Development and validation of an algorithm to estimate incidence and prevalence of breast cancer patients with distant metastasis in Northern Ireland: A population-based study

Abstract

Abstract Introduction: The lack of systematic collection and reporting of breast cancer with distant metastasis (BCDM) means incidence and prevalence is largely unknown. Methods: Patients with primary breast cancer (BC) (Stage I-III and “Stage not known”) and de novo patients (Stage IV at diagnosis) were identified from the Northern Ireland Cancer Registry and linked to hospital inpatient (PAS) and death records (GRO) over the period 1993 to 2020. An expert rules-based algorithm was developed to identify BCDM cases. This was validated using a dataset of 1,028 BC patients diagnosed in 2009 and followed up until 2017 for BCDM (184 BCDM cases). Sensitivity, specificity, positive and negative predictive values (PPV, NPV) were calculated, and incident and prevalent cases reported. Results: Validation demonstrated high sensitivity (95.1%), specificity (99.2%), PPV (96.2%) and NPV (98.9%). Between 2009–2020 incident cases were stable, averaging 254 per year, while the prevalent population increased from 587 to 911 (55% increase), suggesting improved survivorship. In 2020 the highest proportion of patients living with BCDM were existing cases from previous years (71.2%), with 66.6% having progressive BCDM and 33% de novo BCDM. Conclusion: The novel algorithm accurately identified BCDM cases which will help planning, care and support for BCDM patients.