1. Introduction
Cancer is a significant global health challenge in the 21st century, with 19.3 million new cases in 2020 and projections that one in five will develop it in their lifetime [1,2]. Within this broader context, lip and oral cavity cancers constitute a particular concern, ranking as the 16th most common neoplasm worldwide, with 377,713 new cases and 177,757 deaths reported in 2020 [2,3,4]. Together with oropharyngeal cancer, these malignancies account for 476,125 new cases annually, representing 2.5% of all cancers and resulting in 225,900 deaths globally [5].
Lip cancer specifically accounts for 25–30% of oral cavity malignancies [4,6,7,8,9] and presents unique epidemiological patterns that distinguish it from other oral cancers. The disease demonstrates clear demographic preferences, predominantly affecting males (ratios 2.8:1 to 4.5:1) and typically presenting in the seventh decade of life [4,5,10]. These patterns show notable geographic and racial variations [3], suggesting complex interactions between genetic, environmental, and social factors [11].
The etiology of lip cancer remains an area of active investigation. While ultraviolet (UV) radiation represents a well-established primary risk factor [12,13], particularly affecting outdoor workers and rural residents [3], controversy exists regarding the relative contributions of other factors such as tobacco use, alcohol consumption, and socioeconomic conditions [4]. Recent evidence indicates that tobacco and alcohol use act synergistically to increase cancer risk, particularly when combined with occupational exposures [14]. Sociodemographic factors, including educational level and marital status, may independently influence outcomes [11], challenging traditional purely biological models of disease progression.
Prognosis varies significantly by cancer subtype and stage at diagnosis. Despite a generally favorable prognosis (5-year survival rates 66.3–86.5%) [5,10], partly due to low cervical node metastatic rates of 2–5% [4], significant outcome disparities persist. While the early-stage disease (83.3% of cases) typically responds well to treatment [5], the advanced disease (stage III/IV) carries substantially worse outcomes [15], with 5-year overall survival rates of 40–70% [4]. This disparity has sparked debate about optimal screening strategies and treatment approaches, particularly in regions with limited healthcare resources.
Treatment approaches for lip cancer continue to evolve, although surgical resection remains the gold standard [5]. Recent predictive models incorporating multiple clinical variables (tumor depth, nodal status, and perineural invasion) have enhanced prognostication, though validation across diverse populations remains incomplete [11]. Among oral cavity malignancies, lip cancers demonstrate the most favorable outcomes [16], allowing for conservative surgical margins of 0.5–1 cm [17].
Northeastern Brazil, particularly the state of Rio Grande do Norte, provides a distinct environment for studying lip cancer due to its high year-round ultraviolet (UV) radiation exposure, predominantly rural population, and socioeconomic disparities. The region’s unique demographic composition, with a higher proportion of brown-skinned individuals compared to other parts of Brazil, may influence disease incidence and survival outcomes. National cancer statistics indicate that oral cavity cancers account for 8.38% of all cancers in the region, with an estimated incidence rate of 8.35 per 100,000 men and 3.87 per 100,000 women [18].
Compared to developed regions, where early detection and treatment contribute to favorable outcomes, northeastern Brazil faces systemic barriers to healthcare access, leading to delayed diagnosis and higher proportions of advanced-stage disease. Moreover, limited public health initiatives targeting high-risk populations, such as outdoor workers and individuals with low educational attainment, exacerbate the regional burden [18]. Understanding the epidemiological and clinical patterns of lip cancer in this context is critical for developing targeted screening programs, improving early detection, and tailoring treatment protocols to the region’s specific needs.
This study focuses on northeastern Brazil, a region uniquely impacted by high UV radiation exposure, a predominantly rural workforce, and significant healthcare access disparities. By analyzing the survival patterns and risk factors specific to this region, the findings aim to inform tailored public health policies and interventions, addressing the unmet needs of this vulnerable population and serving as a model for similar settings worldwide.
Therefore, this study aims to analyze the epidemiological profile, clinicopathological characteristics, and survival outcomes of 348 lip cancer patients treated at Liga Norte Riograndense Contra o Câncer (LNRCC) over 15 years. Our findings revealed significant associations between disease stage and survival, as well as unique racial outcome patterns that challenge current risk models. These insights should inform the development of targeted screening programs for oral health and treatment protocols specific to northeastern Brazil’s population, consequently improving early detection and patient outcomes and enhancing the quality of life.
2. Materials and Methods
2.1. Ethical Considerations
This retrospective observational study was conducted in accordance with Resolution 466/12 of the Brazilian National Health Council (Conselho Nacional de Saúde—CNS) regarding human subjects’ research. The study protocol was reviewed and approved by the Ethics Committee of Liga Norte Riograndense Contra o Câncer (approval number 1,406,994/2016).
2.2. Study Design
A retrospective prognostic study was conducted through analysis of individual patient data from the Liga Norte Riograndense Contra o Câncer (LNRCC) database, Natal/RN. The observational nature of the study involved the documentation of findings without intervention in patient treatment or care.
2.3. Study Population and Selection Criteria
The study population was identified through a systematic review of medical records at LNRCC over 15 years (between January 2002 and December 2016). Eligible patients were those diagnosed with histopathologically confirmed lip squamous cell carcinoma (LSCC) with a minimum of five years of potential follow-up time. From the initial database review, cases were excluded if they met any of the following criteria: (1) medical records containing less than 10% of relevant clinical information (defined as missing three or more of the following: demographic data, tumor characteristics, treatment details, or follow-up information), (2) patients who did not receive any type of treatment, (3) patients with synchronous primary tumors, (4) cases with incomplete histopathological confirmation, or (5) patients who received initial treatment at other institutions. After applying these criteria, 348 patients were included in the final analysis, with complete clinical data available for 108 patients (31%). A detailed flow diagram is provided in Figure 1.
2.4. Data Collection and Staging
Data were extracted from both clinical records and electronic databases. The collected information included demographic data (sex, age, skin color, educational level, and occupation), risk factor exposure (tobacco use, alcohol consumption, and sun exposure), and clinical parameters. Clinical and pathological data included anatomic tumor location; the clinical staging was assigned to overall stages I through IV, according to the TNM classification system, 7th edition [19], which was the standard during most of the study period, and pathological staging (pTNM). For consistency in analysis, cases from 2002 to 2009 were retrospectively staged using the 7th edition criteria, though this represented a potential limitation of our study. However, changes between the 6th and 7th editions were minimal for lip cancer staging, making significant classification bias unlikely.
Histopathological grades (categorized as well, moderately, or poorly differentiated) were documented, along with all treatment modalities employed (surgery, radiotherapy, chemotherapy, and their combinations) and additional prognostic factors noted during the study period.
2.5. Statistical Analysis and Missing Data Management
Statistical analyses were performed using STATA/IC version 12.0 (StataCorp, College Station, TX, USA) and IBM SPSS Statistics version 22.0 (IBM Corp., Armonk, NY, USA). Initial data assessments revealed complete clinical information for 108 patients (31% of the cohort). Missing data patterns were analyzed using Little’s MCAR test to assess randomness.
The analytical approach began with descriptive statistics to characterize the study population and document the distribution of key variables. Continuous variables were expressed as mean ± standard deviation or median (interquartile range) based on distribution normality (assessed by the Shapiro–Wilk test). Categorical variables were presented as frequencies and percentages. Between-group comparisons used Student’s t-test or the Mann–Whitney U test for continuous variables and chi-square or Fisher’s exact test for categorical variables, as appropriate.
2.6. Survival Analysis
Overall survival (OS) and disease-free survival (DFS) were analyzed using the Kaplan–Meier method. Survival curves were compared between patient groups using log-rank tests, with statistical significance set at p < 0.05. Follow-up time was calculated from the date of diagnosis until death, loss to follow-up, or last contact. Prognostic factors were identified through univariate Cox regression analysis, calculating hazard ratios (HRs) with 95% confidence intervals for each variable of interest. To minimize bias from missing data, survival analyses were performed using both complete case analysis and multiple imputation approaches, with results compared for consistency.
2.7. Multivariate Analysis
Multivariate Cox regression analysis was conducted using a two-step approach. First, variables showing significance (p < 0.10) in univariate analysis were selected as candidates. These variables were then entered into the multivariate model using forward stepwise selection (entry criterion: p < 0.05; removal criterion: p > 0.10). The proportional hazards assumption was tested using Schoenfeld residuals and log-minus-log plots. Model fit was assessed using Cox–Snell residuals. Potential influential observations were identified using DFBETA statistics.
2.8. Association Analysis
Associations between categorical variables were evaluated using chi-square tests or Fisher’s exact test when expected cell frequencies were low (<5). Statistical significance was set at p < 0.05. The final multivariate model construction considered both statistical significance and clinical relevance, aiming to identify the most important prognostic factors while maintaining model parsimony.
3. Results
3.1. Population Characteristics
A total of 348 cases of lip squamous cell carcinoma were identified in the LNRCC database from 2002 to 2016. As shown in Table 1, the study population exhibited a male predominance (70.4%, n = 245) with a male-to-female ratio of 2.4:1. The mean age was 65.51 years (SD = 15.87), with 63.5% of patients aged over 60 years. The majority of patients were brown-skinned (64.1%, n = 223), illiterate (37.9%, n = 132), and resided in the eastern region of the state (33.3%, n = 343).
3.2. Risk Factor Profile
Among documented risk factors, tobacco use was reported by 42.0% (n = 146) of patients, while 16.1% (n = 56) reported alcohol consumption. Combined tobacco and alcohol use was observed in 14.9% (n = 52) of cases, while 21.3% (n = 74) reported no substance use. Occupational sun exposure was documented in 26.7% (n = 93) of patients, while 37.9% (n = 134) reported no direct occupational sun exposure (Table 1).
3.3. Tumor Characteristics
Lower lip involvement predominated, accounting for 89.1% (n = 310) of cases. Tumor size distribution among documented cases revealed the following: T1 tumors (≤2 cm) in 9.5% (n = 33), T2 tumors (2.0–4.0 cm) in 10.1% (n = 35), and T3/T4 tumors (>4.0 cm or invading adjacent structures) in 11.6% (n = 40) of cases. The majority of tumors (82.8%) exhibited moderate differentiation. Cervical lymph node metastasis was present in 11.8% (n = 41) of cases, and distant metastasis was documented in 0.6% (n = 2) of patients (Table 2).
3.4. Disease Staging
Clinical staging (TNM) distribution among documented cases showed Stage I (25.7%), Stage II (23.9%), Stage III (21.1%), and Stage IV (29.4%). As presented in Table 2, similar distributions were observed in pathological staging (pTNM): Stage I (24.8%), Stage II (23.9%), Stage III (19.3%), and Stage IV (32.1%). Notable was the high proportion of missing staging data (69.0%).
3.5. Treatment Outcomes
Surgical intervention was the primary treatment modality, performed in 97.7% (n = 340) of patients, either alone or in combination with other therapies. Complete disease remission was achieved in 80.7% (n = 281) of patients. Multiple primary tumors were documented in 20.7% (n = 72) of cases. The overall mortality rate was 10.1% (n = 35) (Table 3).
3.6. Survival Analysis
As illustrated in Figure 2 and detailed in Table 4, the five-year overall survival rate was 88.90%, with minimal gender difference (89.41% males vs. 87.73% females, p = 0.4359). Significant survival disparities were observed based on the following:
Race: Brown-skinned patients demonstrated better survival (91.05%) compared to white patients (80.09%) (p = 0.018).
Clinical stage: The early-stage disease showed superior survival (92.48% for stages I/II) compared to the advanced disease (57.15% for stages III/IV) (p = 0.0001).
Treatment modality: Single-modality treatment demonstrated better outcomes (95.35%) compared to multimodality treatment (58.31%) (p < 0.001). Disease-free survival was 98.77%, while patients who did not achieve complete remission showed significantly lower survival (22.41%).
3.7. Multivariate Analysis
The final multivariate model retained only race and clinical staging (TNM) as independent prognostic factors (p < 0.0001), highlighting these as essential determinants of survival outcomes in this population (Table 5).
4. Discussion
This study analyzes the epidemiological patterns, clinical characteristics, and survival outcomes of lip cancer in northeastern Brazil through a 15-year retrospective analysis. While our sample size (n = 348) and complete data availability for 108 patients represent limitations, several important observations emerge that contribute to our understanding of lip cancer in this geographic region.
4.1. Demographic and Epidemiological Patterns
The male predominance (70.4%) in our cohort aligns with global trends, though our male-to-female ratio (2.4:1) differs from larger international cohorts, reporting ratios of 4.5:1 [10] and 2.8:1 [5]. This difference might suggest regional differences in risk factor exposure or healthcare-seeking behavior. The relatively lower frequency among women could be attributed to greater healthcare awareness and preventive behaviors, such as regular use of lip protection like lipstick, supporting earlier findings [7,8].
The age distribution in our study revealed a mean age of 65.51 years, with 63.5% of patients over 60 years old, closely matching the reported mean age of 65 ± 13.5 years by Louredo et al. (2022) [5] and aligning with international patterns [4]. This consistent age pattern suggests cumulative effects of risk factors over time [20], with particular relevance to prognosis. Liu et al. (2021) [11] demonstrated that age independently predicts both overall survival (HR: 1.07; 95% CI, 1.07–1.08) and disease-specific survival (HR: 1.05; 95% CI, 1.03–1.06), establishing age as not merely a demographic factor but as an important prognostic indicator.
4.1.1. Racial Distribution and Survival Patterns
A striking finding emerged regarding racial patterns in lip cancer outcomes. The study revealed a higher proportion of cases among brown-skinned individuals (64.1%), who demonstrated significantly better survival (91.05%) compared to white patients (80.09%, p = 0.018). This finding notably contrasts with the previous reports that 98.4% of cases occurred in white patients [10]. The survival advantage in brown-skinned patients not only supports the protective effect of melanin against UV radiation [13] but also retained significance in multivariate analysis (HR: 2.25, p < 0.045), suggesting independent prognostic value beyond other clinical factors. This observation challenges traditional risk factor models focused primarily on UV radiation exposure [12] and suggests the need for population-specific risk assessment approaches.
4.1.2. Socioeconomic Determinants
Educational disparities emerged as another critical factor, with 33.9% of patients being illiterate. Although the lower survival rates among illiterate patients (84.90%) compared to literate patients (90.47%) did not reach statistical significance (p = 0.2252), these findings gain importance when contextualized with other study’s observation that 87.9% of lip cancer patients had low educational levels (≤8 years) [5]. These educational disparities likely contribute to delayed healthcare-seeking behavior [12]. The substantial proportion of patients with occupational sun exposure (26.7%) further aligns with studies linking socioeconomic conditions to outcomes [11] and highlights the complex interplay between social determinants and recognized environmental risk factors [3,21].
4.1.3. Statistical Power and Data Completeness
A critical consideration in interpreting our results is the availability of complete clinical data for 108 patients (31% of the cohort). Post hoc power analysis indicates that our study achieved an 80% power to detect hazard ratios ≥1.8 for major prognostic factors but may have been underpowered for detecting smaller effects or robust subgroup analyses. This limitation particularly affects our ability to draw definitive conclusions about treatment efficacy in specific patient subgroups.
4.2. Clinical and Pathological Characteristics
While limited by missing data, the analysis of the disease stage at presentation suggests patterns that warrant further investigation. Among cases with complete staging information (n = 108), we noticed the following.
4.2.1. Anatomical Distribution and Primary Site
The anatomical distribution in our cohort showed a marked predominance of lower lip involvement (89.1%), exceeding rates reported in previous studies by Louredo et al. (2022) [5] (79.4%) and Han et al. (2016) [10] (77.8%). While commissural lesions demonstrated the lowest survival rate (78.75%), the lack of statistical significance (p = 0.2896) may reflect the small proportion of such cases (2.9%) rather than true biological equivalence. The importance of primary site location is underscored by Liu et al. (2021) [11] finding that it independently predicts survival (HR: 1.08; 95% CI, 1.03–1.14), suggesting that site-specific outcomes warrant continued investigation.
4.2.2. Disease Stage and Progression
Our findings regarding the disease stage at presentation reveal concerning patterns that merit attention. The high proportion of the advanced disease—with 37.1% of cases presenting with tumors larger than 4 cm and 11.6% classified as T3/T4 tumors—contrasts markedly with data from developed regions where the early-stage disease comprises 83.3% of cases [5]. The strong association between advanced stages and poor survival (HR: 6.76, p < 0.0001) emphasizes the critical importance of early detection. These patterns align with observations of poorer prognosis in transitioning countries [3] and suggest significant regional variations in healthcare access or diagnostic capabilities.
4.2.3. Lymph Node Involvement
The cervical lymph node metastasis rate in our population (11.8%) falls within the expected range of 10–20% for mucosal lip SCCs [4]. This rate occupies an intermediate position between cutaneous lip cancer (2–5%) and other oral cavity cancers [4], reflecting the distinct biological behavior of mucosal lip malignancies. However, the high proportion of missing staging data (69.0%) necessitates a cautious interpretation of these findings and highlights the need for more complete documentation in future studies.
4.2.4. Disease Staging and Prognosis
Stage IV disease predominated in both clinical and pathological staging; a pattern that diverges significantly from the early-stage predominance typically seen in developed regions. This distribution suggests systemic barriers to early detection and treatment that require urgent attention [15]. The strong correlation between advanced stage and poor survival outcomes underscores the potential impact of addressing these barriers through enhanced screening and early detection programs [12].
4.3. Treatment Outcomes and Therapeutic Considerations
Our analysis of treatment outcomes provides insights into real-world clinical practice in our region. The predominance of surgical intervention (97.7%, n = 340) aligns with established treatment paradigms [5], yielding a complete remission rate of 80.7% and an overall mortality rate of 10.1%. While we observed significant survival differences between single-modality and multimodality treatment (95.35% vs. 58.31%, p < 0.001), these findings warrant careful interpretation within the context of contemporary predictive models that incorporate multiple clinical variables [11].
Detailed analysis of patients with complete treatment data (n = 108) revealed encouraging outcomes, including high surgical margin clearance rates (76.3% achieving >5 mm margins), acceptable complication rates (22.4% overall, 4.9% major complications), and a five-year overall survival rate of 88.90%. These results are comparable to those reported in larger series, suggesting that standard-of-care treatment protocols can achieve satisfactory outcomes even in resource-limited settings.
Although these conventional approaches demonstrate consistent efficacy, the therapeutic landscape of lip squamous cell carcinoma has witnessed significant evolution in recent years, extending beyond traditional surgical approaches [22]. A particularly promising development is immunotherapy, specifically checkpoint inhibitors targeting PD-1/PD-L1 pathways. Clinical trials of pembrolizumab and nivolumab have demonstrated encouraging outcomes in recurrent and metastatic cases [23,24]. Current research priorities include identifying predictive biomarkers and optimizing therapeutic sequences to enhance patient outcomes while preserving quality of life [25].
Surgical precision has notably improved through innovative techniques, including intraoperative margin assessment with fluorescence guidance and real-time pathology [26]. Complementing these advances, photodynamic therapy (PDT) has emerged as an effective treatment for precancerous lesions and early-stage head and neck squamous cell carcinoma (HNSCC), offering superior cosmetic results with minimal side effects [27]. The integration of advanced reconstruction methods, such as 3D-printed surgical guides and custom prostheses [28], has further enhanced treatment outcomes. However, the implementation of these therapeutic innovations must be carefully tailored to individual patient factors and healthcare resource availability.
4.4. Survival Analysis and Prognostic Factors
Our overall five-year survival rate of 88.90% falls within the range reported in the literature (66.3–86.5%) [5,10]. The counterintuitive finding of better survival among brown-skinned patients (91.05%) compared to white patients (80.09%, p = 0.018) warrants further investigation, particularly given the traditional association between skin pigmentation and UV-related cancer risk [12,13].
The survival difference between early and advanced stages (92.48% vs. 57.15%, p = 0.0001) aligns with previous studies showing substantially worse outcomes for the advanced disease [15]. This finding reinforces the importance of early detection strategies emphasized in the literature [29,30].
4.5. Regional Implications and Risk Factor Assessment
The state of Rio Grande do Norte, located in northeastern Brazil, provides a unique setting for studying lip cancer due to its high year-round ultraviolet (UV) radiation exposure and predominantly rural demographics. These geographic and socioeconomic factors contribute significantly to the incidence and outcomes of lip cancer in the region. Unlike urbanized areas of southeastern Brazil, where access to healthcare facilities and early-detection programs are more readily available, northeastern Brazil faces systemic barriers that exacerbate the burden of advanced-stage disease [12].
Rio Grande do Norte experiences some of the highest levels of UV radiation in Brazil, a major risk factor for lip squamous cell carcinoma, particularly among outdoor workers. The state’s economy is heavily reliant on agriculture, with a large proportion of the population engaged in outdoor labor. This occupational exposure to UV radiation, combined with limited access to sun protection measures and healthcare services, places these workers at a disproportionately high risk. In this study, 26.7% of patients reported occupational sun exposure, reflecting the occupational structure and climatic conditions of the region [12].
In comparison, southeastern states such as São Paulo and Rio de Janeiro have reported lower rates of occupational sun exposure among lip cancer patients, attributed to the predominance of urban professions and greater awareness of sun protection. Additionally, these regions benefit from a more robust healthcare infrastructure, enabling earlier diagnosis and treatment. National cancer registry data reveal that oral cavity cancers represent 8.38% of all malignancies in northeastern Brazil, compared to 6.25% in the Southeastern region, emphasizing the heightened vulnerability of the former [18].
The rural composition of northeastern Brazil further compounds these disparities. Many communities reside far from specialized healthcare centers, delaying access to diagnostics and treatment. In contrast, southeastern states are characterized by a dense network of healthcare facilities and specialized oncology services [12]. These geographic and systemic differences underscore the importance of region-specific public health policies and interventions to address the unique challenges faced by populations in northeastern Brazil.
The synergistic effects of tobacco and alcohol use with occupational exposures [14] highlight the importance of comprehensive risk factor assessment and modification. The unexpected racial survival patterns suggest the need for population-specific approaches to risk assessment and management, particularly in regions with diverse populations.
4.6. Targeted UV Protection Campaigns
Given the well-documented association between UV radiation and lip cancer, especially among outdoor workers, region-specific campaigns promoting sun protection are essential. Strategies should include the distribution of sun-protective gear, such as wide-brimmed hats and high-SPF sunscreens, particularly to agricultural and construction workers. Educational initiatives should emphasize the risks of prolonged sun exposure and the benefits of sun safety practices. Collaboration with employers to implement workplace policies that reduce peak-hour sun exposure and mandate the use of protective measures is also crucial. While these public health strategies are promising, their implementation in northeastern Brazil may face challenges such as limited funding for public health programs, logistical difficulties in reaching remote rural areas, and potential resistance to behavioral change among at-risk populations. Building partnerships with local governments, Non-Governmental Organizations (NGOs), and community leaders will be essential to address these barriers and ensure the long-term sustainability of these interventions.
4.7. Community Health Worker Programs
Training community health workers (CHWs) to identify early signs of lip lesions and provide education on preventive measures could significantly improve early detection rates. These workers, integrated into existing healthcare frameworks, could conduct routine skin checks in high-risk populations, particularly in rural and underserved areas. They could also facilitate access to diagnostic and treatment services through mobile health units or referrals to regional cancer centers while distributing informational materials and protective equipment to increase awareness and accessibility.
4.8. Occupational Health Interventions
Occupational sun exposure was identified in a significant portion of patients, underscoring the need for workplace-specific health interventions. Regional governments and industries employing outdoor workers should subsidize protective gear for low-income workers, introduce mandatory health and safety training on UV risks, and provide incentives for businesses adopting sun protection policies.
4.9. Screening and Early Detection Programs
Mobile screening units equipped to serve remote and rural communities could bridge gaps in healthcare access. These units could perform basic assessments and refer patients for further evaluation, aiming to identify early-stage lesions. Partnerships with local governments and NGOs would ensure sustainability and scalability.
4.10. Limitations and Future Directions
Our 15-year retrospective analysis from northeastern Brazil’s primary cancer treatment center provides important insights while acknowledging certain methodological constraints. As with any retrospective study, we encountered some incomplete medical records, particularly in staging data documentation. Our single-center design, while representing the major regional treatment facility, reflects the patterns and outcomes specific to our catchment area.
The extended study period (2002–2016) captured evolving treatment protocols, providing a comprehensive view of therapeutic trends but limiting direct period-to-period comparisons. While we documented traditional risk factors, a more detailed quantification of exposure variables would strengthen future investigations. Similarly, while our survival analyses yielded significant findings, standardized follow-up protocols would enhance future outcome assessments.
4.11. Clinical Implications and Future Directions
Our findings provide valuable insights into lip cancer patterns in northeastern Brazil, establishing an important baseline for understanding the interplay between socioeconomic factors, healthcare access, and clinical outcomes in our region. While acknowledging the limitations of our single-center retrospective design, these observations lay the groundwork for future investigations. Prospective multi-center studies incorporating standardized data collection, detailed risk factor quantification, and molecular profiling would build upon our findings. Additionally, an investigation into targeted screening programs and population-specific risk assessment tools could enhance early detection strategies in similar healthcare settings [29,30].
Integrating these findings into national and regional cancer control plans could guide resource allocation and program development. Policymakers should prioritize funding for public health campaigns tailored to the region’s demographic and socioeconomic profile. They should also support research on local risk factors and their interactions with genetic predispositions and expand healthcare infrastructure to facilitate timely access to diagnostics and treatment.
5. Conclusions
This retrospective analysis of 348 lip squamous cell carcinoma cases, including 108 with complete clinical data, offers insights into disease patterns in northeastern Brazil while acknowledging sample size limitations. Our findings suggest that current treatment approaches can achieve survival rates comparable to international standards despite resource constraints. The study revealed potential prognostic indicators, particularly noting an unexpected correlation between race and survival that warrants further investigation in larger, multi-center studies.
These results, while preliminary, contribute to our understanding of lip cancer in resource-limited settings and may help guide future investigations aimed at improving patient outcomes in similar contexts.
Our findings underscore the urgent need for region-specific public health strategies in northeastern Brazil, where environmental and socioeconomic factors converge to exacerbate the burden of lip cancer. By highlighting the unique challenges faced by this region, this study provides critical insights that can guide the development of targeted prevention, early detection, and treatment programs, ultimately improving health outcomes and reducing disparities in similar underserved populations.
Author Contributions
Conceptualization, G.C.B.F., S.I.M.L.Q. and B.C.d.V.G.; methodology, B.C.d.V.G.; software, L.E.R.J.; validation, C.F.M. and B.C.d.V.G.; formal analysis, S.I.M.L.Q. and G.C.B.F.; investigation, G.C.B.F.; resources, G.C.B.F.; data curation, G.C.B.F. and S.I.M.L.Q.; writing—original draft preparation, G.C.B.F.; writing—review and editing, L.E.R.J., R.D.A.U.L. and C.F.M.; visualization, L.E.R.J. and C.F.M.; supervision, C.F.M. and B.C.d.V.G.; project administration, B.C.d.V.G. All authors have read and agreed to the published version of the manuscript.
Funding
This research received no external funding.
Institutional Review Board Statement
The study was approved by the Ethics Committee of Liga Norte Riograndense Contra o Câncer (approval number 1,406,994/2016) in accordance with Resolution 466/12 of the Brazilian National Health Council (CNS) regarding research involving human subjects.
Informed Consent Statement
Patient consent was waived due to the retrospective nature of the study involving only analysis of existing medical records and database information, with no direct patient contact or intervention.
Data Availability Statement
The data supporting this study’s findings are available from the corresponding author upon reasonable request.
Conflicts of Interest
The authors declare no conflicts of interest.
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Figure 1. STROBE flow diagram of the study.
Figure 1. STROBE flow diagram of the study.
Figure 2. Kaplan–Meier survival curves for lip squamous cell carcinoma patients treated at Liga Norte Riograndense Contra o Câncer, Natal-RN, Brazil (2002–2016). The graph demonstrates significant survival disparities based on clinical stage and race. Early-stage disease (I/II) showed superior 5-year survival (92.48%) compared to advanced stages (III/IV) (57.15%) (HR = 6.76; 95% CI: 2.31–19.78; p < 0.0001). Brown-skinned patients demonstrated better survival (91.05%) compared to white patients (80.09%) (HR = 2.25; 95% CI: 1.02–4.98; p = 0.045). These factors remained significant in multivariate analysis, suggesting their independent prognostic value. The divergence of curves indicates early separation of risk groups, with differences maintaining significance throughout the follow-up period. The overall 5-year survival rate was 88.90%.
Figure 2. Kaplan–Meier survival curves for lip squamous cell carcinoma patients treated at Liga Norte Riograndense Contra o Câncer, Natal-RN, Brazil (2002–2016). The graph demonstrates significant survival disparities based on clinical stage and race. Early-stage disease (I/II) showed superior 5-year survival (92.48%) compared to advanced stages (III/IV) (57.15%) (HR = 6.76; 95% CI: 2.31–19.78; p < 0.0001). Brown-skinned patients demonstrated better survival (91.05%) compared to white patients (80.09%) (HR = 2.25; 95% CI: 1.02–4.98; p = 0.045). These factors remained significant in multivariate analysis, suggesting their independent prognostic value. The divergence of curves indicates early separation of risk groups, with differences maintaining significance throughout the follow-up period. The overall 5-year survival rate was 88.90%.
Table 1. Sociodemographic and clinical characteristics of lip cancer patients in Natal, RN, Brazil (2002–2016).
Table 1. Sociodemographic and clinical characteristics of lip cancer patients in Natal, RN, Brazil (2002–2016).
Characteristics | n = 348 | % |
---|---|---|
Sociodemographic Profile | ||
Sex | ||
Male | 245 | 70.4 |
Female | 103 | 29.6 |
Age (years) | ||
≤60 years | 127 | 36.5 |
>60 years | 221 | 63.5 |
Mean ± SD | 65.51 ± 15.87 | - |
Race/Skin Color | ||
Brown | 223 | 64.1 |
White | 125 | 35.9 |
Education Level | ||
Illiterate | 132 | 37.9 |
Primary education | 156 | 44.8 |
Secondary education | 48 | 13.8 |
Higher education | 12 | 3.5 |
Occupation | ||
Agricultural worker | 124 | 35.6 |
Construction worker | 52 | 14.9 |
Other outdoor work | 67 | 19.3 |
Indoor work | 105 | 30.2 |
Geographic distribution | ||
Urban area | 185 | 53.2 |
Rural area | 125 | 35.9 |
Coastal area | 38 | 10.9 |
Risk Factors | ||
Tobacco Use | 146 | 42.0 |
Never smoked | 150 | 43.1 |
Current smoker | 146 | 42.0 |
Former smoker | 52 | 14.9 |
Duration of Tobacco Use | ||
<20 years | 42 | 21.2 |
20–40 years | 98 | 49.5 |
>40 years | 58 | 29.3 |
Alcohol Consumption | ||
Never | 240 | 69.0 |
Current | 56 | 16.1 |
Former | 52 | 14.9 |
Combined Tobacco and Alcohol | 52 | 14.9 |
Sun Exposure | ||
Occupational Exposure | ||
No direct exposure | 134 | 37.9 |
<4 h/day | 45 | 12.9 |
4–8 h/day | 121 | 34.8 |
Sun Protection Use | ||
Regular use | 58 | 16.7 |
Irregular use | 127 | 36.5 |
Never | 163 | 46.8 |
Notes: Education levels were categorized as follows: illiterate (no formal education); primary education (1–8 years of schooling); secondary education (9–12 years of schooling); higher education (>12 years of schooling). Occupational sun exposure was documented through detailed occupational history and validated through employment records where available. Duration of tobacco use was calculated from the patient-reported age of initiation to the age of cessation or current age for active smokers. Geographic distribution was determined based on the residential address at the time of diagnosis. Source: Database of Liga Norte Riograndense Contra o Câncer, 2017.
Table 2. Clinical and histopathological characteristics of lip cancer cases (n = 348).
Table 2. Clinical and histopathological characteristics of lip cancer cases (n = 348).
Characteristics | n | % | Valid % * |
---|---|---|---|
Tumor Location | |||
Lower Lip | 310 | 89.1 | 89.1 |
Upper Lip | 28 | 8.0 | 8.0 |
Labial Commissure | 10 | 2.9 | 2.9 |
Tumor Size | |||
≤2 cm (T1) | 33 | 9.5 | 30.6 |
2.1–4.0 cm (T2) | 35 | 10.1 | 32.4 |
>4.0 cm (T3/T4) | 40 | 11.6 | 37.1 |
Missing data | 240 | 69.0 | - |
Disease Extent | |||
Lymph Node Status | |||
N0 | 265 | 76.1 | 86.6 |
N1 | 28 | 8.0 | 9.2 |
N2 | 11 | 3.2 | 3.6 |
N3 | 2 | 0.6 | 0.7 |
Missing data | 42 | 12.1 | - |
Distant Metastasis | |||
M0 | 346 | 99.4 | 99.4 |
M1 | 2 | 0.6 | 0.6 |
Clinical Staging (TNM) | |||
Stage I | 28 | 8.0 | 25.7 |
Stage II | 26 | 7.5 | 23.9 |
Stage III | 23 | 6.6 | 21.1 |
Stage IV | 32 | 9.2 | 29.4 |
Missing data | 240 | 69.0 | - |
Histological Differentiation | |||
Well-differentiated | 20 | 5.7 | 6.3 |
Moderately differentiated | 288 | 82.8 | 90.6 |
Poorly differentiated | 10 | 2.9 | 3.1 |
Missing data | 30 | 8.6 | - |
Surgical Margins | |||
Negative (>5 mm) | 238 | 68.4 | 76.3 |
Close (1–5 mm) | 58 | 16.7 | 18.6 |
Positive (<1 mm) | 16 | 4.6 | 5.1 |
Missing data | 36 | 10.3 | - |
Treatment Modality | |||
Surgery alone | 280 | 80.5 | 80.5 |
Surgery and radiotherapy | 42 | 12.1 | 12.1 |
Surgery and chemoradiation | 15 | 4.3 | 4.3 |
Surgery and chemotherapy | 3 | 0.9 | 0.9 |
Primary radiotherapy | 3 | 0.9 | 0.9 |
Primary chemoradiation | 3 | 0.9 | 0.9 |
Palliative care | 2 | 0.6 | 0.6 |
* Valid percentages exclude missing data. Notes: TNM staging was performed according to AJCC 7th edition criteria. Tumor size measurements were based on clinical examination and imaging findings, with pathological correlation where available. Surgical margins were assessed by frozen section and confirmed by permanent histopathology. Treatment modality selection was based on multidisciplinary tumor board decisions considering patient factors, tumor characteristics, and available resources.
Table 3. Treatment outcomes and follow-up data of lip cancer cases (n = 348).
Table 3. Treatment outcomes and follow-up data of lip cancer cases (n = 348).
Treatment Characteristics and Outcomes | n | % | Valid % * |
---|---|---|---|
Primary Treatment Modality | |||
Surgery alone | 280 | 80.5 | 80.5 |
Surgery and radiotherapy | 42 | 12.1 | 12.1 |
Surgery and chemoradiation | 15 | 4.3 | 4.3 |
Surgery and chemotherapy | 3 | 0.9 | 0.9 |
Primary radiotherapy | 3 | 0.9 | 0.9 |
Primary chemoradiation | 3 | 0.9 | 0.9 |
Palliative care | 2 | 0.6 | 0.6 |
Surgical Margins (n = 312) | |||
Negative (>5 mm) | 238 | 68.4 | 76.3 |
Close (1–5 mm) | 58 | 16.7 | 18.6 |
Positive (<1 mm) | 16 | 4.6 | 5.1 |
Missing data | 36 | 10.3 | - |
Reconstruction Method (n = 340) | |||
Primary closure | 232 | 66.7 | 68.2 |
Local flaps | 84 | 24.1 | 24.7 |
Regional flaps | 20 | 5.7 | 5.9 |
Free flaps | 4 | 1.1 | 1.2 |
Treatment Response | |||
Complete remission | 281 | 80.7 | 80.7 |
Partial response | 42 | 12.1 | 12.1 |
Stable disease | 15 | 4.3 | 4.3 |
Progressive disease | 10 | 2.9 | 2.9 |
Disease Recurrence | |||
Local recurrence | 32 | 9.2 | 9.2 |
Regional recurrence | 16 | 4.6 | 4.6 |
Distant metastasis | 7 | 2.0 | 2.0 |
No recurrence | 293 | 84.2 | 84.2 |
Multiple Primary Tumors | |||
In lip region | 46 | 13.2 | 13.2 |
Other head and neck sites | 20 | 5.7 | 5.7 |
Distant sites | 6 | 1.7 | 1.7 |
None | 276 | 79.3 | 79.3 |
Complications | |||
Minor (Grade I-II) | 61 | 17.5 | 17.5 |
Major (Grade III-IV) | 17 | 4.9 | 4.9 |
None | 270 | 77.6 | 77.6 |
Mortality | |||
Disease-specific | 22 | 6.3 | 6.3 |
Treatment-related | 3 | 0.9 | 0.9 |
Other causes | 10 | 2.9 | 2.9 |
Alive | 313 | 89.9 | 89.9 |
Follow-up Status | |||
Complete follow-up | 266 | 76.4 | 76.4 |
Partial follow-up | 55 | 15.8 | 15.8 |
Lost to follow-up | 27 | 7.8 | 7.8 |
Median follow-up time (months) | 58.3 (range: 6–180) | - | - |
* Valid percentages exclude missing data. Notes: Complete follow-up was defined as regular attendance at scheduled appointments until death or study end date. Partial follow-up was defined as irregular attendance at scheduled appointments. Lost to follow-up was defined as no contact for more than 12 months. The median follow-up time was calculated from the date of diagnosis to the last recorded contact or death.
Table 4. Survival analysis by key prognostic factors (5-year follow-up).
Table 4. Survival analysis by key prognostic factors (5-year follow-up).
Factor | n | 5-Year Survival % (95% CI) | HR | 95% CI | p-Value |
---|---|---|---|---|---|
Clinical Stage | |||||
Stage I/II † | 54 | 92.48 (81.17–97.11) | 1.0 | † | 0.0001 |
Stage III/IV | 55 | 57.15 (42.24–69.55) | 6.44 | 2.21–18.71 | |
Race | |||||
Brown † | 223 | 91.05 (86.05–94.32) | 1.0 | † | 0.018 |
White | 125 | 80.09 (68.63–87.72) | 2.23 | 1.12–4.43 | |
Treatment Modality | |||||
Single modality † | 281 | 95.35 (92.12–97.28) | 1.0 | † | <0.001 |
Multiple modalities | 67 | 58.31 (43.45–70.53) | 9.46 | 4.76–18.79 |
HR: Hazard ratio; CI: confidence interval. † Reference category: In survival analysis, the reference category serves as the baseline group for comparison. A hazard ratio of 1.0 is assigned to the reference category, and the hazard ratios for other categories indicate their relative risk compared to this baseline group. Reference categories were selected based on better prognosis and larger sample size.
Table 5. Multivariate analysis of independent prognostic factors.
Table 5. Multivariate analysis of independent prognostic factors.
Variable | Category | HR Adjusted | 95% CI | p-Value |
---|---|---|---|---|
Clinical Stage | Stage I/II † | 1.0 | † | <0.0001 |
Stage III/IV | 6.76 | 2.31–19.78 | ||
Race | Brown † | 1.0 | † | 0.045 |
White | 2.25 | 1.02–4.98 |
HR: Hazard ratio; CI: confidence interval. † Reference category: In the multivariate Cox regression model, reference categories were selected as the groups with better survival outcomes (Stage I/II and Brown race). The hazard ratio of 1.0 represents the baseline risk, and adjusted hazard ratios for other categories represent their independent effect on survival after controlling for other variables in the model.
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