ABSTRACT
This paper builds on the recently proposed prediction test for muliple endpoints. The prediction test combines information across multiple endpoints while accounting for the correlation between them. The test performs well with small samples relative to the number of endpoints of interest and is flexible in the hypotheses across the individual endpoints that can be combined. The prediction test addresses a global hypothesis that is of particular interest in early-stage studies and can be used as justification for continuing on to a larger trial. However, the prediction test has several limitations which we seek to address. First, the prediction test is overly conservative when both the effect sizes across all endpoints and the number of endpoints are small. By using a parametric bootstrap to estimate the null distribution, we show that the test achieves the nominal error rate in this situation and increases the power of the test. Second, we provide a framework to allow for predictions of a difference on one or more endpoints. Finally, we extend the test with a composite null hypothesis that allows for different null hypothesized predictive abilities across the endpoints which can be especially useful if the study contains both familiar and novel endpoints. We use an example from a physical activity trial to illustrate these extensions.
ABSTRACT
We encountered a problem in which a study's experimental design called for the use of paired data, but the pairing between subjects had been lost during the data collection procedure. Thus we were presented with a data set consisting of pre and post responses but with no way of determining the dependencies between our observed pre and post values. The aim of the study was to assess whether an intervention called Self-Revelatory Performance had an impact on participant's perceptions of Alzheimer's disease. The participant's responses were measured on an Affect grid before the intervention and on a separate grid after. To address the underlying question in light of the lost pairing we utilized a modified bootstrap approach to create a null hypothesized distribution for our test statistic, which was the distance between the two Affect Grids' Centers of Mass. Using this approach we were able to reject our null hypothesis and conclude that there was evidence the intervention influenced perceptions about the disease.
ABSTRACT
BACKGROUND/AIMS: Angiotensin-converting enzyme inhibitors (ACEI) are the antihypertensives of choice in patients with chronic renal failure (CRF). ACEI by decreasing the synthesis of aldosterone, the main regulator of serum potassium, predispose to the development of hyperkalemia. Although hyperkalemia with administration of ACEI is uncommon in patients with a normal renal function, a preexisting abnormality in potassium hemostasis, as seen in patients with chronic renal failure, may increase the risk of hyperkalemia. METHOD: To determine the predictors of development of hyperkalemia (K >5.1 mEq/l) in patients on ACEI, we retrospectively reviewed medical records of 119 patients followed in our renal clinic. RESULTS: The mean age of the patients was 56 +/- (SD) 13 (range 20-84) years. Sixty-three percent were males, and 37% were females. Sixty-seven percent had a history of diabetes. Eighty five percent of the patients had CRF [creatinine clearance (CrCl) <80 ml/min]. The baseline serum Cr was 2.3 +/- 1.2 (range 0.6-6.9) mg/dl, and the CrCl was 50 +/- 27.5 ml/min. Of the 119 patients 46 (38.6%) developed hyperkalemia (mean K 5.68 +/- 0.3, range 5.2-6.7 mEq/l). Ninety-six percent of the patients who developed hyperkalemia had CRF, and 84% were diabetics. Pearson product-moment correlation revealed a significant positive correlation of hyperkalemia with Cr and a negative correlation of hyperkalemia with CrCl and HCO(3) (Cr: r = 0.42, p < 0.0001; CrCl: r = -0.34, p < 0.0001; HCO(3): r = -0.41, p < 0.0001). Multivariate logistic regression analysis revealed diabetes and serum creatinine to be the main predictors of hyperkalemia. In 31 patients hyperkalemia resolved either with a low-potassium (2 g/day) diet or with diet and a decrease in the dose of ACEI. In 15 patients ACEI had to be discontinued due to persistent hyperkalemia. CONCLUSIONS: We conclude that hyperkalemia is common in patients with CRF on ACEI. The majority of the patients who develop hyperkalemia on ACEI have CRF and diabetes. A large number of patients with CRF require discontinuation of ACEI due to hyperkalemia and are deprived of their renoprotective effects.
