Marshall MS, Boyce RD, Deus H, Zhao J, Willighagen E, Samwald M, Pichler E, Hajagos J, Prud’hommeaux E, Stephens S. Emerging practices for mapping life sciences data to RDF - a case series. Journal of Web Semantics. Special Issue: Reasoning with Context in the Semantic Web. (In Press).
Age-related Changes in Antidepressant Pharmacokinetics and Potential Drug-Drug Interactions: A Comparison of Evidence-Based Literature and Package Insert Information
Boyce RD, Handler SM, Karp JF, Hanlon JT. Age-related Changes in Antidepressant Pharmacokinetics and Potential Drug-Drug Interactions: A Comparison of Evidence-Based Literature and Package Insert Information. Am J Geriatr Pharmcother. DOI:10.1016/j.amjopharm.2012.01.001. PMID: 22285509.
Antidepressants are among the most commonly prescribed psychotropic agents for older patients. Little is known about the best source of pharmacotherapy information to consult about key factors necessary to safely prescribe these medications to older patients.
The objective of this study was to synthesize and contrast information in the package insert (PI) with information found in the scientific literature about age-related changes of antidepressants in systemic clearance and potential pharmacokinetic drug-drug interactions (DDIs).
A comprehensive search of two databases (MEDLINE and EMBASE from January 1, 1975 to September 30, 2011) with the use of a combination of search terms (antidepressants, pharmacokinetics, and drug interactions) was conducted to identify relevant English language articles. This information was independently reviewed by two researchers and synthesized into tables. These same two researchers examined the most up-to-date PIs for the 26 agents available at the time of the study to abstract quantitative information about age-related decline in systemic clearance and potential DDIs. The agreement between the two information sources was tested with κ statistics.
The literature reported age-related clearance changes for 13 antidepressants, whereas the PIs only had evidence about 4 antidepressants (κ < 0.4). Similarly, the literature identified 45 medications that could potentially interact with a specific antidepressant, whereas the PIs only provided evidence about 12 potential medication-antidepressant DDIs (κ < 0.4).
The evidence-based literature compared with PIs is the most complete pharmacotherapy information source about both age-related clearance changes and pharmacokinetic DDIs with antidepressants. Future rigorously designed observational studies are needed to examine the combined risk of antidepressants with age-related decline in clearance and potential DDIs on important health outcomes such as falls and fractures in older patients.
Boyce RD, Hanlon JT, Karp JF, Kloke J, Saleh A, Handler SM. A Review of the Effectiveness of Antidepressant Medications for Depressed Nursing Home Residents, Journal of the American Medical Directors Association, 2011 Oct 20. DOI:10.1016/j.jamda.2011.08.009. PMID:22019084.
Antidepressant medications are the most common psychopharmacologic therapy used to treat depressed nursing home (NH) residents. Despite a significant increase in the rate of antidepressant prescribing over the past several decades, little is known about the effectiveness of these agents in the NH population.
To conduct a systematic review of the literature to examine and compare the effectiveness of antidepressant medications for treating major depressive symptoms in elderly NH residents.
The following databases were searched with searches completed prior to January 2011 and no language restriction: MEDLINE, Embase, PsycINFO, CINHAL, CENTRAL, LILACS, ClinicalTrials.gov, International Standard Randomized Controlled Trial Number Register, and the WHO International Clinical Trial Registry Platform. Additional studies were identified from citations in evidence-based guidelines and reviews as well as book chapters on geriatric depression and pharmacotherapy from several clinical references. Studies were included if they described a clinical trial that assessed the effectiveness of any currently-marketed antidepressant for adults aged 65 years or older, who resided in the NH, and were diagnosed by DSM criteria and/or standardized validated screening instruments with Major Depressive Disorder, minor depression, dysthymic disorder, or Depression in Alzheimer's disease.
A total of eleven studies, including four randomized and seven non-randomized open-label trials, met all inclusion and exclusion criteria. It was not feasible to conduct a meta-analysis because the studies were heterogeneous in terms of study design, operational definitions of depression, participant characteristics, pharmacologic interventions, and outcome measures. Of the four randomized trials, two had a control group and did not demonstrate a statistically-significant benefit for antidepressant pharmacotherapy over placebo. While six of the seven non-randomized studies identified a response to an antidepressant, their results must be interpreted with caution as they lacked a comparison group.
The limited amount of evidence from randomized and non-randomized open-label trials suggests that depressed NH residents have a modest response to antidepressant medications. Further research using rigorous study designs are needed to examine the effectiveness and safety of antidepressants in depressed NH residents, and to determine the various facility, provider, and patient factors associated with response to treatment.
Jiang X, R.E. Neapolitan, M.M. Barmada, S.Visweswaran. Learning genetic epistasis using Bayesian network scoring criteria. BMC Bioinformatics; 2011: 12(89). PMID: 21453508
BACKGROUND: Gene-gene epistatic interactions likely play an important role in the genetic basis of many common diseases. Recently, machine-learning and data mining methods have been developed for learning epistatic relationships from data. A well-known combinatorial method that has been successfully applied for detecting epistasis is Multifactor Dimensionality Reduction (MDR). Jiang et al. created a combinatorial epistasis learning method called BNMBL to learn Bayesian network (BN) epistatic models. They compared BNMBL to MDR using simulated data sets. Each of these data sets was generated from a model that associates two SNPs with a disease and includes 18 unrelated SNPs. For each data set, BNMBL and MDR were used to score all 2-SNP models, and BNMBL learned significantly more correct models. In real data sets, we ordinarily do not know the number of SNPs that influence phenotype. BNMBL may not perform as well if we also scored models containing more than two SNPs. Furthermore, a number of other BN scoring criteria have been developed. They may detect epistatic interactions even better than BNMBL.Although BNs are a promising tool for learning epistatic relationships from data, we cannot confidently use them in this domain until we determine which scoring criteria work best or even well when we try learning the correct model without knowledge of the number of SNPs in that model. RESULTS: We evaluated the performance of 22 BN scoring criteria using 28,000 simulated data sets and a real Alzheimer's GWAS data set. Our results were surprising in that the Bayesian scoring criterion with large values of a hyperparameter called α performed best. This score performed better than other BN scoring criteria and MDR at recall using simulated data sets, at detecting the hardest-to-detect models using simulated data sets, and at substantiating previous results using the real Alzheimer's data set. CONCLUSIONS: We conclude that representing epistatic interactions using BN models and scoring them using a BN scoring criterion holds promise for identifying epistatic genetic variants in data. In particular, the Bayesian scoring criterion with large values of a hyperparameter α appears more promising than a number of alternatives.
Jiang X, Visweswaran S, Neapolitan RE. Mining Epistatic Interactions from High-Dimensional Data Sets Using Bayesian Networks, in Holmes, D. and L. Jain (Eds.): Foundations and Intelligent Paradigms--3, Springer-Verlag, Berlin Heidelberg, 2011, DOI:10.1007/978-3-642-23151-3_9.
Jiang X, Neill DB, Cooper GF. On the robustness of Bayesian network based spatial event surveillance. International Journal of Approximate Reasoning, 51 (2010) p 224-239. http://dx.doi.org/10.1016/j.ijar.2009.01.001.
Methods for spatial cluster detection attempt to locate spatial subregions of some larger region where the count of some occurrences is higher than expected. Event surveillance consists of monitoring a region in order to detect emerging patterns that are indicative of some event of interest. In spatial event surveillance, we search for emerging patterns in spatial subregions. A well-known method for spatial cluster detection is Kulldorff’s [M. Kulldorff, A spatial scan statistic, Communications in Statistics: Theory and Methods 26 (6) (1997)] spatial scan statistic, which directly analyzes the counts of occurrences in the subregions. Neill et al. [D.B. Neill, A.W. Moore, G.F. Cooper, A Bayesian spatial scan statistic, Advances in Neural Information Processing Systems (NIPS) 18 (2005)] developed a Bayesian spatial scan statistic called BSS, which also directly analyzes the counts. We developed a new Bayesian-network-based spatial scan statistic, called BNetScan, which models the relationships among the events of interest and the observable events using a Bayesian network. BNetScan is an entity-based Bayesian network that models the underlying state and observable variables for each individual in a population. We compared the performance of BNetScan to Kulldorff’s spatial scan statistic and BSS using simulated outbreaks of influenza and cryptosporidiosis injected into real Emergency Department data from Allegheny County, Pennsylvania. It is an open question whether we can obtain acceptable results using a Bayesian network if the probability distributions in the network do not closely reflect reality, and thus, we examined the robustness of BNetScan relative to the probability distributions used to generate the data in the experiments. Our results indicate that BNetScan outperforms the other methods and its performance is robust relative to the probability distribution that is used to generate the data.
Staheli JP, Boyce R, Kovarik D, Rose TM. CODEHOP PCR and CODEHOP PCR primer design. Methods Mol Biol. 2011;687:57-73. PMID: 20967601.
While PCR primer design for the amplification of known sequences is usually quite straightforward, the design, and successful application of primers aimed at the detection of as yet unknown genes is often not. The search for genes that are presumed to be distantly related to a known gene sequence, such as homologous genes in different species, paralogs in the same genome, or novel pathogens in diverse hosts, often turns into the proverbial search for the needle in the haystack. PCR-based methods commonly used to address this issue involve the use of either consensus primers or degenerate primers, both of which have significant shortcomings regarding sensitivity and specificity. We have developed a novel primer design approach that diminishes these shortcomings and instead takes advantage of the strengths of both consensus and degenerate primer designs, by combining the two concepts into a Consensus-Degenerate Hybrid Oligonucleotide Primer (CODEHOP) approach. CODEHOP PCR primers contain a relatively short degenerate 3' core and a 5' nondegenerate clamp. The 3' degenerate core consists of a pool of primers containing all possible codons for a 3-4 aminoacid motif that is highly conserved in multiply aligned sequences from known members of a protein family. Each primer in the pool also contains a single 5' nondegenerate nucleotide sequence derived from a codon consensus across the aligned aminoacid sequences flanking the conserved motif. During the initial PCR amplification cycles, the degenerate core is responsible for specific binding to sequences encoding the conserved aminoacid motif. The longer consensus clamp region serves to stabilize the primer and allows the participation of all primers in the pool in the efficient amplification of products during later PCR cycles. We have developed an interactive web site and algorithm (iCODEHOP) for designing CODEHOP PCR primers from multiply aligned protein sequences, which is freely available online. Here, we describe the workflow of a typical CODEHOP PCR assay design and optimization and give a specific implementation example along with "best-practice" advice.
Peron EP, Marcum ZA, Boyce R, Hanlon JT, Handler SM. Year in Review: Medication Mishaps in the Elderly. Am J Geriatr Pharmacother. 2011 Feb; 9(1):1-10. PMID 21459304.
Landis Lewis Z, Mello-Thoms C, Gadabu OJ, Gillespie EM, Douglas GP, Crowley RS. The Feasibility of Automating Audit and Feedback for ART Guideline Adherence in Malawi. Accepted to J Am Med Inform Assoc, (JAMIA) April 19, 2011.
ABSTRACT Objective: To determine the feasibility of using electronic medical record (EMR) data to provide audit and feedback of anti-retroviral therapy (ART) clinical guideline adherence to healthcare workers (HCWs) in Malawi. Materials and methods: We evaluated recommendations from Malawi’s ART guidelines using GuideLine Implementability Appraisal criteria. Recommendations that passed selected criteria were converted into ratio-based performance measures. We queried representative EMR data to determine the feasibility of generating feedback for each performance measure, summed clinical encounters representing each performance measure’s denominator, and then measured the distribution of encounter frequency for individual HCWs across nurse and clinical officer groups. Results: We analyzed 423 831 encounters in the EMR data and generated automated feedback for 21 recommendations (12%) from Malawi’s ART guidelines. We identified 11 nurse recommendations and eight clinical officer recommendations. Individual nurses and clinical officers had an average of 45 and 59 encounters per month, per recommendation, respectively. Another 37 recommendations (21%) would support audit and feedback if additional routine EMR data are captured and temporal constraints are modeled. Discussion: It appears feasible to implement automated guideline adherence feedback that could potentially improve HCW performance and supervision. Feedback reports may support workplace learning by increasing HCWs’ opportunities to reflect on their performance. Conclusion: A moderate number of recommendations from Malawi’s ART guidelines can be used to generate automated guideline adherence feedback using existing EMR data. Further study is needed to determine the receptivity of HCWs to peer comparison feedback and barriers to implementation of automated audit and feedback in low-resource settings.