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PubMed2006

A national study of violent behavior in persons with schizophrenia.

CONTEXT: Violent behavior is uncommon, yet problematic, among schizophrenia patients. The complex effects of clinical, interpersonal, and social-environmental risk factors for violence in this population are poorly understood. OBJECTIVE: To examine the prevalence and correlates of violence among schizophrenia patients living in the community by developing multivariable statistical models to assess the net effects of psychotic symptoms and other risk factors for minor and serious violence. DESIGN: A total of 1410 schizophrenia patients were clinically assessed and interviewed about violent behavior in the past 6 months. Data comprise baseline assessments of patients enrolled in the National Institute of Mental Health Clinical Antipsychotic Trials of Intervention Effectiveness. SETTING AND PATIENTS: Adult patients diagnosed as having schizophrenia were enrolled from 56 sites in the United States, including academic medical centers and community providers. MAIN OUTCOME MEASURES: Violence was classified at 2 severity levels: minor violence, corresponding to simple assault without injury or weapon use; and serious violence, corresponding to assault resulting in injury or involving use of a lethal weapon, threat with a lethal weapon in hand, or sexual assault. A composite measure of any violence was also analyzed. RESULTS: The 6-month prevalence of any violence was 19.1%, with 3.6% of participants reporting serious violent behavior. Distinct, but overlapping, sets of risk factors were associated with minor and serious violence. "Positive" psychotic symptoms, such as persecutory ideation, increased the risk of minor and serious violence, while "negative" psychotic symptoms, such as social withdrawal, lowered the risk of serious violence. Minor violence was associated with co-occurring substance abuse and interpersonal and social factors. Serious violence was associated with psychotic and depressive symptoms, childhood conduct problems, and victimization. CONCLUSIONS: Particular clusters of symptoms may increase or decrease violence risk in schizophrenia patients. Violence risk assessment and management in community-based treatment should focus on combinations of clinical and nonclinical risk factors.

Adult↗

PubMed2003

Mortality associated with influenza and respiratory syncytial virus in the United States.

CONTEXT: Influenza and respiratory syncytial virus (RSV) cause substantial morbidity and mortality. Statistical methods used to estimate deaths in the United States attributable to influenza have not accounted for RSV circulation. OBJECTIVE: To develop a statistical model using national mortality and viral surveillance data to estimate annual influenza- and RSV-associated deaths in the United States, by age group, virus, and influenza type and subtype. DESIGN, SETTING, AND POPULATION: Age-specific Poisson regression models using national viral surveillance data for the 1976-1977 through 1998-1999 seasons were used to estimate influenza-associated deaths. Influenza- and RSV-associated deaths were simultaneously estimated for the 1990-1991 through 1998-1999 seasons. MAIN OUTCOME MEASURES: Attributable deaths for 3 categories: underlying pneumonia and influenza, underlying respiratory and circulatory, and all causes. RESULTS: Annual estimates of influenza-associated deaths increased significantly between the 1976-1977 and 1998-1999 seasons for all 3 death categories (P<.001 for each category). For the 1990-1991 through 1998-1999 seasons, the greatest mean numbers of deaths were associated with influenza A(H3N2) viruses, followed by RSV, influenza B, and influenza A(H1N1). Influenza viruses and RSV, respectively, were associated with annual means (SD) of 8097 (3084) and 2707 (196) underlying pneumonia and influenza deaths, 36 155 (11 055) and 11 321 (668) underlying respiratory and circulatory deaths, and 51 203 (15 081) and 17 358 (1086) all-cause deaths. For underlying respiratory and circulatory deaths, 90% of influenza- and 78% of RSV-associated deaths occurred among persons aged 65 years or older. Influenza was associated with more deaths than RSV in all age groups except for children younger than 1 year. On average, influenza was associated with 3 times as many deaths as RSV. CONCLUSIONS: Mortality associated with both influenza and RSV circulation disproportionately affects elderly persons. Influenza deaths have increased substantially in the last 2 decades, in part because of aging of the population, underscoring the need for better prevention measures, including more effective vaccines and vaccination programs for elderly persons.

Adolescent↗

PubMed2005

Genetic testing in an ethnically diverse cohort of high-risk women: a comparative analysis of BRCA1 and BRCA2 mutations in American families of European and African ancestry.

CONTEXT: Ten years after BRCA1 and BRCA2 were first identified as major breast cancer susceptibility genes, the spectrum of mutations and modifiers of risk among many ethnic minorities remain undefined. OBJECTIVES: To characterize the clinical predictors, spectrum, and frequency of BRCA1 and BRCA2 mutations in an ethnically diverse high-risk clinic population and to evaluate the performance of the BRCAPRO statistical model in predicting the likelihood of a mutation. DESIGN, SETTING, AND PARTICIPANTS: Comparative analysis of families (white, Ashkenazi Jewish, African American, Hispanic, Asian) with 2 or more cases of breast and/or ovarian cancer among first- and second-degree relatives. Families were identified at US sites between February 1992 and May 2003; in each family, the individual with the highest probability of being a mutation carrier was tested. MAIN OUTCOME MEASURES: Frequency of BRCA1 and BRCA2 mutations and area under the receiver operating characteristic curve for the BRCAPRO model. RESULTS: The mutation spectrum was vastly different between families of African and European ancestry. Compared with non-Hispanic, non-Jewish whites, African Americans had a lower rate of deleterious BRCA1 and BRCA2 mutations but a higher rate of sequence variations (27.9% vs 46.2% and 44.2% vs 11.5%; P<.001 for overall comparison). Deleterious mutations in BRCA1 and BRCA2 were highest for Ashkenazi Jewish families (69.0%). Early age at diagnosis of breast cancer and number of first- and second-degree relatives with breast and ovarian cancer were significantly associated with an increased likelihood of carrying a BRCA1 or BRCA2 mutation. In discriminating between mutation carriers, BRCAPRO performed as well in African American families as it did in white and Jewish families, with an area under the curve of 0.77 (95% confidence interval, 0.61-0.88) for African American families and 0.70 (95% confidence interval, 0.60-0.79) for white and Jewish families combined. CONCLUSIONS: These data support the use of BRCAPRO and genetic testing for BRCA1 and BRCA2 mutations in the management of high-risk African American families. Irrespective of ancestry, early age at diagnosis and a family history of breast and ovarian cancer are the most powerful predictors of mutation status and should be used to guide clinical decision making.

Adult↗

PubMed1996

Design and analysis of intra-subject variability in cross-over experiments.

Recently, interest has grown in the development of inferential techniques to compare treatment variabilities in the setting of a cross-over experiment. In particular, comparison of treatments with respect to intra-subject variability has greater interest than has inter-subject variability. We begin with a presentation of a general approach for statistical inference within a cross-over design. We discuss three different statistical models where model choice depends on the design and assumptions about carry-over effects. Each model incorporates t-variate random subject effects, where t is the number of treatments. We develop maximum likelihood (ML) and restricted maximum likelihood (REML) approaches to derive parameter estimators and we consider a special case in which closed-form expressions for the variance component estimators are available. Finally, we illustrate the methodologies with the analysis of data from three examples.

Area Under Curve↗

PubMed1996

Statistical analysis of possible bias of clinical judgements due to observing an on-therapy marker variable.

In certain double-blind clinical trials there is the possibility that certain 'marker variables' observable during the trial may in part unblind the trial, even at a subliminal level. At issue is whether or not this potential unblinding biases the investigators' clinical efficacy assessments. This issue arose after the completion of three clinical trials that compared tretinoin emollient cream (TEC) 0.05 per cent to its vehicle in patients with photodamaged skin. The question raised was whether or not possible 'subliminal unblinding' of the investigators and patients, due to the cutaneous irritation associated with topical tretinoin, might have caused a treatment bias in the study. To address this issue, we undertook a reanalysis of these three clinical trials. In doing so, we develop in this paper a statistical modelling approach to address issues of possible bias introduced by the ability to observe such marker variables. The approach utilizes a linear discriminant analysis to introduce an auxiliary categorical variable for the efficacy analysis. A suitable categorical data model permits the estimation of relevant bias effects. We illustrate this approach with data from the three TEC 0.05 per cent trials.

Bias↗

PubMed1998

Assessing treatment-time interaction in clinical trials with time to event data: a meta-analysis of hypertension trials.

Exploration of the variation of treatment effect over time in randomized clinical trials with low event rates is limited by lack of power. A meta-analysis on individual patient data from such trials can partly solve the problem, but brings other computational difficulties. Using an example in hypertension, we describe appropriate methods for graphical description and statistical modelling of treatment-time interactions in large data sets. Also, a method is developed for determining the total number of events required to detect treatment-period interactions of plausible magnitude. We conclude that trialists tend to overinterpret the observed data when looking for potential treatment-time interactions by visual comparisons of survival curves, failing to realize the substantial amounts of data that are needed for their detection and estimation.

Humans↗

PubMed1999

Applying Bayesian ideas to the development of medical guidelines.

Measurements of the quality of health care, in particular the underuse and overuse of medical therapies and diagnostic tests, often involve employment of medical practice guidelines to assess the appropriateness of treatments. This paper presents a case study of a Bayesian analysis for the development of medical guidelines based on expert opinion, using ordinal categorical rater data. We develop guidelines for the use of coronary angiography following an acute myocardial infarction (AMI) for 890 clinical indications using statistical models fit to appropriateness ratings obtained from a nine-member expert panel. The main foci of our analyses were on the estimation of an appropriateness score for each of the clinical indications, an associated measure of precision, and functions of the underlying score. We considered two classes of models that assume the ratings are either in the form of grouped normal data or are ungrouped variables arising from a normal distribution, while permitting rater effects and indication heterogeneity in both. We estimated models using Markov chain Monte Carlo methods and constructed indices quantifying appropriateness based on posterior probabilities of selected model parameters. We compared our model-based approach to the standard approach currently employed in medical guideline development and found that the standard approach correctly identified 99 per cent of the appropriate indications while overestimating appropriateness 18 per cent of the time compared to our model-based approach.

Bayes Theorem↗

PubMed1999

A strategic view of randomized trial design in low-incidence paediatric cancer.

We use a statistical model to examine the relationship between alpha level, sample size, trial duration, patient accrual rate and therapeutic innovation rate on the increase in treatment efficacy achieved after a series of two-treatment randomized phase III trials. In a setting where the trials include most of the patients in the target population for inference, as in some paediatric cancers, we show that the traditional criteria by which one determines trial size are difficult to justify and apply. In particular, using as a measure of evidence type I error levels larger than the typical 5 per cent for judging treatment differences, and performing smaller trials than one would usually consider feasible, yields on average, over a 25-year research course, larger gains in cure rate. Judicious choice of type I error rate and trial size keeps the chance of worsening treatment efficacy at a low level, even while increasing the chance of making large improvements in cure rate. We propose that a more appropriate view of trial design in low-incidence cancer settings is in the overall context of the research setting and long-term goals rather than in the narrow context of the current single trial. From this viewpoint, insistence on large trials and stringent evidence for accepting new treatments can be counter-productive, in that likely gains in efficacy of treatment will be smaller over the long term.

Adolescent↗

PubMed1999

Exposure to PAH and fluoride in aluminum reduction plants in Norway: historical estimation of exposure using process parameters and industrial hygiene measurements.

BACKGROUND: In this study, we describe the methodology used for historical estimation of exposure to fluoride and to PAH in vertical stud Søderberg (VSS) potrooms at two Norwegian aluminum smelters. The assessment was performed in order to develop exposure data for epidemiological studies of cause-specific mortality and cancer incidence. METHODS: The estimation was performed in several steps. In the first step, we estimated the area concentrations of fluoride and PAH in periods with no measurements. Relationships between measured area concentrations and process parameters were investigated by statistical modeling. Process parameters and the models were then used to estimate area concentrations in periods lacking area measurement data. In the second step, the relationships between the area measurements and job specific exposure (personal measurements) were investigated by use of a measurement model. In the last step, the obtained relationships were used to estimate job specific exposure in different periods. RESULTS: The range for the annual exposure estimates in the VSS-potrooms was 0.05-1.7 mg/m3 for fluoride and 3-3,437 micrograms/m3 for PAH. CONCLUSIONS: Despite limitations of available measurements in the early production period, we have concluded that the exposure estimates from this study provide a reasonable tool for the estimation of dose-response relations in subsequent epidemiological analyses.

Air Pollutants, Occupational↗

PubMed1997

Analyzing sibship correlations in birth weight using large sibships from Norway.

Data from the Medical Birth Registry of Norway were used to estimate sibship correlations in large sibships (each with > or = 5 infants among singleton live births surviving the first year of life), while adjusting for covariates such as infant gender, gestational age, maternal age, parity, and time since last pregnancy. This sample of 12,356 full sibs in 2,462 sibships born in Norway between 1968 and 1989 was selected to maximize the information on parity, and a robust approach to estimating both regression coefficients and the sibship correlation using generalized estimating equations (GEE) was employed. In concordance with previous studies, these data showed a high overall correlation in birth weight among full sibs (0.48 +/- 0.01), but this sibship correlation was influenced by parity. In particular, the correlation between the firstborn infant and a subsequent infant was slightly lower than between two subsequent sibs (0.44 +/- 0.01 vs. 0.50 +/- 0.01, respectively). The effect of time between pregnancies was statistically significant, but its predicted impact was modest over the period in which most of these large families were completed. While these data cannot discriminate whether factors influencing birth weight are maternal or fetal in nature, this analysis does illustrate how robust statistical models can be used to estimate sibship correlations while adjusting for covariates in family studies.

Birth Certificates↗

PubMed2000

Reproducibility of the six-minute walking test in chronic heart failure patients.

The six-minute walking test (WT) is used in trials and clinical practice as an easy tool to evaluate the functional capacity of chronic heart failure (CHF) patients. As WT measurements are highly variable both between and within individuals, this study aims at assessing the contribution of the different sources of variation and estimating the reproducibility of the test. A statistical model describing WT measurements as a function of fixed and random effects is proposed and its parameters estimated. We considered 202 stable CHF patients who performed two baseline WTs separated by a 30 minute rest; 49 of them repeated the two tests 3 months later (follow-up control). They had no changes in therapy or major clinical events. Another 31 subjects performed two baseline tests separated by 24 hours. Collected data were analysed using a mixed model methodology. There was no significant difference between measurements taken 30 minutes and 24 hours apart (p = 0.99). A trend effect of 17 (1.4) m (mean (SE)) was consistently found between duplicate tests (p < 0.001). REML estimates of variance components were: 5189 (674) for subject differences in the error-free value; 1280 (304) for subject differences in spontaneous clinical evolution between baseline and follow-up control, and 266 (23) for the within-subject error. Hence, the standard error of measurement was 16.3 m, namely 4 per cent of the average WT performance (403 m) in this sample. The intraclass correlation coefficient was 0.96. We conclude that WT measurements are characterized by good intrasubject reproducibility and excellent reliability. When follow-up studies > or = 3 months are performed, unpredictable changes in individual walking performance due to spontaneous clinical evolution are to be expected. Their clinical significance, however, is not known.

Adult↗

PubMed1993

Cognitive control differences in violent juvenile inpatients.

A stepwise discriminant analysis was used on a calibration sample (n = 135) of dangerous and nondangerous juvenile inpatients to determine which demographic, psychosocial, and cognitive variables best distinguished the violent inpatients. The resulting statistical model was cross-validated on the remainder of the sample (n = 123). Results show that the violent inpatients were more likely to be younger males whose family had a history of criminal behavior and extensive family discord. Moreover, the cognitive variables showed that violent inpatients showed differences in attention and memory, especially when they were processing aggressive stimuli. Results are discussed in terms of the potential ability of cognitive psychology to adopt an ecological perspective and to contribute to forensic assessment.

Adolescent↗

PubMed2006

Prognostic significance of pronormoblasts in erythrocyte predominant myelodysplastic patients.

Recent studies of acute erythroleukemias have reaffirmed DiGuglielmo's syndrome (M6a, myeloblast-predominant) and disease (M6b, pronormoblast-predominant). M6c (mixed myeloblast/pronormoblast) has also been described. However, MDS is still defined according to the percentage of myeloblasts (% myeloblasts) without including the pronormoblast count. A 20-year retrospective study was performed to identify cases demonstrating >or=50% erythrocytic component and <30% calculated blasts (FAB exclusion criteria) without underlying cause (96 cases). Pronormoblast and myeloblast counts and other variables were analyzed as possible explanatory variables of the variations in survival. Considered alone, increasing % myeloblasts and/or percentage of pronormoblasts (% pronormoblasts) were significant predictors of decreasing survival. When all variables were considered as a multivariate group, the best fitting statistical model for predicting survival was a function of age, % pronormoblasts, IPSS cytopenias, platelet count, and percentage erythrocytic component. Of these, % pronormoblasts was by far the most significant. Nonappearance of % myeloblasts in this model is indicative of high correlations of this count with other variables.

Age Factors↗

PubMed2003

Estimating exposures in the asphalt industry for an international epidemiological cohort study of cancer risk.

BACKGROUND: An exposure matrix (EM) for known and suspected carcinogens was required for a multicenter international cohort study of cancer risk and bitumen among asphalt workers. METHODS: Production characteristics in companies enrolled in the study were ascertained through use of a company questionnaire (CQ). Exposures to coal tar, bitumen fume, organic vapor, polycyclic aromatic hydrocarbons, diesel fume, silica, and asbestos were assessed semi-quantitatively using information from CQs, expert judgment, and statistical models. Exposures of road paving workers to bitumen fume, organic vapor, and benzo(a)pyrene were estimated quantitatively by applying regression models, based on monitoring data, to exposure scenarios identified by the CQs. RESULTS: Exposures estimates were derived for 217 companies enrolled in the cohort, plus the Swedish asphalt paving industry in general. Most companies were engaged in road paving and asphalt mixing, but some also participated in general construction and roofing. Coal tar use was most common in Denmark and The Netherlands, but the practice is now obsolete. Quantitative estimates of exposure to bitumen fume, organic vapor, and benzo(a)pyrene for pavers, and semi-quantitative estimates of exposure to these agents among all subjects were strongly correlated. Semi-quantitative estimates of exposure to bitumen fume and coal tar exposures were only moderately correlated. EM assessed non-monotonic historical decrease in exposures to all agents assessed except silica and diesel exhaust. CONCLUSIONS: We produced a data-driven EM using methodology that can be adapted for other multicenter studies.

Cohort Studies↗

PubMed2003

Statistical bioinformatic methods in microbial genome analysis.

It is probable that, increasingly, genome investigations are going to be based on statistical formalization. This review summarizes the state of art and potentiality of using statistics in microbial genome analysis. First, I focus on recent advances in functional genomics, such as finding genes and operons, identifying gene conversion events, detecting DNA replication origins and analysing regulatory sites. Then I describe how to use phylogenetic methods in genome analysis and methods for genome-wide scanning for positively selected amino acids. I conclude with speculations on the future course of genome statistical modeling.

Computational Biology↗

PubMed2003

Precipitation of RNA impurities with high salt in a plasmid DNA purification process: use of experimental design to determine reaction conditions.

The use of high salt solution to precipitate RNA in a pharmaceutical-grade plasmid DNA purification process was investigated. Five antichaotropic salts were tested for their potential to precipitate RNA. Calcium chloride was by far the best precipitant with high RNA removal in a very short incubation time. Calcium chloride precipitation conditions were investigated at two stages of a plasmid purification process using experimental design techniques. The effect of up to five factors on RNA precipitation and plasmid recovery was assessed by statistical modeling. Optimized conditions for calcium chloride precipitation were then introduced to the plasmid purification process resulting in the efficient removal of most impurities (RNA, chromosomal DNA, proteins, and endotoxins).

Calcium Chloride↗

PubMed2002

Preferential transmission of type 1 diabetes from parents to offspring: fact or artifact?

It has been widely reported that men with type 1 diabetes (T1D) tend to be more likely to transmit the disease to their offspring than their female counterparts in Caucasoid populations. Several theories to explain this preferential transmission have been proposed, but so far none of them has been unequivocally proven. Whatever the mechanism, confirmation or refutation of this observation is nonetheless important and practical to the design of future genetic studies of T1D. We carried out some statistical modeling of the preferential transmission. The well-established fact that males have higher a prevalence of T1D than females, an apparent sex difference in fecundity, and a possible misclassification of gestational diabetes mellitus (GDM) as T1D in women have been considered. We demonstrated, first, that the ascertainment of study families through the affected offspring with T1D would generate a higher proportion of fathers than mothers having T1D, even though there was no preferential transmission at all. This can be explained by the male preponderance in T1D prevalence as compared with females, coupled with a greater likelihood of being selected and/or recruited for study in families with T1D fathers due to the fecundity difference. Second, when the study population is ascertained through affected parents, misclassification of mothers with GDM as T1D, and the existence of male/female difference in fecundity in conjunction with a birth order effect, can contribute to the observed preferential transmission, even though there was none. In light of the plausibility of assumptions employed in the analysis and, in particular, an apparent failure to critically examine the effects of these causes of bias in earlier studies, it is perhaps prudent to say that the jury for the existence of preferential transmission in T1D is still out.

Diabetes Mellitus, Type 1↗

PubMed2002

Ascertainment adjustment in complex diseases.

Genetic studies of complex diseases must confront two statistically difficult issues simultaneously. First, in many settings, to minimize the number of individuals to be genotyped, families enriched for disease must be oversampled. Also, statistical models in family studies should allow for residual association. This association will represent unmeasured genetic and environmental factors influencing disease risk. Dealing with these features simultaneously is both compelling and challenging. Burton et al. [2000] (Am. J. Hum. Gen. 69: 1505-14) recently discussed this issue and suggested that ascertainment corrections may lead to problematic parameter estimation. We revisit the issues and examples of Burton et al. [2000] (Am. J. Hum. Genet. 69: 1505-14) and present a more optimistic assessment. Estimation in this context is conceptually straightforward, but may be more problematic in practice. Specifically, we find that even slight misspecification of the random effects distribution in ascertainment-adjusted likelihood can yield severely biased parameter estimates. This result should make scientists wary when interpreting results from ascertainment-adjusted variance-component models. .

Bias↗