University of Leicester
2014TahirMMD.pdf (1.42 MB)

Optimising the management of breast cancer in older patients

Download (1.42 MB)
posted on 2014-05-21, 10:48 authored by Mohammad Tahir
This study aimed to optimise the treatment of early breast cancer in older patients. It tested the hypothesis that comprehensive geriatric assessment (CGA) could be used to predict two-year survival in older breast cancer patients. Based on the CGA scoring a treatment algorithm was devised that could help in recommending whether primary endocrine treatment (PET) or surgery plus endocrine treatment would be best indicated in individual patients. Methods: The study included women >70 years of age with early breast cancer, seen in a dedicated Leicester clinic between 01/2005 and 04/2007. All patients had comprehensive assessment including documentation of Satariano Index of Co-morbidities (SIC), Mini-Mental State Examination (MMSE), Geriatric Depression Score (GDS), Activities of Daily Living (ADL), Instrumental Activities of Daily Living (IADL) and American Society of Anaesthesiologists (ASA) grade. Logistic regression analysis explored any association between these components and two-year survival. Components with positive association were formulated into a Breast Cancer in Elderly Treatment Algorithm (BCETA). Results: 123 patients were included, age range 70-94 (median-82). Twenty-two patients died within two years. Logistic regression analysis found MMSE, ADL, and ASA score to have an independent association with two-year survival. The scores of these components were formulated into a BCETA. Logistic regression revealed a statistically significant association between the BCETA score and two-year survival (p-value 0.00). Other results for the BCETA prognostic model were: sensitivity 89%, specificity 46%, positive predictive value 87%, negative predictive value 52%, odds ratio 7.1 (95% CI 2.5-20.2), and overall accuracy of 81%. C-statistic value (area under ROC curve) for the BCETA score was 0.70. Conclusion: Breast Cancer in Elderly Treatment Algorithm is a new approach to optimise the management of breast cancer in elderly patients. It can help in identifying high-risk patients with expected short-survival who may benefit from PET, if their cancer is hormone receptor positive. Patients with predicted longer life expectancy (lowrisk) may be recommended standard treatment. Further studies are needed to validate it in a larger population.



Walker, Rosemary; Stotter, Anne

Date of award


Author affiliation

Department of Cancer Studies & Molecular Medicine

Awarding institution

University of Leicester

Qualification level

  • Doctoral

Qualification name

  • MD



Usage metrics

    University of Leicester Theses


    No categories selected



    Ref. manager