Citations

AbstractBackgroundThe optimal treatment for respiratory syncytial virus (RSV) infection in adult immunocompromised patients is unknown. We assessed the management of RSV and other non‐influenza respiratory viruses in Midwestern transplant centers.MethodsA survey assessing strategies for RSV and other non‐influenza respiratory viral infections was sent to 13 centers.ResultsMultiplex polymerase chain reaction assay was used for diagnosis in 11/12 centers. Eight of 12 centers used inhaled ribavirin (RBV) in some patient populations. Barriers included cost, safety, lack of evidence, and inconvenience. Six of 12 used intravenous immunoglobulin (IVIG), mostly in combination with RBV. Inhaled RBV was used more than oral, and in the post‐stem cell transplant population, patients with lower respiratory tract infection (LRTI), graft‐versus‐host disease, and more recent transplantation were treated at higher rates. Ten centers had experience with lung transplant patients; all used either oral or inhaled RBV for LRTI, 6/10 treated upper respiratory tract infection (URTI). No center treated non‐lung solid organ transplant (SOT) recipients with URTI; 7/11 would use oral or inhaled RBV in the same group with LRTI. Patients with hematologic malignancy without hematopoietic stem cell transplantation were treated with RBV at a similar frequency to non‐lung SOT recipients. Three of 12 centers, in severe cases, treated parainfluenza and metapneumovirus, and 1/12 treated coronavirus.ConclusionsTreatment of RSV in immunocompromised patients varied greatly. While most centers treat LRTI, treatment of URTI was variable. No consensus was found regarding the use of oral versus inhaled RBV, or the use of IVIG. The presence of such heterogeneity demonstrates the need for further studies defining optimal treatment of RSV in immunocompromised hosts.

ABSTRACT The health care-associated pneumonia (HCAP) criteria have a limited ability to predict pneumonia caused by drug-resistant bacteria and favor the overutilization of broad-spectrum antibiotics. We aimed to derive and validate a clinical prediction score with an improved ability to predict the risk of pneumonia due to drug-resistant pathogens compared to that of HCAP criteria. A derivation cohort of 200 microbiologically confirmed pneumonia cases in 2011 and 2012 was identified retrospectively. Risk factors for pneumonia due to drug-resistant pathogens were evaluated by logistic regression, and a novel prediction score (the drug resistance in pneumonia [DRIP] score) was derived. The score was then validated in a prospective, observational cohort of 200 microbiologically confirmed cases of pneumonia at four U.S. centers in 2013 and 2014. The DRIP score (area under the receiver operator curve [AUROC], 0.88 [95% confidence interval {CI}, 0.82 to 0.93]) performed significantly better ( P = 0.02) than the HCAP criteria (AUROC, 0.72 [95% CI, 0.64 to 0.79]). At a threshold of ≥4 points, the DRIP score demonstrated a sensitivity of 0.82 (95% CI, 0.67 to 0.88), a specificity of 0.81 (95% CI, 0.73 to 0.87), a positive predictive value (PPV) of 0.68 (95% CI, 0.56 to 0.78), and a negative predictive value (NPV) of 0.90 (95% CI, 0.81 to 0.93). By comparison, the performance of HCAP criteria was less favorable: sensitivity was 0.79 (95% CI, 0.67 to 0.88), specificity was 0.65 (95% CI, 0.56 to 0.73), PPV was 0.53 (95% CI, 0.42 to 0.63), and NPV was 0.86 (95% CI, 0.77 to 0.92). The overall accuracy of the HCAP criteria was 69.5% (95% CI, 62.5 to 75.7%), whereas that of the DRIP score was 81.5% (95% CI, 74.2 to 85.6%) ( P = 0.005). Unnecessary extended-spectrum antibiotics were recommended 46% less frequently by applying the DRIP score (25/200, 12.5%) than by use of HCAP criteria (47/200, 23.5%) ( P = 0.004), without increasing the rate at which inadequate treatment recommendations were made. The DRIP score was more predictive of the risk of pneumonia due to drug-resistant pathogens than HCAP criteria and may have the potential to decrease antibiotic overutilization in patients with pneumonia. Validation in larger cohorts of patients with pneumonia due to all causes is necessary.

Genetic variation can affect drug response in multiple ways, although it remains unclear how rare genetic variants affect drug response. The electronic Medical Records and Genomics (eMERGE) Network, collaborating with the Pharmacogenomics Research Network, began eMERGE‐PGx, a targeted sequencing study to assess genetic variation in 82 pharmacogenes critical for implementation of “precision medicine.” The February 2015 eMERGE‐PGx data release includes sequence‐derived data from ∼5,000 clinical subjects. We present the variant frequency spectrum categorized by variant type, ancestry, and predicted function. We found 95.12% of genes have variants with a scaled Combined Annotation‐Dependent Depletion score above 20, and 96.19% of all samples had one or more Clinical Pharmacogenetics Implementation Consortium Level A actionable variants. These data highlight the distribution and scope of genetic variation in relevant pharmacogenes, identifying challenges associated with implementing clinical sequencing for drug treatment at a broader level, underscoring the importance for multifaceted research in the execution of precision medicine.

AbstractDisorders affecting smooth muscle structure/function may require technologies that can generate large scale, differentiated and contractile smooth muscle cells (SMC) suitable for cell therapy. To date no clonal precursor population that provides large numbers of differentiated SMC in culture has been identified in a rodent. Identification of such cells may also enhance insight into progenitor cell fate decisions and the relationship between smooth muscle precursors and disease states that implicate differentiated SMC. In this study, we used classic clonal expansion techniques to identify novel self-renewing Islet 1 (Isl-1) positive primitive progenitor cells (PPC) within rat bone marrow that exhibited canonical stem cell markers and preferential differentiation towards a smooth muscle-like fate. We subsequently used molecular tagging to select Isl-1 positive clonal populations from expanded and de novo marrow cell populations. We refer to these previously undescribed cells as the PPC given its stem cell marker profile, and robust self-renewal capacity. PPC could be directly converted into induced smooth muscle cells (iSMC) using single transcription factor (Kruppel-like factor 4) knockdown or transactivator (myocardin) overexpression in contrast to three control cells (HEK 293, endothelial cells and mesenchymal stem cells) where such induction was not possible. iSMC exhibited immuno- and cytoskeletal-phenotype, calcium signaling profile and contractile responses similar to bona fide SMC. Passaged iSMC could be expanded to a scale sufficient for large scale tissue replacement. PPC and reprogramed iSMC so derived may offer future opportunities to investigate molecular, structure/function and cell-based replacement therapy approaches to diverse cardiovascular, respiratory, gastrointestinal, and genitourinary diseases that have as their basis smooth muscle cell functional aberrancy or numerical loss.

ABSTRACTThe rapid increase and poor survival of esophageal adenocarcinoma (EAC) have led to significant efforts to promote early detection. Given that the premalignant lesion of Barrett's esophagus (BE) is the major known risk factor for EAC, multiple investigators have studied biomarker signatures that can predict malignant progression of BE to EAC. MicroRNAs, a novel class of gene regulators, are small non‐coding RNAs and have been associated with carcinogenesis. MicroRNAs are ideal biomarkers because of their remarkable stability in fixed tissues, a common method for collection of clinical specimens, and in blood either within exosomes or as microRNA‐protein complexes. Multiple studies show potential of microRNAs as tissue and blood biomarkers for diagnosis and prognosis of EAC but the results need confirmation in prospective studies. Although head‐to‐head comparisons are lacking, microRNA panels require less genes than messenger RNA panels for diagnosis of EAC in BE. MicroRNA diagnostic panels will need to be compared for accuracy against global measures of genome instability that were recently shown to be good predictors of progression but require sophisticated analytic techniques. Early studies on blood microRNA panels are promising but have found microRNA markers to be inconsistent among studies. MicroRNA expression in blood is different between various microRNA sub‐compartments such as exosomes and microRNA‐protein complexes and could affect blood microRNA measurements. Further standardization is needed to yield consistent results. We have summarized the current understanding of the tissue and blood microRNA signatures that may predict the development and progression of EAC. J. Cell. Biochem. 117: 1288–1295, 2016. © 2016 Wiley Periodicals, Inc.

The American Joint Committee on Cancer (AJCC) has increasingly recognized the need for more personalized probabilistic predictions than those delivered by ordinal staging systems, particularly through the use of accurate risk models or calculators. However, judging the quality and acceptability of a risk model is complex. The AJCC Precision Medicine Core conducted a 2‐day meeting to discuss characteristics necessary for a quality risk model in cancer patients. More specifically, the committee established inclusion and exclusion criteria necessary for a risk model to potentially be endorsed by the AJCC. This committee reviewed and discussed relevant literature before creating a checklist unique to this need of AJCC risk model endorsement. The committee identified 13 inclusion and 3 exclusion criteria for AJCC risk model endorsement in cancer. The emphasis centered on performance metrics, implementation clarity, and clinical relevance. The facilitation of personalized probabilistic predictions for cancer patients holds tremendous promise, and these criteria will hopefully greatly accelerate this process. Moreover, these criteria might be useful for a general audience when trying to judge the potential applicability of a published risk model in any clinical domain. CA Cancer J Clin 2016;66:370–374. © 2016 American Cancer Society.

This study was performed to determine if there were a time of year that children were more likely to transition into a chronic daily headache. We retrospectively reviewed records of 103 patients with chronic migraine and 104 patients with new daily persistent headache. Of these, 56 chronic migraine and 92 new daily persistent headache patients were able to identify the specific month in which they began to experience daily headaches. Thirty-nine percent of new daily persistent headache patients had an onset of daily headache in either September or January, months traditionally associated with the start of the school semester in the United States. Only a single patient reported onset in May or June. Data for the transition from episodic to chronic migraine also showed higher rates in September and January, but did not reach statistical significance. These data demonstrate the higher rates of new daily persistent headache onset during school start months and question what factors may be responsible for this association.