Abstract

There are substantial differences in the treatment of breast cancer for women aged 70 and older compared to younger postmenopausal women. Older women are less likely to be managed in line with clinical guidelines although the reasons why are unclear. There is also a lack of reliable instruments capable of predicting the impact of treatment for older breast cancer patients in terms of subsequent complications and reduced quality of life. Once identified such instruments could help patients and their doctors make treatment decisions.
 

This study will investigate the extent to which nonstandard management of older women with breast cancer is due to differences in their tumour characteristics, general health and patient preferences. In addition, the ability of a range of health measures to predict post surgical complications and quality of life for older breast cancer patients will be explored.

We will follow the treatment of 450 women aged 65 years and older, diagnosed with operable breast cancer over eighteen months from a sample of 7 breast units selected at random from Lancashire & Cumbria and Merseyside & Cheshire cancer networks. Eligible patients will be identified at MultiDisciplinary Team (MDT) meetings and recruitment will be initially by post with a telephone follow up. Participants will be interviewed before treatment commences (T1).The interview will largely comprise of standard measures of selfreported health and patient preference. Patients undergoing primary surgery will also be sent a postal survey 30 (+/−2) days post surgery (T2), measuring post surgery complications and quality of life. Case note review will take place 3 months postdiagnosis, which will measure comorbidity, diagnostic process, treatment procedures, post surgical complications and tumour characteristics.
 

The extent to which tumour characteristics, patient health and patient preference predict nonstandard management and health measures predict post surgical complications and quality of life will be investigated in mathematical models.