Bridging the Age Gap: a prognostic model that predicts survival and aids in primary treatment decisions for older women with oestrogen receptor‐positive early breast cancer. Issue 12 (30th June 2020) - Ward, S. E.; Holmes, G. R.; Morgan, J. L.; Broggio, J. W.; Collins, K.; Richards, P. D.; Reed, M. W. R.; Wyld, L.
Abstract : Background: A prognostic model was developed and validated using cancer registry data. This underpins an online decision support tool, informing primary treatment choice for women aged 70 years or older with hormone receptor‐positive early breast cancer. Methods: Data from women diagnosed between 2002 and 2010 in the English Northern and Yorkshire and West Midlands regions were used to develop the model. Primary treatment options of surgery with adjuvant endocrine therapy or primary endocrine therapy were compared. Models predicting the hazard of breast cancer‐specific mortality and hazard of other‐cause mortality were combined to derive survival probabilities. The model was validated externally using data from the Eastern Cancer Registration and Information Centre. Results: The model was developed using data from 23 842 women, and validated externally on a data set from 14 526 patients. The overall model calibration was good. At 2 and 5 years, predicted mortality from breast cancer and other causes differed from the observed rate by less than 1 per cent. At 5 years, there were slight overpredictions in breast cancer mortality (2629 predicted versus 2556 observed deaths; P = 0·142) and mortality from all causes (6399 versus 6320 respectively; P = 0·583). The discrepancy varied between subgroups. Model discrimination was 0·75 or above for all mortality measures. Conclusion: A prognostic model for older women with oestrogen receptor‐positive early breast cancer was developed and validated in the present study. This forms a basis for an online decision support tool (https://agegap.shef.ac.uk/ ). Abstract : A new prognostic model is presented, targeted at women aged 70 years and older with early invasive breast cancer. Unlike existing models for adjuvant therapy decisions, the model supports the decision whether to have primary surgery; it explores the use of frailty and co‐morbidity for modelling other‐cause mortality, which is important for this age group. The model forms part of a decision aid for clinicians and their patients. Improves decision‐making Abstract : Antecedentes: Se ha desarrollado y validado un modelo pronóstico utilizando datos del registro de cáncer. Ello ha permitido ofrecer una herramienta online para facilitar la toma de decisiones respecto a la elección del tratamiento inicial en mujeres mayores de 70 años con cáncer de mama precoz y receptores de hormonas positivos. Métodos: Se incluyeron un total de 23.842 mujeres, diagnosticadas entre 2002 y 2010 en las regiones del Norte, Yorkshire y West Midlands inglesas que cumplieron con los criterios de inclusión. Se compararon dos opciones de tratamiento: cirugía primaria asociada a tratamiento endocrino adyuvante o tratamiento primario endocrino. Para estimar la probabilidad de supervivencia se combinaron modelos predictivos para el riesgo de mortalidad específica por cáncer de mama y para el riesgo de mortalidad por otras causas. Se realizó una validación externa con datos del Eastern Cancer Registration and Information Center ( n = 14.526). Resultados: La calibración global del modelo fue buena. A los 2 y 5 años, la mortalidad anticipada por cáncer de mama y por otras causas difería de la observada en menos del 1%. A los 5 años, hubo una ligera sobrevaloración de la predicción de mortalidad por cáncer de mama (prevista versus real: 2.629 versus 2.556, P = 0, 78) y de la mortalidad por todas las causas (6.399 versus 6.320, P = 0, 14). Esta discrepancia varió entre subgrupos. La capacidad discriminativa del modelo fue del 0, 75 o superior para todas las medidas de mortalidad. Conclusión: En este estudio, se desarrolló y validó un modelo pronóstico para mujeres mayores con cáncer de mama precoz positivo para receptores de estrógenos. Esta herramienta que facilita la toma de decisiones está disponible online (https://agegap.shef.ac.uk/ ).