The Prevalence of Human Papillomavirus (HPV) Genotypes in the Oral Mucosae of HIV-Positive Individuals: A Systematic Review and Meta-Analysis.

Papillomaviruses are double-stranded DNA viruses, and it is essential to clarify their genotypic distribution for their effective prevention and clinical management. In this study, we aimed to evaluate the prevalence of HPV genotypes in the normal oral mucosae of HIV-positive individuals. A systematic literature search was conducted across PubMed, Web of Science, Scopus, and Google Scholar to identify peer-reviewed studies published up to 13 February 2025. The inclusion criteria referred to original research studies reporting on the prevalence and genotype-specific distribution of HPV in the oral mucosae of HIV-positive individuals. Statistical analyses were conducted using the MedicReS E-PICOS AI smart biostatistics software (version 21.3, New York, NY, USA) and the MedCalc statistical software package (MedCalc Software Ltd., Ostend, Belgium). The pooled prevalence estimates were calculated using a random-effects meta-analysis model, and heterogeneity was quantified using the Cochrane Q and I² statistics. The presence of publication bias was assessed via the Begg and Mazumdar rank correlation test. High prevalence and heterogeneity of HPV-58 (6.23%), HPV-16 (4.326%), and HPV-66 (3.733%) were observed, indicating significant variability across populations and methodologies. This supports their association with HPV-related oropharyngeal malignancies and the need for the continuous surveillance of HIV-positive individuals. We also observed the elevated detection of LR-HPV genotypes, particularly HPV-13 (7.16%), HPV-5 (5.64%), and HPV-62 (4.24%). These findings indicate that there is substantial heterogeneity in the prevalence of both HR-HPV and LR-HPV genotypes among HIV-positive individuals, with certain genotypes exhibiting higher detection rates across studies, emphasizing the need for targeted surveillance and preventive strategies in this vulnerable population. The application of advanced data analysis methods is essential in enhancing HPV surveillance and implementing effective control measures in this vulnerable population.