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

BACKGROUND: Observational data on composite scores often comes with missing component information. When a complete-case (CC) analysis of composite scores is unbiased, preferable approaches of dealing with missing component information should also be unbiased and provide a more precise estimate. We assessed the performance of several methods compared to CC analysis in estimating the means of common composite scores used in axial spondyloarthritis research. METHODS: Individual mean imputation (IMI), the modified formula method (MF), overall mean imputation (OMI), and multiple imputation of missing component values (MI) were assessed either analytically or by means of simulations from available data collected across Europe. Their performance in estimating the means of the Bath Ankylosing Spondylitis Disease Activity Index (BASDAI), the Bath Ankylosing Spondylitis Functional Index (BASFI), and the Ankylosing Spondylitis Disease Activity Score based on C-reactive protein (ASDAS-CRP) in cases where component information was set missing completely at random was compared to the CC approach based on bias, variance, and coverage. RESULTS: Like the MF method, IMI uses a modified formula for observations with missing components resulting in modified composite scores. In the case of an unbiased CC approach, these two methods yielded representative samples of the distribution arising from a mixture of the original and modified composite scores, which, however, could not be considered the same as the distribution of the original score. The IMI and MF method are, thus, intrinsically biased. OMI provided an unbiased mean but displayed a complex dependence structure among observations that, if not accounted for, resulted in severe coverage issues. MI improved precision compared to CC and gave unbiased means and proper coverage as long as the extent of missingness was not too large. CONCLUSIONS: MI of missing component values was the only method found successful in retaining CC's unbiasedness and in providing increased precision for estimating the means of BASDAI, BASFI, and ASDAS-CRP. However, since MI is susceptible to incorrect implementation and its performance may become questionable with increasing missingness, we consider the implementation of an error-free CC approach a valid and valuable option. TRIAL REGISTRATION: Not applicable as study uses data from patient registries.

• MeSH
• Spondylitis, Ankylosing MeSH
• Axial Spondyloarthritis * MeSH
• C-Reactive Protein analysis   MeSH
• Data Interpretation, Statistical MeSH
• Humans MeSH
• Severity of Illness Index MeSH
• Research Design MeSH
• Bias MeSH
• Check Tag
• Humans MeSH
• Publication type
• Journal Article MeSH
• Geographicals
• Europe MeSH

Genomic selection (GS) potentially offers an unparalleled advantage over traditional pedigree-based selection (TS) methods by reducing the time commitment required to carry out a single cycle of tree improvement. This quality is particularly appealing to tree breeders, where lengthy improvement cycles are the norm. We explored the prospect of implementing GS for interior spruce (Picea engelmannii × glauca) utilizing a genotyped population of 769 trees belonging to 25 open-pollinated families. A series of repeated tree height measurements through ages 3-40 years permitted the testing of GS methods temporally. The genotyping-by-sequencing (GBS) platform was used for single nucleotide polymorphism (SNP) discovery in conjunction with three unordered imputation methods applied to a data set with 60% missing information. Further, three diverse GS models were evaluated based on predictive accuracy (PA), and their marker effects. Moderate levels of PA (0.31-0.55) were observed and were of sufficient capacity to deliver improved selection response over TS. Additionally, PA varied substantially through time accordingly with spatial competition among trees. As expected, temporal PA was well correlated with age-age genetic correlation (r=0.99), and decreased substantially with increasing difference in age between the training and validation populations (0.04-0.47). Moreover, our imputation comparisons indicate that k-nearest neighbor and singular value decomposition yielded a greater number of SNPs and gave higher predictive accuracies than imputing with the mean. Furthermore, the ridge regression (rrBLUP) and BayesCπ (BCπ) models both yielded equal, and better PA than the generalized ridge regression heteroscedastic effect model for the traits evaluated.

• MeSH
• Genotype MeSH
• Genotyping Techniques methods   MeSH
• Polymorphism, Single Nucleotide MeSH
• Models, Genetic * MeSH
• Genetics, Population MeSH
• Selection, Genetic * MeSH
• Picea genetics   MeSH
• Publication type
• Journal Article MeSH
• Research Support, Non-U.S. Gov't MeSH
• Comparative Study MeSH
• Geographicals
• British Columbia MeSH

• MeSH
• Survival MeSH
• Regression Analysis MeSH
• Research statistics & numerical data   MeSH

• Conspectus
• Kombinatorika. Teorie grafů. Matematická statistika. Operační výzkum. Matematické modelování
• NML Fields
• přírodní vědy
• NML Publication type
• kolektivní monografie

INTRODUCTION: Recent advances in machine learning provide new possibilities to process and analyse observational patient data to predict patient outcomes. In this paper, we introduce a data processing pipeline for cardiogenic shock (CS) prediction from the MIMIC III database of intensive cardiac care unit patients with acute coronary syndrome. The ability to identify high-risk patients could possibly allow taking pre-emptive measures and thus prevent the development of CS. METHODS: We mainly focus on techniques for the imputation of missing data by generating a pipeline for imputation and comparing the performance of various multivariate imputation algorithms, including k-nearest neighbours, two singular value decomposition (SVD)-based methods, and Multiple Imputation by Chained Equations. After imputation, we select the final subjects and variables from the imputed dataset and showcase the performance of the gradient-boosted framework that uses a tree-based classifier for cardiogenic shock prediction. RESULTS: We achieved good classification performance thanks to data cleaning and imputation (cross-validated mean area under the curve 0.805) without hyperparameter optimization. CONCLUSION: We believe our pre-processing pipeline would prove helpful also for other classification and regression experiments.

• Publication type
• Journal Article MeSH

BACKGROUND: To describe the 6-year safety and efficacy of etanercept (ETN) in children with extended oligoarticular juvenile idiopathic arthritis (eoJIA), enthesitis-related arthritis (ERA), and psoriatic arthritis (PsA) METHODS: Patients who completed the 2-year, open-label, phase III CLinical Study In Pediatric Patients of Etanercept for Treatment of ERA, PsA, and Extended Oligoarthritis (CLIPPER) were allowed to enroll in its 8-year long-term extension (CLIPPER2). Children received ETN at a once-weekly dose of 0.8 mg/kg, up to a maximum dose of 50 mg/week. Efficacy assessments included the JIA core set of outcomes, the JIA American College of Rheumatology response criteria (JIA-ACR), and the Juvenile Arthritis Disease Activity Score (JADAS). Efficacy data are reported as responder analyses using a hybrid method for missing data imputation and as observed cases. Safety assessments included treatment-emergent adverse events (TEAEs). RESULTS: Out of 127 patients originally enrolled in CLIPPER, 109 (86%) entered CLIPPER2. After 6 years of trial participation (2 years in CLIPPER and 4 years in CLIPPER2), 41 (32%) patients were still taking ETN, 13 (11%) entered the treatment withdrawal phase after achieving low/inactive disease (of whom 7 had to restart ETN), 36 (28%) discontinued treatment for other reasons but are still being observed, and 37 (29%) discontinued treatment permanently. According to the hybrid imputation analysis, proportions of patients achieving JIA ACR90, JIA ACR100, and JADAS inactive disease after the initial 2 years of treatment were 58%, 48%, and 32%, respectively. After the additional 4 years, those proportions in patients who remained in the trial were 46%, 35%, and 24%. Most frequently reported TEAEs [n (%), events per 100 patient-years] were headache [28 (22%), 5.3], arthralgia [24 (19%), 4.6], and pyrexia [20 (16%), 3.8]. Number and frequency of TEAEs, excluding infections and injection site reactions, decreased over the 6-year period from 193 and 173.8, respectively, during year 1 to 37 and 61.3 during year 6. A single case of malignancy (Hodgkin's lymphoma) and no cases of active tuberculosis, demyelinating disorders, or deaths were reported. CONCLUSIONS: Open-label etanercept treatment for up to 6 years was safe, well tolerated, and effective in patients with eoJIA, ERA, and PsA. TRIAL REGISTRATION: ClinicalTrials.gov: CLIPPER, NCT00962741 , registered 20 August, 2009, CLIPPER2, NCT01421069 , registered 22 August, 2011.

• MeSH
• Antirheumatic Agents therapeutic use   MeSH
• Child MeSH
• Etanercept therapeutic use   MeSH
• Arthritis, Juvenile drug therapy   MeSH
• Humans MeSH
• Adolescent MeSH
• Child, Preschool MeSH
• Treatment Outcome MeSH
• Check Tag
• Child MeSH
• Humans MeSH
• Adolescent MeSH
• Male MeSH
• Child, Preschool MeSH
• Female MeSH
• Publication type
• Journal Article MeSH
• Clinical Trial, Phase III MeSH
• Research Support, Non-U.S. Gov't MeSH

BACKGROUND: Somatic EGFR mutations define a subset of non-small cell lung cancers (NSCLC) that have clinical impact on NSCLC risk and outcome. However, EGFR-mutation-status is often missing in epidemiologic datasets. We developed and tested pragmatic approaches to account for EGFR-mutation-status based on variables commonly included in epidemiologic datasets and evaluated the clinical utility of these approaches. METHODS: Through analysis of the International Lung Cancer Consortium (ILCCO) epidemiologic datasets, we developed a regression model for EGFR-status; we then applied a clinical-restriction approach using the optimal cut-point, and a second epidemiologic, multiple imputation approach to ILCCO survival analyses that did and did not account for EGFR-status. RESULTS: Of 35,356 ILCCO patients with NSCLC, EGFR-mutation-status was available in 4,231 patients. A model regressing known EGFR-mutation-status on clinical and demographic variables achieved a concordance index of 0.75 (95% CI, 0.74-0.77) in the training and 0.77 (95% CI, 0.74-0.79) in the testing dataset. At an optimal cut-point of probability-score = 0.335, sensitivity = 69% and specificity = 72.5% for determining EGFR-wildtype status. In both restriction-based and imputation-based regression analyses of the individual roles of BMI on overall survival of patients with NSCLC, similar results were observed between overall and EGFR-mutation-negative cohort analyses of patients of all ancestries. However, our approach identified some differences: EGFR-mutated Asian patients did not incur a survival benefit from being obese, as observed in EGFR-wildtype Asian patients. CONCLUSIONS: We introduce a pragmatic method to evaluate the potential impact of EGFR-status on epidemiological analyses of NSCLC. IMPACT: The proposed method is generalizable in the common occurrence in which EGFR-status data are missing.

• MeSH
• Survival Analysis MeSH
• ErbB Receptors genetics   MeSH
• Humans MeSH
• Mutation MeSH
• Lung Neoplasms * epidemiology   genetics   MeSH
• Carcinoma, Non-Small-Cell Lung * epidemiology   genetics   MeSH
• Check Tag
• Humans MeSH
• Publication type
• Journal Article MeSH
• Research Support, Non-U.S. Gov't MeSH
• Research Support, N.I.H., Extramural MeSH

• MeSH
• Population MeSH
• Sampling Studies MeSH

• Conspectus
• Statistika
• NML Fields
• statistika, zdravotnická statistika

INTRODUCTION: In a previously published randomised, placebo-controlled trial, 800 mg/day of pharmaceutical-grade chondroitin sulfate (CS) was shown to be superior to placebo in reducing pain and improving function over 6 months in patients with symptomatic knee osteoarthritis (OA). The aim of the current post hoc analyses was to evaluate the cost-effectiveness of CS compared with placebo in a European perspective using individual patient data from this clinical trial. METHODS: Patients with knee OA randomised to CS or placebo were followed up at 1, 3 and 6 months. The algo-functional Lequesne index was used to derive the EuroQol Five-Dimension Five-Level (EQ-5D-5L) score based on a validated formula. The EQ-5D-5L scores at each time point were used to calculate the changes in quality-adjusted life years (QALYs) with the area under the curve method. Costs were assessed using the average price of CS in the countries where the original study took place and where CS is currently marketed. The costs of CS in three countries were then used (i.e. the Czech Republic, Italy and Switzerland). The incremental cost-effectiveness ratio (ICER) threshold for CS to be considered cost-effective was set at 91,870 EUR per QALY (equivalent to the usually recommended threshold of US $100,000). The study used an intention-to-treat population, i.e. patients who received one dose of the study drug, and imputed missing values using the basal observation carried forward method. RESULTS: No significant differences in baseline characteristics were observed between the CS group (N = 199) and the placebo group (N = 205). The mean cost of CS for 6 months of treatment was 194.74 EUR. After 6 months of treatment, CS showed a mean ICER of 33,462 (95% CI 5130-61,794) EUR per QALY gained, indicating cost-effectiveness compared with placebo. The acceptability curve for cost-effectiveness shows that the CS treatment is likely to be cost-effective compared with placebo, with a 93% probability when the ceiling ratio is set at 91,870 EUR per QALY gained. CONCLUSIONS: These results highlight the role of CS as a cost-effective therapeutic option in the management of OA. However, further studies taking into account the use of other healthcare resources are warranted for a more complete understanding.

• MeSH
• Cost-Effectiveness Analysis MeSH
• Cost-Benefit Analysis * MeSH
• Osteoarthritis, Knee * drug therapy   economics   MeSH
• Chondroitin Sulfates * therapeutic use   economics   MeSH
• Quality-Adjusted Life Years * MeSH
• Middle Aged MeSH
• Humans MeSH
• Aged MeSH
• Check Tag
• Middle Aged MeSH
• Humans MeSH
• Male MeSH
• Aged MeSH
• Female MeSH
• Publication type
• Journal Article MeSH
• Multicenter Study MeSH
• Randomized Controlled Trial MeSH
• Geographicals
• Czech Republic MeSH
• Italy MeSH
• Switzerland MeSH

OBJECTIVES: Despite growing interest, the cost-effectiveness of eHealth interventions for supporting quality of life of people with dementia and their caregivers remains unclear. This study evaluated the cost-effectiveness of the FindMyApps intervention, compared to digital care-as-usual. FindMyApps aims to help people with dementia and their caregivers find and learn to use tablet apps that may support social participation and self-management of people with dementia and sense of competence of caregivers. METHOD: A randomised controlled trial (Netherlands Trial Register NL8157) was conducted, including people with mild cognitive impairment (MCI) or mild dementia and their informal caregivers (FindMyApps n = 76, digital care-as-usual n = 74). Outcomes for people with MCI/dementia were Quality-Adjusted Life-Years (QALYs), calculated from EQ-5D-5L data and the Dutch tariff for utility scores, social participation (Maastricht Social Participation Profile) and quality of life (Adult Social Care Outcomes Toolkit), and for caregivers, QALYs and sense of competence (Short Sense of Competence Questionnaire). Societal costs were calculated using data collected with the RUD-lite instrument and the Dutch costing guideline. Multiple imputation was employed to fill in missing cost and effect data. Bootstrapped multilevel models were used to estimate incremental total societal costs and incremental effects between groups which were then used to calculate Incremental Cost-Effectiveness Ratios (ICERs). Cost-effectiveness acceptability curves were estimated. RESULTS: In the FindMyApps group, caregiver SSCQ scores were significantly higher compared to care-as-usual, n = 150, mean difference = 0.75, 95% CI [0.14, 1.38]. Other outcomes did not significantly differ between groups. Total societal costs for people with dementia were not significantly different, n = 150, mean difference = €-774, 95%CI [-2.643, .,079]. Total societal costs for caregivers were significantly lower in the FindMyApps group compared to care-as-usual, n = 150, mean difference = € -392, 95% CI [-1.254, -26], largely due to lower supportive care costs, mean difference = €-252, 95% CI [-1.009, 42]. For all outcomes, the probability that FindMyApps was cost-effective at a willingness-to-pay threshold of €0 per point of improvement was 0.72 for people with dementia and 0.93 for caregivers. CONCLUSION: FindMyApps is a cost-effective intervention for supporting caregivers' sense of competence. Further implementation of FindMyApps is warranted.

• MeSH
• Cost-Benefit Analysis * MeSH
• Dementia * therapy   economics   MeSH
• Cognitive Dysfunction therapy   economics   MeSH
• Quality of Life * MeSH
• Quality-Adjusted Life Years MeSH
• Middle Aged MeSH
• Humans MeSH
• Mobile Applications economics   MeSH
• Caregivers * psychology   economics   MeSH
• Aged, 80 and over MeSH
• Aged MeSH
• Telemedicine * economics   MeSH
• Social Participation MeSH
• Check Tag
• Middle Aged MeSH
• Humans MeSH
• Male MeSH
• Aged, 80 and over MeSH
• Aged MeSH
• Female MeSH
• Publication type
• Journal Article MeSH
• Randomized Controlled Trial MeSH
• Geographicals
• Netherlands MeSH