Breast cancer recurrence following active treatment: determining its incidence in the NSW population

Abstract

Objectives: It is important for consumers, clinicians and health service planners to know the risk of recurrence of primary breast cancer after initial treatment. At present, none of Australia's state or territory cancer registries routinely report this information. We aimed to determine the incidence of recurrence in New South Wales (NSW) clinical practice for the period 18 months to 6 years after diagnosis of primary breast cancer.

Study type: Retrospective cohort study using population-based linked health data.

Methods: We identified 2416 women in the 45 and Up Study who were diagnosed with primary invasive breast cancer between 2003 and 2008 in NSW, and who had not had a recurrence 18 months after diagnosis. Unit-level hospital, pharmacy and outpatient medical claims were used to identify treatment for recurrence. Incidence of recurrence was calculated using individual person-time at risk (18 months to 6 years postdiagnosis), with follow-up censored for death or end of study period (median follow-up 3 years). Time to recurrence was calculated, and Cox proportional regression was used to identify women's baseline and active treatment characteristics that were predictive of recurrence up to 6 years postdiagnosis.

Results: 217 women (9%) had a hospital, pharmacy or outpatient claim indicating breast cancer recurrence. Overall annual incidence of recurrence was 3.3%. Recurrence rates were significantly higher for women with node-positive (4.8% vs 2.5% annually; hazard ratio [HR] = 1.7; 95% confidence interval [95% CI] 1.3, 2.3) or hormone receptor-negative tumours (3.8% vs 3.1% annually; HR = 1.3; 95% CI 1.0, 1.7). Women with tumours >2 cm at diagnosis were more likely to experience recurrence than women with smaller/unknown tumours (4.8% vs 2.7% annually; HR = 1.5; 95% CI 1.1, 2.0).

Conclusions: A combination of routinely collected administrative health datasets can be used to determine recurrence rates, allowing future assessment of population-level changes over time and investigations of the real-world impact of specific treatments on outcomes.