David Cella & David T. Eton, Evanston Northwestern Healthcare & Northwestern University

1. Clinically Meaningful Change and Clinical Relevance of the Functional Assessment of Cancer Therapy-Lung: Analysis of ECOG 5592 Data David Cella & David T. Eton, Evanston Northwestern Healthcare & Northwestern University Diane L. Fairclough, AMC Cancer Research Center Philip Bonomi, Rush-Presbyterian St Luke’s Medical Center David H. Johnson, Vanderbilt University Anne Heyes, Cheryl Silberman, & Mike Wolf, AstraZeneca

2. Acknowledgements • National Cancer Institute (grants CA 23318, CA66636, CA21115, CA 17145, CA 49957) • AstraZeneca Pharmaceuticals

3. What is a (clinically) meaningful change? • Meaningful change: A difference or change in score on a health-related quality of life (HRQoL) questionnaire that is important to the involved person or people • “Clinically” meaningful corresponds to a clinically important difference or change in patient status.

4. How are CMCs determined? • Anchor-based methods - Anchoring score differences to traditional clinical parameters (e.g., tumor response, time to progression) • Distribution-based methods - Standard deviation - Standard error of measurement

5. The Present Study • Purpose: To determine CMCs in two score aggregates of the FACT-L (the Lung Cancer Subscale & the Trial Outcomes Index) in advanced non-small cell lung cancer patients. • Data source: Eastern Cooperative Oncology Group study 5592

6. Sample Characteristics E5592 (N = 573) • 63% Female; 37% Male • Mean age = 60 years; range = 32-81 years • 87% Caucasian; 10% Afric-Am; 3% Other • 81% Stage IV; 19% Stage IIIB • Baseline Performance Status: - 68% ECOG 1 - 32% ECOG 0 • Treatment Arm: - 34% cisplatin + etoposide - 33% cisplatin + paclitaxel (high dose) + g-csf - 33% cisplatin + paclitaxel (std dose)

7. HRQoL Assessment • The Functional Assessment of Cancer Therapy - Lung (FACT-L) Questionnaire - Physical well-being (PWB) (7 items) - Social/family well-being (SWB) (7 items) - Emotional well-being (EWB) (5 items) - Functional well-being (FWB) (7 items) - Lung Cancer Subscale (LCS) (7 items) - Trial Outcome Index (TOI) (21 items)

8. HRQoL Assessment • The Functional Assessment of Cancer Therapy - Lung Questionnaire (FACT-L) - Lung Cancer Subscale (LCS): 7 items - Trial Outcome Index (TOI): 21 items • Baseline & 12-week assessments used

9. Anchor-based methods - Independent samples t-tests (baseline) - One-way ANCOVAs on changes in HRQoL over time (controlling for baseline clinical factors) • Distribution-based methods - 1/3 and 1/2 standard deviation (SD) - Standard error of measurement (SEM) SEM = SD (1 - reliability)1/2 Data Analysis

10. Mean (SD) differencesin baseline clinical indicators

11. Baseline to 12-week change in Lung Cancer Subscale score (best overall response) CR/PR > PD

12. Baseline to 12-week change inLung Cancer Subscale score(time to progression: < 116 days vs. > 116 days)

13. Baseline to 12-week change in TrialOutcome Index score (best overall response) CR/PR > PD

14. Baseline to 12-week change inTrial Outcome Index score(time to progression: < 116 days vs. > 116 days)

15. Distribution-based criteriaof clinical significance

16. Summary Based on anchor & distribution-based methods... • A 2 to 3 point score difference approximates a CMC on the LCS of the FACT-L • A 5 to 6 point score difference approximates a CMC on the TOI of the FACT-L

17. E5592 - Shortness of Breath(Higher score corresponds to worse function) Very much Not at all

18. E5592 - Weight loss(Higher score corresponds to worse function) Very much Not at all

19. E5592 - Good appetite(Higher score corresponds to better function) Very much Not at all

20. Practical Implications • Determine sample size in clinical trials • Evaluate treatment efficacy

21. Summary • Baseline HRQL predicts outcome in advanced NSCLC • Longitudinal HRQL adds to the prognostic ability of baseline HRQL • Physical well-being, functional well-being and pt. reported symptoms are reliable predictors of outcome in advanced NSCLC

22. HRQL as a Predictor of Outcome

23. The Present Study • Data source: Eastern Cooperative Oncology Group study 5592 • Objectives (3) - Show that HRQL predicts outcome - Show that changes in HRQL add to the prediction of outcome - Show that longitudinal HRQL data have clinical import

24. HRQoL Assessment • The Functional Assessment of Cancer Therapy - Lung Questionnaire (FACT-L) - Physical well-being (PWB) (7 items) - Social/family well-being (SWB) (7 items) - Emotional well-being (EWB) (5 items) - Functional well-being (FWB) (7 items) - Lung Cancer Subscale (LCS) (7 items) - Trial Outcome Index (TOI) (21 items) • Baseline & 6-week assessments used

25. Outcomes • Time to disease progression • Survival duration

26. Data Analysis • Spearman correlation () • Cox proportional hazards regression • Survival curves

27. Correlations () of Baseline HRQL & Outcome *** p < .001

28. Stepwise Cox Regression for Disease Progression

29. Stepwise Cox Regression for Survival

30. Does change in HRQL predict outcome?

31. 1.0 .8 .6 .4 .2 0.0 0 200 400 600 800 Time to progression based on Trial Outcome Index scores -2 Log likelihood = 2940.24 Overall 2 (7) = 67.67, p<.001 Hi baseline - improve Hi baseline - decline Proportion not progressing Lo baseline - improve Lo baseline - decline Time to progression in days

32. Survival duration based on Physical Well-Being scores -2 Log likelihood = 3058.81 Overall 2 (8) = 67.21, p<.001 Hi baseline - improve Hi baseline - decline Proportion surviving Lo baseline - improve Lo baseline - decline Survival post-randomization in days

33. Summary • Baseline HRQL predicts outcome in advanced NSCLC • Longitudinal HRQL adds to the prognostic ability of baseline HRQL • Physical well-being, functional well-being and pt. reported symptoms are reliable predictors of outcome in advanced NSCLC

34. Practical Implications • Patient stratification in clinical trials • Treatment planning & adjustment

35. Our next step: ALCaMP-2Real-time (weekly) assessment of all lung cancer patients beginning chemotherapy