1. Longitudinal Assessment of Cancer-related Fatigue: When to use it? What does it add? Charles S. Cleeland, PhD Department of Symptom Research The University of Texas M. D. Anderson Cancer Center

2. Fatigue Related To Cancer Treatment  Severe fatigue may be an issue for a defined period of time – treatment and posttreatment  Fatigue related to cancer treatment is: a major problem for cancer patients a major problem for cancer patients a major toxicity of cancer treatment a major toxicity of cancer treatment a reason for treatment delays or discontinuation a reason for treatment delays or discontinuation  Treatment-related fatigue is an excellent target for a wide variety of interventions

3. Measurement Issues  Need for multiple measurements across a specified period  Calls for use of a minimal number of items  Need for methods of analysis that portray the critical time element  Missing data can be a problem

4. Fatigue and Pain under Cancer Therapies Other MDASI Items: Sleep, Distress, Shortness of Breath NSCLC Post Thoracic Surgery Weeks AML/MDS Allo-HSCT Days NSCLC Chemo-radiation Days GI Chemo-radiation Days

5. Top 4 Symptoms in Head and Neck Cancers Severity Weeks 0 2 4 6 8 10 taste food dry mouth fatigue mucus XRT Only (n=46) Burkett et al, 2007, unpublished data Severity END012345 Tx 78910 Weeks 0 2 4 6 8 10 012345 Tx 78910END Chemo + XRT (n=48)

6. Example: Fatigue Severity Across Time Fatigue Severity 012345End of Tx 78910 Time Point 0 1 2 3 4 5 6 7 ChemoXRT (n=48) XRT only (n=46) Pre/Post Outcome Measures Benefits Ease of data gathering No need keep track of patients across a treatment regimen Less resource utilization (e.g., staff burden) Drawbacks Limited in scope Lose impact of symptom between assessments Partial picture of symptom expression t (93)= -.032, p =.97 Burkett et al, 2007, unpublished data x= 2.04 x= 2.02 PRE POST

7. Fatigue Area Under the Curve (AUC): Effectively Combining Severity and Time Longitudinal Data Frequent assessment is invaluable Enables tracking of symptoms across treatment regimens Provides picture of symptom change as the treatment and recovery progresses Area Under the Curve Single value represents time and symptom severity Compares groups using standard statistical methods Compensates for missing data Burkett et al, 2007, unpublished data 0 10 20 30 40 50 60 Baseline Week 2Week 3Week 4Week 5 End of Tx Week 7Week 8Week 9 Week 10 Timepoint Average Fatigue AUC CXRT (n=48) XRT Only (n=46) t (93)=6.41, p =.04 *

8. Summary  Longitudinal measurement using a single item can describe a symptom over a critical time period  We need different ways of thinking about summarizing the data  Frequent measurement is a challenge Diaries have inherent problems Diaries have inherent problems ePRO may be the best way to capture ePRO may be the best way to capture