4.5 Review

Randomized clinical trials in implant therapy: relationships among methodological, statistical, clinical, paratextual features and number of citations

Journal

CLINICAL ORAL IMPLANTS RESEARCH
Volume 18, Issue 4, Pages 419-431

Publisher

WILEY
DOI: 10.1111/j.1600-0501.2007.01350.x

Keywords

clinical features; dental implants; methodological features; paratextual features; randomized clinical trials; science citation index; statistical features

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Objectives: The aim of the present study was to investigate the relationships among reported methodological, statistical, clinical and paratextual variables of randomized clinical trials (RCTs) in implant therapy, and their influence on subsequent research. Materials and methods: The material consisted of the RCTs in implant therapy published through the end of the year 2000. Methodological, statistical, clinical and paratextual features of the articles were assessed and recorded. The perceived clinical relevance was subjectively evaluated by an experienced clinician on anonymous abstracts. The impact on research was measured by the number of citations found in the Science Citation Index. A new statistical technique (Structural learning of Bayesian Networks) was used to assess the relationships among the considered variables. Results: Descriptive statistics revealed that the reported methodology and statistics of RCTs in implant therapy were defective. Follow-up of the studies was generally short. The perceived clinical relevance appeared to be associated with the objectives of the studies and with the number of published images in the original articles. The impact on research was related to the nationality of the involved institutions and to the number of published images. Conclusions: RCTs in implant therapy (until 2000) show important methodological and statistical flaws and may not be appropriate for guiding clinicians in their practice. The methodological and statistical quality of the studies did not appear to affect their impact on practice and research. Bayesian Networks suggest new and unexpected relationships among the methodological, statistical, clinical and paratextual features of RCTs.

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