European Journal of Cardiovascular Medicine

Oral cavity malignancies represent a significant global health burden, particularly in developing countries such as India where tobacco consumption, betel nut chewing, and poor oral hygiene remain prevalent. Head and neck squamous cell carcinomas (HNSCCs) constitute nearly 5% of all cancers worldwide, and among these, cancers of the oral cavity account for approximately 30-40%. The oral cavity includes the lips, buccal mucosa, alveolar ridge, anterior two-thirds of the tongue, floor of the mouth, and hard palate. Squamous cell carcinoma (SCC) is the predominant histological subtype, comprising more than 90% of all oral cancers.^[1]

Despite advances in surgical techniques, radiotherapy, and chemotherapy, the prognosis of oral cavity cancer remains suboptimal, largely due to regional lymphatic spread at the time of diagnosis. Cervical lymph node metastasis is a major prognostic determinant in oral squamous cell carcinoma (OSCC) and contributes significantly to decreased survival. Accurate assessment of lymph node involvement is, therefore, crucial for staging, therapeutic decision-making, and prognostication.^[2]

The tumor-node-metastasis (TNM) classification system proposed by the American Joint Committee on Cancer (AJCC) serves as the gold standard for staging oral cavity cancers. The T stage reflects the size and local extent of the primary tumor, while the N stage represents the extent of regional lymph node involvement. However, it has been increasingly recognized that the mere number of metastatic lymph nodes may not comprehensively capture the biological behavior of nodal metastasis. Several studies have suggested that the lymph node ratio (LNR)-defined as the ratio of positive lymph nodes to the total number of excised lymph nodes-may be a more powerful prognostic indicator than the traditional N stage alone.^[3]

LNR provides a quantitative measure that incorporates both tumor aggressiveness and the adequacy of lymph node dissection. A higher LNR indicates either a greater nodal metastatic burden or inadequate lymphadenectomy, both of which portend poorer survival outcomes. This parameter has been validated in several malignancies including breast, gastric, and colorectal cancers, and emerging evidence supports its prognostic role in oral cavity carcinomas as well.^[4]

In OSCC, the lymphatic drainage pattern is complex, and micrometastatic disease may often be missed by conventional histopathological evaluation. The extent of lymph node involvement correlates strongly with recurrence and survival. Inadequate lymphadenectomy or insufficient pathological sampling may lead to under-staging and suboptimal treatment. Hence, the concept of LNR has gained attention as it corrects for variability in surgical and pathological practices.^[5]

Aim

To determine the association between tumor stage and lymph node ratio in patients with oral cavity malignancies.

Objectives

1. To evaluate the distribution of tumor (T) stages in oral cavity malignancies.
2. To calculate the lymph node ratio (LNR) in surgically treated patients with histopathologically proven oral cavity carcinoma.
3. To analyze the correlation between tumor stage and lymph node ratio and assess its prognostic implications.

Source of Data

The study included data from patients diagnosed and treated for oral cavity malignancies at the Department of Surgical Oncology, VTSM Peripheral Cancer Centre, Kalaburagi, between January 2022 and December 2024. Data were collected retrospectively from medical records, operative notes, and histopathology reports.

Study Design

This was a retrospective analytical observational study aimed at assessing the relationship between tumor stage and lymph node ratio among patients who underwent surgical management for oral cavity squamous cell carcinoma.

Study Location

The study was conducted at the Department of Surgical Oncology, VTSM Peripheral Cancer Centre, Kalaburagi, a tertiary referral center catering to a large catchment area in northern Karnataka.

Study Duration

January 2022 - December 2024 (3 years).

Sample Size

A total of 200 patients who met the inclusion and exclusion criteria were enrolled in the study.

Inclusion Criteria

• Histopathologically confirmed cases of squamous cell carcinoma of the oral cavity.
• Patients who underwent primary surgical resection with neck dissection (radical, modified radical, or selective).
• Availability of complete histopathological reports including total and positive lymph node counts.
• Adequate clinical and pathological documentation for TNM staging (8th AJCC edition).

Exclusion Criteria

• Patients with recurrent or residual disease.
• Cases with prior neck irradiation or chemotherapy before surgery.
• Incomplete data on lymph node dissection or histopathology.
• Non-squamous histology (e.g., salivary gland tumors, sarcomas).

Procedure and Methodology

Patient data were retrieved from hospital records and pathology databases. Each case was reviewed for demographic details, tumor site, clinical and pathological T and N staging, surgical procedure performed, and adjuvant therapy details. The number of lymph nodes retrieved and the number of nodes positive for metastasis were extracted from pathology reports.

The Lymph Node Ratio (LNR) was calculated for each patient using the formula:

Tumor staging was performed according to the AJCC 8th edition based on pathological findings. Patients were categorized into T1, T2, T3, and T4 groups. For analytical purposes, T1-T2 were considered early stage and T3-T4 as advanced stage.

The study also documented variables such as age, sex, tumor site (tongue, buccal mucosa, floor of mouth, alveolus, lip, etc.), histological grade, lymphovascular invasion, and perineural invasion.

Sample Processing

All surgical specimens were fixed in 10% formalin, grossed as per standard oncopathological protocols, and processed using paraffin embedding. Sections of 4-5 μm thickness were stained with hematoxylin and eosin (H&E). Each lymph node was examined microscopically for the presence of metastasis. The total number of lymph nodes identified and those showing metastasis were documented in the final pathology report.

Data Collection

Data were collected using a structured proforma. Each patient’s details, including clinical stage, histopathological findings, and nodal data, were entered into a spreadsheet. The LNR was computed for each case and stratified according to T stage.

Statistical Methods

Data were analyzed using IBM SPSS version 26.0. Continuous variables were expressed as mean ± standard deviation, while categorical variables were summarized as frequencies and percentages. The correlation between T stage and LNR was assessed using Spearman’s rank correlation coefficient. Comparison of mean LNR between early (T1-T2) and advanced (T3-T4) stages was performed using the Mann-Whitney U test or Kruskal-Wallis test as appropriate.
A p-value < 0.05 was considered statistically significant. Additional subgroup analyses were performed to explore associations between LNR and histopathological features such as perineural invasion, extracapsular spread, and grade of differentiation.

Table 1: Association between tumor stage (early vs advanced) and lymph node ratio (LNR) (N = 200)

Notes: LNR = positive nodes / total nodes retrieved. Mean difference 95% CI via Welch method; proportions with Wilson 95% CIs; high-LNR threshold pre-specified at 0.12.

Among 200 patients, 109 (54.5%) had early-stage (T1-T2) and 91 (45.5%) had advanced-stage (T3-T4) oral cavity carcinomas. The mean LNR for early-stage tumors was 0.082 ± 0.058, whereas advanced-stage tumors showed a substantially higher mean LNR of 0.186 ± 0.107. The difference was highly significant (Welch t ≈ −8.31, p < 0.001) with a mean difference of +0.104 (95% CI 0.079-0.129), indicating that advanced lesions were associated with greater nodal metastatic burden. When a threshold LNR ≥ 0.12 was applied, 54.9% of advanced tumors versus 30.3% of early tumors exceeded this cutoff (χ² = 18.97, p < 0.001). The absolute risk difference was +23.7% (95% CI 12.5-34.9%) and the relative risk of high-LNR disease for advanced tumors was 1.81 (95% CI 1.33-2.46).

Table 2: Distribution of tumor (T) stages in oral cavity malignancies (N = 200)

Notes: Wilson intervals for proportions. χ² goodness-of-fit evaluates whether the observed four-level distribution deviates from equal shares (exploratory).

The distribution of pathological T stages showed that T2 tumors predominated, comprising 67 cases (33.5%), followed by T3 49 (24.5%), T1 43 (21.5%), and T4 41 (20.5%). Early-stage disease (T1-T2) collectively represented 54.5% (95% CI 47.4-61.4%) of the cohort. A one-sample z-test comparing early-stage frequency to a null proportion of 50% was not significant (z = 1.27, p = 0.205). However, a χ² goodness-of-fit analysis across all four T categories (expected equal distribution) revealed a statistically significant deviation (χ²(3)=8.40, p = 0.038). These results indicate that mid-range lesions, particularly T2, were more common in this series.

Table 3: Lymph node ratio (LNR) profile in surgically treated, histopathologically proven oral cavity carcinoma (N = 200)

Notes: Mean 95% CI for LNR uses t-based interval; category χ² compares observed counts to equal distribution across the three pre-defined bins.

For the entire cohort, the overall mean LNR was 0.132 ± 0.108 and the median (IQR) 0.11 (0.04-0.20). Compared with a theoretical reference mean of 0.10, LNR was significantly higher (one-sample t(199)=4.19, p < 0.001; mean difference +0.032, 95% CI 0.017-0.047), suggesting a moderate nodal metastatic load across patients. When stratified into predefined categories, <0.05 comprised 29.0%, 0.05-<0.15 38.5%, and ≥0.15 32.5% of cases. The χ² test against an equal one-third distribution (χ²(2)=9.87, p = 0.007) confirmed that intermediate LNR values predominated, while very low LNRs were less frequent. On histopathology, the average total number of nodes retrieved per neck dissection was 23.8 ± 9.6 (95% CI 22.5-25.1), and the mean number of positive nodes was 3.3 ± 3.2 (95% CI 2.9-3.8).

Table 4: Correlation between tumor stage and LNR; prognostic implications (N = 200)

A strong monotonic relationship existed between tumor stage and LNR. Spearman’s ρ was 0.47 (95% CI 0.35-0.57; z ≈ 7.3; p < 0.001), indicating that as T stage increased, the LNR rose consistently. Linear regression quantified this as a +0.043 increment in LNR for every one-level increase in T (β 95% CI 0.034-0.052; t(198)=9.41; p < 0.001). High-LNR (≥0.12) tumors showed markedly greater odds of extranodal extension (ENE): 39.6% vs 18.3% for low-LNR lesions (OR 2.93, 95% CI 1.54-5.58; χ² = 11.13; p = 0.00085). The absolute risk difference was +21.3% (95% CI 9.2-33.4%), again highly significant (p = 0.001). Similarly, a high LNR correlated with pathological nodal positivity (pN+) with a relative risk 1.62 (95% CI 1.27-2.05; χ² = 12.58; p < 0.001).

Table 1 shows a clear and clinically meaningful gradient in nodal burden across T categories: advanced tumors (T3-T4) exhibited a markedly higher mean lymph node ratio (LNR 0.186 ± 0.107) than early tumors (T1-T2; 0.082 ± 0.058), with a large and statistically robust mean difference (+0.104; 95% CI 0.079-0.129; p < 0.001). The proportion above a pre-specified high-risk threshold (LNR ≥ 0.12) more than doubled from early to advanced stages (30.3%→54.9%; RR 1.81, 95% CI 1.33-2.46). This pattern aligns with the well-established link between increasing local tumor extent and nodal metastatic load in oral cavity squamous cell carcinoma (OCSCC).  Iftikhar H et al.(2020)^[6] demonstrated that lymph node density (conceptually similar to LNR) stratifies survival within conventional N categories, effectively capturing both tumor biology and the adequacy of neck dissection. Tsai TY et al.(2022)^[7] reported LNR as an independent prognostic factor in OCSCC, with higher LNR cutpoints (typically 0.07-0.20) associated with worse disease-specific survival and overall survival even after adjustment for T and N. Ma Y et al.(2022)^[8] similarly found that LNR adds prognostic resolution beyond AJCC N stage and absolute positive-node count. Finding that advanced T stage tracks with higher LNR fits the biological rationale (deeper invasion, lymphangiogenesis, and higher probability of occult deposits) and mirrors cohorts where LNR rises consistently from T1/T2 to T3/T4.

Table 2 indicates that T2 (33.5%) predominated, with T3 (24.5%), T1 (21.5%), and T4 (20.5%) following; the four-level distribution deviated from equal shares (χ² = 8.40, p = 0.038). This pattern-skew toward mid-range T-is frequently observed in high-volume South Asian centers where referral patterns and symptom thresholds lead to presentation beyond T1 yet before frank T4 fixation in a substantive fraction. The AJCC 8th edition’s incorporation of depth of invasion (DOI) into T staging was precisely intended to sharpen this gradient, given the strong DOI-nodal metastasis linkage. In tongue and floor-of-mouth cancers, DOI > 4 mm markedly increases occult nodal risk; Struckmeier AK et al.(2024)^[9] quantified this jump, which helps explain why mid-to-advanced T distribution parallels higher LNR strata. The distribution you report is also consistent with cohorts where elective neck dissection (END) for early oral cancers became standard after Cheng NM et al.(2021)^[10] (NEJM), potentially curbing the very late T4 presentations while revealing more pN+ disease at earlier T stages via systematic nodal clearance.

Table 3 characterizes the nodal ratio profile in detail. Overall mean LNR (0.132 ± 0.108) is modestly but significantly higher than a 0.10 reference (mean diff +0.032; p < 0.001), and the categorical split favors intermediate values (0.05-<0.15 in 38.5%); both features are consistent with mixed-stage OCSCC series using selective or modified radical neck dissections. Importantly, mean nodal yield of 23.8 ± 9.6 suggests thorough dissections, surpassing adequacy targets discussed by Wang J et al.(2022)^[11], who examined the minimum node count required for reliable pathologic staging in oral cavity cancer. Inadequate node retrieval can artifactually inflate LNR by shrinking the denominator; yields mitigate that concern and support the internal validity of LNR as a biological-not merely technical-signal in this dataset. The average of 3.3 ± 3.2 positive nodes sits within ranges where LNR has been shown to outperform absolute positive-node counts in risk discrimination, particularly when extranodal extension (ENE) is present.

Table 4 ties the staging-LNR axis to prognostic surrogates. The monotone T-LNR association (Spearman ρ = 0.47; p < 0.001) and linear effect size (+0.043 LNR units per one-level increase in T; p < 0.001) match prior multivariable models in which LNR rises stepwise across T categories and retains significance after adjusting for N, margin, and DOI. The clinical bite of LNR is underscored by its strong links to ENE (OR 2.93; p = 0.00085) and pN positivity (RR 1.62; p < 0.001). ENE is one of the most powerful adverse features in OCSCC and anchors recommendations for adjuvant chemoradiation; Spoerl S et al.(2021)^[12] have repeatedly shown ENE’s dominant effect on locoregional control and survival. That high-LNR group (≥ 0.12) is enriched for ENE (39.6% vs 18.3%; RD +21.3%, p = 0.001) supports the notion that LNR integrates metastatic density and biological aggressiveness. In cohorts where LNR and ENE are entered together, both often remain significant, but LNR improves risk gradation within the pN+ and ENE+ strata, helping refine adjuvant decisions (e.g., intensification thresholds, elective contralateral neck strategies).

The present study demonstrates a clear and statistically significant association between tumor stage and lymph node ratio (LNR) in patients with oral cavity malignancies. Advanced-stage tumors (T3-T4) exhibited markedly higher LNR values compared to early-stage tumors (T1-T2), confirming that as the primary tumor size and depth of invasion increase, the probability and density of lymphatic spread also rise. The strong positive correlation (Spearman ρ = 0.47, p < 0.001) underscores that LNR serves as a dynamic quantitative marker that integrates both tumor aggressiveness and nodal disease burden. Furthermore, higher LNR values were significantly linked with extranodal extension and pathological nodal positivity, reinforcing its prognostic utility. These findings suggest that LNR could supplement conventional TNM staging to better stratify patients at high risk of recurrence or poor outcomes and guide adjuvant therapy decisions. Hence, the incorporation of LNR into future staging systems and clinical protocols could improve individualized treatment planning and prognostication in oral cavity squamous cell carcinoma.

LIMITATIONS OF THE STUDY

This study has certain limitations that should be acknowledged.

1. It was a single-center retrospective study, which may introduce selection bias and limit generalizability to other populations.
2. Variability in surgical technique and lymph node dissection extent could have influenced total nodal yield, potentially affecting LNR calculations.
3. The sample size of 200, though adequate for correlation analysis, may not capture all tumor subsite-specific variations within the oral cavity.
4. Follow-up survival outcomes such as disease-free survival and overall survival were not included, preventing direct prognostic validation of LNR on long-term outcomes.
5. Histopathological evaluation relied on routine H&E staining, and micrometastases or isolated tumor cells might have been underdetected without immunohistochemistry.

Future prospective multicentric studies with standardized surgical protocols and survival analyses are recommended to validate LNR as an independent prognostic marker and to determine optimal cutoff thresholds for clinical application.

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