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Long-term longitudinal patterns of patient-reported quality of life (QOL) after breast cancer (BC) to inform the implementation of personalized pathways of care

JOURNAL OF CLINICAL ONCOLOGY(2023)

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Abstract
12081 Background: There is substantial inter individual variability in long-term trajectories of patient-reported quality of life (QOL) after early BC. Previous work focused on a selected group of patients (pts) treated with chemotherapy (CT) identified a cluster of pts with upfront poor QOL but also pts with severe, persistent post-chemotherapy QOL deterioration. We aimed to expand this work to a non-selected group of pts with early BC to identify latent clusters of pts at risk for QOL deterioration, and to assess the relationship of actionable host factors and health behaviors with trajectory group membership. Methods: We performed a detailed longitudinal analysis of QOL using a large ongoing national prospective clinical cohort (CANcer TOxicity, NCT01993498) of pts with stage I-III BC treated from 2012-2018. QOL (EORTC QLQ-C30 summary score) was assessed at diagnosis (dx, baseline) and year 1, 2, 4 and 6 post-dx. Baseline clinical, sociodemographic, behavioral, tumor-related, and treatment-related characteristics were available. Trajectories of QOL and group membership associations were identified by iterative estimations of group-based trajectory models and multivariable multinomial logistic regression, respectively, among the whole cohort. Results: Among 10,792 pts, 5,695 received adjuvant CT and 8,805 received adjuvant endocrine therapy (ET). Four QOL trajectory groups were identified: excellent (N = 4,934, 45.8%), very good (N = 3,596, 33.3%), deteriorating (N = 1,745, 16.1%), and poor (N = 517, 4.8%). The deteriorating trajectory group reported fairly good baseline QOL (73.3 [95% CI], [72.4 to 74.2]), which significantly worsened at year-1 (63.0 [62.1 to 63.9]) and never recovered to pretreatment values through year-6 (64.7 [63.3 to 66.0]) post diagnosis. Factors associated with membership to the deteriorating group included younger age (aOR, 10-years decrement 1.10 [95% CI, 1.05 to 1.16]), overweight or obesity (aOR v lean, 1.90 [95% CI, 1.60 to 2.25]; 1.25 [95% CI, 1.07 to 1.46], respectively), physical inactivity (aOR v active, 1.13 [95% CI, 1.04 to 1.35]), former smoking behavior (aOR v never, 2.14 [95% CI, 1.80 to 2.54]), Charlson comorbidity score ≥1 (aOR v 0, 1.56 [95% CI, 1.33 to 1.83]), lower household income ( < 3000 EU/month) (aOR v ≥3000, 1.50 [95% CI, 1.30 to 1.72]), receipt of adjuvant CT (aOR v no, 1.35 [95% CI, 1.14 to 1.59]) and receipt of adjuvant ET (aOR v no, 1.46 [95% CI, 1.22 to 1.75]). Conclusions: This study will help identify latent clusters of pts who are at risk of persistent QOL deterioration after BC, independently of receipt of CT. Trajectory clustering can help facilitate the creation of personalized pathways that may include early addressal of actionable factors, including referral to social work and healthy lifestyle interventions. Clinical trial information: NCT01993498 .
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Key words
breast cancer,personalized pathways,life,long-term,patient-reported
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