Analysis of exhaled breath to identify critically ill patients with ventilator-associated pneumonia.

Ventilator-associated pneumonia commonly occurs in critically ill patients. Clinical suspicion results in overuse of antibiotics, which in turn promotes antimicrobial resistance. Detection of volatile organic compounds in the exhaled breath of critically ill patients might allow earlier detection of pneumonia and avoid unnecessary antibiotic prescription. We report a proof of concept study for non-invasive diagnosis of ventilator-associated pneumonia in intensive care (the BRAVo study). Mechanically ventilated critically ill patients commenced on antibiotics for clinical suspicion of ventilator-associated pneumonia were recruited within the first 24 h of treatment. Paired exhaled breath and respiratory tract samples were collected. Exhaled breath was captured on sorbent tubes and then analysed using thermal desorption gas chromatography-mass spectrometry to detect volatile organic compounds. Microbiological culture of a pathogenic bacteria in respiratory tract samples provided confirmation of ventilator-associated pneumonia. Univariable and multivariable analyses of volatile organic compounds were performed to identify potential biomarkers for a 'rule-out' test. Ninety-six participants were enrolled in the trial, with exhaled breath available from 92. Of all compounds tested, the four highest performing candidate biomarkers were benzene, cyclohexanone, pentanol and undecanal with area under the receiver operating characteristic curve ranging from 0.67 to 0.77 and negative predictive values from 85% to 88%. Identified volatile organic compounds in the exhaled breath of mechanically ventilated critically ill patients show promise as a useful non-invasive 'rule-out' test for ventilator-associated pneumonia.

Position statement: The need for EU legislation to require disclosure and labelling of the composition of medical devices.

BACKGROUND: In recent years, skin reactions secondary to the use of medical devices (MD), such as allergic contact dermatitis have increasingly been observed (e.g. to continuous blood sugar monitoring systems, insulin pumps, wound dressings, medical gloves, etc.): this is regarded as a developing epidemic. Lack of labelling of the composition of MD, as well as frequent lack of cooperation of manufacturers to disclose this relevant information, even when contacted by the clinician for the individual case of an established adverse reaction, significantly impede patient care. OBJECTIVES: To advocate for full ingredient labelling in the implementation of EU regulation for MD. METHODS: This position paper reviews the scientific literature, the current regulatory framework adopted for MD to date, and the likely impact, including some costs data in case of the absence of such labelling. RESULTS: Efforts made by several scientific teams, who are trying to identify the culprit of such adverse effects, either via asking for cooperation from companies, or using costly chemical analyses of MD, can only partly, and with considerable delay, compensate for the absence of meaningful information on the composition of MD; hence, patient management is compromised. Indeed, without knowing the chemical substances present, physicians are unable to inform patients about which substances they should avoid, and which alternative MD may be suitable/tolerated. CONCLUSION: There is an urgent need for full and accurate labelling of the chemical composition of MD in contact with the human body.

Improved two-stage estimation to adjust for treatment switching in randomised trials: g-estimation to address time-dependent confounding.

In oncology trials, control group patients often switch onto the experimental treatment during follow-up, usually after disease progression. In this case, an intention-to-treat analysis will not address the policy question of interest - that of whether the new treatment represents an effective and cost-effective use of health care resources, compared to the standard treatment. Rank preserving structural failure time models (RPSFTM), inverse probability of censoring weights (IPCW) and two-stage estimation (TSE) have often been used to adjust for switching to inform treatment reimbursement policy decisions. TSE has been applied using a simple approach (TSEsimp), assuming no time-dependent confounding between the time of disease progression and the time of switch. This is problematic if there is a delay between progression and switch. In this paper we introduce TSEgest, which uses structural nested models and g-estimation to account for time-dependent confounding, and compare it to TSEsimp, RPSFTM and IPCW. We simulated scenarios where control group patients could switch onto the experimental treatment with and without time-dependent confounding being present. We varied switching proportions, treatment effects and censoring proportions. We assessed adjustment methods according to their estimation of control group restricted mean survival times that would have been observed in the absence of switching. All methods performed well in scenarios with no time-dependent confounding. TSEgest and RPSFTM continued to perform well in scenarios with time-dependent confounding, but TSEsimp resulted in substantial bias. IPCW also performed well in scenarios with time-dependent confounding, except when inverse probability weights were high in relation to the size of the group being subjected to weighting, which occurred when there was a combination of modest sample size and high switching proportions. TSEgest represents a useful addition to the collection of methods that may be used to adjust for treatment switching in trials in order to address policy-relevant questions.

The epidemic of methylisothiazolinone contact allergy in Europe: follow-up on changing exposures.

BACKGROUND: Methylisothiazolinone (MI) has caused an unprecedented epidemic of contact allergy in Europe and elsewhere. Subsequently, regulatory action has been taken, at least in Europe, aiming at reducing risk of MI sensitization. OBJECTIVE: To follow-up on the prevalence of contact allergy to MI in consecutively patch tested patients and assess the spectrum of products containing MI or methylchloroisothiazolinone (MCI)/MI in patients positive to MI which elicited current allergic contact dermatitis. METHODS: A cross-sectional survey was performed in 2016 and 2017, including all adult patients patch tested with the baseline series (including MI 0.2% aq.) between 1 May and 31 October at 14 centres in 11 European countries. Patients with positive reactions (+ to +++) to MI were further examined regarding history, clinical characteristics and eliciting products, which were categorized into 34 types and 4 classes (leave-on, rinse-off, household, occupational). The results were compared with the reference year 2015. RESULTS: A total of 317 patients, n = 202 of 4278 tested in 2016 (4.72%) and n = 115 of 3879 tested in 2017 (2.96%), had positive reactions to MI; the previous result from 2015 was 5.97% (P < 0.0001). The share of currently relevant contact allergy among all positive reactions declined significantly as well (P = 0.0032). Concerning product classes, a relative decline of leave-on and a relative increase of rinse-off and household products was noted. CONCLUSION: The prevalence of MI contact allergy decreased by 50% from 2015 to 2017. As a consequence of regulation, the share of cosmetics products (leave-on in particular) eliciting allergic contact dermatitis is decreasing. The chosen method of analysing causative products in sensitized patients has proven useful to monitor effects of intervention.

The cost-effectiveness of universal late-pregnancy screening for macrosomia in nulliparous women: a decision analysis.

OBJECTIVE: To identify the most cost-effective policy for detection and management of fetal macrosomia in late-stage pregnancy. DESIGN: Health economic simulation model. SETTING: All English NHS antenatal services. POPULATION: Nulliparous women in the third trimester treated within the UK NHS. METHODS: A health economic simulation model was used to compare long-term maternal-fetal health and cost outcomes for two detection strategies (universal ultrasound scanning at approximately 36 weeks of gestation versus selective ultrasound scanning), combined with three management strategies (planned caesarean section versus induction of labour versus expectant management) of suspected fetal macrosomia. Probabilities, costs and health outcomes were taken from literature. MAIN OUTCOME MEASURES: Expected costs to the NHS and quality-adjusted life-years (QALYs) gained from each strategy, calculation of net benefit and hence identification of most cost-effective strategy. RESULTS: Compared with selective ultrasound, universal ultrasound increased QALYs by 0.0038 (95% CI 0.0012-0.0076), but also costs by £123.50 (95% CI 99.6-149.9). Overall, the health gains were too small to justify the cost increase given current UK thresholds cost-effective policy was selective ultrasound coupled with induction of labour where macrosomia was suspected. CONCLUSIONS: The most cost-effective policy for detection and management of fetal macrosomia is selective ultrasound scanning coupled with induction of labour for all suspected cases of macrosomia. Universal ultrasound scanning for macrosomia in late-stage pregnancy is not cost-effective. TWEETABLE ABSTRACT: Universal late-pregnancy ultrasound screening for fetal macrosomia is not warranted.

Causal inference for long-term survival in randomised trials with treatment switching: Should re-censoring be applied when estimating counterfactual survival times?

Treatment switching often has a crucial impact on estimates of effectiveness and cost-effectiveness of new oncology treatments. Rank preserving structural failure time models (RPSFTM) and two-stage estimation (TSE) methods estimate 'counterfactual' (i.e. had there been no switching) survival times and incorporate re-censoring to guard against informative censoring in the counterfactual dataset. However, re-censoring causes a loss of longer term survival information which is problematic when estimates of long-term survival effects are required, as is often the case for health technology assessment decision making. We present a simulation study designed to investigate applications of the RPSFTM and TSE with and without re-censoring, to determine whether re-censoring should always be recommended within adjustment analyses. We investigate a context where switching is from the control group onto the experimental treatment in scenarios with varying switch proportions, treatment effect sizes, treatment effect changes over time, survival function shapes, disease severity and switcher prognosis. Methods were assessed according to their estimation of control group restricted mean survival that would be observed in the absence of switching, up to the end of trial follow-up. We found that analyses which re-censored usually produced negative bias (i.e. underestimating control group restricted mean survival and overestimating the treatment effect), whereas analyses that did not re-censor consistently produced positive bias which was often smaller in magnitude than the bias associated with re-censored analyses, particularly when the treatment effect was high and the switching proportion was low. The RPSFTM with re-censoring generally resulted in increased bias compared to the other methods. We believe that analyses should be conducted with and without re-censoring, as this may provide decision-makers with useful information on where the true treatment effect is likely to lie. Incorporating re-censoring should not always represent the default approach when the objective is to estimate long-term survival times and treatment effects.

Computationally efficient methods for fitting mixed models to electronic health records data.

Motivated by two case studies using primary care records from the Clinical Practice Research Datalink, we describe statistical methods that facilitate the analysis of tall data, with very large numbers of observations. Our focus is on investigating the association between patient characteristics and an outcome of interest, while allowing for variation among general practices. We explore ways to fit mixed-effects models to tall data, including predictors of interest and confounding factors as covariates, and including random intercepts to allow for heterogeneity in outcome among practices. We introduce (1) weighted regression and (2) meta-analysis of estimated regression coefficients from each practice. Both methods reduce the size of the dataset, thus decreasing the time required for statistical analysis. We compare the methods to an existing subsampling approach. All methods give similar point estimates, and weighted regression and meta-analysis give similar standard errors for point estimates to analysis of the entire dataset, but the subsampling method gives larger standard errors. Where all data are discrete, weighted regression is equivalent to fitting the mixed model to the entire dataset. In the presence of a continuous covariate, meta-analysis is useful. Both methods are easy to implement in standard statistical software.

What is the optimal systemic treatment of men with metastatic, hormone-naive prostate cancer? A STOPCAP systematic review and network meta-analysis.

Background: Our prior Systemic Treatment Options for Cancer of the Prostate systematic reviews showed improved survival for men with metastatic hormone-naive prostate cancer when abiraterone acetate plus prednisolone/prednisone (AAP) or docetaxel (Doc), but not zoledronic acid (ZA), were added to androgen-deprivation therapy (ADT). Trial evidence also suggests a benefit of combining celecoxib (Cel) with ZA and ADT. To establish the optimal treatments, a network meta-analysis (NMA) was carried out based on aggregate data (AD) from all available studies. Methods: Overall survival (OS) and failure-free survival data from completed Systemic Treatment Options for Cancer of the Prostate reviews of Doc, ZA and AAP and from recent trials of ZA and Cel contributed to this comprehensive AD-NMA. The primary outcome was OS. Correlations between treatment comparisons within one multi-arm, multi-stage trial were estimated from control-arm event counts. Network consistency and a common heterogeneity variance were assumed. Results: We identified 10 completed trials which had closed to recruitment, and one trial in which recruitment was ongoing, as eligible for inclusion. Results are based on six trials including 6204 men (97% of men randomised in all completed trials). Network estimates of effects on OS were consistent with reported comparisons with ADT alone for AAP [hazard ration (HR) = 0.61, 95% confidence interval (CI) 0.53-0.71], Doc (HR = 0.77, 95% CI 0.68-0.87), ZA + Cel (HR = 0.78, 95% CI 0.62-0.97), ZA + Doc (HR = 0.79, 95% CI 0.66-0.94), Cel (HR = 0.94 95% CI 0.75-1.17) and ZA (HR = 0.90 95% CI 0.79-1.03). The effect of ZA + Cel is consistent with the additive effects of the individual treatments. Results suggest that AAP has the highest probability of being the most effective treatment both for OS (94% probability) and failure-free survival (100% probability). Doc was the second-best treatment of OS (35% probability). Conclusions: Uniquely, we have included all available results and appropriately accounted for inclusion of multi-arm, multi-stage trials in this AD-NMA. Our results support the use of AAP or Doc with ADT in men with metastatic hormone-naive prostate cancer. AAP appears to be the most effective treatment, but it is not clear to what extent and whether this is due to a true increased benefit with AAP or the variable features of the individual trials. To fully account for patient variability across trials, changes in prognosis or treatment effects over time and the potential impact of treatment on progression, a network meta-analysis based on individual participant data is in development.

Patch testing with the European baseline series fragrance markers: a 2016 update.

BACKGROUND: Fragrance contact allergy is common and is currently screened for using the following European baseline series fragrance markers: fragrance mix (FM)I, FMII, Myroxylon pereirae and hydroxyisohexyl 3-cyclohexene carboxaldehyde. OBJECTIVES: To investigate the validity of patch testing using these fragrance markers in detecting fragrance allergy to 26 individual fragrance substances for which cosmetic ingredient labelling is mandatory within the European Union. METHODS: We conducted a retrospective review of the patch test records of all patients with eczema who underwent testing using the European baseline series, extended with the individual fragrance substances during the period from 2015 to 2016. RESULTS: Overall, 359 patients (17·2%) reacted to one or more allergens from the labelled fragrance substance series and/or a fragrance marker from the European baseline series. The allergens that were positive with the greatest frequencies were oxidized linalool [n = 154; 7·4%, 95% confidence interval (CI) 6·3-8·6], oxidized limonene (n = 89; 4·3%, 95% CI 3·4-5·2) and Evernia furfuracea (n = 44; 2·1%, 95% CI 1·5-2·8). Of the 319 patients who reacted to any of the labelled fragrance substances, only 130 (40·8%) also reacted to a baseline series fragrance marker. The sensitivity of our history-taking for detecting fragrance allergy was 25·7%. CONCLUSIONS: Given the evolving trends in fragrance allergy, patch testing with FMI, FMII, M. pereirae and hydroxyisohexyl 3-cyclohexene carboxaldehyde is no longer sufficient for screening for fragrance allergy.

European Surveillance System on Contact Allergies (ESSCA): results with the European baseline series, 2013/14.

BACKGROUND: Contact allergy is a common condition and can severely interfere with daily life or professional activities. Due to changes in exposures, such as introduction of new substances, new products or formulations and regulatory intervention, the spectrum of contact sensitization changes. OBJECTIVE: To evaluate the current spectrum of contact allergy to allergens present in the European baseline series (EBS) across Europe. METHODS: Retrospective analysis of data collected by the European Surveillance System on Contact Allergies (ESSCA, www.essca-dc.org) in consecutively patch-tested patients, 2013/14, in 46 departments in 12 European countries. RESULTS: Altogether, 31 689 patients were included in the analysis. Compared to a similar analysis in 2004, the prevalence of contact allergy to methylisothiazolinone went up to around 20% in several departments. In comparison, contact allergy to the metals nickel, cobalt and chromium remained largely stable, at 18.1%, 5.9% and 3.2%, respectively, similar to mostly unchanged prevalence with fragrance mix I, II and Myroxylon pereirae (balsam of Peru) at 7.3%, 3.8% and 5.3%, respectively. In the subgroup of departments diagnosing (mainly) patients with occupational contact dermatitis, the prevalence of work-related contact allergies such as epoxy resin or rubber additives was found to be increased, compared to general dermatology departments. CONCLUSION: Continuous surveillance of contact allergy based on network data offers the identification of time trends or persisting problems, and thus enables focussing in-depth research (subgroup analyses, exposure analysis) on areas where it is needed.

A dynamic landscape of allergen associations in delayed-type cutaneous hypersensitivity.

BACKGROUND: Delayed-type hypersensitivity represents a significant clinical and public health challenge. Patients undergoing patch testing may exhibit positive reactions to more than one allergen. It is recognized that reactions to specific pairs of allergens are associated, reflecting a combination of exposure patterns and structural similarity. OBJECTIVES: To explore the influence of time of testing, age, sex and atopy status on allergen pair associations in a series of 45 110 consecutive patients tested over 30 years. METHODS: Patch test records of all patients undergoing testing with a modified European baseline series between 1985 and 2014 were retrieved from a database at St John's Institute of Dermatology. Reactions were read on days 2 and 4. For each allergen it was recorded whether the allergen was tested and whether the result was positive or negative. RESULTS: This is the largest reported study of patch test allergen pair relationships. Our analysis shows a high degree of variability in allergen pair associations. Rigorous statistical analysis reveals a large number of differences between groups, including a significant increase in the association between formaldehyde and multiple formaldehyde-releasing preservatives over the study period, in addition to pair associations with cobalt and formaldehyde-releasing preservatives. These were present to a significantly greater extent in men than in women. CONCLUSIONS: These observations extend our understanding of cutaneous allergy, with implications for both clinical practice and mechanisms of cutaneous hypersensitivity.

Skin sensitization: Implications for integration of clinical data into hazard identification and risk assessment.

Skin sensitization associated with allergic contact dermatitis is a common health problem and is an important consideration for toxicologists in safety assessment. Historically, in vivo predictive tests have been used with good success to identify substances that have the potential to induce skin sensitization, and these tests formed the basis of safety evaluation. These original tests are now being replaced gradually either by in vitro assays or by further refinements of in vivo methods such as the local lymph node assay. Human data have also been available to inform classification decisions for some substances and have been used by risk managers to introduce measures for exposure reduction. However, humans encounter hazards in the context of exposure rather than in the form of intrinsic hazards per se, and so in this article, we have examined critically the extent to which human data have been used to refine classification decisions and safety evaluations. We have also evaluated information on the burden of human allergic skin disease and used this to address the question of whether, and to what extent, the identification and evaluation of skin sensitization hazards has led to an improvement of public and/or occupational health.

Multivariate meta-analysis using individual participant data.

When combining results across related studies, a multivariate meta-analysis allows the joint synthesis of correlated effect estimates from multiple outcomes. Joint synthesis can improve efficiency over separate univariate syntheses, may reduce selective outcome reporting biases, and enables joint inferences across the outcomes. A common issue is that within-study correlations needed to fit the multivariate model are unknown from published reports. However, provision of individual participant data (IPD) allows them to be calculated directly. Here, we illustrate how to use IPD to estimate within-study correlations, using a joint linear regression for multiple continuous outcomes and bootstrapping methods for binary, survival and mixed outcomes. In a meta-analysis of 10 hypertension trials, we then show how these methods enable multivariate meta-analysis to address novel clinical questions about continuous, survival and binary outcomes; treatment-covariate interactions; adjusted risk/prognostic factor effects; longitudinal data; prognostic and multiparameter models; and multiple treatment comparisons. Both frequentist and Bayesian approaches are applied, with example software code provided to derive within-study correlations and to fit the models.

Allowing for non-adherence to treatment in a randomized controlled trial of two antidepressants (citalopram versus reboxetine): an example from the GENPOD trial.

BACKGROUND: Meta-analyses suggest that reboxetine may be less effective than other antidepressants. Such comparisons may be biased by lower adherence to reboxetine and subsequent handling of missing outcome data. This study illustrates how to adjust for differential non-adherence and hence derive an unbiased estimate of the efficacy of reboxetine compared with citalopram in primary care patients with depression. METHOD: A structural mean modelling (SMM) approach was used to generate adherence-adjusted estimates of the efficacy of reboxetine compared with citalopram using GENetic and clinical Predictors Of treatment response in Depression (GENPOD) trial data. Intention-to-treat (ITT) analyses were performed to compare estimates of effectiveness with results from previous meta-analyses. RESULTS: At 6 weeks, 92% of those randomized to citalopram were still taking their medication, compared with 72% of those randomized to reboxetine. In ITT analysis, there was only weak evidence that those on reboxetine had a slightly worse outcome than those on citalopram [adjusted difference in mean Beck Depression Inventory (BDI) scores: 1.19, 95% confidence interval (CI) -0.52 to 2.90, p = 0.17]. There was no evidence of a difference in efficacy when differential non-adherence was accounted for using the SMM approach for mean BDI (-0.29, 95% CI -3.04 to 2.46, p = 0.84) or the other mental health outcomes. CONCLUSIONS: There was no evidence of a difference in the efficacy of reboxetine and citalopram when these drugs are taken and tolerated by depressed patients. The SMM approach can be implemented in standard statistical software to adjust for differential non-adherence and generate unbiased estimates of treatment efficacy for comparisons of two (or more) active interventions.

Consistency and inconsistency in network meta-analysis: concepts and models for multi-arm studies.

Meta-analyses that simultaneously compare multiple treatments (usually referred to as network meta-analyses or mixed treatment comparisons) are becoming increasingly common. An important component of a network meta-analysis is an assessment of the extent to which different sources of evidence are compatible, both substantively and statistically. A simple indirect comparison may be confounded if the studies involving one of the treatments of interest are fundamentally different from the studies involving the other treatment of interest. Here, we discuss methods for addressing inconsistency of evidence from comparative studies of different treatments. We define and review basic concepts of heterogeneity and inconsistency, and attempt to introduce a distinction between 'loop inconsistency' and 'design inconsistency'. We then propose that the notion of design-by-treatment interaction provides a useful general framework for investigating inconsistency. In particular, using design-by-treatment interactions successfully addresses complications that arise from the presence of multi-arm trials in an evidence network. We show how the inconsistency model proposed by Lu and Ades is a restricted version of our full design-by-treatment interaction model and that there may be several distinct Lu-Ades models for any particular data set. We introduce novel graphical methods for depicting networks of evidence, clearly depicting multi-arm trials and illustrating where there is potential for inconsistency to arise. We apply various inconsistency models to data from trials of different comparisons among four smoking cessation interventions and show that models seeking to address loop inconsistency alone can run into problems. Copyright © 2012 John Wiley & Sons, Ltd.