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Early Optimistic Effect in Periodontology and Implant Dentistry Trials.

ABSTRACT: Differences in effect estimates between early primary trials included in a meta-analysis and the pooled estimate of meta-analysis might indicate potential novelty bias. The objective of this study was to assess the presence of novelty bias in a sample of studies published in periodontology and implant dentistry. On August 7, 2020, we searched the PubMed database for meta-analyses of clinical studies published between August 2015 and August 2020. Meta-analyses with at least 4 primary studies were selected for assessment. We fitted logistic regression models using trial characteristics as predictors to assess the association between these characteristics and 1) the odds of the first trial's estimate to be included in the meta-analysis confidence interval (CI) and 2) the odds of overlap between the first trial's CI and the meta-analysis prediction interval (PI). Ninety-two meta-analyses provided data for assessment. In absolute values, 70% of the meta-analyses have a pooled estimate smaller than the corresponding estimate of the first trial, although there was overlap of the CI of estimates from the first trial and the meta-analysis in 87% of the cases. This is probably due to the small number of trials in most meta-analyses and the subsequently large uncertainty associated with the pooled effect estimate. As the number of trials in the meta-analysis increased, the odds of the treatment effect estimate of the first trial to be included in the meta-analysis CI decreased by 15% for every additional trial (odds ratio, 0.85; 95% CI, 0.73 to 0.96). Meta-analytic effect estimates appear to be more conservative than those from the first trial in the meta-analysis. Our findings show evidence of novelty bias in periodontology and implant dentistry; therefore, clinicians should be aware of the risk of making decisions based on the information reported in new trials because of the risk of exaggerated estimates in these trials.

SUBMITTER: Menne MC

PROVIDER: S-EPMC8721552 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:AimAnalysis of distribution of p-values of continuous differences between test and controls after randomization provides evidence of unintentional error, non-random sampling, or data fabrication in randomized controlled trials (RCTs). We assessed evidence of highly unusual distributions of baseline characteristics of subjects enrolled in clinical trials in implant dentistry.Materials and methodsRCTs published between 2005 and 2020 were systematically searched in Pubmed, Embase, and Cochrane databases. Baseline patient data were extracted from full text articles by two independent assessors. The hypothesis of non-random sampling was tested by comparing the expected and the observed distribution of the p-values of differences between test and controls after randomization.ResultsOne-thousand five-hundred and thirty-eight unique RCTs were identified, of which 409 (26.6%) did not report baseline characteristics of the population, and 671 (43.6%) reported data in forms other than mean and standard deviation and could not be used to assess their random sampling. Four-hundred and fifty-eight trials with 1449 baseline variables in the form of mean and standard deviation were assessed. The study observed an over-representation of very small p-values [<.001, 1.38%, 95% confidence interval (CI) 0.85-2.12 compared to the expected 0.10%, 95% CI 0.00-0.26]. No evidence of over-representation of larger p-values was observed. Unusual distributions were present in 2.38% of RCTs and more frequent in non-registered trials, in studies supported by non-industry funding, and in multi-centre RCTs.ConclusionsThe inability to assess random sampling due to insufficient reporting in 26.6% of trials requires attention. In trials reporting suitable baseline data, unusual distributions were uncommon, and no evidence of data fabrication was detected, but there was evidence of non-random sampling. Continued efforts are necessary to ensure high integrity and trust in the evidence base of the field.

Project description:BACKGROUND:Individuals tend to have an optimism bias, processing desirable information more frequently than undesirable information. However, people who have been diagnosed with depression often have a more pessimistic view of the future. A recent study suggests that future expectations in individuals with dysphoria become more optimistic when asked to make optimistic future predictions about the future. In the present study, we investigated the differential effects of induced optimism training which making optimistic future prediction to change future beliefs in normal participants with various levels of dysphoria (low, mild, high). METHODS:We recruited normal participants (n?=?69) from a local university students and divided participants into three groups (low, mild, high dysphoria) by measuring dysphoric mood. These three groups were assigned to the induced optimism training or control condition. After the training, participants performed the two-stage belief updating task. In the first stage, participants estimated their personal probability of experiencing adverse events while being presented with the average probability of the event occurring to a living person. This information could be desirable for participants(when presented with a probability that was below their estimation) or undesirable (when presented with a probability that was above their estimation). To assess how desirable versus undesirable information influenced beliefs, participants estimated their personal probability of experiencing the events again in the second stage. The amount of update error was calculated as the difference between the estimates in the first stage and the second stage. The difference between the errors was classified as the update bias. RESULTS:After the induced optimism training, individuals with the mild dysphoria demonstrated a higher update bias than low (p?<?.001) and the high dysphoria (p?<?.05) group in induced optimism condition. Significant differences were not found in control group. Results indicates that individuals in the mild dysphoria group showed an increased update bias after being exposed to the induced optimism training Dysphoric mood and trait optimism remained unchanged in both the experimental and control groups. CONCLUSIONS:Results suggest that induced optimism training has potential to change individuals with mild dysphoria perceptions' about the future.

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Early Optimistic Effect in Periodontology and Implant Dentistry Trials.

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