The COSMIN-RoB checklist includes three sections with a total of 10 boxes, which is used to evaluate risk of bias of studies on content validity, internal structure, and other measurement properties. COSMIN classifies reliability, measurement error, criteria validity, hypothesis testing for construct validity, and responsiveness as other measurement properties, which primarily focus on the quality of the (sub)scale as a whole, rather than on the item level. Among the five measurement properties, reliability, measurement error and criteria validity are the most widely used in the studies. Therefore, this paper aims to interpret COSMIN-RoB checklist with examples to guide researchers to evaluate the risk of bias of the studies on reliability, measurement error and criteria validity of PROMs.
Measurement properties studies of patient-reported outcome measures (PROMs) aims to validate the measurement properties of PROMs. In the process of designing and statistical analysis of these measurement properties studies, bias will occur if there are any defects, which will affect the quality of PROMs. Therefore, the COSMIN (consensus-based standards for the selection of health measurement instruments) team has developed the COSMIN risk of bias (COSMIN-RoB) checklist to evaluate risk of bias of studies on measurement properties of PROMs. The checklist can be used to develop systematic reviews of PROMs measurement properties, and for PROMs developers, it can also be used to guide the research design in the measurement tool development process for reducing bias. At present, similar assessment tools are lacking in China. Therefore, this article aims to introduce the primary contents of COSMIN-RoB checklist and to interpret how to evaluate risk of bias of the internal structure studies of PROMs with examples.
Objective To explore the effect of vitamin E (VE) on subclinical atherosclerosis (AS) in patients with newly diagnosed type 2 diabetes mellitus. Methods Eighty-five newly diagnosed type 2 diabetic patients without AS were divided into two groups [VE group (n =43) and control group (n =42)] according to the random numeration table. All the patients received comprehensive intervention including the control of blood glucose, blood pressure, blood lipid and body weight and anti-platelet drugs. VE capsule (200 mg/d) was added to VE group (n =41) to evaluate its effects on the incidence of subclinical AS after one year intervention. Results Three patients withdrew during one year follow up. No significant differences of age, sex, baseline body mass index, waist to hip ratio, blood lipid, blood pressure, 24 h urinary albuminuria, insulin resistance index, high sensitive C-reactive protein level, intima-medial thickness (IMT) of common carotid artery, femoral artery and common iliac artery were found between VE group and control group (Pgt;0.05). The decrease of IMT of common carotid artery in VE group after one year intervention was more significant than that in control group (Plt;0.05), whereas the other metabolic parameters mentioned above showed no significant differences between the two groups (Pgt;0.05). The incidence of subclinical AS was significantly higher in VE group(26.8%, 11/41) than that in control group (7.3%, 3/41) (Plt;0.05). Conclusions One year VE supplementation with multifactorial intervention has no beneficial effect on subclinical AS in newly diagnosed type 2 diabetic patients.