Brian D Gonzalez1, Sharon L Manne2, Jerod Stapleton2, Shannon Myers-Virtue3, Melissa Ozga4, David Kissane4,5, Carolyn Heckman6, Mark Morgan7. 1. Rutgers Cancer Institute of New Jersey, 195 Little Albany Street, New Brunswick, NJ, 08903, USA. Brian.Gonzalez@Rutgers.edu. 2. Rutgers Cancer Institute of New Jersey, 195 Little Albany Street, New Brunswick, NJ, 08903, USA. 3. Temple University School of Dentistry, Philadelphia, PA, USA. 4. Memorial Sloan Kettering Cancer Center, New York, NY, USA. 5. Monash University, Clayton, Australia. 6. Fox Chase Cancer Center, Philadelphia, PA, USA. 7. University of Pennsylvania School of Medicine, Philadelphia, PA, USA.
Abstract
PURPOSE: The course of quality of life after diagnosis of gynecologic cancer is not well understood. We aimed to identify subgroups of gynecologic cancer patients with distinct trajectories of quality of life outcomes in the 18-month period after diagnosis. We also aimed to determine whether these subgroups could be distinguished by predictors derived from Social-Cognitive Processing Theory. METHODS:Gynecologic cancer patients randomized to usual care as part of a psychological intervention trial (NCT01951807) reported on depressed mood, quality of life, and physical impairment soon after diagnosis and at five additional assessments ending 18 months after baseline. Clinical, demographic, and psychosocial predictors were assessed at baseline, and additional clinical factors were assessed between 6 and 18 months after baseline. RESULTS: A two-group growth mixture model provided the best and most interpretable fit to the data for all three outcomes. One class revealed subclinical and improving scores for mood, quality of life, and physical function across 18 months. A second class represented approximately 12 % of patients with persisting depression, diminished quality of life, and greater physical disability. Membership of this high-risk subgroup was associated with holding back concerns, more intrusive thoughts, and use of pain medications at the baseline assessment (ps < .05). CONCLUSIONS:Trajectories of quality of life outcomes were identified in the 18-month period after diagnosis of gynecologic cancer. Potentially modifiable psychosocial risk factors were identified that can have implications for preventing quality of life disruptions and treating impaired quality of life in future research.
RCT Entities:
PURPOSE: The course of quality of life after diagnosis of gynecologic cancer is not well understood. We aimed to identify subgroups of gynecologic cancerpatients with distinct trajectories of quality of life outcomes in the 18-month period after diagnosis. We also aimed to determine whether these subgroups could be distinguished by predictors derived from Social-Cognitive Processing Theory. METHODS: Gynecologic cancerpatients randomized to usual care as part of a psychological intervention trial (NCT01951807) reported on depressed mood, quality of life, and physical impairment soon after diagnosis and at five additional assessments ending 18 months after baseline. Clinical, demographic, and psychosocial predictors were assessed at baseline, and additional clinical factors were assessed between 6 and 18 months after baseline. RESULTS: A two-group growth mixture model provided the best and most interpretable fit to the data for all three outcomes. One class revealed subclinical and improving scores for mood, quality of life, and physical function across 18 months. A second class represented approximately 12 % of patients with persisting depression, diminished quality of life, and greater physical disability. Membership of this high-risk subgroup was associated with holding back concerns, more intrusive thoughts, and use of pain medications at the baseline assessment (ps < .05). CONCLUSIONS: Trajectories of quality of life outcomes were identified in the 18-month period after diagnosis of gynecologic cancer. Potentially modifiable psychosocial risk factors were identified that can have implications for preventing quality of life disruptions and treating impaired quality of life in future research.
Entities:
Keywords:
Depression; Growth mixture modeling; Gynecologic neoplasms; Physical impairment; Quality of life
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