A population-based study on trajectories of HER2 status during neoadjuvant chemotherapy for early breast cancer and metastatic progression.

BACKGROUND: This study aimed to investigate the distribution and changes of HER2 status in untreated tumours, in residual disease and in metastasis, and their long-term prognostic implications. METHODS: This is a population-based cohort study of patients treated with neoadjuvant chemotherapy for breast cancer during 2007-2020 in the Stockholm-Gotland region which comprises 25% of the entire Swedish population. Information was extracted from the National Breast Cancer Registry and electronic patient charts to minimize data missingness and misclassification. RESULTS: In total, 2494 patients received neoadjuvant chemotherapy, of which 2309 had available pretreatment HER2 status. Discordance rates were 29.9% between primary and residual disease (kappa = 0.534), 31.2% between primary tumour and metastasis (kappa = 0.512) and 33.3% between residual disease to metastasis (kappa = 0.483). Adjusted survival curves differed between primary HER2 0 and HER2-low disease (p < 0.001), with the former exhibiting an early peak in risk for death which eventually declined below the risk of HER2-low. Across all disease settings, increasing the number of biopsies increased the likelihood of detecting HER2-low status. CONCLUSION: HER2 status changes during neoadjuvant chemotherapy and metastatic progression, and the long-term behaviours of HER2 0 and HER2-low disease differ, underscoring the need for obtaining tissue biopsies and for extended follow-up in breast cancer studies.

Risk Stratification for Cardiotoxicity in Breast Cancer Patients: Predicting Early Decline of LVEF After Treatment.

This study introduces AI-based models in prediction and risk assessment of early cardiac dysfunction in older breast cancer patients, as a side-effect of their cancer treatment. Using only features extracted during the baseline evaluation of each patient the proposed methodology could predict a decline in LVEF values in 4 different follow-up intervals during the first year after treatment initiation (i.e. months 3-12), with a mean accuracy of 66.67% and up to 73.55%. Selected baseline predictive factors were ranked according to their prevalence in the evaluation experiments, replicating the importance of various cardiac disorders at baseline, LVEF value and a higher age, which are all previously reported, while introducing Diabetes as an important risk factor.Clinical Relevance- Healthcare providers can better assess cardiovascular health status and risk of cardiotoxicity in the cancer treatment continuum. This will enable timely intervention and close monitoring on high risk patients while saving resources for low risk patients.