Nomograms Integrating Body Composition Metrics Predict Total Pathologic Complete Response after Neoadjuvant Systemic...

Area of Science:

• Oncology
• Medical Imaging
• Biostatistics

Background:

• Neoadjuvant systemic therapy (NST) is a critical treatment for locally advanced or unresectable breast cancer.
• Achieving total pathological complete response (tpCR) after NST significantly improves patient prognosis.
• Current prediction models often overlook body composition's role in treatment response.

Purpose of the Study:

• To develop a predictive model for tpCR in breast cancer patients undergoing NST.
• To identify baseline and body composition indicators associated with tpCR.
• To construct a nomogram for assessing NST efficacy and optimizing treatment strategies.

Main Methods:

• Retrospective analysis of 500 breast cancer patients treated with NST (2014-2022).
• Data split into training (350 patients) and validation (150 patients) sets.
• Univariate and multivariate logistic regression analyses to identify predictors of tpCR.
• Nomogram construction based on significant predictors.

Main Results:

• Progesterone receptor-negative status, HER2-positive status, large body surface area, low skeletal muscle index, and high skeletal muscle density were associated with higher tpCR likelihood.
• Advanced AJCC T-stage (4) and N-stage (1) were associated with lower tpCR likelihood.
• A nomogram was developed incorporating these factors to predict tpCR probability.

Conclusions:

• Body composition indicators are significant predictors of tpCR in breast cancer patients receiving NST.
• The developed nomogram offers a tool to predict treatment response and personalize therapy.
• Integrating body composition into prediction models can enhance treatment efficacy and patient outcomes.