317 research outputs found

    Noninferiority trials

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    Noninferiority trials are intended to show that the effect of a new treatment is not worse than that of an active control by more than a specified margin. These trials have a number of inherent weaknesses that superiority trials do not: no internal demonstration of assay sensitivity, no single conservative analysis approach, lack of protection from bias by blinding, and difficulty in specifying the noninferiority margin. Noninferiority trials may sometimes be necessary when a placebo group can not be ethically included, but it should be recognized that the results of such trials are not as credible as those from a superiority trial

    On the Translation of a Treatment's Effect on Disease Progression Into an Effect on Overall Survival

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    There are many examples of treatments for cancer that show a large and statistically significant improvement in progression-free survival (PFS) but fail to show a benefit in overall survival (OS). One recent example that has received considerable attention involves bevacizumab (Avastin) for the treatment of breast cancer. While it seems logical that slowing the rate of progression of a fatal disease would translate into an increase in survival, it is not clear what relative magnitudes of these two effects one should expect. One potential model for the translation of a benefit on disease progression into an OS benefit assumes that patients transition from a low-risk state (pre-progression) into a high-risk state (post-progression), and that the only impact of the treatment is to alter the rate of this transition. In this paper we describe this model and present quantitative results, using an assumption of constant hazards both pre-progression and post-progression. We find that an effect on progression translates into an effect on survival of a smaller magnitude, and that two key factors influence that relationship: the magnitude of the difference between the hazard rate for death in the pre- and post-progression states, and the duration of follow-up

    Room for Improvement in Conducting and Reporting Non-Inferiority Randomized Controlled Trials on Drugs: A Systematic Review

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    BACKGROUND: A non-inferiority (NI) trial is intended to show that the effect of a new treatment is not worse than the comparator. We conducted a review to identify how NI trials were conducted and reported, and whether the standard requirements from the guidelines were followed. METHODOLOGY AND PRINCIPAL FINDINGS: From 300 randomly selected articles on NI trials registered in PubMed at 5 February 2009, we included 227 NI articles that referred to 232 trials. We excluded studies on bioequivalence, trials on healthy volunteers, non-drug trials, and articles of which the full-text version could not be retrieved. A large proportion of trials (34.0%) did not use blinding. The NI margin was reported in 97.8% of the trials, but only 45.7% of the trials reported the method to determine the margin. Most of the trials used either intention to treat (ITT) (34.9%) or per-protocol (PP) analysis (19.4%), while 41.8% of the trials used both methods. Less than 10% of the trials included a placebo arm to confirm the efficacy of the new drug and active comparator against placebo, and less than 5.0% were reporting the similarity of the current trial with the previous comparator's trials. In general, no difference was seen in the quality of reporting before and after the release of the CONSORT statement extension 2006 or between the high-impact and low-impact journals. CONCLUSION: The conduct and reporting of NI trials can be improved, particularly in terms of maximizing the use of blinding, the use of both ITT and PP analysis, reporting the similarity with the previous comparator's trials to guarantee a valid constancy assumption, and most importantly reporting the method to determine the NI margin

    Some considerations in the design and interpretation of antimalarial drug trials in uncomplicated falciparum malaria

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    BACKGROUND: Treatments for uncomplicated falciparum malaria should have high cure rates. The World Health Organization has recently set a target cure rate of 95% assessed at 28 days. The use of more effective drugs, with longer periods of patient follow-up, and parasite genotyping to distinguish recrudescence from reinfection raise issues related to the design and interpretation of antimalarial treatment trials in uncomplicated falciparum malaria which are discussed here. METHODS: The importance of adequate follow-up is presented and the advantages and disadvantages of non-inferiority trials are discussed. The different methods of interpreting trial results are described, and the difficulties created by loss to follow-up and missing or indeterminate genotyping results are reviewed. CONCLUSION: To characterize cure rates adequately assessment of antimalarial drug efficacy in uncomplicated malaria requires a minimum of 28 days and as much as 63 days follow-up after starting treatment. The longer the duration of follow-up in community-based assessments, the greater is the risk that this will be incomplete, and in endemic areas, the greater is the probability of reinfection. Recrudescence can be distinguished from reinfection using PCR genotyping but there are commonly missing or indeterminate results. There is no consensus on how these data should be analysed, and so a variety of approaches have been employed. It is argued that the correct approach to analysing antimalarial drug efficacy assessments is survival analysis, and patients with missing or indeterminate PCR results should either be censored from the analysis, or if there are sufficient data, results should be adjusted based on the identified ratio of new infections to recrudescences at the time of recurrent parasitaemia. Where the estimated cure rates with currently recommended treatments exceed 95%, individual comparisons with new regimens should generally be designed as non-inferiority trials with sample sizes sufficient to determine adequate precision of cure rate estimates (such that the lower 95% confidence interval bound exceeds 90%)

    Informative noncompliance in endpoint trials

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    Noncompliance with study medications is an important issue in the design of endpoint clinical trials. Including noncompliant patient data in an intention-to-treat analysis could seriously decrease study power. Standard methods for calculating sample size account for noncompliance, but all assume that noncompliance is noninformative, i.e., that the risk of discontinuation is independent of the risk of experiencing a study endpoint. Using data from several published clinical trials (OPTIMAAL, LIFE, RENAAL, SOLVD-Prevention and SOLVD-Treatment), we demonstrate that this assumption is often untrue, and we discuss the effect of informative noncompliance on power and sample size
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