Evidence map›Paper›PMID 41327208›Full record

ArticleBMC oral health2025

Key clinical and demographic factors influencing head and neck tumor severity in Lagos.

Emmanuel Temitope Aladenika, Warith Olaitan Akinshipo, Adegbayi Adeola Adekunle, Tosin Bakare, Tamara Busch, Olajumoke Ajibola Effiom, Wasiu Adeyemo, Azeez Butali

Abstract read
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Article in BMC oral health, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

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2 · The registry

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

8 authors.

Emmanuel Temitope AladenikaIowa Institute for Oral Health Research, University of Iowa, Iowa City, IA, USA. emmanuel-aladenika@uiowa.edu.
Warith Olaitan AkinshipoDepartment of Oral and Maxillofacial Pathology/Biology, University of Lagos, Lagos, Nigeria.
Adegbayi Adeola AdekunleDepartment of Oral and Maxillofacial Surgery, University of Lagos, Lagos, Nigeria.
Tosin BakareDepartment of Oral and Maxillofacial Pathology/Biology, University of Lagos, Lagos, Nigeria.
Tamara BuschIowa Institute for Oral Health Research, University of Iowa, Iowa City, IA, USA.
Olajumoke Ajibola EffiomDepartment of Oral and Maxillofacial Pathology/Biology, University of Lagos, Lagos, Nigeria.
Wasiu AdeyemoDepartment of Oral and Maxillofacial Surgery, University of Lagos, Lagos, Nigeria.
Azeez ButaliIowa Institute for Oral Health Research, University of Iowa, Iowa City, IA, USA. azeez-butali@uiowa.edu.

Funding

Whole Genome Sequencing for Orofacial Clefts, Incidental Findings and Role of Community GatekeepersR01DE028300 · NIDCR · UNIVERSITY OF IOWA · PI BUTALI, AZEEZ · 2020 to 2024
$3.9M
Identification of Rare Variants for Orofacial Clefts Using Publicly Available DatasetsR03DE035068 · NIDCR · UNIVERSITY OF IOWA · PI BUTALI, AZEEZ · 2025 to 2025
$296k
NIDCR NIH HHS R01 DE028300NIDCR NIH HHS R03 DE035068
6 · The paper itself

Abstract

backgroundHead and neck tumors pose a major health challenge in Nigeria, yet the factors that influence their severity remain poorly understood. No predictive model currently exists to assess malignancy risk in this population. This study aimed to identify key clinical and demographic predictors and to develop a model for malignancy risk in tumors diagnosed in Lagos, Nigeria.

methodsWe analyzed patient records with tumor diagnoses from 2000 to 2024, obtained from the Oral and Maxillofacial Surgery and Oral Pathology departments of the Lagos University Teaching Hospital. Surgical biopsy records and corresponding histopathology reports were reviewed. Tumor sites were grouped into five anatomical regions: mandible, midface, oral mucosa and salivary glands, extra oral, and unspecified regions. Descriptive statistics summarized patient and tumor features, while statistical analyses examined associations between demographics and tumor severity (benign/malignant). A predictive model for tumor severity was developed using data-splitting and leave-one-out cross-validation approaches.

resultsOf the 1,068 patients, 1,062 had confirmed diagnoses. Median age was 35 years [IQR:23–52], 53.96% were male, and the mandible was the most common site (48.31%). Tumors were most frequent on the right (30.13%) and measured 6 × 4x2cm on average. Median duration of presentation was 12 months [IQR:5–36], with 50.75% benign tumors. Tumor severity was significantly associated with age (47 vs. 28 years), site, laterality, duration (p < 0.001), and sex (p = 0.024), with males more susceptible to malignancy. Age inversely correlated with presentation duration (p = 0.00067), and tumor site was not associated with sex (p = 0.054). Conventional ameloblastoma was the most common benign tumor, while squamous cell carcinoma was the most common malignancy. Multivariate analysis showed malignancy was associated with age (OR = 1.61; p < 0.001), tumor site (midface (OR = 3.88), oral mucosa and salivary glands (OR = 23.8), and extraoral sites (OR = 108.01) compared to the mandible [all p < 0.001]), length (OR = 1.93; p < 0.001), and shorter duration (OR = 0.68; p < 0.001). Central (OR = 0.2), left (OR = 0.46), or right laterality (OR = 0.32) lowered malignancy odds versus unspecified (all p < 0.04). Our predictive model approaches achieved area under the curve of 0.864 and 0.883.

conclusionsWe identified age, site, laterality, and duration before presentation, as key malignancy predictors. This will aid comprehensive care plans for optimal clinical outcomes.

Indexed as

Head and Neck NeoplasmsAdultAge FactorsFemaleHumansMaleMiddle AgedNigeriaRetrospective StudiesRisk FactorsSeverity of Illness IndexYoung AdultHead and neck neoplasmOrofacial tumorsTumor severity prediction

Identifiers

PMID41327208
PMCPMC12777438

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.