Researchers increasingly use meta-analysis to synthesize the results of several studies in order to estimate a common effect. When the outcome variable is continuous, standard meta-analytic approaches assume that the primary studies report the sample mean and standard deviation of the outcome. However, when the outcome is skewed, authors sometimes summarize the data by reporting the sample median and one or both of (i) the minimum and maximum values and (ii) the first and third quartiles, but do not report the mean or standard deviation. To include these studies in meta-analysis, several methods have been developed to estimate the sample mean and standard deviation from the reported summary data. A major limitation of these widely used methods is that they assume that the outcome distribution is normal, which is unlikely to be tenable for studies reporting medians. We propose two novel approaches to estimate the sample mean and standard deviation when data are suspected to be non-normal. Our simulation results and empirical assessments show that the proposed methods often perform better than the existing methods when applied to non-normal data.

Statins reduce all-cause mortality in elderly patients and the magnitude of this effect is substantially larger than had been previously estimated.

Background: Cut-off scores for determining positivity of biomarkers detected by immunohistochemistry are often set arbitrarily and vary between reports. Aims: To evaluate the performance of receiver operating characteristic (ROC) curve analysis in determining clinically important cut-off scores for a novel tumour marker, the receptor for hyaluronic acid mediated motility (RHAMM), and show the reproducibility of the selected cut-off scores in 1197 mismatch-repair (MMR) proficient colorectal cancers (CRC). Methods: Immunohistochemistry for RHAMM was performed using a tissue microarray of 1197 MMRproficient CRC. Immunoreactivity was scored using a semi-quantitative scoring method by evaluating the percentage of positive tumour cells. ROC curve analysis was performed for T stage, N stage, tumour grade, vascular invasion and survival. The score with the shortest distance from the curve to the point with both maximum sensitivity and specificity, i.e. the point (0.0, 1.0), was selected as the cut-off score leading to the greatest number of tumours correctly classified as having or not having the clinical outcome. In order to determine the reliability of the selected cut-off scores, 100 bootstrapped replications were performed to resample the data. Results: The cut-off score for T stage, N stage, tumour grade and vascular invasion was 100% and that for survival 90%. The most frequently selected cut-off score from the 100 resamples was also 100% for T stage, N stage, tumour grade, and vascular invasion and 90% for survival. Conclusions: ROC curve analysis can be used as an alternative method in the selection and validation of cutoff scores for determining the clinically relevant threshold for immunohistochemical tumour positivity.

Subjects with SSc have impaired oral health and oral HRQoL compared with the general population. These data can be used to develop targeted interventions to improve oral health and HRQoL in SSc.