Abstract
Abstract Background Fatigue, cognitive impairment, anxiety, depression, and sleep disturbance are cancer-related behavioral symptoms that may persist years after early-stage breast cancer, affecting quality of life. We aimed to generate a predictive model of long-term cancer-related behavioral symptoms clusters among breast cancer survivors 4 years after diagnosis. Methods Patients with early-stage breast cancer were included from the CANcer TOxicity trial (ClinicalTrials.gov identifier NCT01993498). Our outcome was the proportion of patients reporting cancer-related behavioral symptoms clusters 4 years after diagnosis (≥3 severe symptoms). Predictors, including clinical, behavioral, and treatment-related characteristics; Behavioral Symptoms Score (BSS; 1 point per severe cancer-related behavioral symptom at diagnosis); and a proinflammatory cytokine (interleukin 1b; interleukin 6; tumor necrosis factor α) genetic risk score were tested using multivariable logistic regression, implementing bootstrapped augmented backwards elimination. A 2-sided P less than .05 defined statistical significance. Results In the development cohort (n = 3555), 642 patients (19.1%) reported a cluster of cancer-related behavioral symptoms at diagnosis, and 755 (21.2%) did so 4 years after diagnosis. Younger age (adjusted odds ratio for 1-year decrement = 1.012, 95% confidence interval [CI] = 1.003 to 1.020), previous psychiatric disorders (adjusted odds ratio vs no = 1.27, 95% CI = 1.01 to 1.60), and BSS (adjusted odds ratio ranged from 2.17 [95% CI = 1.66 to 2.85] for BSS = 1 vs 0 to 12.3 [95% CI = 7.33 to 20.87] for BSS = 5 vs 0) were predictors of reporting a cluster of cancer-related behavioral symptoms (area under the curve = 0.73, 95% CI = 0.71 to 0.75). Genetic risk score was not predictive of these symptoms. Results were confirmed in the validation cohort (n = 1533). Conclusion Younger patients with previous psychiatric disorders and higher baseline symptom burden have greater risk of long-term clusters of cancer-related behavioral symptoms. Our model might be implemented in clinical pathways to improve management and test the effectiveness of risk-mitigation interventions among breast cancer survivors.
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