Industry-sponsored research

New treatments compared to established treatments in randomized trials

BACKGROUND

The proportion of proposed new treatments that are 'successful' is of ethical, scientific, and public importance. We investigated how often new, experimental treatments evaluated in randomized controlled trials (RCTs) are superior to established treatments.

OBJECTIVES

Our main question was: "On average how often are new treatments more effective, equally effective or less effective than established treatments?" Additionally, we wanted to explain the observed results, i.e. whether the observed distribution of outcomes is consistent with the 'uncertainty requirement' for enrollment in RCTs. We also investigated the effect of choice of comparator (active versus no treatment/placebo) on the observed results.

SEARCH METHODS

We searched the Cochrane Methodology Register (CMR) 2010, Issue 1 in The Cochrane Library (searched 31 March 2010); MEDLINE Ovid 1950 to March Week 2 2010 (searched 24 March 2010); and EMBASE Ovid 1980 to 2010 Week 11 (searched 24 March 2010).

SELECTION CRITERIA

Cohorts of studies were eligible for the analysis if they met all of the following criteria: (i) consecutive series of RCTs, (ii) registered at or before study onset, and (iii) compared new against established treatments in humans.

DATA COLLECTION AND ANALYSIS

RCTs from four cohorts of RCTs met all inclusion criteria and provided data from 743 RCTs involving 297,744 patients. All four cohorts consisted of publicly funded trials. Two cohorts involved evaluations of new treatments in cancer, one in neurological disorders, and one for mixed types of diseases. We employed kernel density estimation, meta-analysis and meta-regression to assess the probability of new treatments being superior to established treatments in their effect on primary outcomes and overall survival.

MAIN RESULTS

The distribution of effects seen was generally symmetrical in the size of difference between new versus established treatments. Meta-analytic pooling indicated that, on average, new treatments were slightly more favorable both in terms of their effect on reducing the primary outcomes (hazard ratio (HR)/odds ratio (OR) 0.91, 99% confidence interval (CI) 0.88 to 0.95) and improving overall survival (HR 0.95, 99% CI 0.92 to 0.98). No heterogeneity was observed in the analysis based on primary outcomes or overall survival (I(2) = 0%). Kernel density analysis was consistent with the meta-analysis, but showed a fairly symmetrical distribution of new versus established treatments indicating unpredictability in the results. This was consistent with the interpretation that new treatments are only slightly superior to established treatments when tested in RCTs. Additionally, meta-regression demonstrated that results have remained stable over time and that the success rate of new treatments has not changed over the last half century of clinical trials. The results were not significantly affected by the choice of comparator (active versus placebo/no therapy).

AUTHORS' CONCLUSIONS

Society can expect that slightly more than half of new experimental treatments will prove to be better than established treatments when tested in RCTs, but few will be substantially better. This is an important finding for patients (as they contemplate participation in RCTs), researchers (as they plan design of the new trials), and funders (as they assess the 'return on investment'). Although we provide the current best evidence on the question of expected 'success rate' of new versus established treatments consistent with a priori theoretical predictions reflective of 'uncertainty or equipoise hypothesis', it should be noted that our sample represents less than 1% of all available randomized trials; therefore, one should exercise the appropriate caution in interpretation of our findings. In addition, our conclusion applies to publicly funded trials only, as we did not include studies funded by commercial sponsors in our analysis.

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Acknowledgment of uncertainty: a fundamental means to ensure scientific and ethical validity in clinical research

Recognition of the importance of uncertainty in the design of randomized, controlled trials (RCT) has reached the status of a principle. The "uncertainty principle," or less ambiguously, equipoise, holds that a patient should be enrolled in an RCT only if there is substantial uncertainty about which of the trial treatments would benefit the patient most. In fact, the "uncertainty principle" addresses the most important issue of a clinical trial--the choice of an adequate comparative control. Studies in which intervention and control group are believed to be non-equivalent violate the uncertainty principle. Therefore, one would expect that both editors and authors would be particularly careful to include a statement concerning prior beliefs of the investigator(s) about the uncertainty of the treatments that are reported. However, we found no evidence of such a policy in the randomized, controlled trials we examined. We also show that there is a predictable relationship between the uncertainty principle, that is, the moral principle upon which trials are based, and the ultimate outcomes of clinical trials. We postulate that about 50% of innovations are successful, leading to the conclusion that preserving the ethics of clinical research may be the best investment strategy available.