Oropharyngeal squamous cell carcinoma (OPSCC) development is strongly associated with risk factors like smoking, chronic alcohol consumption, and the living environment, but also chronic human papilloma virus (HPV) infection, which can trigger cascade cellular changes leading to a neoplastic transformation. The prevalence of these factors differs among different world regions, and the prevention, diagnosis, and prognosis of OPSCC are highly dependent on them. We performed a retrospective study on 406 patients diagnosed with OPSCC in our region that were classified according to the tumor type, localization and diagnosis stage, demographic characteristics, risk factors, and histological and immunohistochemical features. We found that most of the patients were men from urban areas with a smoking habit, while most of the women in our study were diagnosed with tonsillar OPSCC and had a history of chronic alcoholism. During the immunohistochemical study, we analyzed the tumor immunoreactivity against anti-p16 and anti-HPV antibodies as markers of HPV involvement in tumor progression, as well as the correlation with the percentage of intratumoral nuclei immunomarked with the anti-Ki 67 antibody in serial samples. We observed that the percentage of Ki67-positive nuclei increased proportionally with the presence of intratumoral HPV; thus, active HPV infection leads to an increase in the rate of tumor progression. Our results support the implementation of strategies for OPSCC prevention and early diagnosis and can be a starting point for future studies aiming at adapting surgical and oncological treatment according to the HPV stage for better therapeutic results.

Background/Objectives: Dental caries and gingival inflammation share several biofilm-related determinants. This study evaluated the association between Community Periodontal Index (CPI) screening categories and permanent-dentition caries experience in a consecutively recruited clinical sample of children and adolescents from Southwest Romania. Methods: The multicenter cross-sectional study included 638 participants aged 6–19 years, analyzed as 6–12 years (n = 407) and 13–19 years (n = 231). Analyses included nonparametric comparisons, adjusted Poisson models, a formal CPI-by-age-stratum interaction, continuous-age sensitivity analyses, and generalized Poisson models allowing underdispersion. Results: Mean DMF-T was 4.71 ± 2.55 and 4.93 ± 2.58 in the younger and older strata, respectively. CPI correlated strongly with DMF-T (rho = 0.743 and 0.749; both p < 0.001). Adjusted expected DMF-T counts were higher for CPI 1 and CPI 2 than for CPI 0 in both strata. There was no statistical evidence that the CPI–DMF-T association differed by age stratum (global interaction p = 0.749) or continuous age (p = 0.552). Plaque Index adjustment markedly attenuated CPI estimates; the extent of residual CPI association was sensitive to count-model specification. Conclusions: Higher CPI categories were associated with greater cumulative caries experience in this clinical sample, but the findings do not establish temporality, causality, or predictive validity. Unequal numbers of erupted permanent teeth and CPI-eligible sextants may have contributed to the observed gradient because these quantities were not retained analytically.

Background and Objectives: Caries experience, plaque accumulation, gingival inflammation, and periodontal screening findings may coexist as manifestations of a shared oral-health burden. We examined whether these routinely recorded indicators form distinct multivariable profiles or primarily represent ordered levels along a common burden continuum in children and adolescents. Materials and Methods: This secondary exploratory analysis included 638 participants from a multicenter cross-sectional clinical database: 407 aged 6–12 years and 231 aged 13–19 years. Permanent-dentition Decayed, Missing, and Filled Teeth score, Plaque Index, Gingival Index, and Community Periodontal Index were standardized and analyzed separately by age stratum. Unsupervised K-means clustering compared solutions containing two to five groups to summarize participant-level patterns without imposing predefined clinical categories. Hierarchical Ward classification assessed algorithmic concordance; principal component analysis and a composite standardized burden score assessed dimensionality. Sensitivity analyses excluded the periodontal index or treated it as ordinal with Gower-distance partitioning around medoids, and 1000 repeated 80% subsamples assessed sampling stability using the adjusted Rand index. Results: A single principal component explained 91.0% of variance at 6–12 years and 91.8% at 13–19 years, with all four indicators loading strongly on the same dimension. Ordered cluster membership correlated closely with the composite burden score (Spearman ρ = 0.942 and 0.939; both p < 0.001). The retained low-, intermediate-, and high-burden groupings were highly consistent when the periodontal index was excluded or treated as ordinal and under repeated subsampling. In adolescents, a two-group alternative preserved the low- and high-burden extremes while dividing the intermediate group, indicating that the number of groups changes descriptive granularity rather than revealing a separate phenotype. Conclusions: The principal new finding is that four commonly used oral-health indicators converge on one dominant participant-level burden dimension rather than defining distinct clinical phenotypes. This supports an integrated epidemiological description of cumulative oral-health burden while cautioning against interpreting data-driven groups as diagnostic or treatment categories. The numerical group distributions are sample-specific and require external and longitudinal validation before being transferred to other populations or clinical decision-making.

Background/Objectives: Morphological signs of non-carious tooth surface loss are clinically heterogeneous, and their prevalence depends strongly on the diagnostic framework and threshold used. This exploratory secondary analysis evaluated a study-specific combined morphological outcome restricted to second permanent molars and its association with cumulative caries experience in a regional clinical sample of adolescents. Methods: The analysis included 231 adolescents aged 13–19 years from Dolj, Gorj, and Olt counties, selected from a parent clinical database of 638 participants. The study-specific outcome was coded when a clearly discernible non-carious hard-tissue change compatible with an abrasive, erosive, or abfraction-related morphology was identified on any clinically accessible surface of tooth 17, 27, 37, or 47. This study did not use BEWE, the Smith and Knight Tooth Wear Index, or another validated severity-based tooth wear index; subtype, surface, and severity were not retained separately in the analytical dataset. Dental caries experience was measured using DMF-T. Group comparisons, correlations, and multivariable logistic regression were performed in JASP version 0.96.0. Sensitivity analyses included a participant-level coding audit and a logistic model using DMF-T recalculated after excluding the contribution of teeth 17, 27, 37, and 47. Results: The study-specific morphological outcome was present in 50/231 participants (21.6%). A coding audit confirmed that 181 participants had no positive second molar and 50 had exactly one positive second molar; tooth-specific counts were 14, 15, 12, and 9 for teeth 17, 27, 37, and 47, respectively. In the primary model, male sex (adjusted OR = 3.34, 95% CI 1.67–6.71) and DMF-T (adjusted OR = 1.15 per point, 95% CI 1.01–1.31) were associated with the outcome. After excluding the four evaluated second molars from DMF-T, the caries experience association remained positive but borderline (OR = 1.198, 95% CI 1.000–1.435, p = 0.049), while male sex remained associated (OR = 3.310, 95% CI 1.647–6.652, p < 0.001). Conclusions: A modest exploratory association was observed between the study-specific morphological outcome and cumulative caries experience in this clinical sample. The result should not be interpreted as a standardized NCDL prevalence estimate, a causal relationship, or a prediction model. Confirmation using validated whole-mouth tooth wear measures, outcome-specific reliability assessment, and population-based longitudinal data is required.