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Search indexed PubMed citations on genomics, clinical trials, systematic reviews and public health. Explore titles, authors and supplied subject terms, then open the PubMed record.

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At least 73 records · Page 4Linked to original sources
PubMed2005

Validity and reliability of an inpatient severity of psychiatric illness measure.

Inpatient psychiatric severity measures are often used but few psychometric data are available. This study evaluated the psychometric properties (reliability and validity) of a measure used to assess severity of psychiatric illness among inpatients. Using the severity measure, minimally trained raters conducted retrospective patient record reviews to assess medical necessity for psychiatric hospitalization. The data analysis compared 135 civilly committed psychiatric inpatients with a heterogeneous group of 248 psychiatric inpatients at a general hospital. The severity measure showed acceptable inter-rater reliability in both populations. Two-way analysis of variance showed that the intra-class correlation coefficient for the total score was 0.65 for general hospital subjects and 0.63 for civilly committed subjects. Differences in mean scores were substantial (15 out of a possible 75 points for general hospital subjects versus 42 for civilly committed subjects, Mann-Whitney U = 562, p < 0.001). As expected, all civilly committed subjects were well above admission cut-off score of 12, versus only 64% of the general hospital patients. The measure is appropriate for retrospective severity assessment and may also be useful for pre-admission screening.

Adult↗
PubMed2002

Prediction of survival and opportunistic infections in HIV-infected patients: a comparison of imputation methods of incomplete CD4 counts.

In evaluating the risk of mortality or development of opportunistic infections in HIV-infected patients, the number of CD4 lymphocyte cells per cubic millimetre of blood is widely recognized as one of the best available predictors of such future events. However, its usefulness is limited by the incompleteness and variability of such CD4 measurements during follow-up. Because of these limitations, analysis of such data requires the missing measurements to be 'filled in' or the patients without them to be excluded. We consider multiple imputation of CD4 values based partly on information from other health status measures such as haemoglobin, as well as on the event status of interest. These alternative health status measures are also considered as possible independent predictors of survival endpoints. Our work is motivated by a cohort of 1530 patients enrolled in two AIDS clinical trials. We compare our approach to other strategies such as basing evaluation of risk on baseline CD4, the last measured CD4 before an event, or a time-dependent covariate based on carrying the last CD4 value forward; we conclude with a strong recommendation for multiple imputation.

AIDS-Related Opportunistic Infections↗
PubMed2001

Competing approaches to analysis of failure times with competing risks.

For the analysis of time to event data in contraceptive studies when individuals are subject to competing causes for discontinuation, some authors have recently advocated the use of the cumulative incidence rate as a more appropriate measure to summarize data than the complement of the Kaplan-Meier estimate of discontinuation. The former method estimates the rate of discontinuation in the presence of competing causes, while the latter is a hypothetical rate that would be observed if discontinuations for the other reasons could not occur. The difference between the two methods of analysis is the continuous time equivalent of a debate that took place in the contraceptive literature in the 1960s, when several authors advocated the use of net (adjusted or single decrement life table rates) rates in preference to crude rates (multiple decrement life table rates). A small simulation study illustrates the interpretation of the two types of estimate - the complement of the Kaplan-Meier estimate corresponds to a hypothetical rate where discontinuations for other reasons did not occur, while the cumulative incidence gives systematically lower estimates. The Kaplan-Meier estimates are more appropriate when estimating the effectiveness of a contraceptive method, but the cumulative incidence estimates are more appropriate when making programmatic decisions regarding contraceptive methods. Other areas of application, such as cancer studies, may prefer to use the cumulative incidence estimates, but their use should be determined according to the application.

Computer Simulation↗
PubMed2005

Computational methods in medical decision making: to screen or not to screen?

Screening for a disease such as cancer is often regarded as a beneficial and successful strategy for reducing mortality. However, as with any clinical treatment or intervention, benefit cannot be assumed, and screening can entail both costs and harms, so the screening as a 'treatment' must undergo evaluation. An evaluation requires a definition of the treatment 'benefit', design of studies to measure that benefit with as little bias and variance as possible, and the development of methods for estimating the potential benefit. In screening studies, the factors most central to the evaluation are unobservable (e.g. earliest point in time at which disease becomes detectable, or 'preclinical'; time at which disease might have been detected in the absence of screening; test sensitivity). Thus, screening programs should be evaluated on scenarios in which these factors are varied, to ensure the robustness of the estimated benefit under a variety of circumstances. This article describes the importance of computational methods and simulations to assess the benefit of screening programs, particularly for cancer, based on randomized screening trials, with special attention to benefit time, lead time, and bias due to length-biased sampling.

Computer Simulation↗
PubMed1993

The NHLBI model: a 25 year history.

Although newer techniques and procedures have been developed, many of the clinical trial design and monitoring concepts used today in the NHLBI were implemented 25 years ago. Among these are the organizational structure of multicentre trials and the use of an independent data monitoring committee. Examples of data monitoring committee discussions and decisions are provided.

Clinical Trials as Topic↗
PubMed1993

Monitoring clinical trials: experience of, and proposals under consideration by, the Cancer Therapy Committee of the British Medical Research Council.

The accumulating data from all randomized trials conducted by the Cancer Therapy Committee (CTC) of the British Medical Research Council are monitored on a regular basis. However, for important practical reasons the form of this data monitoring may vary from trial to trial. Thus a trial addressing what is considered a major question in the treatment of cancer patients, (a 'pivotal' or 'high profile' trial), has a formal data monitoring committee (DMC). This is usually made up of two clinicians and one statistician who are completely independent of the trial organization and do not enter patients into the trial. Other trials, which constitute the majority, are monitored by a less formal trial progress group made up of the clinical co-ordinator and trial statistician, sometimes supplemented by a trial participant. Experience with this dual system has led to a new proposal: if the trial progress group wish to modify or stop a trial then they are required to set up and consult an ad hoc DMC for independent advice. This proposal has many advantages, including maximizing the use of resources available, while achieving the degree of objectivity in decision-making required for the many different types of cancer trials conducted by the CTC.

Clinical Trials as Topic↗
PubMedDate not supplied

A method for the analysis of repeated binary outcomes in randomized clinical trials with non-compliance.

When analysing repeated binary data from randomized trials, the model-based approaches, such as generalized estimating equations, are frequently used. Such methods ignore compliance information and give the model-based intention-to-treat estimate of treatment effect. In this paper, the design-based (randomization-based) semi-parametric estimation procedure is given in the estimation of causal risk difference. The resulting risk difference estimator is interpreted as an extension of the instrumental variables estimator for a binary outcome which has the causal interpretation. Extension of the proposed method to stratified analysis is given for data from stratified randomization or meta-analysis. It yields a Mantel-Haenszel type risk difference estimator. As a special case of stratified analysis, the pattern mixture model which stratifies the data by pattern of missing data is performed. Application of the proposed method to a trial in which endpoints were the occurrences of fever over three courses is provided. The same ideas are applied to the causal risk ratio estimation.

Antineoplastic Combined Chemotherapy Protocols↗
PubMed1984

A brief methodological comment on possible inaccuracies induced by multimodal measurement analysis and reporting.

The use of multiple response system measurement adds an important dimension to behavioral medicine research. However, multiple measurement can result in problems in both analyzing and reporting outcome data. Problems in analysis include the increasing of chance findings as the measurement number increases. Problems in reporting include a blurring of response categories when general labels are used, a biased emphasis on the minority of variables showing experimental differences, and a misleading tendency to base comparative conclusions on general labels which do not accurately represent all data measured. Some examples of these problems from methodologically sound studies are described and alternative ways of dealing with the findings from multiple measurements are suggested.

Adult↗
PubMed2001

Dental caries among 10- to 14-year-old children in Ugandan rural areas with 0.5 and 2.5 mg fluoride per liter in drinking water.

The purpose of this study was to report on dental caries among Ugandan children residing in rural areas with either a low or high fluoride concentration in the drinking water, and to assess factors associated with caries. A random sample of 481 children aged 10-14 years was selected from Mpondwe (n = 81) and Kyabayenze (n = 82) in the Kasese district with 0.5 mg and from Mutolere/Kagera (n = 163) and Kabindi (n = 155) in Kisoro with 2.5 mg fluoride/l in the drinking water. The children were examined for caries using the DMFT index as described by the World Health Organization in 1987. The mean DMFT was 0.34 in the whole material. In one low fluoride area, Kyabayenze, all children were caries-free compared to 75% to 86% in the other areas. In Kyabayenze, tea with sugar was taken significantly less frequently than in the other low-fluoride area. In the high-fluoride district, age and consumption of tea with sugar were positively and significantly correlated with caries. Multivariate analyses showed age to be the only significant risk indicator.

Adolescent↗