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At least 145 records · Page 8Linked to original sources
PubMed1989

Variability of indexes for myocardial ischemia: a comparison of exercise treadmill test, ambulatory electrocardiographic monitoring and symptoms of myocardial ischemia.

Fifty-four patients with chronic stable angina were studied to determine and compare weekly variability of indexes for the detection of myocardial ischemia. All patients underwent three single-blind placebo periods, each lasting 1 week. An exercise treadmill test, 24 h ambulatory electrocardiographic (Holter) monitoring (analyzed blindly) and an accurate diary of anginal attacks and nitroglycerin use were obtained at the end of each placebo period. An unbalanced, completely random component of variance analysis was used to calculate a component for within subject variability and a component for among subject variability. The coefficient of variation and percent variation (within subjects) of onset of chest pain during exercise were 19% and 30%, respectively; the corresponding values were 28% and 33% for onset of 1 mm ST depression, 15% and 15% for exercise duration, 44% and 27% for number of ischemic episodes/24 h, 56% and 43% for anginal frequency and 55% and 27% for nitroglycerin consumption, respectively. With use of this statistical method and variation within subjects, the change in the value of each variable necessary to exceed those attributable to spontaneous variation was determined. The trade-off between repeated measurements and number of subjects, the sample size estimated for planning studies and the minimal sample size for using various designs were also determined. Although the data indicate that all indexes for myocardial ischemia, both during exercise and during daily activity, vary considerably, but the exercise variables have less variability and are more reproducible.(ABSTRACT TRUNCATED AT 250 WORDS)

Ambulatory Care↗
PubMedDate not supplied

[Sample size for estimating attributable risk in cross-sectional studies].

The prevalence of a variety of risk factors and their strength of association with a disease can vary greatly among apparently similar communities. In small communities, risk estimates can also vary from year to year. An identification of important risk factors in each community is then needed, so that interventions can be specifically oriented towards the needs of each specific community. The attributable risk is the adequate measure of association for these purposes. The purpose of this paper is to determine the minimum sample size required to detect a given attributable risk in cross-sectional studies. A table was constructed, presenting the number of exposed subjects necessary to detect a given attributable risk for different combinations of prevalence of disease and prevalence of exposure to a given risk factor, with a power of 0.80 and alpha of 0.05.

Cross-Sectional Studies↗
PubMed1991

A simplified general method for cluster-sample surveys of health in developing countries.

General guidelines are presented for the use of cluster-sample surveys for health surveys in developing countries. The emphasis is on methods which can be used by practitioners with little statistical expertise and no background in sampling. A simple self-weighting design is used, based on that used by the World Health Organization's Expanded Programme on Immunization (EPI). Topics covered include sample design, methods of random selection of areas and households, sample-size calculation and the estimation of proportions, ratios and means with standard errors appropriate to the design. Extensions are discussed, including stratification and multiple stages of selection. Particular attention is paid to allowing for the structure of the survey in estimating sample size, using the design effect and the rate of homogeneity. Guidance is given on possible values for these parameters. A spreadsheet is included for the calculation of standard errors.

Child↗
PubMed2004

Mounting a community-randomized trial: sample size, matching, selection, and randomization issues in PRISM.

This paper discusses some of the processes for establishing a large cluster-randomized trial of a community and primary care intervention in 16 local government areas in Victoria, Australia. The development of the trial in terms of design factors such as sample size estimates and the selection and randomization of communities to intervention or comparison is described. The intervention program to be implemented in Program of Resources, Information and Support for Mothers (PRISM) was conceived as a whole community approach to improving support for all mothers in the first 12 months after birth. A cluster-randomized trial was thus the design of choice from the outset. With a limited number of communities available, a matched-pair design with eight pairs was chosen. Sample size estimates, adjusting for the cluster randomization and the pair-matched design, showed that with eight pairs, on average, 800 women from each community would need to respond to provide sufficient power to determine a 3% reduction in the prevalence of maternal depression 6 months after birth-a reduction deemed to be a worthwhile impact of the intervention to be reliably detected at 80% power. The process of selecting suitable communities and matching them into pairs required careful collection of data on numbers of births, size of the local government areas (LGAs), and an assessment of the capacity of communities to implement the intervention. Ways of dealing with boundary issues associated with potential contamination are discussed. Methods for the selection of feasible configurations of sets of pairs and the ultimate allocation to intervention or comparison are provided in detail. Ultimately, all such studies are a balancing act between selecting the minimum number of communities to detect a meaningful outcome effect of an intervention and the maximum size budget and other resources allow.

Adult↗
PubMedDate not supplied

Estimating true burden of disease detected by screening tests of varying validity.

Timely and accurate information on disease load is essential for planning health programs. Unfortunately, complexity, cost and need of skilled personnel limit the use of screening tools of high validity in developing countries. The disease load estimated with tools of low validity differs considerably from true disease load, particularly for diseases of extreme levels of prevalence/incidence. A tool of 70% sensitivity and specificity may yield a prevalence/incidence rate of 34% (CI: 32.23-35.67%) for a disease whose true rate is only 10.0% (CI: 8.94-11.06%). We proposed a procedure to derive the true estimate in such cases, based on the concepts of sensitivity and specificity of a diagnostic/screening test. It is applied on two sets of real data--one pertaining to incidence rate of low birth weight (LBW) and the other to prevalence rate of obesity--where multiple screening tests of varying validity were used to estimate the magnitude. Different screening tests yielded widely varying incidence/prevalence rates of LBW/obesity. The prevalence/incidence rates derived by using the proposed estimation procedure are similar and close to the true estimate obtained by screening tests considered as gold standard. Further, sample size determined on the basis of the results of a tool of low validity may be either larger or smaller than the required sample size. Estimation of true disease load enables determination of correct sample size, thus improving the precision of the estimate and, in some instances, reducing the cost of investigation.

Cost of Illness↗
PubMed2001

Statistical test to assess rank-order imaging studies.

RATIONALE AND OBJECTIVES: Rank-order experiments often provide a reasonable method of determining whether a large-scale receiver operating characteristic study can be justified. The authors' purpose was to formalize a proposed method for analyzing rank-order imaging experiments and provide methods that can be used in determining sample sizes for both cases and raters. MATERIALS AND METHODS: Simulations were conducted to determine the adequacy of the normal approximation of a statistic used to test the null hypothesis of random ordering. For a multireader experiment, formulas are presented and guidelines are provided to enable investigators to determine the number of required readers (raters) and cases for a specific study. RESULTS: When there are at least five ordered images per case, 10 cases are sufficient to test a random rank order. When there are only three or four images for a case, 20 cases are required. The authors constructed tables of statistical power for selected numbers of ordered images, numbers of cases, and degrees of trend, and they also provide an approximation for use in situations that are not tabled. CONCLUSION: The statistical methods for analyzing rank-order experiments and estimating sample sizes for study planning are relatively simple to implement. The derived formulas for sample size estimation, when applied to typical imaging experiments, indicate that modest numbers of cases and readers are required for rank-order studies.

Humans↗
PubMed2004

A two-year clinical follow-up study in 80 CADASIL subjects: progression patterns and implications for clinical trials.

BACKGROUND AND PURPOSE: Cerebral autosomal dominant arteriopathy with subcortical infarcts and leukoencephalopathy (CADASIL) is an inherited small vessel disease causing stroke and dementia. The aim of this study was to explore the patterns of clinical progression in CADASIL, to check for prognostic variables, and to provide sample size estimates for future therapeutic trials. METHODS: Eighty CADASIL subjects (aged 45.7+/-9.9 years [mean+SD]) were followed prospectively during a mean period of 26.3+/-1.1 months. Standardized scales on disability (Rankin), activities of daily living (Barthel index), neurological outcome (National Institutes of Health Stroke Scale [NIHSS]), and cognition (structural interview for diagnosis of Alzheimer dementia and multi-infarct dementia [SIDAM] and Mattis dementia rating scale [MDRS]) were assessed at baseline and at follow-up. RESULTS: All but 1 individual completed the protocol. At follow-up, the cohort had deteriorated with respect to all clinical scales: Rankin scores (0.3+/-0.7 [mean change+/-SD]; P=0.001), Barthel index (-5.4+/-15.9; P<0.001), NIHSS scores (1.0+/-2.6; P=0.001), SIDAM scores (-2.1+/-6.4; P=0.004), and MDRS scores (-4.3+18.5; P=0.09). The spectrum ranged from marked worsening to some degree of improvement. Seventeen patients experienced a new stroke. Overall, there were 18 strokes within 173 person-years, giving an average incidence rate of stroke of 10.4 per 100 person-years (95% CI, 5.6 to 15.2). Age at baseline was found to be a predictor of clinical progression. Sample size estimates show that the number of individuals needed to include in an interventional trial (assumed duration 2 years, assumed treatment effect 40%) is 602 when using stroke occurrence as an outcome measure. CONCLUSIONS: The clinical course of CADASIL includes periods of acute worsening, chronic progression, stabilization, and improvement. Sample size calculations emphasize the need for surrogate markers of disease progression for future interventional trials.

Activities of Daily Living↗
PubMed1989

Measurement error in assessing the size of posterior subcapsular cataracts from retroillumination photographs.

Twenty-six eyes with posterior subcapsular opacities of various sizes were photographed with the Neitz-Kawara Retroillumination camera. The outline of the opacity in a single photograph of each opacity was traced onto a transparent plastic overlay twice by two independent outliners. Two methods were used to estimate the area within the outlines of the opacities. In the first, a transparent overlay with a standard grid was used to count the number of boxes within the outlines. The second method used computer planimetry to estimate the area within the tracings. We estimated the measurement error associated with a single outlining of an opacity and the contribution of the measurement error to overall sample size requirements in studies comparing the mean areas of posterior subcapsular opacities. Variability in the measurement techniques contributed fewer than 20 additional subjects to overall sample size estimates, a small contribution to total sample size requirements in most studies. An outliner's inherent variability in outlining an opacity was a much larger contributor to the measurement error than was variability in assessing the area of the outline of the opacity. While within outliner variability was similar for the two persons outlining the opacities, there were systematic differences in the way the two traced the outlines. Variability from the use of separate photographs of the same opacity taken by different photographers was minimal.

Cataract↗
PubMed1994

Intraindividual variability of fibrinogen levels and cardiovascular risk profile.

Prospective population studies have established that fibrinogen is an independent predictor for ischemic heart disease and stroke. These study conclusions have prompted recommendations that fibrinogen determinations be included in the cardiovascular risk profile. The routine availability of fibrinogen measurements may result in widespread screening prior to establishing the validity of a single fibrinogen level as an accurate descriptor for individual subjects. The objectives of this study were to describe the methodological and intraindividual components of variability in fibrinogen measurements determined by using the Clauss method; to establish the usefulness of a single fibrinogen measurement on risk stratification and retest reproducibility; and to determine the influence of intraindividual fibrinogen variability on sample size estimates. Fibrinogen levels were measured by a modification of the Clauss method. Three cohorts of apparently healthy, nonsmoking volunteers were recruited. The single-day intra-individual component of fibrinogen variability was determined in 39 subjects. For the 5-day intraindividual component of fibrinogen variability, 32 subjects were recruited, and in the 6-week intraindividual study, 28 subjects were included. The coefficient of variation for the methodological component of fibrinogen variability was 5.8% as determined from batch analyses, but the intraindividual coefficient of variation for replicate measures on a single day was 10.7%. The 5-day intraindividual coefficient of variation was 14.2%, and for the 6-week period it was 17.8%. Based on the 6-week data, an average of four fibrinogen measures is required to reduce misclassification error to less than 10%. Sample size estimates were made based on predetermined levels of statistical power and the 6-week intraindividual and interindividual variability estimates.(ABSTRACT TRUNCATED AT 250 WORDS)

Adult↗
PubMed2003

Evaluating the genetic component of ischemic stroke subtypes: a family history study.

BACKGROUND AND PURPOSE: Twin and family history studies support a role for genetic factors in stroke risk. Because the etiology of ischemic stroke is heterogeneous, genetic factors may vary by etiologic subtype. We determined the familial aggregation of stroke risk in different stroke phenotypes and used the results to model estimated sample size requirements for case-control studies. METHODS: One thousand consecutive white subjects with ischemic stroke and 800 white controls matched for age and sex were recruited. A first-degree family history of stroke and myocardial infarction was obtained by structured interview. Stroke subtype was determined with the use of modified Trial of Org 10172 in Acute Stroke Treatment (TOAST) criteria. RESULTS: A family history of stroke at < or =65 years was a significant risk factor for large-vessel disease (odds ratio [OR], 2.24; 95% CI, 1.49 to 3.36; P<0.001) and for small-vessel disease (OR, 1.93; 95% CI, 1.25 to 2.97; P=0.003). When only cases aged <or =65 years were considered, these ORs increased to 2.93 (95% CI, 1.68 to 5.13) (P<0.001) and 3.15 (95% CI, 1.81 to 5.50) (P<0.001), respectively. No significant associations were seen for cardioembolic stroke or stroke of undetermined etiology. CONCLUSIONS: A family history of vascular disease is an independent risk factor for both large-vessel atherosclerosis and small-vessel disease, especially in cases presenting before age 65 years. The estimated sample sizes for case-control studies illustrate how candidate gene studies for ischemic stroke might be made more effective by focusing on these specific phenotypes, in which the genetic component of the disease appears to be strongest.

Aged↗
PubMed1988

Estimation of sample sizes in case-control studies with multiple controls per case: dichotomous data.

In planning case-control studies with matched sets, the calculation of exact sample sizes is difficult, because this calculation depends on some nuisance parameters that are usually unknown in practice. Using the Pitman efficiency of Miettinen's test relative to McNemar's test, Schlesselman and Stolley (Case-control studies: design, conduct, analysis. Oxford: Oxford University Press, 1982:144-70) derived an approximate sample size formula which requires the assumption that the difference in exposure rates between cases and controls is small. Furthermore, on the basis of an assumption similar to that used in Schlesselman and Stolley's approach, Taylor (Stat Med 1986;5:29-36) proposed another approximation formula. In this paper, an alternative and explicit formula that does not require the exposure difference to be small between case and control groups has been derived. Monte Carlo studies are given for comparing the accuracy of these three procedures. The results indicate that when odds ratios of exposure between cases and controls are small (less than or equal to 4) and there is more than one matched control per case, the formula derived in this paper seems to be the best. When odds ratios are large (greater than or equal to 5), however, Taylor's more conservative estimate is recommended, unless the exposure prevalence in the general population is large (0.9).

Epidemiologic Methods↗
PubMedDate not supplied

Testing strategies to reduce diarrhea in persons with HIV using traditional Chinese medicine: acupuncture and moxibustion.

Diarrhea affects more than 60% of persons living with HIV/AIDS. Diarrhea can be caused by pathogens, neoplastic diseases, side effects of medications, malabsorption, and/or enteropathy. Activities of daily living and quality of life are often affected by HIV/AIDS-related diarrhea. Traditional Chinese medical interventions such as acupuncture and moxibustion show promise in the area of gastrointestinal symptom management. The purposes of this study were to (a) determine the influence of acupuncture and moxibustion in reducing the frequency of diarrhea and increasing stool consistency in HIV-infected men with chronic diarrhea (defined as three or more episodes of watery, liquid, or loose stools in a 24-hour period for 3 weeks or more), (b) ascertain the feasibility of the methodology for a future prospective randomized controlled trial, and (c) determine sample size estimate for a prospective randomized controlled trial. Using a time-series design, 15 HIV-positive men with chronic diarrhea received the same acupuncture/moxibustion treatment for six sessions over a 3-week period. Each participant maintained a daily stool frequency/consistency and medication diary. All treatments were administered by a licensed acupuncturist trained in traditional Chinese medicine. Based on the intent to treat analysis comparing the change in stool frequency from baseline (Week 1) to Week 3 and Week 4, stool frequency reduced approximately one episode per day (Week 3: p < .001; Week 4: p < .005). Stool consistency also improved, from baseline to Week 3 and Week 4, by more than 1 point on Hansen's stool consistency scale. Acupuncture and moxibustion are promising modalities for the symptom management of chronic diarrhea in HIV/AIDS. The results of this pilot study also establish the feasibility of a larger study and provide the empirical basis to serve as preliminary data from which to estimate statistical power and sample size for a larger efficacy study, inclusive of women as well as men.

Activities of Daily Living↗
PubMed2005

Continuous covariates in genetic association studies of case-parent triads: gene and gene-environment interaction effects, population stratification, and power analysis.

We propose a multinomial logistic regression method which permits estimation and likelihood ratio tests for allele effects, their interactions with continuous covariates, and assessment of the degree of population stratification in genetic association studies of case-parent triads. Our approach overcomes the constraint imposed by the categorical nature of explanatory variables in the log-linear model. We also demonstrate that the multinomial logistic method can yield efficient inference in the presence of missing parental genotype data via the use of the Expectation-Maximization (EM) algorithm. We performed simulations to compare the multinomial logistic model with the case-pseudosibling conditional logistic model approach, both of which permit the incorporation of continuous covariates. Simulation results indicate that the multinomial logistic model and the conditional logistic model lead to similar estimates in large samples. A simulation-based method of sample size estimation is also used to show that the two models are approximately equivalent in sample size requirements. When parental genotype data are missing, either completely at random or dependent on covariates, the use of the EM algorithm gives multinomial logistic model greater power. Since the multinomial logistic model offers the possibility of assessing the degree of population stratification in the sample and can also provide efficient inference in the presence of missing parental genotypes, the proposed model has an important application in epidemiological family-based association studies.

Journal Article↗
PubMed1998

Sample size calculations for paired or matched ordinal data.

The problem of calculating the number of subjects in a paired or matched study in which the outcome variable is ordinal is discussed. A common approach in the case of a two category variable is to calculate the required number of discordant pairs, and then divide this by the expected proportion of discordant pairs to obtain the total sample size. An approximate solution for the number of discordant pairs is proposed for ordinal data and compared to sample sizes estimated through simulation. It is shown that the sample sizes are underestimated when the number of categories is two, but that the approximation improves as the number of categories increases. Comparison of the required discordant sample size when there are two categories with the required sample size for more than two categories would suggest that the loss of power is not great if a categorical variable is collapsed into only two categories. However, the total sample size required is likely to be greater with only two categories, since the expected proportion of discordant to concordant pairs increases. Since the expected number of discordant pairs is likely to decrease as the number of categories increases, this suggests that as a rule of thumb the required discordant sample size for the two category case be used as an approximation to the total required sample size when the number of categories is greater than two.

Clinical Trials as Topic↗
PubMed1987

Assessing the feasibility of retrospective cohort studies.

While most epidemiologic cohort studies are preceded by some sort of feasibility study, details of such prior investigations are rarely reported. Yet it is during such feasibility studies that critical decisions are made, such as site selection and definition of exposure. Here we present the details on one such feasibility study, conducted to determine the possibility of a cohort mortality study of workers exposed to ethylene oxide. Issues discussed include methods for estimating sample size and power, for estimating levels of exposure, and for assessing the adequacy of personnel records.

Data Collection↗
PubMedDate not supplied

Simple BASIC program for calculating the cervicovaginal FNP and for estimating the sample size of the number of cervicovaginal smears to be rescreened.

OBJECTIVE: To guide cytotechnologists and pathologists in calculating the false negative proportion, or rate, and the number of Papanicolaou smears to be reevaluated for a meaningful assessment of screening performance, a computer program written in BASIC was prepared, based on several recent publications in the field of cytopathology. RESULTS: A complete program listing and sample runs to help users be cognizant of the necessary inputs to run the program. The output from the program gives the results of the various calculations. CONCLUSION: Since the tedious manual calculations are handled by the computer program, it is more likely for those involved in the interpretation of Papanicolaou smears to follow the approaches suggested by experts in these two areas.

Female↗