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2. START NOW: a cognitive behavioral skills training for adolescent girls with conduct or oppositional defiant disorder – a randomized clinical trial

Author

Stadler, Christina, primary, Freitag, Christine M., additional, Popma, Arne, additional, Nauta‐Jansen, Lucres, additional, Konrad, Kerstin, additional, Unternaehrer, Eva, additional, Ackermann, Katharina, additional, Bernhard, Anka, additional, Martinelli, Anne, additional, Oldenhof, Helena, additional, Gundlach, Malou, additional, Kohls, Gregor, additional, Prätzlich, Martin, additional, Kieser, Meinhard, additional, Limprecht, Ronald, additional, Raschle, Nora M., additional, Vriends, Noortje, additional, Trestman, Robert L., additional, Kirchner, Marietta, additional, and Kersten, Linda, additional

Published
2023
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5. The Value of Routine Intravenous Tranexamic Acid in Total Hip Arthroplasty: A Preliminary Study

Author

J. Chin, J. Blackett, D. C. Kieser, C. Frampton, and G. Hooper

Subjects
Orthopedic surgery, RD701-811
Abstract

Objective. To determine the effect on the need for transfusion when intravenous tranexamic acid (TXA) is administered intraoperatively in patients undergoing total hip arthroplasty (THA). Method. A prospective, double blinded, randomised control trial of 88 patients undergoing THA was randomly allocated to receive 1 g of intravenous TXA or normal saline on induction of anaesthesia. All patients received spinal anaesthesia. The primary outcome measure was transfusion rate, and the secondary outcomes were intraoperative blood loss, haemoglobin levels, length of hospital stay, functional scores, and thromboembolic complications. Results. 19.0% of patients given TXA required a blood transfusion, compared with 20.5% given placebo (p=0.87). Secondary outcomes included mean intraoperative blood loss, which was 536.5 ml in the TXA group and 469.8 ml in the placebo group (p=0.276). Day 1 haemoglobin levels were 108.9 g/l in the TXA group versus 104.3 g/l in the placebo group (p=0.114). Day 4 haemoglobin levels were 105.0 g/l and 99.8 g/l, respectively (p=0.130). The mean length of stay in those who received TXA was 4.3days, compared with 4.8days in those given placebo (p=0.20). The Oxford Hip Score showed a mean improvement over a 1-year period of 25.9 points in those who received TXA, compared with 26.7 points in those who received placebo (p=0.679). There were two treatment emergent adverse events: a pulmonary embolism (TXA) and a myocardial infarction (placebo). Conclusions. 1 g IV TXA administered on induction did not significantly reduce the need for blood transfusion, postoperative blood loss, functional scores, or the length of stay in patients undergoing THA. This trial is registered with ACTRN12610001065088.

Published
2020
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7. Optimal unplanned design modification in adaptive two‐stage trials

Author

Maximilian Pilz, Carolin Herrmann, Geraldine Rauch, and Meinhard Kieser

Subjects
Pharmacology, Statistics and Probability, Research Design, Sample Size, Humans, Pharmacology (medical)
Abstract

Adaptive planning of clinical trials allows modifying the entire trial design at any time point mid-course. In this paper, we consider the case when a trial-external update of the planning assumptions during the ongoing trial makes an unforeseen design adaptation necessary. We take up the idea to construct adaptive designs with defined features by solving an optimization problem and apply it to the situation of unplanned design reassessment. By using the conditional error principle, we present an approach on how to optimally modify the trial design at an unplanned interim analysis while at the same time strictly protecting the type I error rate. This linking of optimal design planning and the conditional error principle allows sound reactions to unforeseen events that make a design reassessment necessary.

Published
2022

9. A Positive Quadriceps Active Test, without the Quadriceps Being Active

Author

D. C. Kieser, E. Savage, and P. Sharplin

Subjects
Orthopedic surgery, RD701-811
Abstract

Case. A 55-year-old male with a chronic isolated grade 3 PCL injury who demonstrates a positive quadriceps active test without activating his quadriceps musculature. Conclusion. Gravity and hamstring contraction posteriorly translate the tibia into a subluxed position. Subsequent gastrocnemius contraction with the knee flexed causes an anterior tibial translation by virtue of the mass enlargement of the gastrocnemius muscular bulk, the string of a bow effect, and the anterior origin of the gastrocnemius in relation to the posterior border of the subluxed tibia aided by the normal posterior tibial slope.

Published
2019
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10. Optimization of adaptive designs with respect to a performance score

Author

Carolin Herrmann, Meinhard Kieser, Geraldine Rauch, and Maximilian Pilz

Subjects
Statistics and Probability, Research Design, Sample Size, General Medicine, Statistics, Probability and Uncertainty
Abstract

Adaptive designs are an increasingly popular method for the adaptation of design aspects in clinical trials, such as the sample size. Scoring different adaptive designs helps to make an appropriate choice among the numerous existing adaptive design methods. Several scores have been proposed to evaluate adaptive designs. Moreover, it is possible to determine optimal two-stage adaptive designs with respect to a customized objective score by solving a constrained optimization problem. In this paper, we use the conditional performance score by Herrmann et al. (2020) as the optimization criterion to derive optimal adaptive two-stage designs. We investigate variations of the original performance score, for example, by assigning different weights to the score components and by incorporating prior assumptions on the effect size. We further investigate a setting where the optimization framework is extended by a global power constraint, and additional optimization of the critical value function next to the stage-two sample size is performed. Those evaluations with respect to the sample size curves and the resulting design's performance can contribute to facilitate the score's usage in practice.

Published
2022

16. Certification of Uranium Isotope Amount Ratios in a Suite of Uranium Ore Concentrate Certified Reference Materials

Author

Celia Venchiarutti, Lu Yang, Zoltán Mester, Mostafa Fayek, Xiaolei Zhao, Ying Gao, Zsolt Varga, Juan He, Eduardo A. Gautier, Yoshiki Kimura, Juris Meija, J. D. Inglis, Csaba Tobi, Klaus Mayer, Victoria Genetti, Maria Wallenius, Ryan Sharpe, Kyle M. Samperton, Yetunde Aregbe, Joanna S. Denton, Ali El-Jaby, Andreea Elena Serban, Jung Youn Choi, Viorel Fugaru, B.B.A. Francisco, William E. Kieser, Stephan Richter, Rachel E. Lindvall, Marian Virgolici, Kenny Nadeau, José Luis Ramella, Ruoxi Zhang, Hana Seo, A.A. Reinhard, and Paola Alejandra Babay

Subjects
Waste management, Isotopes of uranium, Mc icp ms, Suite, 010401 analytical chemistry, Geology, Certification, 010403 inorganic & nuclear chemistry, certified reference materials, 01 natural sciences, 0104 chemical sciences, Uranium ore, Certified reference materials, Geochemistry and Petrology, uranium ore concentrate, Environmental science, MC-ICP-MS, TIMS, U isotope ratio
Abstract

In this study, data from thirteen laboratories from around the world are presented for a successful certification of uranium isotope ratios in uranium ore concentrate (UOC) certified reference materials from the National Research Council Canada. Different mass spectrometric measurement principles (including SF-ICP-MS, quadruple ICP-MS, TIMS, MC-ICP-MS, SIMS and AMS) and measurement procedures were employed. In general, data from all sources exhibit good consistency with TIMS and MC-ICP-MS showing superior performance. The three candidate UOC CRMs (UCLO-1, UCHI-1 and UPER-1) have natural uranium isotope ratios with certified values of 0.5304(7) × 10⁻⁴, 0.5475(2) × 10⁻⁴ and 0.5361(4) × 10⁻⁴ for n(²³⁴U)/n(²³⁸U) and 0.007 2563(13), 0.007 2563(10) and 0.007 2542(11) for n(²³⁵U)/n(²³⁸U), respectively, with expanded uncertainty (k = 2) applicable to the last digit of the value given in the parentheses. Information values for n(²³⁶U)/n(²³⁸U) in these three CRMs, measured by AMS, are also provided: 10 × 10⁻¹², 200 × 10⁻¹² and 22 × 10⁻¹². The uncertainties of the proposed certified values of uranium isotope ratios in UOC CRMs are superior to available reference materials, and the values of n(²³⁴U)/n(²³⁸U) and n(²³⁶U)/n(²³⁸U) show significant variation among the three CRMs.

Published
2021

19. Categories, components, and techniques in a modular construction of basket trials for application and further research

Author

Meinhard Kieser, Johannes Krisam, and Moritz Pohl

Subjects
Statistics and Probability, First contact, animal structures, Computer science, business.industry, General Medicine, Decision rule, In-basket test, Modular construction, Modular design, Precision medicine, Notation, Data science, body regions, nervous system, Research Design, Frequentist inference, embryonic structures, Humans, Statistics, Probability and Uncertainty, business, Medical Futility
Abstract

Basket trials have become a virulent topic in medical and statistical research during the last decade. The core idea of them is to treat patients, who express the same genetic predisposition-either personally or their disease-with the same treatment irrespective of the location of the disease. The location of the disease defines each basket and the pathway of the treatment uses the common genetic predisposition among the baskets. This opens the opportunity to share information among baskets, which can consequently increase the information of the basket-wise response with respect to the investigated treatment. This further allows dynamic decisions regarding futility and efficacy of individual baskets during the ongoing trial. Several statistical designs have been proposed on how a basket trial can be conducted and this has left an unclear situation with many options. The different designs propose different mathematical and statistical techniques, different decision rules, and also different trial purposes. This paper presents a broad overview of existing designs, categorizes them, and elaborates their similarities and differences. A uniform and consistent notation facilitates the first contact, introduction, and understanding of the statistical methodologies and techniques used in basket trials. Finally, this paper presents a modular approach for the construction of basket trials in applied medical science and forms a base for further research of basket trial designs and their techniques.

Published
2021

22. Optimal planning of adaptive two-stage designs

Author

Pilz, Maximilian, Kunzmann, Kevin, Herrmann, Carolin, Rauch, Geraldine, Kieser, Meinhard, Pilz, Maximilian [0000-0002-9685-1613], Kunzmann, Kevin [0000-0002-1140-7143], Herrmann, Carolin [0000-0003-2384-7303], Rauch, Geraldine [0000-0002-2451-1660], Kieser, Meinhard [0000-0003-2402-4333], and Apollo - University of Cambridge Repository

Subjects
Research Design, Sample Size, adaptive design, clinical trial, optimal design, sample size calculation
Abstract

Funder: RUPRECHT KARLS UNIVERSITAET HEIDELBERG ‐ Projekt DEAL, Adaptive designs are playing an increasingly important role in the planning of clinical trials. While there exists various research on the optimal determination of a two-stage design, non-optimal versions still are frequently applied in clinical research. In this article, we strive to motivate the application of optimal adaptive designs and give guidance on how to determine them. It is demonstrated that optimizing a trial design with respect to particular objective criteria can have a substantial benefit over the application of conventional adaptive sample size recalculation rules. Furthermore, we show that in many practical situations, optimal group-sequential designs show an almost negligible performance loss compared to optimal adaptive designs. Finally, we illustrate how optimal designs can be tailored to specific operational requirements by customizing the underlying optimization problem.

Published
2021

26. Optimal decision‐making in oncology development programs based on probability of success for phase <scp>III</scp> utilizing phase <scp>II</scp> / <scp>III</scp> data on response and overall survival

Author

Marietta Kirchner, Hakan Demirtas, Meinhard Kieser, Heiko Götte, and Junyuan Xiong

Subjects
Pharmacology, Statistics and Probability, Mathematical optimization, Computer science, media_common.quotation_subject, 01 natural sciences, Phase (combat), Confidence interval, Probability of success, 010104 statistics & probability, 03 medical and health sciences, 0302 clinical medicine, Sample size determination, Clinical endpoint, Pharmacology (medical), Quality (business), 030212 general & internal medicine, 0101 mathematics, Duration (project management), Optimal decision, media_common
Abstract

In clinical development, there is a trade-off between investment and level of confidence in the potential of the drug before going into phase III. Reduced investment requires the use of short-term endpoints. On new compounds, only limited information about the relationship between treatment effects of short- and long-term endpoints is usually available. Therefore, decision-making solely based on short-term endpoints does not seem desirable. Our goal is to plan an efficient development program, which uses short- and long-term endpoints data for decision-making. We found that with limited prior information and restrictions on maximum sample size, decision-making after phase II cannot be substantially improved. We follow the concept of a "phase 2+" design where after a go-to-phase-III-decision, further follow-up data from phase II are employed to make interim decisions on phase III. The program will be stopped early when additional phase II and/or available phase III data lead to a low probability of success (PoS). We utilize information from a multi-categorical short-term endpoint (response status) and a long-term endpoint (overall survival (OS)) to determine the PoS in phase III with OS as the primary endpoint. Optimal combinations of decision boundaries and time points are demonstrated in a simulation study. Our results show that the proposed second look using additional follow-up data from phase II/III improves PoS estimates compared to the first look, especially when prior data about the control arm is available. The proposed planning strategy allows a customized compromise between the quality of decision-making and program duration.

Published
2020

27. A new conditional performance score for the evaluation of adaptive group sequential designs with sample size recalculation

Author

Geraldine Rauch, Maximilian Pilz, Meinhard Kieser, and Carolin Herrmann

Subjects
Statistics and Probability, Epidemiology, Computer science, 01 natural sciences, 010104 statistics & probability, 03 medical and health sciences, 0302 clinical medicine, Interim, performance score, Statistics, 030212 general & internal medicine, 0101 mathematics, clinical trial, Interim analysis, Power (physics), sample size recalculation, Clinical Practice, Variable (computer science), Research Design, Sample size determination, Sample Size, Adaptive design, Group sequential, adaptive group-sequential design, Monte Carlo Method, 600 Technik, Medizin, angewandte Wissenschaften::610 Medizin und Gesundheit::610 Medizin und Gesundheit
Abstract

In standard clinical trial designs, the required sample size is fixed in the planning stage based on initial parameter assumptions. It is intuitive that the correct choice of the sample size is of major importance for an ethical justification of the trial. The required parameter assumptions should be based on previously published results from the literature. In clinical practice, however, historical data often do not exist or show highly variable results. Adaptive group sequential designs allow a sample size recalculation after a planned unblinded interim analysis in order to adjust the sample size during the ongoing trial. So far, there exist no unique standards to assess the performance of sample size recalculation rules. Single performance criteria commonly reported are given by the power and the average sample size; the variability of the recalculated sample size and the conditional power distribution are usually ignored. Therefore, the need for an adequate performance score combining these relevant performance criteria is evident. To judge the performance of an adaptive design, there exist two possible perspectives, which might also be combined: Either the global performance of the design can be addressed, which averages over all possible interim results, or the conditional performance is addressed, which focuses on the remaining performance conditional on a specific interim result. In this work, we give a compact overview of sample size recalculation rules and performance measures. Moreover, we propose a new conditional performance score and apply it to various standard recalculation rules by means of Monte-Carlo simulations.

Published
2020

28. Incorporating historical two‐arm data in clinical trials with binary outcome: A practical approach

Author

Manuel Feißt, Meinhard Kieser, and Johannes Krisam

Subjects
Statistics and Probability, Computer science, Existential quantification, Bayesian probability, Value (computer science), 01 natural sciences, 010104 statistics & probability, 03 medical and health sciences, 0302 clinical medicine, Frequentist inference, Statistics, Humans, Pharmacology (medical), 030212 general & internal medicine, 0101 mathematics, Pharmacology, Clinical Trials as Topic, Models, Statistical, Bayes Theorem, Power (physics), Clinical trial, Research Design, Sample size determination, Data Interpretation, Statistical, Sample Size, Type I and type II errors
Abstract

The feasibility of a new clinical trial may be increased by incorporating historical data of previous trials. In the particular case where only data from a single historical trial are available, there exists no clear recommendation in the literature regarding the most favorable approach. A main problem of the incorporation of historical data is the possible inflation of the type I error rate. A way to control this type of error is the so-called power prior approach. This Bayesian method does not "borrow" the full historical information but uses a parameter 0 ≤ δ ≤ 1 to determine the amount of borrowed data. Based on the methodology of the power prior, we propose a frequentist framework that allows incorporation of historical data from both arms of two-armed trials with binary outcome, while simultaneously controlling the type I error rate. It is shown that for any specific trial scenario a value δ > 0 can be determined such that the type I error rate falls below the prespecified significance level. The magnitude of this value of δ depends on the characteristics of the data observed in the historical trial. Conditionally on these characteristics, an increase in power as compared to a trial without borrowing may result. Similarly, we propose methods how the required sample size can be reduced. The results are discussed and compared to those obtained in a Bayesian framework. Application is illustrated by a clinical trial example.

Published
2020

29. A comparison of Bayesian and frequentist methods in random‐effects network meta‐analysis of binary data

Author

Katrin Jensen, Svenja E. Seide, and Meinhard Kieser

Subjects
Multivariate statistics, Mean squared error, Network Meta-Analysis, Bayesian probability, 01 natural sciences, Education, 010104 statistics & probability, 03 medical and health sciences, 0302 clinical medicine, Bias, Meta-Analysis as Topic, Frequentist inference, Statistics, Humans, Computer Simulation, 030212 general & internal medicine, 0101 mathematics, Mathematics, Bayes estimator, Bayes Theorem, Random effects model, Confidence interval, Bayesian statistics, Research Design, Data Interpretation, Statistical, Algorithms, Software
Abstract

The performance of statistical methods is often evaluated by means of simulation studies. In case of network meta-analysis of binary data, however, simulations are not currently available for many practically relevant settings. We perform a simulation study for sparse networks of trials under between-trial heterogeneity and including multi-arm trials. Results of the evaluation of two popular frequentist methods and a Bayesian approach using two different prior specifications are presented. Methods are evaluated using coverage, width of intervals, bias, and root mean squared error (RMSE). In addition, deviations from the theoretical surface under the cumulative rankings (SUCRAs) or P-scores of the treatments are evaluated. Under low heterogeneity and when a large number of trials informs the contrasts, all methods perform well with respect to the evaluated performance measures. Coverage is observed to be generally higher for the Bayesian than the frequentist methods. The width of credible intervals is larger than those of confidence intervals and is increasing when using a flatter prior for between-trial heterogeneity. Bias was generally small, but increased with heterogeneity, especially in netmeta. In some scenarios, the direction of bias differed between frequentist and Bayesian methods. The RMSE was comparable between methods but larger in indirectly than in directly estimated treatment effects. The deviation of the SUCRAs or P-scores from their theoretical values was mostly comparable over the methods but differed depending on the heterogeneity and the geometry of the investigated network. Multivariate meta-regression or Bayesian estimation using a half-normal prior scaled to 0.5 seems to be promising with respect to the evaluated performance measures in network meta-analysis of sparse networks.

Published
2020

30. Maturation of the Cardiac Autonomic Nervous System Activity in Children and Adolescents

Author

Linda Kersten, Tanja G M Vrijkotte, Stephane A. De Brito, Ineke Nederend, Maider González de Artaza-Lavesa, Beate Herpertz-Dahlmann, Martin Steppan, Hanna Swaab, Aranzazu Fernandez-Rivas, Molly Batchelor, Martin Prätzlich, Katharina Ackermann, Silvina Guijarro, Anne Martinelli, Nora Maria Raschle, Tisse van Nimwegen, Areti Smaragdi, Eco J. C. de Geus, Malou Gundlach, Christine M. Freitag, Iñaki Kerexeta-Lizeaga, Roberta Clanton, Angeliki Konsta, Sarah Baumann, Lisette M. Harteveld, Réka Siklósi, Lynn Valérie Fehlbaum, Christina Stadler, Roberta Dochnal, Gregor Kohls, Amaia Hervás, Dimitris Dikeos, Nienke M. Schutte, Ignazio Puzzo, Jill Suurland, Susanne R. de Rooij, Jack C. Rogers, Meinhard Kieser, Arend D. J. ten Harkel, Lucres M. C. Jansen, Karen Gonzalez, Rosalind Baker, Helen Lazaratou, Graeme Fairchild, Kerstin Konrad, Anka Bernhard, Helena Oldenhof, Arne Popma, Pediatric surgery, VU University medical center, APH - Mental Health, Amsterdam Reproduction & Development (AR&D), Prätzlich, Martin, Ackermann, Katharina, Baker, Rosalind, Batchelor, Molly, Baumann, Sarah, Bernhard, Anka, Clanton, Roberta, Dikeos, Dimitris, Dochnal, Roberta, Fehlbaum, Lynn Valérie, Fernández-Rivas, Aranzazu, Gonzalez, Karen, González de Artaza-Lavesa, Maider, Guijarro, Silvina, Gundlach, Malou, Herpertz-Dahlmann, Beate, Hervas, Amaia, Kersten, Linda, Kohls, Gregor, Konsta, Angeliki, Lazaratou, Helen, Kerexeta-Lizeaga, Iñaki, Martinelli, Anne, van Nimwegen, Tisse, Puzzo, Ignazio, Raschle, Nora Maria, Rogers, Jack, Siklósi, Réka, Smaragdi, Areti, Steppan, Martin, De Brito, Stephane, Fairchild, Graeme, Kieser, Meinhard, Konrad, Kerstin, Freitag, Christine, Stadler, Christina, Biological Psychology, Clinical Developmental Psychology, APH - Personalized Medicine, Epidemiology and Data Science, APH - Aging & Later Life, APH - Health Behaviors & Chronic Diseases, ARD - Amsterdam Reproduction and Development, Public and occupational health, and APH - Methodology

Subjects
Male, Aging, sympathetic nerve activity, animal structures, Adolescent, pediatrics, Physiology, Sympathetic nerve activity, 030204 cardiovascular system & hematology, Development, Pediatrics, 03 medical and health sciences, Young Adult, 0302 clinical medicine, Heart Rate, Pediatric Cardiology, Heart rate variability, Medicine, Humans, Diseases of the circulatory (Cardiovascular) system, Autonomic nervous system, ddc:610, Child, development, Original Research, business.industry, autonomic nervous system, heart rate variability, Infant, Child, Preschool, RC666-701, Electrocardiography, Ambulatory, Female, Cardiology and Cardiovascular Medicine, business, Neuroscience, 030217 neurology & neurosurgery, Follow-Up Studies
Abstract

Journal of the American Heart Association 10(4), e017405 (2021). doi:10.1161/JAHA.120.017405, Published by American Heart Association, New York, NY

Published
2021

34. Forensic Biomechanics

Author

Jules Kieser, Michael Taylor, Debra Carr and Jules Kieser, Michael Taylor, Debra Carr

Published
2012

35. Certification of Uranium Isotope Amount Ratios in a Suite of Uranium Ore Concentrate Certified Reference Materials

Author

Zhang, Ruoxi, primary, Nadeau, Kenny, additional, Gautier, Eduardo Amilcar, additional, Babay, Paola Alejandra, additional, Ramella, José Luis, additional, Virgolici, Marian, additional, Serban, Andreea Elena, additional, Fugaru, Viorel, additional, Kimura, Yoshiki, additional, Venchiarutti, Célia, additional, Richter, Stephan, additional, Aregbe, Yetunde, additional, Varga, Zsolt, additional, Wallenius, Maria, additional, Mayer, Klaus, additional, Seo, Hana, additional, Choi, Jung Youn, additional, Tobi, Csaba, additional, Fayek, Mostafa, additional, Sharpe, Ryan, additional, Samperton, Kyle M., additional, Genetti, Victoria D., additional, Lindvall, Rachel E., additional, Inglis, Jeremy D., additional, Denton, Joanna S., additional, Reinhard, Andrew A., additional, Francisco, Barbara, additional, Zhao, Xiaolei, additional, Kieser, William, additional, He, Juan, additional, Gao, Ying, additional, Meija, Juris, additional, El‐Jaby, Ali, additional, Yang, Lu, additional, and Mester, Zoltan, additional

Published
2021
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36. Risk factors for periprosthetic femoral fractures around total hip arthroplasty: a systematic review and meta‐analysis

Author

Mark D. Stringer, Chris Frampton, Michael C Wyatt, Yi Deng, David C. Kieser, and Gary J. Hooper

Subjects
Reoperation, musculoskeletal diseases, medicine.medical_specialty, Arthroplasty, Replacement, Hip, Periprosthetic, Cochrane Library, Odds, 03 medical and health sciences, 0302 clinical medicine, Risk Factors, Internal medicine, Humans, Medicine, Femur, Risk factor, business.industry, General Medicine, Odds ratio, Confidence interval, surgical procedures, operative, Systematic review, 030220 oncology & carcinogenesis, Meta-analysis, Female, 030211 gastroenterology & hepatology, Surgery, Periprosthetic Fractures, business, Femoral Fractures
Abstract

BACKGROUND Periprosthetic fractures are becoming increasingly common, often leading to poor patient outcomes. The aim of this study was to identify risk factors associated with periprosthetic femoral fractures (PPFFx). METHODS Two independent reviewers conducted a systematic review of the databases MEDLINE, Embase and Cochrane Library according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines, from the earliest available date to December 2017. We included all clinical articles reporting more than 100 post-operative PPFFx around total hip arthroplasty (THA). Outcomes included demographics, fracture type, risk factors and time to fracture. RESULTS A total of 12 868 PPFFx were reported across 18 eligible studies; 64% occurred following primary THA and 36% occurred after revision THA, and 66% of all fractures were in females. Vancouver B2 fractures were the most common type (39%). We found the odds of sustaining a PPFFx is significantly lower after a primary THA compared to revision THA (odds ratio 0.31, 95% confidence interval 0.24-0.40, P

Published
2019

37. Primary appendicular soft‐tissue sarcoma resection: What tumour parameters affect wound closure planning?

Author

Gary C O'Toole, Niall P McGoldrick, Barry Moran, C. Gillham, Peter Barrett, Mary B. Codd, Derek T. Cawley, and David C. Kieser

Subjects
Male, medicine.medical_specialty, Reconstructive surgery, Local excision, Soft Tissue Neoplasms, Dermatology, Resection, 030207 dermatology & venereal diseases, 03 medical and health sciences, Postoperative Complications, 0302 clinical medicine, medicine, Humans, 030212 general & internal medicine, Sutures, medicine.diagnostic_test, business.industry, Soft tissue sarcoma, Sarcoma, Magnetic resonance imaging, Original Articles, Middle Aged, medicine.disease, Magnetic Resonance Imaging, Predictive factor, Drainage, Female, Surgery, Wound closure, Radiology, business, Negative-Pressure Wound Therapy
Abstract

Wound closure after wide, local excision of an appendicular soft‐tissue sarcoma (STS) can be challenging. This study evaluates the value of magnetic resonance imaging (MRI)‐based tumour parameters in planning wound closure. A total of 71 patients with a primary limb‐based STS, excluding vascular or osseous involvement, excluding the shoulder or hand and hip or foot were included. Axial MRI images were used to measure the circumferences and cross‐sectional areas of the limb, bone, and tumour. The tumour diameter, length, and depth at the level of maximal tumour dimension were measured to identify the tumour's relative contribution to the planning of optimal wound closure management through primary closure (PC) or reconstructive surgery (RS). Eighteen patients required planned wound RS. Wound complications occurred in 14% overall. Tumours, which were closed by PC, were of significantly greater depth, shorter radial diameter, and shorter tumour circumference relative to those closed by RS. On multivariate analysis, tumour depth was the greatest contributory factor in predicting type of wound closure. A quantitative analysis of MRI‐based tumour parameters demonstrates tumour depth as the most predictive factor in planning for the type of wound closure and may prove beneficial in providing greater insight into planned wound management of sarcoma resection.

Published
2019

38. Adjustment for exploratory cut‐off selection in randomized clinical trials with survival endpoint

Author

Meinhard Kieser, Heiko Götte, and Marietta Kirchner

Subjects
Statistics and Probability, Biometry, Time Factors, Endpoint Determination, media_common.quotation_subject, Posterior probability, Population, 01 natural sciences, Confirmatory trial, law.invention, 010104 statistics & probability, 03 medical and health sciences, 0302 clinical medicine, Randomized controlled trial, law, Statistics, Humans, Medicine, 030212 general & internal medicine, 0101 mathematics, education, Selection (genetic algorithm), Randomized Controlled Trials as Topic, media_common, Selection bias, Likelihood Functions, education.field_of_study, business.industry, General Medicine, Survival Analysis, Biomarker (medicine), Statistics, Probability and Uncertainty, Approximate Bayesian computation, business, Biomarkers
Abstract

Defining the target population based on predictive biomarkers plays an important role during clinical development. After establishing a relationship between a biomarker candidate and response to treatment in exploratory phases, a subsequent confirmatory trial ideally involves only subjects with high potential of benefiting from the new compound. In order to identify those subjects in case of a continuous biomarker, a cut-off is needed. Usually, a cut-off is chosen that resulted in a subgroup with a large observed treatment effect in an exploratory trial. However, such a data-driven selection may lead to overoptimistic expectations for the subsequent confirmatory trial. Treatment effect estimates, probability of success, and posterior probabilities are useful measures for deciding whether or not to conduct a confirmatory trial enrolling the biomarker-defined population. These measures need to be adjusted for selection bias. We extend previously introduced Approximate Bayesian Computation techniques for adjustment of subgroup selection bias to a time-to-event setting with cut-off selection. Challenges in this setting are that treatment effects become time-dependent and that subsets are defined by the biomarker distribution. Simulation studies show that the proposed method provides adjusted statistical measures which are superior to naïve Maximum Likelihood estimators as well as simple shrinkage estimators.

Published
2019

39. Integrated evaluation of targeted and non‐targeted therapies in a network meta‐analysis

Author

Katrin Jensen, Tanja Proctor, and Meinhard Kieser

Subjects
Statistics and Probability, Biometry, Endpoint Determination, Computer science, medicine.medical_treatment, Bayesian probability, Machine learning, computer.software_genre, 01 natural sciences, Targeted therapy, 010104 statistics & probability, 03 medical and health sciences, 0302 clinical medicine, medicine, Humans, Meta-regression, 030212 general & internal medicine, Precision Medicine, 0101 mathematics, business.industry, Contrast (statistics), General Medicine, Regression, Treatment Outcome, Meta-analysis, Regression Analysis, Biomarker (medicine), Aggregate data, Artificial intelligence, Statistics, Probability and Uncertainty, business, computer, Biomarkers
Abstract

Individualized therapies for patients with biomarkers are moving more and more into the focus of research interest when developing new treatments. Hereby, the term individualized (or targeted) therapy denotes a treatment specifically developed for biomarker-positive patients. A network meta-analysis model for a binary endpoint combining the evidence for a targeted therapy from individual patient data with the evidence for a non-targeted therapy from aggregate data is presented and investigated. The biomarker status of the patients is either available at patient-level in individual patient data or at study-level in aggregate data. Both types of biomarker information have to be included. The evidence synthesis model follows a Bayesian approach and applies a meta-regression to the studies with aggregate data. In a simulation study, we address three treatment arms, one of them investigating a targeted therapy. The bias and the root-mean-square error of the treatment effect estimate for the subgroup of biomarker-positive patients based on studies with aggregate data are investigated. Thereby, the meta-regression approach is compared to approaches applying alternative solutions. The regression approach has a surprisingly small bias even in the presence of few studies. By contrast, the root-mean-square error is relatively greater. An illustrative example is provided demonstrating implementation of the presented network meta-analysis model in a clinical setting.

Published
2019

41. Preoperative chemoradiotherapy versus chemotherapy for adenocarcinoma of the esophagus and esophagogastric junction (AEG): systematic review with individual participant data (IPD) network meta-analysis (NMA)

Author

Ronellenfitsch, Ulrich, additional, Friedrichs, Juliane, additional, Grilli, Maurizio, additional, Hofheinz, Ralf-Dieter, additional, Jensen, Katrin, additional, Kieser, Meinhard, additional, Kleeff, Jörg, additional, Michalski, Christoph W., additional, Michl, Patrick, additional, Seide, Svenja, additional, Vey, Johannes, additional, Vordermark, Dirk, additional, and Proctor, Tanja, additional

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2021
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43. Effects of pre-operative isolation on postoperative pulmonary complications after elective surgery: an international prospective cohort study

Author

Simoes, JFF, Nepogodiev, D, Ademuyiwa, A, Buarque, I, El-Boghdadly, K, Gebreyohanes, M, Glasbey, JC, Kronberger, E, Kruijff, S, Li, E, Loeffler, M, Mashbari, H, Pata, F, Smart, N, Sayyed, R, Shu, S, Sund, M, Bhangu, A, Simoes, J, Ahmed, W-U-R, Argus, L, Ball, A, Bywater, EP, Blanco-Colino, R, Brar, A, Chaudhry, D, Dawson, BE, Duran, I, Elhadi, M, Gujjuri, RR, Jones, CS, Harrison, EM, Kamarajah, SK, Keatley, JM, Lawday, S, Mann, H, Marson, EJ, Mclean, KA, Norman, L, Ots, R, Outani, O, Picciochi, M, Santos, I, Shaw, C, Taylor, EH, Trout, IM, Varghese, C, Venn, ML, Xu, W, Dajti, I, Gjata, A, Kacimi, SEO, Boccalatte, L, Cox, D, Pockney, P, Townend, P, Aigner, F, Kronberger, IE, Samadov, E, Alderazi, A, Hossain, K, Padmore, G, van Ramshorst, G, Lawani, I, Cerovac, A, Delibegovic, S, Baiocchi, G, Ataide Gomes, GM, Buarque, IL, Gohar, M, Slavchev, M, Nwegbu, C, Agarwal, A, Martin, J, Ng-Kamstra, J, Marta Modolo, M, Olivos, M, Lou, W, Ren, D-L, Andres Calvache, J, Rivera, CJ-P, Hadzibegovic, AD, Kopjar, T, Mihanovic, J, Aviles Jimenez, PM, Gouvas, N, Klat, J, Novysedlak, R, Amisi, N, Christensen, P, El-Hussuna, A, Batista, S, Lincango-Naranjo, E, Emile, S, Arevalo Sandoval, DA, Dhufera, H, Hailu, S, Mengesha, MG, Kauppila, JH, Arnaud, AP, Demetrashvili, Z, Albertsmeier, M, Lederhuber, H, Loeffler, MW, Acquah, DK, Ofori, B, Tabiri, S, Metallidis, S, Tsoulfas, G, Aguilera-Arevalo, M-L, Recinos, G, Mersich, T, Wettstein, D, Ghosh, D, Kembuan, G, Milan, PB, Khosravi, MH, Mozafari, M, Hilmi, A, Mohan, H, Zmora, O, Gallo, G, Pellino, G, Fujimoto, Y, Kuroda, N, Satoi, S, Abou Chaar, MK, Ayasra, F, Fakhradiyev, I, Hamdun, IHS, Jin-Young, J, Jamal, M, Karout, L, Gulla, A, Rasoaherinomenjanahary, F, Samison, LH, Roslani, AC, Duran Sanchez, II, Samantha Gonzalez, D, Martinez, L, Jose Martinez, M, Nayen, A, Ramos-De la Medina, A, Nunez, J, Nashidengo, PR, Shah, R, Shrestha, AL, Jonker, P, Noltes, M, Steinkamp, P, Wright, D, Abdur-Rahman, L, Adisa, A, Osinaike, B, Seyi-Olajide, J, Williams, O, Williams, E, Pejkova, S, Al Balushi, Z, Qureshi, AU, Mohsen, MA, Abukhalaf, SA, Cukier, M, Gomez-Fernandez, H, Shu Yip, S, Vasquez Ojeda, XP, Dione Sacdalan, M, Major, P, Azevedo, J, Cunha, MF, Zarour, A, Bonci, E-A, Negoi, I, Efetov, S, Kochetkov, V, Litvin, A, Ingabire, JA, Bucyibaruta, G, Faustin, N, Habumuremyi, S, Imanishimwe, A, de Dieu, HJ, Munyaneza, E, Ncogoza, I, Alameer, E, Ndong, A, Radenkovic, D, Chew, MH, Koh, F, Ngu, J, Panyko, A, Bele, U, Kosir, JA, Daoud, H, Minaya Bravo, AM, Jayarajah, U, Wickramasinghe, D, Adam, MEAE, Rutegard, M, Adamina, M, Gialamas, E, Horisberger, K, Alshaar, M, Huang, A, Lohsiriwat, V, Charles, S, Jlassi, H, Isik, A, Leventoglu, S, Lekuya, HM, Lule, H, Kopetskyi, S, Alsaadi, H, Alshryda, S, Alser, O, Bankhead-Kendall, B, Breen, K, Kaafarani, H, Cal, FB, Al-Naggar, H, Maimbo, M, Mazingi, D, Abbott, T, Akhbari, M, Benson, R, Bhanderi, S, Biccard, B, Caruana, E, Chakrabortee, S, Chapatwala, R, Costas-Chavarri, A, Demetriades, AK, Desai, A, Di Saverio, S, Drake, T, Edwards, J, Evans, J, Fiore, M, Ford, S, Fotopoulou, C, Fowler, A, Futaba, K, Ganly, I, James, HG, Griffiths, E, Gronchi, A, Hutchinson, P, Hyman, GY, Incorvia, J, Jain, R, Jenkinson, M, Khan, T, Knight, SR, Kolias, A, Kudsk-Iversen, S, Kwan, TY, Leung, E, Mayol, J, McKay, S, Meara, JG, Mills, E, Moug, S, Patel, A, Perinotti, R, Rice, HE, Roberts, K, Schache, A, Shaw, R, Stephens, M, Stewart, GD, Teasdale, E, Vaughan-Shaw, P, Vidya, R, Wright, N, Wuraola, F, Zimmelman, N, Agastra, E, Thereska, D, Martin Lucchini, S, Laudani, V, Chwat, C, Pedraza Salazar, II, Pantoja Pachajoa, DA, Duro, A, Calderon Arancibia, JA, D'Aulerio, G, Dudi-Venkata, N, Egoroff, N, Farik, S, Lott, N, Moss, J-L, Rennie, S, Tan, L, Vo, UG, Watson, D, Watters, D, Bright, T, Hollington, P, Zhou, X, Kroon, HM, Farfus, A, Barker, J, Watson, E, Stevens, S, Latif, H, Dawson, AC, Chuan, A, Muralidharan, V, Wong, E, Ackermann, T, Pacilli, M, Hodgson, R, Heriot, A, Choong, P, Brown, W, Lidder, S, Yeung, J, Traeger, L, Regalo, G, Gourlay, R, Badiani, S, Koh, C, Putnis, S, Haider, F, Mitul, AR, Komen, N, Dhondt, B, Cappeliez, S, Pigeolet, M, Schoneveld, M, Stijns, J, Oosterlinck, W, Flamey, N, Kpangon, C, Agbadebo, M, Tobome, SR, Barros, AV, Aguiar Junior, S, do Amaral Campos, HG, Gross, J, Fernandez Coimbra, FJ, Kowalski, LP, Makdissi, F, Nakagawa, S, Duprat Neto, JP, Vartanian, JG, Yazbek, G, Zequi, SC, Flumignan, R, Jaworska, N, Dell, A, Shanthanna, H, Behzadi, A, Nessim, C, Mozel, M, St-germain, P, Russell, C, Groot, G, Safieddine, N, Wijeysundera, D, Eskander, A, Chadi, S, MacKenzie, S, Flexman, A, Heredia, F, Villanueva, J, Waissbluth, S, Macchiavello, R, Escudero, MI, Fuentes, T, Mimica, X, Bolivar Saenz, D, Caicedo, L, Pablo Alzate, J, Luna, J, Pedraza Alonso, NF, Ortiz Silva, C, Rodriguez, J, Silva-Igua, L, Torres, ML, Maria Trujillo, L, Nieto Calvache, AJ, Balanta-Melo, J, Figueroa-Casanova, R, Garcia-Montoya, O-J, Marulanda Toro, CA, Velez Botero, M, Mendoza Arango, MC, Diaz Martinez, E, Gutierrez Perdomo, V, Montenegro, E, Rodriguez-Abreu, J, Mejia, D, Abouelnagah, G, Shehata, S, Rida, AHEF, Hassan, RA, Saad, MM, Loaloa, MR, Mostafa, B, Qassem, M, Fahmy, M, Abozied, H, Azzam, AY, Ghozy, S, Sallam, A, Shehta, A, Abdelkhalek, M, Samaka, R, Morsy, A, Sherif, AE, Negussie, A, Fisseha, T, Shumbash, K, Abebe, M, Yasin, SM, Akililu, YB, Megersa, A, Tefera, T, Assefa, M, Atnafu, B, Tsegaye, B, Bezabih, YS, Sisay, S, Bekele, K, Jira, M, Derilo, H, Degefa, E, Tadesse, A, Nidaw, M, Sarjanoja, E, Testelin, S, Boucher, S, Jouffret, L, Lakkis, Z, Le Bian, AZ, Harper, L, des Deserts, MD, Andre, B, Slim, K, Verhaeghe, R, Police, A, Girard, E, Chebaro, A, Nkembi, AS, Arnalsteen, L, Ballouhey, Q, Mege, D, Jeandel, C, Duchalais, E, Bouche, P-A, Manceau, G, Cretolle, C, Hervieux, E, Girard, N, Seguin-Givelet, A, Gaujoux, S, De Simone, B, Boisson, M, Bergeat, D, Fredon, F, Nappi, F, Kassir, R, Scalabre, A, Migliorelli, F, Ezanno, A-C, Seeliger, B, Vaysse, C, Charbonneau, H, Misrai, V, Abbo, O, Angeles, MA, Brunaud, L, Modabber, A, Wolf, S, Kamphues, C, Hoehn, P, Glowka, TR, Rokohl, AC, Bork, U, Fluegen, G, Horch, RE, Schmedding, A, Schnitzbauer, A, Eberbach, H, Schlager, D, Spelsberg, F, Keppler, L, Hecker, A, Wolfer, S, Ronellenfitsch, U, Nitschke, C, Peiper, C, Hakami, I, Welter, S, Nikolaieva, K, Roth, A, Lindert, J, Gousias, K, Rissmann, A, Linz, VC, Rahbari, N, Rassweiler-Seyfried, M-C, Gut, AE, Gempt, J, Reim, D, Wagner, A, Keppler, AM, Stoleriu, MG, Saier, T, Stadler, J, Kaiser, JC, Brunner, SM, Pfister, K, Herzberg, J, Nowak, K, Reinhard, T, Stavrou, GA, Koenigsrainer, A, Konrads, C, Quante, M, Laban, S, von Pusch, S, Hirschburger, M, Doerner, J, Wiegering, A, Tampaki, EC, Gutierrez Ruiz, A, Rodas, A, Lucia Portilla, A, Carrera, J, Duarte, AB, Lowey, M, Barillas, S, Suroy, A, Vaishnav, D, Chowdappa, RG, Madabhavi, I, Bhat, D, Venkatappa, SK, Thakar, S, Jain, K, Kumar, A, Nagar, M, Mishra, T, Sekar, A, Gupta, A, Kaman, L, Karthigeyan, M, Tripathi, M, Rammohan, A, Vayoth, SO, Rajanbabu, A, Subbian, A, Gupta, R, Raut, M, Evelyn R, N, Kannaiyan, L, Matai, A, Misra, S, Bhende, V, Muthu, S, Ghosh, I, Sharma, A, Bajaj, A, Rajan, S, Agarwal, G, Pawar, P, Alexander, P, Vijayakumar, MV, Hameed, BMZ, Badareesh, L, Chaudhry, NK, Baliarsing, L, Dharap, S, Kulkarni, A, Thyavihally, Y, Sharma, RD, Pramesh, CS, Soni, R, Dube, SK, Sharma, S, Singh, H, Bains, L, Ghodke, R, Sodhai, V, Maji, S, Basu, S, Mahakalkar, C, Kannan, R, Mehraj, A, Ranganath, N, Phadnis, A, Yadev, I, Kavalaka, A, Mittal, R, Vallam, KC, Akhavizadegan, H, Maleki, ER, Kandevani, NY, Ikele, H, McNestry, C, Fleming, C, O'Brien, S, Abd Elwahab, S, Davis, N, Javadpour, M, McDonnell, B, Connor, CO, Bolger, J, Clancy, C, Croghan, SM, Donlon, N, Cullinane, C, Creavin, B, Muheilan, M, Earley, H, Kabir, SMU, Fahadullah, M, Ryan, E, Connelly, T, Hashimoto, D, Alqudah, MA, Alajalen, A, Omari, RY, Qasem, A, Alawneh, Y, Ahmad, A, Aladawi, O, Alrayes, B, Haidar, H, Husain, S, Qassem, F, Sumadi, A, Abu Salhiyeh, A, Al-Manaseer, BM, Alsunna, Z, Ra'ed, H, Hamad, FRB, Abuleil, A, Jimaale, EAM, Abu-Mehsen, M, Olaywah, N, Wafi, O, Ababneh, H, Abu-Ismail, L, Khamees, A, Alkhatib, A, Bolatbekova, R, Kulimbet, M, Nurgozhin, T, Saliev, T, Zhussupov, B, Almabayev, Y, Kaidarova, D, Tamoos, K, Aqeelah, A, Mohammed, AAK, Al Maadany, F, Alkadeeki, G, Gahwagi, M, Aldressi, W, Amnaina, M, Alansari, AHA, Alkaseek, A, Yagoub, G, Ben Amer, A, Salem, M, Almugaddami, A, Burgan, D, Abdelkabir, M, Alshareef, K, Ben Jouira, RAI, Meelad, A, Bouhuwaish, A, Dwaga, SE, Khalifa, H, Almiqlash, B, Suliaman, T, Alawami, M, Elhajdawe, F, Aboazamazem, H, Ellojli, I, Msherghi, A, Saleh, IA, Alayan, M, Ndayishyigikiye, MD, Munyika, A, Plarre, P, Borowski, DW, Wells, C, Teague, R, Elliott, B, Kieser, D, Mohyieldin, O, McIntosh, N, Haran, C, King, J, Ha, J, McGuinness, MJ, Adesanya, O, Olaogun, J, Akinmade, A, Bwala, K, Agbonrofo, P, Afolabi, A, Usang, U, Ekenze, S, Olori, S, Lawal, TA, Okunlola, A, Ekiti, I, Kache, S, Sale, D, Anyanwu, L-J, Okereke, C, Tolani, MA, Filipce, V, Todorovic, L, Stavridis, S, Massoud, JG, Alsibai, S, Sultan, R, Altaf, HN, Bhatti, ABH, Waqar, SH, Aziz, A, Kerawala, AA, Rai, L, Anwer, M, Tariq, A, Ayub, B, Niazi, SU, Naseem, MY, Sarwar, MZ, Khokhar, MI, Zahid, IA, Majid, HJ, Talat, N, Asif, M, Chaudhary, MH, Farooq, U, Ahmad, S, Mabood, W, Bukhari, SI, Tariq, M, Yaqoob, E, Javed, S, Malik, MU, Yaqoob, HN, Falcon Pacheco, GM, Mas Melendez, R, Paucar Urbina, ADP, Rios Chiuyari, J, Otiniano Alvarado, CE, Rivera Lau, LF, Borda-Luque, G, Niquen-Jimenez, M, Arias, C, Zegarra, S, Betalleluz Pallardel, J, Ugarte Oscco, RA, Mendiola, G, Carpio Colmenares, YT, Zapata, CS, Rosa Ortiz, M, Borges, FC, Viveiros, O, Serralheiro, P, Santos-Costa, P, Mendes, F, Melo, MR, Cardoso, P, Soares, A, Pereira, RG, Silva, N, Caiado, A, Sacras, ML, Azevedo, P, Almeida-Reis, R, Oliveira, J, Nogueiro, J, Sampaio-Alves, M, Costa, LC, Baia, C, Deus, AC, Branquinho, R, Marcal, A, Tojal, A, Makkai-Popa, ST, Mironescu, A, Grama, F, Toma, EA, Filipescu, D, Bacalbasa, N, Motas, N, Ionescu, S, Ginghina, O, Costea, R, Zarnescu, NO, Drasovean, R, Dimofte, M-G, Porumb, V, Kirov, M, Molitvin, Y, Pykhteev, V, Raevskaya, M, Butyrskii, A, Alshahrani, M, Althumairi, A, Alzerwi, N, Al Ameer, A, Madkhali, T, Almulhim, AS, Ghazwani, S, Ayoub, A, Iskander, O, Ghunaim, M, Alharthi, M, Alzaidi, TM, Alyami, M, Al Amri, A, AlFakhri, A, Alhefdhi, A, Chowdhury, S, Nouh, T, Alshehri, A, Alzahrani, A, Alalawi, Y, Awad, S, Konate, I, Tendeng, J, Teo, NZ, Aqil, S, Barrena Lopez, C, Sanchez Mozo, A, Rodriguez Infante, A, Caja Vivancos, P, Prieto, M, Alberdi San Roman, I, Gomez Fernandez, L, Munoz Vives, JM, Carreras-Castaner, A, Diaz-Feijoo, B, Sieira-Gil, R, Turrado-Rodriguez, V, Sanchez Lopez, A, Sanchez-Cabus, S, Jimenez Toscano, M, Canals Sin, MP, Garcia Laura, S, Martin Sole, O, Palazon Bellver, P, Perez-Bertolez, S, Prat-Ortells, J, Riba Martinez, M, Rubio-Palau, J, Tarrado, X, Alonso Mendoza, V, Bescos, C, Espin-Basany, E, Espinosa-Bravo, M, Gil-Sala, D, Gonzalez-Suarez, S, Montferrer Estruch, N, Porteiro Marino, L, Rodriguez-Tesouro, A, Rojas Portilla, F, Tormos Perez, MP, Vives, I, Garcia De Cortazar, U, Tudela, K, Landaluce-Olavarria, A, Estaire Gomez, M, Almoguera, J, Ugarte-Sierra, B, Jimenez, V, Bertrand, M, Cardenas Puiggros, L, Delisau-Puig, O, Garcia-Adamez, J, Julia Bergkvist, D, Maldonado-Marcos, E, Diego Garcia, L, Roldon Golet, M, Soto-Darias, I, Cristina Rahy-Martin, A, Enjuto, D, Ramos-Luengo, A, Delgado Fernandez, J, Lugo Duarte, C, Ojeda Thies, C, Marquez, L, Crego Vita, D, Dziakova, J, Canno Velasco, J, Mateo-Sierra, O, Quintana-Villamandos, B, Rey Valcarcel, C, Rio, J, Roman Garcia de Leon, L, Di Martino, M, Prada, J, Serrano Gonzalez, J, Losada, M, Castell Gomez, JT, Corripio-Sanchez, R, Forero-Torres, A, Manuel Morales-Puebla, J, Perez-Chrzanowska, H, Valderrabano Gonzalez, S, Yebes, A, Zapardiel, I, Diez Alonso, M, Morales Palacios, N, Cabanero Sanchez, A, Sanchez Fernandez, F, Abad Gurumeta, A, Abad-Motos, A, Corella, F, Ripolles-Melchor, J, Sanz-Gonzalez, R, Alcaraz Fuentes, M, Fernandez Martin, MT, Calvo Espino, P, Carrasco Prats, M, Fernandez-Lopez, A-J, Garcia Escudero, D, Garcia Soria, V, Martinez Alonso, JA, Ruiz-Marin, M, Gomez Perez, B, Moya-Angeler, J, Fernandez Martinez, D, Llaquet Bayo, H, Colas-Ruiz, E, Bella Romera, S, Gavalda Pellice, MT, Jorda Sole, M, Ruiz Velasquez, EJ, Nunez, B, Jimenez, R, Zabaleta, J, Jose Gonzalez-Gimeno, M, Ortega Vazquez, I, Perez Ferrer, A, Martin-Laez, R, Moreno Suarez, M, Freiria Eiras, MA, Ramallo-Solis, I, Gomez-Rosado, J-C, Oliver Guillen, JR, Achalandabaso Boira, M, Catala Bauset, JC, Domenech, J, Badenes, R, Carlos Bernal-Sprekelsen, J, Sancho-Muriel, J, De Andres-Asenjo, B, Tejero-Pintor, FJ, Vallve-Bernal, M, Vazquez Melero, A, Simoes, JFF, Nepogodiev, D, Ademuyiwa, A, Buarque, I, El-Boghdadly, K, Gebreyohanes, M, Glasbey, JC, Kronberger, E, Kruijff, S, Li, E, Loeffler, M, Mashbari, H, Pata, F, Smart, N, Sayyed, R, Shu, S, Sund, M, Bhangu, A, Simoes, J, Ahmed, W-U-R, Argus, L, Ball, A, Bywater, EP, Blanco-Colino, R, Brar, A, Chaudhry, D, Dawson, BE, Duran, I, Elhadi, M, Gujjuri, RR, Jones, CS, Harrison, EM, Kamarajah, SK, Keatley, JM, Lawday, S, Mann, H, Marson, EJ, Mclean, KA, Norman, L, Ots, R, Outani, O, Picciochi, M, Santos, I, Shaw, C, Taylor, EH, Trout, IM, Varghese, C, Venn, ML, Xu, W, Dajti, I, Gjata, A, Kacimi, SEO, Boccalatte, L, Cox, D, Pockney, P, Townend, P, Aigner, F, Kronberger, IE, Samadov, E, Alderazi, A, Hossain, K, Padmore, G, van Ramshorst, G, Lawani, I, Cerovac, A, Delibegovic, S, Baiocchi, G, Ataide Gomes, GM, Buarque, IL, Gohar, M, Slavchev, M, Nwegbu, C, Agarwal, A, Martin, J, Ng-Kamstra, J, Marta Modolo, M, Olivos, M, Lou, W, Ren, D-L, Andres Calvache, J, Rivera, CJ-P, Hadzibegovic, AD, Kopjar, T, Mihanovic, J, Aviles Jimenez, PM, Gouvas, N, Klat, J, Novysedlak, R, Amisi, N, Christensen, P, El-Hussuna, A, Batista, S, Lincango-Naranjo, E, Emile, S, Arevalo Sandoval, DA, Dhufera, H, Hailu, S, Mengesha, MG, Kauppila, JH, Arnaud, AP, Demetrashvili, Z, Albertsmeier, M, Lederhuber, H, Loeffler, MW, Acquah, DK, Ofori, B, Tabiri, S, Metallidis, S, Tsoulfas, G, Aguilera-Arevalo, M-L, Recinos, G, Mersich, T, Wettstein, D, Ghosh, D, Kembuan, G, Milan, PB, Khosravi, MH, Mozafari, M, Hilmi, A, Mohan, H, Zmora, O, Gallo, G, Pellino, G, Fujimoto, Y, Kuroda, N, Satoi, S, Abou Chaar, MK, Ayasra, F, Fakhradiyev, I, Hamdun, IHS, Jin-Young, J, Jamal, M, Karout, L, Gulla, A, Rasoaherinomenjanahary, F, Samison, LH, Roslani, AC, Duran Sanchez, II, Samantha Gonzalez, D, Martinez, L, Jose Martinez, M, Nayen, A, Ramos-De la Medina, A, Nunez, J, Nashidengo, PR, Shah, R, Shrestha, AL, Jonker, P, Noltes, M, Steinkamp, P, Wright, D, Abdur-Rahman, L, Adisa, A, Osinaike, B, Seyi-Olajide, J, Williams, O, Williams, E, Pejkova, S, Al Balushi, Z, Qureshi, AU, Mohsen, MA, Abukhalaf, SA, 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Corella, F, Ripolles-Melchor, J, Sanz-Gonzalez, R, Alcaraz Fuentes, M, Fernandez Martin, MT, Calvo Espino, P, Carrasco Prats, M, Fernandez-Lopez, A-J, Garcia Escudero, D, Garcia Soria, V, Martinez Alonso, JA, Ruiz-Marin, M, Gomez Perez, B, Moya-Angeler, J, Fernandez Martinez, D, Llaquet Bayo, H, Colas-Ruiz, E, Bella Romera, S, Gavalda Pellice, MT, Jorda Sole, M, Ruiz Velasquez, EJ, Nunez, B, Jimenez, R, Zabaleta, J, Jose Gonzalez-Gimeno, M, Ortega Vazquez, I, Perez Ferrer, A, Martin-Laez, R, Moreno Suarez, M, Freiria Eiras, MA, Ramallo-Solis, I, Gomez-Rosado, J-C, Oliver Guillen, JR, Achalandabaso Boira, M, Catala Bauset, JC, Domenech, J, Badenes, R, Carlos Bernal-Sprekelsen, J, Sancho-Muriel, J, De Andres-Asenjo, B, Tejero-Pintor, FJ, Vallve-Bernal, M, and Vazquez Melero, A

Abstract

We aimed to determine the impact of pre-operative isolation on postoperative pulmonary complications after elective surgery during the global SARS-CoV-2 pandemic. We performed an international prospective cohort study including patients undergoing elective surgery in October 2020. Isolation was defined as the period before surgery during which patients did not leave their house or receive visitors from outside their household. The primary outcome was postoperative pulmonary complications, adjusted in multivariable models for measured confounders. Pre-defined sub-group analyses were performed for the primary outcome. A total of 96,454 patients from 114 countries were included and overall, 26,948 (27.9%) patients isolated before surgery. Postoperative pulmonary complications were recorded in 1947 (2.0%) patients of which 227 (11.7%) were associated with SARS-CoV-2 infection. Patients who isolated pre-operatively were older, had more respiratory comorbidities and were more commonly from areas of high SARS-CoV-2 incidence and high-income countries. Although the overall rates of postoperative pulmonary complications were similar in those that isolated and those that did not (2.1% vs 2.0%, respectively), isolation was associated with higher rates of postoperative pulmonary complications after adjustment (adjusted OR 1.20, 95%CI 1.05-1.36, p = 0.005). Sensitivity analyses revealed no further differences when patients were categorised by: pre-operative testing; use of COVID-19-free pathways; or community SARS-CoV-2 prevalence. The rate of postoperative pulmonary complications increased with periods of isolation longer than 3 days, with an OR (95%CI) at 4-7 days or ≥ 8 days of 1.25 (1.04-1.48), p = 0.015 and 1.31 (1.11-1.55), p = 0.001, respectively. Isolation before elective surgery might be associated with a small but clinically important increased risk of postoperative pulmonary complications. Longer periods of isolation showed no reduction in the risk of postoperative pu

Published
2021

44. Diagnostic instruments for autism spectrum disorder (ASD)

Author

Vllasaliu, Leonora, additional, Jensen, Katrin, additional, Hoss, Stephanie, additional, Landenberger, Marie, additional, Menze, Marianne, additional, Schütz, Magdalena, additional, Ufniarz, Krystyna, additional, Kieser, Meinhard, additional, and Freitag, Christine M, additional

Published
2021
Full Text
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50. Optimal sample size allocation and go/no-go decision rules for phase II/III programs where several phase III trials are performed

Author

Marietta Kirchner, Meinhard Kieser, and Stella Preussler

Subjects
Statistics and Probability, Integrated business planning, Mathematical optimization, Phase iii trials, Generalization, Computer science, Clinical Decision-Making, General Medicine, Decision rule, Biostatistics, 01 natural sciences, Phase (combat), Variable cost, 010104 statistics & probability, 03 medical and health sciences, Clinical Trials, Phase II as Topic, 0302 clinical medicine, Clinical Trials, Phase III as Topic, Sample size determination, Sample Size, Go/no go, Humans, 030212 general & internal medicine, 0101 mathematics, Statistics, Probability and Uncertainty
Abstract

The conduct of phase II and III programs is costly, time-consuming and, due to high failure rates in late development stages, risky. There is a strong connection between phase II and III trials as the go/no-go decision and the sample size chosen for phase III are based on the results observed in phase II. An integrated planning of phase II and III is therefore reasonable. The success of phase II/III programs crucially depends on the allocation of the resources to phase II and III in terms of sample size and the rule applied to decide whether to stop or to proceed with phase III. Recently, a utility-based approach was proposed, where optimal planning of phase II/III programs is achieved by taking fixed and variable costs of the drug development program and potential gains after a successful launch into account. However, this method is restricted to programs with a single phase III trial, while regulatory authorities usually require statistical significance in two or more phase III trials. We present a generalization of this procedure to programs where two or more phase III trials are performed. Optimal phase II sample sizes and go/no-go decision rules are provided for time-to-event outcomes and cases, where at least one, two, or three phase III trials need to be successful. Different drug development program strategies (e.g. one large vs. two phase III trials) are compared within these different cases. Application to practical examples typically met in oncology trials illustrates the proposed method.

Published
2018

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