ArticleCancer research and treatment2026
Nomograms Integrating Body Composition Metrics Predict Total Pathologic Complete Response after Neoadjuvant Systemic Therapy for Breast Cancer.
Article in Cancer research and treatment, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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1 citing paper in PubMed.
- Artificial intelligence standardizes CT-based body composition analysis in breast cacer to address methodological heterogeneity.Frontiers in oncology · 2026Review
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Abstract
purposeNeoadjuvant systemic therapy (NST) is a systemic treatment for locally advanced or initially unresectable breast cancer before surgery. Patients who achieved total pathologic complete response (tpCR) after NST exhibited significantly better overall prognosis than patients with non-pathological complete response. MATERIALS AND
methodsThis study collected baseline indicators, body composition indicators, and tpCR results of breast cancer patients at the First Affiliated Hospital of Nanjing Medical University. Patients were divided into training set and validation set in a ratio of 7:3. Univariable and multivariable logistic regression analyses were performed, and the probability of tpCR was predicted by constructing nomograms based on the results of the multivariable logistic regression analysis.
resultsThe study included 500 patients between 2014 and 2022 with breast cancer who underwent NST. The training set and validation set consist of 350 and 150 patients, respectively. Patients with progesterone receptor-negative status (p < 0.001), human epidermal growth factor receptor 2-positive status (p < 0.001), large body surface area (p=0.091), low skeletal muscle index (p=0.008), and high skeletal muscle density (p=0.004) were more likely to achieve tpCR. Patients with American Joint Committee on Cancer (AJCC) T-stage 4 (p=0.126), AJCC N-stage 1 (p=0.026) were less likely to achieve tpCR.
conclusionExisting tpCR prediction models mostly focus on tumor biological characteristics and ignore the effect of body compositions. This study constructed a nomogram to predict tpCR in patients with breast cancer undergoing NST based on baseline and body composition indicators. This nomogram can help assess efficacy and optimize treatment strategies, thus improving the overall prognosis of patients.
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