Classifying publications from the clinical and translational science award program along the translational research spectrum: a machine learning approach

BACKGROUND: Translational research is a key area of focus of the National Institutes of Health (NIH), as demonstrated by the substantial investment in the Clinical and Translational Science Award (CTSA) program. The goal of the CTSA program is to accelerate the translation of discoveries from the bench to the bedside and into communities. Different classification systems have been used to capture the spectrum of basic to clinical to population health research, with substantial differences in the number of categories and their definitions. Evaluation of the effectiveness of the CTSA program and of translational research in general is hampered by the lack of rigor in these definitions and their application. This study adds rigor to the classification process by creating a checklist to evaluate publications across the translational spectrum and operationalizes these classifications by building machine learning-based text classifiers to categorize these publications. METHODS: Based on collaboratively developed definitions, we created a detailed checklist for categories along the translational spectrum from T0 to T4. We applied the checklist to CTSA-linked publications to construct a set of coded publications for use in training machine learning-based text classifiers to classify publications within these categories. The training sets combined T1/T2 and T3/T4 categories due to low frequency of these publication types compared to the frequency of T0 publications. We then compared classifier performance across different algorithms and feature sets and applied the classifiers to all publications in PubMed indexed to CTSA grants. To validate the algorithm, we manually classified the articles with the top 100 scores from each classifier. RESULTS: The definitions and checklist facilitated classification and resulted in good inter-rater reliability for coding publications for the training set. Very good performance was achieved for the classifiers as represented by the area under the receiver operating curves (AUC), with an AUC of 0.94 for the T0 classifier, 0.84 for T1/T2, and 0.92 for T3/T4. CONCLUSIONS: The combination of definitions agreed upon by five CTSA hubs, a checklist that facilitates more uniform definition interpretation, and algorithms that perform well in classifying publications along the translational spectrum provide a basis for establishing and applying uniform definitions of translational research categories. The classification algorithms allow publication analyses that would not be feasible with manual classification, such as assessing the distribution and trends of publications across the CTSA network and comparing the categories of publications and their citations to assess knowledge transfer across the translational research spectrum

Occurrence of liver cirrhosis in England, a cohort study, 1998-2009: a comparison with cancer

OBJECTIVES: There is no routine registration of the occurrence of newly diagnosed cases of cirrhosis in the United Kingdom. This study seeks to determine precise estimates and trends of the incidence of cirrhosis in England, and directly compare these figures with those for the 20 most commonly diagnosed cancers in the United Kingdom. METHODS: We used the Clinical Practice Research Datalink and linked English Hospital Episode Statistics to perform a population-based cohort study. Adult incident cases with a diagnosis of cirrhosis between January 1998 and December 2009 were identified. We described trends in incidence by sex and etiology. We performed a direct standardization to estimate the number of people being newly diagnosed with cirrhosis in 2009, and calculated the change in incidence between 1998 and 2009. RESULTS: A total of 5,118 incident cases of cirrhosis were identified, 57.9% were male. Over the 12-year period, crude incidence increased by 50.6%. Incidence increased for both men and women and all etiology types. We estimated approximately 17,000 people were newly diagnosed with cirrhosis in 2009 in the United Kingdom, greater than that of the fifth most common cancer non-Hodgkin's lymphoma. The percentage change in incidence of cirrhosis between 1998 and 2009 for both men (52.4%) and women (38.3%) was greater than that seen for the top four most commonly diagnosed cancers in the United Kingdom (breast, lung, bowel, and prostate). CONCLUSIONS: The occurrence of cirrhosis increased more than that of the top four cancers during 1998 to 2009 in England. Strategies to monitor and reduce the incidence of this disease are urgently needed

Transcriptomal Insights of Heart Failure from Normality to Recovery.

Current management of heart failure (HF) is centred on modulating the progression of symptoms and severity of left ventricular dysfunction. However, specific understandings of genetic and molecular targets are needed for more precise treatments. To attain a clearer picture of this, we studied transcriptome changes in a chronic progressive HF model. Fifteen sheep (Ovis aries) underwent supracoronary aortic banding using an inflatable cuff. Controlled and progressive induction of pressure overload in the LV was monitored by echocardiography. Endomyocardial biopsies were collected throughout the development of LV failure (LVF) and during the stage of recovery. RNA-seq data were analysed using the PANTHER database, Metascape, and DisGeNET to annotate the gene expression for functional ontologies. Echocardiography revealed distinct clinical differences between the progressive stages of hypertrophy, dilatation, and failure. A unique set of transcript expressions in each stage was identified, despite an overlap of gene expression. The removal of pressure overload allowed the LV to recover functionally. Compared to the control stage, there were a total of 256 genes significantly changed in their expression in failure, 210 genes in hypertrophy, and 73 genes in dilatation. Gene expression in the recovery stage was comparable with the control stage with a well-noted improvement in LV function. RNA-seq revealed the expression of genes in each stage that are not reported in cardiovascular pathology. We identified genes that may be potentially involved in the aetiology of progressive stages of HF, and that may provide future targets for its management

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Additional file 5. Threshold validation: For 50 articles randomly chosen from each decile of the scores returned by the T0 classifier this file lists the PMID, the classifier score, and a manual classification of either “T0” or “not T0”