Aims The SCORE project was initiated to develop a risk scoring system for use in the clinical management of cardiovascular risk in European clinical practice. Methods and results The project assembled a pool of datasets from 12 European cohort studies, mainly carried out in general population settings. There were 205 178 persons (88 080 women and 117 098 men) representing 2.7 million person years of follow-up. There were 7934 cardiovascular deaths, of which 5652 were deaths from coronary heart disease. Ten-year risk of fatal cardiovascular disease was calculated using a Weibull model in which age was used as a measure of exposure time to risk rather than as a risk factor. Separate estimation equations were calculated for coronary heart disease and for non-coronary cardiovascular disease. These were calculated for high-risk and low-risk regions of Europe. Two parallel estimation models were developed, one based on total cholesterol and the other on total

/pdf/estimation-of-ten-year-risk-of-fatal-cardiovascular-disease-392wpgra75.pdf

Estimation of ten-year risk of fatal cardiovascular disease in Europe: the SCORE project

Funnel plots for detecting bias in meta-analysis: guidelines on choice of axis.

Publication and related bias in meta-analysis : power of statistical tests and prevalence in the literature

Purpose A number of studies have investigated the relationship between microsatellite instability (MSI) and colorectal cancer (CRC) prognosis. Although many have reported a better survival with MSI, estimates of the hazard ratio (HR) among studies differ. To derive a more precise estimate of the prognostic significance of MSI, we have reviewed and pooled data from published studies. Methods Studies stratifying survival in CRC patients by MSI status were eligible for analysis. The principal outcome measure was the HR. Data from eligible studies were pooled using standard techniques. Results Thirty-two eligible studies reported survival in a total of 7,642 cases, including 1,277 with MSI. There was no evidence of publication bias. The combined HR estimate for overall survival associated with MSI was 0.65 (95% CI, 0.59 to 0.71; heterogeneity P = .16; I2 = 20%). This benefit was maintained restricting analyses to clinical trial patients (HR = 0.69; 95% CI, 0.56 to 0.85) and patients with locally advanced CRC ...

Systematic Review of Microsatellite Instability and Colorectal Cancer Prognosis

Caring for a family member with dementia is generally regarded as a chronically stressful process, with potentially negative physical health consequences. However, no quantitative analysis has been conducted on this literature. The authors combined the results of 23 studies to compare the physical health of caregivers with demographically similar noncaregivers. When examined across 11 health categories, caregivers exhibited a slightly greater risk for health problems than did noncaregivers. However, sex and the health category assessed moderated this relationship. Stronger relationships occurred with stress hormones, antibodies, and global reported health. The authors argue that a theoretical model is needed that relates caregiver stressors to illness and proffers moderating roles for vulnerabilities and resources and mediating roles for psychosocial distress and health behaviors.

/pdf/is-caregiving-hazardous-to-one-s-physical-health-a-meta-9lei6w7pdo.pdf

Is caregiving hazardous to one's physical health? A meta-analysis.

Program concord implements L. I. Lin’s concordance correlation coefficient (Lin, 1989), as well as the limits-of-agreement procedure (Bland and Altman, 1986). Recently, Lin (2000 )i ssued an erratum reporting a number of typographical errors in his seminal 1989 paper. Further, changes in Stata Version 7 required modification of concord .T his note rep orts the effect of the errors and provides a corrected and updated program.

https://journals.sagepub.com/doi/pdf/10.1177/1536867X0200200206

A note on the concordance correlation coefficient

Tests for publication bias in meta-analysis

Meta-analysis is a statistical technique for combining results from multiple independent studies, with the aim of estimating a single overall effect. The routines in this package provide facilities to conduct meta-analyses of binary (event) or continuous data from two groups, or intervention effect estimates with corresponding standard errors or confidence intervals. This is an updated version of metan as published in Stata Journal Issue 8, and prior to that in STB-44, authored by Michael J Bradburn, Jonathan J Deeks and Douglas G Altman. Updates include a wide range of random-effects models; cumulative and influence analysis; meta-analysis of proportions; and better handling of heterogeneity, continuity correction and returned values. The routine for constructing forest plots has been separated off (‘forestplot’ command) and hugely extended; extremely flexible and generalised forest plots may now be produced. Also included is an “immediate” command ‘metani’, which accepts numlists or matrices as input rather than variables in memory; the ‘metannt’ program for binary data, which displays estimated intervention effects in terms of the absolute reduction in risk and number needed to treat; and the ‘labbe’ program which produces L'Abbe plots to examine whether the assumption of a common odds ratio, risk ratio or risk difference is reasonable. Further information on this package, including validation scripts, may be found at https://github.com/UCL/metan; and a description of available Stata meta-analysis commands may be found at http://www.stata.com/support/faqs/stat/meta.html.

Thomas Steichen

Papers

A note on the concordance correlation coefficient

Tests for publication bias in meta-analysis

METAN: Stata module for fixed and random effects meta-analysis

Concordance correlation coefficient

Nonparametric trim and fill analysis of publication bias in meta-analysis: erratum