Hierarchical network meta-analysis models to address sparsity of events and differing treatment classifications with regard to adverse outcomes

This is the accepted version of the article, which has been published in final form at DOI: 10.1002/sim.6131.Meta-analysis for adverse events resulting from medical interventions has many challenges, in part due to small numbers of such events within primary studies. Furthermore, variability in drug dose, potential differences between drugs within the same pharmaceutical class and multiple indications for a specific treatment can all add to the complexity of the evidence base. This paper explores the use of synthesis methods, incorporating mixed treatment comparisons, to estimate the risk of adverse events for a medical intervention, while acknowledging and modelling the complexity of the structure of the evidence base. The motivating example was the effect on malignancy of three anti-tumour necrosis factor (anti-TNF) drugs (etanercept, adalimumab and infliximab) indicated to treat rheumatoid arthritis. Using data derived from 13 primary studies, a series of meta-analysis models of increasing complexity were applied. Models ranged from a straightforward comparison of anti-TNF against non-anti-TNF controls, to more complex models in which a treatment was defined by individual drug and its dose. Hierarchical models to allow 'borrowing strength' across treatment classes and dose levels, and models involving constraints on the impact of dose level, are described. These models provide a flexible approach to estimating sparse, often adverse, outcomes associated with interventions. Each model makes its own set of assumptions, and approaches to assessing goodness of fit of the various models will usually be extremely limited in their effectiveness, due to the sparse nature of the data. Both methodological and clinical considerations are required to fit realistically complex models in this area and to evaluate their appropriateness.Partially supported by a National Institute for Health Research Senior Investigator Awar

Systematic review and meta-analysis. small intestinal bacterial overgrowth in chronic pancreatitis

BACKGROUND: Evidence on small intestinal bacterial overgrowth (SIBO) in patients with chronic pancreatitis (CP) is conflicting. AIM: The purpose of this study was to perform a systematic review and meta-analysis on the prevalence of SIBO in CP and to examine the relationship of SIBO with symptoms and nutritional status. METHODS: Case-control and cross-sectional studies investigating SIBO in CP patients were analysed. The prevalence of positive tests was pooled across studies, and the rate of positivity between CP cases and controls was calculated. RESULTS: In nine studies containing 336 CP patients, the pooled prevalence of SIBO was 36% (95% confidence interval (CI) 17-60%) with considerable heterogeneity (I2 = 91%). A sensitivity analysis excluding studies employing lactulose breath test gave a pooled prevalence of 21.7% (95% CI 12.7-34.5%) with lower heterogeneity (I2 = 56%). The odds ratio for a positive test in CP vs controls was 4.1 (95% CI 1.6-10.4) (I2 = 59.7%). The relationship between symptoms and SIBO in CP patients varied across studies, and the treatment of SIBO was associated with clinical improvement. CONCLUSIONS: One-third of CP patients have SIBO, with a significantly increased risk over controls, although results are heterogeneous, and studies carry several limitations. The impact of SIBO and its treatment in CP patients deserve further investigation

Estimating the cost-effectiveness of detecting cases of chronic hepatitis C infection on reception into prison

Background In England and Wales where less than 1% of the population are Injecting drug users (IDUs), 97% of HCV reports are attributed to injecting drug use. As over 60% of the IDU population will have been imprisoned by the age of 30 years, prison may provide a good location in which to offer HCV screening and treatment. The aim of this work is to examine the cost effectiveness of a number of alternative HCV case-finding strategies on prison reception Methods A decision analysis model embedded in a model of the flow of IDUs through prison was used to estimate the cost effectiveness of a number of alternative case-finding strategies. The model estimates the average cost of identifying a new case of HCV from the perspective of the health care provider and how these estimates may evolve over time. Results The results suggest that administering verbal screening for a past positive HCV test and for ever having engaged in illicit drug use prior to the administering of ELISA and PCR tests can have a significant impact on the cost effectiveness of HCV case-finding strategies on prison reception; the discounted cost in 2017 being £2,102 per new HCV case detected compared to £3,107 when no verbal screening is employed. Conclusion The work here demonstrates the importance of targeting those individuals that have ever engaged in illicit drug use for HCV testing in prisons, these individuals can then be targeted for future intervention measures such as treatment or monitored to prevent future transmission

Factors influencing the impact of pharmacogenomic prescribing on adherence to nicotine replacement therapy: A qualitative study of participants from a randomized controlled trial

Pharmacogenomics may improve health outcomes in two ways: by more precise and therefore more effective prescribing, tailored to genotype, and by increasing perceived effectiveness of treatments and so motivation for adherence. Little is known about patients’ experiences of, and reactions to, receiving pharmacogenomically tailored treatments. The aim of this study was to explore the impact of pharmacogenomic prescribing of nicotine replacement therapy (NRT) on smokers’ initial expectations of quit success, adherence, and perceived important differences from previous quit attempts. Semi-structured interviews were conducted with 40 smokers, purposively sampled from the Personalized Extra Treatment (PET) trial (ISRCTN 14352545). Together with NRT patches, participants were prescribed doses of oral NRT based on either mu-opioid receptor (OPRM1) genotype or nicotine dependence questionnaire score (phenotype). Data were analyzed using framework analysis, comparing views of participants in the two trial arms. Although most participants understood the basis for their prescribed NRT dose, it little influenced their views. The salient features of this quit attempt were the individualized behavioral support and combined NRT, not pharmacogenomic tailoring. Participants’ initial expectations of success were mostly based on prior experiences of quitting. They attributed taking medication to nurse advice to do so, and attributed reducing or stopping it to side effects, forgetfulness, or practical difficulties. Intentional nonadherence appeared very rare. Pharmacogenomic NRT prescribing was not especially remarkable to participants and did not seem to influence adherence. Where services already tailor prescriptions to phenotype and provide individualized behavioral support for treatment adherence, pharmacogenomic prescribing may have limited additional benefit

Do Economic Evaluations in Primary Care Prevention and the Management of Hypertension Conform to Good Practice Guidelines? A Systematic Review

Background: Results of previous research have identified the need for further investigation into the compliance with good practice guidelines for current decision-analytic modeling (DAM). Objective: To identify the extent to which recent model-based economic evaluations of interventions focused on lowering the blood pressure (BP) of patients with hypertension conform to published guidelines for DAM in health care using a five-dimension framework developed to assess compliance to DAM guidelines. Methods: A systematic review of English language articles was undertaken to identify published model-based economic evaluations that examined interventions aimed at lowering BP. The review covered the period January 2000 to March 2015 and included the following electronic bibliographic databases: EMBASE and Medline via Ovid interface and the Centre for Reviews and Dissemination’s (CRD) NHS-EED. Data were extracted based on different components of good practice across five dimensions utilizing a framework to assess compliance to DAM guidelines. Results: Thirteen articles were included in this review. The review found limited compliance to good practice DAM guidelines, which was most frequently justified by the lack of data. Conclusions: The assessment of structural uncertainty cannot yet be considered common practice in primary prevention and management of hypertension, and researchers seem to face difficulties with identifying sources of structural uncertainty and then handling them correctly. Additional guidelines are needed to aid researchers in identifying and managing sources of potential structural uncertainty. Adherence to guidelines is not always possible and it does pose challenges, in particular when there are limitations due to data availability that restrict, for example, a validation process

Designing a Predictive Coding System for Electronic Discovery

Not long ago, the concept of using predictive coding and other technologies to assist with the electronic discovery process seemed revolutionary. Da Silva Moore and Global Aerospace stand as the first major cases where judges strongly supported predictive coding.1-2 A recent Indiana case recognized it as a useful method for reducing the amount of potentially relevant evidence that has to be searched and culled.3 Within just a few short years, using predictive coding as part of an electronic discovery process is now considered acceptable and perhaps even expected. It is not difficult to appreciate the advantages of predictive coding and its superiority over a manual process at various steps of electronic discovery, particularly during the review step.4-11 However, questions still remain about the efficacy of the predictive coding process and the tools that are available.12-13 Because the use of predictive coding systems in law is still in its infancy, it presents us with an opportunity to design something that will not only take advantage of the power of big data and computational algorithms, but that will also incorporate design and usability principles to provide an attractive and easy-to-use interface for lawyers to interact with. Predictive coding uses natural language processing and other mathematical models to enhance search results, but the essence of these systems is that they actually learn and the precision of the retrieval improves as additional collections of evidence are entered. Behind-the-scenes will be a repository where all of the evidence for a case resides. Our system will assist the lawyers in reducing the time and cost of an electronic discovery process as well as minimize the chances for mistakes in determining which evidence is relevant to a case and which evidence can be withheld under attorney-client privilege, as attorney work-product or another confidentiality doctrine. 1. Da Silva Moore v. Publicis Groupe & MSL Group, No. 11 Civ. 1279, 2012 WL 607412 (ALC) (AJP) (S.D.N.Y. Feb. 24, 2012). 2. Global Aerospace, Inc. v. Landow Aviation, L.P., No. CL 61040 (Vir. Cir. Ct. Apr. 23, 2012). 3. In re Biomet, 2013 WL 1729682 (N.D. Ind. Apr. 18, 2013). 4. Alison Silverstein and Geoffrey Vance. E-Discovery Myth Busters: Why Predictive Coding is Safe, Successful and Smart. Peer to Peer, Vol. 29, No. 4, December 2013, pp. 66-69. 5. John Papageorge. Predictive Coding Gaining Support in Courts. Indiana Lawyer, January 29-February 11, 2014, p. 8. 6. Adam M. Acosta. Predictive Coding: The Beginning of a New E-Discovery Era. Res Gestae, October 2012, pp. 8-14. 7. Ajith (AJ) Samuel. Analytics Driving the E-Discovery Process. Peer to Peer, Vol. 28, No. 2, June 2012. 8. Richard Acello. Beyond Prediction: Technology-Assisted Review Enters the Lexicon. ABA Journal, August 2012, pp. 37, 70. 9. Barry Murphy. The Rise of Technology-Assisted Review (TAR). Peer to Peer, Vol. 28, No. 2, June 2012, pp. 10. Brian Ingram. Controlling E-Discovery Costs in a Big Data World. Peer to Peer, Vol. 29, No. 1, March 2013. 11. Hal Marcus and Susan Stone. Beyond Predictive Coding - The True Power of Data Analytics [webinar]. International Legal Technology Association, May 19, 2015. 12. Jessica Watts and Gareth Evans. Predictive Coding in the Real World [webinar]. International Legal Technology Association, August 5, 2015. 13. Danielle Bethea. Predictive Coding: Revolutionizing Review or Still Gaining Momentum? Litigation and Practice Support: ITLA White Paper, International Legal Technology Association, June 2014

Exploring the roles of urinary HAI-1, EpCAM and EGFR in bladder cancer prognosis and risk stratification

Objectives: To investigate whether elevated urinary HAI-1, EpCAM and EGFR are independent prognostic biomarkers within non-muscle-invasive bladder cancer (NMIBC) patients, and have utility for risk stratification to facilitate treatment decisions. Results: After accounting for EAU risk group in NMIBC patients, the risk of BC-specific death was 2.14 times higher (95% CI: 1.08 to 4.24) if HAI-1 was elevated and 2.04 times higher (95% CI: 1.02 to 4.07) if EpCAM was elevated. The majority of events occurred in the high-risk NMIBC group and this is where the biggest difference is seen in the survival curves when plotted for EAU risk groups separately. In MIBC patients, being elevated for any of the three biomarkers was significantly associated with BC-specific mortality after accounting for other risk factors, HR = 4.30 (95% CI: 1.85 to 10.03). Patients and Methods: Urinary levels of HAI-1, EpCAM and EGFR were measured by ELISA in 683 and 175 patients with newly-diagnosed NMIBC and MIBC, respectively, recruited to the Bladder Cancer Prognosis Programme. Associations between biomarkers and progression, BC-specific mortality and all-cause mortality were evaluated using univariable and multivariable Cox regression models, adjusted for European Association of Urology (EAU) NMIBC risk groups. The upper 25% of values for each biomarker within NMIBC patients were considered as elevated. Exploratory analyses in urine from MIBC patients were also undertaken. Conclusion: Urinary HAI-1 and EpCAM are prognostic biomarkers for NMIBC patients. These biomarkers have potential to guide treatment decisions for high-risk NMIBC patients. Further analyses are required to define the roles of HAI-1, EpCAM and EGFR in MIBC patients

Allosteric mechanism of action of the therapeutic anti-IgE antibody omalizumab

Immunoglobulin E and its interactions with receptors FcϵRI and CD23 play a central role in allergic disease. Omalizumab, a clinically approved therapeutic antibody, inhibits the interaction between IgE and FcϵRI, preventing mast cell and basophil activation, and blocks IgE binding to CD23 on B cells and antigen-presenting cells. We solved the crystal structure of the complex between an omalizumab-derived Fab and IgE-Fc, with one Fab bound to each Cϵ3 domain. Free IgE-Fc adopts an acutely bent structure, but in the complex it is only partially bent, with large-scale conformational changes in the Cϵ3 domains that inhibit the interaction with FcϵRI. CD23 binding is inhibited sterically due to overlapping binding sites on each Cϵ3 domain. Studies of omalizumab Fab binding in solution demonstrate the allosteric basis for FcϵRI inhibition and, together with the structure, reveal how omalizumab may accelerate dissociation of receptor-bound IgE from FcϵRI, exploiting the intrinsic flexibility and allosteric potential of IgE

Should we screen for the sexually-transmitted infection Mycoplasma genitalium? Evidence synthesis using a transmission-dynamic model

There is increasing concern about Mycoplasma genitalium as a cause of urethritis, cervicitis, pelvic inflammatory disease (PID), infertility and ectopic pregnancy. Commercial nucleic acid amplification tests (NAATs) are becoming available, and their use in screening for M. genitalium has been advocated, but M. genitalium's natural history is poorly-understood, making screening's effectiveness unclear. We used a transmission-dynamic compartmental model to synthesise evidence from surveillance data and epidemiological and behavioural studies to better understand M. genitalium's natural history, and then examined the effects of implementing NAAT testing. Introducing NAAT testing initially increases diagnoses, by finding a larger proportion of infections; subsequently the diagnosis rate falls, due to reduced incidence. Testing only symptomatic patients finds relatively little infection in women, as a large proportion is asymptomatic. Testing both symptomatic and asymptomatic patients has a much larger impact and reduces cumulative PID incidence in women due to M. genitalium by 31.1% (95% range:13.0%-52.0%) over 20 years. However, there is important uncertainty in M. genitalium's natural history parameters, leading to uncertainty in the absolute reduction in PID and sequelae. Empirical work is required to improve understanding of key aspects of M. genitalium's natural history before it will be possible to determine the effectiveness of screening