Introduction
Localized gingival enlargement (LGE) is a clinical
presentation that often poses a diagnostic dilemma in dental and
clinical practice (1,2). In a recent study, the prevalence and
clinical features of localized gingival enlargements (LGEs) were
analyzed in Thai patients over a 20-year period. LGEs were
categorized by nature and concordance between clinical and
pathological diagnoses was assessed. Using key clinical factor
including size, consistency, color, duration and patient age, a
decision tree model was developed to help clinicians distinguish
malignant from non-malignant LGEs (3). Among all groups of LGEs, malignant
LGEs were the most critical due to their life-threatening
potential. However, within the malignant LGE group, differences in
patient demographics and clinical characteristics were observed.
This observation is likely due to the wide spectrum of neoplastic
origins of malignant LGEs, which include epithelial malignancies
such as squamous cell carcinoma (SCC), verrucous carcinoma,
hematologic malignancies such as lymphoma and plasmacytoma,
salivary gland malignancies such as mucoepidermoid carcinoma,
adenoid cystic carcinoma and even metastatic cancers (4,5).
With regard to a previous study conducted by our
group, lesion size, consistency, color, duration and patient age
were critical factors for distinguishing malignant from
non-malignant LGEs. The proposed diagnostic guide may assist
clinicians in assessing malignancy risk in LGEs (3). However, certain malignant LGEs remain
challenging to diagnose due to their rarity and clinical
resemblance to benign lesions (6-8).
Further studies with larger sample sizes may improve the
understanding of these conditions.
To the best of the authors' knowledge, the
clinicopathological features of malignant LGEs in the Thai
population has not been specifically analyzed. Therefore, the
present study aimed to provide comprehensive clinical data to
improve the clinical diagnostic accuracy of malignant LGEs by
investigating their prevalence, origins and clinical information in
a large sample of Thai patients. In addition, the diagnostic
concordance between different origins of malignant LGEs and
examined comparable clinical data among these cases. The present
study focused exclusively on malignant LGEs over a 40-year period,
analyzing differences between epithelial and non-epithelial
origins, emphasizing the frequent misdiagnosis of non-epithelial
malignant lesions, and identifying potential key clinical
predictors.
Materials and methods
Data collection
The present retrospective single-center study was
approved by the Faculty of Dentistry/Faculty of Pharmacy, Mahidol
University, Institutional Review Board (approval no.
COA.No.MU-DT/PY-IRB 2022/047.2209). All procedures performed in the
present study were in accordance with the Declaration of Helsinki.
Histopathological reports of LGEs were retrospectively retrieved
from the archives of the Department of Oral and Maxillofacial
Pathology, Faculty of Dentistry, Mahidol University, between 1982
and 2021. All archived cases were systematically reviewed. To
minimize temporal heterogeneity in the diagnostic criteria,
pathological diagnoses were reassessed and where necessary, updated
according to the 2022 World Health Organization classification
(9). Only cases with a confirmed
malignant diagnosis and documented clinical presentation as LGE
were selected. Lesions originating from bony tissue or located on
the alveolar mucosa, edentulous alveolar ridges, or other
masticatory mucosa such as the hard palate or maxillary tuberosity
were excluded. Thus, only lesions associated with the gingiva
surrounding natural teeth were included. Patient demographic data,
such as age and sex, clinical information, such as duration,
location, color, consistency, surface texture and size, clinical
diagnoses, including either a sole working diagnosis or the
first-listed diagnosis in differential diagnoses and final
pathological diagnoses were gathered from the pathological request
forms and patients' medical records. Eligible cases were
consecutively retrieved from the departmental archives during the
study period. Case selection was based solely on histopathologic
diagnosis and documented clinical presentation as LGE, without
additional sampling or selective inclusion, thereby minimizing
selection bias within the institution. Case selection and data
extraction were performed using predefined criteria to ensure
consistency across the study period.
Data analysis
For descriptive analysis, malignant LGEs were
categorized into five origins: Epithelial, salivary gland,
hematological, metastatic and others. The epithelial origin
category refers specifically to malignant tumors arising from the
surface squamous epithelium. All cases, except for metastatic
tumors, originated primarily in the oral cavity. Diagnostic
concordance between clinical and pathological diagnoses across
different malignant LGE origins was assessed based on the sole
working clinical diagnosis recorded at initial evaluation or the
first-listed diagnosis in differential diagnoses. The results were
presented as percentage concordance rates. To facilitate
concordance analysis, both clinical and pathological diagnoses were
reclassified into distinct categories representing the nature of
LGE diseases, including reactive lesions, benign tumors, infections
and inflammation, malignant lesions and others. Diagnostic
concordance was defined as a match between clinical and
pathological diagnoses regarding their respective categories. Given
the inherently limited sample size of this cohort, the present
study elected to retain this case in all other analyses where
complete data were available, in order to preserve statistical
power and maximize data utilization. This decision resulted in
differing denominators between the diagnostic concordance analysis
and the remaining analyses. Comparison of patient demographic data
and clinical information between epithelial and non-epithelial
malignant LGEs was performed using the χ2 test. The odds
ratio was calculated using simple logistic regression analysis to
identify an independent risk factor associated with non-epithelial
malignant LGEs. A decision tree based on clinical characteristics
for distinguishing between epithelial and non-epithelial malignant
LGEs was constructed using the conditional inference tree
methodology (10). The missing data
were handled using pairwise exclusion. For each statistical
analysis, cases with missing values for the variable under
investigation were excluded only from that specific analysis,
allowing all available data to be utilized without unnecessary
listwise deletion. All statistical analyses were performed using R
software (version 4.3.1). P<0.05 was considered to indicate a
statistically significant difference.
Results
Malignant LGEs based on their
origins
Out of 19,505 total biopsy cases reviewed, 96 cases
(0.5%) were identified as malignant LGEs presenting specifically in
dentate areas. Among these, epithelial tumors were the most common
(60.4%), followed by hematological tumors (14.6%), salivary gland
tumors (10.4%), metastatic tumors (8.3%) and others (6.3%; Fig. 1A). The specific diagnoses of these
malignant cases, categorized and color-coded by type, are shown in
Fig. 1B. SCC was the most
prevalent, comprising 55.2% of malignant LGEs, followed by
non-Hodgkin lymphoma (13.5%) and mucoepidermoid carcinoma
(7.3%).
Diagnostic concordances
Of the 96 malignant LGE cases, one case was excluded
from the concordance analysis due to the absence of a recorded
clinical or differential diagnosis, leaving 95 cases for evaluation
(Table I). Concordance was
determined based on whether the histopathological diagnosis matched
either the sole working diagnosis or the first-listed diagnosis
listed in the differential diagnoses. Concordance rates were higher
in epithelial malignant LGEs (72.4%) than in non-epithelial
malignancies (47.4%). Salivary gland malignancies exhibited the
lowest concordance rate (20%), followed by metastatic tumors
(25%).
 | Table IDiagnostic concordances among
different types of malignant LGE cases. |
Table I
Diagnostic concordances among
different types of malignant LGE cases.
| Type of malignant
LGE | No. of cases
(n=95a) | Concordance (%) |
|---|
| Epithelial
tumors | 57 | 42/57 (72.4%) |
| Non-epithelial
tumors | 38 | 18/38 (47.4%) |
|
Hematological
tumors | 14 | 10/14 (71.4%) |
|
Salivary
gland tumors | 10 | 2/10 (20.0%) |
|
Metastatic
tumors | 8 | 2/8 (25.0%) |
|
Others | 6 | 4/6 (66.7%) |
Analysis of non-concordance malignant
LGE cases
A total of 35 cases of malignant LGE were clinically
misdiagnosed. When categorized by origin, over half of these
misdiagnosed cases were non-epithelial malignant LGEs, accounting
for 57.1% (Table II). Overall,
most misdiagnoses were initially recognized as reactive lesions,
notably in cases of hematological and metastatic malignancies.
Furthermore, salivary gland malignancies were often misidentified
as benign tumors.
| Table IIAnalysis of non-concordant malignant
LGE cases based on the nature of the disease. |
Table II
Analysis of non-concordant malignant
LGE cases based on the nature of the disease.
| | | Nature |
|---|
| Type of malignant
LGEs | Non-concordance cases
(n=35) | Reactive | Inflammation | Benign | Others |
|---|
| Epithelial
tumors | 15 (42.9%) | 7 (46.7%) | 4 (26.7%) | 2 (13.3%) | 2 (13.3%) |
| Non-epithelial
tumors | 20 (57.1%) | 9 (45.0%) | 3 (15.0%) | 7 (35.0%) | 2 (10.0%) |
|
Hematological
tumors | 4 (11.4%) | 3 (75.0%) | - | 1 (25.0%) | - |
|
Salivary
gland tumors | 8 (22.9%) | - | 3 (37.5%) | 5 (62.5%) | - |
|
Metastatic
tumors | 6 (17.1%) | 5 (83.3%) | - | 1 (16.7%) | - |
|
Others | 2 (05.7%) | 1 (50.0%) | - | - | 2 (50.0%) |
Demographic data and clinical
information
Age, site, surface texture and color are marked
demographic and clinical factors that differ between epithelial and
non-epithelial malignant LGEs (Table
III). Epithelial malignancies were predominantly observed in
patients >40 years old (mean=58.7 years), while non-epithelial
cases included younger patients (mean=47.5 years; P=0.004).
Epithelial malignant LGEs were more commonly located on the
mandibular gingiva, while non-epithelial cases tended to occur on
the maxillary gingiva (P=0.044). With regard to surface texture,
the majority of epithelial cases exhibited a rough surface, whereas
non-epithelial cases exhibited an equal mix of smooth and rough
textures (P=0.003). For color, non-epithelial malignancies were
most often red, followed by pink and other colors, while epithelial
malignancies indicated an equal distribution of red and white
(P=0.014). No significant differences were noted between the two
groups regarding sex, duration, consistency, or size. The two types
indicated similar male-to-female ratios and typically presented
with a duration of <3 months.
| Table IIIPatient demographics and clinical data
for epithelial and non-epithelial malignant LGE cases. |
Table III
Patient demographics and clinical data
for epithelial and non-epithelial malignant LGE cases.
| Clinical
variables | Epithelial
malignant LGE (n=58) | Non-epithelial
malignant LGE (n=38) | P-value |
|---|
| Sex | | | |
|
Male | 26 (44.8%) | 21 (55.3%) | 0.317 |
|
Female | 32 (55.2%) | 17 (44.8%) | |
| Age (years) | | | |
|
Mean
(SD) | 58.7 (15.1) | 47.5 (16.0) | |
|
≤ 40 | 5 (08.6%) | 12 (31.6%) | 0.004b |
|
>40 | 51(87.9%) | 25 (65.8%) | |
|
N/A | 2 (03.4%) | 1 (02.6%) | |
| Duration | | | |
|
≤3
months | 40 (69.0%) | 27 (71.1%) | 0.614 |
|
>3
months | 9 (15.5%) | 8 (21.1%) | |
|
N/A | 9 (15.5%) | 3 (07.9%) | |
| Site | | | |
|
Maxilla | 24 (41.4%) | 24 (63.2%) | 0.044a |
|
Mandible | 33 (57.0%) | 13 (34.2%) | |
|
N/A | 1 (01.7%) | 1 (02.6%) | |
| Surface
texture | | | |
|
Smooth | 3 (05.2%) | 7 (18.4%) | 0.003b |
|
Rough | 30 (51.7%) | 8 (21.1%) | |
|
Ulcerated | 1 (01.7%) | - | |
|
N/A | 24 (41%) | 23 (60.5%) | |
| Consistency | | | |
|
Firm | 13 (22.4%) | 15 (39.5%) | 0.151 |
|
Soft | 25 (43.1%) | 16 (42.1%) | |
|
Others | - | 2 (05.3%) | |
|
N/A | 20 (34.5%) | 5 (13.2%) | |
| Color | | | |
|
Pink | 6 (10.3%) | 6 (15.8%) | 0.014a |
|
Red | 13 (22.4%) | 13 (34.2%) | |
|
White | 12 (21.0%) | 2 (05.3%) | |
|
Others | - | 4 (10.5%) | |
|
N/A | 27 (46.6%) | 13 (34.2%) | |
| Size | | | |
|
≤2 cm | 17 (29.3%) | 18 (47.4%) | 0.233 |
|
>2
cm | 19 (32.8%) | 11 (29.0%) | |
|
N/A | 22 (38.0%) | 9 (23.7%) | |
Simple logistic regression analysis
and decision tree model
All clinical factors with significant differences in
the χ2 test were analyzed using simple logistic
regression, revealing several significant predictors of
non-epithelial malignant LGEs. Lesions with a smooth surface
texture were strongly associated with non-epithelial malignant LGEs
[Odds ratio (OR): 13.13, 95% confidence interval (CI): 2.27-75.86]
followed by red-colored lesions (OR: 6.00, 95% CI: 1.12-32.28).
Younger patients, notably those <40 years, indicated higher odds
(OR: 4.90, 95% CI: 1.55-15.43), as did lesions located at the
maxilla (OR: 2.36, 95% CI: 1.01-5.48).
A decision tree for differentiating epithelial and
non-epithelial malignant LGEs was generated using a recursive
partitioning process (Fig. 2). The
analysis identified surface texture as the primary discriminating
factor, followed by age. These findings confirm the strong
predictive potential of this approach for distinguishing between
epithelial and non-epithelial malignant LGEs. A non-epithelial
origin was associated with LGEs that had a smooth surface (77.8%)
or, if rough, occurred in patients younger than 40 years (66.8%).
The matrix performance of the decision tree analysis demonstrated a
sensitivity of 87.93%, specificity of 47.37%, precision of 71.83%,
accuracy of 71.88% and F1 score of 79.07%.
Discussion
In the present study, a clinicopathological analysis
of 96 malignant LGEs was conducted over a 40-year period at the
Faculty of Dentistry, Mahidol University. Of the total biopsied
specimens, malignant LGEs constituted 0.5% of cases, contrasting
with the prior reported prevalence of 0.0006 to 0.005% (4,11). As
our institution serves as a university-based referral center, the
cases were obtained from biopsy records submitted by both internal
faculty members and external dental clinics. Therefore, the
potential impact of referral bias is considered minimal. Biopsy
submissions included lesions with clinically benign appearances as
well as those considered clinically suspicious, atypical, or
persistent. Consequently, the spectrum of submitted cases is
unlikely to have substantially influenced the observed proportion
of malignant lesions. When focusing on gingival lesions, Li et
al (12) reported a higher
prevalence of 33.17% for malignant neoplasms in non-dental plaque
gingival diseases among the Chinese population, while other studies
have shown prevalence rates of gingival malignancies ranging from
3.69-8% (13-16).
These studies included broader populations and did not focus
exclusively on LGEs, making direct comparisons difficult. Such
variations in study populations lead to inconsistent results and
hinder direct comparisons. In addition, most research on LGEs has
focused on reactive lesions, primarily fibroma, pyogenic granuloma,
peripheral ossifying fibroma and peripheral giant cell lesion
(17-20).
This underscores the limited knowledge of malignant LGEs. To the
best of the authors' knowledge, this is the first study
specifically focusing on this topic.
Of malignant LGEs, ~60% are of epithelial origin,
similar to the 46% reported by Tamiolakis et al (4). This underscores the high proportion of
malignant epithelial tumors, such as SCC, occurring at the gingival
site. Non-epithelial malignant LGEs comprised 39.6% of cases, with
hematological tumors (14.6%) being the most common, followed by
salivary gland tumors (10.4%), metastatic tumors (8.3%) and others
(6.3%). Although Tamiolakis et al (4) did not identify any salivary gland
malignant LGEs, they noted higher frequencies of hematological
tumors (30.8%) and metastatic tumors (23.1%) in their study.
Notably, these variations in prevalence may be influenced by
ethno-geographical factors.
To further analyze the data, diagnostic concordance
rates were evaluated between origins of malignant LGEs. The
findings revealed that non-epithelial malignant LGEs exhibited a
lower concordance rate than epithelial LGEs. The majority of the
diagnostic discordances were initially identified as reactive
lesions, notably in cases of hematological and metastatic tumors.
These findings align with prior reports describing oral metastatic
malignancies and lymphoma mimicking reactive lesions (21-23).
Notably, salivary gland malignancies presented the lowest
concordance rate among non-epithelial malignant LGEs, with most
cases being misdiagnosed as benign tumors. This may be attributed
to their typical presentation as slow-growing masses (24).
The analysis indicated that surface texture, color,
patient age and lesion location were key factors in distinguishing
between epithelial and non-epithelial malignant LGEs, with surface
texture being the strongest factor, followed by color, age and
location. Non-epithelial malignant LGEs are 13 times more likely to
have a smooth surface. These findings align with the decision tree
of Mortazavi et al (25),
which suggests that exophytic lesions with rough surfaces are more
likely to be of epithelial origin, while those with smooth surfaces
are indicative of non-epithelial lesions, including mesenchymal and
salivary gland tumors. Therefore, surface texture may serve as a
useful indicator in distinguishing between these two groups.
With regard to color, white coloration is frequently
observed in epithelial malignant LGEs, often attributed to abnormal
keratin formation on the surface, notably in SCC and verrucous
carcinoma. In contrast to this observation, non-epithelial
malignancies exhibited a wider range of colors other than white.
Salivary gland malignancies may appear pink, bluish to red, or
normal-colored nodular mass (25),
while oral lymphomas typically present as normal, red or purple
(26). The present study
demonstrated that non-epithelial malignant LGEs are six times more
likely to appear red. These color variations may be associated with
the location of malignant cells or the vascularity of the tumors,
influencing lesion appearance. It is interesting to note that while
color appears to indicate general malignancy, it does not
differentiate between epithelial and non-epithelial malignancies in
diagnostic tree analysis. This finding is also consistent with the
previous study conducted by our group, which indicated that color
could distinguish benign from malignant LGEs but only with low to
moderate malignancy risk (3).
It was shown that non-epithelial malignant LGEs are
4.9 times more likely to develop in patients <40 years old.
Among these cases, sarcomas were the most prevalent, consistent
with findings by Santos-Leite et al (27) who reported that gingival sarcomas
commonly occur in the fourth decade of life. This also aligns with
a prior study indicating that oral SCC, the most common epithelial
cancer, typically occurs in older patients (>40 years) (28). The present study revealed that
non-epithelial malignant LGEs are 2.3 times more likely to occur on
the maxillary gingiva, which was consistent with previous reports
on gingival malignancies. Non-Hodgkin lymphomas have demonstrated a
higher prevalence in the maxillary gingiva, with twice the number
of cases reported compared with the mandible (29). Similarly, oral metastases involving
the gingiva are more commonly found in the maxilla than in the
mandible (30). Conversely, the
majority of gingival SCCs occur in the mandible (31). These findings highlight the
diagnostic challenge of non-epithelial malignant LGEs, which often
mimic benign or reactive lesions and may lead to delayed diagnosis.
Early recognition is critical, as certain lesions, such as
sarcomas, require prompt and more aggressive management. The
identified clinical features, particularly younger patient age and
smooth surface texture, may help clinicians raise suspicion for
malignancy and support earlier biopsy and referral, thereby
improving diagnostic accuracy and patient management.
Given the diagnostic challenges associated with
malignant LGEs, the present clinicopathological analysis provided
clinically relevant insights; however, several limitations warrant
consideration. This was a single-center study conducted within a
defined population, which may limit generalizability to other
geographic or ethnic groups. Future multicenter studies would help
further evaluate the generalizability of these results. In
addition, although the extended study period is an advantage, it
also introduces potential heterogeneity in biopsy indications,
clinical documentation and diagnostic standards. Clinical
impressions were recorded during routine dental care by different
clinicians over nearly four decades and may therefore reflect
variability in individual judgment and documentation practices.
Furthermore, the evolution of diagnostic frameworks, including
updates in World Health Organization tumor classifications and the
increasing availability of immunohistochemical techniques may have
influenced case interpretation, notably in earlier years. To
minimize temporal inconsistencies, all eligible cases were
reassessed and confirmed according to current diagnostic standards
at the time of the present study. A considerable proportion of
clinical variables were unavailable, particularly in earlier cases,
reflecting the retrospective nature of the present study and
historical documentation practices. To avoid overfitting and loss
of statistical power in this relatively limited cohort, univariable
logistic regression analyses were performed to explore the
association between each clinical factor and the outcome
independently. Inclusion of all variables in a multivariable
logistic regression model would have markedly reduced the effective
sample size and potentially introduced instability and bias into
the estimates.
To further explore potential confounding and
interactions among variables (including age, location and clinical
appearance), decision-tree analysis was also conducted. This
approach allows simultaneous evaluation of multiple predictors,
accounts for interactions between variables, and identifies
hierarchical relationships that may not be captured in standard
regression modeling. Accordingly, while the logistic regression
analyses were exploratory and unadjusted, the decision-tree model
provided a multivariable framework incorporating interrelated
factors in outcome prediction. Despite these limitations, the
available data allowed identification of clinically meaningful
predictors. Nevertheless, the findings should be interpreted with
caution and future studies with more complete and standardized data
collection, ideally using prospective multicenter designs, are
needed to validate and expand upon these results.
Furthermore, diagnostic concordance was defined
based on agreement between clinical and pathological diagnoses
according to reclassified ‘nature of disease’ categories. While
this pragmatic approach enabled standardized comparison across a
long retrospective period with variable documentation, it may
oversimplify clinical diagnostic accuracy. Specifically, it
emphasizes recognition of biological behavior, such as malignant
compared with non-malignant rather than exact entity level
agreement. This approach may also influence concordance rates,
notably for salivary gland and hematological malignancies that can
clinically mimic reactive lesions. These findings should therefore
be interpreted within this context. In addition, the use of simple
logistic regression limits adjustment for confounding among
interrelated variables such as age, site and clinical features.
Given the limited sample size and missing data, multivariable
modeling was not feasible. Although decision tree analysis was used
to explore variable interactions, residual confounding cannot be
excluded.
Among malignant LGEs, unsurprisingly, SCC was the
most prevalent. However, nearly 40% of these malignancies
originated from non-epithelial sources, which exhibited a notably
low diagnostic concordance rate. Non-epithelial malignancies are
more likely to have a smooth surface, appear red, occur more
frequently in younger patients, and are predominantly located in
the maxilla. By considering these clinical parameters, clinicians
may be able to differentiate between epithelial and non-epithelial
malignant LGEs more effectively, potentially leading to more
accurate diagnoses and improved patient outcomes.
Acknowledgements
Not applicable.
Funding
Funding: This study was supported by the Faculty of Dentistry,
Mahidol University, Thailand.
Availability of data and materials
The data generated in the present study may be
requested from the corresponding author.
Authors' contributions
DR was responsible for the conceptualization,
methodology, writing the original draft and project administration.
PS was responsible for conceptualization, visualization, writing,
reviewing and editing. NK was responsible for writing, reviewing,
editing and supervision. TA was responsible for methodology, formal
analysis, writing, reviewing and editing. NS was responsible for
software, formal analysis and validation. VN, WA, SH and SA were
responsible for formal analysis, investigation and visualization.
PL was responsible for conceptualization, supervision, validation,
writing, reviewing and editing. DR and PL confirm the authenticity
of all the raw data. All authors read and approved the final
version of the manuscript.
Ethics approval and consent to
participate
The present retrospective study was conducted in
accordance with the Declaration of Helsinki ethical standards and
approved by the Faculty of Dentistry/Faculty of Pharmacy, Mahidol
University, Institutional Review Board (COA.No.MU-DT/PY-IRB
2022/047.2209). For this type of study, patient informed consent
was waived by the Institutional Review Board due to its
retrospective nature.
Patient consent for publication
Not applicable.
Competing interests
The authors declare that they have no competing
interests.
References
|
1
|
Singhal R, Singh A, Rastogi P and Dixit J:
Odontogenic myxoma presenting as localized inflammatory gingival
enlargement: A diagnostic dilemma. J Indian Soc Periodontol.
16:461–464. 2012.PubMed/NCBI View Article : Google Scholar
|
|
2
|
Parihar S, Garg RK and Narain P: Primary
extra-nodal non-Hodgkin's lymphoma of gingiva: A diagnostic
dilemma. J Oral Maxillofac Pathol. 17(320)2013.PubMed/NCBI View Article : Google Scholar
|
|
3
|
Sripodok P, Lapthanasupkul P, Arayapisit
T, Kitkumthorn N, Srimaneekarn N, Neeranadpuree V,
Amornwatcharapong W, Hempornwisarn S, Amornwikaikul S and
Rungraungrayabkul D: Development of a decision tree model for
predicting the malignancy of localized gingival enlargements based
on clinical characteristics. Sci Rep. 14(22185)2024.PubMed/NCBI View Article : Google Scholar
|
|
4
|
Tamiolakis P, Chatzopoulou E, Frakouli F,
Tosios KI and Sklavounou-Andrikopoulou A: Localized gingival
enlargements. A clinicopathological study of 1187 cases. Med Oral
Patol Oral Cir Bucal. 23:e320–e325. 2018.PubMed/NCBI View Article : Google Scholar
|
|
5
|
Holmstrup P, Plemons J and Meyle J:
Non-plaque-induced gingival diseases. J Clin Periodontol. 45 (Suppl
20):S28–S43. 2018.PubMed/NCBI View Article : Google Scholar
|
|
6
|
Nuyen BA and Tang CG: Gingival metastasis:
A case report and literature review. Perm J. 20:71–73.
2016.PubMed/NCBI View Article : Google Scholar
|
|
7
|
Gupta R, Debnath N, Nayak PA and
Khandelwal V: Gingival squamous cell carcinoma presenting as
periodontal lesion in the mandibular posterior region. BMJ Case
Rep. 2014(bcr2013202511)2014.PubMed/NCBI View Article : Google Scholar
|
|
8
|
Manjunatha BS, Gowramma R, Nagarajappa D
and Tanveer A: Extranodal non-Hodgkin's lymphoma presenting as
gingival mass. J Indian Soc Periodontol. 15:418–420.
2011.PubMed/NCBI View Article : Google Scholar
|
|
9
|
WHO Classification of Tumours Editorial
Board: Head and neck tumours, 5th ed. International Agency for
Research on Cancer, Lyon, 2022. https://publications.iarc.fr/.
|
|
10
|
Hothorn T, Hornik K and Zeileis A:
Unbiased Recursive Partitioning: A Conditional Inference Framework.
J Comput Graph Stat. 15:651–674. 2006.
|
|
11
|
Bello IO and Qannam A: Gingival and
alveolar ridge overgrowths: A histopathological evaluation from
Saudi Arabia. Saudi Dent J. 34:509–515. 2022.PubMed/NCBI View Article : Google Scholar
|
|
12
|
Li X, Zhang J, Zhang H and Li T: Biopsied
non-dental plaque-induced gingival diseases in a Chinese
population: A single-institute retrospective study. BMC Oral
Health. 21(265)2021.PubMed/NCBI View Article : Google Scholar
|
|
13
|
Shamim T, Varghese VI, Shameena PM and
Sudha S: A retrospective analysis of gingival biopsied lesions in
South Indian population: 2001-2006. Med Oral Patol Oral Cir Bucal.
13:E414–E418. 2008.PubMed/NCBI
|
|
14
|
Montazer Lotf-Elahi MS, Farzinnia G and
Jaafari-Ashkavandi Z: Clinicopathological study of 1000 biopsied
gingival lesions among dental outpatients: A 22-year retrospective
study. BMC Oral Health. 22(154)2022.PubMed/NCBI View Article : Google Scholar
|
|
15
|
Alblowi JA and Binmadi NO: Histopathologic
analysis of gingival lesions: A 20-year retrospective study at one
academic dental center. J Clin Exp Dent. 10:e561–e566.
2018.PubMed/NCBI View Article : Google Scholar
|
|
16
|
Dilsiz A and Sevinc Gu SNL: Investigation
of biopsied non-plaque-induced Gingival Lesions in a Turkish
population: A 5-year retrospective study. Eurasian J Med.
55:100–103. 2023.PubMed/NCBI View Article : Google Scholar
|
|
17
|
Buchner A, Shnaiderman-Shapiro A and Vered
M: Relative frequency of localized reactive hyperplastic lesions of
the gingiva: A retrospective study of 1675 cases from Israel. J
Oral Pathol Med. 39:631–638. 2010.PubMed/NCBI View Article : Google Scholar
|
|
18
|
Savage NW and Daly CG: Gingival
enlargements and localized gingival overgrowths. Aust Dent J. 55
(Suppl 1):S55–S60. 2010.PubMed/NCBI View Article : Google Scholar
|
|
19
|
Lakkam BD, Astekar M, Alam S, Sapra G,
Agarwal A and Agarwal AM: Relative frequency of oral focal reactive
overgrowths: An institutional retrospective study. J Oral
Maxillofac Pathol. 24:76–80. 2020.PubMed/NCBI View Article : Google Scholar
|
|
20
|
Zhao N, Yesibulati Y, Xiayizhati P, He YN,
Xia RH and Yan XZ: A large-cohort study of 2971 cases of epulis:
focusing on risk factors associated with recurrence. BMC Oral
Health. 23(229)2023.PubMed/NCBI View Article : Google Scholar
|
|
21
|
Dhawad MS and Nimonkar PV: Metastatic
carcinoma of gingiva mimicking pyogenic granuloma. J Maxillofac
Oral Surg. 10:163–165. 2011.PubMed/NCBI View Article : Google Scholar
|
|
22
|
Rim JH, Moon SE, Chang MS and Kim JA:
Metastatic hepatocellular carcinoma of gingiva mimicking pyogenic
granuloma. J Am Acad Dermatol. 49:342–343. 2003.PubMed/NCBI View Article : Google Scholar
|
|
23
|
Donaduzzi LC, Reinheimer A, da Silva MAR,
de Noronha L, Johann ACBR, Franco A, Couto SAB and Souza PHC:
Primary diffuse large B cell lymphoma mimicking hyperplastic
reactive lesion (Lymphoma of the Oral Cavity). Case Rep Pathol.
2018(2981689)2018.PubMed/NCBI View Article : Google Scholar
|
|
24
|
Thielker J, Grosheva M, Ihrler S, Wittig A
and Guntinas-Lichius O: Contemporary management of benign and
malignant parotid tumors. Front Surg. 5(39)2018.PubMed/NCBI View Article : Google Scholar
|
|
25
|
Mortazavi H, Safi Y, Baharvand M, Rahmani
S and Jafari S: Peripheral exophytic oral lesions: A clinical
decision tree. Int J Dent. 2017(9193831)2017.PubMed/NCBI View Article : Google Scholar
|
|
26
|
de Oliveira EM, de Caceres CVBL,
Santos-Silva AR, Vargas PA, Lopes MA, Pontes HAR, Pontes FSC,
Mesquita RA, de Sousa SF, Abreu LG, et al: Clinical diagnostic
approach for oral lymphomas: A multi-institutional, observational
study based on 107 cases. Oral Surg Oral Med Oral Pathol Oral
Radiol. 136:427–435. 2023.PubMed/NCBI View Article : Google Scholar
|
|
27
|
Santos-Leite EG, Louredo BV, de Souza LL,
Pontes HA, Pontes FS, Dos Santos JN, Henriques ÁC, de Castro JF,
Carvalho EJ, Leonel AC, et al: Gingival neoplasms: A multicenter
collaborative study of 888 patients in Brazil. Med Oral Patol Oral
Cir Bucal. 28:e301–e309. 2023.PubMed/NCBI View Article : Google Scholar
|
|
28
|
Udeabor SE, Rana M, Wegener G, Gellrich NC
and Eckardt AM: Squamous cell carcinoma of the oral cavity and the
oropharynx in patients less than 40 years of age: A 20-year
analysis. Head Neck Oncol. 4(28)2012.PubMed/NCBI View Article : Google Scholar
|
|
29
|
Triantafillidou K, Dimitrakopoulos J,
Iordanidis F and Gkagkalis A: Extranodal non-hodgkin lymphomas of
the oral cavity and maxillofacial region: A clinical study of 58
cases and review of the literature. J Oral Maxillofac Surg.
70:2776–2785. 2012.PubMed/NCBI View Article : Google Scholar
|
|
30
|
Seoane J, Van der Waal I, Van der Waal RI,
Cameselle-Teijeiro J, Antón I, Tardio A, Alcázar-Otero JJ,
Varela-Centelles P and Diz P: Metastatic tumours to the oral
cavity: A survival study with a special focus on gingival
metastases. J Clin Periodontol. 36:488–492. 2009.PubMed/NCBI View Article : Google Scholar
|
|
31
|
Soo KC, Spiro RH, King W, Harvey W and
Strong EW: Squamous carcinoma of the gums. Am J Surg. 156:281–285.
1988.PubMed/NCBI View Article : Google Scholar
|
