Individual meropenem epithelial lining fluid and plasma PK/PD target attainment.

It is unclear whether plasma is a reliable surrogate for target attainment in the epithelial lining fluid (ELF). The objective of this study was to characterize meropenem target attainment in plasma and ELF using prospective samples. The first 24-hour T was evaluated vs 1xMIC and 4xMIC targets at the patient (i.

Iohexol-measured glomerular filtration rate and urinary biomarker changes between vancomycin and vancomycin plus piperacillin-tazobactam in a translational rat model.

Recent clinical studies have reported additive nephrotoxicity with the combination of vancomycin and piperacillin-tazobactam. However, preclinical models have failed to replicate this finding. This study assessed differences in iohexol-measured glomerular filtration rate (GFR) and urinary injury biomarkers among rats receiving this antibiotic combination.

Machine Learning To Stratify Methicillin-Resistant Staphylococcus aureus Risk among Hospitalized Patients with Community-Acquired Pneumonia.

Methicillin-resistant Staphylococcus aureus (MRSA) is an uncommon but serious cause of community-acquired pneumonia (CAP). A lack of validated MRSA CAP risk factors can result in overuse of empirical broad-spectrum antibiotics. We sought to develop robust models predicting the risk of MRSA CAP using machine learning using a population-based sample of hospitalized patients with CAP admitted to either a tertiary academic center or a community teaching hospital.

Maximum Accuracy Machine Learning Statistical Analysis-A Novel Approach.

Logistic regression is a statistical tool of paramount significance in the field of epidemiology and ranks as one of the most frequently published multivariable analyses for designs involving a single binary dependent variable and one or more independent variables in the fields of public health and medical research.

Characterizing Risk Factors for Clostridioides difficile Infection among Hospitalized Patients with Community-Acquired Pneumonia.

Hospitalized patients with community-acquired pneumonia (CAP) are at risk of developing Clostridioides difficile infection (CDI). We developed and tested clinical decision rules for identifying CDI risk in this patient population. The study was a single-center retrospective, case-control analysis of hospitalized adult patients empirically treated for CAP between 1 January 2014 and 3 March 2018.

The First 2 Years of Biosimilar Epoetin for Cancer and Chemotherapy-Induced Anemia in the U.S.: A Review from the Southern Network on Adverse Reactions.

Biosimilars are biologic drug products that are highly similar to reference products in analytic features, pharmacokinetics and pharmacodynamics, immunogenicity, safety, and efficacy. Biosimilar epoetin received Food and Drug Administration (FDA) approval in 2018. The manufacturer received an FDA nonapproval letter in 2017, despite receiving a favorable review by FDA's Oncologic Drugs Advisory Committee (ODAC) and an FDA nonapproval letter in 2015 for an earlier formulation.

Consequences to patients, clinicians, and manufacturers when very serious adverse drug reactions are identified (1997-2019): A qualitative analysis from the Southern Network on Adverse Reactions (SONAR).

Background: Adverse drug/device reactions (ADRs) can result in severe patient harm. We define very serious ADRs as being associated with severe toxicity, as measured on the Common Toxicity Criteria Adverse Events (CTCAE)) scale, following use of drugs or devices with large sales, large financial settlements, and large numbers of injured persons. We report on impacts on patients, clinicians, and manufacturers following very serious ADR reporting.

Antimicrobial never events: Objective application of a framework to assess vancomycin appropriateness.

To address appropriateness of antibiotic use, we implemented an electronic framework to evaluate antibiotic "never events" (NEs) at 2 medical centers. Patient-level vancomycin administration records were classified as NEs or non-NEs. The objective framework allowed capture of true-positive vancomycin NEs in one-third of patients identified by the electronic strategy.

Improving oncology biosimilar launches in the EU, the USA, and Japan: an updated Policy Review from the Southern Network on Adverse Reactions.

The EU, the USA, and Japan account for the majority of biological pharmacotherapy use worldwide. Biosimilar regulatory approval pathways were authorised in the EU (2006), in Japan (2009), and in the USA (2015), to facilitate approval of biological drugs that are highly similar to reference products and to encourage market competition. Between 2007 and 2020, 33 biosimilars for oncology were approved by the European Medicines Agency (EMA), 16 by the US Food and Drug Administration (FDA), and ten by the Japan Pharmaceuticals and Medical Devices Agency (PMDA).

End of an era of administering erythropoiesis stimulating agents among Veterans Administration cancer patients with chemotherapy-induced anemia.

Erythropoisis stimulating agent (ESA) use was addressed in Food and Drug Administration (FDA) Oncology Drug Advisory Committee (ODAC) meetings between 2004 and 2008. FDA safety-focused regulatory actions occurred in 2007 and 2008. In 2007, black box warnings advised of early death and venous thromboembolism (VTE) risks with ESAs in oncology.

Fibromyalgia Impact Reduction Using Online Personal Health Informatics: Longitudinal Observational Study.

Background: Personal health informatics have the potential to help patients discover personalized health management strategies that influence outcomes. Fibromyalgia (FM) is a complex chronic illness requiring individualized strategies that may be informed by analysis of personal health informatics data. An online health diary program with dynamic feedback was developed to assist patients with FM in identifying symptom management strategies that predict their personal outcomes, and found reduced symptom levels associated with program use.

End of an era for erythropoiesis-stimulating agents in oncology.

Erythropoiesis-stimulating agents (ESAs) are available to treat chemotherapy-induced anemia (CIA). In 2007-2008, regulatory notifications advised of venous thromboembolism and mortality risks while the Center for Medicare and Medicaid Services' restricted ESA initiation to patients with hemoglobin <10 g/dl. In 2010, a Risk Evaluation and Mitigation Strategies required consent prior to administration.

Caveat Medicus: Clinician experiences in publishing reports of serious oncology-associated adverse drug reactions.

Oncology-associated adverse drug/device reactions can be fatal. Some clinicians who treat single patients with severe oncology-associated toxicities have researched case series and published this information. We investigated motivations and experiences of select individuals leading such efforts.

Regulatory and Clinical Experiences with Biosimilar Filgrastim in the U.S., the European Union, Japan, and Canada.

Biosimilar filgrastims are primarily indicated for chemotherapy-induced neutropenia prevention. They are less expensive formulations of branded filgrastim, and biosimilar filgrastim was the first biosimilar oncology drug administered in European Union (EU) countries, Japan, and the U.S.

Identifying causal mechanisms in health care interventions using classification tree analysis.

Rationale, Aims, And Objectives: Mediation analysis identifies causal pathways by testing the relationships between the treatment, the outcome, and an intermediate variable that mediates the relationship between the treatment and outcome. This paper introduces classification tree analysis (CTA), a machine-learning procedure, as an alternative to conventional methods for analysing mediation effects.

Method: Using data from the JOBS II study, we compare CTA to structural equation models (SEMs) by assessing their consistency in revealing mediation effects on 2 outcomes; reemployment (a binary variable) and depressive symptoms (a continuous variable).

Minimizing imbalances on patient characteristics between treatment groups in randomized trials using classification tree analysis.

Rationale, Aims, And Objectives: Randomization ensures that treatment groups do not differ systematically in their characteristics, thereby reducing threats to validity that may otherwise explain differences in outcomes. Large observed imbalances in patient characteristics may indicate that selection bias is being introduced into the treatment allocation process. We introduce classification tree analysis (CTA) as a novel algorithmic approach for identifying potential imbalances in characteristics and their interactions when provisionally assigning each new participant to one or the other treatment group.

Modeling time-to-event (survival) data using classification tree analysis.

Rationale, Aims, And Objectives: Time to the occurrence of an event is often studied in health research. Survival analysis differs from other designs in that follow-up times for individuals who do not experience the event by the end of the study (called censored) are accounted for in the analysis. Cox regression is the standard method for analysing censored data, but the assumptions required of these models are easily violated.

Melanoma complicating treatment with natalizumab for multiple sclerosis: A report from the Southern Network on Adverse Reactions (SONAR).

A 43-year-old female with multiple sclerosis developed urethral melanoma. The only potential risk factor was treatment with natalizumab, a humanized monoclonal antibody against α4 integrins. To investigate the risk-exposure relationship, we reviewed this case, all other published cases, and cases of natalizumab-associated melanoma reported to regulatory agencies.

Tale of Two Erythropoiesis-Stimulating Agents: Utilization, Dosing, Litigation, and Costs of Darbepoetin and Epoetin Among South Carolina Medicaid-Covered Patients With Cancer and Chemotherapy-Induced Anemia.

Purpose: The US Food and Drug Administration (FDA) has approved epoetin and darbepoetin for chemotherapy-induced anemia (CIA). Approved epoetin and darbepoetin dosing schedules were three times per week and weekly, respectively, although off-label, less frequent scheduling was common. In 2004, 2007, and 2008, a US Food and Drug Administration Advisory Committees warned of risks associated with erythropoiesis-stimulating agents.

Using classification tree analysis to generate propensity score weights.

Rationale, Aims And Objectives: In evaluating non-randomized interventions, propensity scores (PS) estimate the probability of assignment to the treatment group given observed characteristics. Machine learning algorithms have been proposed as an alternative to conventional logistic regression for modelling PS in order to avoid limitations of linear methods. We introduce classification tree analysis (CTA) to generate PS which is a "decision-tree"-like classification model that provides accurate, parsimonious decision rules that are easy to display and interpret, reports P values derived via permutation tests, and evaluates cross-generalizability.

Persistent erectile dysfunction in men exposed to the 5α-reductase inhibitors, finasteride, or dutasteride.

Importance: Case reports describe persistent erectile dysfunction (PED) associated with exposure to 5α-reductase inhibitors (5α-RIs). Clinical trial reports and the manufacturers' full prescribing information (FPI) for finasteride and dutasteride state that risk of sexual adverse effects is not increased by longer duration of 5α-RI exposure and that sexual adverse effects of 5α-RIs resolve in men who discontinue exposure.

Objective: Our chief objective was to assess whether longer duration of 5α-RI exposure increases risk of PED, independent of age and other known risk factors.

Combining machine learning and propensity score weighting to estimate causal effects in multivalued treatments.

Rationale, Aims And Objectives: Interventions with multivalued treatments are common in medical and health research; examples include comparing the efficacy of competing interventions and contrasting various doses of a drug. In recent years, there has been growing interest in the development of methods that estimate multivalued treatment effects using observational data. This paper extends a previously described analytic framework for evaluating binary treatments to studies involving multivalued treatments utilizing a machine learning algorithm called optimal discriminant analysis (ODA).