Introduction: The advent of the COVID-19 pandemic has led to the sudden disruption of routine medical care, and the subsequent reorganization of hospital structures and therapeutic algorithms, aiming at protecting patients and health professionals. This was inevitably bound to affect our Breast Unit, dilating both pre- and post-operative times. The aim of this study was to evaluate the effect on patients' flow of organizational and logistic changes ( key interventions ) based on lean thinking implemented after the COVID-19 outbreak. Materials and Methods: Clinical and demographic data were retrospectively collected from patients undergoing sentinel lymph node biopsy for breast cancer at the Verona University Hospital from January 2018 to June 2020. Patients enrolled ( n = 341) were divided into two groups according to date of admission: before (Group A; n = 294) and after (Group B; n = 47) the implementation of key interventions. Each case in Group B was subsequently matched 1:1 by means of case-control matching with cases from Group A for age, comorbidities, and type of surgery (Subgroup A1; N = 47). Pre-admission time (T0) and length of stay (T1) were compared between the three groups. Results: Median T0 was 312 h, whereas median T1 was 24 h. Patients in Group B had a higher frequency of comorbidities (57.4 vs. 25.2%, p = 0.001) and underwent mastectomy more often than patients in Group A (61.7 vs. 36.7%, p = 0.001). Both median T0 and T1 were higher in group B than in group A (384 vs. 300 h, p = 0.001, 48 vs. 24 h, p = 0.001, respectively). Median T0 and T1 did not significantly differ between Group B and Subgroup A1 (all p > 0.05). Conclusions: Lean thinking and new technologies could prove useful to the optimization of preoperative and postoperative times during the current pandemic, minimizing healthcare personnel and patients' exposure to SARS-CoV-2, and promoting a rational use of limited resources, while complying with oncological principles.
The aim of this analysis was to investigate the potential impact of Ki67 assay in a series of patients affected by early stage invasive lobular carcinoma (ILC) undergone surgery. Clinical-pathological data were correlated with disease-free and overall survival (DFS/OS). The maximally selected Log-Rank statistics analysis was applied to the Ki67 continuous variable to estimate appropriate cut-offs. The Subpopulation Treatment Effect Pattern Plot (STEPP) analysis was performed to assess the interaction between 'pure' or 'mixed' histology ILC and Ki67. At a median follow-up of 67 months, 10-years DFS and OS of 405 patients were 67.8 and 79.8 %, respectively. Standardized Log-Rank statistics identified 2 optimal cut-offs (6 and 21 %); 10-years DFS and OS were 75.1, 66.5, and 30.2 % (p = 0.01) and 84.3, 76.4 and 59 % (p = 0.003), for patients with a Ki67 < 6 %, between 6 and 21 %, and >21 %, respectively. Ki67 and lymph-node status were independent predictor for longer DFS and OS at the multivariate analysis, with radiotherapy (for DFS) and age (for OS). Ki67 highly replicated at the internal cross-validation analysis (DFS 85 %, OS 100 %). The STEPP analysis showed that DFS rate decreases as Ki67 increases and those patients with 'pure' ILC performed worse than 'mixed' histology. Despite the retrospective and exploratory nature of the study, Ki67 was able to significantly discriminate the prognosis of patients with ILC, and the effect was more pronounced for patients with 'pure' ILC.
