ArticleCancer management and research2020
The Evaluation of Magee Equation 2 in Predicting Response and Outcome in Hormone Receptor-Positive and HER2-Negative Breast Cancer Patients Receiving Neoadjuvant Chemotherapy.
Article in Cancer management and research, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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2 citing papers in PubMed, 6 citations in OpenAlex.
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5 authors at 2 institutions in 2 countries.
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No grant is acknowledged in the PubMed record.
Abstract
background and purposeMagee Equations have been developed as accurate tools for predicting response and clinical outcomes in breast cancer patients treated with adjuvant systemic therapy using basic clinicopathological parameters. This study aims to evaluate the alternative application of Magee Equation 2 score in predicting pathological complete response (pCR) after neoadjuvant chemotherapy (NAC) in hormone receptor (HR)-positive, HER2-negative breast cancer. PATIENTS AND
methodsPatients with HR-positive, HER2-negative breast cancer who received NAC from January 2010 to May 2018 at Siriraj Hospital, Mahidol University, Thailand, were recruited. Pre-treatment status of HR and HER2 was used to calculate the Magee Equation 2 scores. The pCR rates among different clinicopathological parameters were analyzed. Survival analysis was performed by Log-rank test. Kaplan-Meier survival curves were analyzed.
resultsA total of 215 patients were eligible. The pCR rates for low, intermediate, and high scores were 4.8%, 3.6%, and 23.8%, respectively. Patients with high scores had significantly higher size reduction and pCR rates compared to those with intermediate or low scores (
conclusionAmong patients with HR-positive and HER2-negative breast cancer treated with NAC, Magee Equation 2 might be used as a tool for predicting the pCR and clinical outcome.
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