A Real World Perspective of PARP Inhibitor Use in Gynecological Cancer Patients.

Introduction: Over the last few years, targeted therapy has become the mainstay maintenance treatment of patients with ovarian cancer including patients with BRCA1/BRCA2 mutations. Poly ADP ribose polymerase inhibitors (PARPi) are effective in the treatment of patients who are in complete or partial remission. PARPi are known to cause hematological adverse events (AEs), but have not been compared directly to each other. Objective: Primary objective was to compare the incidence of hematological and non-hematological AEs associated with the use of PARPi. Methods: This was a single institution, retrospective study evaluating patients who were treated with PARPi for ovarian cancer from January 2017 to October 2020. Patients were stratified according to which PARP inhibitor they received. Results: Ninety-two patients were included in final analysis. Thirty-one (33.7%) patients received niraparib and 61 (66.3%) patients received olaparib. Median age of patients were 64.3 (range, 33.8 to 92.3) years, 66 (71.7%) were white, and 84 (91.3%) had an ECOG PS of 0/1. Patients in the niraparib group experienced a higher rate of hematologic AEs, with 11 (35.5%), 20 (64.5%), and 18 (58.1%) experiencing neutropenia, anemia, and thrombocytopenia, respectively. Eight (13.1%), 24 (39.3%), and 16 (26.2%) patients in the olaparib group experienced neutropenia, anemia, and thrombocytopenia, respectively. Conclusion: This single institution retrospective study outlines the hematological toxicities observed between two PARPi. Our results suggested that niraparib tended to be associated with a higher risk for hematologic toxicities than olaparib. Anemia was the most common hematologic toxicity which was consistent with what has been widely documented in the literature.

Racial/ethnic discrimination, anxiety, and suicidal thoughts among ethnoracially minoritized college students.

Rates of suicidal thoughts and behaviors have disproportionately increased among ethnoracially minoritized college students. Despite growing evidence suggesting racial/ethnic discrimination may confer suicide-related risk, less is known about mechanisms underlying this relation. The present study aimed to clarify the potential role of anxiety in the association between racial/ethnic discrimination and suicidal thoughts. Participants (N = 747; 61% female; 63% U.S. born) were college students ages 18-29 years old (M = 19.84; SD = 2.22) who identified from an ethnoracially minoritized background (34% Asian, 33% Latinx/Hispanic, 23% Black, and 10% as other ethnoracially minoritized group). They were recruited from a minority-serving institution in the Northeast United States, and completed a battery of surveys online. Findings from multiple hierarchical linear regression models and bootstrapping procedures suggest there is a direct association between racial/ethnic discrimination and suicidal thoughts among Black college students only, though not among college students identifying as Latinx, Asian, and other race/ethnicity. Further, there was an indirect association between racial/ethnic discrimination and suicidal thoughts through generalized anxiety, though not race-based anxiety or social anxiety, across different ethnoracially minoritized groups. This information would help improve the cultural responsiveness of suicide prevention strategies for college students by refining identification of individuals at greatest risk for the harmful effects of racial/ethnic discrimination and providing more refined targets for intervention. (PsycInfo Database Record (c) 2022 APA, all rights reserved).

A contemporary review of rearranged during transfection-selective inhibitors.

OBJECTIVE: Rearranged during transfection genes are present in 1-2% of patients who have non-small cell lung cancer and 10-30% of patients with papillary thyroid cancer. The objective of this article is to review the current rearranged during transfection inhibitors indicated for patients with rearranged during transfection-mutated cancers and their future directions.Data sources: The pivotal phase I/II studies for selpercatinib and pralsetinib were evaluated. Current studies on rearranged during transfection inhibitors were searched on ClinicalTrials.gov using the key word "RET."Data summary: Selpercatinib and pralsetinib were the first two U.S. Food and Drug Administration-approved rearranged during transfection-selective inhibitors for advanced or metastatic rearranged during transfection fusion-positive non-small cell lung cancer, rearranged during transfection-mutant medullary thyroid cancer, and rearranged during transfection fusion-positive thyroid cancer. Both agents showed promising efficacy with objective response rate ranging from 60% to 73% in all aforementioned rearranged during transfection-mutated cancers. Additionally, benefits were seen even in patients with intracranial metastasis at baseline. Both showed favorable safety profiles. Some common class adverse events included elevated liver function tests and hypertension. Hematologic side effects such as anemia and neutropenia were more common with pralsetinib. Selpercatinib had interactions with acid suppressive therapy and specific instructions when used concomitantly. CONCLUSIONS: While the rearranged during transfection inhibitors are generally well-tolerated, each agent possesses slightly different efficacy, side-effect profile, and drug-drug interactions.

ensembleTax: an R package for determinations of ensemble taxonomic assignments of phylogenetically-informative marker gene sequences.

BACKGROUND: High-throughput sequencing of phylogenetically informative marker genes is a widely used method to assess the diversity and composition of microbial communities. Taxonomic assignment of sampled marker gene sequences (referred to as amplicon sequence variants, or ASVs) imparts ecological significance to these genetic data. To assign taxonomy to an ASV, a taxonomic assignment algorithm compares the ASV to a collection of reference sequences (a reference database) with known taxonomic affiliations. However, many taxonomic assignment algorithms and reference databases are available, and the optimal algorithm and database for a particular scientific question is often unclear. Here, we present the ensembleTax R package, which provides an efficient framework for integrating taxonomic assignments predicted with any number of taxonomic assignment algorithms and reference databases to determine ensemble taxonomic assignments for ASVs. METHODS: The ensembleTax R package relies on two core algorithms: taxmapper and assign.ensembleTax. The taxmapper algorithm maps taxonomic assignments derived from one reference database onto the taxonomic nomenclature (a set of taxonomic naming and ranking conventions) of another reference database. The assign.ensembleTax algorithm computes ensemble taxonomic assignments for each ASV in a data set based on any number of taxonomic assignments determined with independent methods. Various parameters allow analysts to prioritize obtaining either more ASVs with more predicted clade names or more robust clade name predictions supported by multiple independent methods in ensemble taxonomic assignments. RESULTS: The ensembleTax R package is used to compute two sets of ensemble taxonomic assignments for a collection of protistan ASVs sampled from the coastal ocean. Comparisons of taxonomic assignments predicted by individual methods with those predicted by ensemble methods show that conservative implementations of the ensembleTax package minimize disagreements between taxonomic assignments predicted by individual and ensemble methods, but result in ASVs with fewer ranks assigned taxonomy. Less conservative implementations of the ensembleTax package result in an increased fraction of ASVs classified at all taxonomic ranks, but increase the number of ASVs for which ensemble assignments disagree with those predicted by individual methods. DISCUSSION: We discuss how implementation of the ensembleTax R package may be optimized to address specific scientific objectives based on the results of the application of the ensembleTax package to marine protist communities. While further work is required to evaluate the accuracy of ensemble taxonomic assignments relative to taxonomic assignments predicted by individual methods, we also discuss scenarios where ensemble methods are expected to improve the accuracy of taxonomy prediction for ASVs.