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This disease includes multiple subtypes, each with unique biological features and treatment responses. Despite significant advancements in detection and therapy, challenges remain, particularly in managing aggressive forms like triple\u2010negative breast cancer and overcoming drug resistance. Breast cancer classification and subtype determination are typically performed by immunohistochemistry (IHC) method, which assesses four key markers (ER, PR, HER2, KI67); however, due to the recognized issues with this approach\u2014especially regarding the evaluation of Ki67\u2014there is a risk of misclassification. Patients who may be suitable for chemotherapy could miss possible advantages and only experience needless toxicity as a result of improper treatment decisions. Molecular profiling has improved breast cancer management, enabling the creation of multigene prognostic tests (MPTs) like Oncotype Dx, MammaPrint, Prosigna, Endopredict, and Breast Cancer Index which assess gene expression profiles to more accurately predict recurrence risks. These tools help personalize treatment, identifying patients who can avoid chemotherapy and\/or extended endocrine therapy. While many MPTs are available, only Oncotype Dx and MammaPrint have prospective validation, with Prosigna providing additional prognostic insights by incorporating clinical variables. Molecular tests are especially usefull in the \u201c<jats:italic>gray zone<\/jats:italic>,\u201d which includes tumors measuring between 1 and 3\u2009cm with 0\u20133 positive lymph nodes and an intermediate proliferation index. However, their clinical utility has not been definitively established, and significant differences exist between them. This article provides an in\u2010depth analysis of established genomic assays, including testing procedures, clinical validity, utility, diagnostic frameworks, and methodologies. Our comparison aims to improve early breast cancer management by guiding pathologists and oncologists in optimizing the use of genomic assays in clinical practice. By presenting this information, we aim to enhance understanding of the clinical utility and effectiveness of these assays, supporting the development of personalized treatment strategies for early breast cancer patients. Genomic assays offer important insights that can support treatment decisions in early\u2010stage breast cancer, especially when used alongside other clinical evaluations, predictive tools, and management guidelines. While multiple gene expression profiling tests are available, they classify patients differently and are not interchangeable; therefore, their application should be at the clinician's discretion during the decision\u2010making process. It is essential that these tests are not the sole factor in determining the best treatment plan: other clinical considerations and patient preferences should also play a significant role in guiding treatment decisions.<\/jats:p>","DOI":"10.1002\/mc.23893","type":"journal-article","created":{"date-parts":[[2025,2,17]],"date-time":"2025-02-17T07:25:42Z","timestamp":1739777142000},"page":"789-800","update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":13,"title":["Evaluation and Comparison of Prognostic Multigene Tests in Early\u2010Stage Breast Cancer: Which Is the Most Effective? A Literature Review Exploring Clinical Utility to Enhance Therapeutic Management in Luminal Patients"],"prefix":"10.1002","volume":"64","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-4709-633X","authenticated-orcid":false,"given":"Marianna Rita","family":"Brogna","sequence":"first","affiliation":[{"name":"Pathology Unit, Istituto Nazionale Tumori\u2010IRCCS\u2010Fondazione G. Pascale Naples Italy"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Gerardo","family":"Ferrara","sequence":"additional","affiliation":[{"name":"Pathology Unit, Istituto Nazionale Tumori\u2010IRCCS\u2010Fondazione G. Pascale Naples Italy"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Valeria","family":"Varone","sequence":"additional","affiliation":[{"name":"Pathology Unit, Istituto Nazionale Tumori\u2010IRCCS\u2010Fondazione G. 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