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We propose a parametric model for describing chronic disease mortality from cohort data and illustrate its use for Type 2 diabetes. The model uses ideas from accelerated life testing in reliability theory and conceptualizes the occurrence of a chronic disease as putting the observational unit to an enhanced stress level, which is supposed to shorten its lifetime. It further addresses the issue of semi-competing risk, that is, the asymmetry of death and diagnosis of disease, where the disease can be diagnosed before death, but not after. With respect to the cohort structure of the data, late entry into the cohort is taken into account and prevalent as well as incident cases inform the analysis. We finally give an extension of the model that allows age at disease diagnosis to be observed not exactly, but only partially within an interval. Model parameters can be straightforwardly estimated by Maximum Likelihood, using the assumption of a Gompertz distribution we show in a small simulation study that this works well. Data of the Cardiovascular Disease, Living and Ageing in Halle (CARLA) study, a population-based cohort in the city of Halle (Saale) in the eastern part of Germany, are used for illustration., (© 2024 The Author(s). Statistics in Medicine published by John Wiley & Sons Ltd.)

Weighting methods are widely used for causal effect estimation in non-randomised studies. In general, these methods use the propensity score (PS), the probability of receiving the treatment given the covariates, to arrive at the respective weights. All of these "modelling" methods actually optimize prediction of the respective outcome, which is, in the PS model, treatment assignment. However, this does not match with the actual aim of weighting, which is eliminating the association between covariates and treatment assignment. In the "balancing" approach, covariates are thus balanced directly by solving systems of numerical equations, explicitly without fitting a PS model. To compare modelling, balancing and hybrid approaches to weighting we performed a large simulation study for a binary treatment and a survival outcome. For maximal practical relevance all simulation parameters were selected after a systematic review of medical studies that used PS methods for analysis. We also introduce a new hybrid method that uses the idea of the covariate balancing propensity score and matching weights, thus avoiding extreme weights. In addition, we present a corrected robust variance estimator for some of the methods. Overall, our simulations results indicate that balancing approach methods work worse than expected. However, among the considered balancing methods, entropy balancing consistently outperforms the variance balancing approach. All methods estimating the average treatment effect in the overlap population perform well with very little bias and small standard errors even in settings with misspecified propensity score models. Finally, the coverage using the standard robust variance estimator was too high for all methods, with the proposed corrected robust variance estimator improving coverage in a variety of settings., (© 2024 The Authors. Statistics in Medicine published by John Wiley & Sons Ltd.)

Meta-analysis of diagnostic studies is still field of ongoing biometrical research. Especially, clinical researchers call for methods that allow for a comparison of different diagnostic tests to a common gold standard. Focussing on two diagnostic tests, the main parameters of interest are differences of sensitivities and specificities (with their corresponding confidence intervals) between the two diagnostic tests while accounting for the various associations across the two tests and the single studies. Similar to our previous work using generalized linear mixed models to this task, we propose a model with a quadrivariate response consisting of the two sensitivities and the two specificities of both tests. This new approach uses the ideas of copula modelling, and especially a quadrivariate Gaussian copula and a quadrivariate vine copula, which is built from bivariate Plackett copulas. The different copulas are compared in a simulation study and illustrated by the application of population-based screening for type 2 diabetes., (Copyright © 2017 John Wiley & Sons, Ltd.)

The purpose of this single-centre prospective non-randomised study was to evaluate the effectiveness of an interdisciplinary care programme to enhance self-management in patients with haematopoietic stem cell transplantation (HSCT). Patients undergoing HSCT, aged >14 years with informed consent were recruited (n = 79). Patients in the intervention group (IG) received standard care plus the SCION-HSCT intervention to counteract three problems after HSCT: muscle weakness, oral mucositis and malnutrition. Control group patients received standard care. Primary endpoint was global health-related quality of life (HRQoL) at discharge (EORTC QLQ C30 v. 3.0). Baseline characteristics were balanced between both groups, except physical performance (ECOG) being significantly lower for patients of the IG. At discharge, no group differences could be seen regarding HRQoL. Non-confirmatory post hoc analyses showed for patients of the IG a shorter duration of hospitalisation (MD -10.90; 95% CI -18.05 to -3.75) and increased activity during hospitalisation (MD 2.44; 95% CI 1.27-3.61). In conclusion, clinical effectiveness of the intervention could not be proven with respect to the aspired improvement of HRQoL. However, the nurse-led interdisciplinary caring programme could be carried out in every day ward routine. Further research should focus on working mechanisms of complex interventions aiming to improve HRQoL of patients undergoing HSCT., (© 2016 John Wiley & Sons Ltd.)

Background: The standardized protocol for performing the strip patch test has proven to be valid, but evidence on its reliability is still missing., Objective: To estimate the parallel-test reliability of the strip patch test as compared with the conventional patch test., Methods: In this multicentre, prospective, randomized, investigator-blinded reliability study, 132 subjects were enrolled. Simultaneous duplicate strip and conventional patch tests were performed with the Finn Chambers ® on Scanpor ® tape test system and the patch test preparations nickel sulfate 5% pet., potassium dichromate 0.5% pet., and lanolin alcohol 30% pet. Reliability was estimated by the use of Cohen's kappa coefficient., Results: Parallel-test reliability values of the three standard patch test preparations turned out to be acceptable, with slight advantages for the strip patch test. The differences in reliability were 9% (95%CI: -8% to 26%) for nickel sulfate and 23% (95%CI: -16% to 63%) for potassium dichromate, both favouring the strip patch test., Conclusions: The standardized strip patch test method for the detection of allergic contact sensitization in patients with suspected allergic contact dermatitis is reliable. Its application in routine clinical practice can be recommended, especially if the conventional patch test result is presumably false negative., (© 2017 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.)

Summarizing the information of many studies using a meta-analysis becomes more and more important, also in the field of diagnostic studies. The special challenge in meta-analysis of diagnostic accuracy studies is that in general sensitivity and specificity are co-primary endpoints. Across the studies both endpoints are correlated, and this correlation has to be considered in the analysis. The standard approach for such a meta-analysis is the bivariate logistic random effects model. An alternative approach is to use marginal beta-binomial distributions for the true positives and the true negatives, linked by copula distributions. In this article, we propose a new, nonparametric approach of analysis, which has greater flexibility with respect to the correlation structure, and always converges. In a simulation study, it becomes apparent that the empirical coverage of all three approaches is in general below the nominal level. Regarding bias, empirical coverage, and mean squared error the nonparametric model is often superior to the standard model, and comparable with the copula model. The three approaches are also applied to two example meta-analyses., (Copyright © 2015 John Wiley & Sons, Ltd.)

Meta-analyses with rare events, especially those that include studies with no event in one ('single-zero') or even both ('double-zero') treatment arms, are still a statistical challenge. In the case of double-zero studies, researchers in general delete these studies or use continuity corrections to avoid them. A number of arguments against both options has been given, and statistical methods that use the information from double-zero studies without using continuity corrections have been proposed. In this paper, we collect them and compare them by simulation. This simulation study tries to mirror real-life situations as completely as possible by deriving true underlying parameters from empirical data on actually performed meta-analyses. It is shown that for each of the commonly encountered effect estimators valid statistical methods are available that use the information from double-zero studies without using continuity corrections. Interestingly, all of them are truly random effects models, and so also the current standard method for very sparse data as recommended from the Cochrane collaboration, the Yusuf-Peto odds ratio, can be improved on. For actual analysis, we recommend to use beta-binomial regression methods to arrive at summary estimates for the odds ratio, the relative risk, or the risk difference. Methods that ignore information from double-zero studies or use continuity corrections should no longer be used. We illustrate the situation with an example where the original analysis ignores 35 double-zero studies, and a superior analysis discovers a clinically relevant advantage of off-pump surgery in coronary artery bypass grafting., (Copyright © 2014 John Wiley & Sons, Ltd.)

There are still challenges when meta-analyzing data from studies on diagnostic accuracy. This is mainly due to the bivariate nature of the response where information on sensitivity and specificity must be summarized while accounting for their correlation within a single trial. In this paper, we propose a new statistical model for the meta-analysis for diagnostic accuracy studies. This model uses beta-binomial distributions for the marginal numbers of true positives and true negatives and links these margins by a bivariate copula distribution. The new model comes with all the features of the current standard model, a bivariate logistic regression model with random effects, but has the additional advantages of a closed likelihood function and a larger flexibility for the correlation structure of sensitivity and specificity. In a simulation study, which compares three copula models and two implementations of the standard model, the Plackett and the Gauss copula do rarely perform worse but frequently better than the standard model. We use an example from a meta-analysis to judge the diagnostic accuracy of telomerase (a urinary tumor marker) for the diagnosis of primary bladder cancer for illustration., (Copyright © 2013 John Wiley & Sons, Ltd.)

Background: As a modification of patch testing, the strip patch test was established to obtain more sensitive and reliable test results. Comparative data on diagnostic accuracy for both tests are missing., Objectives: To compare the diagnostic accuracy of strip patch tests and patch tests in detecting sensitizations in patients with suspected allergic contact dermatitis by using patient history as the reference standard., Patients/methods: In a multicentre, prospective, investigator-blinded study 790 patients were enrolled. The defined reference standard was established prior to patch testing. Patch tests were performed with nickel sulfate, potassium dichromate, and lanolin alcohol. Duplicate tests were simultaneously performed on both sides of the back, of which one randomly chosen side was tape stripped beforehand, according to a standardized procedure. Primary outcome was the difference in sensitivity between strip patch test and patch test., Results: Seven hundred and eighty-seven patients were included in the analysis. Strip patch tests detected considerably more sensitization to nickel sulfate and potassium dichromate than patch tests: differences of sensitivities were 16.4% (95% CI, 8.7-24.1%) for nickel sulfate and 25.0% (95% CI, 8.9-41.0%) for potassium dichromate, both favouring the strip patch test., Conclusions: The standardized strip patch test proved to be accurate and clinically safe and is promising to improve diagnosis of allergic contact dermatitis beyond the patch test.

The number needed to treat (NNT) is a popular measure to describe the absolute effect of a new treatment compared with a standard treatment or placebo in clinical trials with binary outcome. For use of NNT measures in epidemiology to compare exposed and unexposed subjects, the terms 'number needed to be exposed' (NNE) and 'exposure impact number' (EIN) have been proposed. Additionally, in the framework of logistic regression a method was derived to perform point and interval estimation of NNT measures with adjustment for confounding by using the adjusted odds ratio (OR approach). In this paper, a new method is proposed which is based upon the average risk difference over the observed confounder values (ARD approach). A decision has to be made, whether the effect of allocating an exposure to unexposed persons or the effect of removing an exposure from exposed persons should be described. We use the term NNE for the first and the term EIN for the second situation. NNE is the average number of unexposed persons needed to be exposed to observe one extra case; EIN is the average number of exposed persons among one case can be attributed to the exposure. By means of simulations it is shown that the ARD approach is better than the OR approach in terms of bias and coverage probability, especially if the confounder distribution is wide. The proposed method is illustrated by application to data of a cohort study investigating the effect of smoking on coronary heart disease., (Copyright (c) 2007 John Wiley & Sons, Ltd.)

Background: Pressure ulcers affect 10% of people in hospitals and older people are at highest risk. The correlation between nutritional intake and the development of pressure ulcers is suggested by several studies, but the results are inconsistent., Objectives: To evaluate the effectiveness of enteral and parenteral nutrition on the prevention and treatment of pressure ulcers., Search Strategy: The Cochrane Wounds Group Specialised Trials Register and the Cochrane Central register of Controlled Trials were searched in September 2002. An additional search of PubMed and Cinahl and hand search of conference proceedings and journals was performed, bibliographies of relevant articles were examined and experts in the field as well as manufacturers were contacted in order to find additional literature that may be relevant., Selection Criteria: Randomised controlled trials evaluating the effectiveness of enteral or parenteral nutrition on the prevention and treatment of pressure ulcers by measuring the incidence of new ulcers, ulcer healing or changes in pressure ulcer severity. There were no restrictions on patients, setting, date, publication status or language., Data Collection and Analysis: Abstracts were independently inspected and full articles were obtained of potentially relevant studies. In case of disagreement advice was sought from a third person (AK). Data extraction and assessment of quality were undertaken by the three reviewers independently., Main Results: Only 8 randomised controlled trials out of 16 potentially relevant articles were included. However, most of the 8 trials included are small and of poor methodological quality., Prevention: Four studies compared a combination of nutritional supplements, consisting of a minimum of energy and protein in different dosages, for the prevention of pressure ulcers. The largest study found that nutritional supplements reduced the number of new pressure ulcers (Bourdel-M 2000). The three smaller studies lacked power., Treatment: Four studies evaluated the effects of nutritional supplements for the treatment of existing pressure ulcers: one trial examined mixed nutritional supplements, one trial examined zinc, another the effect of proteins, and two studies compared ascorbic acid. The trials included are heterogeneous with regard to participants, interventions and outcomes; therefore it was considered inappropriate to perform a meta-analysis., Reviewer's Conclusions: It was not possible to draw any firm conclusions on the effect of enteral and parenteral nutrition on the prevention and treatment of pressure ulcers. Further trials of high methodological quality are necessary.

The logistic regression model has become the standard analysing tool for binary responses in medical statistics. Methods for assessing goodness-of-fit, however, are less developed where this problem is especially pronounced in performing global goodness-of-fit tests with sparse data, that is, if the data contain only a small numbers of observations for each pattern of covariate values. In this situation it has been known for a long time that the standard goodness-of-fit tests (residual deviance and Pearson chi-square) behave unsatisfactorily if p-values are calculated from the chi(2)-distribution. As a remedy in this situation the Hosmer-Lemeshow test is frequently recommended; it relies on a new grouping of the observations to avoid sparseness, where this grouping depends on the estimated probabilities from the model. It has been shown, however, that the Hosmer-Lemeshow test also has some deficiencies, for example, it depends heavily on the calculating algorithm and thus different implementations might lead to different conclusions regarding the fit of the model. We present some alternative tests from the statistical literature which should also perform well with sparse data. Results from a simulation study are given which show that there exist some goodness-of-fit tests (for example, the Farrington test) that have good properties regarding size and power and that even outperform the Hosmer-Lemeshow test. We illustrate the various tests with an example from dermatology on occupational hand eczema in hairdressers., (Copyright 2002 John Wiley & Sons, Ltd.)

In irritancy studies, measurement of transepidermal water loss (TEWL) is a widely used technique to assess barrier function. Using inappropriate statistical methods, however, leads to loss of information and misinterpretation of results. In this paper, we discuss some problems and pitfalls when using a suitable statistical technique for most designs in bioengineering studies, analysis of variance (ANOVA): multiple comparisons, choice of sample size and violation of statistical assumptions. For clarification of these points, a practical example will be given. Using the proposed adequate statistical methods correctly will, although accompanied by increased complexity, increase the efficiency of bioengineering studies.