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Purpose: To assess the incidence and clinical significance of discrepancy in subspecialty interpretation of outside breast imaging examinations for newly diagnosed breast cancer patients presenting to a tertiary cancer center.Materials and Methods: This Institutional Review Board-approved retrospective study included patients presenting from July 2016 to March 2017 to a National Cancer Institute-designated comprehensive cancer center for second opinion after breast cancer diagnosis. Outside and second opinion radiology reports of 252 randomly selected patients were compared by two subspecialty breast radiologists to consensus. A peer review score was assigned, modeled after ACR's RADPEERTM peer review metric: 1-agree; 2-minor discrepancy (unlikely clinically significant); 3-moderate discrepancy (may be clinically significant); 4-major discrepancy (likely clinically significant). Among cases with clinically significant discrepancies, rates of clinical management change (management alterations including change in follow-up, neoadjuvant therapy use, and surgical management as a direct result of image review), and detection of additional malignancy were assessed through electronic medical record review.Results: A significant difference in interpretation (scores = 3 or 4) was seen in 41 of 252 cases (16%, 95% confidence interval [CI], 11.7%-20.8%). The difference led to additional workup in 38 of 252 cases (15%, 95% CI 10.6%-19.5%) and change in clinical management in 18 of 252 cases (7.1%, 95% CI 4.0%-10.2%), including 15 of 252 with change in surgical management (6.0%, 95% CI, 3.0%-8.9%). An additional malignancy or larger area of disease was identified in 11 of 252 cases (4.4%, 95% CI, 1.8%-6.9%).Conclusion: Discrepancy between outside and second-opinion breast imaging subspecialists frequently results in additional workup for breast cancer patients, changes in treatment plan, and identification of new malignancies. [ABSTRACT FROM AUTHOR]

Introduction The necessity of using granulocyte-colony stimulating factor (G-CSF) during dose-dense (DD) paclitaxel (T) after doxorubicin and cyclophosphamide (AC) is unclear. Methods This was a retrospective cohort study including patients with stage I-III breast cancer treated at Dana-Farber Cancer Institute with adjuvant DD-ACT between January 2011 and December 2013. Descriptive analyses evaluating patterns of G-CSF utilization during T were performed. Results Overall, 156 patients were treated with DD-ACT by 26 providers. The majority of patients (135, 87%) received at least one dose of G-CSF during T (group 1), 17% of these patients received it in only one cycle and 48% received it in all four cycles. Reasons for omitting G-CSF included high baseline absolute neutrophil count and pain. Twenty-one (13%) patients did not receive any G-CSF during T (group 2). Respectively, 94% and 90% of patients completed the treatment in groups 1 and 2. There were no cases of treatment cessation due to neutropenia. Six percent of patients in group 1 had at least one treatment delay. There were no treatment delays reported in group 2. Variation in the use of G-CSF by provider and by patient was found, with 11 providers choosing not to use G-CSF in at least one patient. Conclusions We identified substantial variation in the use of G-CSF within the practice. However, omission of G-CSF was not associated with treatment delays or adverse events. Prospective studies are warranted to formally test whether routine G-CSF is necessary during dose-dense T therapy. [ABSTRACT FROM AUTHOR]

Service processes, for example in transportation, telecommunications or the health sector, are the backbone of today׳s economies. Conceptual models of service processes enable operational analysis that supports, e.g., resource provisioning or delay prediction. In the presence of event logs containing recorded traces of process execution, such operational models can be mined automatically. In this work, we target the analysis of resource-driven, scheduled processes based on event logs. We focus on processes for which there exists a pre-defined assignment of activity instances to resources that execute activities. Specifically, we approach the questions of conformance checking ( how to assess the conformance of the schedule and the actual process execution ) and performance improvement ( how to improve the operational process performance ). The first question is addressed based on a queueing network for both the schedule and the actual process execution. Based on these models, we detect operational deviations and then apply statistical inference and similarity measures to validate the scheduling assumptions, thereby identifying root-causes for these deviations. These results are the starting point for our technique to improve the operational performance. It suggests adaptations of the scheduling policy of the service process to decrease the tardiness (non-punctuality) and lower the flow time. We demonstrate the value of our approach based on a real-world dataset comprising clinical pathways of an outpatient clinic that have been recorded by a real-time location system (RTLS). Our results indicate that the presented technique enables localization of operational bottlenecks along with their root-causes, while our improvement technique yields a decrease in median tardiness and flow time by more than 20%. [ABSTRACT FROM AUTHOR]