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Biomedical subjects

M G Kenward

Publications and source records attributed to M G Kenward.

At least 19 recordsLinked to original sources
PubMed2006

Age at introduction of new foods and advanced beta cell autoimmunity in young children with HLA-conferred susceptibility to type 1 diabetes.

AIMS/HYPOTHESIS: Evidence for the role of infant feeding in the development of beta cell autoimmunity is inconsistent. We set out to study the effects of breastfeeding and of age at introduction of supplementary foods on the development of beta cell autoimmunity. SUBJECTS AND METHODS: A prospective birth cohort of 3,565 infants with HLA-DQB1-conferred susceptibility to type 1 diabetes was recruited between 1996 and 2001 from two university hospital areas in Finland. Blood samples were collected at 3- to 12-month intervals to measure antibodies against islet cells, insulin, glutamate dehydroxylase and islet antigen 2. The families kept a record on the age at introduction of new foods, and for each visit completed a structured dietary questionnaire. The endpoint was repeated positivity for islet cell antibodies together with at least one of the other three antibodies. RESULTS: The overall or exclusive duration of breastfeeding was not associated with the risk of developing the endpoint. An early age at introduction of fruits and berries (< or =4 months) was related to increased risk of developing positivity for the endpoint (hazard ratio [95% CI] for earliest tertile 2.02 [1.03-3.95] and for midtertile 1.97 [1.06-3.64] compared with latest tertile >4 months). Also, introducing roots between 3 and 3.9 months (midtertile) was related to increased risk of the endpoint (hazard ratio [95% CI] for the earliest tertile 1.04 [0.57-1.90] and for midtertile 1.82 [1.19-2.79] compared with latest tertile). These associations were independent of several putative socio-demographic and perinatal confounding factors. CONCLUSIONS/INTERPRETATION: Our findings suggest that an early age at introduction of fruits and berries and roots associates independently with beta cell autoimmunity, contradicting earlier findings from smaller birth cohort studies.

Age Factors↗
PubMed2005

Use of antimicrobials and risk of type 1 diabetes in a population-based mother-child cohort.

AIMS/HYPOTHESIS: The aim of this study was to investigate whether the use of antimicrobials is associated with the risk of childhood type 1 diabetes. MATERIALS AND METHODS: The study population included all children born in Finland between 1996 and 2000 who were diagnosed with type 1 diabetes by the end of 2002. For each case (n=437), four matched controls were selected. Data on diabetes and the maternal use of antimicrobials was derived from nationwide registries. RESULTS: Maternal use of phenoxymethyl penicillins (odds ratio [OR]=1.70, 95% CI 1.08-2.68, p=0.022) or quinolone antimicrobials (OR=2.43, 95% CI 1.16-5.10, p=0.019) before pregnancy was associated with an increased risk of type 1 diabetes in the child, whereas the use of other specific antimicrobials was not related to the risk. The risk was also higher among mother-child pairs where macrolides were used both by the mother before pregnancy and by the child, compared with pairs where neither used macrolides (OR=1.76, 95% CI 1.05-2.94, p=0.032). Maternal use of antimicrobials during pregnancy was not associated with an increased risk. The high use of antimicrobials by the child (more than seven vs seven or less purchases) was related to greater risk (OR=1.66, 95% CI 1.24-2.24, p=0.001). CONCLUSIONS/INTERPRETATION: Overall, the use of antimicrobials before pregnancy, during pregnancy or during childhood was not related to the risk of childhood type 1 diabetes. However, the use of some specific antimicrobials by the mother before pregnancy and by the child may be associated with an increased risk. Further studies are needed to confirm these associations and to elucidate the underlying mechanisms of action.

Adult↗
PubMed2003

A comparison of two methods for the estimation of precision with incomplete longitudinal data, jointly modelled with a time-to-event outcome.

Several methods for the estimation and comparison of rates of change in longitudinal studies with staggered entry and informative drop-outs have been recently proposed. For multivariate normal linear models, REML estimation is used. There are various approaches to maximizing the corresponding log-likelihood; in this paper we use a restricted iterative generalized least squares method (RIGLS) combined with a nested EM algorithm. An important statistical problem in such approaches is the estimation of the standard errors adjusted for the missing data (observed data information matrix). Louis has provided a general technique for computing the observed data information in terms of completed data quantities within the EM framework. The multiple imputation (MI) method for obtaining variances can be regarded as an alternative to this. The aim of this paper is to develop, apply and compare the Louis and a modified MI method in the setting of longitudinal studies where the source of missing data is either death or disease progression (informative) or end of the study (assumed non-informative). Longitudinal data are simultaneously modelled with the missingness process. The methods are illustrated by modelling CD4 count data from an HIV-1 clinical trial and evaluated through simulation studies. Both methods, Louis and MI, are used with Monte Carlo simulations of the missing data using the appropriate conditional distributions, the former with 100 simulations, the latter with 5 and 10. It is seen that naive SEs based on the completed data likelihood can be seriously biased. This bias was largely corrected by Louis and modified MI methods, which gave broadly similar estimates. Given the relative simplicity of the modified MI method, it may be preferable.

Algorithms↗
PubMed2001

Bayesian discrimination with longitudinal data.

The motivation for the methodological development is a double-blind clinical trial designed to estimate the effect of regular injection of growth hormone, with the purpose of identifying growth hormone abusers in sport. The data formed part of a multicentre investigation jointly sponsored by the European Union and the International Olympic Committee. The data are such that for each individual there is a matrix of marker variables by time point (nominally 8 markers at each of 7 time points). Data arise out of a double-blind trial in which individuals are given growth hormone at one of two dose levels or placebo daily for 28 days. Monitoring by means of blood samples is at 0, 21, 28, 30, 33, 42 and 84 days. We give a new method of Bayesian discrimination for multivariate longitudinal data. This involves a Kronecker product covariance structure for the time by measurements (markers) data on each individual. This structure is estimated by an empirical Bayes approach, using an ECM algorithm, within a Bayesian Gaussian discrimination model. In future one may have markers for an individual at one or more time points. The method gives probabilities that an individual is on placebo or on one of the two dose regimes.

Journal Article↗
PubMed2001

Sensitivity analysis for nonrandom dropout: a local influence approach.

Diggle and Kenward (1994, Applied Statistics 43, 49-93) proposed a selection model for continuous longitudinal data subject to nonrandom dropout. It has provoked a large debate about the role for such models. The original enthusiasm was followed by skepticism about the strong but untestable assumptions on which this type of model invariably rests. Since then, the view has emerged that these models should ideally be made part of a sensitivity analysis. This paper presents a formal and flexible approach to such a sensitivity assessment based on local influence (Cook, 1986, Journal of the Royal Statistical Society, Series B 48, 133-169). The influence of perturbing a missing-at-random dropout model in the direction of nonrandom dropout is explored. The method is applied to data from a randomized experiment on the inhibition of testosterone production in rats.

Animals↗
PubMed2000

Obesity, increased linear growth, and risk of type 1 diabetes in children.

OBJECTIVE: The purpose of the present study was to evaluate the effect of obesity and linear growth on the risk of developing type 1 diabetes in children. RESEARCH DESIGN AND METHODS: The study population consists of all diabetic children <15 years of age diagnosed from September 1986 to April 1989 in Finland and their birth date- and sex-matched population-based control subjects. Growth data were obtained from well-baby clinics and school health care units for 586 diabetic and 571 control subjects, resulting in a total of 18,823 paired weight-height observations. RESULTS: Both boys and girls who developed type 1 diabetes were heavier and taller throughout childhood than control children. A 10% unit increment in relative weight was associated with a 50-60% increase in the risk of type 1 diabetes before 3 years of age and a 20-40% increase from 3 to 10 years of age. The increase in risk of type 1 diabetes for 1 SD score increment in relative height was 20-30%. Obesity (relative weight > 120%) after 3 years of age was associated with a more than twofold risk of developing type 1 diabetes. CONCLUSIONS: The present observation that obesity and rapid linear growth are risk factors for type 1 diabetes in children indicates that the increase in the prevalence of obesity and secular growth that has occurred in most industrialized countries over the last decades may be involved in the increase in type 1 diabetes incidence simultaneously observed in many countries.

Aging↗
PubMed1999

Parametric models for incomplete continuous and categorical longitudinal data.

This paper reviews models for incomplete continuous and categorical longitudinal data. In terms of Rubin's classification of missing value processes we are specifically concerned with the problem of nonrandom missingness. A distinction is drawn between the classes of selection and pattern-mixture models and, using several examples, these approaches are compared and contrasted. The central roles of identifiability and sensitivity are emphasized throughout.

Data Interpretation, Statistical↗
PubMed1999

Infant feeding, early weight gain, and risk of type 1 diabetes. Childhood Diabetes in Finland (DiMe) Study Group.

OBJECTIVE: To evaluate whether the increased risk of type 1 diabetes conferred by an early introduction of cow's milk supplements can be mediated by accelerated growth in formula-fed infants. RESEARCH DESIGN AND METHODS: All children < or = 14 years of age who were diagnosed with type 1 diabetes from September 1986 to April 1989 were invited to participate in the study. Birth date- and sex-matched control children were randomly selected from the Finnish Population Registry. At least three weight measurements from the first year of life were obtained for 435 full-term diabetic subjects and 386 control subjects from well-baby clinics and school health care units. RESULTS: Increase in body weight was greater in the diabetic girls than in the control girls, and the difference increased from 111 g (95% CI 0-218, P = 0.04) at 1 month of age to 286 g (95% CI 123-450, P = 0.0006) at 7 months. For boys, the difference in weight between the diabetic subjects and the control subjects remained stable during infancy (difference 95 g, 95% CI-2-205, P = 0.09). Increased weight was associated on average with a 1.5-fold risk of type 1 diabetes. Early introduction of formula feeding (< 3 vs. > or = 3 months) was also associated with an increased risk of type 1 diabetes after adjustment for the individual weight gain curve (adjusted odds ratio 1.53, 95% CI 1.1-2.2). No evidence for interaction was observed. CONCLUSIONS: These observations indicate that an early exposure to cow's milk formula-feeding and rapid growth in infancy are independent risk factors of childhood type 1 diabetes.

Adolescent↗
PubMed1999

Analysis of incomplete public health data.

The problem of dealing with missing values is common throughout statistics and is very prominent with epidemiologic data in the broad sense. Not only do data collection procedures break down, but subjects may be lost to follow up, or simply withdraw their consent without further providing a reason for doing so. In this paper, we review a framework for handling incomplete studies, and then concentrate on a specific case. It comes from a complex health interview survey, conducted in Belgium in 1997, where different types of missingness arise at various levels of the hierarchical sampling procedure.

Belgium↗
PubMed1998

Selection models for repeated measurements with non-random dropout: an illustration of sensitivity.

The outcome-based selection model of Diggle and Kenward for repeated measurements with non-random dropout is applied to a very simple example concerning the occurrence of mastitis in dairy cows, in which the occurrence of mastitis can be modelled as a dropout process. It is shown through sensitivity analysis how the conclusions concerning the dropout mechanism depend crucially on untestable distributional assumptions. This example is exceptional in that from a simple plot of the data two outlying observations can be identified that are the source of the apparent evidence for non-random dropout and also provide an explanation of the behaviour of the sensitivity analysis. It is concluded that a plausible model for the data does not require the assumption of non-random dropout.

Animals↗
PubMed1998

Achilles tendon rupture and sciatica: a possible correlation.

The association between Achilles tendon rupture and sciatica was investigated by questionnaire in 138 patients who underwent repair of an Achilles tendon rupture, and in a group of individuals nominated by the patients, matched for age, sex, and occupation. A total of 102 patients (74%) and 128 peer nominated controls (71%) replied to the questionnaire. Of the 102 respondent patients, 18 had an officebased job, 47 were involved in skilled nonmanual work, and 16 were retired. Back pain had been experienced by 63 of the patients who replied to the questionnaire, and by 91 (75%) of the individuals in the control group (difference not significant). In about 30% of both groups, the pain confined them to bed for at least two days, and resulted in absence from work. Thirteen of the patients and 16 of the controls had undergone thoracic, lumbar, or sacral radiography. One individual in each group had received surgery for back pain. However, 35 of 102 patients had experienced sciatic pain before Achilles tendon rupture. Pain of a similar nature had been experienced by only 15 individuals in the control group (12%) (p < 0.001). Using this study design, we found a highly significant association between Achilles tendon rupture and sciatica. We propose that this association could be due to impaired afferent signals from the lower leg, or to similar collagen or vascular anomalies of the vertebral disc and the Achilles tendon.

Achilles Tendon↗
PubMed1997

Assessment of late results of surgery in talipes equino-varus: a reliability study.

UNLABELLED: The variability of a method for clinical and functional assessment of the long-term results of surgical correction of idiopathic congenital talipes equino varus was studied in ten boys and four girls (average age: 19.1 (SD 2.3 years); 22 affected feet) with radiographical evidence of fusion of the foot and ankle ossification centres. Patients were measured twice, 1 week-1 month apart, by the same investigator and were assessed twice on each visit. Assessment included anthropometry, functional assessment and subjective functional evaluation. Calf circumference, skinfold thickness, foot length and width were highly reproducible. Foot length was not significantly influenced by the operation whereas calf circumference, skinfold thickness and foot width were. Although highly reproducible, hopping was not significantly affected by operation. Active and passive range of motion were significantly different. Each was highly reproducible and both were significantly affected by the operation. Patients reported a high and highly reproducible (within two points) functional level. CONCLUSION: An assistant-administered functional questionnaire together with measurement of active and passive range of motion allows easy, valid and reproducible assessment of long-term results of surgery for idiopathic congenital talipes equino-varus correction. A significant effect of the number and type of operation was evidenced.

Adolescent↗
PubMed1997

Small sample inference for fixed effects from restricted maximum likelihood.

Restricted maximum likelihood (REML) is now well established as a method for estimating the parameters of the general Gaussian linear model with a structured covariance matrix, in particular for mixed linear models. Conventionally, estimates of precision and inference for fixed effects are based on their asymptotic distribution, which is known to be inadequate for some small-sample problems. In this paper, we present a scaled Wald statistic, together with an F approximation to its sampling distribution, that is shown to perform well in a range of small sample settings. The statistic uses an adjusted estimator of the covariance matrix that has reduced small sample bias. This approach has the advantage that it reproduces both the statistics and F distributions in those settings where the latter is exact, namely for Hotelling T2 type statistics and for analysis of variance F-ratios. The performance of the modified statistics is assessed through simulation studies of four different REML analyses and the methods are illustrated using three examples.

Analysis of Variance↗
PubMed1994

The analysis of binary and categorical data from crossover trials.

A review is presented of methods for the analysis of discrete data from crossover trials. The definition and interpretation of the model for the data is used as a central theme. Distinctions are drawn between different types of model, particularly marginal and subject specific. It is seen how much recent methodology for analysing correlated categorical data can be applied successfully to the crossover setting. The current accessibility of each method is considered and the different approaches are illustrated and compared using two examples.

Bias↗
PubMed1994

An application of maximum likelihood and generalized estimating equations to the analysis of ordinal data from a longitudinal study with cases missing at random.

Data are analysed from a longitudinal psychiatric study in which there are no dropouts that do not occur completely at random. A marginal proportional odds model is fitted that relates the response (severity of side effects) to various covariates. Two methods of estimation are used: generalized estimating equations (GEE) and maximum likelihood (ML). Both the complete set of data and the data from only those subjects completing the study are analysed. For the completers-only data, the GEE and ML analyses produce very similar results. These results differ considerably from those obtained from the analyses of the full data set. There are also marked differences between the results obtained from the GEE and ML analysis of the full data set. The occurrence of such differences is consistent with the presence of a non-completely-random dropout process and it can be concluded in this example that both the analyses of the completers only and the GEE analysis of the full data set produce misleading conclusions about the relationships between the response and covariates.

Age Factors↗
PubMed1993

Effect of the prenatal maternal environment on the control of breathing during non-rapid-eye-movement sleep in the developing lamb.

This study examines the effects of altering the prenatal maternal metabolic and hormonal environment via chronic cold exposure of under-fed ewes on developmental changes in breathing control of developing lambs. Breathing frequency and timing were measured during non rapid-eye-movement (non-REM) sleep in lambs born from either shorn or unshorn ewes after being maintained for at least one hour at warm (28-19 degrees C) and cool (14-5 degrees C) ambient temperatures at 1, 4, 14 and 30 days of age. Breathing frequency and oxygen consumption were significantly higher in 1 day old lambs born from shorn ewes compared with those lambs born from unshorn ewes, at both warm and cool ambient temperatures. In the shorn group breathing frequency decreased between 1 and 4 days of age and continued decreasing upto 30 days of age, during which period inspiratory and to a greater extent expiratory time, lengthened. Laryngeal "braking" of expiratory airflow was observed in more than 50% of lambs born from shorn ewes during non-REM sleep in the warm at 4, 14 and 30 days of age, and in the cold at 14 and 30 days of age. In contrast, lambs born from unshorn ewes showed no change in breathing frequency between 1 and 4 days of age, but a decrease was observed between 4 and 14 days of age, whilst laryngeal "braking" of expiratory airflow was rarely observed at any age.(ABSTRACT TRUNCATED AT 250 WORDS)

Animals↗
PubMed1992

Alternative approaches to the analysis of binary and categorical repeated measurements.

The purpose of this paper is to describe, illustrate, and compare a number of different approaches to the analysis of repeated binary and categorical data. These approaches include empirical generalized least squares and generalized estimating equations, as well as traditional log-linear modeling methods. It is shown that the interpretation of the parameters in the various models depends critically on the type of model fitted. In particular, we contrast the population-averaged and subject-specific models. Two example data sets are used to illustrate the approaches, and throughout we concentrate on methods that can be easily implemented.

Clinical Trials as Topic↗