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

Integrin α6Bβ4 inhibits colon cancer cell proliferation and c-Myc activity

<p>Abstract</p> <p>Background</p> <p>Integrins are known to be important contributors to cancer progression. We have previously shown that the integrin β4 subunit is up-regulated in primary colon cancer. Its partner, the integrin α6 subunit, exists as two different mRNA splice variants, α6A and α6B, that differ in their cytoplasmic domains but evidence for distinct biological functions of these α6 splice variants is still lacking.</p> <p>Methods</p> <p>In this work, we first analyzed the expression of integrin α6A and α6B at the protein and transcript levels in normal human colonic cells as well as colorectal adenocarcinoma cells from both primary tumors and established cell lines. Then, using forced expression experiments, we investigated the effect of α6A and α6B on the regulation of cell proliferation in a colon cancer cell line.</p> <p>Results</p> <p>Using variant-specific antibodies, we observed that α6A and α6B are differentially expressed both within the normal adult colonic epithelium and between normal and diseased colonic tissues. Proliferative cells located in the lower half of the glands were found to predominantly express α6A, while the differentiated and quiescent colonocytes in the upper half of the glands and surface epithelium expressed α6B. A relative decrease of α6B expression was also identified in primary colon tumors and adenocarcinoma cell lines suggesting that the α6A/α6B ratios may be linked to the proliferative status of colonic cells. Additional studies in colon cancer cells showed that experimentally restoring the α6A/α6B balance in favor of α6B caused a decrease in cellular S-phase entry and repressed the activity of c-Myc.</p> <p>Conclusion</p> <p>The findings that the α6Bβ4 integrin is expressed in quiescent normal colonic cells and is significantly down-regulated in colon cancer cells relative to its α6Aβ4 counterpart are consistent with the anti-proliferative influence and inhibitory effect on c-Myc activity identified for this α6Bβ4 integrin. Taken together, these findings point out the importance of integrin variant expression in colon cancer cell biology.</p

Crisis discharges and readmission risk in acute psychiatric male inpatients

<p>Abstract</p> <p>Background</p> <p>Severe pressures on beds in psychiatric services have led to the implementation of an early ("crisis") discharge policy in the Western Cape, South Africa. The study examined the effect of this policy and length of hospital stay (LOS) on readmission rates in one psychiatric hospital in South Africa.</p> <p>Methods</p> <p>Discharge summaries of adult male patients (<it>n </it>= 438) admitted to Stikland Psychiatric Hospital during 2004 were retrospectively examined. Each patient's clinical course was then analysed for the period between January 1^st, 2004, and August 31^st, 2006.</p> <p>Results</p> <p>Although shorter LOS was associated with decreased readmission rates, the effect of crisis discharges was far more powerful. Patients discharged as usual had a far lower risk of readmission than those discharged due to bed pressures (i.e. crisis discharge).</p> <p>Conclusion</p> <p>Increased risks associated with the early discharge policy necessitate the urgent review of the current management of bed shortages in this inpatient facility. The strengthening of community initiatives, particularly assertive outreach could be a way forward.</p

Attribution: how is it relevant for loss and damage policy and practice?

Attribution has become a recurring issue in discussions about Loss and Damage (L&D). In this highly-politicised context, attribution is often associated with responsibility and blame; and linked to debates about liability and compensation. The aim of attribution science, however, is not to establish responsibility, but to further scientific understanding of causal links between elements of the Earth System and society. This research into causality could inform the management of climate-related risks through improved understanding of drivers of relevant hazards, or, more widely, vulnerability and exposure; with potential benefits regardless of political positions on L&D. Experience shows that it is nevertheless difficult to have open discussions about the science in the policy sphere. This is not only a missed opportunity, but also problematic in that it could inhibit understanding of scientific results and uncertainties, potentially leading to policy planning which does not have sufficient scientific evidence to support it. In this chapter, we first explore this dilemma for science-policy dialogue, summarising several years of research into stakeholder perspectives of attribution in the context of L&D. We then aim to provide clarity about the scientific research available, through an overview of research which might contribute evidence about the causal connections between anthropogenic climate change and losses and damages, including climate science, but also other fields which examine other drivers of hazard, exposure, and vulnerability. Finally, we explore potential applications of attribution research, suggesting that an integrated and nuanced approach has potential to inform planning to avert, minimise and address losses and damages. The key messages are In the political context of climate negotiations, questions about whether losses and damages can be attributed to anthropogenic climate change are often linked to issues of responsibility, blame, and liability. Attribution science does not aim to establish responsibility or blame, but rather to investigate drivers of change. Attribution science is advancing rapidly, and has potential to increase understanding of how climate variability and change is influencing slow onset and extreme weather events, and how this interacts with other drivers of risk, including socio-economic drivers, to influence losses and damages. Over time, some uncertainties in the science will be reduced, as the anthropogenic climate change signal becomes stronger, and understanding of climate variability and change develops. However, some uncertainties will not be eliminated. Uncertainty is common in science, and does not prevent useful applications in policy, but might determine which applications are appropriate. It is important to highlight that in attribution studies, the strength of evidence varies substantially between different kinds of slow onset and extreme weather events, and between regions. Policy-makers should not expect the later emergence of conclusive evidence about the influence of climate variability and change on specific incidences of losses and damages; and, in particular, should not expect the strength of evidence to be equal between events, and between countries. Rather than waiting for further confidence in attribution studies, there is potential to start working now to integrate science into policy and practice, to help understand and tackle drivers of losses and damages, informing prevention, recovery, rehabilitation, and transformation

Comparison of early-, late-, and non-participants in a school-based asthma management program for urban high school students

<p>Abstract</p> <p>Background</p> <p>To assess bias and generalizability of results in randomized controlled trials (RCT), investigators compare participants to non-participants or early- to late-participants. Comparisons can also inform the recruitment approach, especially when working with challenging populations, such as urban adolescents. In this paper, we describe characteristics by participant status of urban teens eligible to participate in a RCT of a school-based, web-based asthma management program.</p> <p>Methods</p> <p>The denominator for this analysis was all students found to be eligible to participate in the RCT. Data were analyzed for participants and non-participants of the RCT, as well as for students that enrolled during the initially scheduled recruitment period (early-participants) and persons that delayed enrollment until the following fall when recruitment was re-opened to increase sample size (late-participants). Full Time Equivalents (FTEs) of staff associated with recruitment were estimated.</p> <p>Results</p> <p>Of 1668 teens eligible for the RCT, 386 enrolled early, and 36 enrolled late, leaving 1246 non-participants. Participants were younger (p < 0.01), more likely to be diagnosed, use asthma medication, and have moderate-to-severe disease than non-participants, odds ratios (95% Confidence Intervals) = 2.1(1.7-2.8), 1.7(1.3-2.1), 1.4(1.0-1.8), respectively. ORs were elevated for the association of late-participation with Medicaid enrollment, 1.9(0.7-5.1) and extrinsic motivation to enroll, 1.7(0.6-5.0). Late-participation was inversely related to study compliance for teens and caregivers, ORs ranging from 0.1 to 0.3 (all p-values < 0.01). Early- and late-participants required 0.45 FTEs/100 and 3.3 FTEs/100, respectively.</p> <p>Conclusions</p> <p>Recruitment messages attracted youth with moderate-to-severe asthma, but extending enrollment was costly, resulting in potentially less motivated, and certainly less compliant, participants. Investigators must balance internal versus external validity in the decision to extend recruitment. Gains in sample size and external validity may be offset by the cost of additional staff time and the threat to internal validity caused by lower participant follow-up.</p> <p>Trial Registration</p> <p>ClinicalTrials.gov: <a href="http://www.clinicaltrials.gov/ct2/show/NCT00201058">NCT00201058</a></p

Deciding Together?:Best Interests and Shared Decision-Making in Paediatric Intensive Care

In the western healthcare, shared decision making has become the orthodox approach to making healthcare choices as a way of promoting patient autonomy. Despite the fact that the autonomy paradigm is poorly suited to paediatric decision making, such an approach is enshrined in English common law. When reaching moral decisions, for instance when it is unclear whether treatment or non-treatment will serve a child’s best interests, shared decision making is particularly questionable because agreement does not ensure moral validity. With reference to current common law and focusing on intensive care practice, this paper investigates what claims shared decision making may have to legitimacy in a paediatric intensive care setting. Drawing on key texts, I suggest these identify advantages to parents and clinicians but not to the child who is the subject of the decision. Without evidence that shared decision making increases the quality of the decision that is being made, it appears that a focus on the shared nature of a decision does not cohere with the principle that the best interests of the child should remain paramount. In the face of significant pressures toward the displacement of the child’s interests in a shared decision, advantages of a shared decision to decisional quality require elucidation. Although a number of arguments of this nature may have potential, should no such advantages be demonstrable we have cause to revise our commitment to either shared decision making or the paramountcy of the child in these circumstances

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

Multi-omic profiling reveals the ataxia protein sacsin is required for integrin trafficking and synaptic organization.

Autosomal recessive spastic ataxia of Charlevoix-Saguenay (ARSACS) is a childhood-onset cerebellar ataxia caused by mutations in SACS, which encodes the protein sacsin. Cellular ARSACS phenotypes include mitochondrial dysfunction, intermediate filament disorganization, and progressive death of cerebellar Purkinje neurons. It is unclear why the loss of sacsin causes these deficits or why they manifest as cerebellar ataxia. Here, we perform multi-omic profiling in sacsin knockout (KO) cells and identify alterations in microtubule dynamics and mislocalization of focal adhesion (FA) proteins, including multiple integrins. Deficits in FA structure, signaling, and function can be rescued by targeting PTEN, a negative regulator of FA signaling. ARSACS mice possess mislocalization of ITGA1 in Purkinje neurons and synaptic disorganization in the deep cerebellar nucleus (DCN). The sacsin interactome reveals that sacsin regulates interactions between cytoskeletal and synaptic adhesion proteins. Our findings suggest that disrupted trafficking of synaptic adhesion proteins is a causal molecular deficit in ARSACS

"I am pregnant and my husband has diabetes. Is there a risk for my child?" A qualitative study of questions asked by email about the role of genetic susceptibility to diabetes

<p>Abstract</p> <p>Background</p> <p>Diabetes Mellitus is a global health problem. Scientific knowledge on the genetics of diabetes is expanding and is more and more utilised in clinical practice and primary prevention strategies. Health consumers have become increasingly interested in genetic information. In the Netherlands, the <it>National Genetic Research and Information Center </it>provides online information about the genetics of diabetes and thereby offers website visitors the opportunity to ask a question per email. The current study aims at exploring people's need of (additional) information about the role of inheritance in diabetes. Results may help to tailor existing clinical and public (online) genetic information to the needs of an increasing population at risk for diabetes.</p> <p>Methods</p> <p>A data base with emailed questions about diabetes and inheritance (n = 172) is used in a secondary content analysis. Questions are posted in 2005-2009 via a website providing information about more than 600 inheritable disorders, including all diabetes subtypes. Queries submitted were classified by contents as well as persons' demographic profiles.</p> <p>Results</p> <p>Questions were received by diabetes patients (49%), relatives (30%), and partners (21%). Questioners were relatively young (54.8% ≤ 30 years) and predominantly female (83%). Most queries related to type 1 diabetes and concerned topics related to (future) pregnancy and family planning. Questioners mainly asked for risk estimation, but also clarifying information (about genetics of diabetes in general) and advice (mostly related to family planning) was requested. Preventive advice to reduce own diabetes risk was hardly sought.</p> <p>Conclusions</p> <p>Genetic information on diabetes provided by professionals or public health initiatives should address patients, as well as relatives and partners. In particular women are receptive to genetic information; they worry about the diabetes related health of (future) offspring. It seems important that information on the contribution of genetics to type 1 diabetes is more readily available. Considering the high prevalence of type 2 diabetes with strong evidence for a genetic predisposition, more effort seems needed to promote awareness around familial clustering and primary prevention.</p

Temporal changes in HCV genotype distribution in three different high risk populations in San Francisco, California

Abstract Background Hepatitis C virus (HCV) genotype (GT) has become an important measure in the diagnosis and monitoring of HCV infection treatment. In the United States (U.S.) HCV GT 1 is reported as the most common infecting GT among chronically infected patients. In Europe, however, recent studies have suggested that the epidemiology of HCV GTs is changing. Methods We assessed HCV GT distribution in 460 patients from three HCV-infected high risk populations in San Francisco, and examined patterns by birth cohort to assess temporal trends. Multiple logistic regression was used to assess factors independently associated with GT 1 infection compared to other GTs (2, 3, and 4). Results Overall, GT 1 was predominant (72.4%), however younger injection drug users (IDU) had a lower proportion of GT 1 infections (54.7%) compared to older IDU and HIV-infected patients (80.5% and 76.6%, respectively). Analysis by birth cohort showed increasing proportions of non-GT 1 infections associated with year of birth: birth before 1970 was independently associated with higher adjusted odds of GT 1: AOR 2.03 (95% CI: 1.23, 3.34). African-Americans as compared to whites also had higher adjusted odds of GT 1 infection (AOR: 3.37; 95% CI: 1.89, 5.99). Conclusions Although, HCV GT 1 remains the most prevalent GT, especially among older groups, changes in GT distribution could have significant implications for how HCV might be controlled on a population level and treated on an individual level