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Interim Monitoring in Randomized Trials

Interim Monitoring in Randomized Trials. Which trials require monitoring? Why alter/stop a clinical trial early? Who should decide? What should be monitored? How often should you monitor? What statistical methods to use? How can a trial be altered? Fascinating examples.

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Interim Monitoring in Randomized Trials

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  1. Interim Monitoring inRandomized Trials • Which trials require monitoring? • Why alter/stop a clinical trial early? • Who should decide? • What should be monitored? • How often should you monitor? • What statistical methods to use? • How can a trial be altered? • Fascinating examples...

  2. Which Trials to Monitor • Trials in which there is a possibility • of unexpected harm from the intervention • of unexpected benefit from the intervention • that the question will not be answered • Increasingly viewed by the NIH as an independent advisory board • May not be feasible in small, short trials

  3. Why Stop a Trial Early? • Harm clearly demonstrated • Benefit clearly demonstrated • Not possible to demonstrate benefit • trial design flawed • low enrollment, high noncompliance, poor data, high drop-out • no difference between groups • Research question answered by another study

  4. Who Should Decide? • Sponsor • Investigators • Independent monitoring board, without conflict of interest • experts -? investigators • ethicists - ? representative of Sponsor • statisticians -? representative of NIH - ? lay persons

  5. What Should You Monitor? • Issues early in the trial • trial design • recruitment • compliance • loss to follow-up • data quality and timeliness • information from other studies

  6. What Should You Monitor? • Issues later in the trial • primary and secondary outcomes • clear benefit • clear harm • no conditional power • adverse events • side effects • subgroups

  7. How Often to Monitor? • Initial meeting several months before start-up • review protocol, classification of outcomes and adverse events, adjudication, etc • review and accept DSMB guidelines, statistical methods and meeting schedule • Subsequent meetings • often enough to achieve goals • not so often that there is no new data • depends on the duration of the trial and perceived risk of the intervention

  8. Confidentiality • DSMB usually does not share interim results with sponsors, investigators, ppts • Open session • DSMB, sponsor, investigators, NIH, FDA • recruitment, retention, data quality • overall findings • Closed session • DSMB members, + statistician • between group findings • discussion regarding modifications

  9. Statistical Methods for Interim Monitoring • Perform tests of significance and • stop the trial if any p<.05 • Simple, but wrong total testsoverall alpha 1 .05 2 .08 5 .14 10 .20 20 .35

  10. Interim Analyses in the CDP +2 +1 0 -1 -2 Z Value 10 20 30 40 50 60 70 80 90 100 Month of Follow-up

  11. Statistical Methods • Perform tests of significance and adjust the test-wise alpha • Bonferroni • Classical sequential methods • Group sequential methods • Pocock • Haybittle and Peto • O’Brien and Flemming • Lan and DeMets

  12. Group Sequential Methods • O’Brien - small i for early tests Flemming gradually increasing i N=5 interim tests;  = .05 initial 1=.00001; f=.041 • Lan-  spending function DeMets defined by N previous “looks” proportion of data/time between

  13. Alpha Spending LookZ-valueP-value 1 4.56 .00001 2 3.23 .0001 3 2.63 .009 4 2.28 .023 5 2.04 .041

  14. Symmetric Stopping Boundaries 6 4.56 3.23 2.63 4 2.28 2 2.04 Z Stop for Harm 0 Stop for Benefit 1st Look 2nd Look 3rd Look 4th Look 5th Look -2 -2.04 -2.28 -4 -2.63 -3.23 -4.56 -6

  15. Conditional Power Compute p(reject Ho given data so far) Deterministic Curtailed Sampling • assume all future outcomes in treated • assume all future outcomes in placebo Stochastic Curtailed Sampling • assume Ho true • assume Ha true

  16. How Can a Trial Be Altered? • Early alterations • change entry criteria • increase sample size • change outcome • adjust dose • Goals of these changes • make the trial successful (definitive result) • change original protocol as little as possible • Timely, high quality data crucial

  17. How Can a Trial Be Altered? • Later alterations • increase duration of the trial • modify the trial protocol • stop one arm of the intervention • terminate high risk groups • add safety measures • others • terminate the trial early

  18. Interim Monitoring • NOT simply a statistical issue • Must weigh: • Possible baseline differences in groups • Possible bias in assessment of outcome • Impact of missing data • Differential co-intervention or noncompliance • Internal consistency of findings • Impact of early termination on medical practice and public health

  19. Nuts and Bolts • Board chosen early • Data Monitoring Plan • board members • variables and analyses • frequency of monitoring • statistical methods • guidelines for decisions • Timely, accurate and complete data

  20. Coronary Arrhythmia Suppression Trial • 1727 of planned 4400 subjectsafter MI with ventricular ectopy • Flecainide, encainide or moricizine vs. pbo • Mean follow-up 1 year of planned 5 years • Outcomes - mortality from arrhythmia, total mortality

  21. Coronary Arrhythmia Suppression Trial OutcomeF/EPlacebop N randomized 730 725 Arrhythmic death 33 9 .0006 Total death 56 22 .0003

  22. Beta-blocker Heart Attack Trial • Subjects - 3,837 persons 5-21 days after MI • Intervention - propranolol 180-240mg/day vs placebo • Follow-up - 40 of planned 48 months • Outcome - mortality

  23. Beta-blocker Heart Attack Trial AnalysesMonth Deaths Z Critical Value 1 11 56 1.68 5.88 2 16 77 2.24 5.04 3 21 126 2.37 3.79 4 28 177 2.30 3.19 5 34 247 2.34 2.64 6 40 318 2.82 2.30 7 48

  24. Coronary Drug Project • Subjects - 8,341 men post-MI • Interventions - estrogen 2.5 and 5.0 mg QD dextrothyroxine 6 mg QD clofibrate 1.8 gm QD niacin 3.0 gm QD placebo • Follow-up - 1.5 to 2.5 of planned 5 years • Outcomes - death, MI, cancer, VTE

  25. Coronary Drug Project CEE 5 mgPlaceboRR ( n=1,119)(n=2,789) CHD event 11.0% 7.5% 1.5 PE or DVT 3.5% 1.5% 2.3* Total mortality 9.7% 8.2% 1.2 JAMA, 1970

  26. Coronary Drug Project • Low-dose CEE (2.5 mg/d) stopped after 2.5 years for similar findings • D-thyroxin found to increase death rate at 3 years in men with abnormal baseline EKG • D-thyroxin stopped in all men with abnormal baseline EKG

  27. HERS DSMB ReportMonitoring for VTEs . . . 6 . . . . . 4 . Stop for Harm Stop for Benefit 2 . Z 0 6 mo 1.5 yr 2.5yr 3.5 yr End -2 -4 -6

  28. HERS DSMB ReportMonitoring for CHD Death 6 . . . 4 . Stop for Harm . Stop for Benefit . 2 . . . . Z 0 6 mo 1.5 yr 2.5yr 3.5 yr End -2 -4 -6

  29. WHI - Overall Risk and Benefit Harm% Change in Risk • CHD +29% • Stroke +41% • Breast cancer +26% • Pulm. embolus +2.1X Global Index Benefit • Hip fracture -34% • Colorectal cancer -37%

  30. Letrozole for Breast Cancer • In early stage ER+ breast cancer • 5 years of tamoxifen reduces recurrence • longer treatment LESS effective • tamoxifen may have estrogenic activity • Treatment with letrozole after tamoxifen might reduce recurrence

  31. Letrozole after Tamoxifen Trial • Subjects - postmenopausal women treated with 4 to 6 years of adjuvant tamoxifen for breast cancer • Intervention - letrozole 2.5 mg QD • Follow-up - planned 5 years • Outcomes - disease free survival overall survival quality of life safety Goss, NEJM, 2003

  32. DSMB Guidelines • Expect 515 events (recurrent cancer) • Review safety twice yearly • Interim analysis twice, after • 171 (1/3 expected total) events • 342 (2/3 expected total) events • Lan and DeMets -spending function with O’Brien-Flemming boundaries

  33. First Interim Analysis • 5187 women enrolled (planned 4800) • Mean 2.4 yrs of follow-up (planned 5) • 207 events (40% of expected) LetrozolePlacebo RH P-value N events 75 132 .57 .00008 4-year DFS 93% 87% .001 Deaths 31 42 4-year S 96% 94% .76

  34. First Interim Analysis LetrozolePlaceboP-value Flushes 47% 40% <.001 Arthritis 6% 3% <.001 Arthralgia 21% 17% <.001 Osteoporosis 5.8% 4.5% 0.07 Fracture 3.6% 2.9% 0.24 CVD events 4.1% 3.6% 0.40

  35. Issues • How long does benefit last? • Does benefit strengthen over time? • Does treatment reduce mortality? • Do findings support 5 years of treatment with letrozole? • Were side effects underestimated? • How will other trials be affected?

  36. Stopping Trials • Stopping for harm often not adequately planned in advance • harm goes on too long • stopping boundaries unreasonable • Stopping for benefit raises issues because less data obtained on: • long-term benefit • side effects

  37. Summary - Interim Monitoring • Interim monitoring very important • Should be planned in advance • Should be performed well • Any change in trial protocol should be carefully considered, weighing many issues

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