Biostatisticians lead the way

1. Biostatisticians lead the way Kit Roes Biostatistics UMC Utrecht BMS-ANed 22oktober 2009 Biostatistics as conscience of the life sciences

2. François Chifflart (1825–1901), La Conscience (after Victor Hugo)

3. Conscience • Is an ability or a faculty that distinguishes whether one's actions are right or wrong. • It leads to feelings of remorse when a human does things that go against his/her moral values, and to feelings of rectitude or integrity when actions conform to moral values. • The extent to which such moral judgments are, or should be, based wholly in reason has been a matter of controversy almost throughout the history of Western philosophy.

4. Perspective(s)(and potential conflicts of interests?)

5. This presentation • Biostatistics in pharma industry • Examples • Data irregularities • FDA Advisory Committee • DSMB & stopping studies • Roles & responsibilities: are statisticians sufficiently equipped? • Concluding remarks

6. Biostatistics in pharma R&D Statistics / Quantitative modeling Pre-clinical / CMC Marketing & Lead Pre-clinical / CMC Target Lead Registration Development Sales Optimization Development I II Clinical Clinical b II III Development Development a Exploratory Full Development Discovery Development and Launch Research Development

7. Collaborating scientists Relatively unstructured Scientists also analyze data Statisticians more advanced Clinical teams with clear roles & responsibilities Statisticians analyze data Routinely involved in interaction with authorities Teams within statistics collaborate on same project Quality control Quality control Statistics Leadership At R&D Leadership level Early Stage Pharmacology and toxicology Biomarkers, Pharmacogenetics &omics Bio-analysis & assay validation Early clinical development Late Stage Clinical Development Integrated analyses for submissions Interaction with regulatory authorities, Phase IV, safety monitoring & signal detection and publication support

8. Pharmaceutical statisticians Little Use of Statistics  “Required” use Statistics  Tactical use of Statistics  Strategic use of Statistics & “Statistical thinking”  1955 2009 Rockhold, 2002

9. Regulated • Confirmatory trials • ICH E9 • Additional guidance (FDA, EMEA) • DMCs, Non-inferiority, Flexible designs, Missing data • …… • All registrations in US: re-analysis of key results, publicly available, including critical assessments (Advisory Committees) • EMEA: Critical assessment (including statistical issues), publicly available. • Obligation to report results of all analyses performed (also post-hoc)

10. Perfect world?

11. Data irregularities • Electronic patient diaries (ePRO) • Huge amounts of data • Graphical checking as initial data analysis • Can reveal patterns • With elaborate algorithm identified sites suspect of clustering of entry times • See also O’Gorman (DIA Clinical Forum, 2009)

12. As it should be…

13. Pattern emerges……

14. Data irregularities Through internal Advisory Committee on suspected fraud (with statistician): • Sites investigated / audited / confirmed • Reporting to authorities, including solution for analysis • Pro-active measures for all new trials with similar devices

15. FDA Advisory Committee • Independent experts • Advise FDA on approval • Questions • Efficacious in… • Safe in… • (Benefit / Risk?) • Vote FDA Briefing Company Briefing Question and answer

16. FDA Advisory Committee DR. SZEGEDI: With regard to suicidality, be it completed suicide or suicide attempts, we have done several analyses and I would like Dr. Kit Rous from Biometrix to explain them to you. DR. RUES: Thank you, Dr. Szegedi. If I understand your question correctly, I think the concern is that actually the rates of suicide to suicide attempts might differ in short and long term where actually as a result, the comparison across all time versus placebo would not provide the correct picture. We have addressed that question and we have done so by actually comparing suicides and suicide attempts because there are only very few suicides to draw any conclusions comparatively for asenapine and olanzapine, http://www.fda.gov/downloads/AdvisoryCommittees/CommitteesMeetingMaterials/Drugs/PsychopharmacologicDrugsAdvisoryCommittee/UCM179980.pdf

17. Topics of statistical nature • Missing data / drop-out • Survival analysis / hazard rate assumptions • Treatment by Center and US vs Non-US • Strength of evidence (positive/negative/failed trials)

18. Key roles and challenges • Prepare for and address the “statistical” questions. • Communication • (Help) Ensure the whole team does not go beyond what the data allow to conclude. • Maintain integrity (while you cannot have everything your way)

19. DSMB LIFT The LIFT study (NEJM, Aug 14, 2008.The Effect of Tibolone in Older Postmenopausal Women, S.R. Cummings et al.) Randomized, placebo controlled study in 4538 osteoporotic, postmenopausal women to evaluate the effect of 3 yrs treatment for prevention of vertebral fractures. • Primary endpoint: Incident vertebral factures after 3 years of treatment • Secondary: Clinical fractures • Key safety (pre-defined, partly): • Endometrial hyperplasia Breast cancer, All cancer • CHD, Stroke or TIA • VTE

20. DSMB Charter • Membership, responsibilities, procedures, reports, unblinding, conflict of interest. • Key efficacy data and key safety data to be monitored. • Sequential monitoring of incidence of vertebral fractures (Lan-Demets with a symmetric 5% O’Brien-Fleming-type spending function). Additional considerations when interpreting the data: “No single statistical decision rule or procedure can take the place of the well reasoned consideration of all aspects of the data by a group of concerned, competent and experienced persons with a wide range of scientific backgrounds and points of view.”

21. (1): A safety concern August 2005 (average follow up 2.4 years) the LIFT DSMB: • Indicates shortly before their August 26, 2005 meeting that they might share a safety concern with representatives of Steering Committee and Sponsor. • That may involve (partial) unblinding.

22. Steering Cee & Sponsor procedure Written and dated agreement was made to the following procedure (statistician responsible): Potential unblinding to full report if needed: • Two key Steering Committee members (incl. chair). • The (non voting) Steering Committee member on behalf of the sponsor. • Two senior managers from the sponsor (Medical Affairs (MD) and statistician), not involved in trial. Subsequently, a larger group could be unblinded to limited information, if necessary for execution of the DSMB recommendation.

23. (1): What happened? DSMB recommends: • Inform LIFT participants and scientific community of observed increased risk of stroke associated with tibolone in this study. • Include rates, relative hazards, CI’s and p-values. • Participants to re-consent. • Continue the trial for important additional scientific data. Steering Committee and sponsor representatives: • Decided not to be further unblinded (beyond what will be made public). BMJ 2005, 8 October. LIFT study to continue as planned. D.E. Grobbee.

24. (2): Stopping the trial February 2006 (6 months later) • DSMB recommends discontinuation: • Increased risk of stroke persisted in the LIFT study. • Primary endpoint established, crossing the pre-defined stopping boundary. • Sponsor representatives and key Steering Committee members enabled to review unblinded report (after written confidentiality statement and over the weekend). • Sponsor and Steering Committee reach same conclusion and support DSMB recommendation. BMJ 2006,18 March, LIFT study is discontinued. S.R. Cummings on behalf of LIFT Steering Committee

25. DSMBs Key area where statisticians continue to make a huge contribution to clinical research integrity. • Innovation in statistical methodology • Impact on DSMB operation and status • Typically area where statisticians are in the lead (although not the chair) • Ellenberg, Fleming & De Mets, Whitehead, Pocock • EMEA Guideline, FDA Guidance • Internal pharma SOPs

26. Roles & responsibilities Adequately equipped? • Technical knowledge and continuous innovation • Non-quantitative (biology, medicine, regulations) • Collaboration and teamwork • Communication • Leadership • Integrity (ethics….)

27. Unscientific: Google hits • Chemistry and Ethics 5.5 M • Physics and Ethics 6 M • Mathematics and Ethics 7 M • Statistics and Ethics 12 M • Psychology and Ethics 15 M • Medicine and Ethics 19 M • Law and Ethics 40 M

28. Professional standards • ISI Declaration of Professional Ethics • ASA Ethical Guidelines for Statistical Practice • RSS Code of Conduct • Statistics Netherlands (CBS), and Norway, and…… • ………..

29. Society Paymasters Colleagues Subjects Conflicting interests Guarding against misuse and misinterpretation Benefits as large as possible Objective, transparent about limitations Clarity in roles and responsibilities Impartial assessment of alternative methods No pre-emption of outcomes Safeguard privileged info while revealing methods Maintaining confidence in statistics Transparency of methods Knowing ones own ethical principles and those of collaborators Principles of Informed Consent ISI Declaration of Professional Ethics

30. ASA and RSS Add: • Statistical analysis should be open to assessment, limits and source of data analyzed visible. • Data available for analysis by appropriate others • Acknowledge that statistician can be overruled by others (RSS)

31. Concluding remarks • Keep our own conscience clear • Peer review and collaborative work on projects* • Innovate • Integrity maintained as part of group shared value • Organization and seniority to facilitate • Educate ourselves (if not already done) • Statistics and ethics (curricula available) * Registration of VVS-Biostatisticians