Predicting Penicillin Allergy: A United States Multicenter Retrospective Study.

BACKGROUND: Using the reaction history in logistic regression and machine learning (ML) models to predict penicillin allergy has been reported based on non-US data. OBJECTIVE: We developed ML positive penicillin allergy testing prediction models from multisite US data. METHODS: Retrospective data from 4 US-based hospitals were grouped into 4 datasets: enriched training (1:3 case-control matched cohort), enriched testing, nonenriched internal testing, and nonenriched external testing. ML algorithms were used for model development. We determined area under the curve (AUC) and applied the Shapley Additive exPlanations (SHAP) framework to interpret risk drivers. RESULTS: Of 4777 patients (mean age 60 [standard deviation: 17] years; 68% women, 91% White, and 86% non-Hispanic) evaluated for penicillin allergy labels, 513 (11%) had positive penicillin allergy testing. Model input variables were frequently missing: immediate or delayed onset (71%), signs or symptoms (13%), and treatment (31%). The gradient-boosted model was the strongest model with an AUC of 0.67 (95% confidence interval [CI]: 0.57-0.77), which improved to 0.87 (95% CI: 0.73-1) when only cases with complete data were used. Top SHAP drivers for positive testing were reactions within the last year and reactions requiring medical attention; female sex and reaction of hives/urticaria were also positive drivers. CONCLUSIONS: An ML prediction model for positive penicillin allergy skin testing using US-based retrospective data did not achieve performance strong enough for acceptance and adoption. The optimal ML prediction model for positive penicillin allergy testing was driven by time since reaction, seek medical attention, female sex, and hives/urticaria.

Oncologist counseling practice and COVID-19 vaccination outcomes for patients with history of PEG-asparaginase hypersensitivity.

Vaccination against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is an effective strategy to prevent serious coronavirus disease 2019 (COVID-19) and is important for oncology patients. mRNA-based COVID-19 vaccines are contraindicated in those with a history of severe or immediate allergy to any vaccine component, including polyethylene glycol (PEG)2000. Patients with acute lymphoblastic leukemia/lymphoma receive asparaginase conjugated to PEG5000 (PEG-ASNase) and those with PEG-ASNase-associated hypersensitivity may be unnecessarily excluded from receiving mRNA COVID-19 vaccines. We, therefore, surveyed oncologists on COVID-19 vaccine counseling practice and vaccination outcomes in COVID-19 vaccination-eligible patients and show safe receipt of mRNA vaccines despite PEG-ASNase hypersensitivity.

Role of clinical history in beta-lactam hypersensitivity.

PURPOSE OF REVIEW: Understand how the clinical history has been used to risk stratify patients reporting a beta-lactam allergy, both in clinical care pathways and predictive models. RECENT FINDINGS: Drug allergy clinical care pathways have emerged as a safe and effective method of stratifying patients with a reported beta-lactam allergy into risk categories, with 'low-risk' patients able to proceed straight to direct challenges or test doses. These methods have streamlined antibiotic stewardship policies and penicillin allergy de-labeling. However, how to define 'low-risk' has been subject to much debate. New research has developed predictive models that utilize the clinical history to assess a patient's true risk of beta-lactam allergy. SUMMARY: The clinical history has long been an essential part of drug allergy evaluation and has proven invaluable within the past decade in the development of drug allergy clinical pathways. Evidence-based predictive models that use the clinical history to assess a patient's true risk of beta-lactam allergy offer tremendous promise, but differ in crucial areas such as the populations they study, the predictor variables they use, and the ultimate accuracy they attain. These models highlight key aspects of the drug allergy history and pave the way for future large-scale research.

Preoperative penicillin allergy testing in patients undergoing cardiac surgery.

BACKGROUND: Cefazolin is a first-line prophylactic antibiotic used to prevent surgical site infections (SSIs) in cardiac surgery. Patients with a history of penicillin allergy often receive less effective second-line antibiotics, which is associated with an increased SSI risk. OBJECTIVE: To describe the impact of preoperative penicillin allergy evaluation on perioperative cefazolin use in patients undergoing cardiac surgery. METHODS: We performed a retrospective cohort study of patients with a documented penicillin allergy who underwent cardiac surgery at the Massachusetts General Hospital from September 2015 to December 2018. We describe penicillin allergy evaluation assessment and outcomes. We evaluated the association between preoperative penicillin allergy evaluation and first-line perioperative antibiotic use using a multivariable logistic regression model. RESULTS: Of 3802 cardiac surgical patients, 510 (13%) had a documented penicillin allergy; 165 (33%) were referred to allergy and immunology practitioners. Of 160 patients (31%) who underwent penicillin allergy evaluation (ie, penicillin skin testing and, if results were negative, an amoxicillin challenge), 154 (97%) were found not to have a penicillin allergy. Patients who underwent preoperative penicillin allergy evaluation were more likely to receive the first-line perioperative antibiotic (92% vs 38%, P < .001). After adjusting for potential confounders, patients who underwent preoperative penicillin allergy evaluation had higher odds of first-line perioperative antibiotic use (adjusted odds ratio, 26.6; 95% CI, 12.8-55.2). CONCLUSION: Integrating penicillin allergy evaluation into routine preoperative care ensured that almost all evaluated patients undergoing cardiac surgery received first-line antibiotic prophylaxis, a critical component of SSI risk reduction. Further efforts are needed to increase access to preoperative allergy evaluation.