A prognostic tool to predict fatigue in women with early-stage breast cancer undergoing radiotherapy

Courtier, Nicholas ORCID: https://orcid.org/0000-0001-6098-5882, Gambling, Tina ORCID: https://orcid.org/0000-0003-3489-9539, Enright, Stephanie, Barrett-Lee, Peter, Abraham, J. and Mason, Malcolm David ORCID: https://orcid.org/0000-0003-1505-2869 2013. A prognostic tool to predict fatigue in women with early-stage breast cancer undergoing radiotherapy. The Breast 22 (4) , pp. 504-509. 10.1016/j.breast.2012.10.002

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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.

Item Type:	Article
Date Type:	Publication
Status:	Published
Schools:	Healthcare Sciences Medicine
Subjects:	R Medicine > RC Internal medicine > RC0254 Neoplasms. Tumors. Oncology (including Cancer)
Uncontrolled Keywords:	Fatigue; Breast cancer; Radiotherapy; Risk prediction
Publisher:	Elsevier
ISSN:	0960-9776
Last Modified:	21 Oct 2022 10:25
URI:	https://orca.cardiff.ac.uk/id/eprint/40134

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