Data & Safety Monitoring of Clinical Trials in Intervention and Drug Abuse Services Research

1. Data & Safety Monitoring of Clinical Trials in Intervention and Drug Abuse Services Research Redonna K. Chandler, Ph.D. Services Research Branch Division of Epidemiology, Services, and Prevention Research Nabila El-Bassel, Ph.D. School of Social Work, Columbia University, AHSR Conference October 25, 2005

2. Overview • Background to data & safety monitoring (DSM) • Safety monitoring • Data monitoring

3. Benefits DSM • Funding agency • Quality of the data • Safety of participants • Early detection of safety/efficacy • Support oversight • Facilitate communication with regulatory entities (e.g., IRBs for multisite trials) • Cost-benefit

4. Benefits DSM • Investigator • Ongoing oversight • Scientific support • Protocol fidelity • Accuracy of measures • Reliable data • Protocol adjustments • Prevention and early detection of risks • Early assessment of efficacy • Cost-benefit

5. Benefits of DSM • Subject • Protocol adjustments • Early detection of signals (safety/efficacy) • Avoid unnecessary medical risks • Avoid unnecessary exposure to futile intervention • Benefit from overwhelming efficacy

6. Why Does NIH Require DSM in Behavioral Research? • Provides mechanism of on-going review • SAFETY: Safeguards study participants by tracking adverse events, especially of vulnerable populations • DATA: Ensures integrity and credibility of trial results. • DSMB provides independent review and recommendation by experts not involved with study

7. Diversity in HS Clinical Research • Evaluation of existing common practices as a intervention (e.g., change in case load) or comparison group • Evaluation of a practice that is being changed due to a new policy or program • Evaluations of placement, prediction, staff training, or supervision models that were developed by experts (or expert committees) • Combination or minor adaptations of existing protocols to a new setting or population • Replication in the field of a new behavioral or pharmaceutical protocol developed through basic research

8. DSM Issues in HSR • HSR focuses less on safety and efficacy than on “effectiveness” relative to existing practice • Less concerned with FDA and more concerned with multiple IRBs, OPRR, high risk populations (e.g., drug users, offenders, victims, adolescents) • HSR typically involves more heterogeneous populations, staff and sites • HSR has less control and needs to focus more on implementation and adherence/fidelity • HSR interventions typically involve multiple components delivered over multiple sessions and indirect effects on the outcomes

9. Why DSM make sense for HSR • DSMB has a consistent track record in other areas of helping PIs to better plan and implement major studies • Having DSM may speed up approval process from OPRR, IRBs, and other local institutions. • DSMB provides critical third opinion when asking a funder for a modification or additional funds in order to make the study work. • DSM (B) reminds the PI about key review criteria of influential journals.

10. Differences in DSM for 3 Types of Research Behavioral Phase III Multicenter Safety Interim analysis Integrity of data Efficacy AEs/SAEs Protocol and therapy adherence Data management Service Phase III Multicenter Interim analysis Integrity of data Safety Effectiveness Protocol and service adherence Data management AEs/SAEs Medication Safety Mortality Phase III Interim analysis Integrity of data FDA rq’d AEs/SAEs Efficacy Protocol adherence Data management Main Indications Main Foci of Review

11. Intimate PartnerViolence HIV Risk Drug Use IPV and HIV Among Drug-Involved Women Columbia University School of Social WorkSocial Intervention Group

12. HIV Prevention Messages • Few empirically-tested HIV prevention interventions exist for women who experience IPV • HIV and STI prevention efforts have consistently focused on two main messages: • practice mutual monogamy • use condoms • Many women lack the power to consistently engage in these behaviors and these behaviors may increase risk of IPV for some women

13. HIV Risk & IPV Among Drug-Involved Women • WHO has identified IPV as a leading risk factor for HIV infection among women • HIV & IPV are two overlapping global health problems affecting a significant number of drug-involved women • Rates of IPV among drug-involved women fall between 60%-80% • Over the last 15 years, HIV intervention researchers have begun to include information on IPV risk and protection in intervention trials tailored to drug-involved women, with special attention paid to protection and safety planning

14. Project WORTHAIMS of The Study • To design and test the efficacy of an HIV intervention with incarcerated women in New York City, in order to reduce HIV risk (increase condom use, reduce STIs, reduce number of sex partners, and reduce incidence of exchanging sex for money or drugs) • To improve self efficacy, communication and problem solving skills, help seeking, and access to social support.

15. Design • 146 drug-involved women incarcerated at Rikers Island jail. • Randomized two different arms: 3 two hour HIV/AIDS informational group sessions or 8 two-hour skills-building group sessions that met twice a week in jail followed by six booster sessions that occurred monthly in the community.

16. PerceivedVulnerability Self-Efficacy Relationship Safety Project WORTH Integrated Theoretical Model of HIV Behavioral Change Among Women in Jail Information and Raising Awareness of Co-Occurrence of IPV & Drug Use Development of Self-Regulatory, Problem-Solving, & Negotiation Skills • HIV Risk Reduction • Drug Risk Reduction Social Support & Access to Services

17. Demographics • Mean age 32.8 (SD=6.48) • Number of previous incarcerations (3.72) • Regular crack/cocaine use(90 days) (62%) • Regular heroin use (90 days) (22.8) • HIV positive (15.9%) • History of Partner Abuse (80%)

18. Safety Monitoring

19. Safety Concerns for Women Participating in HIV Research • Three HIV-related contexts have been found to increase women’s risk for IPV: • Attempts to negotiate condom use and/or refusal to have unprotected • Disclosure of HIV or STIs • Partner notification of STIs & HIV, which is mandated in certain states These contexts require consistent monitoring ensure women’s safety in participating in HIV intervention research:

20. Demographics Relevant to Safety Monitoring • 1/3 of the women required safety planning because they felt unsafe returning to their sex partner • 20% needed access to a battered women’s shelter • 25% had no place to live and were homeless

21. Safety in HIV Intervention Research:Monitoring Subject Behavior • Assess level of danger in all stages of the research, especially if a woman: • Decides to negotiate HIV risk reduction behavior with partner (asks to use condoms, says no to sex without condoms, uses the female condom without his knowledge) • Decides to disclose HIV status to partner • Sexual partners notified by Health Dept. of woman’s STI positive status

22. Safety in HIV Intervention Research:Monitoring Partner Behavior • Assess partner’s behaviors and woman’s perception of and actual IPV risks if a partner: • Follows her to drug treatment where she receives the intervention sessions • Prevents her from receiving services • Isolates her from her social network • Discovers her participation in the study and escalates IPV

23. Adverse Event (AE) • Any reaction, side effect, or untoward event that occurs during study participation • Includes study enrollment, intervention & follow-up • Involves subject or others • Reported by subject or is a clinically significant abnormal finding on physical exam or lab test • Therapeutic failures are not AEs!

24. Serious Adverse Event (SAE) • Any reaction, side effect, or untoward event occurring during study participation that is of a more serious nature than an AE • May involve subject or others • Defined uniquely for each protocol

25. FDA-defined SAEs • Death • Immediately life-threatening • Hospitalization • Prolongation of hospitalization • Permanent or substantially disabling • Birth defect

26. Project Worth Adverse Events(Anticipated) • IPV • Verbal/Physical Assault • Confidentiality Breach • FDA Defined SAE’s as Related to Study

27. Reported Adverse Events • Fighting with other inmates • 1/3 of the women reported experiencing IPV duirng community-based booster sessions • 10% of the women reported that disclosure of STIs or HIV led to IPV • Recidivism rate within 3 months was 30%

28. Reported Serious Adverse Events • 35% women hospitalized or used emergency room • 1 SAE study related hospitalization due to IPV resulting to negotiating condom use • 1 IPV resulting from refusal have unprotected sex

29. Safety Procedures During Intervention Implementation • Repeat risk assessment of IPV and partner behaviors during the intervention delivery • Assess safety of practicing skills learned in intervention with partner • Assess safety of bringing intervention materials home; provide option to leave materials with research staff • Emphasize confidentiality at each session • Provide safety planning, particularly when practicing negotiation skills • Safety planning for children/others

30. Safety Quality Control Procedures • Detailed training for safety assessment, planning and referral to services/treatment • Risks study participation poses to safety • Conducting safety assessment • How/when to provide safety planning and referrals (clinical expertise important) • Identify/respond to AEs • Referral protocols for IPV • Interventionists trained in negotiation/refusal skills ensure safety • PI certification of safety assessment/planning competencies

31. Safety Q&A Procedures • Adherence to safety measures monitored through: • Assessing fidelity: assessment/ safety protocols using process measures and tapes • Evaluation of QA procedures by external group (DSMB) • Proper reporting and follow-up of AE’s • Evaluation of risk-benefit each subject for study participation and apply specific criteria determine when risks outweigh benefits

32. Data Monitoring

33. Challenges • HSR focuses less on safety and efficacy, then on “effectiveness” relative to existing practice • HSR typically involves more heterogeneous populations, staff and sites • HSR has less control and needs to focus more on implementation and adherence/fidelity • HSR interventions typically involve multiple component interventions delivered over multiple sessions and indirect effects on the outcomes

34. Data Monitoring • Theory, Logical Model, Preliminary Data Support Hypotheses • Sample Size • Recruitment & Retention • Fidelity to Intervention • Accuracy, Completeness, Quality of Data • Primary/Secondary Endpoints

35. Issues Relevant to Data Monitoring • Confidentiality • Intervention fidelity • Difficulty locating subjects for follow-up

36. Data Monitoring Procedures • Community Advisory Board • Scientific Advisory Board • External Q&A Review Process • Manualized Protocols for Assessment, Intervention, Safety Planning • Extensive Staff Training • Development of Data Management System • Software monitored recruitment, enrollment, attendance, Q&A, adverse events • Web-based System Enter Process Measures

37. Data Q&A Procedures • Manualized Staff Training • PI Certification of Staff Competency on Assessment, Intervention, Safety Planning, Adverse Event Reporting Process • Taped Interviews, Intervention Sessions • External Q&A Review of 20% Session Tapes • Periodic External Review Case-flow Data

38. Federal Resources • NIDA DESPR DSM materials: • http://www.cjdats.org • NIDA’s general website: • http://165.112.78.61/funding/DSMBSOP.htlm • NIH & FDA: • http://grants2.nih.gov/grants/guide/notice-files/not99-107.html • http://www.fda.gov/cker/guidance/iche3.pdf • http://www.fda.gov/cder/guidance/1888dft.htm • http://www.fda.gov/medwatch/safety/3500.pdf

39. Books & Articles • Ellenberg, S.S., Fleming, T.R., & DeMets, D.L. (2002). Data monitoring committess in clinical trials: A Practical Perspective. West Sussex, England: John Wiley & Sons. • Fleming, T.R., & DeMets, D.L. (1993). Monitoring of clinical trials: Issues and recommendations. Controlled Clinical Trials, 14, 183-197. • Jennison, C. & Turnbull, B. (1990). Statistical approaches to interim monitoring of medical trials: A review and commentary. Statistical Science, 5(4), 299-317. • O’Brien, P.C., Fleming, T.R. (1979). A multiple testing procedure for clinical trials. Biometrics, 35, 549-556.

40. Other Resources • Consort guidelines: • http://www.consort-statement.org/Checklist.doc

41. Questions