Deep learning with electronic health records for short-term fracture risk identification : crystal bone algorithm development and validation

Background: Fractures as a result of osteoporosis and low bone mass are common and give rise to significant clinical, personal, and economic burden. Even after a fracture occurs, high fracture risk remains widely underdiagnosed and undertreated. Common fracture risk assessment tools utilize a subset of clinical risk factors for prediction, and often require manual data entry. Furthermore, these tools predict risk over the long term and do not explicitly provide short-term risk estimates necessary to identify patients likely to experience a fracture in the next 1-2 years. Objective: The goal of this study was to develop and evaluate an algorithm for the identification of patients at risk of fracture in a subsequent 1- to 2-year period. In order to address the aforementioned limitations of current prediction tools, this approach focused on a short-term timeframe, automated data entry, and the use of longitudinal data to inform the predictions. Methods: Using retrospective electronic health record data from over 1,000,000 patients, we developed Crystal Bone, an algorithm that applies machine learning techniques from natural language processing to the temporal nature of patient histories to generate short-term fracture risk predictions. Similar to how language models predict the next word in a given sentence or the topic of a document, Crystal Bone predicts whether a patient’s future trajectory might contain a fracture event, or whether the signature of the patient’s journey is similar to that of a typical future fracture patient. A holdout set with 192,590 patients was used to validate accuracy. Experimental baseline models and human-level performance were used for comparison. Results: The model accurately predicted 1- to 2-year fracture risk for patients aged over 50 years (area under the receiver operating characteristics curve [AUROC] 0.81). These algorithms outperformed the experimental baselines (AUROC 0.67) and showed meaningful improvements when compared to retrospective approximation of human-level performance by correctly identifying 9649 of 13,765 (70%) at-risk patients who did not receive any preventative bone-health-related medical interventions from their physicians. Conclusions: These findings indicate that it is possible to use a patient’s unique medical history as it changes over time to predict the risk of short-term fracture. Validating and applying such a tool within the health care system could enable automated and widespread prediction of this risk and may help with identification of patients at very high risk of fracture

Application of the National Osteoporosis Foundation Guidelines to postmenopausal women and men: the Framingham Osteoporosis Study.

Summary We applied the 2008 National Osteoporosis Foundation (NOF) Guidelines to Framingham Osteoporosis Study participants and found nearly one half of Caucasian postmenopausal women and one sixth of men aged 50 years and older would be recommended for osteoporosis treatment. Given the high proportion of persons recommended for treatment, NOF Guidelines may need to be re-evaluated with respect to budget impact. Introduction Little is known about the public health impact of the NOF Guidelines. Therefore, we determined the proportion of US Caucasians recommended for treatment of osteoporosis according to NOF Guidelines (2003 and 2008). Methods One thousand nine hundred and forty-six postmenopausal women and 1,681 men aged ≥50 years from the Framingham Study with information on bone mineral density (1987–2001) were included. Information on clinical predictors was used to estimate the 10-year probability of hip and major osteoporotic fracture by FRAX® (version 3.0). Results Overall proportion of women meeting treatment criterion was less when the 2008 NOF Guidelines were applied (41.1%) compared with 2003 Guidelines (47.8%). The proportion of women aged 75 years increased slightly (78.3% in 2003, 86.0% in 2008). Seventeen percent of men aged ≥50 years met treatment criterion (2.5% aged 50–64 years, 49.8% aged >75 years). Conclusions Nearly one half of Caucasian postmenopausal women and one sixth of men aged 50 years and older would be recommended for osteoporosis treatment according to 2008 NOF Guidelines. Given the high proportion of persons recommended for treatment, NOF Guidelines may need to be re-evaluated with respect to budget impact

The risk of hip and non-vertebral fractures in type 1 and type 2 diabetes: A systematic review and meta-analysis update

Background Diabetes is associated with increased fracture risk but we do not know what affects this risk. We investigated the risk of hip and non-vertebral fractures in diabetes and whether this risk was affected by age, gender, body mass index, diabetes type and duration, insulin use and diabetic complications. Methods We selected a previously published review to be updated. MEDLINE, Embase and Cochrane databases were searched up to March 2020. We included observational studies with age and gender-adjusted risk of fractures in adults with diabetes compared to adults without diabetes. We extracted data from published reports that we summarised using random effects model. Findings From the 3140 records identified, 49 were included, 42 in the hip fracture analysis, reporting data from 17,571,738 participants with 319,652 fractures and 17 in the non-vertebral fracture review, reporting data from 2,978,487 participants with 181,228 fractures. We found an increase in the risk of fracture in diabetes both for hip (RR 4.93, 3.06–7.95, in type 1 diabetes and RR1.33, 1.19–1.49, in type 2 diabetes) and for non-vertebral fractures (RR 1.92, 0.92–3.99, in type 1 and RR 1.19, 1,11–1.28 in type 2). At the hip, the risk was higher in the younger population in both type 1 and type 2 diabetes. In those with type 2 diabetes, longer diabetes duration and insulin use was associated with an increased risk. We did not investigate the effect of bone density, falls, anti-diabetic drugs and hypoglycemia. Conclusion Diabetes is associated with an increase in both hip and non-vertebral fracture risk

Large-scale pharmacogenomic study of sulfonylureas and the QT, JT and QRS intervals: CHARGE Pharmacogenomics Working Group

Sulfonylureas, a commonly used class of medication used to treat type 2 diabetes, have been associated with an increased risk of cardiovascular disease. Their effects on QT interval duration and related electrocardiographic phenotypes are potential mechanisms for this adverse effect. In 11 ethnically diverse cohorts that included 71 857 European, African-American and Hispanic/Latino ancestry individuals with repeated measures of medication use and electrocardiogram (ECG) measurements, we conducted a pharmacogenomic genome-wide association study of sulfonylurea use and three ECG phenotypes: QT, JT and QRS intervals. In ancestry-specific meta-analyses, eight novel pharmacogenomic loci met the threshold for genome-wide significance (P<5 × 10−8), and a pharmacokinetic variant in CYP2C9 (rs1057910) that has been associated with sulfonylurea-related treatment effects and other adverse drug reactions in previous studies was replicated. Additional research is needed to replicate the novel findings and to understand their biological basis

Scintillation Counters for the D0 Muon Upgrade

We present the results of an upgrade to the D0 muon system. Scintillating counters have been added to the existing central D0 muon system to provide rejection for cosmic ray muons and out-of-time background, and to provide additional fast timing information for muons in an upgraded Tevatron. Performance and results from the 1994-1996 Tevatron run are presented.Comment: 30 pages, 25 postscript figure

Genome-wide meta-analysis of variant-by-diuretic interactions as modulators of lipid traits in persons of European and African ancestry

Hypertension (HTN) is a significant risk factor for cardiovascular morbidity and mortality. Metabolic abnormalities, including adverse cholesterol and triglycerides (TG) profiles, are frequent comorbid findings with HTN and contribute to cardiovascular disease. Diuretics, which are used to treat HTN and heart failure, have been associated with worsening of fasting lipid concentrations. Genome-wide meta-analyses with 39,710 European-ancestry (EA) individuals and 9925 African-ancestry (AA) individuals were performed to identify genetic variants that modify the effect of loop or thiazide diuretic use on blood lipid concentrations. Both longitudinal and cross sectional data were used to compute cohort-specific interaction results, which were then combined through meta-analysis in each ancestry. These ancestry-specific results were further combined through trans-ancestry meta-analysis. Analysis of EA data identified two genome-wide significant (p < 5 × 10−8) loci with single nucleotide variant (SNV)-loop diuretic interaction on TG concentrations (including COL11A1). Analysis of AA data identified one genome-wide significant locus adjacent to BMP2 with SNV-loop diuretic interaction on TG concentrations. Trans-ancestry analysis strengthened evidence of association for SNV-loop diuretic interaction at two loci (KIAA1217 and BAALC). There were few significant SNV-thiazide diuretic interaction associations on TG concentrations and for either diuretic on cholesterol concentrations. Several promising loci were identified that may implicate biologic pathways that contribute to adverse metabolic side effects from diuretic therapy

Evidence of Color Coherence Effects in W+jets Events from ppbar Collisions at sqrt(s) = 1.8 TeV

We report the results of a study of color coherence effects in ppbar collisions based on data collected by the D0 detector during the 1994-1995 run of the Fermilab Tevatron Collider, at a center of mass energy sqrt(s) = 1.8 TeV. Initial-to-final state color interference effects are studied by examining particle distribution patterns in events with a W boson and at least one jet. The data are compared to Monte Carlo simulations with different color coherence implementations and to an analytic modified-leading-logarithm perturbative calculation based on the local parton-hadron duality hypothesis.Comment: 13 pages, 6 figures. Submitted to Physics Letters

Breast cancer metastasis to gynaecological organs: a clinico-pathological and molecular profiling study

Breast cancer metastasis to gynaecological organs is an understudied pattern of tumour spread. We explored clinico-pathological and molecular features of these metastases to better understand whether this pattern of dissemination is organotropic or a consequence of wider metastatic dissemination. Primary and metastatic tumours from 54 breast cancer patients with gynaecological metastases were analysed using immunohistochemistry, DNA copy-number profiling, and targeted sequencing of 386 cancer-related genes. The median age of primary tumour diagnosis amongst patients with gynaecological metastases was significantly younger compared to a general breast cancer population (46.5 versus 60 years; p < 0.0001). Median age at metastatic diagnosis was 54.4, time to progression was 4.8 years (range 0-20 years), and survival following a diagnosis of metastasis was 1.95 years (range 0-18 years). Patients had an average of five involved sites (most frequently ovary, fallopian tube, omentum/peritoneum), with fewer instances of spread to the lungs, liver, or brain. Invasive lobular histology and luminal A-like phenotype were over-represented in this group (42.8 and 87.5%, respectively) and most patients had involved axillary lymph nodes (p < 0.001). Primary tumours frequently co-expressed oestrogen receptor cofactors (GATA3, FOXA1) and harboured amplifications at 8p12, 8q24, and 11q13. In terms of phenotype conversion, oestrogen receptor status was generally maintained in metastases, FOXA1 increased, and expression of progesterone receptor, androgen receptor, and GATA3 decreased. ESR1 and novel AR mutations were identified. Metastasis to gynaecological organs is a complication frequently affecting young women with invasive lobular carcinoma and luminal A-like breast cancer, and hence may be driven by sustained hormonal signalling. Molecular analyses reveal a spectrum of factors that could contribute to de novo or acquired resistance to therapy and disease progression.Jamie R Kutasovic, Amy E McCart Reed, Renique Males, Sarah Sim, Jodi M Saunus ... Liana Dedina ... et al