Issues re: Adverse Events

1. Issues re: Adverse Events • Elicited vs. volunteered • Nuisance AEs • Attribution of cause

2. AEs for FAT? • The company’s standard approach: Record any symptoms or conditions the subject has experienced: _________________________________ _________________________________ • What’s wrong with this approach?

3. An alternative? “Since your last visit, has a doctor told you you had (check all that apply)” � A blood clot in the leg (venous thrombosis) � A blood clot in the lung (“P.E.”)… (for all possible diseases) …ditto for all possible symptoms • What’s wrong with this approach?

4. The Aspirin Myocardial Infarction Study

5. Which approach is most likely to find real AEs? • Eliciting AE’s increases rates in placebo and treatment groups • Not clear whether one approach is more likely to detect AEs as statistically significant

6. Pro elicited More AEs Easier to code; cheaper Con: Miss unexpected AEs Approaches to AEsVolunteered vs. elicited Pro volunteered • Fewer AEs • Finds unexpected AEs Con: • Hard to code; costly

7. Issues re: Adverse Events • Elicited vs. volunteered • Nuisance AEs • Attribution of cause

8. The Bunion Problem • FIT Trial of alendronate in 6,400 women for 4 years • Recorded over 20,000 episodes of URIs (and thousands of reports of bunions!) • Enormous data management effort and cost • How could this be avoided?

9. How to minimize ‘nuisance’AEs • Elicit uncommon, plausible and important AEs • Limit collection of minor AEs to samples of subjects

10. FDA AE classifications • Serious AEs • Deaths • Hospitalized • Cancer (except skin cancer) • Birth defects • SAEs “definitely or probably” due to study drug must be reported to company and by the company to FDA in 24°

11. The problem of attribution • AEs must be classified as • Definitely • Probably • Possibly, or • Not... ...related to the study drug

12. Attribution • Attributions to drug may be as likely with placebo as with active drug… • This could be studied using Coordinating Center databases Volunteer?

13. The FAT AE plan • Elicit DVT, PE, hot flashes (etc) with • “Has doctor told you that you have…?” • Open ended collection for other AEs • in a sample? • Elicit serious AEs in all • Hospitalizations

14. Multicenter trials Industry-sponsored trials

15. Multicenter trials • 2 to 1,000+ centers • Usually individual practices • Sometimes professional research centers • Standard protocol • “Case-report forms” (AKA “CRFs”) • Usually in addition to records for clinical care • Data management system • Paper forms, electronic entry (fax, web) • Fed to a “Coordinating Center”

16. Multicenter trialsThe Cast of Characters • Sponsor • Provides the $ • Industry: designs the study and owns the data • Contract Research Organization (CRO) • Does the sponsor’s bidding • Collects clinical sites • Develops the CRF’s (usually) • Manages the data and provides to the sponsor or FDA • (Usually) Hires and supervises the site monitors (CRAs)

17. Multicenter trialsSite Monitoring • To make sure every entry into the study data system matches the paper CRF’s and entries into the medical record • Make sure that the clinical site is following instructions • Do not check or oversee the quality of exams or interviews for data collection • Accounts for about 30% of the total cost of multicenter trials!

18. Multicenter trialsScientific Structures • Steering Committee (or Scientific Advisory Board) • “Investigator Assembly” • Subcommittees • Publications, Recruitment and Retention… • Data Safety Monitoring Board (DSMB, DMC…) • Universal in NIH-sponsored trials • Uncommon in industry-initiated trials

19. Multicenter trials • Why organize them for your research? • When you need the statistical power. • Later stages of your career.

20. Multicenter trials • Why participate? • Money • New treatments for your patients • Can be fun/interesting • May be able to analyze data (NIH) or publish. • Depends on circumstance, sponsor, and your initiative

21. Industry-sponsored research has become a commercial enterprise • ~70 to 80% of all industry-sponsored trials are done in private practices or commercial research clinics and run by sponsors or CROs • <30% of industry-sponsored research is done “by academic centers” • About 2-3 dozen small university-based non-profit coordinating centers

22. Reasons to avoid industry-sponsored trials • Bad reputation for biased results • They control the money and data • Little or no value for academic promotion • Can lose money • Can get into trouble at UCSF

23. Reasons for working with industry • They have the drugs and resources • The results of industry trials influence practice • Money • The experience can be impactful and educational, if managed well

24. Individual Cases

25. Dr. S • Junior faculty, investigator on mentor’s grant from Pfizer to test a drug for incontinence • Invited to attend meeting at Miami resort to attend an advisory board on a new ‘selective estrogen receptor modulator’ that might influence incontinence. • Trip cost: $3,500; consultation fee: $1,500 • Should you attend?

26. Vote on a UCSF Policy • Academic Senate Committee is split on a UCSF-wide policy governing allowable payments from industry to faculty for consulting and honoraria (for speaking) and related expenses. 1. Faculty should be allowed to receive ≤ $10,000/year from sponsors of their research 2. Faculty should not be allowed to receive any payments from sponsors of their research 3. This policy should be applied only to research involving human subjects

27. A Scandal • Results of a trial of a new AIDS drug are negative (except in a small subgroup) • A lead investigator on a trial of a new drug for AIDS writes a paper emphasizing the negative results. The company blocks publication insisting on including the results from the subgroup. • The investigator publishes the paper over the objections of the sponsor. The sponsor sues.

28. A Scandal • Results of a trial of a new AIDS drug are negative (except in a small subgroup) • A lead investigator on a trial of a new drug for AIDS writes a paper emphasizing the negative results. The company blocks publication insisting on including the results from the subgroup. • The investigator publishes the paper over the objections of the sponsor. The sponsor sues. What is wrong with this approach?

29. MORE Trial Results • 7,705 women treated with raloxifene. Primary outcome-reduced vertebral fractures 40%. • Main paper in JAMA on 3-year results • Graphs and tables regarding vertebral fracture • Mention in text: no effect on other fractures • Paper on 4-year results • “Continued reduction in vertebral fracture” • No mention of other fractures

30. Bias • Financial incentives bias the research • Biased analysis and reporting of results • (Bekelman: industry sponsorship likelihood of ‘pro-industry result about 3.6-fold.) • Biased trial designs • Biased selection of research questions

31. Fundamental problems • The sponsor has • data • data analysts • medical writers • Usually, sponsors have no checks on what they can publish, except the first author • First authors often too busy or inexperienced

32. A set of principles Always • Get the data (or unfettered access) • Get a data analyst (and medical writer?) • Have a publications committee with a voting majority from outside • Make your own slides • Report your sponsors and support in presentations and papers

33. What is the responsibility of a publicly sponsored university? • Work with industry to influence the rigor and objectivity of research • Be a model of ethical principles, uninfluenced by ties to industry?