Temporal trends in population-level cure of cancer: the Australian context

What is known?

With the improvements in cancer diagnosis and treatment, more patients with cancer are surviving for longer periods than before. We use a measure called “Population cure”, which is when the mortality rate among people diagnosed with a specific cancer type is the same as that in the general population. This study aims to quantify the proportion of Australian cancer patients who could be considered cured and how this varied by cancer type.

What is new?

Cancer types were grouped into four categories based on their cure proportions and how this measure had changed over time. The first group (including lung, stomach and pancreatic cancers) had low population cure and little change over time, indicating a continuing lack of effective diagnostic and treatment options over time. The second group (including myeloma) had lower population cure but it had improved over time, indicating there had been substantial improvements in the effectiveness of diagnosis and/or treatment. The third group (including melanoma, cervical and ovarian cancers) had higher population cure but little change over time, indicating that the efficient diagnosis and/or treatment in 1980s did not significantly improve over time. The fourth group (including prostate, breast and bowel cancers) had high population cure and increases over time, indicating good initial cancer management and substantial improvement over time.

What does this mean?

For cancers with poor survival, where little has changed over time either in prolonging life or achieving statistical cure, efforts should be focused on reducing the prevalence of known risk factors and earlier detection, thereby enabling more effective treatment.

Cure models provide unique insights into whether survival improvements are due to prolonging life, or through curing the disease.

Contact: Peter Baade

Reference: Kou K, Dasgupta P, Cramb SM, Yu XQ, Baade PD. Temporal trends in population-level cure of cancer: the Australian context. Cancer Epidemiology Biomarkers and Prevention. 2020; 29(3):625-635.

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