Effect of Pneumococcal Conjugate Vaccine on Pneumonia Incidence Rates among Children 2-59 Months of Age, Mongolia, 2015-2021.

Starting in June 2016, the 13-valent pneumococcal conjugate vaccine (PCV13) was introduced into the routine immunization program of Mongolia by using a 2+1 dosing schedule, phased by district. We used prospective hospital surveillance to evaluate the vaccine's effect on pneumonia incidence rates among children 2-59 months of age over a 6-year period. Of 17,607 children with pneumonia, overall adjusted incidence rate ratios showed decreased primary endpoint pneumonia, very severe pneumonia, and probable pneumococcal pneumonia until June 2021. Results excluding and including the COVID-19 pandemic period were similar. Pneumonia declined in 3 districts that introduced PCV13 with catch-up campaigns but not in the 1 district that did not. After PCV13 introduction, vaccine-type pneumococcal carriage prevalence decreased by 44% and nonvaccine-type carriage increased by 49%. After PCV13 introduction in Mongolia, the incidence of more specific pneumonia endpoints declined in children 2-59 months of age; additional benefits were conferred by catch-up campaigns.

A comparison of strategies for selecting auxiliary variables for multiple imputation.

Multiple imputation (MI) is a popular method for handling missing data. Auxiliary variables can be added to the imputation model(s) to improve MI estimates. However, the choice of which auxiliary variables to include is not always straightforward. Several data-driven auxiliary variable selection strategies have been proposed, but there has been limited evaluation of their performance. Using a simulation study we evaluated the performance of eight auxiliary variable selection strategies: (1, 2) two versions of selection based on correlations in the observed data; (3) selection using hypothesis tests of the "missing completely at random" assumption; (4) replacing auxiliary variables with their principal components; (5, 6) forward and forward stepwise selection; (7) forward selection based on the estimated fraction of missing information; and (8) selection via the least absolute shrinkage and selection operator (LASSO). A complete case analysis and an MI analysis using all auxiliary variables (the "full model") were included for comparison. We also applied all strategies to a motivating case study. The full model outperformed all auxiliary variable selection strategies in the simulation study, with the LASSO strategy the best performing auxiliary variable selection strategy overall. All MI analysis strategies that we were able to apply to the case study led to similar estimates, although computational time was substantially reduced when variable selection was employed. This study provides further support for adopting an inclusive auxiliary variable strategy where possible. Auxiliary variable selection using the LASSO may be a promising alternative when the full model fails or is too burdensome.

On the use of multiple imputation to address data missing by design as well as unintended missing data in case-cohort studies with a binary endpoint.

BACKGROUND: Case-cohort studies are conducted within cohort studies, with the defining feature that collection of exposure data is limited to a subset of the cohort, leading to a large proportion of missing data by design. Standard analysis uses inverse probability weighting (IPW) to address this intended missing data, but little research has been conducted into how best to perform analysis when there is also unintended missingness. Multiple imputation (MI) has become a default standard for handling unintended missingness and is typically used in combination with IPW to handle the intended missingness due to the case-control sampling. Alternatively, MI could be used to handle both the intended and unintended missingness. While the performance of an MI-only approach has been investigated in the context of a case-cohort study with a time-to-event outcome, it is unclear how this approach performs with a binary outcome. METHODS: We conducted a simulation study to assess and compare the performance of approaches using only MI, only IPW, and a combination of MI and IPW, for handling intended and unintended missingness in the case-cohort setting. We also applied the approaches to a case study. RESULTS: Our results show that the combined approach is approximately unbiased for estimation of the exposure effect when the sample size is large, and was the least biased with small sample sizes, while MI-only and IPW-only exhibited larger biases in both sample size settings. CONCLUSIONS: These findings suggest that a combined MI/IPW approach should be preferred to handle intended and unintended missing data in case-cohort studies with binary outcomes.

Nasopharyngeal Pneumococcal Colonization Density Is Associated With Severe Pneumonia in Young Children in the Lao People's Democratic Republic.

BACKGROUND: No studies have explored the association between pneumococcal nasopharyngeal density and severe pneumonia using the World Health Organization (WHO) 2013 definition. In Lao People's Democratic Republic (Lao PDR), we determine the association between nasopharyngeal pneumococcal density and severe pneumonia in children. METHODS: A prospective observational study was undertaken at Mahosot Hospital, Vientiane, from 2014 to mid-2018. Children <5 years admitted with acute respiratory infections (ARIs) were included. Clinical and demographic data were collected alongside nasopharyngeal swabs for pneumococcal quantification by lytA real-time quantitative polymerase chain reaction. Severe pneumonia was defined using the 2013 WHO definition. For pneumococcal carriers, a logistic regression model examined the association between pneumococcal density and severe pneumonia, after adjusting for potential confounders including demographic and household factors, 13-valent pneumococcal conjugate vaccine status, respiratory syncytial virus co-detection, and preadmission antibiotics. RESULTS: Of 1268 participants with ARI, 32.3% (n = 410) had severe pneumonia and 36.9% (n = 468) had pneumococcal carriage. For pneumococcal carriers, pneumococcal density was positively associated with severe pneumonia (adjusted odds ratio, 1.4 [95% confidence interval, 1.1-1.8]; P = .020). CONCLUSIONS: Among children with ARIs and pneumococcal carriage, pneumococcal carriage density was positively associated with severe pneumonia in Lao PDR. Further studies may determine if pneumococcal density is a useful marker for pneumococcal conjugate vaccine impact on childhood pneumonia.

Evaluation of multiple imputation approaches for handling missing covariate information in a case-cohort study with a binary outcome.

BACKGROUND: In case-cohort studies a random subcohort is selected from the inception cohort and acts as the sample of controls for several outcome investigations. Analysis is conducted using only the cases and the subcohort, with inverse probability weighting (IPW) used to account for the unequal sampling probabilities resulting from the study design. Like all epidemiological studies, case-cohort studies are susceptible to missing data. Multiple imputation (MI) has become increasingly popular for addressing missing data in epidemiological studies. It is currently unclear how best to incorporate the weights from a case-cohort analysis in MI procedures used to address missing covariate data. METHOD: A simulation study was conducted with missingness in two covariates, motivated by a case study within the Barwon Infant Study. MI methods considered were: using the outcome, a proxy for weights in the simple case-cohort design considered, as a predictor in the imputation model, with and without exposure and covariate interactions; imputing separately within each weight category; and using a weighted imputation model. These methods were compared to a complete case analysis (CCA) within the context of a standard IPW analysis model estimating either the risk or odds ratio. The strength of associations, missing data mechanism, proportion of observations with incomplete covariate data, and subcohort selection probability varied across the simulation scenarios. Methods were also applied to the case study. RESULTS: There was similar performance in terms of relative bias and precision with all MI methods across the scenarios considered, with expected improvements compared with the CCA. Slight underestimation of the standard error was seen throughout but the nominal level of coverage (95%) was generally achieved. All MI methods showed a similar increase in precision as the subcohort selection probability increased, irrespective of the scenario. A similar pattern of results was seen in the case study. CONCLUSIONS: How weights were incorporated into the imputation model had minimal effect on the performance of MI; this may be due to case-cohort studies only having two weight categories. In this context, inclusion of the outcome in the imputation model was sufficient to account for the unequal sampling probabilities in the analysis model.

Levels of pneumococcal conjugate vaccine coverage and indirect protection against invasive pneumococcal disease and pneumonia hospitalisations in Australia: An observational study.

BACKGROUND: There is limited empiric evidence on the coverage of pneumococcal conjugate vaccines (PCVs) required to generate substantial indirect protection. We investigate the association between population PCV coverage and indirect protection against invasive pneumococcal disease (IPD) and pneumonia hospitalisations among undervaccinated Australian children. METHODS AND FINDINGS: Birth and vaccination records, IPD notifications, and hospitalisations were individually linked for children aged <5 years, born between 2001 and 2012 in 2 Australian states (New South Wales and Western Australia; 1.37 million children). Using Poisson regression models, we examined the association between PCV coverage, in small geographical units, and the incidence of (1) 7-valent PCV (PCV7)-type IPD; (2) all-cause pneumonia; and (3) pneumococcal and lobar pneumonia hospitalisation in undervaccinated children. Undervaccinated children received <2 doses of PCV at <12 months of age and no doses at ≥12 months of age. Potential confounding variables were selected for adjustment a priori with the assistance of a directed acyclic graph. There were strong inverse associations between PCV coverage and the incidence of PCV7-type IPD (adjusted incidence rate ratio [aIRR] 0.967, 95% confidence interval [CI] 0.958 to 0.975, p-value < 0.001), and pneumonia hospitalisations (all-cause pneumonia: aIRR 0.991 95% CI 0.990 to 0.994, p-value < 0.001) among undervaccinated children. Subgroup analyses for children <4 months old, urban, rural, and Indigenous populations showed similar trends, although effects were smaller for rural and Indigenous populations. Approximately 50% coverage of PCV7 among children <5 years of age was estimated to prevent up to 72.5% (95% CI 51.6 to 84.4) of PCV7-type IPD among undervaccinated children, while 90% coverage was estimated to prevent 95.2% (95% CI 89.4 to 97.8). The main limitations of this study include the potential for differential loss to follow-up, geographical misclassification of children (based on residential address at birth only), and unmeasured confounders. CONCLUSIONS: In this study, we observed substantial indirect protection at lower levels of PCV coverage than previously described-challenging assumptions that high levels of PCV coverage (i.e., greater than 90%) are required. Understanding the association between PCV coverage and indirect protection is a priority since the control of vaccine-type pneumococcal disease is a prerequisite for reducing the number of PCV doses (from 3 to 2). Reduced dose schedules have the potential to substantially reduce program costs while maintaining vaccine impact.

A comparison of multiple imputation strategies for handling missing data in multi-item scales: Guidance for longitudinal studies.

Medical research often involves using multi-item scales to assess individual characteristics, disease severity, and other health-related outcomes. It is common to observe missing data in the scale scores, due to missing data in one or more items that make up that score. Multiple imputation (MI) is a popular method for handling missing data. However, it is not clear how best to use MI in the context of scale scores, particularly when they are assessed at multiple waves of data collection resulting in large numbers of items. The aim of this article is to provide practical advice on how to impute missing values in a repeatedly measured multi-item scale using MI when inference on the scale score is of interest. We evaluated the performance of five MI strategies for imputing missing data at either the item or scale level using simulated data and a case study based on four waves of the Longitudinal Study of Australian Children (LSAC). MI was implemented using both multivariate normal imputation and fully conditional specification, with two rules for calculating the scale score. A complete case analysis was also performed for comparison. Based on our results, we caution against the use of a MI strategy that does not include the scale score in the imputation model(s) when the scale score is required for analysis.

Multiple imputation of semi-continuous exposure variables that are categorized for analysis.

Semi-continuous variables are characterized by a point mass at one value and a continuous range of values for remaining observations. An example is alcohol consumption quantity, with a spike of zeros representing non-drinkers and positive values for drinkers. If multiple imputation is used to handle missing values for semi-continuous variables, it is unclear how this should be implemented within the standard approaches of fully conditional specification (FCS) and multivariate normal imputation (MVNI). This question is brought into focus by the use of categorized versions of semi-continuous exposure variables in analyses (eg, no drinking, drinking below binge level, binge drinking, heavy binge drinking), raising the question of how best to achieve congeniality between imputation and analysis models. We performed a simulation study comparing nine approaches for imputing semi-continuous exposures requiring categorization for analysis. Three methods imputed the categories directly: ordinal logistic regression, and imputation of binary indicator variables representing the categories using MVNI (with two variants). Six methods (predictive mean matching, zero-inflated binomial imputation, and two-part imputation methods with variants in FCS and MVNI) imputed the semi-continuous variable, with categories derived after imputation. The ordinal and zero-inflated binomial methods had good performance across most scenarios, while MVNI methods requiring rounding after imputation did not perform well. There were mixed results for predictive mean matching and the two-part methods, depending on whether the estimands were proportions or regression coefficients. The results highlight the need to consider the parameter of interest when selecting an imputation procedure.

Practical strategies for handling breakdown of multiple imputation procedures.

Multiple imputation is a recommended method for handling incomplete data problems. One of the barriers to its successful use is the breakdown of the multiple imputation procedure, often due to numerical problems with the algorithms used within the imputation process. These problems frequently occur when imputation models contain large numbers of variables, especially with the popular approach of multivariate imputation by chained equations. This paper describes common causes of failure of the imputation procedure including perfect prediction and collinearity, focusing on issues when using Stata software. We outline a number of strategies for addressing these issues, including imputation of composite variables instead of individual components, introducing prior information and changing the form of the imputation model. These strategies are illustrated using a case study based on data from the Longitudinal Study of Australian Children.

Evaluation of the impact of childhood 13-valent pneumococcal conjugate vaccine introduction on adult pneumonia in Ulaanbaatar, Mongolia: study protocol for an observational study.

BACKGROUND: Community-acquired pneumonia is an important cause of morbidity and mortality in adults. Approximately one-third of pneumonia cases can be attributed to the pneumococcus. Pneumococcal conjugate vaccines (PCVs) protect against colonisation with vaccine-type serotypes. The resulting decrease in transmission of vaccine serotypes leads to large indirect effects. There are limited data from developing countries demonstrating the impact of childhood PCV immunisation on adult pneumonia. There are also insufficient data available on the burden and severity of all-cause pneumonia and respiratory syncytial virus (RSV) in adults from low resource countries. There is currently no recommendation for adult pneumococcal vaccination with either pneumococcal polysaccharide vaccine or PCVs in Mongolia. We describe the protocol developed to evaluate the association between childhood 13-valent PCV (PCV13) vaccination and trends in adult pneumonia. METHODS: PCV13 was introduced into the routine childhood immunisation schedule in Mongolia in a phased manner from 2016. In March 2019 we initiated active hospital-based surveillance for adult pneumonia, with the primary objective of evaluating trends in severe hospitalised clinical pneumonia incidence in adults 18 years and older in four districts of Ulaanbaatar. Secondary objectives include measuring the association between PCV13 introduction and trends in all clinically-defined pneumonia, radiologically-confirmed pneumonia, nasopharyngeal carriage of S. pneumoniae and pneumonia associated with RSV or influenza. Clinical questionnaires, nasopharyngeal swabs, urine samples and chest radiographs were collected from enrolled patients. Retrospective administrative and clinical data were collected for all respiratory disease-related admissions from January 2015 to February 2019. DISCUSSION: Establishing a robust adult surveillance system may be an important component of monitoring the indirect impact of PCVs within a country. Monitoring indirect impact of childhood PCV13 vaccination on adult pneumonia provides additional data on the full public health impact of the vaccine, which has implications for vaccine efficiency and cost-effectiveness. Adult surveillance in Mongolia will contribute to the limited evidence available on the burden of pneumococcal pneumonia among adults in low- and middle-income countries, particularly in the Asia-Pacific region. In addition, it is one of the few examples of implementing prospective, population-based pneumonia surveillance to evaluate the indirect impact of PCVs in a resource-limited setting.

Temporal decline in diarrhea episodes and mortality in Kiribati children two years following rotavirus vaccine introduction, despite high malnutrition rates: a retrospective review.

BACKGROUND: Kiribati introduced rotavirus vaccine in 2015. To estimate the impact of rotavirus vaccine on acute gastroenteritis (AGE) and severe acute malnutrition (SAM) among children under 5 in Kiribati, a retrospective review of inpatient and outpatient AGE and hospitalized SAM was undertaken. METHODS: Inpatient data for admissions and hospital deaths due to AGE, SAM and all-causes were collected for children under 5 from all hospitals on the main island, Tarawa, from January 2010-December 2013 (pre-rotavirus vaccine) and January 2016-September 2017 (post-rotavirus vaccine). National outpatient diarrhea data were collected from January 2010 to August 2017 for under 5. An interrupted time-series analysis was undertaken to estimate the effect of rotavirus vaccine on the rates of inpatient and outpatient AGE, inpatient SAM; and inpatient case fatality rates for AGE and SAM, were calculated pre- and post-rotavirus vaccine introduction. RESULTS: The incidence rate of AGE admissions from Tarawa and national AGE outpatient presentations significantly declined by 37 and 44%, respectively, 2 years following rotavirus vaccine introduction. There was a significant decline in the percentage of AGE contributing to all-cause under 5 admissions (12·8% vs. 7·2%, p < 0·001) and all-cause under-five mortality (15·9% vs. 5·7%, p = 0·006) pre- and post-rotavirus vaccine introduction. The estimated incidence rate of inpatient SAM decreased by 24% in under 5 s, 2 years following rotavirus vaccine introduction. CONCLUSIONS: AGE morbidity and mortality and hospitalized SAM rates have declined following rotavirus vaccine introduction in Kiribati children.

Oxygen systems to improve clinical care and outcomes for children and neonates: A stepped-wedge cluster-randomised trial in Nigeria.

BACKGROUND: Improving oxygen systems may improve clinical outcomes for hospitalised children with acute lower respiratory infection (ALRI). This paper reports the effects of an improved oxygen system on mortality and clinical practices in 12 general, paediatric, and maternity hospitals in southwest Nigeria. METHODS AND FINDINGS: We conducted an unblinded stepped-wedge cluster-randomised trial comparing three study periods: baseline (usual care), pulse oximetry introduction, and stepped introduction of a multifaceted oxygen system. We collected data from clinical records of all admitted neonates (<28 days old) and children (28 days to 14 years old). Primary analysis compared the full oxygen system period to the pulse oximetry period and evaluated odds of death for children, children with ALRI, neonates, and preterm neonates using mixed-effects logistic regression. Secondary analyses included the baseline period (enabling evaluation of pulse oximetry introduction) and evaluated mortality and practice outcomes on additional subgroups. Three hospitals received the oxygen system intervention at 4-month intervals. Primary analysis included 7,716 neonates and 17,143 children admitted during the 2-year stepped crossover period (November 2015 to October 2017). Compared to the pulse oximetry period, the full oxygen system had no association with death for children (adjusted odds ratio [aOR] 1.06; 95% confidence interval [CI] 0.77-1.46; p = 0.721) or children with ALRI (aOR 1.09; 95% CI 0.50-2.41; p = 0.824) and was associated with an increased risk of death for neonates overall (aOR 1.45; 95% CI 1.04-2.00; p = 0.026) but not preterm/low-birth-weight neonates (aOR 1.30; 95% CI 0.76-2.23; p = 0.366). Secondary analyses suggested that the introduction of pulse oximetry improved oxygen practices prior to implementation of the full oxygen system and was associated with lower odds of death for children with ALRI (aOR 0.33; 95% CI 0.12-0.92; p = 0.035) but not for children, preterm neonates, or neonates overall (aOR 0.97, 95% CI 0.60-1.58, p = 0.913; aOR 1.12, 95% CI 0.56-2.26, p = 0.762; aOR 0.90, 95% CI 0.57-1.43, p = 0.651). Limitations of our study are a lower-than-anticipated power to detect change in mortality outcomes (low event rates, low participant numbers, high intracluster correlation) and major contextual changes related to the 2016-2017 Nigerian economic recession that influenced care-seeking and hospital function during the study period, potentially confounding mortality outcomes. CONCLUSIONS: We observed no mortality benefit for children and a possible higher risk of neonatal death following the introduction of a multifaceted oxygen system compared to introducing pulse oximetry alone. Where some oxygen is available, pulse oximetry may improve oxygen usage and clinical outcomes for children with ALRI. TRIAL REGISTRATION: Australian New Zealand Clinical Trials Registry: ACTRN12617000341325.

Early Peritoneal Dialysis and Major Adverse Events After Pediatric Cardiac Surgery: A Propensity Score Analysis.

OBJECTIVES: Early peritoneal dialysis may have a role in modulating the inflammatory response after cardiopulmonary bypass. This study sought to test the effect of early peritoneal dialysis on major adverse events after pediatric cardiac surgery involving cardiopulmonary bypass. DESIGN: In this observational study, the outcomes in infants post cardiac surgery who received early peritoneal dialysis (within 6 hr of completing cardiopulmonary bypass) were compared with those who received late peritoneal dialysis. The primary outcome was a composite of one or more of cardiac arrest, emergency chest reopening, requirement for extracorporeal membrane oxygenation, or death. Secondary outcomes included duration of mechanical ventilation, length of intensive care, and hospital stay. A propensity score methodology utilizing inverse probability of treatment weighting was used to minimize selection bias due to timing of peritoneal dialysis. SETTING: Cardiac ICU, The Royal Children's Hospital, Melbourne, VIC, Australia. PATIENTS: From 2012 to 2015, infants who were commenced on peritoneal dialysis after cardiac surgery were included. MEASUREMENTS AND MAIN RESULTS: Among 239 eligible infants, 56 (23%) were commenced on early peritoneal dialysis and 183 (77%) on late peritoneal dialysis. At 90 days, early peritoneal dialysis as compared with late peritoneal dialysis was associated with a decreased risk of primary outcome (relative risk, 0.16; 95% CI, 0.05-0.47; p < 0.001 and absolute risk difference, -18.1%; 95% CI, -25.1 to -11.1; p < 0.001). Early peritoneal dialysis was also associated with a decrease in duration of mechanical ventilation and intensive care stay. Among infants with a cardiopulmonary bypass greater than 150 minutes, early peritoneal dialysis was also associated with a survival advantage (relative risk, 0.14; 95% CI, 0.03-0.84; p = 0.03 and absolute risk difference, -7.8; 95% CI, -13.6 to -2; p = 0.008). CONCLUSIONS: Early peritoneal dialysis in infants post cardiac surgery is associated with a decrease in the rate of major adverse events. The role of early peritoneal dialysis warrants the conduct of randomized trials both in high and low-to-middle income countries; any beneficial effects if confirmed have the potential to strongly influence outcomes for children born with congenital heart disease.

Using Paid and Free Facebook Methods to Recruit Australian Parents to an Online Survey: An Evaluation.

BACKGROUND: The prevalence of social media makes it a potential alternative to traditional offline methods of recruiting and engaging participants in health research. Despite burgeoning use and interest, few studies have rigorously evaluated its effectiveness and feasibility in terms of recruitment rates and costs, sample representativeness, and retention. OBJECTIVE: This study aimed to determine the feasibility of using Facebook to recruit employed Australian parents to an online survey about managing work and family demands, specifically to examine (1) recruitment rates and costs; (2) sample representativeness, compared with a population-based cohort of parents; and (3) retention, including demographic and health characteristics of parents who returned to complete a follow-up survey 6 weeks later. METHODS: Recruitment was conducted using 20 paid Facebook advertising campaigns, supplemented with free advertising approaches such as posts on relevant Facebook pages and requests for professional networks to circulate the survey link via Facebook. Recruitment rates and costs were evaluated using the Checklist for Reporting Results of Internet E-Surveys, including view rate, participation rate, completion rate, cost per consent, and cost per completer. Sample representativeness was evaluated by comparing demographic and outcome variables with a comparable sample from the Longitudinal Study of Australian Children including educational attainment, marital status, country of birth, neighborhood disadvantage, work-family conflict, and psychological distress. Retention was evaluated by comparing the number and demographic characteristics of participants at recruitment and at 6-week follow-up. RESULTS: Recruitment strategies together resulted in 6653 clicks on the survey link, from which 5378 parents consented to participate and 4665 (86.74%) completed the survey. Of those who completed the survey, 85.94% (4009/4665) agreed to be recontacted, with 57.79% (2317/4009) completing the follow-up survey (ie, 43.08% [2317/5378] of parents who consented to the initial survey). Paid Facebook advertising recruited nearly 75% of the sample at Aus $2.32 per completed survey (Aus $7969 spent, 3440 surveys completed). Compared with a population-based sample, participants at baseline were more likely to be university educated (P<.001), experience greater work-family conflict (P<.001) and psychological distress (P<.001), and were less likely to be born outside Australia (P<.001) or live in a disadvantaged neighborhood (P<.001). CONCLUSIONS: Facebook provided a feasible, rapid method to recruit a large national sample of parents for health research. However, some sample biases were observed and should be considered when recruiting participants via Facebook. Retention of participants at 6- to 8-week follow-up was less than half the initial sample; this may reflect limited ongoing participant engagement for those recruited through social media, compared with face-to-face.

What Influences Parental Engagement in Early Intervention? Parent, Program and Community Predictors of Enrolment, Retention and Involvement.

Poor participant engagement undermines individual and public health benefits of early intervention programs. This study assessed the extent to which three types of engagement (participant enrolment, retention and involvement) were influenced by individual, program and contextual factors. Data were from a cluster randomised controlled trial (N = 1447) of a community-based parenting program, delivered at two levels of intensity (group sessions with and without individualised home coaching) conducted in Victoria, Australia. Individual (parent and family) factors and program factors were assessed by parent report and administrative records, and contextual factors by area-level population statistics. Data were analysed using multilevel logistic or linear regression models. Individual and contextual factors predicted enrolment, while family and program factors were more influential on program retention and parents' active involvement. Provision of individualised support was important to all forms of engagement, particularly for families experiencing the greatest barriers to participation. These findings indicate that different strategies are required to effectively support families in the processes of enrolling, continuing to attend and actively participating in early intervention programs.

Sustained Antibody Responses 6 Years Following 1, 2, or 3 Doses of Quadrivalent Human Papillomavirus (HPV) Vaccine in Adolescent Fijian Girls, and Subsequent Responses to a Single Dose of Bivalent HPV Vaccine: A Prospective Cohort Study.

BACKGROUND: The duration of antibody response following reduced human papillomavirus (HPV) vaccine doses has not been determined. We compared the antibody responses in girls previously vaccinated with zero, 1, 2, or 3 doses of quadrivalent HPV vaccine (4vHPV; Gardasil, Merck) 6 years previously. METHODS: A prospective cohort study was undertaken in 200 Fijian girls 15-19 years of age. Approximately equal numbers of girls from 2 main ethnic groups (Fijians of Indian descent [FID] and Indigenous Fijians [iTaukei]) in Fiji were recruited for each dosage groups. Blood was drawn before and 28 days following a single dose of bivalent HPV vaccine (2vHPV; Cervarix, GlaxoSmithKline). We measured neutralizing antibodies (NAb) against HPV-6, -11, -16, and -18 using the pseudovirion-based neutralization assay. RESULTS: After 6 years (before a dose of 2vHPV was given), the geometric mean NAb titers for all 4 HPV types were not statistically different between 2-dose (2D) and 3-dose (3D) recipients: HPV-6 (3D: 2216 [95% confidence interval {CI},1695-2896]; 2D: 1476 [95% CI, 1019-2137]; P = .07), HPV-11 (3D: 4431 [95% CI, 3396-5783]; 2D: 2951 [95% CI, 1984-4390]; P = .09), HPV-16 (3D: 3373 [95% CI, 2511-4530]; 2D: 3275 [95% CI, 2452-4373]; P = .89); HPV-18 (3D: 628 [95% CI: 445-888]; 2D: 606 [95% CI, 462-862]; P = .89), and were higher in FID than iTaukei girls. Although 1-dose recipients had significantly lower NAb titers than 2-/3-dose recipients, their NAb titers were 5- to 30-fold higher than unvaccinated girls. Post-2vHPV NAb titers against HPV-16 and -18 were not statistically different between girls who received 1, 2, or 3 doses of 4vHPV previously. CONCLUSIONS: Two doses of 4vHPV provide similar NAb titers as 3 doses for 6 years, although the clinical significance is unknown. A single dose of 4vHPV elicits antibodies that persisted for at least 6 years, and induced immune memory, suggesting possible protection against HPV vaccine types after a single dose of 4vHPV.

Model checking in multiple imputation: an overview and case study.

BACKGROUND: Multiple imputation has become very popular as a general-purpose method for handling missing data. The validity of multiple-imputation-based analyses relies on the use of an appropriate model to impute the missing values. Despite the widespread use of multiple imputation, there are few guidelines available for checking imputation models. ANALYSIS: In this paper, we provide an overview of currently available methods for checking imputation models. These include graphical checks and numerical summaries, as well as simulation-based methods such as posterior predictive checking. These model checking techniques are illustrated using an analysis affected by missing data from the Longitudinal Study of Australian Children. CONCLUSIONS: As multiple imputation becomes further established as a standard approach for handling missing data, it will become increasingly important that researchers employ appropriate model checking approaches to ensure that reliable results are obtained when using this method.

Missing data in FFQs: making assumptions about item non-response.

OBJECTIVE: FFQs are a popular method of capturing dietary information in epidemiological studies and may be used to derive dietary exposures such as nutrient intake or overall dietary patterns and diet quality. As FFQs can involve large numbers of questions, participants may fail to respond to all questions, leaving researchers to decide how to deal with missing data when deriving intake measures. The aim of the present commentary is to discuss the current practice for dealing with item non-response in FFQs and to propose a research agenda for reporting and handling missing data in FFQs. RESULTS: Single imputation techniques, such as zero imputation (assuming no consumption of the item) or mean imputation, are commonly used to deal with item non-response in FFQs. However, single imputation methods make strong assumptions about the missing data mechanism and do not reflect the uncertainty created by the missing data. This can lead to incorrect inference about associations between diet and health outcomes. Although the use of multiple imputation methods in epidemiology has increased, these have seldom been used in the field of nutritional epidemiology to address missing data in FFQs. We discuss methods for dealing with item non-response in FFQs, highlighting the assumptions made under each approach. CONCLUSIONS: Researchers analysing FFQs should ensure that missing data are handled appropriately and clearly report how missing data were treated in analyses. Simulation studies are required to enable systematic evaluation of the utility of various methods for handling item non-response in FFQs under different assumptions about the missing data mechanism.

Long-term intra-individual variability of albuminuria in type 2 diabetes mellitus: implications for categorization of albumin excretion rate.

BACKGROUND: Diabetic kidney disease (DKD) is the leading cause of end-stage renal disease in the Western world. Early and accurate identification of DKD offers the best chance of slowing the progression of kidney disease. An important method for evaluating risk of progressive DKD is abnormal albumin excretion rate (AER). Due to the high variability in AER, most guidelines recommend the use of more than or equal to two out of three AER measurements within a 3- to 6-month period to categorise AER. There are recognised limitations of using AER as a marker of DKD because one quarter of patients with type 2 diabetes may develop kidney disease without an increase in albuminuria and spontaneous regression of albuminuria occurs frequently. Nevertheless, it is important to investigate the long-term intra-individual variability of AER in participants with type 2 diabetes. METHODS: Consecutive AER measurements (median 19 per subject) were performed in 497 participants with type 2 diabetes from 1999 to 2012 (mean follow-up 7.9 ± 3 years). Baseline clinical characteristics were collected to determine associations with AER variability. Participants were categorised as having normo-, micro- or macroalbuminuria according to their initial three AER measurements. Participants were then categorised into four patterns of AER trajectories: persistent, intermittent, progressing and regressing. Coefficients of variation were used to measure intra-individual AER variability. RESULTS: The median coefficient of variation of AER was 53.3%, 76.0% and 67.0% for subjects with normo-, micro- or macroalbuminuria at baseline. The coefficient of variation of AER was 37.7%, 66% and 94.8% for subjects with persistent, intermittent and progressing normoalbuminuria; 43%, 70.6%, 86.1% and 82.3% for subjects with persistent, intermittent, progressing and regressing microalbuminuria; and 55.2%, 67% and 82.4% for subjects with persistent, intermittent and regressing macroalbuminuria, respectively. CONCLUSION: High long-term variability of AER suggests that two out of three AER measurements may not always be adequate for the optimal categorisation and prediction of AER.

Posterior predictive checking of multiple imputation models.

Multiple imputation is gaining popularity as a strategy for handling missing data, but there is a scarcity of tools for checking imputation models, a critical step in model fitting. Posterior predictive checking (PPC) has been recommended as an imputation diagnostic. PPC involves simulating "replicated" data from the posterior predictive distribution of the model under scrutiny. Model fit is assessed by examining whether the analysis from the observed data appears typical of results obtained from the replicates produced by the model. A proposed diagnostic measure is the posterior predictive "p-value", an extreme value of which (i.e., a value close to 0 or 1) suggests a misfit between the model and the data. The aim of this study was to evaluate the performance of the posterior predictive p-value as an imputation diagnostic. Using simulation methods, we deliberately misspecified imputation models to determine whether posterior predictive p-values were effective in identifying these problems. When estimating the regression parameter of interest, we found that more extreme p-values were associated with poorer imputation model performance, although the results highlighted that traditional thresholds for classical p-values do not apply in this context. A shortcoming of the PPC method was its reduced ability to detect misspecified models with increasing amounts of missing data. Despite the limitations of posterior predictive p-values, they appear to have a valuable place in the imputer's toolkit. In addition to automated checking using p-values, we recommend imputers perform graphical checks and examine other summaries of the test quantity distribution.