Variable selection under multiple imputation using the bootstrap in a prognostic study

Background: Missing data is a challenging problem in many prognostic studies. Multiple imputation (MI) accounts for imputation uncertainty that allows for adequate statistical testing. We developed and tested a methodology combining MI with bootstrapping techniques for studying prognostic variable selection. Method: In our prospective cohort study we merged data from three different randomized controlled trials (RCTs) to assess prognostic variables for chronicity of low back pain. Among the outcome and prognostic variables data were missing in the range of 0 and 48.1%. We used four methods to investigate the influence of respectively sampling and imputation variation: MI only, bootstrap only, and two methods that combine MI and bootstrapping. Variables were selected based on the inclusion frequency of each prognostic variable, i.e. the proportion of times that the variable appeared in the model. The discriminative and calibrative abilities of prognostic models developed by the four methods were assessed at different inclusion levels. Results: We found that the effect of imputation variation on the inclusion frequency was larger than the effect of sampling variation. When MI and bootstrapping were combined at the range of 0% (full model) to 90% of variable selection, bootstrap corrected c-index values of 0.70 to 0.71 and slope values of 0.64 to 0.86 were found. Conclusion: We recommend to account for both imputation and sampling variation in sets of missing data. The new procedure of combining MI with bootstrapping for variable selection, results in multivariable prognostic models with good performance and is therefore attractive to apply on data sets with missing values

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

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

Cost-effectiveness of an exercise program during pregnancy to prevent gestational diabetes: Results of an economic evaluation alongside a randomised controlled trial

<p>Abstract</p> <p>Background</p> <p>The prevalence of gestational diabetes mellitus (GDM) is increasing worldwide. GDM and the risks associated with GDM lead to increased health care costs and losses in productivity. The objective of this study is to evaluate whether the FitFor2 exercise program during pregnancy is cost-effective from a societal perspective as compared to standard care.</p> <p>Methods</p> <p>A randomised controlled trial (RCT) and simultaneous economic evaluation of the FitFor2 program were conducted. Pregnant women at risk for GDM were randomised to an exercise program to prevent high maternal blood glucose (n = 62) or to standard care (n = 59). The exercise program consisted of two sessions of aerobic and strengthening exercises per week. Clinical outcome measures were maternal fasting blood glucose levels, insulin sensitivity and infant birth weight. Quality of life was measured using the EuroQol 5-D and quality-adjusted life-years (QALYs) were calculated. Resource utilization and sick leave data were collected by questionnaires. Data were analysed according to the intention-to-treat principle. Missing data were imputed using multiple imputations. Bootstrapping techniques estimated the uncertainty surrounding the cost differences and incremental cost-effectiveness ratios.</p> <p>Results</p> <p>There were no statistically significant differences in any outcome measure. During pregnancy, total health care costs and costs of productivity losses were statistically non-significant (mean difference €1308; 95%CI €-229 - €3204). The cost-effectiveness analyses showed that the exercise program was not cost-effective in comparison to the control group for blood glucose levels, insulin sensitivity, infant birth weight or QALYs.</p> <p>Conclusion</p> <p>The twice-weekly exercise program for pregnant women at risk for GDM evaluated in the present study was not cost-effective compared to standard care. Based on these results, implementation of this exercise program for the prevention of GDM cannot be recommended.</p> <p>Trial registration</p> <p>NTR1139</p

Cost-effectiveness of nurse-led self-help for recurrent depression in the primary care setting: design of a pragmatic randomized trial

<p>Abstract</p> <p>Background</p> <p>Major Depressive Disorder is a leading cause of disability, tends to run a recurrent course and is associated with substantial economic costs due to increased healthcare utilization and productivity losses. Interventions aimed at the prevention of recurrences may reduce patients' suffering and costs. Besides antidepressants, several psychological treatments such as preventive cognitive therapy (PCT) are effective in the prevention of recurrences of depression. Yet, many patients find long-term use of antidepressants unattractive, do not want to engage in therapy sessions and in the primary care setting psychologists are often not available. Therefore, it is important to study whether PCT can be used in a nurse-led self-help format in primary care. This study sets out to test the hypothesis that usual care plus nurse-led self-help for recurrent depression in primary care is feasible, acceptable and cost-effective compared to usual care only.</p> <p>Design</p> <p>Patients are randomly assigned to ‘nurse-led self-help treatment plus usual care’ (134 participants) or ‘usual care’ (134 participants). Randomisation is stratified according to the number of previous episodes (2 or 3 previous episodes versus 4 or more). The primary clinical outcome is the cumulative recurrence rate of depression meeting DSM-IV criteria as assessed by the Structured-Clinical-Interview-for-DSM-IV- disorders at one year after completion of the intervention. Secondary clinical outcomes are quality of life, severity of depressive symptoms, co-morbid psychopathology and self-efficacy. As putative effect-moderators, demographic characteristics, number of previous episodes, type of treatment during previous episodes, age of onset, self-efficacy and symptoms of pain and fatigue are assessed. Cumulative recurrence rate ratios are obtained under a Poisson regression model. Number-needed-to-be-treated is calculated as the inverse of the risk-difference. The economic evaluation is conducted from a societal perspective, both as a cost-effectiveness analysis (costs per depression free survival year) and as a cost-utility analysis (costs per quality adjusted life-year).</p> <p>Discussion</p> <p>The purpose of this paper is to outline the rationale and design of a nurse-led, cognitive therapy based self-help aimed at preventing recurrence of depression in a primary care setting. Only few studies have focused on psychological self-help interventions aimed at the prevention of recurrences in primary care patients.</p> <p>Trial registration</p> <p>NTR3001 (<url>http://www.trialregister.nl</url>)</p

Obesity, antenatal depression, diet and gestational weight gain in a population cohort study

Purpose: The aims of this paper are to examine: (1) the relationship between high pre-pregnancy BMI and antenatal depression; (2) whether BMI and antenatal depression interact to predict diet and gestational weight gain (GWG). Methods: Data came from the Avon Longitudinal Study of Parents and Children (ALSPAC). Underweight women were excluded. Pre-pregnancy BMI was self-reported and antenatal depression was assessed using the Edinburgh Postnatal Depression Scale at 18 and 32 weeks’ gestation to identify persistently elevated depressive symptoms (EPDS>12). Dietary patterns were calculated from food frequency questionnaires at 32 weeks’ gestation. GWG was categorised using the USA Institute of Medicine guidelines. Results: This study included 13,314 pregnant women. Obese women had significantly higher odds of antenatal depression than normal weight controls after adjusting for sociodemographics and health behaviours (aOR 1.39, 95%CI 1.05–1.84). Every unit increase in pre-pregnancy BMI was associated with approximately 3% higher odds of antenatal depression (aOR 1.03, 95%CI 1.01-1.05). Antenatal depression was not meaningfully associated with dietary patterns after adjusting for confounders and was not associated with inadequate or excessive GWG. There was no evidence for an interaction of depression and BMI on either diet or GWG. Conclusions Healthcare professionals should be aware of the dose-response relationship between high pre-pregnancy BMI and antenatal depression

Animal-related factors associated with moderate-to-severe diarrhea in children younger than five years in western Kenya: A matched case-control study

Background Diarrheal disease remains among the leading causes of global mortality in children younger than 5 years. Exposure to domestic animals may be a risk factor for diarrheal disease. The objectives of this study were to identify animal-related exposures associated with cases of moderate-to-severe diarrhea (MSD) in children in rural western Kenya, and to identify the major zoonotic enteric pathogens present in domestic animals residing in the homesteads of case and control children. Methodology/Principal findings We characterized animal-related exposures in a subset of case and control children (n = 73 pairs matched on age, sex and location) with reported animal presence at home enrolled in the Global Enteric Multicenter Study in western Kenya, and analysed these for an association with MSD. We identified potentially zoonotic enteric pathogens in pooled fecal specimens collected from domestic animals resident at children’s homesteads. Variables that were associated with decreased risk of MSD were washing hands after animal contact (matched odds ratio [MOR] = 0.2; 95% CI 0.08–0.7), and presence of adult sheep that were not confined in a pen overnight (MOR = 0.1; 0.02–0.5). Variables that were associated with increased risk of MSD were increasing number of sheep owned (MOR = 1.2; 1.0–1.5), frequent observation of fresh rodent excreta (feces/urine) outside the house (MOR = 7.5; 1.5–37.2), and participation of the child in providing water to chickens (MOR = 3.8; 1.2–12.2). Of 691 pooled specimens collected from 2,174 domestic animals, 159 pools (23%) tested positive for one or more potentially zoonotic enteric pathogens (Campylobacter jejuni, C. coli, non-typhoidal Salmonella, diarrheagenic E. coli, Giardia, Cryptosporidium, or rotavirus). We did not find any association between the presence of particular pathogens in household animals, and MSD in children. Conclusions and significance Public health agencies should continue to promote frequent hand washing, including after animal contact, to reduce the risk of MSD. Future studies should address specific causal relations of MSD with sheep and chicken husbandry practices, and with the presence of rodents

Implementing the chronic care model for frail older adults in the Netherlands: study protocol of ACT (frail older adults: care in transition)

<p>Abstract</p> <p>Background</p> <p>Care for older adults is facing a number of challenges: health problems are not consistently identified at a timely stage, older adults report a lack of autonomy in their care process, and care systems are often confronted with the need for better coordination between health care professionals. We aim to address these challenges by introducing the geriatric care model, based on the chronic care model, and to evaluate its effects on the quality of life of community-dwelling frail older adults.</p> <p>Methods/design</p> <p>In a 2-year stepped-wedge cluster randomised clinical trial with 6-monthly measurements, the chronic care model will be compared with usual care. The trial will be carried out among 35 primary care practices in two regions in the Netherlands. Per region, practices will be randomly allocated to four allocation arms designating the starting point of the intervention. <it>Participants</it>: 1200 community-dwelling older adults aged 65 or over and their primary informal caregivers. Primary care physicians will identify frail individuals based on a composite definition of frailty and a polypharmacy criterion. Final inclusion criterion: scoring 3 or more on a disability case-finding tool. <it>Intervention</it>: Every 6 months patients will receive a geriatric in-home assessment by a practice nurse, followed by a tailored care plan. Expert teams will manage and train practice nurses. Patients with complex care needs will be reviewed in interdisciplinary consultations. <it>Evaluation</it>: We will perform an effect evaluation, an economic evaluation, and a process evaluation. Primary outcome is quality of life as measured with the Short Form-12 questionnaire. Effect analyses will be based on the “intention-to-treat” principle, using multilevel regression analysis. Cost measurements will be administered continually during the study period. A cost-effectiveness analysis and cost-utility analysis will be conducted comparing mean total costs to functional status, care needs and QALYs. We will investigate the level of implementation, barriers and facilitators to successful implementation and the extent to which the intervention manages to achieve the transition necessary to overcome challenges in elderly care.</p> <p>Discussion</p> <p>This is one of the first studies assessing the effectiveness, cost-effectiveness and implementation process of the chronic care model for frail community-dwelling older adults.</p> <p>Trial registration</p> <p>The Netherlands National Trial Register NTR2160.</p

Mindful "Vitality in Practice": an intervention to improve the work engagement and energy balance among workers; the development and design of the randomised controlled trial

<p>Abstract</p> <p>Background</p> <p>Modern working life has become more mental and less physical in nature, contributing to impaired mental health and a disturbed energy balance. This may result in mental health problems and overweight. Both are significant threats to the health of workers and thus also a financial burden for society, including employers. Targeting work engagement and energy balance could prevent impaired mental health and overweight, respectively.</p> <p>Methods/Design</p> <p>The study population consists of highly educated workers in two Dutch research institutes. The intervention was systematically developed, based on the Intervention Mapping (IM) protocol, involving workers and management in the process. The workers' needs were assessed by combining the results of interviews, focus group discussions and a questionnaire with available literature. Suitable methods and strategies were selected resulting in an intervention including: eight weeks of customized mindfulness training, followed by eight sessions of e-coaching and supporting elements, such as providing fruit and snack vegetables at the workplace, lunch walking routes, and a buddy system. The effects of the intervention will be evaluated in a RCT, with measurements at baseline, six months (T1) and 12 months (T2). In addition, cost-effectiveness and process of the intervention will also be evaluated.</p> <p>Discussion</p> <p>At baseline the level of work engagement of the sample was "average". Of the study population, 60.1% did not engage in vigorous physical activity at all. An average working day consists of eight sedentary hours. For the Phase II RCT, there were no significant differences between the intervention and the control group at baseline, except for vigorous physical activity. The baseline characteristics of the study population were congruent with the results of the needs assessment. The IM protocol used for the systematic development of the intervention produced an appropriate intervention to test in the planned RCT.</p> <p>Trial registration number</p> <p>Netherlands Trial Register (NTR): <a href="http://www.trialregister.nl/trialreg/admin/rctview.asp?TC=2199">NTR2199</a></p

Mammographic density and markers of socioeconomic status: a cross-sectional study

BACKGROUND: Socioeconomic status (SES) is known to be positively associated with breast cancer risk but its relationship with mammographic density, a marker of susceptibility to breast cancer, is unclear. This study aims to investigate whether mammographic density varies by SES and to identify the underlying anthropometric, lifestyle and reproductive factors leading to such variation. METHODS: In a cross-sectional study of mammographic density in 487 pre-menopausal women, SES was assessed from questionnaire data using highest achieved level of formal education, quintiles of Census-derived Townsend scores and urban/rural classification of place of residence. Mammographic density was measured on digitised films using a computer-assisted method. Linear regression models were fitted to assess the association between SES variables and mammographic density, adjusting for correlated variables. RESULTS: In unadjusted models, percent density was positively associated with SES, with an absolute difference in percent density of 6.3% (95% CI 1.6%, 10.5%) between highest and lowest educational categories, and of 6.6% (95% CI -0.7%, 12.9%) between highest and lowest Townsend quintiles. These associations were mainly driven by strong negative associations between these SES variables and lucent area and were attenuated upon adjustment for body mass index (BMI). There was little evidence that reproductive factors explained this association. SES was not associated with the amount of dense tissue in the breast before or after BMI adjustment. The effect of education on percent density persisted after adjustment for Townsend score. Mammographic measures did not vary according to urban/rural place of residence. CONCLUSIONS: The observed SES gradients in percent density paralleled known SES gradients in breast cancer risk. Although consistent with the hypothesis that percent density may be a mediator of the SES differentials in breast cancer risk, the SES gradients in percent density were mainly driven by the negative association between SES and BMI. Nevertheless, as density affects the sensitivity of screen-film mammography, the higher percent density found among high SES women would imply that these women have a higher risk of developing cancer but a lower likelihood of having it detected earlier