SynthesisBMC cancer2026
Ultrasound-based predictive models for response to neoadjuvant chemotherapy in breast cancer: a systematic review and meta-analysis.
Synthesis in BMC cancer, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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6 authors.
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Abstract
objectiveThis meta-analysis aimed to assess the diagnostic efficacy of ultrasound-based prediction models in evaluating the response to neoadjuvant chemotherapy (NAC) in breast cancer patients.
methodsA systematic review was conducted using PubMed, Embase, and Web of Science from inception to May 2025. We focused on studies evaluating ultrasound-based prediction models for NAC response in breast cancer. Two investigators independently performed study selection and data extraction according to predefined eligibility criteria. The risk of bias was assessed using the Prediction Model Risk of Bias Assessment Tool (PROBAST). Meta-analysis was performed using Stata 14.0 software, with the area under the curve (AUC) and its 95% confidence interval (CI) as the primary measure of diagnostic accuracy.
resultsFourteen retrospective studies with a total of 35 prediction models were included. PROBAST assessment indicated a high overall risk of bias in most studies (10 out of 14). The pooled AUC for all ultrasound-based prediction models in predicting NAC response was 0.84 (95% CI: 0.82, 0.86). However, substantial heterogeneity was observed among the studies (I
conclusionUltrasound-based prediction models show encouraging discriminative ability for predicting pCR (pooled AUC 0.84, 95% CI 0.82-0.86), suggesting preliminary potential. However, given the high risk of bias, substantial heterogeneity, and geographic limitation (all studies from China), the current evidence should be considered exploratory and hypothesis-generating rather than practice-changing. Future prospective, multicenter, and rigorously designed studies are needed to confirm these findings.
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