Bmc Med Res Methodol
-
Bmc Med Res Methodol · Jan 2006
Room for improvement? A survey of the methods used in systematic reviews of adverse effects.
Although the methods for conducting systematic reviews of efficacy are well established, there is much less guidance on how systematic reviews of adverse effects should be performed. ⋯ There is an obvious need to improve the methodology and reporting of systematic reviews of adverse effects. The methodology around identification and quality assessment of primary data is the main concern.
-
Bmc Med Res Methodol · Jan 2006
Methodological standards in non-inferiority AIDS trials: moving from adherence to compliance.
The interpretation of the results of active-control trials regarding the efficacy and safety of a new drug is important for drug registration and following clinical use. It has been suggested that non-inferiority and equivalence studies are not reported with the same quantitative rigor as superiority studies. ⋯ Conclusions about non-inferiority should be drawn on the basis of the confidence interval analysis of an appropriate primary endpoint, using the predefined criteria for non-inferiority, in both OT and ITT, in compliance with the non-inferiority and equivalence CONSORT statement. We suggest that the use of the non-inferiority chi-square test may provide additional useful information.
-
Bmc Med Res Methodol · Jan 2006
Multivariable risk prediction can greatly enhance the statistical power of clinical trial subgroup analysis.
When subgroup analyses of a positive clinical trial are unrevealing, such findings are commonly used to argue that the treatment's benefits apply to the entire study population; however, such analyses are often limited by poor statistical power. Multivariable risk-stratified analysis has been proposed as an important advance in investigating heterogeneity in treatment benefits, yet no one has conducted a systematic statistical examination of circumstances influencing the relative merits of this approach vs. conventional subgroup analysis. ⋯ These results suggest that under many likely scenarios, a multivariable risk-stratified approach will have substantially greater statistical power than conventional subgroup analysis for detecting heterogeneity in treatment benefits and safety related to previously unidentified treatment-related harm. Subgroup analyses must always be well-justified and interpreted with care, and conventional subgroup analyses can be useful under some circumstances; however, clinical trial reporting should include a multivariable risk-stratified analysis when an adequate externally-developed risk prediction tool is available.
-
Bmc Med Res Methodol · Jan 2006
Does a "Level I Evidence" rating imply high quality of reporting in orthopaedic randomised controlled trials?
The Levels of Evidence Rating System is widely believed to categorize studies by quality, with Level I studies representing the highest quality evidence. We aimed to determine the reporting quality of Randomised Controlled Trials (RCTs) published in the most frequently cited general orthopaedic journals. ⋯ Our findings suggest that readers should not assume that 1) studies labelled as Level I have high reporting quality and 2) Level I studies have better reporting quality than Level II studies. One should address methodological safeguards individually.
-
Bmc Med Res Methodol · Jan 2006
Comparative StudyBeyond logistic regression: structural equations modelling for binary variables and its application to investigating unobserved confounders.
Structural equation modelling (SEM) has been increasingly used in medical statistics for solving a system of related regression equations. However, a great obstacle for its wider use has been its difficulty in handling categorical variables within the framework of generalised linear models. ⋯ The analysis of binary data can be greatly enhanced by Yule's transformation of odds ratios into estimated correlation matrix that can be further analysed by SEM. The interpretation of results is aided by expressing them as odds ratios which are the most frequently used measure of effect in medical statistics.