Association of Health Behaviors and Quality of Life in Lymphoma Survivors

Priyanka Pophali, Melissa C. Larson, Dennis P. Robinson, Cristine Allmer, Allison C. Rosenthal, Umar Farooq, Brian K. Link, Matthew J. Maurer, James R. Cerhan and Carrie A. Thompson


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Background: Lymphoma survivors are at risk for long term and late effects which may negatively impact quality of life (QOL). Few studies have assessed the impact of change in health behaviors (physical activity (PA), alcohol and smoking) on QOL, specifically in lymphoma survivors.

Methods: Patients were prospectively enrolled <9 months of diagnosis into the Lymphoma SPORE Molecular Epidemiology Resource cohort. At baseline and 3-year follow-up (FU3), patients self-reported QOL, smoking, alcohol use and PA. At FU3, survivors reported change in health behaviors since diagnosis. The Godin Leisure Score Index (LSI) was calculated as a measure of PA (Pophali et al. ASH 2017); modeled by tertile. QOL was measured via FACT-G; the total and sub-scales [emotional (EWB), functional (FWB), physical (PWB), and social/family well-being (SFWB)] scores were transformed to a 0-100 scale. Patients who completed <80% of QOL questions were excluded. The association of QOL with health behaviors was evaluated using Kruskal-Wallis test (categorical) and Spearman's rank correlation (continuous).

Results: At baseline, 2805 participants were evaluable for QOL of which 2025 were evaluable at FU3. The median age at diagnosis was 62 (IQR 52-69) years. Majority were males (N=1148, 56.8%), with advanced stage III-IV disease (N=941, 62%) and ECOG performance status <2 (N=1935, 96%).

At baseline, smoking status was current (N=237), former (N=802), never (N=1310) or not available (NA, N= 456). Current smokers had a significantly lower median QOL scores compared to former and never smokers for EWB (75 vs 79 vs 79, p<0.01), FWB (71 vs 79 vs 79, p<0.01), PWB (86 vs 89 vs 89, p=0.02), SFWB (86 vs 90 vs 89, p=0.02) and total FACT-G (67 vs 82 vs 82, p<0.01). The median number of pack years smoked among current &former smokers was 15.6 (range 0.5-126). There was a significant negative correlation of pack years smoked with FWB (p=0.05), and total FACT-G (p=0.04). At FU3, current smokers had significantly lower median scores compared to former and never smokers for FWB (80 vs 86 vs 86, p=0.01), PWB (89 vs 93 vs 93, p<0.01) and total FACT-G (82 vs 86 vs 87, p<0.01). EWB (83 vs 88 vs 88, p=0.12) and SFWB (83 vs 86 vs 86, p=0.12) were also lower than never and former smokers but not statistically significant. Smoking status was decreased (N=30), increased (N=0) and unchanged (N=1439) at FU3. There was no association of change in smoking with change in QOL.

At baseline, alcohol use status was current (N=1189), former (N=506), never (N=518) and NA (N=592). Current alcohol users had the highest FWB (79 vs 75 vs 75, p<0.01) vs former and never users. Former users vs current and never users had the lowest PWB (86 vs 89 vs 89, p<0.01), SFWB (88 vs 89 vs 92, p<0.01) and total FACT-G (80 vs 83 vs 82, p<0.01). EWB was similar in all 3 groups. Among current & former alcohol users, the average number of drinks/week was 3.4. There was no association of the number of drinks/week with QOL except positive correlation with PWB (p=0.01). At FU3, alcohol use was reported as increased (N=40), decreased (N=312) and no change (N=875). There was no association between change in alcohol use and change in QOL.

At baseline, participants with PA in the high vs low LSI tertile had significantly better median scores for FWB (79 vs 75, p=0.01), SFWB (93 vs 89, p<0.01) and total FACT-G (83 vs 82, p<0.01). At FU3, participants in the high vs low LSI tertile had significantly better scores on all subscales and total FACT-G with a significant positive correlation between the continuous LSI and QOL (FACT-G total and subscales). PA was reported as increased (N=107), decreased (N=394) and no change (N=495). There was a significant association of increase in PA with change in PWB (p<0.01), EWB (p=0.01), FWB (p<0.01) and total FACT-G (p<0.01) from baseline to FU3, but not with change in SFWB (p=0.06).

In a sensitivity analysis, QOL was modeled for health behaviors in the subset of patients with QOL assessed prior to treatment; results were consistent with the QOL in all patients.

Conclusions: Health behaviors in lymphoma survivors are significantly associated with QOL: better QOL is associated with not smoking, more PA, and moderate alcohol use. Current alcohol consumption, as opposed to former alcohol use, may be related to overall health status. An increase in PA after lymphoma diagnosis is associated with an increase in the QOL. Thus, modification of health behaviors has the potential to impact QOL in lymphoma survivors.

Disclosures Cerhan: Celgene: Research Funding; Nanostring: Research Funding; Jannsen: Other: Scientific Advisory Board.

  • * Asterisk with author names denotes non-ASH members.

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