Purpose A substantial need for effective and safe treatment options is still unmet for patients with heavily pre-treated human epidermal growth factor receptor 2 (HER2)-positive metastatic breast cancer (MBC). Herein, we assessed the efficacy and safety of pyrotinib plus trastuzumab and chemotherapy in patients with heavily treated HER2-positive MBC. Methods In this single-arm exploratory phase II trial, patients with HER2-positive MBC previously treated with trastuzumab plus lapatinib or pertuzumab, received pyrotinib plus trastuzumab and chemotherapy. The primary end point was progression-free survival (PFS) in the total population (TP). Secondary end points included PFS in the subgroup with brain metastases (Sub-BrM), confirmed objective response rate (ORR), clinical benefit rate (CBR), disease control rate (DCR), exploration of predictive factors of PFS, and safety. Results Between November 1, 2018, and March 31, 2021, 40 patients were eligible for this study. The median PFS reached 7.5 months (95% confidence interval [CI] 4.7 to 9.9 months) and 9.4 months (95% CI 6.6 to 12.1 months) in the TP and Sub-BrM, respectively. ORR was 50.5% (20/40). CBR was 75.5% (30/40) and DCR reached 97.5% (39/40). Cox univariate and multivariate analyses demonstrated that liver or/and lung metastases was the significant adverse prognostic factor for PFS (p = 0.018; p = 0.026; respectively). The most frequent grade 3 or 4 treatment-related adverse events were diarrhea, neutropenia and leukopenia. No new safety signals were observed. Conclusion Pyrotinib plus trastuzumab and chemotherapy offered a promising option with manageable safety profile for heavily pre-treated HER2-positive MBC, especially for those without liver or/and lung metastases.

BackgroundOvertreatment of axillary lymph node dissection (ALND) may occur in patients with axillary positive sentinel lymph node (SLN) but negative non-SLN (NSLN). Developing a magnetic resonance imaging (MRI)-based radiomics nomogram to predict axillary NSLN metastasis in patients with SLN-positive breast cancer could effectively decrease the probability of overtreatment and optimize a personalized axillary surgical strategy.MethodsThis retrospective study included 285 patients with positive SLN breast cancer. Fifty five of them had metastatic NSLNs and 230 had non-metastatic NSLNs. MRI-based radiomic features of primary tumors were extracted and MRI morphologic findings of the primary tumor and axillary lymph nodes were assessed. Four models, namely, a radiomics signature, an MRI-clinical nomogram, and two MRI-clinical-radiomics nomograms were established based on MRI morphologic findings, clinicopathologic characteristics, and MRI-based radiomic features to predict the NSLN status. The optimal predictors in each model were selected using the 5-fold cross-validation (CV) method. Their predictive performances were determined by the receiver operating characteristic (ROC) curves analysis. The area under the curves (AUCs) of different models was compared by the Delong test. Their discrimination capability, calibration curve, and clinical usefulness were also assessed.ResultsThe 5-fold CV analysis showed that the AUCs ranged from 0.770 to 0.847 for the radiomics signature, from 0.720 to 0.824 for the MRI-clinical nomogram, from 0.843 to 0.932 for the MRI-clinical-radiomics nomogram. The optimal predictive factors in the radiomics signature, MRI-clinical nomogram, and MRI-clinical-radiomics nomogram were one texture feature of diffusion-weighted imaging (DWI), two clinicopathologic features together with one MRI morphologic finding, and the DWI-based texture feature together with the two clinicopathologic features plus the one MRI morphologic finding, respectively. The MRI-clinical-radiomics nomogram with CA 15-3 included achieved the highest AUC compared with the radiomics signature (0.868 vs. 0.806, P <0.001) and MRI-clinical nomogram (0.868 vs. 0.761; P <0.001). In addition, the MRI-clinical-radiomics nomogram without CA 15-3 showed a higher performance than that of the radiomics signature (AUC, 0.852 vs. 0.806, P = 0.016) and the MRI-clinical nomogram (AUC, 0.852 vs. 0.761, P = 0.007). The MRI-clinical-radiomics nomograms showed good discrimination and good calibration. Decision curve analysis demonstrated that the MRI-clinical-radiomics nomograms were clinically useful.ConclusionThe MRI-clinical-radiomics nomograms developed in our study showed high predictive performance, which can be used to predict the axillary NSLN status in SLN-positive breast cancer patients before surgery.

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