Prognosis of p16 and Human Papillomavirus Discordant Oropharyngeal Cancers and the Exploration of Using Natural Language Processing to Analyze Free-Text Pathology Reports.

Purpose: Treatment deintensification for human papillomavirus-positive (HPV+)-associated oropharyngeal cancer (OPC) has been the catalyst of experts worldwide. In situ hybridization is optimal to identify HPV+ OPC, but immunohistochemistry for its surrogate p16INK4a (p16) is standard-of-care given its availability and sensitivity. HPV testing is not required for clinical management, so treatments are often administered on the basis of p16 status alone.

Application of Machine Learning to the Prediction of Cancer-Associated Venous Thromboembolism.

Venous thromboembolism (VTE) is a common and impactful complication of cancer. Several clinical prediction rules have been devised to estimate the risk of a thrombotic event in this patient population, however they are associated with limitations. We aimed to develop a predictive model of cancer-associated VTE using machine learning as a means to better integrate all available data, improve prediction accuracy and allow applicability regardless of timing for systemic therapy administration.

Relations of Current and Past Cancer with Severe Outcomes among 104,590 Hospitalized COVID-19 Patients: The COVID EHR Cohort at the University of Wisconsin.

Background: There is mixed evidence about the relations of current versus past cancer with severe COVID-19 outcomes and how they vary by patient and cancer characteristics.

Methods: Electronic health record data of 104,590 adult hospitalized patients with COVID-19 were obtained from 21 United States health systems from February 2020 through September 2021. In-hospital mortality and ICU admission were predicted from current and past cancer diagnoses.

Effectiveness of MRNA booster vaccine among healthcare workers in New York City during the Omicron surge, December 2021 to January 2022.

Objective: To describe effectiveness of mRNA vaccines by comparing 2-dose (2D) and 3-dose (3D) healthcare worker (HCW) recipients in the setting of Omicron variant dominance. Performance of 2D and 3D vaccine series against SARS-CoV-2 variants and the clinical outcomes of HCWs may inform return-to-work guidance.

Methods: In a retrospective study from December 15, 2020 to January 15, 2022, SARS-CoV-2 infections among HCWs at a large tertiary cancer centre in New York City were examined to estimate infection rates (aggregated positive tests / person-days) and 95% CIs over the Omicron period in 3D and 2D mRNA vaccinated HCWs and were compared using rate ratios.

Implementing a Clinical Decision Tool to Improve Oncologic Venous Thromboembolism Management.

Background: Cancer patients with venous thromboembolic (VTE) disease are complex, and many factors must be considered when initiating anticoagulation management. Clinical decision support systems can aid in decision-making by utilizing guidelines at the point of care.

Objectives: The purpose of our project was to develop, implement, and evaluate an electronic clinical decision tool (CDT) utilizing evidence-based guidelines to aid in decision-making for adult oncologic patients who present with new VTE to symptom care clinics.

Clinical and Genomic Characterization of Severe Acute Respiratory Syndrome Coronavirus 2 (SARS CoV-2) Infections in mRNA Vaccinated Health Care Personnel in New York City.

Background: Vaccine-induced clinical protection against severe acute respiratory syndrome coronavirus 2 (SARS CoV-2) variants is an evolving target. There are limited genomic level data on SARS CoV-2 breakthrough infections and vaccine effectiveness (VE) since the global spread of the B.1.