Showing papers on "Funnel plot published in 1999"

Adverse life-events and risk of breast cancer: A meta-analysis

Abstract: Objective. Studies examining the relationship between adverse life events and breast cancer have produced conflicting results. A systematic review of the published studies was therefore carried out. Methods. Electronic databases and bibliographies of review articles were searched for studies in any language. Studies were assessed for methodological quality by two reviewers. Results. Twenty-nine studies were found. These were of variable quality. Random effects meta-analysis of the higher quality studies found no significant relationship between breast cancer and either bereavement (summary odds ratio(OR)=0. 9;95% confidence interval (CI) 0. 57 to 1. 45) or other adverse life-events (summary OR=0. 8; 95% CI 0. 61 to 1. 06). Funnel plots may be suggestive of publication bias, with small studies reporting negative findings less likely to be published. Conclusions. Good quality case-control studies, and the single large prospective study in this area, do not support the hypothesis of a casual relationship between adverse life events and onset of breast cancer.

Bias in meta-analysis and funnel plot asymmetry.

Abstract: International experiences reveal the important role played by scientific research and systematic study a problems, in effectively tackling change in the health sector. Meta-analysis was introduced to address the problem of synthesizing the large quantity of information on a particular subject. It is viewed, only as a step in the process of developing better tools to quantify information across studies. The selection of trials for inclusion in a meta-analysis may be biased if selection is restricted to published trials, to trials published in English language journals, to trials published in prestigious journals or to trials cited by other authors. Funnel plot is graphical display of sample size plotted against effect size for the studies included in a meta-analysis, which can be used to investigate bias. When all the studies have been located, the distribution of points should resemble a funnel. If there are gaps in the funnel shape it indicates that some studies may have not been published or located. In evaluating bias, we use meta-analysis studies about radiotherapy alone versus combined radiotherapy and chemotherapy in stages IIIa and IIIb non-small cell lung cancer. A simple analysis of funnel plots provides useful test for the likely presence of bias in meta-analyses, but as the capacity to detect bias will be limited when meta-analyses are based on a limited number of small trials the results from such analyses should be treated with considerable caution.

Relation between hostility and coronary heart disease. Evidence does not support link.

Abstract: Editor—The summary points of Hemingway and Marmot’s review of psychosocial risk factors for coronary heart disease may be misleading.1 The first of these states that “prospective cohort studies show a possible aetiological role for type A/hostility.” However, of the four prospective studies of hostility, only two show any significant association between hostility and coronary heart disease (one for women only). Six of the nine aetiological studies of type A behaviour also show no association with coronary heart disease. The other three studies give no information on completeness of follow up or whether outcomes such as angina were assessed in a blinded manner. One of these studies had minimal adjustment for confounding. No study showed any prognostic role for type A behaviour or hostility. Taken together, these studies do not represent robust evidence that these psychological variables have an important role in the development or prognosis of coronary heart disease. The authors also rightly suggest that the role of publication bias should be considered. We recently investigated this by re-examining a meta-analysis, also cited by Hemingway and Marmot, which pooled several prospective and retrospective studies of hostility and coronary heart disease and concluded that hostility was an independent risk factor.2 A funnel plot of these studies suggests publication and related biases (figure (top)), indicating underpublication of negative results. However, the apparent publication bias is more likely to be a result of poor methodological quality—in particular, inadequate adjustment for confounding in the primary studies. When we took this into account (using regression to adjust the effect sizes according to the number of variables used as adjusters in the primary study) the relation between hostility and coronary heart disease disappeared and the funnel plot became symmetrical (figure (bottom)). This supports the view that publication bias among these studies should be considered only when other sources of bias, such as the internal validity of the included studies, are taken into account, as suggested by Egger et al.3 Claims about the toxicity of type A behaviour and hostility have led to the development of behavioural “treatments” for these putative risk factors. A recent editorial also went as far as to suggest that, as hostility appeared to be a “toxic component,” we should all be nice to each other.4 Perhaps in the light of Hemingway and Marmot’s review, and the above comments, this advice should be reconsidered.