The Analysis and Interpretation of Pain Clinical Trial Outcomes: Enhancing Understanding

1. The Analysis and Interpretation of Pain Clinical Trial Outcomes:Enhancing Understanding John T. Farrar, MD, PhD University of Pennsylvania

2. Surrogate Outcomes Only three “real” outcomes • Birth • Death • Quality of life

3. Changing the State of the Brain What do you see?

4. Why Do We Care • RCTs - important for most medical therapy • Did not need an RCT for introduction of penicillin • Pneumococcal pneumonia • No penicillin - Last week 9/10 people died • With penicillin – This week 1/10 people died • Corollary – if you identify the right group, measurement and design issues statistics will be less controvertial

5. Outline of the Presentation • Measurement must be appropriate • Handling of missing data is important • Part 1: How do patients report pain • Part 2: Analysis • Part 3: Interpretation

6. Pain is a Subjective Experience • No “objective” direct measure • Not easy to relate to an underlying neurologic process in an individual • Depend on subjects to accurately report their experience • Creates inter-person variation in the reporting of pain that is unavoidable • Creates observer discomfort about the validity of the measure

7. Pain Measures - Intensity Scales 0__1__2__3__4__5__6__7__8__9__10 |____________________________________________| | | Least Worst None Mild Moderate Severe Excruciating  Intra-person reliability – Good Inter-person reliability – Poor

8. How do Patients DecideIf a Treatment is Useful Does the treatment make my symptoms better now? Are there any side-effects? Is the pain relief “good enough”? >>>> Am I better overall? >>>> Should I take something else?

9. Global Rating of Quality of Life Overall how would you rate your quality of life: over the last ______: 0 1 2 3 4 5 6 7 8 9 10 Worst Best It can be it can be

10. Global Change in Quality of Life How has your quality of life changed over the last ______: (or - since the last _____:) Very Much Worse Very Much better No change Much Worse A little worse A little better MuchBetter

11. Another View on Scales

12. How Do Patients Use a Numeric Scale(Acute Pain) • Study data: Randomized clinical trial of oral trans-mucosal fentanyl versus placebo • Method: Re-analysis of data set stratified on baseline pain intensity score • Population: 89 cancer pain patients with acute breakthrough pain • Results =>

13. Data Collection Instrument • Baseline • Pain Intensity 1_2_3_4_5_6_7_8_9_10 • At 15, 30, 45 and 60 minutes • Pain Intensity 1_2_3_4_5_6_7_8_9_10 • Pain Relief 0 (none) 1(slight) 2(mod.) 3(lots) 4(comp.) • Second rescue medication - Time________ • Overall Performance • 0 (none) 1(slight) 2(moderate) 3(lots) 4(complete)

14. Raw Change in Pain Intensity Compared to Global Performance Scale Global Performance Scale

15. Percent Change in Pain Intensity Compared to Global Performance Scale Global Performance Scale

16. How Do Patients Use a Numeric Scale(Chronic Pain) • Study data - RCTs of pregabalin in multiple diseases • Method – Compared measured pain intensity (0-10 NRS) and patients global impression of change (PGIC) • Population - Data on 2,724 subjects from 10 clinical trials of diabetic neuropathy (3), postherpetic neuralgia (3), chronic low back pain (2), fibromyalgia (1) and osteoarthritis (2).

19. Clinically Important Differencesfor the 0-10 NRS • Used the global response levels as the metric of a clinical importance response • Compared change in 0-10 NRS measure over time to this standard • Determined the clinically important change cut-off by calculating: • Sensitivity, specificity and accuracy • Receiver Operator Characteristic (ROC) analysis

20. Studies of Duloxetine • Secondary analysis of 5 studies • Diabetic neuropathy – 3 • Fibromyalgia – 2 • Total number of patients – 1600 • Study period – 12 weeks • Pain measures – 0-10 NRS • Worst, least, average • Patient global impression of change

22. Receiver Operator Response Curve Percentage Pain Intensity Difference

23. Clinically Important Values

24. Part 1: Conclusion • Patients use the 0-10 NRS scale primarily as a percent scale and is best analyzed as a percent change from baseline pain • A 30-35% improvement on the 0-10 NRS pain intensity scale is a reasonable cut-off point for a clinically important change

25. Two Groups Randomized:Both centered at 20% change at end of the study Percent change from baseline

26. Actually Bimodal Distribution Percent change from baseline

27. Actually Bimodal Distribution Percent change from baseline

29. Study Efficiency Mean vs Dichotomous Analysis Efficiency = 1.145 (T-test N=30, Chi-sq N=26) Mean of Control Group and Low Probability Responders = 15% Mean of the Treated Group = 34%; Cut-off = 33%

30. Group Mean Results – PIDOral Transmucosal Fentanyl Citrate (OTFC) p<.001 at all time points Farrar JT, et al Oral transmucosal fentanyl citrate: randomized, double-blinded, placebo-controlled trial for treatment of breakthrough pain in cancer patients. Journal of the National Cancer Institute 1998; 90(8): 611-6

31. OTFC Study Outcomes: Relative Risk Comparison At 60 minutes

32. OTFC Looked at Density Plots

33. Density FunctionCumulativeDistributionFunction

34. OTFC Placebo Proportion of Responders(at different cut off points - for 30 minutes) Cumulative Distribution of Responders Graph Proportion of Responders Percentage Pain Intensity Difference

35. Mean Value Does Not Provide a Unique Answer to the Clinical Question • Mean value for the change in pain intensity over time is 10%. This would be observed if: • 1) every patient in the treatment group improved by 10%, or • 2) if 50% of the treatment group got better by 20% and 50% had no improvement, or • 3) if 50% of the treatment group got better by 40% and 50% got worse by 20%.

36. FDA Primary Data Analysis • Data source • Neuropathic pain RCTs (n=15) • Indications • Post-herpetic neuralgia (n=7) • Diabetic peripheral neuropathy (n=8) • Pharmaceuticals • Pregabalin (n=11) • Gabapentin (n=2) • Duloxetine (n=2) • Primary outcome measure • Change in 0-10 NRS pain score

37. Representative Data

40. Method • Each RCT was analyzed using absolute and percent change of the mean pain score. • List of the analytic methods compared for each trial for between group analyses (active treatment vs. placebo) • T-test • Wilcoxon rank sum test • Kolmogorov-Smirnov test • ROC based - AUC comparison • Ordinal logistic regression • Log rank

41. KS = Kolmogorov-Smirnov • OL = Ordinal logistic regression • LR = Log rank • T = T-test with equal variance • RS = Wilcoxon rank sum test • ROC = AUC comparison

42. Rank Totals • T = T-test with equal variance • RS = Wilcoxon rank sum test • ROC = AUC comparison • KS = Kolmogorov-Smirnov • OL = Ordinal logistic regression • LR = Log rank

43. Conclusions • Tools for measuring pain have high inter-person variability and lower intra-person variability • Mean values do not provide a unique answer to the clinical question of how many people get better • Responder analysis accurately reflect the number of people in each treatment group that reach a level of change in that study

44. Conclusions (cont) • To the degree that the test group is an accurate representation of the general population the response rates in the treated group will reflect what the clinician is likely to see, regardless of the reason for the response. • Both mean value and the responder analysis provide useful information and should be presented.

45. THANK YOU Research Group Additional Collaborators Robert Dworkin Dennis Turk Nathaniel Katz Michael Rowbotham Russel Portenoy John Messina Michael Poole Mitchell Max Jesse Berlin • Chris Rowan • Kevin Haynes • Andrea Troxel • Brian Strom • Rosemary Polomano