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Oral Potentially Malignant Disorders and Oral Cancer in Saudi Arabia: An Epidemiological Review of the Literature.

Khalid AljohaniAli Abdullah AlqarniMolly HarteRawia AlghamdiSaja AlzahraniRui Albuquerque
Published in: Journal of clinical medicine (2024)
Background: Oral potentially malignant disorders (OPMDs) are a group of chronic oral mucosal diseases associated with an increased risk of malignant transformation. Multiple studies have investigated the prevalence of these conditions in multiple regions; however, there are limited data about the prevalence of OPMDs in the Kingdom of Saudi Arabia (KSA). This paper aims to review the prevalence of OPMDs in the KSA, to ensure better understanding of the population risk and propose a more standardised approach to the diagnosis and management of this group across the KSA. In addition, this review will discuss the prevalence of oral cancer in the KSA, considering independent risk factors for oral cancer development. Methods: Electronic databases including PubMed, Medline, Medscape, ScienceDirect, StatPearls, BMC Oral Health and the Cochrane Library were searched with the keywords "Oral Potentially Malignant Disorders"; "Saudi Arabia"; and "Oral Cancer". Identified articles were reviewed independently by 2 reviewers against defined inclusion and exclusion criteria. Results: 16 studies were included in this review. The prevalence of OPMDs in KSA varies significantly depending on age, gender, social habits, background disease and dental status. Conclusions: This review highlights the need for up-to-date data on the prevalence, distribution, and characteristics of OPMDs in KSA. The diverse prevalence rates and distinct characteristics of various OPMDs emphasise the necessity for targeted preventive measures. As the data on OPMDs in KSA remains limited, future research efforts should prioritise the establishment of comprehensive epidemiological studies to inform effective public health interventions in this region.
Keyphrases
  • risk factors
  • saudi arabia
  • public health
  • oral health
  • big data
  • healthcare
  • mental health
  • electronic health record
  • machine learning