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Publication bias in antipsychotic trials: an analysis of efficacy comparing the published literature to the US Food and Drug Administration database.

ABSTRACT: Publication bias compromises the validity of evidence-based medicine, yet a growing body of research shows that this problem is widespread. Efficacy data from drug regulatory agencies, e.g., the US Food and Drug Administration (FDA), can serve as a benchmark or control against which data in journal articles can be checked. Thus one may determine whether publication bias is present and quantify the extent to which it inflates apparent drug efficacy.FDA Drug Approval Packages for eight second-generation antipsychotics-aripiprazole, iloperidone, olanzapine, paliperidone, quetiapine, risperidone, risperidone long-acting injection (risperidone LAI), and ziprasidone--were used to identify a cohort of 24 FDA-registered premarketing trials. The results of these trials according to the FDA were compared with the results conveyed in corresponding journal articles. The relationship between study outcome and publication status was examined, and effect sizes derived from the two data sources were compared. Among the 24 FDA-registered trials, four (17%) were unpublished. Of these, three failed to show that the study drug had a statistical advantage over placebo, and one showed the study drug was statistically inferior to the active comparator. Among the 20 published trials, the five that were not positive, according to the FDA, showed some evidence of outcome reporting bias. However, the association between trial outcome and publication status did not reach statistical significance. Further, the apparent increase in the effect size point estimate due to publication bias was modest (8%) and not statistically significant. On the other hand, the effect size for unpublished trials (0.23, 95% confidence interval 0.07 to 0.39) was less than half that for the published trials (0.47, 95% confidence interval 0.40 to 0.54), a difference that was significant.The magnitude of publication bias found for antipsychotics was less than that found previously for antidepressants, possibly because antipsychotics demonstrate superiority to placebo more consistently. Without increased access to regulatory agency data, publication bias will continue to blur distinctions between effective and ineffective drugs.

SUBMITTER: Turner EH

PROVIDER: S-EPMC3308934 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:BackgroundPrevious studies of drug trials submitted to regulatory authorities have documented selective reporting of both entire trials and favorable results. The objective of this study is to determine the publication rate of efficacy trials submitted to the Food and Drug Administration (FDA) in approved New Drug Applications (NDAs) and to compare the trial characteristics as reported by the FDA with those reported in publications.Methods and findingsThis is an observational study of all efficacy trials found in approved NDAs for New Molecular Entities (NMEs) from 2001 to 2002 inclusive and all published clinical trials corresponding to the trials within the NDAs. For each trial included in the NDA, we assessed its publication status, primary outcome(s) reported and their statistical significance, and conclusions. Seventy-eight percent (128/164) of efficacy trials contained in FDA reviews of NDAs were published. In a multivariate model, trials with favorable primary outcomes (OR = 4.7, 95% confidence interval [CI] 1.33-17.1, p = 0.018) and active controls (OR = 3.4, 95% CI 1.02-11.2, p = 0.047) were more likely to be published. Forty-one primary outcomes from the NDAs were omitted from the papers. Papers included 155 outcomes that were in the NDAs, 15 additional outcomes that favored the test drug, and two other neutral or unknown additional outcomes. Excluding outcomes with unknown significance, there were 43 outcomes in the NDAs that did not favor the NDA drug. Of these, 20 (47%) were not included in the papers. The statistical significance of five of the remaining 23 outcomes (22%) changed between the NDA and the paper, with four changing to favor the test drug in the paper (p = 0.38). Excluding unknowns, 99 conclusions were provided in both NDAs and papers, nine conclusions (9%) changed from the FDA review of the NDA to the paper, and all nine did so to favor the test drug (100%, 95% CI 72%-100%, p = 0.0039).ConclusionsMany trials were still not published 5 y after FDA approval. Discrepancies between the trial information reviewed by the FDA and information found in published trials tended to lead to more favorable presentations of the NDA drugs in the publications. Thus, the information that is readily available in the scientific literature to health care professionals is incomplete and potentially biased.

Project description:ImportancePublishing study protocols might reduce research waste because of unclear methods or incomplete reporting; on the other hand, there might be few additional benefits of publishing protocols for registered trials that are never completed or published. No study has investigated the proportion of published protocols associated with published results.ObjectiveTo estimate the proportion of published trial protocols for which there are not associated published results.Design, setting, and participantsThis cross-sectional study used stratified random sampling to identify registered clinical trials with protocols published between January 2011 and August 2022 and indexed in PubMed Central. Ongoing studies and those within 1 year of the primary completion date on ClinicalTrials.gov were excluded. Published results were sought from August 2022 to March 2023 by searching ClinicalTrials.gov, emailing authors, and using an automated tool, as well as through incidental discovery.Main outcomes and measuresThe primary outcome was a weighted estimate of the proportion of registered trials with published protocols that also had published main results. The proportion of trials with unpublished results was estimated using a weighted mean.ResultsFrom 1500 citations that were screened, 308 clinical trial protocols were included, and it was found that 87 trials had not published their main results. Most included trials were investigator-initiated evaluations of nonregulated products. When published, results appeared a mean (SD) of 3.4 (2.0) years after protocol publications. With the use of a weighted mean, an estimated 4754 (95% CI, 4296-5226) eligible clinical trial protocols were published and indexed in PubMed Central between 2011 and 2022. In the weighted analysis, 1708 of those protocols (36%; 95% CI, 31%-41%) were not associated with publication of main results. In a sensitivity analysis excluding protocols published after 2019, an estimated 25% (95% CI, 20%-30%) of 3670 (95% CI, 3310-4032) protocol publications were not associated with publication of main results.Conclusions and relevanceThis cross-sectional study of clinical trial protocols published on PubMed Central between 2011 and 2022 suggests that many protocols were not associated with subsequent publication of results. The overall benefits of publishing study protocols might outweigh the research waste caused by unnecessary protocol publications.

Project description:BackgroundRandomized controlled trials (RCTs) are the gold standard for evidence-based practice, but their development and implementation is resource intensive. We aimed to describe modern RCTs in gastrointestinal (GI) cancer and identify predictors of successful accrual and publication.Materials and methodsClinicalTrials.gov was queried for phase III GI cancer RCTs opened between 2010 and 2019 and divided into two cohorts: past and recruiting. Past trials were analyzed for predictors of successful accrual and the subset with ≥3 years follow-up were analyzed for predictors of publication. Univariate and multivariable (MVA) logistic regression were used to identify covariates associated with complete accrual and publication status.ResultsA total of 533 GI RCTs were opened from 2010 to 2019, 244 of which are still recruiting. In the "past" trials cohort (235/533) MVA, Asian continent of enrollment was a predictor for successful accrual, whereas trials with prolonged enrollment (duration longer than median of 960 days) trended to failed accrual. Predictors for publication on MVA included international enrollment and accrual completion. Sponsorship was not associated with accrual or publication. Notably, 33% of past trials remain unpublished, and 60% of trials that were closed early remain unpublished.ConclusionAccrual rate and the primary continent of enrollment drive both trial completion and publication in GI oncology. Accrual must be streamlined to enhance the impact of RCTs on clinical management. A large portion of trials remain unpublished, underscoring the need to encourage dissemination of all trials to, at a minimum, inform future trial design.Implications for practiceTwo-thirds of gastrointestinal (GI) oncology phase III randomized controlled trials successfully accrue; however, one third of these trials are unpublished and more than half of trials that close early are unpublished. The strongest predictors for publication are successful accrual and international collaborations. Initiatives to optimize the trial enrollment process need to be explored to maximize the potential for trials to engender progress in clinical practice. Moreover, this study identified a significant publication bias in the realm of GI oncology, and the field should promote reporting of all trials in order to better inform future trial questions and design.

Project description:Background:Publication bias is a form of scientific misconduct. It threatens the validity of research results and the credibility of science. Although several tests on publication bias exist, no in-depth evaluations are available that examine which test performs best for different research settings. Methods:Four tests on publication bias, Egger's test (FAT), p-uniform, the test of excess significance (TES), as well as the caliper test, were evaluated in a Monte Carlo simulation. Two different types of publication bias and its degree (0%, 50%, 100%) were simulated. The type of publication bias was defined either as file-drawer, meaning the repeated analysis of new datasets, or p-hacking, meaning the inclusion of covariates in order to obtain a significant result. In addition, the underlying effect (β = 0, 0.5, 1, 1.5), effect heterogeneity, the number of observations in the simulated primary studies (N = 100, 500), and the number of observations for the publication bias tests (K = 100, 1,000) were varied. Results:All tests evaluated were able to identify publication bias both in the file-drawer and p-hacking condition. The false positive rates were, with the exception of the 15%- and 20%-caliper test, unbiased. The FAT had the largest statistical power in the file-drawer conditions, whereas under p-hacking the TES was, except under effect heterogeneity, slightly better. The CTs were, however, inferior to the other tests under effect homogeneity and had a decent statistical power only in conditions with 1,000 primary studies. Discussion:The FAT is recommended as a test for publication bias in standard meta-analyses with no or only small effect heterogeneity. If two-sided publication bias is suspected as well as under p-hacking the TES is the first alternative to the FAT. The 5%-caliper test is recommended under conditions of effect heterogeneity and a large number of primary studies, which may be found if publication bias is examined in a discipline-wide setting when primary studies cover different research problems.

Project description:The United States (US) Food and Drug Administration (FDA) approves new drugs based on sponsor-submitted clinical trials. The publication status of these trials in the medical literature and factors associated with publication have not been evaluated. We sought to determine the proportion of trials submitted to the FDA in support of newly approved drugs that are published in biomedical journals that a typical clinician, consumer, or policy maker living in the US would reasonably search.We conducted a cohort study of trials supporting new drugs approved between 1998 and 2000, as described in FDA medical and statistical review documents and the FDA approved drug label. We determined publication status and time from approval to full publication in the medical literature at 2 and 5 y by searching PubMed and other databases through 01 August 2006. We then evaluated trial characteristics associated with publication. We identified 909 trials supporting 90 approved drugs in the FDA reviews, of which 43% (394/909) were published. Among the subset of trials described in the FDA-approved drug label and classified as "pivotal trials" for our analysis, 76% (257/340) were published. In multivariable logistic regression for all trials 5 y postapproval, likelihood of publication correlated with statistically significant results (odds ratio [OR] 3.03, 95% confidence interval [CI] 1.78-5.17); larger sample sizes (OR 1.33 per 2-fold increase in sample size, 95% CI 1.17-1.52); and pivotal status (OR 5.31, 95% CI 3.30-8.55). In multivariable logistic regression for only the pivotal trials 5 y postapproval, likelihood of publication correlated with statistically significant results (OR 2.96, 95% CI 1.24-7.06) and larger sample sizes (OR 1.47 per 2-fold increase in sample size, 95% CI 1.15-1.88). Statistically significant results and larger sample sizes were also predictive of publication at 2 y postapproval and in multivariable Cox proportional models for all trials and the subset of pivotal trials.Over half of all supporting trials for FDA-approved drugs remained unpublished >/= 5 y after approval. Pivotal trials and trials with statistically significant results and larger sample sizes are more likely to be published. Selective reporting of trial results exists for commonly marketed drugs. Our data provide a baseline for evaluating publication bias as the new FDA Amendments Act comes into force mandating basic results reporting of clinical trials.

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Publication bias in antipsychotic trials: an analysis of efficacy comparing the published literature to the US Food and Drug Administration database.

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