 is ruled out, data are submitted for regulatory approval • At the FDA, this data must be made public when given approval • Essentially publishing interim results – will trial continue or remain compliant?
T2D Paradigm (5)One trial scenario • Public release of interim data may affect • Recruitment • Patient profile of new patients entered • Patient compliance to assigned treatment • Patient assessment of benefit & risk • Experience from cancer trials • Places DMC in a challenging position • Typically do not release interim data until trial is over or results very convincing • Want to protect overall integrity of the trial
T2D Paradigm (6)One trial scenario • Neither sponsors or regulators (eg FDA) have found an ideal solution • Several trials underway using this paradigm of a single trial • Some already submitted for drug approval • Not clear of the impact on the continuing “1.3 RR” portion of the trial