Gene Screening for Prognosis of Non-Muscle-Invasive Bladder Carcinoma under Competing Risks Endpoints.

Background: Discovering clinically useful molecular markers for predicting the survival of patients diagnosed with non−muscle-invasive bladder cancer can provide insights into cancer dynamics and improve treatment outcomes. However, the presence of competing risks (CR) endpoints complicates the estimation and inferential framework. There is also a lack of statistical analysis tools and software for coping with the high-throughput nature of these data, in terms of marker screening and selection. Aims: To propose a gene screening procedure for proportional subdistribution hazards regression under a CR framework, and illustrate its application in using molecular profiling to predict survival for non-muscle invasive bladder carcinoma. Methods: Tumors from 300 patients diagnosed with bladder cancer were analyzed for genomic abnormalities while controlling for clinically important covariates. Genes with expression patterns that were associated with survival were identified through a screening procedure based on proportional subdistribution hazards regression. A molecular predictor of risk was constructed and examined for prediction accuracy. Results: A six-gene signature was found to be a significant predictor associated with survival of non−muscle-invasive bladder cancer, subject to competing risks after adjusting for age, gender, reevaluated WHO grade, stage and BCG/MMC treatment (p-value < 0.001). Conclusion: The proposed gene screening procedure can be used to discover molecular determinants of survival for non−muscle-invasive bladder cancer and in general facilitate high-throughput competing risks data analysis with easy implementation.

Gene Screening in High-Throughput Right-Censored Lung Cancer Data.

Background: Advances in sequencing technologies have allowed collection of massive genome-wide information that substantially advances lung cancer diagnosis and prognosis. Identifying influential markers for clinical endpoints of interest has been an indispensable and critical component of the statistical analysis pipeline. However, classical variable selection methods are not feasible or reliable for high-throughput genetic data. Our objective is to propose a model-free gene screening procedure for high-throughput right-censored data, and to develop a predictive gene signature for lung squamous cell carcinoma (LUSC) with the proposed procedure. Methods: A gene screening procedure was developed based on a recently proposed independence measure. The Cancer Genome Atlas (TCGA) data on LUSC was then studied. The screening procedure was conducted to narrow down the set of influential genes to 378 candidates. A penalized Cox model was then fitted to the reduced set, which further identified a 6-gene signature for LUSC prognosis. The 6-gene signature was validated on datasets from the Gene Expression Omnibus. Results: Both model-fitting and validation results reveal that our method selected influential genes that lead to biologically sensible findings as well as better predictive performance, compared to existing alternatives. According to our multivariable Cox regression analysis, the 6-gene signature was indeed a significant prognostic factor (p-value < 0.001) while controlling for clinical covariates. Conclusions: Gene screening as a fast dimension reduction technique plays an important role in analyzing high-throughput data. The main contribution of this paper is to introduce a fundamental yet pragmatic model-free gene screening approach that aids statistical analysis of right-censored cancer data, and provide a lateral comparison with other available methods in the context of LUSC.

Adipose-Derived Inflammatory and Coagulant Mediators in Patients With Sepsis.

ABSTRACT: Results from preclinical sepsis studies using rodents are often criticized as not being reproducible in humans. Using a murine model, we previously reported that visceral adipose tissues (VAT) are highly active during the acute inflammatory response, serving as a major source of inflammatory and coagulant mediators. The purpose of this study was to determine whether these findings are recapitulated in patients with sepsis and to evaluate their clinical significance. VAT and plasma were obtained from patients undergoing intra-abdominal operations with noninflammatory conditions (control), local inflammation, or sepsis. In mesenteric and epiploic VAT, gene expression of pro-inflammatory (TNFα, IL-6, IL-1α, IL-1ß) and pro-coagulant (PAI-1, PAI-2, TSP-1, TF) mediators was increased in sepsis compared with control and local inflammation groups. In the omentum, increased expression was limited to IL-1ß, PAI-1, and PAI-2, showing a depot-specific regulation. Histological analyses showed little correlation between cellular infiltration and gene expression, indicating a resident source of these mediators. Notably, a strong correlation between PAI-1 expression in VAT and circulating protein levels was observed, both being positively associated with markers of acute kidney injury (AKI). In another cohort of septic patients stratified by incidence of AKI, circulating PAI-1 levels were higher in those with versus without AKI, thus extending these findings beyond intra-abdominal cases. This study is the first to translate upregulation of VAT mediators in sepsis from mouse to human. Collectively, the data suggest that development of AKI in septic patients is associated with high plasma levels of PAI-1, likely derived from resident cells within VAT.

Prescribing patterns of opioid analgesics in a dental setting: 2013-2018.

OBJECTIVE: Analgesic prescribing patterns are influenced by internal and external factors. Understanding these factors could help improve prescribing practices. STUDY DESIGN: We conducted a retrospective analysis of electronic health records with regard to analgesic prescriptions written from 2013 through 2018 at the University of Kentucky College of Dentistry. Deidentified information (age, gender, dental procedures, analgesic drug, quantity, and refills) were recorded and studied with respect to national guidelines and recent state legislation using the χ2 test, analysis of variance, logistic regression, and multiple linear regression. RESULTS: Opioids comprised 74.9% of the 17,099 analgesic prescriptions written. Extractions were most commonly associated with opioid prescriptions. Multivariate analysis showed that (1) older patients were more likely to receive an opioid prescription (P < .01) but with fewer pills (P < .01); (2) surgical extractions were associated with a lower opioid prescription rate (P < .01) but more opioid pills per prescription compared with nonsurgical extractions (P < .01); and (3) the odds of receiving an opioid prescription and the number of opioid pills prescribed decreased over year after release of the national guideline (P < .01) and after enactment of state legislation (P < .01). CONCLUSIONS: Regulations and guidelines were associated with reduction in opioid prescriptions.

Status epilepticus alert reduces time to administration of second-line antiseizure medications.

BACKGROUND: Status epilepticus (SE) is a neurologic emergency with high morbidity and mortality. Delays in SE treatment are common in clinical practice and can be associated with poorer outcomes. Our goal was to determine whether the implementation of an SE alert protocol improves time to administration of a second-line antiseizure medication (ASM) in hospitalized adults. METHODS: We developed and implemented an inpatient SE alert system. A quasiexperimental cohort study was performed. We analyzed all patients aged 18-85 years who were managed at the University of Kentucky Medical Center using the SE alert protocol between March 2015 and June 2017 (n = 19). Controls were the first 20 consecutive patients treated for SE over the same time period, but who were managed with usual care (i.e., without SE alert protocol). RESULTS: Time to administration of a second-line ASM was shorter with the use of the SE alert system (22.21 ± 3.44 minutes) compared to usual care (58.30 ± 6.72 minutes; p < 0.0001). CONCLUSION: Implementation of an SE alert system led to a marked improvement in time to administration of a second-line ASM. CLASSIFICATION OF EVIDENCE: This study provides Class III evidence that for adult inpatients treated for SE, implementation of an SE alert protocol reduces time to administration of second-line ASM.