Search PubMed⌕ Search

Biomedical subjects

Ian R White

Publications and source records attributed to Ian R White.

At least 19 recordsLinked to original sources
PubMed2007

Instrumental variables and interactions in the causal analysis of a complex clinical trial.

We consider the application of instrumental variable techniques in a longitudinal clinical trial in paediatric HIV/AIDS, with a substantial degree of non-compliance to randomized treatment (Nelfinavir versus placebo) and with left censoring of the outcome variable (HIV RNA concentration). We consider in detail the assumptions and implications behind the inclusion and exclusion of interactions between randomized arm and baseline covariates in modelling actual treatment received, and between treatment and baseline covariates in modelling outcome. Estimated treatment effects were sensitive to inclusion of interactions, and we show how such sensitivity can be explored and explained.

Anti-HIV Agents↗
PubMed2007

Analysis of cluster randomized cross-over trial data: a comparison of methods.

In a cluster randomized cross-over trial, all participating clusters receive both intervention and control treatments consecutively, in separate time periods. Patients recruited by each cluster within the same time period receive the same intervention, and randomization determines order of treatment within a cluster. Such a design has been used on a number of occasions. For analysis of the trial data, the approach of analysing cluster-level summary measures is appealing on the grounds of simplicity, while hierarchical modelling allows for the correlation of patients within periods within clusters and offers flexibility in the model assumptions. We consider several cluster-level approaches and hierarchical models and make comparison in terms of empirical precision, coverage, and practical considerations. The motivation for a cluster randomized trial to employ cross-over of trial arms is particularly strong when the number of clusters available is small, so we examine performance of the methods under small, medium and large (6, 18, 30) numbers of clusters. One hierarchical model and two cluster-level methods were found to perform consistently well across the designs considered. These three methods are efficient, provide appropriate standard errors and coverage, and continue to perform well when incorporating adjustment for an individual-level covariate. We conclude that choice between hierarchical models and cluster-level methods should be influenced by the extent of complexity in the planned analysis.

Cluster Analysis↗
PubMed2007

Patch test frequency to p-phenylenediamine: follow up over the last 6 years.

While the frequency of patch test reactivity to many cosmetic allergens has decreased over the last 20 years, we have previously shown that in our clinic, the patch test reactivity to p-phenylenediamine (PPD) has remained stubbornly high between 2.5% and 4.2% in the years when patch testing was performed with 1% PPD. Further retrospective analysis of the PPD patch test frequency over the last 6 years shows an increasing rate of PPD patch test frequency, showing an upward linear trend. This increasing trend cannot be fully explained by any increase in patch testing of Southern Asian patients or of sensitization caused by PPD exposure from 'temporary henna tattoos'. An alternative explanation may be the increasing use of permanent hair dyes.

Dermatitis, Contact↗
PubMed2006

Bayesian synthesis of epidemiological evidence with different combinations of exposure groups: application to a gene-gene-environment interaction.

Meta-analysis to investigate the joint effect of multiple factors in the aetiology of a disease is of increasing importance in epidemiology. This task is often challenging in practice, because studies typically concentrate on studying the effect of only one exposure, sometimes may report the interaction between two exposures, but rarely address more complex interactions that involve more than two exposures. In this paper, we develop a meta-analysis framework that combines estimates from studies of multiple exposures. A key development is an approach to combining results from studies that report information on any subset or combination of the full set of exposures. The model requires assumptions to be made about the prevalence of the specific exposures. We discuss several possible model specifications and prior distributions, including information internal and external to the meta-analysis data set, and using fixed-effect and random-effects meta-analysis assumptions. The methodology is implemented in an original meta-analysis of studies relating the risk of bladder cancer to two N-acetyltransferase genes, NAT1 and NAT2, and smoking status.

Arylamine N-Acetyltransferase↗
PubMed2006

Previous preeclampsia, preterm delivery, and delivery of a small for gestational age infant and the risk of unexplained stillbirth in the second pregnancy: a retrospective cohort study, Scotland, 1992-2001.

Women with a previous stillbirth are known to be at increased risk of stillbirth in subsequent pregnancies. However, few studies have addressed the association between other complications of pregnancy and the future risk of stillbirth. Using linkage of national pregnancy and perinatal death registries, the authors performed a retrospective cohort study of 133,163 women having a second birth in Scotland between 1992 and 2001 whose first infant was liveborn. The risk of unexplained stillbirth was increased among women with a previous preterm birth (adjusted hazard ratio (HR) = 2.04, 95% confidence interval (CI): 1.34, 3.11), previous delivery of a small for gestational age (SGA) infant (HR = 2.14, 95% CI: 1.59, 2.87), and previous preeclampsia (HR = 1.68, 95% CI: 1.07, 2.62). The associations were similar after adjustment for maternal age, height, marital and smoking status, and interpregnancy interval. There was a statistically significant positive interaction between previous delivery of a SGA infant and previous preeclampsia (p = 0.01): Women with this combination in their first pregnancy had an approximately fivefold risk of unexplained stillbirth in the second pregnancy (HR = 4.95, 95% CI: 2.63, 9.32). Associations were stronger with SGA unexplained stillbirths. The authors conclude that complicated first births of liveborn infants are associated with an increased risk of unexplained stillbirth in the next pregnancy.

Confidence Intervals↗
PubMed2006

Maternal and biochemical predictors of spontaneous preterm birth among nulliparous women: a systematic analysis in relation to the degree of prematurity.

BACKGROUND: Nulliparous women are at increased risk of spontaneous preterm birth. Other maternal and biochemical risk factors have also been described. However, it is unclear whether these associations are strong enough to offer clinically useful prediction. It is also unclear whether the predictive power of these factors varies in relation to the degree of prematurity. METHODS: The risk of spontaneous preterm birth associated with maternal characteristics and second trimester serum screening data was analysed in a dataset of 84 391 first births in Scotland between 1992 and 2001 using Cox and logistic regression. Variation in the relative risk of preterm birth over the period 24-36 weeks was assessed using a test of the proportional hazards assumption. RESULTS: The risk of spontaneous preterm birth was positively associated with maternal serum levels of alpha-fetoprotein, socioeconomic deprivation, number of previous therapeutic abortions, smoking, and being unmarried and was negatively associated with height and body mass index. The risk of preterm birth at 24-28 weeks, but not later gestations, was increased in association with maternal levels of human chorionic gonadotrophin >95th percentile, maternal age <20, and two or more previous miscarriages. The area under the receiver operating characterise curve (95% CI) for models based on these factors was 0.67 (0.63-0.71) for 24-28 weeks, 0.65 (0.62-0.68) for 29-32 weeks, and 0.62 (0.61-0.63) for 33-36 weeks. CONCLUSIONS: Time to event analytic methods can identify factors that are differentially associated with spontaneous preterm birth according to the degree of prematurity. However, models based on maternal and biochemical data perform poorly as a screening test for any degree of spontaneous preterm birth.

Adult↗
PubMed2006

Mercaptobenzothiazole or the mercapto-mix: which should be in the standard series?

Mercaptobenzothiazole (MBT) compounds are well known contact allergens. To detect rubber allergic patients we use both MBT (2% in petrolatum) and a mercapto-mix with 4 constituents of 0.5% each in our standard series. In this article the EECDRG presents data of in total 32,475 consecutive tested patients attending the respective contact dermatitis clinics from 11 centres in Europe to determine if the mix and MBT detected the same allergic patients. We found 327 patients positive to the mix or MBT, or to both. 261 were positive to the mix and 254 to MBT. MBT was negative in 73 patients who were positive to the mix. If the mix had not been in the standard series, on average 22% of patients allergic to a mercapto-compound would have been missed, for MBT this would have been on average 20%. All clinics would have missed a significant number of positive reactions if both compounds had not been tested. We conclude, that both the mercapto mix and MBT are required in the standard series.

Benzothiazoles↗
PubMed2006

Not only oxidized R-(+)- but also S-(-)-limonene is a common cause of contact allergy in dermatitis patients in Europe.

Limonene, one of the most often used fragrance terpenes in any kind of scented products, is prone to air-oxidation. The oxidation products formed have a considerable sensitizing potential. In previous patch test studies on consecutively tested dermatitis patients, oxidized R-limonene has been proven to be a good and frequent indicator of fragrance-related contact allergy. The current study extends these investigations to 6 European clinics of dermatology, where the oxidation mixture of both enantiomers of limonene (R and S) have been tested in 2411 dermatitis patients. Altogether, 63 out of 2411 patients tested (2.6%) reacted to 1 or both the oxidized limonene preparations. Only 2.3% reacted to the oxidized R-limonene and 2.0% to the oxidized S-limonene. In 57% of the cases, simultaneous reactions were observed to both oxidation mixtures. Concomitant reactions to the fragrance mix, colophonium, Myroxylon pereirae, and fragrance-related contact allergy were common in patients reacting to 1 or both the oxidized limonene enantiomers. Our study provides clinical evidence for the importance of oxidation products of limonene in contact allergy. It seems advisable to screen consecutive dermatitis patients with oxidized limonene 3% petrolatum, although this patch test material is not yet commercially available.

Cyclohexenes↗
PubMed2006

Predicting the risk for sudden infant death syndrome from obstetric characteristics: a retrospective cohort study of 505,011 live births.

OBJECTIVE: We sought to develop a simple robust method for assessing the risk for sudden infant death syndrome (SIDS) on the basis of obstetric characteristics. METHODS: A population-based retrospective cohort study was conducted of data from the linked Scottish Morbidity Record, Stillbirth and Infant Death Enquiry and General Registrar's Office database of births and deaths, encompassing births in Scotland between 1992 and 2001. All women who had a singleton live birth between 24 and 43 weeks' gestation and for whom data were available (n = 505,011), divided into model development and validation samples, were studied. The main outcome measure was death of the infant in the first year of life as a result of SIDS. RESULTS: The risk for SIDS was modeled in the development sample using logistic regression with the following predictors: maternal age, parity, marital status, smoking, and the birth weight and the gender of the infant. When the model was evaluated in the validation sample, the area under the receiver operating characteristic curve was 0.84 and the incidence of SIDS was 0.7 per 10,000 (95% confidence interval: 0.3-1.4) among 126,253 women in the lower 50% of predicted risk and 29.7 per 10,000 (95% confidence interval: 23.4-37.2) among the 25,250 women in the top 10% of predicted risk. A logistic-regression model then was developed for the whole population, and the output was converted into adjusted likelihood ratios. These are tabulated and provide a simple method for assessing the risk for SIDS associated with any combination of obstetric characteristics. CONCLUSIONS: A model that uses maternal characteristics and outcome at birth is predictive of the risk for SIDS. This model is presented in a simple form that allows calculation of the individual risk for SIDS.

Birth Weight↗
PubMed2005

Eliciting and using expert opinions about influence of patient characteristics on treatment effects: a Bayesian analysis of the CHARM trials.

When randomized trial results are available for several different groups of patients, neither applying the overall results to each type of patient nor using group-specific results is entirely satisfactory. Instead, we estimate group-specific treatment effects using a Bayesian approach with informative priors for the treatment x group interactions. We describe how we elicited these prior beliefs about the effects of a new drug for the treatment of heart failure in three different patient groups. Using results from three trials, one in each patient group, the posterior mean treatment effects are very similar to the trial-specific maximum likelihood estimates, showing that in this case each trial effectively stands by itself. Our methods can also be applied to subgroup analyses in a single clinical trial, where subgroup-specific posterior means are likely to lie between the subgroup-specific maximum likelihood estimates and the pooled maximum likelihood estimates.

Bayes Theorem↗
PubMed2005

Intensive case management for severe psychotic illness: is there a general benefit for patients with complex needs? A secondary analysis of the UK700 trial data.

The UK700 trial failed to demonstrate an overall benefit of intensive case management (ICM) in patients with severe psychotic illness. This does not discount a benefit for particular subgroups, and evidence of a benefit of ICM for patients of borderline intelligence has been presented. The aim of this study is to investigate whether this effect is part of a general benefit for patients with severe psychosis complicated by additional needs. In the UK700 trial patients with severe psychosis were randomly allocated to ICM or standard case management. For each patient group with complex needs the effect of ICM is compared with that in the rest of the study cohort. Outcome measures are days spent in psychiatric hospital and the admission and discharge rates. ICM may be of benefit to patients with severe psychosis complicated by borderline intelligence or depression, but may cause patients using illicit drugs to spend more time in hospital. There was no convincing evidence of an effect of ICM in a further seven patient groups. ICM is not of general benefit to patients with severe psychosis complicated by additional needs. The benefit of ICM for patients with borderline intelligence is an isolated effect which should be interpreted cautiously until further data are available.

Critical Care↗
PubMed2005

Predicting cesarean section and uterine rupture among women attempting vaginal birth after prior cesarean section.

BACKGROUND: There is currently no validated method for antepartum prediction of the risk of failed vaginal birth after cesarean section and no information on the relationship between the risk of emergency cesarean delivery and the risk of uterine rupture. METHODS AND FINDINGS: We linked a national maternity hospital discharge database and a national registry of perinatal deaths. We studied 23,286 women with one prior cesarean delivery who attempted vaginal birth at or after 40-wk gestation. The population was randomly split into model development and validation groups. The factors associated with emergency cesarean section were maternal age (adjusted odds ratio [OR] = 1.22 per 5-y increase, 95% confidence interval [CI]: 1.16 to 1.28), maternal height (adjusted OR = 0.75 per 5-cm increase, 95% CI: 0.73 to 0.78), male fetus (adjusted OR = 1.18, 95% CI: 1.08 to 1.29), no previous vaginal birth (adjusted OR = 5.08, 95% CI: 4.52 to 5.72), prostaglandin induction of labor (adjusted OR = 1.42, 95% CI: 1.26 to 1.60), and birth at 41-wk (adjusted OR = 1.30, 95% CI: 1.18 to 1.42) or 42-wk (adjusted OR = 1.38, 95% CI: 1.17 to 1.62) gestation compared with 40-wk. In the validation group, 36% of the women had a low predicted risk of caesarean section (< 20%) and 16.5% of women had a high predicted risk (> 40%); 10.9% and 47.7% of these women, respectively, actually had deliveries by caesarean section. The predicted risk of caesarean section was also associated with the risk of all uterine rupture (OR for a 5% increase in predicted risk = 1.22, 95% CI: 1.14 to 1.31) and uterine rupture associated with perinatal death (OR for a 5% increase in predicted risk = 1.32, 95% CI: 1.02 to 1.73). The observed incidence of uterine rupture was 2.0 per 1,000 among women at low risk of cesarean section and 9.1 per 1,000 among those at high risk (relative risk = 4.5, 95% CI: 2.6 to 8.1). We present the model in a simple-to-use format. CONCLUSIONS: We present, to our knowledge, the first validated model for antepartum prediction of the risk of failed vaginal birth after prior cesarean section. Women at increased risk of emergency caesarean section are also at increased risk of uterine rupture, including catastrophic rupture leading to perinatal death.

Age Factors↗
PubMed2005

Randomised controlled trial of acute mental health care by a crisis resolution team: the north Islington crisis study.

OBJECTIVE: To evaluate the effectiveness of a crisis resolution team. DESIGN: Randomised controlled trial. PARTICIPANTS: 260 residents of the inner London Borough of Islington who were experiencing crises severe enough for hospital admission to be considered. INTERVENTIONS: Acute care including a 24 hour crisis resolution team (experimental group), compared with standard care from inpatient services and community mental health teams (control group). MAIN OUTCOME MEASURES: Hospital admission and patients' satisfaction. RESULTS: Patients in the experimental group were less likely to be admitted to hospital in the eight weeks after the crisis (odds ratio 0.19, 95% confidence interval 0.11 to 0.32), though compulsory admission was not significantly reduced. A difference of 1.6 points in the mean score on the client satisfaction questionnaire (CSQ-8) was not quite significant (P = 0.07), although it became so after adjustment for baseline characteristics (P = 0.002). CONCLUSION: Crisis resolution teams can reduce hospital admissions in mental health crises. They may also increase satisfaction in patients, but this was an equivocal finding.

Adolescent↗
PubMed2005

The effect of measurement error in risk factors that change over time in cohort studies: do simple methods overcorrect for 'regression dilution'?

BACKGROUND: The attenuation of the relationship between disease and a risk factor subject to error through 'regression dilution' is well recognized, and researchers often make attempts to adjust for its effects. However, the adjustment methods most often adopted in cohort studies make an implicit assumption that the relationship is driven exclusively by current error-free levels of the risk factor and not by past levels. Here we investigate the bias that is introduced if this assumption is invalid. METHODS: We model disease risk at a particular time in terms of error-free levels of the risk factor at that time and in past periods, and summarize the 'life-course' risk factor-disease relationship using crude current level, history adjusted current level and lifetime level associations. Using systolic blood pressure data from the Framingham Heart Study we show the impact of measurement error on these associations and investigate the biases that can occur with simple correction methods. RESULTS: A simple 'ratio of ranges' type correction factor overestimates the lifetime level association by 29% in the presence of a relatively modest dependency of current risk on past levels (levels 5 years ago half as predictive of current risk as current levels). CONCLUSIONS: Simple methods of correction for regression dilution bias can lead to substantial overcorrection if the risk factor-disease relationship is not short term.

Adult↗
PubMed2005

Assessing subgroup effects with binary data: can the use of different effect measures lead to different conclusions?

BACKGROUND: In order to use the results of a randomised trial, it is necessary to understand whether the overall observed benefit or harm applies to all individuals, or whether some subgroups receive more benefit or harm than others. This decision is commonly guided by a statistical test for interaction. However, with binary outcomes, different effect measures yield different interaction tests. For example, the UK Hip trial explored the impact of ultrasound of infants with suspected hip dysplasia on the occurrence of subsequent hip treatment. Risk ratios were similar between subgroups defined by level of clinical suspicion (P = 0.14), but odds ratios and risk differences differed strongly between subgroups (P < 0.001). DISCUSSION: Interaction tests on different effect measures differ because they test different null hypotheses. A graphical technique demonstrates that the difference arises when the subgroup risks differ markedly. We consider that the test of interaction acts as a check on the applicability of the trial results to all included subgroups. The test of interaction should therefore be applied to the effect measure which is least likely a priori to exhibit an interaction. We give examples of how this might be done. SUMMARY: The choice of interaction test is especially important when the risk of a binary outcome varies widely between subgroups. The interaction test should be pre-specified and should be guided by clinical knowledge.

Data Interpretation, Statistical↗
PubMed2005

Adjusting for partially missing baseline measurements in randomized trials.

Adjustment for baseline variables in a randomized trial can increase power to detect a treatment effect. However, when baseline data are partly missing, analysis of complete cases is inefficient. We consider various possible improvements in the case of normally distributed baseline and outcome variables. Joint modelling of baseline and outcome is the most efficient method. Mean imputation is an excellent alternative, subject to three conditions. Firstly, if baseline and outcome are correlated more than about 0.6 then weighting should be used to allow for the greater information from complete cases. Secondly, imputation should be carried out in a deterministic way, using other baseline variables if possible, but not using randomized arm or outcome. Thirdly, if baselines are not missing completely at random, then a dummy variable for missingness should be included as a covariate (the missing indicator method). The methods are illustrated in a randomized trial in community psychiatry.

Data Interpretation, Statistical↗
PubMed2005

Analyzing the duration of recurrent events in clinical trials: a comparison of approaches using data from the UK700 trial of psychiatric case management.

In studies of chronic disease the outcome measure may be based upon the duration of recurring illness. Our example is the UK700 trial of psychiatric case management, where the total number of days spent in hospital over a 2-year follow-up was the primary outcome. Investigations of treatment effect modifiers were undertaken using an analysis of that primary outcome, a comparison of length of hospitalizations, and also a multi-state modeling approach. The days in hospital outcome was relatively straightforward to analyze, and allowed the complete randomized treatment groups to be compared. In contrast, the comparison of length of hospitalizations included only hospitalized patients, with censored observations not being well accommodated. The multi-state model provided separate treatment effect estimates for admission and discharge, this being more informative about how any reduction in days spent in hospital is achieved. Estimation of the treatment effects through the use of proportional hazards regression allowed appropriate incorporation of censored observations. However, with the multi-state model approach treatment effect estimates are not based upon comparisons of complete randomized treatment groups, as individuals are removed from the risk set for admission whilst at risk for discharge, and vice versa. We conclude that total duration is an appropriate primary outcome for clinical trials, but that multi-state models deserve greater use as an informative secondary analysis.

Case Management↗