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The twin pandemics of COVID-19 and structural racism brought into focus health disparities and disproportionate impacts of disease on communities of color. Health equity has subsequently emerged as a priority. Recognizing that the future of health care will be informed by advanced information technologies including artificial intelligence (AI), machine learning, and algorithmic applications, the authors argue that to advance towards states of improved health equity, health information professionals need to engage in and encourage the conduct of research at the intersections of health equity, health disparities, and computational biomedical knowledge (CBK) applications. Recommendations are provided with a means to engage in this mobilization effort., (Copyright © 2024 Nancy J. Allee, Gerald Perry, Gabriel R.Rios, Joshua C. Rubin, Vignesh Subbian, Deborah E. Swain, Terrie R. Wheeler.)

Answer questions and earn CME/CNE The revision of the eighth edition of the primary tumor, lymph node, and metastasis (TNM) classification of the American Joint Commission of Cancer (AJCC) for breast cancer was determined by a multidisciplinary team of breast cancer experts. The panel recognized the need to incorporate biologic factors, such as tumor grade, proliferation rate, estrogen and progesterone receptor expression, human epidermal growth factor 2 (HER2) expression, and gene expression prognostic panels into the staging system. AJCC levels of evidence and guidelines for all tumor types were followed as much as possible. The panel felt that, to maintain worldwide value, the tumor staging system should remain based on TNM anatomic factors. However, the recognition of the prognostic influence of grade, hormone receptor expression, and HER2 amplification mandated their inclusion into the staging system. The value of commercially available, gene-based assays was acknowledged and prognostic input added. Tumor biomarkers and low Oncotype DX recurrence scores can alter prognosis and stage. These updates are expected to provide additional precision and flexibility to the staging system and were based on the extent of published information and analysis of large, as yet unpublished databases. The eighth edition of the AJCC TNM staging system, thus, provides a flexible platform for prognostic classification based on traditional anatomic factors, which can be modified and enhanced using patient biomarkers and multifactorial prognostic panel data. The eighth edition remains the worldwide basis for breast cancer staging and will incorporate future online updates to remain timely and relevant. CA Cancer J Clin 2017;67:290-303. © 2017 American Cancer Society., (© 2017 American Cancer Society.)