title: A prognostic tool to predict fatigue in women with early-stage breast cancer undergoing radiotherapy.
abstract: BACKGROUND
  Fatigue during and after radiotherapy impacts negatively on normal functioning and quality of life. A pre-treatment estimate of the risk of fatigue would facilitate the targeting of timely interventions to limit consequential behavioural symptoms arising. We have developed a prognostic tool to predict the risk of fatigue in women with early-stage breast cancer undergoing radiotherapy.
  
  
  METHODS
  Socio-demographic, clinical and self-reported characteristics were recorded for 100 women prescribed adjuvant radiotherapy for stages Tis-T2N1 breast cancer. Multiple logistic regression was used to develop a parsimonious prognostic model. The performance of the model when predicting fatigue for individuals not in the study was estimated by a leave-one-out cross-validation. A statistical weighting was assigned to the model variables to render a Fatigue Propensity Score of between 0 and 15. The ability of the Propensity Score to discriminate fatigued participants was estimated via receiver operating characteristic curve analysis.
  
  
  RESULTS
  38% of participants reported significant fatigue during radiotherapy. Fatigue risk was predicted by elevated pre-treatment fatigue and anxiety, and diagnoses other than invasive ductal carcinoma (ductal carcinoma in-situ, invasive lobular and rarer carcinoma subtypes). The positive predictive value of the prognostic model was 80%. A Propensity Score threshold of ≥6 corresponded to a specificity of 90.3% and a sensitivity of 76.3%. The area under the receiver operating characteristic curve was 0.83 for the cross-validation sample.
  
  
  CONCLUSIONS
  Application of the Fatigue Propensity Score in the patient pathway can help direct fatigue management resources at those patients most likely to benefit.
authors.affiliation: School of Healthcare Studies, Cardiff University, Cardiff, UK. courtier@cardiff.ac.uk
authors.forename: N
authors.initials: N
authors.lastname: Courtier
authors.forename: T
authors.initials: T
authors.lastname: Gambling
authors.forename: S
authors.initials: S
authors.lastname: Enright
authors.forename: P
authors.initials: P
authors.lastname: Barrett-Lee
authors.forename: J
authors.initials: J
authors.lastname: Abraham
authors.forename: M D
authors.initials: MD
authors.lastname: Mason
mesh_terms: D000368:Aged; D001943:Breast Neoplasms / Q000150:complications* / Q000473:pathology / Q000532:radiotherapy; D002277:Carcinoma / Q000150:complications* / Q000473:pathology / Q000532:radiotherapy; D018270:Carcinoma, Ductal, Breast / Q000150:complications / Q000473:pathology / Q000532:radiotherapy; D018275:Carcinoma, Lobular / Q000150:complications / Q000473:pathology / Q000532:radiotherapy; D005221:Fatigue / Q000150:complications* / Q000175:diagnosis; D005260:Female; D006801:Humans; D016015:Logistic Models; D008875:Middle Aged; D011379:Prognosis; D018570:Risk Assessment / Q000379:methods