Evaluating Ultrasound as a Predictor of Pathological Response to Neoadjuvant Chemotherapy in Breast Cancer Patients: A Systematic Review and Meta-Analysis - Scorecard - MDSpire

Evaluating Ultrasound as a Predictor of Pathological Response to Neoadjuvant Chemotherapy in Breast Cancer Patients: A Systematic Review and Meta-Analysis

  • By

  • Qing Feng Shi

  • Peng Fei Hu

  • Yong Hong Liu

  • January 13, 2026

  • 0 min

Share

Clinical Scorecard: Evaluating Ultrasound as a Predictor of Pathological Response to Neoadjuvant Chemotherapy in Breast Cancer Patients: A Systematic Review and Meta-Analysis

At a Glance

CategoryDetail
ConditionBreast Cancer
Key MechanismsNeoadjuvant chemotherapy reduces tumor burden and nodal involvement, potentially improving surgical outcomes.
Target PopulationAdult patients with breast cancer undergoing neoadjuvant chemotherapy.
Care SettingOncology clinics and hospitals performing neoadjuvant chemotherapy.

Key Highlights

  • Ultrasound (US) is emerging as a predictor of pathological response to neoadjuvant chemotherapy.
  • The systematic review included 72 studies with a total of 8439 patients.
  • Variability in study results highlights the need for standardized evaluation of US in this context.

Guideline-Based Recommendations

Diagnosis

  • Utilize ultrasound imaging to assess response to neoadjuvant chemotherapy in breast cancer patients.

Management

  • Incorporate ultrasound findings into treatment planning to personalize neoadjuvant chemotherapy.

Monitoring & Follow-up

  • Regularly evaluate ultrasound results during the course of neoadjuvant chemotherapy.

Risks

  • Consider potential biases in patient selection and diagnostic accuracy when interpreting ultrasound results.

Patient & Prescribing Data

Adult breast cancer patients undergoing neoadjuvant chemotherapy.

Ultrasound may help in predicting treatment response, thus guiding further management.

Clinical Best Practices

  • Adhere to PRISMA guidelines for systematic reviews when evaluating ultrasound studies.
  • Conduct thorough quality assessments of studies using QUADAS-2 to evaluate bias.

References

Original Source(s)

Related Content