Comparison of techniques for handling missing covariate data within prognostic modelling studies: a simulation study

Background: There is no consensus on the most appropriate approach to handle missing covariate data within prognostic modelling studies. Therefore a simulation study was performed to assess the effects of different missing data techniques on the performance of a prognostic model. Methods: Datasets were generated to resemble the skewed distributions seen in a motivating breast cancer example. Multivariate missing data were imposed on four covariates using four different mechanisms; missing completely at random (MCAR), missing at random (MAR), missing not at random (MNAR) and a combination of all three mechanisms. Five amounts of incomplete cases from 5% to 75% were considered. Complete case analysis (CC), single imputation (SI) and five multiple imputation (MI) techniques available within the R statistical software were investigated: a) data augmentation (DA) approach assuming a multivariate normal distribution, b) DA assuming a general location model, c) regression switching imputation, d) regression switching with predictive mean matching (MICE-PMM) and e) flexible additive imputation models. A Cox proportional hazards model was fitted and appropriate estimates for the regression coefficients and model performance measures were obtained. Results: Performing a CC analysis produced unbiased regression estimates, but inflated standard errors, which affected the significance of the covariates in the model with 25% or more missingness. Using SI, underestimated the variability; resulting in poor coverage even with 10% missingness. Of the MI approaches, applying MICE-PMM produced, in general, the least biased estimates and better coverage for the incomplete covariates and better model performance for all mechanisms. However, this MI approach still produced biased regression coefficient estimates for the incomplete skewed continuous covariates when 50% or more cases had missing data imposed with a MCAR, MAR or combined mechanism. When the missingness depended on the incomplete covariates, i.e. MNAR, estimates were biased with more than 10% incomplete cases for all MI approaches. Conclusion: The results from this simulation study suggest that performing MICE-PMM may be the preferred MI approach provided that less than 50% of the cases have missing data and the missing data are not MNAR

Imputation strategies for missing binary outcomes in cluster randomized trials

<p>Abstract</p> <p>Background</p> <p>Attrition, which leads to missing data, is a common problem in cluster randomized trials (CRTs), where groups of patients rather than individuals are randomized. Standard multiple imputation (MI) strategies may not be appropriate to impute missing data from CRTs since they assume independent data. In this paper, under the assumption of missing completely at random and covariate dependent missing, we compared six MI strategies which account for the intra-cluster correlation for missing binary outcomes in CRTs with the standard imputation strategies and complete case analysis approach using a simulation study.</p> <p>Method</p> <p>We considered three within-cluster and three across-cluster MI strategies for missing binary outcomes in CRTs. The three within-cluster MI strategies are logistic regression method, propensity score method, and Markov chain Monte Carlo (MCMC) method, which apply standard MI strategies within each cluster. The three across-cluster MI strategies are propensity score method, random-effects (RE) logistic regression approach, and logistic regression with cluster as a fixed effect. Based on the community hypertension assessment trial (CHAT) which has complete data, we designed a simulation study to investigate the performance of above MI strategies.</p> <p>Results</p> <p>The estimated treatment effect and its 95% confidence interval (CI) from generalized estimating equations (GEE) model based on the CHAT complete dataset are 1.14 (0.76 1.70). When 30% of binary outcome are missing completely at random, a simulation study shows that the estimated treatment effects and the corresponding 95% CIs from GEE model are 1.15 (0.76 1.75) if complete case analysis is used, 1.12 (0.72 1.73) if within-cluster MCMC method is used, 1.21 (0.80 1.81) if across-cluster RE logistic regression is used, and 1.16 (0.82 1.64) if standard logistic regression which does not account for clustering is used.</p> <p>Conclusion</p> <p>When the percentage of missing data is low or intra-cluster correlation coefficient is small, different approaches for handling missing binary outcome data generate quite similar results. When the percentage of missing data is large, standard MI strategies, which do not take into account the intra-cluster correlation, underestimate the variance of the treatment effect. Within-cluster and across-cluster MI strategies (except for random-effects logistic regression MI strategy), which take the intra-cluster correlation into account, seem to be more appropriate to handle the missing outcome from CRTs. Under the same imputation strategy and percentage of missingness, the estimates of the treatment effect from GEE and RE logistic regression models are similar.</p

Sialic Acid Glycobiology Unveils Trypanosoma cruzi Trypomastigote Membrane Physiology.

Trypanosoma cruzi, the flagellate protozoan agent of Chagas disease or American trypanosomiasis, is unable to synthesize sialic acids de novo. Mucins and trans-sialidase (TS) are substrate and enzyme, respectively, of the glycobiological system that scavenges sialic acid from the host in a crucial interplay for T. cruzi life cycle. The acquisition of the sialyl residue allows the parasite to avoid lysis by serum factors and to interact with the host cell. A major drawback to studying the sialylation kinetics and turnover of the trypomastigote glycoconjugates is the difficulty to identify and follow the recently acquired sialyl residues. To tackle this issue, we followed an unnatural sugar approach as bioorthogonal chemical reporters, where the use of azidosialyl residues allowed identifying the acquired sugar. Advanced microscopy techniques, together with biochemical methods, were used to study the trypomastigote membrane from its glycobiological perspective. Main sialyl acceptors were identified as mucins by biochemical procedures and protein markers. Together with determining their shedding and turnover rates, we also report that several membrane proteins, including TS and its substrates, both glycosylphosphatidylinositol-anchored proteins, are separately distributed on parasite surface and contained in different and highly stable membrane microdomains. Notably, labeling for α(1,3)Galactosyl residues only partially colocalize with sialylated mucins, indicating that two species of glycosylated mucins do exist, which are segregated at the parasite surface. Moreover, sialylated mucins were included in lipid-raft-domains, whereas TS molecules are not. The location of the surface-anchored TS resulted too far off as to be capable to sialylate mucins, a role played by the shed TS instead. Phosphatidylinositol-phospholipase-C activity is actually not present in trypomastigotes. Therefore, shedding of TS occurs via microvesicles instead of as a fully soluble form

Perspective from a Younger Generation -- The Astro-Spectroscopy of Gisbert Winnewisser

Gisbert Winnewisser's astronomical career was practically coextensive with the whole development of molecular radio astronomy. Here I would like to pick out a few of his many contributions, which I, personally, find particularly interesting and put them in the context of newer results.Comment: 14 pages. (Co)authored by members of the MPIfR (Sub)millimeter Astronomy Group. To appear in the Proceedings of the 4th Cologne-Bonn-Zermatt-Symposium "The Dense Interstellar Medium in Galaxies" eds. S. Pfalzner, C. Kramer, C. Straubmeier, & A. Heithausen (Springer: Berlin

Cost-effectiveness of problem-solving treatment in comparison with usual care for primary care patients with menthal health problems: a randomized trial

BACKGROUND: Mental health problems are common and are associated with increased disability and health care costs. Problem-Solving Treatment (PST) delivered to these patients by nurses in primary care might be efficient. The aim of this study was to evaluate the cost-effectiveness of PST by mental health nurses compared with usual care (UC) by the general practitioner for primary care patients with mental health problems. METHODS: An economic evaluation from a societal perspective was performed alongside a randomized clinical trial. Patients with a positive General Health Questionnaire score (score ≥ 4) and who visited their general practitioner at least three times during the past 6 months were eligible. Outcome measures were improvement on the Hospital Anxiety and Depression Scale and QALYs based on the EQ-5D. Resource use was measured using a validated questionnaire. Missing cost and effect data were imputed using multiple imputation techniques. Bootstrapping was used to analyze costs and cost-effectiveness of PST compared with UC. RESULTS: There were no statistically significant differences in clinical outcomes at 9 months. Mean total costs were €4795 in the PST group and €6857 in the UC group. Costs were not statistically significantly different between the two groups (95% CI -4698;359). The cost-effectiveness analysis showed that PST was cost-effective in comparison with UC. Sensitivity analyses confirmed these findings. CONCLUSIONS: PST delivered by nurses seems cost-effective in comparison with UC. However, these results should be interpreted with caution, since the difference in total costs was mainly caused by 3 outliers with extremely high indirect costs in the UC group. TRIAL REGISTRATION: Nederlands Trial Register ISRCTN5102101

Higher-order multipole amplitudes in charmonium radiative transitions

Using 24 million $\psi' \equiv \psi(2S)$ decays in CLEO-c, we have searched for higher multipole admixtures in electric-dipole-dominated radiative transitions in charmonia. We find good agreement between our data and theoretical predictions for magnetic quadrupole (M2) amplitudes in the transitions $\psi' \to \gamma \chi_{c1,2}$ and $\chi_{c1,2} \to \gamma J/\psi$, in striking contrast to some previous measurements. Let $b_2^J$ and $a_2^J$ denote the normalized M2 amplitudes in the respective aforementioned decays, where the superscript $J$ refers to the angular momentum of the $\chi_{cJ}$. By performing unbinned maximum likelihood fits to full five-parameter angular distributions, we determine the ratios $a_2^{J=1}/a_2^{J=2} = 0.67^{+0.19}_{-0.13}$ and $a_2^{J=1}/b_2^{J=1} = -2.27^{+0.57}_{-0.99}$, where the theoretical predictions are independent of the charmed quark magnetic moment and are $a_2^{J=1}/a_2^{J=2} = 0.676 \pm 0.071$ and $a_2^{J=1}/b_2^{J=1} = -2.27 \pm 0.16$.Comment: 32 pages, 7 figures, acceptance updat

Dalitz Plot Analysis of Ds to K+K-pi+

We perform a Dalitz plot analysis of the decay Ds to K+K-pi+ with the CLEO-c data set of 586/pb of e+e- collisions accumulated at sqrt(s) = 4.17 GeV. This corresponds to about 0.57 million D_s+D_s(*)- pairs from which we select 14400 candidates with a background of roughly 15%. In contrast to previous measurements we find good agreement with our data only by including an additional f_0(1370)pi+ contribution. We measure the magnitude, phase, and fit fraction of K*(892) K+, phi(1020)pi+, K0*(1430)K+, f_0(980)pi+, f_0(1710)pi+, and f_0(1370)pi+ contributions and limit the possible contributions of other KK and Kpi resonances that could appear in this decay.Comment: 21 Pages,available through http://www.lns.cornell.edu/public/CLNS/, submitted to PR