Reducing contamination risk in cluster-randomized infectious disease-intervention trials.

Background: Infectious disease interventions are increasingly tested using cluster-randomized trials (CRTs). These trial settings tend to involve a set of sampling units, such as villages, whose geographic arrangement may present a contamination risk in treatment exposure. The most widely used approach for reducing contamination in these settings is the so-called fried-egg design, which excludes the outer portion of all available clusters from the primary trial analysis. However, the fried-egg design ignores potential intra-cluster spatial heterogeneity and makes the outcome measure inherently less precise. Whereas the fried-egg design may be appropriate in specific settings, alternative methods to optimize the design of CRTs in other settings are lacking. Methods: We present a novel approach for CRT design that either fully includes or fully excludes available clusters in a defined study region, recognizing the potential for intra-cluster spatial heterogeneity. The approach includes an algorithm that allows investigators to identify the maximum number of clusters that could be included for a defined study region and maintain randomness in both the selection of included clusters and the allocation of clusters to either the treatment group or control group. The approach was applied to the design of a CRT testing the effectiveness of malaria vector-control interventions in southern Malawi. Conclusions: Those planning CRTs to evaluate interventions should consider the approach presented here during trial design. The approach provides a novel framework for reducing the risk of contamination among the CRT randomization units in settings where investigators determine the reduction of contamination risk as a high priority and where intra-cluster spatial heterogeneity is likely. By maintaining randomness in the allocation of clusters to either the treatment group or control group, the approach also permits a randomization-valid test of the primary trial hypothesis.

Breast-feeding and childhood-onset type 1 diabetes: a pooled analysis of individual participant data from 43 observational studies.

OBJECTIVE: To investigate if there is a reduced risk of type 1 diabetes in children breastfed or exclusively breastfed by performing a pooled analysis with adjustment for recognized confounders. RESEARCH DESIGN AND METHODS: Relevant studies were identified from literature searches using MEDLINE, Web of Science, and EMBASE. Authors of relevant studies were asked to provide individual participant data or conduct prespecified analyses. Meta-analysis techniques were used to combine odds ratios (ORs) and investigate heterogeneity between studies. RESULTS: Data were available from 43 studies including 9,874 patients with type 1 diabetes. Overall, there was a reduction in the risk of diabetes after exclusive breast-feeding for >2 weeks (20 studies; OR = 0.75, 95% CI 0.64-0.88), the association after exclusive breast-feeding for >3 months was weaker (30 studies; OR = 0.87, 95% CI 0.75-1.00), and no association was observed after (nonexclusive) breast-feeding for >2 weeks (28 studies; OR = 0.93, 95% CI 0.81-1.07) or >3 months (29 studies; OR = 0.88, 95% CI 0.78-1.00). These associations were all subject to marked heterogeneity (I(2) = 58, 76, 54, and 68%, respectively). In studies with lower risk of bias, the reduced risk after exclusive breast-feeding for >2 weeks remained (12 studies; OR = 0.86, 95% CI 0.75-0.99), and heterogeneity was reduced (I(2) = 0%). Adjustments for potential confounders altered these estimates very little. CONCLUSIONS: The pooled analysis suggests weak protective associations between exclusive breast-feeding and type 1 diabetes risk. However, these findings are difficult to interpret because of the marked variation in effect and possible biases (particularly recall bias) inherent in the included studies.

Birth order and childhood type 1 diabetes risk: a pooled analysis of 31 observational studies.

BACKGROUND: The incidence rates of childhood onset type 1 diabetes are almost universally increasing across the globe but the aetiology of the disease remains largely unknown. We investigated whether birth order is associated with the risk of childhood diabetes by performing a pooled analysis of previous studies. METHODS: Relevant studies published before January 2010 were identified from MEDLINE, Web of Science and EMBASE. Authors of studies provided individual patient data or conducted pre-specified analyses. Meta-analysis techniques were used to derive combined odds ratios (ORs), before and after adjustment for confounders, and investigate heterogeneity. RESULTS: Data were available for 6 cohort and 25 case-control studies, including 11,955 cases of type 1 diabetes. Overall, there was no evidence of an association prior to adjustment for confounders. After adjustment for maternal age at birth and other confounders, a reduction in the risk of diabetes in second- or later born children became apparent [fully adjusted OR = 0.90 95% confidence interval (CI) 0.83-0.98; P = 0.02] but this association varied markedly between studies (I² = 67%). An a priori subgroup analysis showed that the association was stronger and more consistent in children < 5 years of age (n = 25 studies, maternal age adjusted OR = 0.84 95% CI 0.75, 0.93; I² = 23%). CONCLUSION: Although the association varied between studies, there was some evidence of a lower risk of childhood onset type 1 diabetes with increasing birth order, particularly in children aged < 5 years. This finding could reflect increased exposure to infections in early life in later born children.

Maternal age at birth and childhood type 1 diabetes: a pooled analysis of 30 observational studies.

OBJECTIVE: The aim if the study was to investigate whether children born to older mothers have an increased risk of type 1 diabetes by performing a pooled analysis of previous studies using individual patient data to adjust for recognized confounders. RESEARCH DESIGN AND METHODS: Relevant studies published before June 2009 were identified from MEDLINE, Web of Science, and EMBASE. Authors of studies were contacted and asked to provide individual patient data or conduct prespecified analyses. Risk estimates of type 1 diabetes by maternal age were calculated for each study, before and after adjustment for potential confounders. Meta-analysis techniques were used to derive combined odds ratios and to investigate heterogeneity among studies. RESULTS: Data were available for 5 cohort and 25 case-control studies, including 14,724 cases of type 1 diabetes. Overall, there was, on average, a 5% (95% CI 2-9) increase in childhood type 1 diabetes odds per 5-year increase in maternal age (P = 0.006), but there was heterogeneity among studies (heterogeneity I(2) = 70%). In studies with a low risk of bias, there was a more marked increase in diabetes odds of 10% per 5-year increase in maternal age. Adjustments for potential confounders little altered these estimates. CONCLUSIONS: There was evidence of a weak but significant linear increase in the risk of childhood type 1 diabetes across the range of maternal ages, but the magnitude of association varied between studies. A very small percentage of the increase in the incidence of childhood type 1 diabetes in recent years could be explained by increases in maternal age.

Joint modelling of repeated measurements and time-to-event outcomes: the fourth Armitage lecture.

In many longitudinal studies, the outcomes recorded on each subject include both a sequence of repeated measurements at pre-specified times and the time at which an event of particular interest occurs: for example, death, recurrence of symptoms or drop out from the study. The event time for each subject may be recorded exactly, interval censored or right censored. The term joint modelling refers to the statistical analysis of the resulting data while taking account of any association between the repeated measurement and time-to-event outcomes. In this paper, we first discuss different approaches to joint modelling and argue that the analysis strategy should depend on the scientific focus of the study. We then describe in detail a particularly simple, fully parametric approach. Finally, we use this approach to re-analyse data from a clinical trial of drug therapies for schizophrenic patients, in which the event time is an interval-censored or right-censored time to withdrawal from the study due to adverse side effects.

Exploratory analysis of longitudinal trials with staggered intervention times.

Longitudinal trials involving surgical interventions commonly have subject-specific intervention times, due to constraints on the availability of surgeons and operating theatres. Moreover, the intervention often effects a discontinuous change in the mean response. We propose a nonparametric estimator for the mean response profile of longitudinal data with staggered intervention times and a discontinuity at the times of intervention, as an exploratory tool to assist the formulation of a suitable parametric model. We use an adaptation of the standard generalized additive model algorithm for estimation, with smoothing constants chosen by a cross-validation criterion. We illustrate the method using longitudinal data from a trial to assess the effect of lung resection surgery in the treatment of emphysema patients.

Do clever brains age more slowly? Further exploration of a nun result.

Recent epidemiological evidence suggests that individuals who have higher levels of mental ability in youth experience a slower cognitive decline as they grow old. In a sample of 3,263 Newcastle residents, average scores on a vocabulary test (Raven's 1965 'Mill Hill A') did not vary, while average scores on a test of fluid mental ability (the Heim, 1970, AH 4 (1) group intelligence test) sharply declined with age from 49 to 92 years. In young adults, Mill Hill A scores are good proxies for AH 4 (1) scores. This relationship allowed individuals' youthful AH 4 (1) test scores to be estimated from their current, unchanged, Mill Hill A scores so that age-related changes in AH 4 test scores over the adult life-span could be estimated and compared between high and low ability groups, men and women, and individuals of different levels of socio-economic advantage. The cross-sectional estimated rate of age-related decline in general mental ability was found to be the same for people of all levels of ability and socio-economic advantage, and not to differ between men and women.

Survival and symptom progression in a geographically based cohort of patients with primary biliary cirrhosis: follow-up for up to 28 years.

BACKGROUND & AIMS: Although several excellent studies have described the natural history of primary biliary cirrhosis, most were reported from tertiary referral centers. We examined the prognosis of primary biliary cirrhosis in a comprehensive geographically defined cohort. METHODS: We followed up 770 primary biliary cirrhosis patients prevalent between January 1987 and December 1994 until death, transplantation, or censor on January 1, 2000, by interview and review of case notes and death certificates. Analysis of survival data was performed with Kaplan-Meier methods and Cox regression. RESULTS: Median patient survival was 9.3 years from diagnosis. Patient age, alkaline phosphatase, albumin, and bilirubin at diagnosis independently predicted survival in Cox modeling. Prothrombin time and histologic stage did not independently affect survival. Observed survival was predicted well by this model and by the Mayo prognostic score (R2(M) = 0.37 and 0.18, respectively; R2(M) is a likelihood-based measure of the percentage information gain from the model due to covariates). Forty-two percent of deaths were caused by liver disease. Thirty-nine patients had liver transplantations by the censor date. Survival was much poorer than for an age- and sex-matched control population (standardized mortality ratio = 2.87 [1.73 excluding liver deaths]). The most common symptoms at diagnosis were pruritus (18.9%) and fatigue (21.0%). Twenty-six percent of patients developed liver failure by 10 years after diagnosis. CONCLUSIONS: Although primary biliary cirrhosis is often now diagnosed at an early stage, the diagnosis still carries important prognostic implications. A significant proportion of patients develop liver failure, require transplantation, or die prematurely after this diagnosis.