Citations

The emergence of pathologist-driven molecular reflex testing for tumoural biomarkers is a significant advancement in cancer diagnostics, facilitating targeted cancer therapy for our patients. Based on our experience, the Canadian landscape of pathologist-driven reflex biomarker testing for melanoma lacks standardization and is plagued by a lack of awareness by pathologists and clinicians. This paper comprehensively examines the approaches to reflex biomarker testing for melanoma patients across Canada, highlighting the regional variations in the criteria for initiating molecular testing, the biomarkers tested, and the molecular techniques employed. We also discuss the clinical relevance of biomarkers, emphasizing their alignment with the National Comprehensive Cancer Network ® (NCCN ® ) Clinical Practice Guidelines in Oncology (NCCN Guidelines ® ) as well as ancillary tests such as BRAF VE1 immunohistochemistry to detect BRAF V600E mutation and molecular techniques such as real-time polymerase chain reaction, matrix-assisted laser desorption ionization-time of flight mass spectrometry and next-generation sequencing. Our proposed standardized minimum criteria for reflex testing prioritize melanomas with Breslow thickness >4 mm or disseminated disease, who will most benefit from enhanced delivery of biomarkers and expedited access to targeted therapies while attempting to balance cost-effectiveness and utilization of public healthcare resources with patient outcomes.

Immunotherapy has shown significant improvement in the survival of patients with hepatocellular carcinoma (HCC) compared to TKIs as first-line treatment. Unfortunately, approximately 30% of HCC exhibits intrinsic resistance to ICIs, making new therapeutic combinations urgently needed. The dysregulation of the Notch signaling pathway observed in HCC can affect immune cell response, reducing the efficacy of cancer immunotherapy. Here, we provide an overview of how Notch signaling regulates immune responses and present the therapeutic rationale for combining Notch signaling inhibition with ICIs to improve HCC treatment. Moreover, we propose using exosomes as non-invasive tools to assess Notch signaling activation in hepatic cancer cells, enabling accurate stratification of patients who can benefit from combined strategies.

AbstractThe aim of this study was to identify hospital‐based workplace violence (WPV) risk factors with the Haddon Matrix Model (HMM) to determine its potential utility to conceptualize multiple risks for WPV events. This descriptive study utilized two independent convenience samples Data from behavioral emergencies (2014–2015) for patient violence (N = 192) and from health care staff (N = 380) 12‐month violence survey responses (2015) in a Midwestern academic hospital were analyzed. Logistic regression examined patient features associated with physical violence. Survey questions pertained to employee, environment, and cultural factors associated with WPV; responses were examined with Chi‐square and two‐sample t‐tests. Violence risk factors populated the 4 Haddon Matrix domains at pre‐event time frames as Host (worker)‐age/demographics, Agent (patient)‐age/gender, Physical Environment‐door/window structure, and Social Environment‐worker safety. Risks at event time frames populated for Agent—behavior/delirium, and Physical Environment—event medication/patient identification. The Haddon Matrix identification of hospital violence risks indicates its utility as a comprehensive approach to workplace violence.

ABSTRACT There are limited and conflicting data on sex and urban‐rural disparities in outcomes of patients with pulmonary embolism (PE) in the reproductive age group. Our object was to assess sex disparities in the reproductive age group cohort. All adult non‐elective admissions in the reproductive age group (18−49 years) with a primary diagnosis of PE and with no missing sex/age data were identified using the National Inpatient Sample. Females and males were stratified into rural and urban location based on hospital information. Outcomes of interest included in‐hospital mortality, complication rates, variations in management, total hospitalization costs, and length of stay. During 01/01/2016 to 12/31/2020, 180,898 PE admissions aged 18−49 years were identified (rural—12,319 [6.8%]). Females comprised 54.8% and 55.1% of the rural and urban cohorts, respectively. Overall, compared to males, females in urban and rural regions had largely comparable rates of definitive PE interventions, except lower rates of catheter directed therapy (4.7 vs. 3.6%, p < 0.001) in females admitted to urban hospitals. Despite younger age, higher comorbidity, and lower utilization of PE interventions, females in both regions had similar unadjusted in‐hospital mortality (rural 1.1% vs. 1.0%; p = 0.93 and urban 1.8% vs. 1.7%; p = 0.78) and hospitalization costs compared to males. In conclusion, females of reproductive age group had comparable in‐hospital outcomes to males in both urban and rural areas. Females in urban areas had lower utilization of advanced PE interventions, potentially indicating selective management strategies in different settings.

Abstract Background Acquired resistance to temozolomide (TMZ) chemotherapy due to DNA mismatch repair (MMR) enzyme deficiency is a barrier to improving outcomes for isocitrate dehydrogenase (IDH) wild-type glioblastoma (GBM) patients. KL-50 is a new imidazotetrazine-based therapeutic designed to induce DNA interstrand cross-links, and subsequent double-stranded breaks, in an MMR-independent manner in cells with O-6-methylguanine-DNA methyltransferase (MGMT) deficiency. Previous research showed its efficacy against LN229 glioma cells with MMR and MGMT knockdown. Its activity against patient-derived GBM that model post-TMZ recurrent tumors is unclear. Methods We created MMR-deficient GBM patient-derived xenografts through exposure to TMZ, followed by treatment with additional TMZ or KL-50. We also generated isogenic, MSH6 knockout (KO) patient-derived GBM and tested them for sensitivity to TMZ and KL-50. Results KL-50 extended the median survival of mice intracranially engrafted with either patient-derived TMZ-naïve GBM6 or TMZ-naïve GBM12 by 1.75-fold and 2.15-fold, respectively (P &lt; 0.0001). A low dose (4 Gy) of fractionated RT further extended the survival of KL-50-treated GBM12 mice (median survival = 80 days for RT + KL-50 vs. 71 days KL-50 alone, P = 0.018). KL-50 also extended the median survival of mice engrafted with post-TMZ, MMR-deficient GBM6R-m185 (140 days for KL-50 vs. 37 days for vehicle, P &lt; 0.0001). MSH6 KO increased TMZ IC50 for GBM6 and GBM12 cultures by &gt;5-fold and &gt;12-fold for cell death and live cell count outputs, respectively. In contrast, MSH6-KO actually decreased KL-50 IC50 by 10–80%. Conclusion KL-50-based compounds are a promising new strategy for the treatment of MGMT-deficient, MMR-deficient GBM that recurs after frontline TMZ.

Abstract Objective The goal is to provide an overview of artificial intelligence (AI) and machine learning (ML) methodology and appraisal tailored to clinicians and researchers in the headache field to facilitate interdisciplinary communications and research. Background The application of AI to the study of headache and other healthcare challenges is growing rapidly. It is critical that these findings be accurately interpreted by headache specialists, but this can be difficult for non‐AI specialists. Methods This paper is a narrative review of the fundamentals required to understand ML/AI headache research. Using guidance from key leaders in the field of headache medicine and AI, important references were reviewed and cited to provide a comprehensive overview of the terminology, methodology, applications, pitfalls, and bias of AI. Results We review how AI models are created, common model types, methods for evaluation, and examples of their application to headache medicine. We also highlight potential pitfalls relevant when consuming AI research, and discuss ethical issues of bias, privacy and abuse generated by AI. Additionally, we highlight recent related research from across headache‐related applications. Conclusion Many promising current and future applications of ML and AI exist in the field of headache medicine. Understanding the fundamentals of AI will allow readers to understand and critically appraise AI‐related research findings in their proper context. This paper will increase the reader's comfort in consuming AI/ML‐based research and will prepare them to think critically about related research developments.