The aim of this study was to identify and characterize aetiological and predisposing factors in denture-related stomatitis (DRS), by means of a case-control, transversal study, in a large cohort of 140 persons wearing removable maxillary polymethylamethacrylate prostheses. Data were obtained by (1) a questionnaire that included the identification of the subject, demographic and social data, medical history and behaviour; (2) intra-oral examination; (3) evaluation of the prosthesis; (4) microbiological examination; (5) yeast identification and analyses using Epi-info and the chi-square test. Results showed significant associations between DRS and yeasts, gender, age and alcohol consumption. We also found a significant relationship between the presence of yeasts and hyposalivation and decreased salivary pH. We found a highly significant difference between groups with and without DRS concerning the presence or absence of yeasts, regardless of the sample origin. Most cases of DRS showed the presence of Candida albicans. The results confirm a highly significant difference between groups with and without DRS concerning the presence or absence of yeasts.

This study aimed to identify risk factors for the incidence of peri-implant pathology. One-thousand, two-hundred and seventy-fifty patients (255 cases and 1020 controls), rehabilitated with dental implants, were included. Peri-implant pathology was defined as the presence of peri-implant pockets ≥ 5 mm, bleeding on probing, vertical bone loss, and loss of attachment ≥ 2 mm. Cases and controls were matched for age, gender, and duration of follow-up. A logistic regression model was used, with estimation of the OR for each variable and interaction, with a level of significance of 5%. The risk factors for peri-implant pathology were: history of periodontitis (OR = 19), bacterial plaque (OR = 3.6), bleeding (OR = 2.9), bone level on the medium third of the implant (OR = 13.9), lack of prosthetic fit or non-optimal screw joint (OR = 5.9), metal-ceramic restorations (OR = 3.9), and the interaction between bacterial plaque and the proximity of other teeth or implants (PROXI) (OR = 4.3). PROXI (OR = 0.44) exerted a protective effect when independent. Based on the results, peri-implant pathology represents a group of multifactorial situations with interaction of biological and biomechanical components in its pathogenesis. It was possible to model the condition and to assess, with high precision, the risk profile of each patient.

Objective. The aim of this study was to perform a systematic review of prevalence studies to determine the rate of malignant transformation of oral leukoplakia and assess the influence of demographic factors (age, gender, and geographic region) on the overall transformation rate. Study Design. A search was conducted for publications until July 2019 in 4 electronic databases and peer-reviewed journals. A manual search was performed on the bibliographies of the collected articles, and the authors were contacted for additional information. This study was previously registered with the trial number CRD42019126909 and study quality assessed through established methods. The results were expressed by means of proportions or odds ratios with a 95% confidence interval. Metaregression was undertaken to evaluate possible sources of heterogeneity, and funnel plot visual analysis was performed to assess publication bias.Results. The 34 observational epidemiologic studies included reported data on 26,209 patients with oral leukoplakia from 18 different countries. Meta-analysis of 32 studies (23,489 patients) presented an estimated overall mean proportion of malignant transformation rate of 9.70% (7.80À11.70) (I 2 = 98.66%; t 2 < 0.001; x 2 = 23.18; degrees of freedom [df] = 31). When comparing genders, the odds ratio favored males with 0.622 (0.468À0.826) (I 2 = 29.77%; t 2 = 0.089; x 2 = 22.78; df = 16). Conclusions. Within the limitations of the included studies in this systematic review, the results suggest that the malignant transformation rate was dependent on demographic factors and follow-up time. Future studies should include the development of guidelines to standardize the methodology for long-term follow-up assessment, thus reducing the risk of bias. (Oral Surg Oral Med Oral Pathol Oral Radiol 2020;000:1À12) Statement of Clinical RelevanceMost oral cancers develop from pre-existing lesions, oral leukoplakia being the most prevalent and well known. The early detection and treatment of leukoplakia have been debated, and one of the greatest challenges is identifying lesions that will undergo malignant transformation.

Based on the results, six predictors for the incidence of peri-implant pathology can be modified to significantly improve the outcome. It was possible to stratify patients per risk category according to the risk score, providing a tool for clinicians to support their decision-making process.

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Dental implants long term success rely on the establishment of a stable condition. This stability may be negatively influenced by the coexistence of peri-implant pathology, provoking loss of the supporting bone tissue around the implant. A large range in the prevalence of this condition is observed when analyzing different reports in the literature given the different definitions for peri-implant pathology. The background for this investigation was the assumption that peri-implant pathology is a group of multifactorial situations with several potential non-sufficient, non-necessary causes and the absence of risk models to aid the decision process in the maintenance of implant supported restorations. We explored these important aspects and investigated potential risk factors and statistical models for peri-implant pathology based on a model of sufficient and component causes. We found that biological and biomechanical factors can be involved as causal mechanisms of peri-implant pathology. Our study established three different statistical models based on binary conditional regression analysis, with the representative model presenting high sensitivity, specificity and accuracy, providing high positive and negative likelihood ratios. This model will represent a valid tool for the clinician in the maintenance of implant-supported fixed prosthetic rehabilitations.

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