Long-term behavioral symptom clusters among survivors of early-stage breast cancer. development and validation of a predictive model

Abstract

Background Fatigue, cognitive impairment, anxiety, depression, and sleep disturbance are cancer-related behavioral symptoms (CRBS) that may persist years after early-stage breast cancer (BC), affecting quality of life. We aimed at generating a predictive model of long-term CRBS clusters among BC survivors four years post-diagnosis. Methods Patients with early-stage BC were included from the CANcer TOxicity (NCT01993498). Our outcome was the proportion of patients reporting CRBS clusters four years post-diagnosis (≥3 severe CRBS). Predictors, including clinical, behavioral, and treatment-related characteristics, Behavioral Symptoms Score (BSS; 1 point per severe CRBS at diagnosis) and a pro-inflammatory cytokine (IL-1b, IL-6, TNFα)-genetic risk score, were tested using multivariable logistic regression, implementing bootstrapped Augmented Backwards Elimination. A two-sided p-value < 0.05 defined statistical significance. Results In the development cohort (N = 3555), 642 patients (19.0%) reported a cluster of CRBS at diagnosis and 755 (21.2%) did so four years post-diagnosis. Younger age (adjusted Odds Ratio [aOR] for 1-year decrement: 1.012; 95% Confidence Interval [CI] 1.003-1.020); previous psychiatric disorders (aOR vs no: 1.27; 95% CI 1.01-1.60); and BSS (aOR ranged from 2.17 [1.66-2.85] for BSS = 1 vs 0 to 12.3 [7.33-20.87] for BSS = 5 vs 0) were predictors of reporting a cluster of CRBS (AUC 0.73 [95%CI 0.71-0.75]). Genetic risk score was not predictive of CRBS. 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 CRBS. Our model might be implemented in clinical pathways to improve management and test the effectiveness of risk mitigation interventions among breast cancer survivors.