Combining estimates of interest in prognostic modelling studies after multiple imputation: current practice and guidelines

Background: Multiple imputation (MI) provides an effective approach to handle missing covariate data within prognostic modelling studies, as it can properly account for the missing data uncertainty. The multiply imputed datasets are each analysed using standard prognostic modelling techniques to obtain the estimates of interest. The estimates from each imputed dataset are then combined into one overall estimate and variance, incorporating both the within and between imputation variability. Rubin's rules for combining these multiply imputed estimates are based on asymptotic theory. The resulting combined estimates may be more accurate if the posterior distribution of the population parameter of interest is better approximated by the normal distribution. However, the normality assumption may not be appropriate for all the parameters of interest when analysing prognostic modelling studies, such as predicted survival probabilities and model performance measures. Methods: Guidelines for combining the estimates of interest when analysing prognostic modelling studies are provided. A literature review is performed to identify current practice for combining such estimates in prognostic modelling studies. Results: Methods for combining all reported estimates after MI were not well reported in the current literature. Rubin's rules without applying any transformations were the standard approach used, when any method was stated. Conclusion: The proposed simple guidelines for combining estimates after MI may lead to a wider and more appropriate use of MI in future prognostic modelling studies

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

Infectious Disease Ontology

Technological developments have resulted in tremendous increases in the volume and diversity of the data and information that must be processed in the course of biomedical and clinical research and practice. Researchers are at the same time under ever greater pressure to share data and to take steps to ensure that data resources are interoperable. The use of ontologies to annotate data has proven successful in supporting these goals and in providing new possibilities for the automated processing of data and information. In this chapter, we describe different types of vocabulary resources and emphasize those features of formal ontologies that make them most useful for computational applications. We describe current uses of ontologies and discuss future goals for ontology-based computing, focusing on its use in the field of infectious diseases. We review the largest and most widely used vocabulary resources relevant to the study of infectious diseases and conclude with a description of the Infectious Disease Ontology (IDO) suite of interoperable ontology modules that together cover the entire infectious disease domain

Comparison of imputation methods for handling missing covariate data when fitting a Cox proportional hazards model: a resampling study

<p>Abstract</p> <p>Background</p> <p>The appropriate handling of missing covariate data in prognostic modelling studies is yet to be conclusively determined. A resampling study was performed to investigate the effects of different missing data methods on the performance of a prognostic model.</p> <p>Methods</p> <p>Observed data for 1000 cases were sampled with replacement from a large complete dataset of 7507 patients to obtain 500 replications. Five levels of missingness (ranging from 5% to 75%) were imposed on three covariates using a missing at random (MAR) mechanism. Five missing data methods were applied; a) complete case analysis (CC) b) single imputation using regression switching with predictive mean matching (SI), c) multiple imputation using regression switching imputation, d) multiple imputation using regression switching with predictive mean matching (MICE-PMM) and e) multiple imputation using flexible additive imputation models. A Cox proportional hazards model was fitted to each dataset and estimates for the regression coefficients and model performance measures obtained.</p> <p>Results</p> <p>CC produced biased regression coefficient estimates and inflated standard errors (SEs) with 25% or more missingness. The underestimated SE after SI resulted in poor coverage with 25% or more missingness. Of the MI approaches investigated, MI using MICE-PMM produced the least biased estimates and better model performance measures. However, this MI approach still produced biased regression coefficient estimates with 75% missingness.</p> <p>Conclusions</p> <p>Very few differences were seen between the results from all missing data approaches with 5% missingness. However, performing MI using MICE-PMM may be the preferred missing data approach for handling between 10% and 50% MAR missingness.</p

A Mycobacterial Enzyme Essential for Cell Division Synergizes with Resuscitation-Promoting Factor

The final stage of bacterial cell division requires the activity of one or more enzymes capable of degrading the layers of peptidoglycan connecting two recently developed daughter cells. Although this is a key step in cell division and is required by all peptidoglycan-containing bacteria, little is known about how these potentially lethal enzymes are regulated. It is likely that regulation is mediated, at least partly, through protein–protein interactions. Two lytic transglycosylases of mycobacteria, known as resuscitation-promoting factor B and E (RpfB and RpfE), have previously been shown to interact with the peptidoglycan-hydrolyzing endopeptidase, Rpf-interacting protein A (RipA). These proteins may form a complex at the septum of dividing bacteria. To investigate the function of this potential complex, we generated depletion strains in M. smegmatis. Here we show that, while depletion of rpfB has no effect on viability or morphology, ripA depletion results in a marked decrease in growth and formation of long, branched chains. These growth and morphological defects could be functionally complemented by the M. tuberculosis ripA orthologue (rv1477), but not by another ripA-like orthologue (rv1478). Depletion of ripA also resulted in increased susceptibility to the cell wall–targeting β-lactams. Furthermore, we demonstrate that RipA has hydrolytic activity towards several cell wall substrates and synergizes with RpfB. These data reveal the unusual essentiality of a peptidoglycan hydrolase and suggest a novel protein–protein interaction as one way of regulating its activity

Cloxacillin versus vancomycin for presumed late-onset sepsis in the Neonatal Intensive Care Unit and the impact upon outcome of coagulase negative staphylococcal bacteremia: a retrospective cohort study

BACKGROUND: Coagulase negative staphylococcus (CONS) is the main cause of late-onset sepsis in Neonatal Intensive Care Units (NICU). Although CONS rarely causes fulminant sepsis, vancomycin is frequently used as empiric therapy. Indiscriminate use of vancomycin has been linked to the emergence of vancomycin resistant organisms. The objective of this study was to compare duration of CONS sepsis and mortality before and after implementation of a policy of selective vancomycin use and compare use of vancomycin between the 2 time periods. METHODS: A retrospective study was conducted of infants ≥4 days old, experiencing signs of sepsis with a first positive blood culture for CONS, during two 12-month periods. Late-onset sepsis was treated empirically with vancomycin and gentamicin during period 1, and cloxacillin and gentamicin during period 2. The confidence interval method was used to assess non-inferiority of the outcomes between the two study groups. RESULTS: There were 45 episodes of CONS sepsis during period 1 and 37 during period 2. Duration of sepsis was similar between periods (hazard ratio of 1.00, 95%CI: 0.64, 1.57). One death during period 2 was possibly related to CONS sepsis versus none in period 1. Vancomycin was used in 97.8% of episodes in period 1 versus 81.1% of episodes in period 2. CONCLUSION: Although we failed to show non-inferiority of duration of sepsis in the cloxacillin and gentamicin group compared to the vancomycin and gentamicin group, duration of sepsis was clinically similar. Restricting vancomycin for confirmed cases of CONS sepsis resistant to oxacillin appears effective and safe, and significantly reduces vancomycin use in the NICU

A non-randomised, single-centre comparison of induction chemotherapy followed by radiochemotherapy versus concomitant chemotherapy with hyperfractionated radiotherapy in inoperable head and neck carcinomas

BACKGROUND: The application of induction chemotherapy failed to provide a consistent benefit for local control in primary treatment of advanced head and neck (H&N) cancers. The aim of this study was to compare the results of concomitant application of radiochemotherapy for treating locally advanced head-and-neck carcinoma in comparison with the former standard of sequential radiochemotherapy. METHODS: Between 1987 and 1995 we treated 122 patients with unresectable (stage IV head and neck) cancer by two different protocols. The sequential protocol (SEQ; 1987–1992) started with two courses of neoadjuvant chemotherapy (cisplatin [CDDP] + 120-h continuous infusions (c.i.) of folinic acid [FA] and 5-fluorouracil [5-FU]), followed by a course of radiochemotherapy using conventional fractionation up to 70 Gy. The concomitant protocol (CON; since 1993) combined two courses of FA/5-FU c.i. plus mitomycin (MMC) concomitantly with a course of radiotherapy up to 30 Gy in conventional fractionation, followed by a hyperfractionated course up to 72 Gy. Results from the two groups were compared. RESULTS: Patient and tumor characteristics were balanced (SEQ = 70, CON = 52 pts.). Mean radiation dose achieved (65.3 Gy vs. 71.6 Gy, p = 0.00), response rates (67 vs. 90 % for primary, p = 0.02), and local control (LC; 17.6% vs. 41%, p = 0.03), were significantly lower in the SEQ group, revealing a trend towards lower disease-specific (DSS; 19.8% vs. 31.4%, p = 0.08) and overall (14.7% vs. 23.7%, p = 0.11) survival rates after 5 years. Mucositis grades III and IV prevailed in the CON group (54% versus 44%). Late toxicity was similar in both groups. CONCLUSION: Concurrent chemotherapy seemed more effective in treating head and neck tumors than induction chemotherapy followed by chemoradiation, resulting in better local control and a trend towards improved survival

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

Analysis of urinary oligosaccharides in lysosomal storage disorders by capillary high-performance anion-exchange chromatography–mass spectrometry

Many lysosomal storage diseases are characterized by an increased urinary excretion of glycoconjugates and oligosaccharides that are characteristic for the underlying enzymatic defect. Here, we have used capillary high-performance anion-exchange chromatography (HPAEC) hyphenated to mass spectrometry to analyze free oligosaccharides from urine samples of patients suffering from the lysosomal storage disorders fucosidosis, α-mannosidosis, GM1-gangliosidosis, GM2-gangliosidosis, and sialidosis. Glycan fingerprints were registered, and the patterns of accumulated oligosaccharides were found to reflect the specific blockages of the catabolic pathway. Our analytical approach allowed structural analysis of the excreted oligosaccharides and revealed several previously unpublished oligosaccharides. In conclusion, using online coupling of HPAEC with mass spectrometric detection, our study provides characteristic urinary oligosaccharide fingerprints with diagnostic potential for lysosomal storage disorders

Immediate Outcome Indicators in Perioperative Care: A Controlled Intervention Study on Quality Improvement in Hospitals in Tanzania.

Outcome assessment is the standard for evaluating the quality of health services worldwide. In this study, outcome has been divided into immediate and final outcome. Aim was to compare an intervention hospital with a Continuous Quality Improvement approach to a control group using benchmark assessments of immediate outcome indicators in surgical care. Results were compared to final outcome indicators. Surgical care quality in six hospitals in Tanzania was assessed from 2006-2011, using the Hospital Performance Assessment Tool. Independent observers assessed structural, process and outcome quality using checklists based on evidence-based guidelines. The number of surgical key procedures over the benchmark of 80% was compared between the intervention hospital and the control group. Results were compared to Case Fatality Rates. In the intervention hospital, in 2006, two of nine key procedures reached the benchmark, one in 2009, and four in 2011. In the control group, one of nine key procedures reached the benchmark in 2006, one in 2009, and none in 2011. Case Fatality Rate for all in-patients in the intervention hospital was 5.5% (n = 12,530) in 2006, 3.5% (n = 21,114) in 2009 and 4.6% (n = 18,840) in 2011. In the control group it was 3.1% (n = 17,827) in 2006, 4.2% (n = 13,632) in 2009 and 3.8% (n = 17,059) in 2011. Results demonstrated that quality assurance improved performance levels in both groups. After the introduction of Continuous Quality Improvement, performance levels improved further in the intervention hospital while quality in the district hospital did not. Immediate outcome indicators appeared to be a better steering tool for quality improvement compared to final outcome indicators. Immediate outcome indicators revealed a need for improvement in pre- and postoperative care. Quality assurance programs based on immediate outcome indicators can be effective if embedded in Continuous Quality Improvement. Nevertheless, final outcome indicators cannot be neglected