Esthetic Perception of Different Clinical Situations of Maxillary Lateral Incisor Agenesis According to Populations with Dental and Non-Dental Backgrounds: A Systematic Review and Meta-Analysis

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Abstract

Treatment of unilateral or bilateral maxillary lateral incisor agenesis is challenging, time-consuming, expensive, and requires careful treatment planning, predictability, and esthetics. This review aimed to identify differences in esthetic perception among orthodontists, general dentists, differentiated dentists, and laypersons, which may interfere with treatment options. EBSCO, PubMed, ScienceDirect, Cochrane Library databases, and Google Scholar were searched using keyword pairing and a Boolean expression, “(congenitally missing OR agenesis OR hypodontia) AND (maxillary lateral incisors) AND (esthetic perception OR smile) AND (laypersons OR dental professional OR general dentist OR orthodontists).” Reviews and case studies were excluded. A total of 13 studies were selected for qualitative analysis (adapted ROBINS-I) and 11 were selected for meta-analysis (p < 0.05) after being sub-grouped into “Opening vs. Closure” and “No remodeling vs. Dental remodeling vs. Dental and gingival remodeling” groups. A meta-analysis evaluated the magnitude of the difference between groups based on differences in means and effect sizes (α = 0.05; 95% CI; Z-value 1.96), revealing that the esthetic perception of maxillary lateral incisor agenesis treatment remains controversial even among professionals. Gingival remodeling was not valued compared to isolated dental remodeling. Studies lack rigorously comparable methodologies. Discussion with the patient is pertinent in doubtful situations, as the best treatment option remains unclear, and overtreatment should be avoided.

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The PRISMA 2020 statement: an updated guideline for reporting systematic reviews

Matthew J L Page, Joanne E McKenzie, Patrick Bossuyt … (2024)

The Preferred Reporting Items for Systematic reviews and Meta-Analyses (PRISMA) statement, published in 2009, was designed to help systematic reviewers transparently report why the review was done, what the authors did, and what they found. Over the past decade, advances in systematic review methodology and terminology have necessitated an update to the guideline. The PRISMA 2020 statement replaces the 2009 statement and includes new reporting guidance that reflects advances in methods to identify, select, appraise, and synthesise studies. The structure and presentation of the items have been modified to facilitate implementation. In this article, we present the PRISMA 2020 27-item checklist, an expanded checklist that details reporting recommendations for each item, the PRISMA 2020 abstract checklist, and the revised flow diagrams for original and updated reviews.

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ROBINS-I: a tool for assessing risk of bias in non-randomised studies of interventions

Jonathan AC Sterne, Miguel A. Hernán, Barnaby Reeves … (2018)

Non-randomised studies of the effects of interventions are critical to many areas of healthcare evaluation, but their results may be biased. It is therefore important to understand and appraise their strengths and weaknesses. We developed ROBINS-I (“Risk Of Bias In Non-randomised Studies - of Interventions”), a new tool for evaluating risk of bias in estimates of the comparative effectiveness (harm or benefit) of interventions from studies that did not use randomisation to allocate units (individuals or clusters of individuals) to comparison groups. The tool will be particularly useful to those undertaking systematic reviews that include non-randomised studies.

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Estimating the sample mean and standard deviation from the sample size, median, range and/or interquartile range

Xiang Wan, Wenqian Wang, Jiming Liu … (2014)

Background In systematic reviews and meta-analysis, researchers often pool the results of the sample mean and standard deviation from a set of similar clinical trials. A number of the trials, however, reported the study using the median, the minimum and maximum values, and/or the first and third quartiles. Hence, in order to combine results, one may have to estimate the sample mean and standard deviation for such trials. Methods In this paper, we propose to improve the existing literature in several directions. First, we show that the sample standard deviation estimation in Hozo et al.’s method (BMC Med Res Methodol 5:13, 2005) has some serious limitations and is always less satisfactory in practice. Inspired by this, we propose a new estimation method by incorporating the sample size. Second, we systematically study the sample mean and standard deviation estimation problem under several other interesting settings where the interquartile range is also available for the trials. Results We demonstrate the performance of the proposed methods through simulation studies for the three frequently encountered scenarios, respectively. For the first two scenarios, our method greatly improves existing methods and provides a nearly unbiased estimate of the true sample standard deviation for normal data and a slightly biased estimate for skewed data. For the third scenario, our method still performs very well for both normal data and skewed data. Furthermore, we compare the estimators of the sample mean and standard deviation under all three scenarios and present some suggestions on which scenario is preferred in real-world applications. Conclusions In this paper, we discuss different approximation methods in the estimation of the sample mean and standard deviation and propose some new estimation methods to improve the existing literature. We conclude our work with a summary table (an Excel spread sheet including all formulas) that serves as a comprehensive guidance for performing meta-analysis in different situations. Electronic supplementary material The online version of this article (doi:10.1186/1471-2288-14-135) contains supplementary material, which is available to authorized users.