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2022, Volume 38, Number 3, Page(s) 227-234
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DOI: 10.5146/tjpath.2021.01566 |
Evaluation of Histomorphological Parameters to Predict Occult Nodal Metastasis in Early-Stage Oral Squamous Cell Carcinoma |
Rahul VERMA, Ashok SINGH, Nilotpal CHOWDHURY, Prashant Pranesh JOSHI, Prashant DURGAPAL, Shalinee RAO, Sanjeev KISHORE |
Department of Pathology, All India Institute of Medical Sciences, RISHIKESH, INDIA |
Keywords: Oral squamous cell carcinoma, Nodal metastasis, Histomorphological parameters, Early-stage tumors |
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Objective: The oral squamous cell carcinoma (OSCC) treatment protocol depends upon lymph node metastasis. Elective neck dissection for
early-stage OSCC (pT1/T2) elective neck dissection reduces the morbidity rate. It also reduces the overall survival and thus it becomes important
to detect lymph node metastasis in early-stage OSCC.
Material and Method: Various histomorphological parameters have been studied to predict nodal metastasis in early-stage OSCC. We aim
to evaluate these parameters in the context of nodal metastasis. 78 cases of early-stage OSCC were included in the study with histopathologic
parameters like tumor size, grade, tumor depth of invasion (DOI), lymphovascular invasion (LVI), perineural invasion (PNI), worst pattern of
invasion (WPOI), and lymph node level.
Results: Out of the 78 patients, 32 patients had lymph node metastasis. T stage, DOI, LVI, and WPOI showed statistically significant deviance
from the null model (P-values of 0.007, 0.01, 0.04 and 0.02 respectively). The Odds Ratio (OR) of T stage, DOI, LVI and WPOI were 4.45 (95%
C.I =1.47-14.1), 4.4 (95% C.I =1.32-15.88), 8.12 (95% C.I =1.002-198.20), and 3.39 (95% C.I =1.24-9.74) respectively. On multivariate analysis
(Firth logistic regression) using DOI, LVI, and WPOI as independent variables, only T-stage and WPOI retained statistical significance.
Conclusion: The prognostic information supplied by evaluating DOI, LVI, and WPOI warrants the inclusion of these parameters in the standard
reporting format for all cases of OSCC. |
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Oral cancer is the eighth most common malignancy
in the world and third most common in India with an
incidence rate of 12.6 per 100000 population 1. Oral
squamous cell carcinoma (OSCC) accounts for almost 90%
of the oral malignancies (2). The multifactorial etiology
ranges from tobacco chewing to genetics. It is also twice
as common in males as compared to females with a high
mortality rate and overall 5-year survival rate of 50%,
which further decreases to 20-36% with nodal metastasis
3,4. According to the National Comprehensive Cancer
Network (NCCN) Head and Neck Cancer guidelines,
the treatment modality for OSCC varies from resection
of the primary with or without the neck dissection. Neck
dissection is recommended in advanced stages like T3 and
T4. However, there is disagreement over the approach for
early-stage OSCC i.e. T1-2, N0. Although neck dissection
in early-stage OSCC reduces the morbidity, it also exposes
the patient to unnecessary neoadjuvant therapy and
overtreatment. On the other hand, primary resection
without neck dissection may lead to increased overall survival compared to the elective neck dissection group
5. Thus it becomes the utmost necessity to detect lymph
node metastasis, especially in early-stage OSCC. Depth of
invasion (DOI) is considered to be the best predictor of
occult metastatic disease. It is recommended that clinical
judgment should be utilized for cases having DOI of 2-4
mm and elective neck dissection should be done for
DOI >4 mm 6. Other histological parameters like the
worst pattern of invasion (WPOI), tumor differentiation,
T-stage, extra-nodal extension (ENE), lymphovascular
invasion (LVI), and perineural invasion (PNI) are also
being studied as predictors of local and distant occult
metastasis, thus collaborating in the overall decisionmaking
for elective nodal dissection and further helping
in reducing the incidence of treatment failure 7,8. These
histological parameters can be used to create a predictive
model to ascertain the risk of metastasis in early-stage
OSCC and further aiding in treatment decision-making.
Various risk prediction models have been suggested by
the authors to predict the nodal metastasis in the early
as well as late-stage OSCC 9-11. Most of the scores and systems are being validated in the western countries only
with an exception to the Brandwein Gensler risk model
which was validated in the Indian scenario by Chaturvedi
et al 9. A new scoring system, the Aditi-Nuzhat Lymphnode
Prediction Score (ANLPS) System, was developed
by Arora et al. exclusively on the Indian population for
early-stage OSCC 11. Our study aims to analyze various
histomorphological parameters of early-stage OSCC as
predictors of occult nodal metastasis. |
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Abstract
Introduction
Methods
Results
Disscussion
References
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This retrospective analytical study was conducted in the
Department of Pathology, in a tertiary care hospital in North
India, by reviewing the archival data of all the OSCC patients
who went for primary tumor resection with or without neck
node dissection during the period of one year from January
2019 to December 2020. Patients with biopsy- proven
OSCC and pathological stage pT1/T2 were included in the
study. Patients with prior neoadjuvant therapy, recurrence,
multiple tumors, verrucous carcinoma, and incomplete
data were excluded from the study. After recording the
demographic and clinical details, the cases were reviewed
by two pathologists independently for the following
parameters: tumor size, histopathological tumor grade
(well, moderate and poorly differentiated), pathological
tumor stage (TNM), DOI, regional lymph node metastasis
along with the cervical level, LVI, PNI, and WPOI. On
histology, the tumor was graded as described by Que et
al 12. Tumors showing easily recognizable squamous
epithelium, abundant keratinization, intercellular bridges,
minimal pleomorphism, and basally located mitotic figures
were graded as well-differentiated (Grade 1). Those tumors
where squamous lineage was difficult to determine, having
none or minimal keratinization and marked nuclear
atypia were graded as poorly differentiated (Grade 3),
and tumor cells having features in between well and
poorly differentiated grades with focal keratinization and
pearl formation were graded as moderately differentiated
(Grade 2.) DOI was measured in millimeters ( mm) using
an eyepiece graticule micrometer from the basement
membrane of adjacent normal to the deepest point of
invasion (Figure 1). WPOI was graded as 1-4 and 5. WPOI
1-4 included tumors having pushing borders (WPOI 1),
finger-like tumor borders (WPOI 2), large islands of >15
tumor cells/ island close to <1 mm to the main tumor
(WPOI 3), small islands of <15 tumor cells/ island close to
<1 mm to the main tumor and dispersed tumor satellites
>1 mm away from the main tumor (WPOI 5, Figure 2)
13. WPOI 1-4 tumors are non-aggressive and thus were
kept in one subgroup. TNM Staging was done according
to the American Joint Committee on Cancer (AJCC)
classification. Figure 3 shows a mandibulectomy specimen
having OSCC reported as pathological T-stage 2. The level of lymph nodes involved was also noted for creating the
prediction model of nodal metastasis.
Click Here to Zoom |
Figure 1: Depth of invasion (DOI) measurement in oral squamous
cell carcinoma (OSCC). Histomorphological picture showing
DOI of 3mm in an OSCC pathological stage T2 (H&E stain, 2x
magnification) |
Click Here to Zoom |
Figure 2: Histomorphological picture showing WPOI-5 an OSCC
pathological stage T2 (H&E stain, 4x magnification) |
Statistical Analysis
Statistical analyses were performed using R software (v
3.6.0) 14, with help from the packages “exact2x2” 15,
“pROC” 16, and “logistf” 17. Descriptive analysis
for clinical factors was done with continuous variables
described as Mean ±standard deviation and categorical
variables described as proportion. For univariate analysis
of the histopathological parameters with nodal status,
the significance of the association between dichotomous
categorical variables (LVI, WPOI, T stage: stage 1 vs. stage
2, DOI dichotomized into two groups: less than 4 cm
and greater than or equal to 4 cm) and node status was
estimated by the usual Fisher’s exact test and matching
confidence interval 15 of the conditional odds ratio by
the “exact2x2” R package. For 2x6 tables (e.g. relationship
between tumor site and lymph node status), the generalized
Fisher’s exact test was used. The univariate analysis of
DOI as a continuous variable was also done by univariate
Firth logistic regression. The variables that were found
statistically significant at an alpha of 0.05 were further
studied in a multivariate analysis using Firth penalized
logistic regression and profile penalized log-likelihood
confidence intervals 18. The assumption of linearity in the
logit for the Firth regression was tested by the Box-Tidwell
test. We subsequently performed a ROC curve analysis for
the continuous variables significantly associated with nodal
metastasis on univariate analysis. Finally, Mann-Whitney-
Wilcoxon tests and Fisher exact tests were used to examine
the relationship between the variables found significant in
univariate analysis. All tests were 2-sided with significance
considered at p<0.05. |
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Abstract
Introduction
Methods
Results
Disscussion
References
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The baseline demographics and clinicopathological data
of a total of 189 cases were recorded (Table I). The mean
age of the patients comprising 170 (89.9%) males and 19
(10.1%) females was 48±12.9 years. Buccal mucosa (n=95)
(50.2%) was the most common primary site in the oral
mucosa followed by the tongue (n=60) (31.7%). Most of
the cases were moderately differentiated histological grade
n=112(59.2%) and T4a pathological stage n=74(39.6%). A
total of 90(47.6%) cases were found to be nodal positive
with maximum cases (n=25) (27.7%) falling in the N1
pathological stage. A total of 78 cases were found to be of
the pT1/T2 stage. These cases were included in the study
for further analysis.
Click Here to Zoom |
Table I: Baseline demographics and clinicopathological
data of all cases. |
Clinical Parameters of T1/T2 Tumors
Table II summarizes the results of the clinical and
demographic parameters of early-stage OSCC (T1/T2) to
evaluate them as predictors of nodal metastasis. None of
the parameters was statistically significant to predict the
nodal metastasis.
Click Here to Zoom |
Table II: Demographic and clinical parameters in early-stage OSCC (T1/T2). |
Histomorphological Parameters of Early-Stage OSCC
(T1/T2)
Table III summarizes the association of various histomorphological
parameters with the lymph node status. Out
of all the parameters, four parameters composed of the
T-stage, DOI, LVI, and WPOI were statistically significant.
Click Here to Zoom |
Table III: Histomorphological parameters in early-stage OSCC (T1/T2). The statistical significance has been tested by the Fisher exact
test, with corresponding Confidence intervals, unless indicated otherwise. |
Other parameters did not show a statistically significant
correlation with nodal metastasis in early-stage OSCC
(T1/T2). On multivariate analysis, only WPOI and T-stage
retained their significance (Table IV), but these results are
limited by a small sample size. The Box-Tidwell test did not
reveal a statistically significant violation of the assumption
of linearity of the logit when using the Firth penalized
logistic regression.
Click Here to Zoom |
Table IV: Result of multivariate Firth logistic regression done using the variables found to be statistically significant on univariate
analysis, with the 95% CI of the odds ratio. |
On a ROC curve analysis for DOI, a cut off of 6 mm was
found to give the highest sum of sensitivity and specificity,
and thus the Youden J. The results of the sensitivity and
specificity at the region of highest performance along with
the area under the curve are given in Table V.
Click Here to Zoom |
Table V: The Specificity and Sensitivity at various thresholds for the ROC curve analysis of the Depth of Invasion (DOI), along with the
Area under curve (AUC) with 95% Confidence intervals by the deLong Method. |
We also performed tests for the association between the
significant factors found in univariate analysis. Among
these factors, DOI was significantly associated with the
T-stage (P-value <0.001 by the Mann-Whitney-Wilcoxon
test) and showed a trend towards significance with LVI
(p-value of 0.09 by the Mann-Whitney-Wilcoxon test test).
None of the other factors showed a significant association
with each other. |
Top
Abstract
Introduction
Methods
Results
Disscussion
References
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The oral cancer burden worldwide is approximately 300000/
year out of which India has the highest share (20%). OSCC
is the commonest malignancy in the oral cavity with a male
to female ratio of 3:1 19. According to NCCN guidelines,
the treatment protocol for OSCC depends upon the TNM staging. The mainstay of the treatment is primary resection
with or without neck node dissection. For advanced-stage
OSCC, i.e. T3-T4, treatment includes primary resection with
neck node dissection followed by neoadjuvant therapy if
necessary. However, for early-stage OSCC, i.e. T1-T2, there
is an option for either performing elective neck dissection
or observing with follow up so that loco-regional recurrence
is detected early and salvage surgery can be performed 20.
Although OSCC with no clinical nodal involvement rarely
(<10%) presents with nodal metastasis, it is imperative to
detect occult metastasis in early-stage OSCC. Elective neck
dissection provides comprehensive clearance of nodes,
increases overall survival rate, and prevents loco-regional
recurrences, in addition to increasing the aesthetic and
functional morbidity 21. Several authors have compared
elective node dissection and follow up observation in
early-stage OSCC and found the nodal recurrence rate
to be higher in the observation group compared to the
elective node dissection group. These patients were further
subjected to salvage surgery, which involves aggressive
approach and increases mortality 22-24. Determining
which approach to follow thus requires multiple large-scale
studies and comprehensive reviews.
The various histological parameters are being studied
as prognostic factors associated with the survival rate in
OSCC 25. We studied the histological parameters like
pathological TNM stage, tumor grade, DOI, WPOI, PNI,
and LVI.
DOI has been considered as an important prognostic as well
as regional nodal involvement parameter in many studies
11,26-28. The National Comprehensive Cancer Network
(NCCN) Head and Neck Cancer guidelines suggest elective
neck dissection in tumors with DOI greater than 4 mm.
DOI is different from the tumor thickness as the former one
is measured from the basement membrane between tumor
and adjacent normal surface to the maximum depth of the
tumor whereas tumor thickness also takes into account
the mucosal surface of the tumor. The AJCC 8th edition
now uses DOI for staging 29. In our study, DOI failed to
retain its significance in the multivariate analysis, possibly
due to its association with the T-stage (p-value <0.001
using the Mann-Whitney-Wilcoxon test) causing multi
collinearity and due to the small sample size. However, due
to the importance of DOI found in other papers, we still
conducted a univariate ROC curve analysis of DOI (Table
V), and reported the area under the curve and estimated
best cut-off according to our analysis. DOI was found to
have a modest predictive value in such a univariate analysis.
The worst pattern of invasion (WPOI) is an important
prognostic factor for oral cavity squamous carcinomas
30-32. Five different patterns of WPOI 1-5 have been
described 13. Various studies suggested that WPOI 5
is associated with a higher risk of lymph node metastasis
compared to the other patterns (WPOI 1-4) in early-stage
OSCC 11,33,34. Our findings were also in concordance
with these studies. Moreover when measured together
with DOI, the chances of predicting the occult metastasis
increase. However, some studies have shown discordant
results suggesting no effect of WPOI on occult metastasis
26,35.
Lymphovascular invasion (LVI) was also associated with
lymph nodal metastasis, with a high odds ratio. However,
the predictive effect of LVI was limited by the relatively low
number of cases having a positive LVI. The positive cases,
however, were associated with a greatly increased risk of
metastasis (5 out of 6 cases in our study having LVI had
lymph nodal metastasis). Even in the multivariate analysis,
even though LVI by itself did not have a significant p-value
at an alpha of 0.05.
The T-stage was another important prognostic factor that
also retained its importance in multivariate analysis. In doing
so, it possibly competed against DOI due to significant
association and caused the latter to lose its significance. This
effect was exacerbated by the small sample size. However,
we believe that all the factors that were significant in the
univariate analysis are important predictors for nodal
metastasis in early-stage OSCC, and information from all
the factors should be considered.
It is pertinent to mention that while reporting histopathological
samples from OSCC these parameters should be
evaluated in the standard reporting format as they are
associated with a high risk of nodal metastasis. In our
study, grade and perineural invasion were not statistically
significant to provide any information regarding metastasis.
Multifactorial predictive models and scoring systems
have been suggested by authors. These models evaluate
multiple histomorphological parameters at different levels
to predict metastasis. Multiple variables seem to predict
more accurately when evaluated in large-scale studies
than individual ones 11,28,36. We found WPOI 5 and
T-stage as better predictors in early-stage OSCC, while it
was extremely likely that DOI and LVI have a significant
association with the same. However, the study was limited
due to the small sample size. This led to sparsity of data,
which carries a risk of optimistic estimates of odds ratios
by ordinary logistic regression. Therefore, we carried out
a Firth logistic regression, which is a standard method for
reducing small sample bias. The Firth method uses a method
known as penalized likelihood 18. A possible alternative
would have been to use exact logistic regression, e.g. using
the R package “elrm”. However, exact logistic regression
is a computationally intensive Monte Carlo Markov chain
(MCMC) method. The presence of a continuous variable
as a predictor further increases the sparsity, demanding
greater computational power. In our case, we did not get
valid exact logistic regression results for our multivariate
analysis even after 10 million iterations leaving us the
choice of using just penalization methods like the Firth
logistic regression.
We evaluated some of the histological parameters involved
in predicting the nodal metastasis in early-stage OSCC.
T-stage, WPOI, DOI, and LVI were the major significant
parameters that influenced the nodal metastasis on
univariate analysis. Inclusion of these parameters in routine
standard reporting will increase the likelihood of predicting
the nodal metastasis and hence guiding the clinicians to
choose the best treatment protocol for the patients.
CONFLICT of INTEREST
None.
AUTHORSHIP CONTRIBUTIONS
Concept: RV, Design: AS, Data collection or processing:
RV, Analysis or Interpretation: NC, Literature search: PPJ,
Writing: PD, Approval: SR, SK. |
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Abstract
Introduction
Methods
Results
Discussion
References
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Abstract
Introduction
Methods
Results
Discussion
References
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Copyright © 2022 The Author(s). This is an open-access article published by the Federation of Turkish Pathology Societies under the terms of the Creative Commons Attribution License that permits unrestricted use, distribution, and reproduction in any medium or format, provided the original work is properly cited. No use, distribution, or reproduction is permitted that does not comply with these terms. |
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