No abstract

On December 16, 2020, the FDA granted regular approval to margetuximab-cmkb (MARGENZA), in combination with chemotherapy, for the treatment of adult patients with HER2-positive (HER2+) metastatic breast cancer who have received two or more prior anti-HER2 regimens, at least one of which was for metastatic disease. Approval was based on data from SOPHIA, a multicenter, randomized, open-label, active controlled study comparing margetuximab with trastuzumab, in combination with chemotherapy. The primary efficacy endpoint was progression-free survival (PFS) by blinded independent central review. SOPHIA demonstrated a 0.9-month difference in median PFS between the two treatment arms [5.8 vs. 4.9 months, respectively; stratified HR, 0.76 (95% confidence interval: 0.59–0.98; P = 0.0334)]. Overall survival (OS) was immature at the data cut-off date of September 10, 2019. Infusion-related reactions (IRR) are an important safety signal associated with margetuximab plus chemotherapy. In SOPHIA, 13% of patients treated with margetuximab plus chemotherapy reported IRRs, of which 1.5% were grade 3. The most commonly reported adverse drug reactions (>10%) with margetuximab in combination with chemotherapy were fatigue/asthenia, nausea, diarrhea, vomiting, constipation, headache, pyrexia, alopecia, abdominal pain, peripheral neuropathy, arthralgia/myalgia, cough, decreased appetite, dyspnea, IRR, palmar-plantar erythrodysesthesia, and extremity pain. Overall, the favorable risk-benefit profile for margetuximab when added to chemotherapy supported its approval for the intended indication.

The vital nodes are the ones that play an important role in the organization of network structure or the dynamical behaviors of networked systems. Previous studies usually applied the node centralities to quantify the importance of nodes. Realizing that the percolation clusters are dominated by local connections in the subcritical phase and by global connections in the supercritical phase, in this paper we propose a new method to identify the vital nodes via a competitive percolation process that is based on an Achlioptas process. Compared with the existing node centrality indices, the new method performs overall better in identifying the vital nodes that maintain network connectivity and facilitate network synchronization when considering different network structure characteristics, such as link density, degree distribution, assortativity, and clustering. We also find that our method is more tolerant of noisy data and missing data. More importantly, compared with the unique ranking list of nodes given by most centrality methods, the randomness of the percolation process expands the possibility space of the optimal solutions, which is of great significance in practical applications.