Systemic Therapy in Breast Cancer.

Therapeutic advances in breast cancer have significantly improved outcomes in recent decades. In the early setting, there has been a gradual shift from adjuvant-only to neoadjuvant strategies, with a growing focus on customizing post-neoadjuvant treatments through escalation and de-escalation based on pathologic response. At the same time, the transition from a pre-genomic to a post-genomic era, utilizing specific assays in the adjuvant setting and targeted sequencing in the advanced stage, has deepened our understanding of disease biology and aided in identifying molecular markers associated with treatment benefit. Finally, the introduction of new drug classes such as antibody-drug conjugates, and the incorporation in the (neo)adjuvant setting of therapies previously investigated in the advanced stage, like immunotherapy and CDK4-6 inhibitors, poses new challenges in treatment sequencing.

Surgical Site Infection in the Intensive Care Setting After Posterior Spinal Fusion: A Case Series Highlighting the Microbial Profile, Risk Factors, and the Importance of Comorbid Disease Burden.

BACKGROUND: Most posterior spinal fusion (PSF) patients do not require admission to an intensive care unit (ICU), and those who do may represent an underinvestigated, high-risk subpopulation. OBJECTIVE: To identify the microbial profile of and risk factors for surgical site infection (SSI) in PSF patients admitted to the ICU postoperatively. METHODS: We examined 3965 consecutive PSF patients treated at our institution between 2000 and 2015 and collected demographic, clinical, and procedural data. Comorbid disease burden was quantified using the Charlson Comorbidity Index (CCI). We performed multivariable logistic regression to identify risk factors for SSI, readmission, and reoperation. RESULTS: Anemia, more levels fused, cervical surgery, and cerebrospinal fluid leak were positively associated with ICU admission, and minimally invasive surgery was negatively associated. The median time to infection was equivalent for ICU patients and non-ICU patients, and microbial culture results were similar between groups. Higher CCI and undergoing a staged procedure were associated with readmission, reoperation, and SSI. When stratified by CCI into quintiles, SSI rates show a strong linear correlation with CCI ( P = .0171, R = 0.941), with a 3-fold higher odds of SSI in the highest risk group than the lowest (odds ratio = 3.15 [1.19, 8.07], P = .032). CONCLUSION: Procedural characteristics drive the decision to admit to the ICU postoperatively. Patients admitted to the ICU have higher rates of SSI but no difference in the timing of or microorganisms that lead to those infections. Comorbid disease burden drives SSI in this population, with a 3-fold greater odds of SSI for high-risk patients than low-risk patients.

Metastatic Myxofibrosarcoma with Durable Response to Temozolomide Followed by Atezolizumab: A Case Report.

Myxofibrosarcoma (MFS) is a well-recognized histotype of soft tissue sarcomas that generally presents with localized disease. Herein, we describe the case of a patient with metastatic MFS who experienced durable response to sixth-line therapy with temozolomide. Upon further progression, his tumor was notable for a high tumor mutational burden, and he was subsequently treated with seventh-line immunotherapy, atezolizumab, achieving a second durable response. This case highlights the role of immunotherapy after administration of alkylating agents. Review of the literature indicates that recurrent tumors treated with alkylating agents often experience hypermutation as a means of developing resistance and that checkpoint inhibitors are subsequently effective in these tumors. KEY POINTS: To the authors' knowledge, this is the first report of a patient with myxofibrosarcoma with high tumor mutational burden after administration of temozolomide monotherapy. Hypermutation may be a resistance mechanism for patients with soft tissue sarcoma who develop resistance to alkylating agents. Checkpoint inhibition may be effective therapy in patients with soft tissue sarcoma with high tumor mutational burden as a consequence of alternate systemic therapy resistance.

Surgical Site Infection, Readmission, and Reoperation After Posterior Long Segment Fusion.

STUDY DESIGN: Retrospective case series. OBJECTIVE: We sought to identify risk factors associated with surgical site infection (SSI) after posterior long segment spinal fusion (PLSF). SUMMARY OF BACKGROUND DATA: Patients who undergo PLSF may be at elevated risk of SSI. Identifying factors associated with SSI in these operations can help risk stratify patients and tailor management. METHODS: We analyzed PLSFs-seven or more levels-at our institution from 2000 to 2015. Data on patients' clinical characteristics, procedural factors, and antimicrobial management were collected. Multivariable analysis identified factors independently associated with outcomes of interest. RESULTS: In 628 cases, SSI was associated with steroid use (P = 0.024, odds ratio [OR] = 2.54) and using cefazolin (P < 0.001, OR = 4.37) or bacitracin (P = 0.010, OR 3.49) irrigation, as opposed to gentamicin or other irrigation. Gram-positive infections were more likely with staged procedures (P = 0.021, OR 4.91) and bacitracin irrigation (P < 0.001, OR = 17.98), and less likely with vancomycin powder (P = 0.050, OR 0.20). Gram-negative infections were more likely with a history of peripheral arterial disease (P = 0.034, OR = 3.21) or cefazolin irrigation (P < 0.001, OR 25.47). Readmission was more likely after staged procedures (P = 0.003, OR = 3.31), cervical spine surgery (P = 0.023, OR = 2.28), or cefazolin irrigation (P = 0.039, OR = 1.85). Reoperation was more common with more comorbidities (P = 0.022, OR 1.09), staged procedures (P < 0.001, OR = 4.72), cervical surgeries (P = 0.013, OR = 2.36), more participants in the surgery (P = 0.011, OR = 1.06), using cefazolin (P < 0.001, OR = 3.12) or bacitracin (P = 0.009, OR = 3.15) irrigation, and higher erythrocyte sedimentation rate at readmission (P = 0.009, OR = 1.04). Washouts were more likely among patients with more comorbidities (P = 0.013, OR = 1.16), or who used steroids (P = 0.022, OR = 2.92), and less likely after cervical surgery (P = 0.028, OR = 0.24). Instrumentation removal was more common with bacitracin irrigation (p = 0.013, OR = 31.76). CONCLUSION: Patient factors, whether a procedure is staged, and choice of antibiotic irrigation affect the risk of SSI and ensuing management required.Level of Evidence: 4.

Using artificial intelligence (AI) to predict postoperative surgical site infection: A retrospective cohort of 4046 posterior spinal fusions.

OBJECTIVES: Machine Learning and Artificial Intelligence (AI) are rapidly growing in capability and increasingly applied to model outcomes and complications within medicine. In spinal surgery, post-operative surgical site infections (SSIs) are a rare, yet morbid complication. This paper applied AI to predict SSIs after posterior spinal fusions. PATIENTS AND METHODS: 4046 posterior spinal fusions were identified at a single academic center. A Deep Neural Network DNN classification model was trained using 35 unique input variables The model was trained and tested using cross-validation, in which the data were randomly partitioned into training n = 3034 and testing n = 1012 datasets. Stepwise multivariate regression was further used to identify actual model weights based on predictions from our trained model. RESULTS: The overall rate of infection was 1.5 %. The mean area under the curve (AUC), representing the accuracy of the model, across all 300 iterations was 0.775 (95 % CI [0.767,0.782]) with a median AUC of 0.787. The positive predictive value (PPV), representing how well the model predicted SSI when a patient had SSI, over all predictions was 92.56 % with a negative predictive value (NPV), representing how well the model predicted absence of SSI when a patient did not have SSI, of 98.45 %. In analyzing relative model weights, the five highest weighted variables were Congestive Heart Failure, Chronic Pulmonary Failure, Hemiplegia/Paraplegia, Multilevel Fusion and Cerebrovascular Disease respectively. Notable factors that were protective against infection were ICU Admission, Increasing Charlson Comorbidity Score, Race (White), and being male. Minimally invasive surgery (MIS) was also determined to be mildly protective. CONCLUSION: Machine learning and artificial intelligence are relevant and impressive tools that should be employed in the clinical decision making for patients. The variables with the largest model weights were primarily comorbidity related with the exception of multilevel fusion. Further study is needed, however, in order to draw any definitive conclusions.