BACKGROUND: The Evidence Based Medicine (EBM) paradigm requires that results from Randomized Controlled Trials (RCTs) must be assessed for validity before being assimilated. However, evaluating available evidence is often still based on intuitive processes rather than on rigorous scientific analysis. OBJECTIVE: To establish a hierarchy among the different factors influencing the level of evidence of RCT results, using a Monte Carlo simulation. METHODS: The complete RCT model involved three submodels: i) the input-output submodel for the prediction of events (using the sigmoid dose-response relationship as the basic model), ii) the execution submodel for deviations from a randomized, controlled two-arm parallel trial related to either patient-specific or investigator-specific elements or both: placebo or nocebo effect, errors of measurement, effect of concomitant therapy, regression to the mean phenomenon, blinding process, loss to follow-up and randomization process, iii) the covariate distribution submodel. RESULTS: The most important factors influencing discrepancies in the true-to-observed odds ratio were the blinding process, the measurement errors (affecting either the therapeutic or the adverse effects), the placebo effect, the effect of concomitant therapies and to a less extent the randomization process. Whereas the randomization process remained the only relevant factor in double-blinded trials, the hierarchy of other factors was modified according to the type of blinding. CONCLUSION: In RCTs, the hierarchy of confounding factors differs according to the type of blinding and the current short list of components of the strength of evidence (poorly concealed randomization and lack of blinding) appears to be incomplete.
RCT Entities:
BACKGROUND: The Evidence Based Medicine (EBM) paradigm requires that results from Randomized Controlled Trials (RCTs) must be assessed for validity before being assimilated. However, evaluating available evidence is often still based on intuitive processes rather than on rigorous scientific analysis. OBJECTIVE: To establish a hierarchy among the different factors influencing the level of evidence of RCT results, using a Monte Carlo simulation. METHODS: The complete RCT model involved three submodels: i) the input-output submodel for the prediction of events (using the sigmoid dose-response relationship as the basic model), ii) the execution submodel for deviations from a randomized, controlled two-arm parallel trial related to either patient-specific or investigator-specific elements or both: placebo or nocebo effect, errors of measurement, effect of concomitant therapy, regression to the mean phenomenon, blinding process, loss to follow-up and randomization process, iii) the covariate distribution submodel. RESULTS: The most important factors influencing discrepancies in the true-to-observed odds ratio were the blinding process, the measurement errors (affecting either the therapeutic or the adverse effects), the placebo effect, the effect of concomitant therapies and to a less extent the randomization process. Whereas the randomization process remained the only relevant factor in double-blinded trials, the hierarchy of other factors was modified according to the type of blinding. CONCLUSION: In RCTs, the hierarchy of confounding factors differs according to the type of blinding and the current short list of components of the strength of evidence (poorly concealed randomization and lack of blinding) appears to be incomplete.
Authors: Henrik Engblom; Einar Heiberg; David Erlinge; Svend Eggert Jensen; Jan Erik Nordrehaug; Jean-Luc Dubois-Randé; Sigrun Halvorsen; Pavel Hoffmann; Sasha Koul; Marcus Carlsson; Dan Atar; Håkan Arheden Journal: J Am Heart Assoc Date: 2016-03-09 Impact factor: 5.501