A prognostic survival model for women diagnosed with invasive breast cancer in Queensland, Australia

descriptive epidemiology

What is known?

Prognostic models can help inform cancer patients about their future health outcome. It can also assist the decision making of clinicians and patients in regard to management and treatment of the cancer.

In contrast to previous studies considering survival following treatment, this study aimed to develop a prognostic model to better understand why there is a large variation in survival from breast cancer from the time of diagnosis.

What is new?

A recent study examined around 3,300 Queensland women who were diagnosed with invasive breast cancer between 2010 and 2013 and obtained their survival information up to December 2018.

Data were collected from various sources including telephone interviews, questionnaires, and the Queensland Cancer Register medical records.

The key factors identified as being predictive of poorer survival included:

  • a more advanced stage at diagnosis
  • a higher tumour grade
  • ‘triple negative’ breast cancers
  • symptom-detected rather than screen-detected.

Given the large variability in survival after a cancer diagnosis, we tried to understand why some women survive for longer than others. The final prognostic model explained about 36% of this variation in survival for women diagnosed with breast cancer, with ‘stage at diagnosis’ alone explaining 26% of the variation.

What does this mean?

These results confirmed the prognostic importance of identifying the stage, grade and clinical subtype of breast cancers, in addition to highlighting the independent survival benefit of breast cancers diagnosed through screening.

Understanding what additional factors contribute to the substantial unexplained variation in survival outcomes remains an important objective.

Contact: Peter Baade

Reference: Baade P, Fowler H, Kou K, Dunn J, Chambers S, Pyke C, Aitken J. A prognostic survival model for women diagnosed with invasive breast cancer in Queensland, Australia. Breast Cancer Research and Treatment. 2022. doi: 10.1007/s10549-022-06682-5.

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