Longitudinal Change in Fatigue, Depression, Sleep, and Daily Activity in Patients Undergoing Chemotherapy for Gynecologic Cancer

Transcription

1 Longitudinal Change in Fatigue, Depression, Sleep, and Daily Activity in Patients Undergoing Chemotherapy for Gynecologic Cancer Heather Jim, Ph.D. Leigh Anne Faul, Ph.D. Marcela Peres Sachin Apte, M.D. Paul Jacobsen, Ph.D. Moffitt Cancer Center, Tampa FL

2 Symptom Clusters During Chemotherapy Fatigue is common and highly correlated with depression Why?

3 Symptom Clusters During Chemotherapy Fatigue is common and highly correlated with depression Why? Fatigue may contribute to depression Prospectively predicts 11% [Visser & Smets, Supp Care Cancer 1998; 6:101-8]

4 Symptom Clusters During Chemotherapy Fatigue is common and highly correlated with depression Why? Fatigue may contribute to depression Prospectively predicts 11% [Visser & Smets, Supp Care Cancer 1998; 6:101-8] Depression may contribute to fatigue Prospectively predicts 4% [Visser & Smets, Supp Care Cancer 1998; 6:101-8]

5 Symptoms During Chemotherapy Fatigue is common and highly correlated with depression Why? Fatigue may contribute to depression Prospectively predicts 11% [Visser & Smets, Supp Care Cancer 1998; 6:101-8] Depression may contribute to fatigue Prospectively predicts 4% [Visser & Smets, Supp Care Cancer 1998; 6:101-8] Additional variable(s) may contribute to both Sleep/activity patterns

6 Sleep/Activity Patterns The rhythmicity of sleep and physical activity behaviors Measured with actigraph worn on nondominant wrist Generates activity counts per minute Calculates sleep and wakefulness, validated by polysomnography

7 Sleep/Activity Patterns The rhythmicity of sleep and physical activity behaviors Measured with MiniMitter Actigraph-Score worn on non-dominant wrist

8 Sleep/Activity Patterns The rhythmicity of sleep and physical activity behaviors Measured with MiniMitter Actigraph-Score worn on non-dominant wrist

9 Study Aims To examine longitudinal changes in weekly fatigue, depression, and sleep/activity patterns To explore cascade model of prospective associations between daily symptoms Hypothesis: sleep/activity associated with later fatigue, fatigue associated with later depression

10 Study Design The week before and the week after the first three chemotherapy cycles: Actigraphic monitoring Weekly summary measures of fatigue and depression at the end of each week Daily bedtimes and rising times Current fatigue and depression daily at 10 am, 2 pm, and 6 pm Week: Day: Clinic 1 Clinic 2 Clinic 3

11 Calculation of Weekly Variables Depression/Fatigue Depression: Center for Epidemiological Studies Depression (CESD; 0 to 60 scale, lower better) Fatigue: Fatigue Symptom Inventory (FSI; most fatigue, 0 to 10 scale, lower better) Actigraphy: MiniMitter Actiwatch Score Nighttime activity: weekly average of activity counts during rest periods (lower better) Daytime percent sleep: weekly average of percent of time categorized by actigraph as sleep during the day (lower better) Log-transformed prior to analysis

12 Calculation of Daily Variables Depression/Fatigue Weekly most: the single highest rating over a oneweek period (of 21 ratings; lower better) Daily most: the single highest rating over one day (of 3 ratings; lower better) Actigraphy Nighttime activity: average activity count during single rest period (lower better) Daytime percent sleep: percent of time categorized as sleep by actigraph during single day (lower better)

13 Eligibility Diagnosed with gynecologic cancer Scheduled to receive intravenous platinumbased chemotherapy at Moffitt No previous chemotherapy in past two months Age 18 or older Able to speak and read English Free of observable or documented psychiatric or neurological disorders that would interfere with study participation Able to provide informed consent

14 Status of Current Study Recruitment and data collection ongoing Goal: 80 participants Preliminary findings from first 40 participants

15 Sample Characteristics (n=40) Age Mean: 64 (range: 38-86) Race 90% Caucasian Ethnicity 93% non-hispanic Education 15% completed college Marital status 63% married Cancer Type Cervical 5% Endometrial 21% Ovarian 49% Uterine 12% Peritoneal 5% Fallopian 7% Received previous chemo 42% (mean 2 courses, range 1-7) Prescription Meds Antidepressants 24% Sedatives 59%

16 Changes in Symptoms by Week

17 Changes in Symptoms by Week

18 Changes in Symptoms by Week RM ANOVA F CESD Depression 5.59** FSI Fatigue 4.77** Nighttime Activity 4.78** Daytime Percent Sleep 3.56* Significant Differences by Time Point Pre Chemo 1 < Post Chemo 1 Pre Chemo 3 < Post Chemos 2, 3 Pre Chemo 1 < Post Chemos 1, 2, 3 Pre Chemo 2 < Post Chemo 1 Pre Chemo 3 < Post Chemo 1 Pre Chemo 1 < Post Chemos 1, 2 Pre Chemo 3 < Post Chemo 1 Pre Chemo 1 < Post Chemos 1, 2, 3 Pre Chemo 2 < Post Chemos 1, 2, 3 *p<.05, **p<.01

19 Changes in Symptoms By Day

20 Changes in Symptoms By Day

21 Changes in Symptoms By Day

22 Correlations: Chemo 3 depress 3 depress 4 depress 5 Nighttime activity 3 Nighttime activity 4 Nighttime activity 5 fatigue 3 fatigue * **.15 fatigue 5.58**.58**.49** depress 3 depress depress 5 *p<.05, **p<.01

23 Correlations: Chemo 3 depress 3 depress 4 depress 5 Daytime sleep 3 Daytime sleep 4 Daytime sleep 5 fatigue 3 fatigue * **.15 fatigue 5.58**.58**.49** depress 3 depress *.44*.48* depress 5 *p<.05, **p<.01

24 Conclusions: Weekly Data Cyclical weekly pattern of symptoms Greatest fatigue, depression, nighttime activity, and daytime sleep in weeks after chemotherapy, some recovery prior to next chemo

25 Conclusions: Daily Data Daily prospective associations between symptoms at days 3-5 post-chemo 3 Fatigue associated with later depression and daytime sleep No associations between nighttime activity, fatigue, and depression

26 Conclusions: Daily Data Daily prospective associations between symptoms Fatigue associated with later depression and daytime sleep No associations between nighttime activity, fatigue, and depression Patients not fatigued due to nighttime sleep disturbance Results similar when controlling for anti-depressant and sedative prescriptions

27 Conclusions: Daily Data Daily prospective associations between symptoms Fatigue associated with later depression and daytime sleep No associations between nighttime activity, fatigue, and depression Patients not fatigued due to nighttime sleep disturbance Results similar when controlling for anti-depressant and sedative use Preliminary evidence for cascade model with fatigue as early symptom Contrary to hypothesis of sleep/activity patterns as early symptom

28 Future Research Directions Conduct analyses with full sample for additional power to detect changes Prospective prediction of residualized change in symptoms Biological mechanisms underlying fatigue, e.g. anemia, pro-inflammatory cytokines

29 Acknowledgements Moffitt Faculty/Postdocs Paul Jacobsen, Ph.D. Sachin Apte, M.D. Ann Chen, Ph.D. Leigh Anne Faul, Ph.D. William Roberts, M.D. Brent Small, Ph.D. Robert Wenham, M.D. Study Coordinators Angelina Fink Marcela Peres Pam Reiersen Angela Stringham Survey Methods Core Gwen Quinn, Ph.D. Lindsay King Sashanna Roman Kristin Tillery Renelle Whyte Funding: NCI R03CA