Reporting bias in the literature on the associations of health-related behaviors and statins with cardiovascular disease and all-cause mortality. - Leandro Fórnias Machado de Rezende; Juan Pablo Rey-López; Thiago Hérick de Sá; Nicholas Chartres; Alice Fabbri; Lauren Powell; Emmanuel Stamatakis; Lisa Bero (PLoS Biology)
Reporting bias in the literature occurs when there is selective revealing or suppression of results, influenced by the direction of findings. We assessed the risk of reporting bias in the epidemiological literature on health-related behavior (tobacco, alcohol, diet, physical activity, and sedentary behavior) and cardiovascular disease mortality and all-cause mortality and provided a comparative assessment of reporting bias between health-related behavior and statin (in primary prevention) meta-analyses. We searched Medline, Embase, Cochrane Methodology Register Database, and Web of Science for systematic reviews synthesizing the associations of health-related behavior and statins with cardiovascular disease mortality and all-cause mortality published between 2010 and 2016. Risk of bias in systematic reviews was assessed using the ROBIS tool. Reporting bias in the literature was evaluated via small-study effect and excess significance tests. We included 49 systematic reviews in our study. The majority of these reviews exhibited a high overall risk of bias, with a higher extent in health-related behavior reviews, relative to statins. We reperformed 111 meta-analyses conducted across these reviews, of which 65% had statistically significant results (P < 0.05). Around 22% of health-related behavior meta-analyses showed small-study effect, as compared to none of statin meta-analyses. Physical activity and the smoking research areas had more than 40% of meta-analyses with small-study effect. We found evidence of excess significance in 26% of health-related behavior meta-analyses, as compared to none of statin meta-analyses. Half of the meta-analyses from physical activity, 26% from diet, 18% from sedentary behavior, 14% for smoking, and 12% from alcohol showed evidence of excess significance bias. These biases may be distorting the body of evidence available by providing inaccurate estimates of preventive effects on cardiovascular and all-cause mortality.