Search PubMed⌕ Search

SEARCH · Search PubMed

Results for “Biostatistics”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 109 records · Page 6Linked to original sources
PubMed1980

Biostatistical analysis of the collaborative glaucoma study. I. Summary report of the risk factors for glaucomatous visual-field defects.

A prospective collaborative study was conducted in five centers during a 13-year period to identify factors that influence the development of visual-field defects (GVFDs) of open angle glaucoma. In 5,000 subjects, GVFDs developed in only 1.7% of eyes. Statistical analysis of 26 factors at first examination identified five that were significantly related to the development of GVFDs--outflow facility, age, applanation pressure, cup-disc ratio, and pressure change after water drinking. Their absolute initial value, and not its change with time, was the important predictor. Multivariate analysis showed their collective predictive power to be undesirably poor, indicating that other factors must play an important role in the development of GVFDs. Mortality-table analysis indicated that during a period of five years, 98.54% of eyes with initial pressure less than 20 mm Hg continued to be free from GVFDs as compared with 93.34% of those with pressure of 20 mm Hg or greater.

Aged↗
PubMed1978

Management of familial breast cancer. I. Biostatistical-genetic aspects and their limitations as derived from a familial breast cancer resource.

Practical guidelines are given to promote decision-making logic by the physician in managing patients seeking consultation (consultands) because they may be at high familial risk for breast cancer and associated malignant neoplasms. The protocol is designed to aid in the assessment of patients who may become candidates for intensified cancer surveillance and/or prophylactic surgery. A resource comprised of 90 extended breast cancer-prone pedigrees provides the basis for these specific recommendations. The resource shows marked tumor heterogeneity among pedigrees, an approximate 50% incidence of breast cancer and associated malignancies among offspring of affected parents, and threefold higher risk for development of mammary carcinoma in the opposite breast of familial patients with unilateral disease than in sporadic patients. In utilizing this protocol, it is crucial that family history be highly accurate from the standpoint of genealogic relationships and pathologic tumor verification so that management recommendations may reflect sound risk factor assessment. Interpretation of familial risk factors should ideally be made by an informed medical-geneticist. All members of the medical team should then be appraised of familial risk and collectively engage in decision making with the consultand. We believe that this approach can foster more effective control of familial breast cancer.

Adolescent↗
PubMed1996

Tutorial in biostatistics. Designing studies for dose response.

'Dose response' refers to the regression of a response on a stimulus. We review a number of options for dose-response designs, and compare various designs which may be used in practice. We start with two group designs. Next, we introduce basic optimal approximate design theory for simple linear and quadratic regression illustrating different criteria of optimality and their effect on the allocation of the levels of the dose. Then we obtain the efficiencies of these optimal approximate designs and some simple designs which have intuitive appeal (symmetry, equal spacing of treatments, reduced numbers of observations at the highest and lowest doses).

Dose-Response Relationship, Drug↗
PubMed1996

Guidelines for budgeting biostatistics involvement in research projects.

This paper seeks to help biostatisticians develop realistic budgets for their involvement in research projects. The approach is to list categories of expenses and associated questions about the types and levels of projected costs that the budget planner needs to consider. I subdivide the expense categories into smaller subcomponents that should provide for better planning. I also propose an algorithm for determining hourly rates.

Algorithms↗
PubMed1997

Tutorial in biostatistics Bayesian data monitoring in clinical trials.

Many clinical trials organizations use regular interim analyses to monitor the accruing results in large clinical trials. In disease areas such as cancer, where survival is usually a major outcome variable, ethical considerations may lead to a stipulated requirement for data monitoring of mortality. This monitoring has frequently taken the form of limiting interim analyses to be few in number, and specifying an extreme p-value of, for example, p < 0.001 or p < 0.01 as grounds for early termination of the trial. Group-sequential methods are also used. However, none of these approaches formally assesses the impact that the results of a clinical trial may have upon clinical practice. Thus a trial might be terminated early because of apparent treatment benefits, but might fail to influence sceptical clinicians to modify their future treatment policy. We discuss the application of Bayesian methods, including the use of uninformative, sceptical and enthusiastic priors, and demonstrate that the necessary calculations are both straightforward to perform and easy to interpret statistically and clinically. Methods are illustrated with interim analyses of a clinical trial in oesophageal cancer.

Bayes Theorem↗
PubMed1998

Tutorial in biostatistics methods for interval-censored data.

In standard time-to-event or survival analysis, occurrence times of the event of interest are observed exactly or are right-censored, meaning that it is only known that the event occurred after the last observation time. There are numerous methods available for estimating the survival curve and for testing and estimation of the effects of covariates in this context. In some situations, however, the times of the events of interest may only be known to have occurred within an interval of time. In clinical trials, for example, patients are often seen at pre-scheduled visits but the event of interest may occur in between visits. These data are interval-censored. Owing to the lack of well-known statistical methodology and available software, a common ad hoc approach is to assume that the event occurred at the end (or beginning or midpoint) of each interval, and then apply methods for standard time-to-event data. However, this approach can lead to invalid inferences, and in particular will tend to underestimate the standard errors of the estimated parameters. The purpose of this tutorial is to illustrate and compare available methods which correctly treat the data as being interval-censored. It is not meant to be a full review of all existing methods, but only those which are available in standard statistical software, or which can be easily programmed. All approaches will be illustrated on two data sets and compared with methods which ignore the interval-censored nature of the data. We hope this tutorial will allow those familiar with the application of standard survival analysis techniques the option of applying appropriate methods when presented with interval-censored data.

Acquired Immunodeficiency Syndrome↗