Head and neck cancer, comprising malignancies in the oral cavity, pharynx, larynx, thyroid gland, salivary glands, and other head and neck regions, is a prevalent malignancy worldwide. In 2020, global incidence rates reported approximately 377,713 new cases of oral cancer, 98,412 of oropharyngeal cancer, 84,254 of hypopharyngeal cancer, and 184,615 of laryngeal cancer (1). Squamous cell carcinoma (SCC), the predominant form of head and neck cancer, originates from the malignant transformation of the squamous epithelium in these regions and constitutes about 90% of all such cancers (2). Common primary sites include the oral cavity, pharynx, and larynx (3). Head and neck squamous cell carcinoma (HNSCC) is notably characterized by invasive growth and a propensity for lymph node metastasis, posing significant diagnostic and treatment challenges globally.

In this context, substantial research has been dedicated to identifying biomarkers for HNSCC (4–6), aiming to enhance disease management, particularly in diagnosis and prognosis. However, limitations in biomarker verification, insufficient quantity or quality of marker molecules, and detection challenges persist. Moreover, methodological flaws in some studies, such as inadequate sample sizes, further complicate these challenges (7–9). Currently, there is no universally accepted definitive prognostic or predictive biomarker for HNSCC.

Despite the heterogeneity observed in tumors, a common characteristic is their uncontrolled proliferative capacity (10). Ki-67, a prominent proliferation marker in human tumor cells, is crucial during interphase and mitosis, with its cellular distribution varying significantly throughout the cell cycle (11). It has been identified as an independent marker for predicting the prognosis of various malignancies, including those of the lung, breast, kidney, and prostate (12–15). In HNSCC, substantial evidence supports Ki-67’s prognostic value (16–19). Nonetheless, the validity of this evidence is often questioned due to small sample sizes, and conflicting views exist regarding Ki-67’s correlation with HNSCC prognosis (20, 21). Furthermore, the nomogram model based on Ki-67 characteristic expression for head and neck squamous carcinoma is currently not a focal point of research.

To address these discrepancies, this study endeavors to evaluate the prognostic value of Ki-67 and construct a prognostic model incorporating Ki-67 in HNSCC by analyzing a large patient cohort, thus offering more substantial and reliable evidence.

This investigation encompassed a retrospective cohort of 764 patients diagnosed with four principal subtypes of head and neck squamous cell carcinoma (HNSCC): oral squamous cell carcinoma (OSCC), oropharyngeal squamous cell carcinoma (OPSCC), hypopharyngeal squamous cell carcinoma (HPSCC), and laryngeal squamous cell carcinoma (LSCC). These patients were admitted to our institution between 2012 and 2022. A thorough analysis of their medical records yielded vital clinicopathological data, including age, sex, primary tumor site, pathological grade, and clinical TNM stage, adjudicated per the 8th edition of the Union for International Cancer Control’s Cancer Staging Manual. Additionally, information on recurrence, metastasis, survival status, and duration of survival as of December 31, 2022, was meticulously collected.

To augment this data, immunohistochemical staining was performed on formalin-fixed, paraffin-embedded surgical specimens, primarily focusing on the expression of Ki-67. This study received full approval from our Institutional Review Board (Ethics approval number: WCHSIRB-D-2023-437) and was rigorously conducted in alignment with the ethical guidelines set forth in the Declaration of Helsinki.

The identification of prognostic biomarkers and the development of prognostic models for head and neck squamous cell carcinoma (HNSCC) are pivotal for predicting patient outcomes and guiding clinical decision-making. This facilitates the adoption of personalized clinical strategies (22). Ki-67, a nuclear protein initially discovered in proliferating Hodgkin’s lymphoma cells by Gerdes et al. (23), is exclusively expressed during mitosis and absent in quiescent cells. Its expression, regulated by cell cycle-dependent transcription and protein degradation (24), marks it as a critical cell proliferation marker. Despite its established prognostic efficacy in various tumors, insights into Ki-67’s role in HNSCC remain varied, influenced by factors like sample size, detection techniques, and cut-off values for grouping (25–27).

In our study, Kaplan-Meier curves and log-rank tests identified Ki-67 as a prognostic risk factor for HNSCC. Cox multivariate analysis, controlling for confounders, confirmed Ki-67’s role as an independent prognostic factor alongside age, recurrence, and metastasis. Our study’s prognostic model, incorporating Ki-67, age, recurrence, and metastasis, revealed that recurrence and metastasis had a more substantial impact on prognosis than Ki-67 expression and age, as evidenced by their higher hazard ratio values. The model’s C-index was 0.721, indicating excellent predictive efficacy (28). The calibration curve corroborated the nomogram’s accuracy in reflecting actual patient survival.

Furthermore, within the Cox proportional hazards model, while the HR for Ki-67 expression exceeded 1, it was lower than that of other variables. This can be attributed to the Ki-67 expression being analyzed as a continuous variable with values ranging from 0 to 100. The HR for Ki-67 expression in the overall cohort was 1.009, representing that if the expression of Ki-67 increased by 1, the risk of patient death increased by 1.009. Upon further analysis, by stratifying Ki-67 expression into two groups based on a predefined cut-off value for the Cox model, we observed a substantially increased HR for Ki-67 expression. Nevertheless, we advocate for the utilization of Ki-67 expression as a continuous variable. This approach not only preserves the integrity of the data but also ensures that the Nomogram remains uninfluenced by arbitrary cut-off values for Ki-67 expression, thereby enhancing its utility.

Unlike prior studies that often relied solely on clinical, gene transcription, or gene expression data for prognostic modeling, our research uniquely integrated clinical data with immunohistochemical staining. Immunohistochemical staining, a standard procedure in tumor pathology, is both cost-effective and time-efficient. It proves more manageable in clinical settings than gene expression analysis. By simply assessing Ki-67 levels alongside key clinicopathological features, one can predict a patient’s prognosis using the nomogram. This predictive insight equips clinicians with solid evidence, facilitating informed decision-making about subsequent treatment steps. For instance, a poor predicated prognosis may prompt the consideration of active measures, including postoperative radiotherapy and chemotherapy. This has a positive effect on the overall prognosis of the patient. Moreover, the prognostic model’s presentation through a nomogram offers clarity, ease of understanding, and practical applicability.

Our research also explored Ki-67 expression’s correlation with clinicopathological features in HNSCC patients. Elevated Ki-67 expression in advanced-stage and poorly differentiated tumors highlighted its link to cell proliferation (29). Notably, Ki-67 expression was significantly higher in males than females, possibly reflecting variations in sex hormones or lifestyle factors like tobacco and alcohol use (30, 31). HPV infection status also appeared to influence proliferative activity (32). A significant difference in Ki-67 expression across different sites necessitated subgroup analysis, revealing Ki-67 as a prognostic biomarker only in OSCC. Because of this, we additionally constructed a separate nomogram for OSCC, demonstrating a prognostic model for containing Ki-67 expression. The prognostic significance of Ki-67 expression in OPSCC, HPSCC, and LSCC was not established, highlighting the need for further research, particularly due to sample size constraints.

Previous studies on Ki-67 expression in HNSCC have employed various cut-off values, including ROC curve-derived values (33), medians (13), quartiles (34), and data distribution-based values (17). Our study utilized both the median and ROC-derived optimal cut-off values, finding the latter to offer more significant prognostic variance. In calculating the cut-off value via the ROC curve, we analyzed a substantial cohort to establish this threshold. In future research, it is imperative to undertake prospective studies to affirm the prognostic significance of Ki-67 expression and to address pivotal concerns, including the determination of cut-off values. Various methodologies for quantifying Ki-67 expression, such as positive cell and area ratios, underscore the need for standardized assessment procedures. The lack of standardization, as highlighted in breast cancer studies (35, 36), calls for the establishment of consistent protocols for Ki-67 assessment in HNSCC.

In summary, this research encompassed a comprehensive analysis of 764 patients hospitalized from 2012 to 2022. It meticulously investigated the correlation between Ki-67 expression and a spectrum of clinicopathological characteristics in HNSCC. Our survival analysis unequivocally established Ki-67 as a negative prognostic biomarker for HNSCC. We developed a nomogram as a prognostic prediction model, integrating Ki-67 expression, which promises to contribute significantly to future clinical practice. However, it is crucial to acknowledge the inherent heterogeneity of head and neck tumors, underscoring the need for further validation of our findings in specific sites such as the oropharynx, hypopharynx, and larynx. Future research directions should focus on refining methodologies, including Ki-67 counting techniques, antigen retrieval processes, and determining the optimal cut-off value for Ki-67 expression. The ultimate goal is to establish a standardized and universally applicable procedure for assessing Ki-67 in HNSCC, thereby enhancing the accuracy and reliability of prognostic predictions in clinical settings.

The raw data supporting the conclusions of this article will be made available by the authors, without undue reservation.

The studies involving humans were approved by West China Hospital of Stomatology Institutional Review Board. The studies were conducted in accordance with the local legislation and institutional requirements. The participants provided their written informed consent to participate in this study.

TW: Conceptualization, Data curation, Formal analysis, Investigation, Methodology, Visualization, Writing – original draft, Writing – review & editing. LX: Data curation, Formal analysis, Investigation, Visualization, Writing – review & editing. ZL: Data curation, Formal analysis, Investigation, Writing – review & editing. ZH: Data curation, Investigation, Writing – review & editing. NH: Data curation, Investigation, Writing – review & editing. YL: Methodology, Supervision, Validation, Writing – review & editing. BY: Conceptualization, Formal analysis, Investigation, Methodology, Project administration, Supervision, Writing – review & editing.