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PubMed1992

Sample size for studying intermediate endpoints within intervention trails or observational studies.

An intermediate endpoint is a biologic event or marker that is a precursor to a given health outcome. Examples of potential intermediate endpoints include serum cholesterol for coronary heart disease, endogenous steroid hormones for breast cancer, and CD4 count for acquired immunodeficiency syndrome. When one is studying a potential intermediate endpoint in the context of an intervention trial, five types of questions may be investigated: 1) Does the intervention affect the intermediate endpoint? 2) Is the intermediate endpoint associated with prognostic or risk factors? 3) Is the intermediate endpoint associated with the main outcome? 4) Is the intervention effect on the main outcome mediated by the intermediate endpoint? 5) Are the prognostic or risk factor effects mediated by the intermediate endpoint? In this paper, the authors show that each of these questions had different sample size requirements, and they illustrate their point with a discussion of an ancillary study of large bowel epithelial proliferation in the National Cancer Institute's Polyp Prevention Trial. The same methods may be used in an observational study, in which case questions 2, 3, and 5 are relevant. However, much larger numbers than those used in the Polyp Prevention Trial example will be required when the main outcome is rare.

Colonic Polyps↗

PubMed2005

A randomized controlled trial of beta-blockers versus endoscopic band ligation for primary prophylaxis: a large sample size is required to show a difference in bleeding rates.

Primary prophylaxis with nonselective beta-blockers in high-risk subjects has been shown to be effective in reducing both esophageal variceal bleeding and mortality. Recently it has been suggested that band ligation may be a better option for primary prophylaxis. We compared nonselective beta-blockers with band ligation in patients with large varices (F2, F3) and elevated hepatic venous wedge pressure gradient (HVWPG, > or = 12 mm Hg). All patients were prospectively followed for variceal bleeding, mortality, and treatment-related complications. Based on previous published studies, we estimated that 90 patients in each arm would be required to show a difference in bleeding rate. The study was prematurely terminated when we realized that our estimated sample size was inadequate to show a difference based on the observed bleeding rate. At the time of termination, 31 patients (Child A, 11; B, 14; C, 6), with a mean HVWPG of 19 +/- 9.1 mm Hg, were randomized to either band ligation (group A; n = 16) or beta-blockers (group B; n = 15). Baseline demographics of both groups were similar and the mean follow-up period was 27.4 +/- 12.9 months. During the follow-up, two patients in group A and one patient in group B had bleeding. Nine patients (29%; group A, six; group B, three; P = ns) died due to non-bleeding-related causes and five (16%) patients (group A, three; group B, two) underwent liver transplantation. Treatment-related complication were minimal in both groups. Despite the selection of high-risk patients, the observed bleeding rate was much lower than anticipated. Based on our observed bleeding rates, 424 patients would be required in each arm to show a difference between band ligation and beta-blocker therapy.

Adrenergic beta-Antagonists↗

PubMed1994

Multipoint radiation hybrid mapping: comparison of methods, sample size requirements, and optimal study characteristics.

There are several statistical methods available for analyzing radiation hybrid (RH) data, but little is known about the ordering accuracy we can expect under common study conditions. Using analytic methods and computer simulation, we compared the ordering accuracy of three multipoint statistical methods: minimum breaks (MB), maximum likelihood (ML), and maximum posterior probability (PP). For 8, 12, and 16 markers and all combinations of numbers of hybrids, retention patterns, and marker spacings considered, the probabilities that the true order is identified as the best order were considerably higher with the ML and PP methods than with the MB method. ML and PP performed similarly, but PP tended to give slightly greater support for the best order than did ML. Our results can be used as guidelines for determining sample size requirements and optimal marker spacing for future RH mapping experiments. For equally spaced markers, intermarker spacing of 30 to 50 cR gave the highest probability of correctly ordering all the markers. For randomly spaced markers, 10-20 cR average intermarker spacing resulted in the highest proportion of markers being placed in a 1000:1 framework map. Assuming equal retention in the analysis when a centromeric model would be more appropriate did not affect the ability of the ML method to accurately order the markers, but did influence the distance estimates obtained.

Animals↗

PubMed1992

Assessment of vitamin A deficiency in a rural area in Mali. Estimation of sample size for the impression cytology test.

The prevalence of vitamin A deficiency among two to ten years old children in a rural area of Mali was assessed by ophthalmic examination, determination of plasma retinol levels and impression cytology with transfer tests. A Public Health problem of vitamin A deficiency was identified in this rural area by: the prevalence of nightblindness significantly (p < 0.001) above the cut-off (1%) defined by the World Health Organization (WHO); the prevalence of corneal scarring significantly (p < 0.001) above the WHO's cut-off (0.05%); the percentage of subjects with plasma retinol levels below 0.35 mumol/l (10 micrograms/dl) significantly (p < 0.001) higher than the WHO's threshold (5%); and 52.8 +/- 8.2% children with "Abnormal" impression cytology as determined by the impression cytology test (IC). This preliminary survey confirmed widespread vitamin A deficiency in Mali. The minimum sample size required for a study using the impression cytology test to determinate a Public Health problem in a population was calculated for different situations. Ophthalmic examination indicated a very high rate of active trachoma (29.6 +/- 7.0%), and a relationship between active trachoma and impression cytology results was identified.

Child↗

PubMed1992

Detection of the relationship between moderate alcoholic beverage consumption and serum levels of estradiol in normal postmenopausal women: effects of alcohol consumption quantitation methods and sample size adequacy.

The purpose of this study was to evaluate the detectability of an effect of moderate alcoholic beverage consumption on the biologic correlate of postmenopausal estradiol levels. Total weekly consumption and beverage-specific intake were assessed using both self-reported usual consumption information and prospective food record data. In terms of total weekly drinks, discrepancies were observed in 35 of the 101 women who reported alcohol use; no consistent pattern of overreporting/underreporting was seen. Although the two alcohol estimates were highly correlated, the relationship between estradiol levels and total weekly alcohol intake was found to be detectable when alcohol consumption based on the food record data was analyzed, but not when the self-report data were examined in a two-tailed hypothesis-testing situation. Evaluating the association between postmenopausal estradiol levels and the two estimates of alcohol intake in random samples of varying sample sizes generated from the mother population of 128 normal postmenopausal women confirmed the finding that the prospectively obtained alcohol data better predict the relationship. Based on the results of this study, it must be concluded that self-reported usual alcohol consumption data must be used with caution when examining an association between alcohol intake and a biologic effect.

Alcohol Drinking↗

PubMed1997

Adequacy testing of training set sample sizes in the development of a computer-assisted diagnosis scheme.

RATIONALE AND OBJECTIVES: The authors assessed the performance changes of a computer-assisted diagnosis (CAD) scheme as a function of the number of regions used for training (rule-setting). MATERIALS AND METHODS: One hundred twenty regions depicting actual masses and 400 suspicious but actually negative regions were selected as a testing data set from a database of 2,146 regions identified as suspicious on 618 mammograms. An artificial neural network using 24 and 16 region-based features as input neurons was applied to classify the regions as positive or negative for the presence of a mass. CAD scheme performance was evaluated on the testing data set as the number of regions used for training increased from 60 to 496. RESULTS: As the number of regions in the training sets increased, the results decreased and plateaued beyond a sample size of approximately 200 regions. Performance with the testing data set continued to improve as the training data set increased in size. CONCLUSION: A trend in a system's performance as a function of training set size can be used to assess adequacy of the training data set in the development of a CAD scheme.

Breast Neoplasms↗

PubMed1993

Bayesian predictive inference for units with small sample sizes. The case of binary random variables.

The National Health Interview Survey is designed to produce precise estimates for the entire United States but not for individual states. In this study, Bayesian predictive inference is used to provide point estimates and measures of variability for the desired finite population quantities. The investigation reported here concerns binary random variables such as the occurrence of at least one doctor visit within the past 12 months. The specification is hierarchic. First, for each cluster, there is a separate logistic regression relating a patient's probability of a doctor visit with his or her characteristics. Second, there is a multivariate linear regression linking the (cluster) regression parameters to covariates measured at the cluster level. A fully Bayesian analysis is carried out; this technique provides gains over synthetic estimation and conventional randomization-based analysis. The reported approach is potentially useful for any situation when the sample size associated with a unit of interest (e.g., a hospital or small geographic area) is too small to permit satisfactory inference using only the data from that unit.

Bayes Theorem↗

PubMed2000

in children. Its results were drawn with limited sample size obtained after a short phase of data collection. A further study should be conducted to get more precise and valid results that may be useful for preventing UTI among children.

This hospital-based case-control study was conducted from September 1998 to January 1999 in Metro Manila, Philippines. General objective of the study is to determine the association between selected hygiene behavior and urinary tract infection (UTI) among children aged 6-12 years. Specifically, the study is designed to examine the relationship between UTI and urination, defecation, washing and bathing habits. Twenty-three cases of children with UTI and an equal number of controls were recruited in four tertiary hospitals. The study association was determined by using odds ratio, the chi-square test and the Fisher exact test, where appropriate, in simple analysis. Furthermore, exact logistic regression analysis was applied to overcome the problem of small sample size. The data suggested that bathing habit less than daily, holding of urination during daytime, and washing habit after defecation might have risk effects on UTI. There was not enough evidence of significant association between UTI and other study exposures. Among extraneous variables, age group or school enrollment of children had a borderline significant association with UTI after adjusted simultaneously for selected variables. This study served as a pilot of the Preventive Nephrology Project (Department of Health, Philippines) in determining selected risk factors of

Case-Control Studies↗

PubMed1992

Low-dose (7.5 mg) oral methotrexate for chronic progressive multiple sclerosis. Design of a randomized, placebo-controlled trial with sample size benefits from a composite outcome variable including preliminary data on toxicity.

OBJECTIVE: To present a detailed description of (1) the study design of this ongoing trial, (2) advantages of using a composite outcome variable instead of multiple individual outcome measures, (3) treatment group characteristics at baseline, and (4) observed short-term methotrexate (MTX) toxicity. DESIGN: Randomized, double-masked, placebo-controlled intervention study. SETTING: Referral-based outpatient multidisciplinary multiple sclerosis (MS) clinic. PATIENTS: Participation offered to all clinically definite chronic progressive multiple sclerosis (CPMS) patients attending clinic ages 21 to 60, disease duration > 1 year, Expanded Disability Status Scale (EDSS) score 3.0 to 6.5 (ambulatory with moderate disability). Patients first stratified by EDSS 3.0 to 5.5 and 6.0 to 6.5, then randomized to MTX or placebo treatment. INTERVENTION: Weekly oral low-dose (7.5 mg) MTX or identical-appearing placebo for 2 years followed by a 1-year observation period. MAIN OUTCOME MEASURES: Sample size calculations undertaken prior to enrolling patients based upon a composite outcome variable consisting of designated change in any of the following functional measures: (1) EDSS, (2) Ambulation Index (AI), (3) Box and Block Test (BBT), and (4) 9-Hole Peg Test (9HPT). RESULTS: (1) Treatment group characteristics were comparable at baseline, (2) no patient has been withdrawn for adverse effects or lost to follow-up, (3) no significant short-term MTX toxicity has been observed. CONCLUSIONS: (1) The use of a composite outcome measure in the design of MS clinical trials is a promising alternative to multiple individual outcome measures that are relatively insensitive to detecting clinical change, (2) low-dose oral weekly MTX does not appear to be associated with significant short-term toxicity in CPMS. Conclusions regarding therapeutic efficacy of MTX in MS must await completion of this clinical trial.

Adult↗

PubMedDate not supplied

Cryptic variation in butterfly eyespot development: the importance of sample size in gene expression studies.

Previous studies have shown that development can be robust to variation in parameters such as the timing or level of gene expression. This leads to the prediction that natural populations should be able to host developmental variation that has little phenotypic effect. Cryptic variation is of particular interest because it can result in selectable phenotypes when "released" by environmental or genetic factors. Currently, however, we have little idea of how variation is distributed between genes or over time in pattern formation processes. Here we survey expression of Notch (N), Spalt (Sal), and Engrailed (En) during butterfly eyespot determination to better understand how pattern formation may vary within a population. We observed substantial heterochronic variance in the progress of spatial expression patterns for all three proteins, suggesting some degree of developmental buffering in eyespot development. Peak variance for different proteins was found at both early and late stages of development, contrasting with previous models suggesting that the distribution of variance should be more temporally focused during pattern formation. We speculate that our observations are representative of a standing reservoir of cryptic variation that may contribute to phenotypic evolution under certain circumstances. Our results also provide a strong cautionary message that gene expression studies with limited sample sizes can be positively misleading in terms of inferring expression pattern time series, as well as for making cross-species phylogenetic comparisons.

Animals↗

PubMed2006

A score test for determining sample size in matched case-control studies with categorical exposure.

The paper considers the problem of determining the number of matched sets in 1 : M matched case-control studies with a categorical exposure having k + 1 categories, k > or = 1. The basic interest lies in constructing a test statistic to test whether the exposure is associated with the disease. Estimates of the k odds ratios for 1 : M matched case-control studies with dichotomous exposure and for 1 : 1 matched case-control studies with exposure at several levels are presented in Breslow and Day (1980), but results holding in full generality were not available so far. We propose a score test for testing the hypothesis of no association between disease and the polychotomous exposure. We exploit the power function of this test statistic to calculate the required number of matched sets to detect specific departures from the null hypothesis of no association. We also consider the situation when there is a natural ordering among the levels of the exposure variable. For ordinal exposure variables, we propose a test for detecting trend in disease risk with increasing levels of the exposure variable. Our methods are illustrated with two datasets, one is a real dataset on colorectal cancer in rats and the other a simulated dataset for studying disease-gene association.

Algorithms↗

PubMed1985