Extensions and applications of generalized linear mixed models for network meta-analysis of randomized controlled trials

Network meta-analyses of published clinical trials has received increased attention over the past years with some meta-analytic publications having had a big impact on the cost-benefit assessment of important drugs. Much of the research has been based on Bayesian analysis using so called base-line contrast model. The research in network meta-analysis methodology has in parts been isolated from other fields of mathematical statistics and is lacking an integrative framework clearly separating statistical models and assumptions, inferential principles, and computational algorithms. The very extensive past research on ANOVA and MANOVA of un- balanced designs, variance component models, generalised linear models with fixed and/or random effects, provides a wealth of useful approaches and insights. These models are especially common in agricultural statistics and this thesis extended the use of the general statistical methods mainly applied in agricultural statistics to applications of network meta-analysis of clinical trials. The methods were applied to four different research problems in separate manuscripts. The first manuscript was based on a simulated case (based on real example) where some of the trials provided individual patient data and some only aggregated data. The outcome type considered was continuous normally distributed data. This manuscript provides models for jointly model the individual patient data and aggregated data. It was also explored how much information is lost if data is aggregated and how to quantify the amount of lost information. The second manuscript was based a real life dataset with pain medications used in acute postoperative pain. The outcome of interest was binomial, whether a subject experienced pain relief or not. The dataset used for NMA included 261 trials with 52 different treatment and dose combinations, making it extraordinarily rich and large network. The third manuscript developed methods for a case of time-to-event-outcome extracted from published Kaplan-Meier curves of survival analyses. This re-generated individual patient data was then used to model and compare the Kaplan-Meier curves and hazards of different treatments. The fourth manuscript of the thesis was tackling the problem of between-trial variance estimation for a specific method of Hartung-Knapp in classical two-treatment meta-analysis. The main finding of the paper was that in some cases random effect meta-analysis using Hartung-Knapp method may yield shorter confidence intervals for combined treatment effect than fixed effect meta-analysis and therefore the recommendation is to always compare results from Hartung-Knapp method with fixed effect meta-analysis. This thesis explored and developed the use of generalized linear mixed models in a setting of network meta-analysis of randomized clinical trials. In practice the most popular analysis method in the field of network meta-analysis has been the baseline contrast model which is usually fitted in a Bayesian framework. The baseline contrast model and Bayesian estimation provides great flexibility, but also come with some unnecessary complications for certain types of analyses. This thesis showed how methods originally developed and extensively used in agricultural research can be used in other field providing efficient calculation, estimation, and inference. Some of the examples used in this thesis arose from analyses needed for real applications in drug development and were directly used in medical research.  In den letzten Jahren haben Netzwerk-Meta-Analysen von publizierten Ergebnissen klinischer Studien viel Aufmerksamkeit erhalten und die Kosten-Nutzen-Einschätzung wichtiger pharmazeutischer Präparate in erheblichem Umfang beeinflusst. Ein Großteil der methodischen Forschung zur Meta-Analyse konzentrierte sich dabei auf Bayessche Methoden im sogenannten Baseline-Contrast-Modell. Diese methodischen Untersuchungen haben z.T. losgelöst von anderen Bereichen der mathematischen Statistik stattgefunden. Daher fehlte ein integrativer Rahmen, welcher mathematische Modelle und Annahmen, Prinzipien der Inferenz und Algorithmen zur Ermittlung von Effektschätzungen klar voneinander trennte. Die sehr umfangreichen Erkenntnisse zur Varianzanalyse (ANOVA und MANOVA) unbalanzierter Versuchsanordnungen, Varianzkomponentenmodellen sowie generalisierten linearen Modellen mit festen und zufälligen Effekten, welche in der Vergangenheit, nicht zuletzt im Bereich der Agrarwissenschaften, erlangt wurden, sind auch für die Methodik der Meta-Analyse sehr nützlich. Diese Arbeit erweitert die Nutzung solcher Methoden auf die Netzwerk-Meta-Analyse klinischer Studien. Die Anwendung dieser Methoden wird in vier Manuskripten dieser kumulativen Thesis dargestellt. Im ersten Manuskript wird eine Situation untersucht, bei der für einen Teil der untersuchten klinischen Studien individuelle Patientendaten (IPD) vorliegen, für einen anderen Teil indes nur aggregierte Daten (AD). Das Manuskript stellt Modelle vor, welche sich für die gemeinsame Analyse solcher Daten eignen. Es wird angenommen, dass die Daten Normalverteilungen entstammen. Die Daten wurden basierend auf realen Studiendaten simuliert. Das Manuskript untersucht, wieviel Information durch die Datenaggregation verloren geht und wie dieser Informationsverlust quantifiziert werden kann. Das zweite Manuskript untersucht einen Datensatz aus 261 klinischen Studien, in denen insgesamt 52 verschiedene Behandlungen gegen akute postoperative Schmerzen geprüft wurden. Die Zielgröße ist binär und hält fest, ob Schmerzlinderung erzielt wurde oder nicht. Aufgrund der vielen Studien und Behandlungen liegt hier ein aussergewöhnlich umfangreiches und komplexes Netzwerk vor. Im dritten Manuskript werden Methoden zur Analyse von Überlebenszeitdaten vorgestellt. Die Daten wurden mithilfe von Softwaretools aus publizierten Kaplan-Meier-Kurven extrahiert. Die so gewonnenen individuellen Patientendaten wurden benutzt, um die Überlebenskurven zu modellieren und die Hazardraten verschiedener Behandlungen zu vergleichen. Das vierte Manuskript betrachtet einen speziellen Aspekt der Inter-Studien-Varianzschätzung in der klassischen Meta-Analyse mit zwei Behandlungsarmen. Das Hauptergebnis dieser Untersuchung ist, dass die sogenannte Hartung-Knapp-Methode in Modellen mit zufälligen Effekten in bestimmten Fällen zu kürzeren Konfidenzintervallen für die kombinierte Behandlungseffektschätzung führen kann als die entsprechende Schätzung in einem Modell mit festen Effekten. Daher wird empfohlen, in konkreten Analysen beide Methoden zu verwenden und die Ergebnisse zu vergleichen. Übergreifendes Thema dieser Thesis ist die Untersuchung generalisierter linearer gemischter Modelle für Netzwerk-Meta-Analysen klinischer Studien. In der Praxis ist in diesem Bereich das Baseline-Kontrast-Modell mit Bayesschen Effektschätzungen das populärste Modell. Dieses Modell und die Methode der Bayes-Schätzung erlauben hohe Flexibilität, aber in manchen Fällen verkomplizieren sie die Analyse auf unnötige Weise. Diese Arbeit zeigt, wie Methoden, die ursprünglich in den Agrarwissenschaften entwickelt wurden und ausgiebig genutzt werden, auch für die Meta-Analyse klinischer Studien effiziente Schätz- und Inferenzmethoden zur Verfügung stellen. Einige der Beispiele in dieser Arbeit sind durch Anwendungen in der Medikamentenentwicklung motiviert und wurden bereits in konkreten medizinischen Forschungsvorhaben eingesetzt

Skinnets vikt och skinnets längd : ger ett djur som väger mycket också ett stort och högklassigt skinn?

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Nahkontapaino ja nahan pituus : saadaanko painavasta eläimestä myös iso ja laadukas nahka?

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Uppleva och göra : en studie i att förbättra förståelsen för fotosyntesen genom ett dramatiserande lärande

Validerat; 20101217 (root

Non-proportional hazards in network meta-analysis: efficient strategies for model building and analysis

Objectives: To develop efficient approaches for fitting network meta-analysis (NMA) models with time-varying hazard ratios (such as fractional polynomials and piecewise constant models) to allow practitioners to investigate a broad range of models rapidly and to achieve a more robust and comprehensive model selection strategy. Methods: We reformulated the fractional polynomial and piecewise constant NMA models using analysis of variance–like parameterization. With this approach, both models are expressed as generalized linear models (GLMs) with time-varying covariates. Such models can be fitted efficiently with standard frequentist techniques. We applied our approach to the example data from the study by Jansen et al, in which fractional polynomial NMA models were introduced. Results: Fitting frequentist fixed-effect NMAs for a large initial set of candidate models took less than 1 second with standard GLM routines. This allowed for model selection from a large range of hazard ratio structures by comparing a set of criteria including Akaike information criterion/Bayesian information criterion, visual inspection of goodness-of-fit, and long-term extrapolations. The “best” models were then refitted in a Bayesian framework. Estimates agreed very closely. Conclusions: NMA models with time-varying hazard ratios can be explored efficiently with a stepwise approach. A frequentist fixed-effect framework enables rapid exploration of different models. The best model can then be assessed further in a Bayesian framework to capture and propagate uncertainty for decision-making

Validity and reliability of the Fatigue Severity Scale in Finnish multiple sclerosis patients

BackgroundFatigue is one of the most debilitating symptoms in multiple sclerosis (MS) considerably interfering with patients’ daily functioning. Both researchers and clinicians need psychometrically robust methods to evaluate fatigue in MS.ObjectivesThe objective of this study was (i) to evaluate the psychometric properties of the Finnish version of the Fatigue Severity Scale (FSS) and (ii) to describe the results among patients with MS.MethodsIn total, 553 patients with MS (mean age, 53.8 years; standard deviation [SD], 11.4; 79% women: mean patient-defined disease severity, Expanded Disability Status Scale [EDSS] 4.0, SD, 2.5) completed the self-administered questionnaires including the FSS. A standard procedure was used for the translation of the FSS.ResultsThe mean (SD) score for the FSS was 4.5 (1.7); in 65% of the patients, the score was ≥4.0. The data quality of the FSS was excellent, with 99.6% of computable scale scores. Floor and ceiling effects were minimal. The FSS showed high internal consistency (Cronbach's alpha, 0.95). Unidimensionality was supported based on confirmatory factor analysis with the comparative fit index being 0.94. The FSS showed moderate/high correlations with the perceived burden of the disease, quality of life and disease severity, whereas, age or gender did not have a significant effect on the FSS score.ConclusionsThe Finnish version of the FSS showed satisfactory reliability and validity and thus can be regarded as a feasible measure of self-reported fatigue.</div

Improvement of Signs and Symptoms of Nonradiographic Axial Spondyloarthritis in Patients Treated With Secukinumab: Primary Results of a Randomized, Placebo-Controlled Phase III Study

Objective: To report the primary (1-year) results from PREVENT, the first phase III study evaluating secukinumab in patients with active nonradiographic axial spondyloarthritis (SpA). Methods: A total of 555 patients were randomized (1:1:1) to receive subcutaneous secukinumab 150 mg with a loading dose (loading dose [LD] group), secukinumab 150 mg without a loading dose (non–loading dose [NL] group), or placebo weekly and then every 4 weeks starting at week 4. The NL group received placebo at weeks 1, 2, and 3 to maintain blinding. Switch to open-label secukinumab or standard of care was permitted after week 20. The study had 2 independent analysis plans, per European Union and non-US (plan A; week 16) and US (plan B; week 52) regulatory requirements. The primary end point was 40% improvement in disease activity according to the Assessment of SpondyloArthritis international Society (ASAS40) criteria at week 16 (in the LD group) and at week 52 (in the NL group) in tumor necrosis factor inhibitor (TNFi)–naive patients. Safety analyses included all patients who received ≥1 dose of study treatment. Results: Overall, 481 patients completed 52 weeks of treatment, including 84.3% (156 of 185) in the LD group, 89.7% (165 of 184) in the NL group, and 86.0% (160 of 186) in the placebo group. The proportion of patients who switched to open-label or standard of care between weeks 20 and 48 was 50.8% in the LD group, 47.3% in the NL group, and 64.0% in the placebo group. Both primary and all secondary end points were met at week 16. The proportion of TNFi-naive patients who met ASAS40 was significantly higher for LD at week 16 (41.5%) and NL at week 52 (39.8%) versus placebo (29.2% at week 16 and 19.9% at week 52; both P < 0.05). No new safety findings were reported. Conclusion: Our findings indicate that secukinumab 150 mg provides significant and sustained improvement in signs and symptoms of nonradiographic axial SpA through 52 weeks. Safety was consistent with previous reports

Secukinumab in non-radiographic axial spondyloarthritis : subgroup analysis based on key baseline characteristics from a randomized phase III study, PREVENT

Background: To investigate the efficacy of secukinumab in patients with active non-radiographic axial spondyloarthritis (nr-axSpA) grouped by disease activity as assessed by C-reactive protein (CRP) levels and/or magnetic resonance imaging (MRI) scores, human leukocyte antigen (HLA)-B27 status, and sex. Methods: The phase III PREVENT study randomized (1:1:1) 555 patients to receive subcutaneous secukinumab 150 mg with (LD) or without (NL) loading dose or placebo weekly, followed by every 4 weeks starting at week 4. Here, we report the results of a post hoc analysis reporting the efficacy outcomes (pooled secukinumab) to 16 weeks by CRP, MRI, HLA-B27, and sex. Results: Efficacy differences between the secukinumab and the placebo groups were highest in the CRP+, MRI+, HLA-B27+, and male subgroups, particularly for Ankylosing Spondylitis Disease Activity Score-CRP inactive disease and Assessment of SpondyloArthritis international Society (ASAS) partial remission outcomes. ASAS40 response rates in the CRP+/MRI+ subgroup was 52.3% (secukinumab) versus 21.8% (placebo; P < 0.0001) at week 16. ASAS40 response rates (secukinumab versus placebo) were 43.9% versus 32.6% in HLA-B27+, 32.7% versus 16.4% in HLA-B27 - subgroups, 51.2% versus 30.8% in male, and 31.7% versus 25.3% in female patients, respectively. Conclusions: Secukinumab improved the signs and symptoms of nr-axSpA across patients grouped by CRP (+/-) and/or MRI (+/-) status, HLA-B27 (+/-) status, and sex. The highest treatment differences between secukinumab and placebo were observed in patients with both elevated CRP and evidence of sacroiliitis on MRI. Treatment difference was minimal between HLA-B27 (+) and (-) subgroups. Male patients had higher relative responses than female patients

Schwann Cell Coculture Improves the Therapeutic Effect of Bone Marrow Stromal Cells on Recovery in Spinal Cord-Injured Mice

Studies of bone marrow stromal cells (MSCs) transplanted into the spinal cord-injured rat give mixed results: some groups report improved locomotor recovery while others only demonstrate improved histological appearance of the lesion. These studies show no clear correlation between neurological improvements and MSC survival. We examined whether MSC survival in the injured spinal cord could be enhanced by closely matching donor and recipient mice for genetic background and marker gene expression and whether exposure of MSCs to a neural environment (Schwann cells) prior to transplantation would improve their survival or therapeutic effects. Mice underwent a clip compression spinal cord injury at the fourth thoracic level and cell transplantation 7 days later. Despite genetic matching of donors and recipients, MSC survival in the injured spinal cord was very poor (~1%). However, we noted improved locomotor recovery accompanied by improved histopathological appearance of the lesion in mice receiving MSC grafts. These mice had more white and gray matter sparing, laminin expression, Schwann cell infiltration, and preservation of neurofilament and 5-HT-positive fibers at and below the lesion. There was also decreased collagen and chondroitin sulphate proteoglycan deposition in the scar and macrophage activation in mice that received the MSC grafts. The Schwann cell cocultured MSCs had greater effects than untreated MSCs on all these indices of recovery. Analyses of chemokine and cytokine expression revealed that MSC/Schwann cell cocultures produced far less MCP-1 and IL-6 than MSCs or Schwann cells cultured alone. Thus, transplanted MSCs may improve recovery in spinal cord-injured mice through immunosuppressive effects that can be enhanced by a Schwann cell coculturing step. These results indicate that the temporary presence of MSCs in the injured cord is sufficient to alter the cascade of pathological events that normally occurs after spinal cord injury, generating a microenvironment that favors improved recovery

Functional Brachyury Binding Sites Establish a Temporal Read-out of Gene Expression in the Ciona Notochord

The appearance of the notochord represented a milestone in Deuterostome evolution. The notochord is necessary for the development of the chordate body plan and for the formation of the vertebral column and numerous organs. It is known that the transcription factor Brachyury is required for notochord formation in all chordates, and that it controls transcription of a large number of target genes. However, studies of the structure of the cis-regulatory modules (CRMs) through which this control is exerted are complicated in vertebrates by the genomic complexity and the pan-mesodermal expression territory of Brachyury. We used the ascidian Ciona, in which the single-copy Brachyury is notochord-specific and CRMs are easily identifiable, to carry out a systematic characterization of Brachyury-downstream notochord CRMs. We found that Ciona Brachyury (Ci-Bra) controls most of its targets directly, through non-palindromic binding sites that function either synergistically or individually to activate early- and middle-onset genes, respectively, while late-onset target CRMs are controlled indirectly, via transcriptional intermediaries. These results illustrate how a transcriptional regulator can efficiently shape a shallow gene regulatory network into a multi-tiered transcriptional output, and provide insights into the mechanisms that establish temporal read-outs of gene expression in a fast-developing chordate embryo