Building Data-Driven Pathways From Routinely Collected Hospital Data:A Case Study on Prostate Cancer

Background: Routinely collected data in hospitals is complex, typically heterogeneous, and scattered across multiple Hospital Information Systems (HIS). This big data, created as a byproduct of health care activities, has the potential to provide a better understanding of diseases, unearth hidden patterns, and improve services and cost. The extent and uses of such data rely on its quality, which is not consistently checked, nor fully understood. Nevertheless, using routine data for the construction of data-driven clinical pathways, describing processes and trends, is a key topic receiving increasing attention in the literature. Traditional algorithms do not cope well with unstructured processes or data, and do not produce clinically meaningful visualizations. Supporting systems that provide additional information, context, and quality assurance inspection are needed. Objective: The objective of the study is to explore how routine hospital data can be used to develop data-driven pathways that describe the journeys that patients take through care, and their potential uses in biomedical research; it proposes a framework for the construction, quality assessment, and visualization of patient pathways for clinical studies and decision support using a case study on prostate cancer. Methods: Data pertaining to prostate cancer patients were extracted from a large UK hospital from eight different HIS, validated, and complemented with information from the local cancer registry. Data-driven pathways were built for each of the 1904 patients and an expert knowledge base, containing rules on the prostate cancer biomarker, was used to assess the completeness and utility of the pathways for a specific clinical study. Software components were built to provide meaningful visualizations for the constructed pathways. Results: The proposed framework and pathway formalism enable the summarization, visualization, and querying of complex patient-centric clinical information, as well as the computation of quality indicators and dimensions. A novel graphical representation of the pathways allows the synthesis of such information. Conclusions: Clinical pathways built from routinely collected hospital data can unearth information about patients and diseases that may otherwise be unavailable or overlooked in hospitals. Data-driven clinical pathways allow for heterogeneous data (ie, semistructured and unstructured data) to be collated over a unified data model and for data quality dimensions to be assessed. This work has enabled further research on prostate cancer and its biomarkers, and on the development and application of methods to mine, compare, analyze, and visualize pathways constructed from routine data. This is an important development for the reuse of big data in hospitals

A mathematical model of the human metabolic system and metabolic flexibility

In healthy subjects some tissues in the human body display metabolic flexibility, by this we mean the ability for the tissue to switch its fuel source between predominantly carbohydrates in the post prandial state and predominantly fats in the fasted state. Many of the pathways involved with human metabolism are controlled by insulin, and insulin- resistant states such as obesity and type-2 diabetes are characterised by a loss or impairment of metabolic flexibility. In this paper we derive a system of 12 first-order coupled differential equations that describe the transport between and storage in different tissues of the human body. We find steady state solutions to these equations and use these results to nondimensionalise the model. We then solve the model numerically to simulate a healthy balanced meal and a high fat meal and we discuss and compare these results. Our numerical results show good agreement with experimental data where we have data available to us and the results show behaviour that agrees with intuition where we currently have no data with which to compare

Seasonal change in the daily timing of behaviour of the common vole, Microtus arvalis

1. Seasonal effects on daily activity patterns in the common vole were established by periodic trapping in the field and continuous year round recording of running wheel and freeding activity in cages exposed to natural meteorological conditions. 2. Trapping revealed decreased nocturnality in winter as compared to summer. This was paralelled by a winter reduction in both nocturnal wheel running and feeding time in cages. 3. Frequent trap checks revealed a 2 h rhythm in daytime catches in winter, not in summer. Cage feeding activity in daytime was always organized in c. 2 h intervals, but day-to-day variations in phase blurred the rhythm in summer in a summation of individual daily records. Thus both seasonal and short-term temporal patterns are consistent between field trappings and cage feeding records. 4. Variables associated with the seasonal change in daily pattern were: reproductive state (sexually active voles more nocturnal), age (juveniles more nocturnal), temperature (cold days: less nocturnal), food (indicated by feeding experiments), habitat structure (more nocturnal in habitat with underground tunnels). 5. Minor discrepancies between field trappings and cage feeding activity can be explained by assuming increased trappability of voles in winter. Cage wheel running is not predictive of field trapping patterns and is thought to reflect behavioral motivations not associated with feeding but with other activities (e.g., exploratory, escape, interactive behaviour) undetected by current methods, including radiotelemetry and passage-counting. 6. Winter decrease in nocturnality appears to involve a reduction in nocturnal non-feeding and feeding behaviour and is interpreted primarily as an adaptation to reduce energy expenditure in adverse but socially stable winter conditions.

The impact of obesity on time spent with the provider and number of medications managed during office-based physician visits using a cross-sectional, national health survey

<p>Abstract</p> <p>Background</p> <p>Obesity is associated with morbidity, mortality, and increased health care costs. Few studies have examined the impact of obesity on outpatient office visits. The purpose of this study was to determine if outpatient visits by obese persons required more time with the provider and more prescription medication management compared to visits made by non-obese persons.</p> <p>Methods</p> <p>Obesity status was determined for 9,280 patient visits made by persons aged 18 years or older in the 2006 National Ambulatory Medical Care Survey. Multivariate analyses compared obese and non-obese visits, stratified by sex, for duration of the visit and the number of medications mentioned at the visit.</p> <p>Results</p> <p>Average duration of visit was higher among visits with patients determined to be obese. However, these differences were not considered significant after statistical testing. Visits made by obese female patients were significantly more likely to involve more than two prescription medications (OR 1.26, 95% CI 1.05 - 1.51) and visits made by obese male patients were significantly more likely to involve more than two prescription medications (OR 1.46, 95% CI 1.16 - 1.83) as compared to visits made by non-obese patients.</p> <p>Conclusion</p> <p>Time spent with the provider was found to be greater among visits with obese patients, but not significantly different from visits with non-obese patients. The number of medications for each visit was found to be significantly greater for visits where the patient was considered to be obese. Increased time for the visit and increased numbers of medication for each visit translate into increased costs. These findings document the impact of obesity on our health care system and have great implications on medical care cost and planning.</p

Nutritional Systems Biology Modeling: From Molecular Mechanisms to Physiology

The use of computational modeling and simulation has increased in many biological fields, but despite their potential these techniques are only marginally applied in nutritional sciences. Nevertheless, recent applications of modeling have been instrumental in answering important nutritional questions from the cellular up to the physiological levels. Capturing the complexity of today's important nutritional research questions poses a challenge for modeling to become truly integrative in the consideration and interpretation of experimental data at widely differing scales of space and time. In this review, we discuss a selection of available modeling approaches and applications relevant for nutrition. We then put these models into perspective by categorizing them according to their space and time domain. Through this categorization process, we identified a dearth of models that consider processes occurring between the microscopic and macroscopic scale. We propose a “middle-out” strategy to develop the required full-scale, multilevel computational models. Exhaustive and accurate phenotyping, the use of the virtual patient concept, and the development of biomarkers from “-omics” signatures are identified as key elements of a successful systems biology modeling approach in nutrition research—one that integrates physiological mechanisms and data at multiple space and time scales

The SNAPSHOT study protocol : SNAcking, Physical activity, Self-regulation, and Heart rate Over Time

Peer reviewedPublisher PD

Molecular evolution of HoxA13 and the multiple origins of limbless morphologies in amphibians and reptiles

Developmental processes and their results, morphological characters, are inherited through transmission of genes regulating development. While there is ample evidence that cis-regulatory elements tend to be modular, with sequence segments dedicated to different roles, the situation for proteins is less clear, being particularly complex for transcription factors with multiple functions. Some motifs mediating protein-protein interactions may be exclusive to particular developmental roles, but it is also possible that motifs are mostly shared among different processes. Here we focus on HoxA13, a protein essential for limb development. We asked whether the HoxA13 amino acid sequence evolved similarly in three limbless clades: Gymnophiona, Amphisbaenia and Serpentes. We explored variation in ω (dN/dS) using a maximum-likelihood framework and HoxA13sequences from 47 species. Comparisons of evolutionary models provided low ω global values and no evidence that HoxA13 experienced relaxed selection in limbless clades. Branch-site models failed to detect evidence for positive selection acting on any site along branches of Amphisbaena and Gymnophiona, while three sites were identified in Serpentes. Examination of alignments did not reveal consistent sequence differences between limbed and limbless species. We conclude that HoxA13 has no modules exclusive to limb development, which may be explained by its involvement in multiple developmental processes

Towards Alignment Independent Quantitative Assessment of Homology Detection

Identification of homologous proteins provides a basis for protein annotation. Sequence alignment tools reliably identify homologs sharing high sequence similarity. However, identification of homologs that share low sequence similarity remains a challenge. Lowering the cutoff value could enable the identification of diverged homologs, but also introduces numerous false hits. Methods are being continuously developed to minimize this problem. Estimation of the fraction of homologs in a set of protein alignments can help in the assessment and development of such methods, and provides the users with intuitive quantitative assessment of protein alignment results. Herein, we present a computational approach that estimates the amount of homologs in a set of protein pairs. The method requires a prevalent and detectable protein feature that is conserved between homologs. By analyzing the feature prevalence in a set of pairwise protein alignments, the method can estimate the number of homolog pairs in the set independently of the alignments' quality. Using the HomoloGene database as a standard of truth, we implemented this approach in a proteome-wide analysis. The results revealed that this approach, which is independent of the alignments themselves, works well for estimating the number of homologous proteins in a wide range of homology values. In summary, the presented method can accompany homology searches and method development, provides validation to search results, and allows tuning of tools and methods

Defining the phenotypes of sickle cell disease.

The sickle cell gene is pleiotropic in nature. Although it is a single gene mutation, it has multiple phenotypic expressions that constitute the complications of sickle cell disease. The frequency and severity of these complications vary considerably both latitudinally in patients and longitudinally in the same patient over time. Thus, complications that occur in childhood may disappear, persist or get worse with age. Dactylitis and stroke, for example, occur mostly in childhood, whereas leg ulcers and renal failure typically occur in adults. It is essential that the phenotypic manifestations of sickle cell disease be defined accurately so that communication among providers and researchers facilitates the implementation of appropriate and cost-effective diagnostic and therapeutic modalities. The aim of this review is to define the complications that are specific to sickle cell disease based on available evidence in the literature and the experience of hematologists in this field

Anti-tumour activity and toxicity of the new prodrug9-aminocamptothecin glucuronide (9ACG) in mice

Cancer chemotherapy is limited by the modest therapeutic index of most antineoplastic drugs. Some glucuronide prodrugs may display selective anti-tumour activity against tumours that accumulate β-glucuronidase. We examined the toxicity and anti-tumour activity of 9-aminocamptothecin glucuronide, a new glucuronide prodrug of 9-aminocamptothecin, to evaluate its potential clinical utility. 9-aminocamptothecin glucuronide was 25–60 times less toxic than 9-aminocamptothecin to five human cancer cell lines. β-glucuronidase activated 9-aminocamptothecin glucuronide to produce similar cell killing as 9-aminocamptothecin or topotecan. The in vivo toxicity of 9-aminocamptothecin glucuronide in BALB/c mice was dose-, route-, sex- and age-dependent. 9-aminocamptothecin glucuronide was significantly less toxic to female than to male mice but the difference decreased with age. 9-aminocamptothecin glucuronide and 9-aminocamptothecin produced similar inhibition (∼80%) of LS174T human colorectal carcinoma tumours. 9-aminocamptothecin glucuronide cured a high percentage of CL1-5 human lung cancer xenografts with efficacy that was similar to or greater than 9-aminocamptothecin, irinotecan and topotecan. The potent anti-tumour activity of 9-aminocamptothecin glucuronide suggests that this prodrug should be further evaluated for cancer treatment