The diagnostic performance of minimally invasive biopsy in predicting breast pathological complete response after neoadjuvant systemic therapy in breast cancer: A meta-analysis

Abstract

Background: Neoadjuvant systemic therapy (NST) is commonly used in patients with early stage breast cancer before definitive surgery. The standard diagnostic approach for pathologic complete response (pCR) of the breast is breast surgery and pathologic examination. In recent years, several trials investigated the predictive value of image-guided minimally invasive biopsy (MIB) for breast pCR after NST. This study conducted a meta-analysis to evaluate the diagnostic accuracy of MIB. Materials and Methods: We identified relevant research reports in online databases through February 2020. The Quality Assessment of Diagnostic Accuracy Studies 2 (QUADAS-2) tool was used to evaluate the quality of included trials. We extracted relevant data and constructed a 2 × 2 contingency table to analyze the predictive accuracy of MIB for breast pCR. Subgroup analyses and meta-regressions were also performed to investigate potential causes of heterogeneity. Results: Nine trials (with 1,030 breast cancer patients) were included in this meta-analysis. The pooled sensitivity and specificity of MIB were 0.72 [95% confidence interval (CI): 0.61–0.81] and 0.99 (95% CI: 0.89–1.00), respectively. By combining relevant data, there were no significant differences in sensitivity or specificity among different molecular subtypes of breast cancer (P > 0.05). Subgroup analyses and meta-regressions implied that trials with responses not limited to clinical complete response (cCR) had a significantly higher accuracy of MIB than those with only cCR (RDOR: 7.65; 95% CI: 1.05–55.46; P = 0.046). Conclusion: Current image-guided MIB methods are not accurate enough in terms of predicting breast pCR after NST. It is of utmost clinical importance to standardize the MIB procedure and incorporate other factors into the evaluation in order to improve the accuracy to an acceptable level.