Quantitative MRI radiomics in the prediction of molecular classifications of breast cancer subtypes in the TCGA/TCIA data set

Using quantitative radiomics, we demonstrate that computer-extracted magnetic resonance (MR) image-based tumor phenotypes can be predictive of the molecular classification of invasive breast cancers. Radiomics analysis was performed on 91 MRIs of biopsy-proven invasive breast cancers from National Cancer Institute’s multi-institutional TCGA/TCIA. Immunohistochemistry molecular classification was performed including estrogen receptor, progesterone receptor, human epidermal growth factor receptor 2, and for 84 cases, the molecular subtype (normal-like, luminal A, luminal B, HER2-enriched, and basal-like). Computerized quantitative image analysis included: three-dimensional lesion segmentation, phenotype extraction, and leave-one-case-out cross validation involving stepwise feature selection and linear discriminant analysis. The performance of the classifier model for molecular subtyping was evaluated using receiver operating characteristic analysis. The computer-extracted tumor phenotypes were able to distinguish between molecular prognostic indicators; area under the ROC curve values of 0.89, 0.69, 0.65, and 0.67 in the tasks of distinguishing between ER+ versus ER−, PR+ versus PR−, HER2+ versus HER2−, and triple-negative versus others, respectively. Statistically significant associations between tumor phenotypes and receptor status were observed. More aggressive cancers are likely to be larger in size with more heterogeneity in their contrast enhancement. Even after controlling for tumor size, a statistically significant trend was observed within each size group (P = 0.04 for lesions ≤ 2 cm; P = 0.02 for lesions >2 to≤ 5 cm) as with the entire data set (P-value = 0.006) for the relationship between enhancement texture (entropy) and molecular subtypes (normal-like, luminal A, luminal B, HER2-enriched, basal-like). In conclusion, computer-extracted image phenotypes show promise for high-throughput discrimination of breast cancer subtypes and may yield a quantitative predictive signature for advancing precision medicine

Size Doesn't Matter: Towards a More Inclusive Philosophy of Biology

notes: As the primary author, O’Malley drafted the paper, and gathered and analysed data (scientific papers and talks). Conceptual analysis was conducted by both authors.publication-status: Publishedtypes: ArticlePhilosophers of biology, along with everyone else, generally perceive life to fall into two broad categories, the microbes and macrobes, and then pay most of their attention to the latter. ‘Macrobe’ is the word we propose for larger life forms, and we use it as part of an argument for microbial equality. We suggest that taking more notice of microbes – the dominant life form on the planet, both now and throughout evolutionary history – will transform some of the philosophy of biology’s standard ideas on ontology, evolution, taxonomy and biodiversity. We set out a number of recent developments in microbiology – including biofilm formation, chemotaxis, quorum sensing and gene transfer – that highlight microbial capacities for cooperation and communication and break down conventional thinking that microbes are solely or primarily single-celled organisms. These insights also bring new perspectives to the levels of selection debate, as well as to discussions of the evolution and nature of multicellularity, and to neo-Darwinian understandings of evolutionary mechanisms. We show how these revisions lead to further complications for microbial classification and the philosophies of systematics and biodiversity. Incorporating microbial insights into the philosophy of biology will challenge many of its assumptions, but also give greater scope and depth to its investigations

Racial Disparity in Cardiac Surgery Risk and Outcome: Report From a Statewide Quality Initiative

Background: Racial disparities persist in health care. Our study objective was to evaluate racial disparity in cardiac surgery in Maryland. Methods: A statewide database was used to identify patients. Demographics, comorbidities, and predicted risk of death were compared between races. Crude mortality and incidence of complications were compared between groups, as were risk-adjusted odds for mortality and major morbidity or mortality. Results: The study included 23,094 patients. Most patients were white (75.8%), followed by African American (16.3%), Asian (3.8%), and other races (4.1%). African Americans had a higher preoperative risk for mortality based on The Society of Thoracic Surgeons predictive models compared with white patients (3.0% vs 2.3%, P \u3c .001). African Americans also had higher prevalence of diabetes mellitus, hypertension, peripheral vascular disease, and cerebral vascular disease than white patients. After adjustment for preoperative risk, there was no difference in 30-day mortality between African Americans (odds ratio [OR], 1.26; 95% confidence interval [CI], 0.99-1.59), Asians (OR, 1.22; 95% CI, 0.75-1.97), and other races (OR, 1.18; 95% CI, 0.74-1.89) compared with whites. African Americans had lower risk-adjusted odds of major morbidity or mortality compared with whites (OR, 0.83; 95% CI, 0.75-0.93). Conclusions: African American cardiac surgical patients have the highest preoperative risk in Maryland. Patients appeared to receive excellent cardiac surgical care, regardless of race, as risk-adjusted mortality did not differ between groups, and African American patients had lower risk-adjusted odds of major morbidity or mortality than white patients. Future interventions in Maryland should be aimed at reducing preoperative risk disparity in cardiac surgical patients

Racial disparities among patients on venovenous extracorporeal membrane oxygenation in the pre–Coronavirus Disease 2019 and Coronavirus Disease 2019 eras: A retrospective registry reviewCentral MessagePerspective

Objectives: Although many studies have addressed such disparities caused by COVID-19, to our knowledge, no study has focused on the association of race on outcomes for patients with COVID-19 requiring venovenous extracorporeal membrane oxygenation support. The goal of this study was to assess association of race on death and duration on venovenous extracorporeal membrane oxygenation in both the pre–COVID-19 and COVID-19 eras. Methods: We retrospectively reviewed the Extracorporeal Life Support Organization registry and included adults (≥18 years) who required venovenous extracorporeal membrane oxygenation between January 2019 and April 2021. We performed descriptive statistics and multivariable logistic regression. Our primary outcomes were death and extracorporeal membrane oxygenation duration. Results: A total of 7477 patients were included after excluding 340 patients (4.3%) who were missing race data. In the COVID-19 era, 1474 of 2777 COVID-19–positive patients (53.1%) died. Our regression model suggested somewhat of a protective effect on death for Black and multiple race patients. Additionally, a diagnosis of COVID-19 and patients in the COVID-19 era in general, irrespective of COVID-19 diagnosis, had higher odds of death. Hispanic patients had the longest average venovenous extracorporeal membrane oxygenation run times. Conclusions: Our study using data from the international Extracorporeal Life Support Organization Registry provides updated data on patients supported with venovenous extracorporeal membrane oxygenation in the pre–COVID-19 and COVID-19 eras between 2019 and 2021 with a focus on race. Patients in the COVID-19 era group also had higher mortality compared with those in the pre–COVID-19 era even after being adjusted for COVID-19 diagnosis. Black and multiple races appeared somewhat protective in terms of death. Hispanic race was associated with longer venovenous extracorporeal membrane oxygenation duration