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Missing outcome data are common in clinical trials and despite a well-designed study protocol, some of the randomized participants may leave the trial early without providing any or all of the data, or may be excluded after randomization. Premature discontinuation causes loss of information, potentially resulting in attrition bias leading to problems during interpretation of trial findings. The causes of information loss in a trial, known as mechanisms of missingness, may influence the credibility of the trial results. Analysis of trials with missing outcome data should ideally be handled with intention to treat (ITT) rather than per protocol (PP) analysis. However, true ITT analysis requires appropriate assumptions and imputation of missing data. Using a worked example from a published dental study, we highlight the key issues associated with missing outcome data in clinical trials, describe the most recognized approaches to handling missing outcome data, and explain the principles of ITT and PP analysis.

Erworben im Rahmen der Schweizer Nationallizenzen (http://www.nationallizenzen.ch), Background: Worldwide, 14.9 million infants (11%) are born preterm each year. Up to 40% of preterm births (PTBs) are associated with genital tract infections. The vaginal pH can reflect changes in the vaginal milieu and, if elevated, indicates an abnormal flora or infection. Objective: The aim of the study was to investigate whether an increased antenatal vaginal pH >4.5 in pre-labour pregnant women is associated with an increased PTB rate 4.5 may be associated with a higher risk for PTB. It is recommended to conduct a randomised controlled trial (RCT) to investigate the effectiveness of antenatal pH screening to prevent PTB. Tweetable abstract Pregnant women with an increased vaginal pH >4.5 may be at higher risk to experience preterm birth.

OBJECTIVES The purpose of the study was to provide empirical evidence about the reporting of methodology to address missing outcome data and the acknowledgement of their impact in Cochrane systematic reviews in the mental health field. METHODS Systematic reviews published in the Cochrane Database of Systematic Reviews after January 1, 2009 by three Cochrane Review Groups relating to mental health were included. RESULTS One hundred ninety systematic reviews were considered. Missing outcome data were present in at least one included study in 175 systematic reviews. Of these 175 systematic reviews, 147 (84%) accounted for missing outcome data by considering a relevant primary or secondary outcome (e.g., dropout). Missing outcome data implications were reported only in 61 (35%) systematic reviews and primarily in the discussion section by commenting on the amount of the missing outcome data. One hundred forty eligible meta-analyses with missing data were scrutinized. Seventy-nine (56%) of them had studies with total dropout rate between 10 and 30%. One hundred nine (78%) meta-analyses reported to have performed intention-to-treat analysis by including trials with imputed outcome data. Sensitivity analysis for incomplete outcome data was implemented in less than 20% of the meta-analyses. CONCLUSIONS Reporting of the techniques for handling missing outcome data and their implications in the findings of the systematic reviews are suboptimal.

Klinische Entscheidungen sollten auf der Grundlage von Ergebnissen qualitativ hochwertiger klinischer Studien und systematischer Ubersichtsarbeiten getroffen werden. Herkommliche Ubersichtsarbeiten vergleichen, wenn moglich, die Ergebnisse von Untersuchungen derselben Behandlungsmasnahme miteinander, um prazisere Aussagen zur Effektivitat des jeweiligen Verfahrens treffen zu konnen. Gibt es allerdings mehrere Behandlungsmasnahmen fur ein und dasselbe Problem, wird es schwierig zu bestimmen, welche davon die Beste ist, da nur Studien ausgewertet werden, die dieselben Interventionen miteinander vergleichen. Die aktuellen Fortschritte bei der Synthese von Daten im Rahmen einer Netzwerk-Metaanalyse (network meta-analysis, NMA) ermoglichen die gemeinsame Untersuchung der Wirkung unterschiedlicher Behandlungsmasnahmen fur ein Problem und die Beurteilung ihrer Effektivitat. Die NMA ist zwar ein neues Verfahren in der Zahnmedizin und der Kieferorthopadie, das jedoch ein wichtiges Hilfsmittel fur eine evidenzbasierte Kieferorthopadie sein kann.

Missing outcome data is a major threat in meta-analytical studies of schizophrenia. Most clinical trials in psychiatry report only continuous outcome measures and express the effect of an intervention as a difference of means. However, these results are difficult to interpret for clinicians. Converting continuous data to binary response rates is one possible solution to the problem. Based on means and standard deviations for a continuous outcome, we examined the performance of an imputation method to define a dichotomous outcome using original individual patients' data from 16 randomized trials (6276 participants) comparing antipsychotic drugs in schizophrenia. We concluded that the imputed values re-captured in a reasonable degree the observed values providing a simple and practical alternative methodological choice for imputation of missing binary data in schizophrenia trials; nevertheless, the imputation method tended to introduce biases, especially for extreme risks and large treatment differences.

To examine age-related changes in TFrom our pool of clinical pediatric MRI examinations at 3T all patients with normal conventional MRI scans were retrospectively selected. Depending on their clinical findings the identified 99 patients (0-199months) were divided into 43 healthy controls and 56 diseased children with various clinical abnormalities (developmental delay, epilepsy, prematurity, and deafness). TAge significantly reduced TUsing T

Background In a meta-analysis of trials with missing outcome data, a parameter known as informative missing odds ratio (IMOR) can be used to quantify the relationship between informative missingness and a binary outcome. IMORs also account for the increased uncertainty due to missingness in the meta-analysis results. Purpose To extend the idea of IMOR into a network meta-analysis (NMA) setting in order to explore the impact of missing outcome data on the inferences about the relative effectiveness of several competing treatments in psychiatric trials. Methods IMORs were estimated in two datasets comparing anti-manic treatments and antidepressants. The outcome was response to treatments. In the original meta-analyses, missing participants were assumed to have failed regardless the treatment they were allocated to. To evaluate the robustness of this assumption in each dataset, several imputations of the missing outcomes were studied by an IMOR parameter in the NMA model. By comparing the odds ratios for efficacy under the initial analysis and under several assumptions about the missingness, we assessed the consistency of the conclusions. The missing data mechanism was studied by comparing the prior with the posterior IMOR distribution. Models were fitted using Markov chain Monte Carlo (MCMC) in WinBUGS. Results In both datasets, the relative effectiveness of the treatments seems to be affected only by the two extreme imputation scenarios of worst- and best-case analyses. Moreover, heterogeneity increases in both datasets under these two extreme scenarios. Overall, there is a non-significant change on the ranking of the anti-manic and antidepressant treatments. The posterior and prior IMOR distributions are very similar showing that the data do not provide any information about the true outcome in missing participants. There is a very weak indication that missing participants tend to fail in placebo and paroxetine, while the opposite occurs for sertraline, fluoxetine, and fluvoxamine. Limitations Investigation of informative missingness was limited two classes of treatments and for dichotomous outcome measures. The proportion of missing outcomes was very low overall, and hence, the power of detecting any differences in effectiveness estimated under the various imputation methods is small. Conclusions Sensitivity analysis to account for missing outcome data and their uncertainty in the NMA can be undertaken by extending the idea of IMOR. In two case examples, we found no differences between the various models due to low missing data rate. In line with previous observations, data carry little information about the reason of missingness.

Objectives Tο report challenges encountered during the extraction process from Cochrane reviews in mental health and Campbell reviews and to indicate their implications on the empirical performance of different methods to handle missingness. Methods We used a collection of meta-analyses on binary outcomes collated from a previous work on missing outcome data. To evaluate the accuracy of their extraction, we developed specific criteria pertaining to the reporting of missing outcome data in systematic reviews. Using the most popular methods to handle missing binary outcome data, we investigated the implications of the accuracy of the extracted meta-analysis on the random-effects meta-analysis results. Results Of 113 meta-analyses from Cochrane reviews, 60 (53%) were judged as “unclearly” extracted (ie, no information on the outcome of completers but available information on how missing participants were handled) and 42 (37%) as “unacceptably” extracted (ie, no information on the outcome of completers as well as no information on how missing participants were handled). For the remaining meta-analyses, it was judged that data were “acceptably” extracted (ie, information on the completers' outcome was provided for all trials). Overall, “unclear” extraction overestimated the magnitude of the summary odds ratio and the between-study variance and additionally inflated the uncertainty of both meta-analytical parameters. The only eligible Campbell review was judged as “unclear.” Conclusions Depending on the extent of missingness, the reporting quality of the systematic reviews can greatly affect the accuracy of the extracted meta-analyses and by extent, the empirical performance of different methods to handle missingness.

Patient dropout is common in mental health trials. It is important to understand why patients drop out from trials, so that measures can be taken to minimize its occurrence. This research sought to identify trial characteristics that have an impact on premature discontinuation in antipsychotic trials for schizophrenia. Methods: Poisson regression analysis was applied with dropout rate per patient-week as the dependent variable and trial characteristics as independent variables. Multinomial logistic regression analysis was performed to examine whether the same characteristics predict whether patients drop out without providing any outcome data and whether they drop out with sufficient early data for a 'last observation carried forward' analysis to be performed. Results: trials with adequate allocation concealment, double blinding, placebo as control, higher precision, larger trial size, at least three treatment arms, recent publication, conduct in the United States and enrollment of inpatients were all associated with higher dropout rates. Similar factors were associated with whether a patient was more likely to be evaluated at least once, or be excluded entirely from the analysis. However, blinding status did not predict the former type of dropout, and allocation concealment, higher precision and larger sample size, number of arms, recent publication and recruiting inpatient did not predict the latter type of dropout. Conclusions: high dropout rates in antipsychotic trials can be associated with various characteristics, and appears to be particularly associated with use of placebo and study size. © 2013 Elsevier B.V. and ECNP.

Summary Background The question of which antipsychotic drug should be preferred for the treatment of schizophrenia is controversial, and conventional pairwise meta-analyses cannot provide a hierarchy based on the randomised evidence. We aimed to integrate the available evidence to create hierarchies of the comparative efficacy, risk of all-cause discontinuation, and major side-effects of antipsychotic drugs. Methods We did a Bayesian-framework, multiple-treatments meta-analysis (which uses both direct and indirect comparisons) of randomised controlled trials to compare 15 antipsychotic drugs and placebo in the acute treatment of schizophrenia. We searched the Cochrane Schizophrenia Group's specialised register, Medline, Embase, the Cochrane Central Register of Controlled Trials, and ClinicalTrials.gov for reports published up to Sept 1, 2012. Search results were supplemented by reports from the US Food and Drug Administration website and by data requested from pharmaceutical companies. Blinded, randomised controlled trials of patients with schizophrenia or related disorders were eligible. We excluded trials done in patients with predominant negative symptoms, concomitant medical illness, or treatment resistance, and those done in stable patients. Data for seven outcomes were independently extracted by two reviewers. The primary outcome was efficacy, as measured by mean overall change in symptoms. We also examined all-cause discontinuation, weight gain, extrapyramidal side-effects, prolactin increase, QTc prolongation, and sedation. Findings We identified 212 suitable trials, with data for 43 049 participants. All drugs were significantly more effective than placebo. The standardised mean differences with 95% credible intervals were: clozapine 0·88, 0·73–1·03; amisulpride 0·66, 0·53–0·78; olanzapine 0·59, 0·53–0·65; risperidone 0·56, 0·50–0·63; paliperidone 0·50, 0·39–0·60; zotepine 0·49, 0·31–0·66; haloperidol 0·45, 0·39–0·51; quetiapine 0·44, 0·35–0·52; aripiprazole 0·43, 0·34–0·52; sertindole 0·39, 0·26–0·52; ziprasidone 0·39, 0·30–0·49; chlorpromazine 0·38, 0·23–0·54; asenapine 0·38, 0·25–0·51; lurasidone 0·33, 0·21–0·45; and iloperidone 0·33, 0·22–0·43. Odds ratios compared with placebo for all-cause discontinuation ranged from 0·43 for the best drug (amisulpride) to 0·80 for the worst drug (haloperidol); for extrapyramidal side-effects 0·30 (clozapine) to 4·76 (haloperidol); and for sedation 1·42 (amisulpride) to 8·82 (clozapine). Standardised mean differences compared with placebo for weight gain varied from −0·09 for the best drug (haloperidol) to −0·74 for the worst drug (olanzapine), for prolactin increase 0·22 (aripiprazole) to −1·30 (paliperidone), and for QTc prolongation 0·10 (lurasidone) to −0·90 (sertindole). Efficacy outcomes did not change substantially after removal of placebo or haloperidol groups, or when dose, percentage of withdrawals, extent of blinding, pharmaceutical industry sponsorship, study duration, chronicity, and year of publication were accounted for in meta-regressions and sensitivity analyses. Interpretation Antipsychotics differed substantially in side-effects, and small but robust differences were seen in efficacy. Our findings challenge the straightforward classification of antipsychotics into first-generation and second-generation groupings. Rather, hierarchies in the different domains should help clinicians to adapt the choice of antipsychotic drug to the needs of individual patients. These findings should be considered by mental health policy makers and in the revision of clinical practice guidelines. Funding None.

This study evaluated the diagnostic value of D-dimer, CRP, and leucocytes count to detect an underlying pulmonary embolism (PE) in patients with pneumonia. A predictive model of an underlying PE, based on laboratory markers and clinical symptoms, was our ultimate objective. Overall 100 patients underwent a computed tomography angiography (CTA) of the lung: 54 with coexistence of PE and pneumonia (cases) and 46 with pneumonia without PE (controls). Cases and controls were matched 1 : 1. Symptoms and paraclinical findings were registered on admission. Receiver operating characteristic (ROC) curves, search for an optimal threshold, and conditional logistic regression analysis were conducted. D-dimer has a moderate ability to detect PE in pneumonia. Sensitivity of D-dimer was estimated at 97.78% and specificity at 11.11%. No optimal cut-point has acceptable diagnostic ability. After excluding patients with sepsis, sensitivity was reduced to 96.97%, whereas specificity increased to 16.13%. Consolidation in chest X-ray and positive D-dimer predict better an underlying PE as D-dimer itself. Thus, discriminatory power of the prediction model (AUC of 0.740) is not much greater than D-dimer (AUC of 0.703). No threshold that could increase the diagnostic value of D-dimer or a prediction model which is significantly better than D-dimer itself was identified.

AIM To assess the risk of bias (RoB) in a subset of randomized controlled trials (RCTs) published in orthodontic journals using the Cochrane RoB tool and to identify associations between domain RoB assessment and treatment effect estimates. MATERIALS AND METHODS Fifty consecutive issues of four major orthodontic journals were electronically searched to identify RCTs. The quality of the included studies was assessed using the Cochrane RoB tool, which involves seven domains rated as 'low', 'unclear' or 'high': random sequence generation, allocation concealment, blinding of participants and personnel, blinding of outcome assessment, incomplete outcome data, and selective outcome reporting, and other threats to internal validity. Estimates and confidence intervals (CIs) were recorded or calculated where possible for binary and continuous outcome measures. Meta-regression models were employed to assess the impact of RoB per domain on the magnitude of treatment effect. RESULTS One hundred and one eligible studies involving 128 pair-wise comparisons were retrieved. Blinding of outcome assessors and incomplete outcome data were frequently judged as 'high' for RoB both for studies with binary and continuous outcome (42.9 and 48.8 per cent, respectively). For binary outcomes, high RoB regarding random sequence generation [odds ratio (OR): 5.97, 95% CI: 2.03, 17.63, P-value: 0.002] and incomplete outcome data (OR: 4.07, 95% CI: 1.03, 16.15, P-value: 0.05) were more likely to provide exaggerated effect estimates. CONCLUSIONS There is a need for improved clinical trial methodology and reporting, in order to avoid inflated associations and erroneous conclusions.

Animal and human studies suggest that vitamin D regulates functions of the reproductive system. Vitamin D deficiency is prevalent in women of reproductive age. Vitamin D status has been associated with in vitro fertilisation outcome, features of polycystic ovarian syndrome (PCOS) and endometriosis. The aims of our study were to investigate the prevalence of vitamin D deficiency of infertile women living in central Germany, to identify risk factors for vitamin D deficiency and to specify seasonal variations of vitamin D status. This was a retrospective cohort study at an academic tertiary care centre (N = 113) and an Outpatient Centre for Reproductive Medicine (N = 193) of women presenting for infertility treatment. The statistical evaluation was descriptive and explorative. Possible risk factors associated with an increased risk for vitamin D deficiency were assessed using multiple logistic regression models. Variables with p value less than 0.05 were further assessed in a multivariable logistic regression model. Overall, 98.2 % of patients at centre 1 and 81.3 % of women with impaired fertility at centre 2 had deficient or insufficient vitamin D levels. Overweight BMI and limited exposure to sun (winter, spring and autumn trimester) were associated with an increased risk of vitamin D deficiency. Vitamin D levels did not vary according to age or infertility associated disorders (e.g. endometriosis, PCOS). The rate of vitamin D deficiency among women with impaired fertility is alarming. Prospective studies are pressingly needed to confirm a causal relationship and to investigate the potential therapeutic benefits of vitamin D supplementation in this population.

The gender gap: discrepant human T-cell reconstitution after cord blood stem cell transplantation in humanized female and male mice

The purpose of the study was to provide empirical evidence about the reporting of methodology to address missing outcome data and the acknowledgement of their impact in Cochrane systematic reviews in the mental health field.Systematic reviews published in the Cochrane Database of Systematic Reviews after January 1, 2009 by three Cochrane Review Groups relating to mental health were included.One hundred ninety systematic reviews were considered. Missing outcome data were present in at least one included study in 175 systematic reviews. Of these 175 systematic reviews, 147 (84%) accounted for missing outcome data by considering a relevant primary or secondary outcome (e.g., dropout). Missing outcome data implications were reported only in 61 (35%) systematic reviews and primarily in the discussion section by commenting on the amount of the missing outcome data. One hundred forty eligible meta-analyses with missing data were scrutinized. Seventy-nine (56%) of them had studies with total dropout rate between 10 and 30%. One hundred nine (78%) meta-analyses reported to have performed intention-to-treat analysis by including trials with imputed outcome data. Sensitivity analysis for incomplete outcome data was implemented in less than 20% of the meta-analyses.Reporting of the techniques for handling missing outcome data and their implications in the findings of the systematic reviews are suboptimal.

Systematic reviews of well-designed trials constitute a high level of scientific evidence and are important for medical decision making. Meta-analysis facilitates integration of the evidence using a transparent and systematic approach, leading to a broader interpretation of treatment effectiveness and safety than can be attained from individual studies. Traditional meta-analyses are limited to comparing just 2 interventions concurrently and cannot combine evidence concerning multiple treatments. A relatively recent extension of the traditional meta-analytical approach is network meta-analysis, which allows, under certain assumptions, the quantitative synthesis of all evidence under a unified framework and across a network of all eligible trials. Network meta-analysis combines evidence from direct and indirect information via common comparators; interventions can therefore be ranked in terms of the analyzed outcome. In this article, the network meta-analysis approach is introduced in a nontechnical manner using a worked example on the treatment effectiveness of conventional and self-ligating appliances.

Summary Background Conventional meta-analyses have shown inconsistent results for efficacy of pharmacological treatments for acute mania. We did a multiple-treatments meta-analysis, which accounted for both direct and indirect comparisons, to assess the effects of all antimanic drugs. Methods We systematically reviewed 68 randomised controlled trials (16 073 participants) from Jan 1, 1980, to Nov 25, 2010, which compared any of the following pharmacological drugs at therapeutic dose range for the treatment of acute mania in adults: aripiprazole, asenapine, carbamazepine, valproate, gabapentin, haloperidol, lamotrigine, lithium, olanzapine, quetiapine, risperidone, topiramate, and ziprasidone. The main outcomes were the mean change on mania rating scales and the number of patients who dropped out of the allocated treatment at 3 weeks. Analysis was done by intention to treat. Findings Haloperidol (standardised mean difference [SMD] −0·56 [95% CI −0·69 to −0·43]), risperidone (–0·50 [–0·63 to −0·38), olanzapine (–0·43 [–0·54 to −0·32], lithium (–0·37 [–0·63 to −0·11]), quetiapine (–0·37 [–0·51 to −0·23]), aripiprazole (–0·37 [–0·51 to −0·23]), carbamazepine (–0·36 [–0·60 to −0·11], asenapine (–0·30 [–0·53 to −0·07]), valproate (–0·20 [–0·37 to −0·04]), and ziprasidone (–0·20 [–0·37 to −0·03]) were significantly more effective than placebo, whereas gabapentin, lamotrigine, and topiramate were not. Haloperidol had the highest number of significant differences and was significantly more effective than lithium (SMD −0·19 [95% CI −0·36 to −0·01]), quetiapine (–0·19 [–0·37 to 0·01]), aripiprazole (–0·19 [–0·36 to −0·02]), carbamazepine (–0·20 [–0·36 to −0·01]), asenapine (–0·26 [–0·52 to 0·01]), valproate (–0·36 [–0·56 to −0·15]), ziprasidone −0·36 [–0·56 to −0·15]), lamotrigine (–0·48 [–0·77 to −0·19]), topiramate (–0·63 [–0·84 to −0·43]), and gabapentin (–0·88 [−1·40 to −0·36]). Risperidone and olanzapine had a very similar profile of comparative efficacy, being more effective than valproate, ziprasidone, lamotrigine, topiramate, and gabapentin. Olanzapine, risperidone, and quetiapine led to significantly fewer discontinuations than did lithium, lamotrigine, placebo, topiramate, and gabapentin. Interpretation Overall, antipsychotic drugs were significantly more effective than mood stabilisers. Risperidone, olanzapine, and haloperidol should be considered as among the best of the available options for the treatment of manic episodes. These results should be considered in the development of clinical practice guidelines. Funding None.

Importance There is debate about the effectiveness of psychiatric treatments and whether pharmacotherapy or psychotherapy should be primarily used. Objectives To perform a systematic overview on the efficacy of pharmacotherapies and psychotherapies for major psychiatric disorders and to compare the quality of pharmacotherapy and psychotherapy trials. Evidence Review We searched MEDLINE, EMBASE, PsycINFO, and the Cochrane Library (April 2012, with no time or language limit) for systematic reviews on pharmacotherapy or psychotherapy vs placebo, pharmacotherapy vs psychotherapy, and their combination vs either modality alone. Two reviewers independently selected the meta-analyses and extracted efficacy effect sizes. We assessed the quality of the individual trials included in the pharmacotherapy and psychotherapy meta-analyses with the Cochrane risk of bias tool. Findings The search yielded 45 233 results. We included 61 meta-analyses on 21 psychiatric disorders, which contained 852 individual trials and 137 126 participants. The mean effect size of the meta-analyses was medium (mean, 0.50; 95% CI, 0.41-0.59). Effect sizes of psychotherapies vs placebo tended to be higher than those of medication, but direct comparisons, albeit usually based on few trials, did not reveal consistent differences. Individual pharmacotherapy trials were more likely to have large sample sizes, blinding, control groups, and intention-to-treat analyses. In contrast, psychotherapy trials had lower dropout rates and provided follow-up data. In psychotherapy studies, wait-list designs showed larger effects than did comparisons with placebo. Conclusions and Relevance Many pharmacotherapies and psychotherapies are effective, but there is a lot of room for improvement. Because of the multiple differences in the methods used in pharmacotherapy and psychotherapy trials, indirect comparisons of their effect sizes compared with placebo or no treatment are problematic. Well-designed direct comparisons, which are scarce, need public funding. Because patients often benefit from both forms of therapy, research should also focus on how both modalities can be best combined to maximize synergy rather than debate the use of one treatment over the other.