There is limited information on the association between participants' clinical status or trajectories and missing data in electronic monitoring studies of bipolar disorder (BD). We collected self-ratings scales and sensor data in 145 adults with BD. Using a new metric, Missing Data Ratio (MDR), we assessed missing self-rating data and sensor data monitoring activity and sleep. Missing data were lowest for participants in the midst of a depressive episode, intermediate for participants with subsyndromal symptoms, and highest for participants who were euthymic. Over a mean ± SD follow-up of 246 ± 181 days, missing data remained unchanged for participants whose clinical status did not change throughout the study (i.e., those who entered the study in a depressive episode and did not improve, or those who entered the study euthymic and remained euthymic). Conversely, when participants' clinical status changed during the study (e.g., those who entered the study euthymic and experienced the occurrence of a depressive episode), missing data for self-rating scales increased, but not for sensor data. Overall missing data were associated with participants' clinical status and its changes, suggesting that these are not missing at random.

• MeSH
• Bipolar Disorder * epidemiology   MeSH
• Adult MeSH
• Middle Aged MeSH
• Humans MeSH
• Longitudinal Studies MeSH
• Young Adult MeSH
• Self Report MeSH
• Check Tag
• Adult MeSH
• Middle Aged MeSH
• Humans MeSH
• Young Adult MeSH
• Male MeSH
• Female MeSH
• Publication type
• Journal Article MeSH

BACKGROUND: Magnetic resonance spectroscopy provides metabolic information about living tissues in a non-invasive way. However, there are only few multi-centre clinical studies, mostly performed on a single scanner model or data format, as there is no flexible way of documenting and exchanging processed magnetic resonance spectroscopy data in digital format. This is because the DICOM standard for spectroscopy deals with unprocessed data. This paper proposes a plugin tool developed for jMRUI, namely jMRUI2XML, to tackle the latter limitation. jMRUI is a software tool for magnetic resonance spectroscopy data processing that is widely used in the magnetic resonance spectroscopy community and has evolved into a plugin platform allowing for implementation of novel features. RESULTS: jMRUI2XML is a Java solution that facilitates common preprocessing of magnetic resonance spectroscopy data across multiple scanners. Its main characteristics are: 1) it automates magnetic resonance spectroscopy preprocessing, and 2) it can be a platform for outputting exchangeable magnetic resonance spectroscopy data. The plugin works with any kind of data that can be opened by jMRUI and outputs in extensible markup language format. Data processing templates can be generated and saved for later use. The output format opens the way for easy data sharing- due to the documentation of the preprocessing parameters and the intrinsic anonymization--for example for performing pattern recognition analysis on multicentre/multi-manufacturer magnetic resonance spectroscopy data. CONCLUSIONS: jMRUI2XML provides a self-contained and self-descriptive format accounting for the most relevant information needed for exchanging magnetic resonance spectroscopy data in digital form, as well as for automating its processing. This allows for tracking the procedures the data has undergone, which makes the proposed tool especially useful when performing pattern recognition analysis. Moreover, this work constitutes a first proposal for a minimum amount of information that should accompany any magnetic resonance processed spectrum, towards the goal of achieving better transferability of magnetic resonance spectroscopy studies.

• MeSH
• Algorithms * MeSH
• Electronic Data Processing statistics & numerical data   MeSH
• Humans MeSH
• Magnetic Resonance Spectroscopy methods   MeSH
• Magnetic Resonance Imaging methods   MeSH
• Image Processing, Computer-Assisted methods   MeSH
• Software * MeSH
• Check Tag
• Humans MeSH
• Publication type
• Journal Article MeSH
• Research Support, Non-U.S. Gov't MeSH

• MeSH
• Data Anonymization MeSH
• Disease Outbreaks MeSH
• Data Collection MeSH
• Ebolavirus MeSH

• Conspectus
• Veřejné zdraví a hygiena
• NML Fields
• infekční lékařství
• veřejné zdravotnictví
• NML Publication type
• publikace WHO

Functional diversity (FD) is an important component of biodiversity that quantifies the difference in functional traits between organisms. However, FD studies are often limited by the availability of trait data and FD indices are sensitive to data gaps. The distribution of species abundance and trait data, and its transformation, may further affect the accuracy of indices when data is incomplete. Using an existing approach, we simulated the effects of missing trait data by gradually removing data from a plant, an ant and a bird community dataset (12, 59, and 8 plots containing 62, 297 and 238 species respectively). We ranked plots by FD values calculated from full datasets and then from our increasingly incomplete datasets and compared the ranking between the original and virtually reduced datasets to assess the accuracy of FD indices when used on datasets with increasingly missing data. Finally, we tested the accuracy of FD indices with and without data transformation, and the effect of missing trait data per plot or per the whole pool of species. FD indices became less accurate as the amount of missing data increased, with the loss of accuracy depending on the index. But, where transformation improved the normality of the trait data, FD values from incomplete datasets were more accurate than before transformation. The distribution of data and its transformation are therefore as important as data completeness and can even mitigate the effect of missing data. Since the effect of missing trait values pool-wise or plot-wise depends on the data distribution, the method should be decided case by case. Data distribution and data transformation should be given more careful consideration when designing, analysing and interpreting FD studies, especially where trait data are missing. To this end, we provide the R package "traitor" to facilitate assessments of missing trait data.

• MeSH
• Biodiversity * MeSH
• Species Specificity MeSH
• Quantitative Trait, Heritable * MeSH
• Publication type
• Journal Article MeSH
• Research Support, Non-U.S. Gov't MeSH

OBJECTIVES: We aimed to compare various methods for imputing disease activity in longitudinally collected observational data of patients with axial spondyloarthritis (axSpA). METHODS: We conducted a simulation study on data from 8583 axSpA patients from ten European registries. Disease activity was assessed by the Axial Spondyloarthritis Disease Activity Score (ASDAS) and the corresponding low disease activity (LDA; ASDAS<2.1) state at baseline, 6 and 12 months. We focused on cross-sectional methods which impute missing values of an individual at a particular time point based on the available information from other individuals at that time point. We applied nine single and five multiple imputation methods, covering mean, regression and hot deck methods. The performance of each imputation method was evaluated via relative bias and coverage of 95% confidence intervals for the mean ASDAS and the derived proportion of patients in LDA. RESULTS: Hot deck imputation methods outperformed mean and regression methods, particularly when assessing LDA. Multiple imputation procedures provided better coverage than the corresponding single imputation ones. However, none of the evaluated methods produced unbiased estimates with adequate coverage across all time points, with performance for missing baseline data being worse than for missing follow-up data. Predictive mean and weighted predictive mean hot deck imputation procedures consistently provided results with low bias. CONCLUSIONS: This study contributes to the available methods for imputing disease activity in observational research. Hot deck imputation using predictive mean matching exhibited the highest robustness and is thus our suggested approach.

• MeSH
• Axial Spondyloarthritis * diagnosis   epidemiology   MeSH
• Adult MeSH
• Data Interpretation, Statistical MeSH
• Humans MeSH
• Longitudinal Studies MeSH
• Observational Studies as Topic * MeSH
• Cross-Sectional Studies MeSH
• Registries MeSH
• Spondylarthritis diagnosis   MeSH
• Severity of Illness Index * MeSH
• Check Tag
• Adult MeSH
• Humans MeSH
• Male MeSH
• Female MeSH
• Publication type
• Journal Article MeSH
• Geographicals
• Europe MeSH

Durvalumab představuje monoklonální protilátku, která stimuluje imunitní systém v rozpoznávání a usmrcování nádorových buněk. Durvalumab prokázal svoji účinnost i bezpečnost v léčbě lokálně pokročilého neresekabilního nemalobuněčného plicního karcinomu po kurativní chemoradioterapii jako udržovací léčba na základě výsledků klinické studie PACIFIC, jejíž aktualizovaná data byla publikována v tomto roce. Současně získal durvalumab registraci pro léčbu generalizovaného malobuněčného plicního karcinomu s chemoterapií a následně jako monoterapie na základě studie CASPIAN, jejíž aktualizovaná data jsou opět předmětem tohoto sdělení. Úhrada z veřejného zdravotního pojištění v této druhé indikaci v tuto chvíli bohužel chybí. Současně jsou prezentovány povzbudivé výsledky pacienta s malobuněčným plicním karcinomem léčeného durvalumabem v našem komplexním onkologickém centru.

Durvalumab represents a monoclonal antibody which stimulates the immune system in the detection and killing of the tumor cells. Durvalumab has proven safety and effectivity in the treatment of the locally advanced non-resectable non-small cell lung cancer after curative chemoradiotherapy as maintenance therapy based on the results of the clinical trial PACIFIC. The updated results of this trial were published this year. At the same time durvalumab gained registration for the treatment of the metastatic small cell lung cancer with chemotherapy and as maintenance therapy based on the results of the CASPIAN trial, which updated results are again presented in this paper. Unfortunately the health insurance reimbursement for the second mentioned indication is missing so far. There is also presented very promising case report with patient with small cell lung cancer treated with durvalumab.

• Keywords
• durvalumab, studie PACIFIC, studie CASPIAN,
• MeSH
• Clinical Trials, Phase III as Topic MeSH
• Middle Aged MeSH
• Humans MeSH
• Small Cell Lung Carcinoma diagnostic imaging   diagnosis   drug therapy   MeSH
• Antibodies, Monoclonal * therapeutic use   MeSH
• Carcinoma, Non-Small-Cell Lung * diagnostic imaging   diagnosis   drug therapy   MeSH
• Tomography, X-Ray Computed MeSH
• Randomized Controlled Trials as Topic MeSH
• Check Tag
• Middle Aged MeSH
• Humans MeSH
• Male MeSH

Pro léčbu revmatoidní artritidy je k dispozici pět inhibitorů TNF-α. Jedná se o léky účinné, které mají dlouhodobě prokázaný dobrý bezpečnostní profil. Certolizumab pegol (CZP) představuje novou pegylovanou humanizovanou protilátku proti TNF-α, která je charakterizována chyběním Fc fragmentu. Výhodami CZP jsou rychlý nástup účinku a nízké riziko vzniku reakce v místě vpichu. Určitou výhodu může představovat také snížené riziko přestupu CZP přes placentu během gravidity. Výsledky zaslepených fází a dlouhodobých extenzí klinických studií podporují dobrou účinnost a bezpečnost CZP v monoterapii a převážně v kombinaci s konvenčními chorobu modifikujícími antirevmatickými léky u pacientů se středně až vysoce aktivní revmatoidní artritidou. Nedávno byl CZP schválen pro léčbu psoriatické artritidy a axiální spondyloartritidy. V této přehledové práci jsou rozebrána klinická hodnocení a jejich dlouhodobé výsledky s ohledem na účinnost a bezpečnost CZP v indikaci revmatoidní artritidy.

There are five TNF-α inhibitors available for the treatment of rheumatoid arthritis. These are effective drugs with good safety profile demonstrated over long-term. Certolizumab pegol (CZP) is a new pegylated humanized anti-TNF-α antibody characterized by missing Fc fragment. Advantages of CZP include rapid onset of action and low risk of injection site reaction. A potential advantage may also be the reduced risk of placental transfer of CZP during pregnancy. Results from blinded phases and long-term extensions of clinical studies support good efficacy and safety of CZP in monotherapy, and predominantly in combination with conventional disease-modifying anti- -rheumatic drugs in patients with moderate to high-activity rheumatoid arthritis. CZP has recently been approved for the treatment of psoriatic arthritis and axial spondyloarthritis. This overview analyses clinical trials and their long-term results focusing on the efficacy and safety of CZP in the indication of rheumatoid arthritis.

• MeSH
• Antirheumatic Agents * administration & dosage   MeSH
• Biological Therapy methods   MeSH
• Drug Evaluation MeSH
• Antibodies, Monoclonal, Humanized administration & dosage   adverse effects   MeSH
• Immunoglobulin Fab Fragments * administration & dosage   pharmacology   MeSH
• Injections, Subcutaneous MeSH
• Drug Therapy, Combination MeSH
• Humans MeSH
• Methotrexate administration & dosage   MeSH
• Drug-Related Side Effects and Adverse Reactions epidemiology   etiology   MeSH
• Polyethylene Glycols therapeutic use   MeSH
• Arthritis, Rheumatoid * diagnosis   drug therapy   MeSH
• Treatment Outcome MeSH
• Dose-Response Relationship, Drug * MeSH
• Check Tag
• Humans MeSH
• Publication type
• Review MeSH

BACKGROUND AND OBJECTIVES: The pharmacokinetics of polyethylene glycol-conjugated asparaginase (PEG-ASNase) are characterized by an increase in elimination over time, a marked increase in ASNase activity levels from induction to reinduction, and high inter- and intraindividual variability. A population pharmacokinetic (PopPK) model is required to estimate individual dose intensity, despite gaps in monitoring compliance. METHODS: In the AIEOP-BFM ALL 2009 trial, two PEG-ASNase administrations (2500 U/m2 intravenously) during induction (14-day interval) and one administration during reinduction were administered in children with acute lymphoblastic leukemia. ASNase activity levels were monitored weekly. A PopPK model was used for covariate modeling and external validation. The predictivity of the model in case of missing data was tested for observations, as well as for the derived parameters of the area under the concentration time curve (AUC0-∞) and time above different thresholds. RESULTS: Compared to the first administration in induction (1374 patients, 6069 samples), the initial clearance and volume of distribution decreased by 11.0% and 15.9%, respectively, during the second administration during induction and by 41.2% and 28.4% during reinduction. Furthermore, the initial clearance linearly increased for children aged > 8 years and was 7.1% lower for females. The model was successfully externally validated (1253 patients, 5523 samples). In case of missing data, > 52% of the predictions for observations and > 82% for derived parameters were within ± 20% of the nominal value. CONCLUSION: A PopPK model that describes the complex pharmacokinetics of PEG-ASNase was successfully externally validated. AUC0-∞ or time above different thresholds, which are parameters describing dose intensity, can be estimated with high predictivity, despite missing data. ( www.clinicaltrials.gov , NCT01117441, first submitted date: May 3, 2010).

• MeSH
• Precursor Cell Lymphoblastic Leukemia-Lymphoma drug therapy   MeSH
• Asparaginase administration & dosage   pharmacokinetics   MeSH
• Models, Biological * MeSH
• Child MeSH
• Infant MeSH
• Humans MeSH
• Adolescent MeSH
• Area Under Curve MeSH
• Polyethylene Glycols administration & dosage   pharmacokinetics   MeSH
• Child, Preschool MeSH
• Antineoplastic Agents administration & dosage   pharmacokinetics   MeSH
• Tissue Distribution MeSH
• Check Tag
• Child MeSH
• Infant MeSH
• Humans MeSH
• Adolescent MeSH
• Male MeSH
• Child, Preschool MeSH
• Female MeSH
• Publication type
• Journal Article MeSH
• Clinical Trial MeSH
• Multicenter Study MeSH
• Validation Study MeSH

Cíl studie: Analyzovat data o cyklech in vitro fertilizace – IVF – v Národním registru asistované reprodukce (NRAR). Typ studie: Retrospektivní studie. Metodika: Bylo analyzováno celkem 107 529 záznamů o všech cyklech asistované reprodukce v NRAR za roky 2007–2011 se zaměřením především na cykly IVF, a to podle standardů European IVF monitoring – Eureopean Society of Human Reproduction and Embryology (EIM ESHRE). Výsledky: V Česku je ročně přibližně 11 000–14 000 zahájených cyklů IVF. Ve shodě s všeobecnou zkušeností se výsledky léčby IVF výrazně liší podle věku žen. Úplnost dat v NRAR významně klesá se stoupající dobou od začátku cyklu, a v případě údajů o porodu nedosahuje mnohdy ani 50 %. Efektivitu IVF tedy nelze zatím hodnotit. Závěr: Počet pracovišť asistované reprodukce v Česku stále roste. Cyklů IVF (a obdobně i kryotransferů) provedených ročně v Česku a vykázaných v NRAR je přibližně setrvalý počet. Ve věkové skupině do 34 let je patrný mírný úbytek cyklů IVF, zatímco ve skupině 34–40 let mírný nárůst. Přibývá cyklů v dárcovském programu (Darování oocytů a Přijetí darovaných oocytů). Efektivita léčby metodou IVF je vzhledem k významnému podílu chybějících dat v NRAR zatím nehodnotitelná. Je zapotřebí jednak posílit zpětnou vazbu na centra ohledně zadání chybějících údajů, jednak propojit NRAR s registrem porodů a potratů ke získání těch údajů, které centra mohou získat jen obtížně.

Objective: Analysis of IVF cycles (excluding donor oocytes programs) in Czech National Assisted Reproduction Register (NRAR). Design: Retrospective study. Methods: We analyzed NRAR data from 1. 1. 2007 to 31. 12. 2011 (107 529 cycles) concerning IVF cycles, according standards of European IVF monitoring – European Society of Human Reproduction and Embryology (EIM ESHRE). Results: Yearly in Czech Republic there is 10 000–14 000 initiated IVF cycles. In agreement with common experience, IVF results differ depending the age of woman. The completeness of data in NRAR decreases significantly during the cycle course; data concerning the delivery after the cycle are missing in more than 50% of cycles in some years. So, parameters of cycle effectiveness are not possible to evaluate yet. Conclusion: Number of IVF centers in Czech Republic is still growing. Number of IVF cycles (and similarly frozen embryo transfer cycles) in Czech Republic is in general yearly very similar. In the subgroup of the age under 34, the number of cycles slightly diminishes, in the age group 34–40 increases. Number of cycles in Oocyte donation cycles and in Oocyte reception cycles is increasing. The effectiveness of IVF treatments is not possible to evaluate due to an important part of cycles with missing data concerning pregnancies and deliveries. It is necessary to stimulate centers to send missing data, but also to create the interconnection with the Deliveries register and the Abortions register, to reach data in cases, where it is really difficult to reach them by centers.

• Keywords
• IVF, efektivita,
• MeSH
• Oocyte Donation statistics & numerical data   MeSH
• Adult MeSH
• Fertilization in Vitro statistics & numerical data   MeSH
• Cryopreservation statistics & numerical data   MeSH
• Humans MeSH
• Oocyte Retrieval statistics & numerical data   MeSH
• Registries statistics & numerical data   MeSH
• Retrospective Studies MeSH
• Data Collection methods   MeSH
• Pregnancy statistics & numerical data   MeSH
• Age Distribution MeSH
• Pregnancy Outcome MeSH
• Check Tag
• Adult MeSH
• Humans MeSH
• Pregnancy statistics & numerical data   MeSH
• Female MeSH

• MeSH
• Morals * MeSH
• Religion * MeSH
• Publication type
• Letter MeSH