Gender disparities in the overall survival of patients with minimally invasive squamous cell carcinoma of the lung: a retrospective analysis of the Surveillance, Epidemiology, and End Results Program database

Introduction

The 2022 survey by the International Agency for Research on Cancer (IARC) identified lung cancer as the most common and deadliest cancer globally (1). Lung cancer is histologically categorized into subtypes including adenocarcinoma, squamous cell carcinoma, large cell carcinoma, and small cell carcinoma, among which adenocarcinoma and squamous cell carcinoma have the highest incidence rates. Lung squamous cell carcinoma (LUSC) is associated with a poorer overall survival (OS) compared to lung adenocarcinoma (LUAD) (2,3).

Prognostic differences between LUAD and LUSC stem from factors such as tumor location, molecular biology, and precision medicine. LUSC often develops centrally and spreads multifocally along the bronchial submucosa, leading to a poorer OS as compared to LUAD. Meanwhile, LUAD presents a greater number of therapeutic targets due to identifiable molecular markers. In contrast, LUSC has a lower mutation frequency in effective targets such as EGFR, ALK, and ROS1 but higher mutation rates in challenging targets such as TP53 and CDKN2A (4,5). The genetic mutations in most patients with LUSC remain unidentified, hindering advancements in targeted therapies and limiting treatment options (6,7). Moreover, the tumor microenvironments (TME) of these cancer types differ significantly (8,9). Consequently, some researchers have proposed eliminating the non-small cell lung cancer (NSCLC) classification to foster innovation in lung cancer therapies (10).

The refined classification of LUAD significantly enhances treatment precision, and patients with LUAD can thus expect a better prognosis compared to those with LUSC. According to the 2011 multidisciplinary classification by the International Association for the Study of Lung Cancer (IASLC), the American Thoracic Society (ATS), and the European Respiratory Society (ERS), lung minimally invasive adenocarcinoma (MIA) is defined as a tumor with a maximum diameter of ≤3 cm, an invasive focus within the lesion of ≤5 mm, and no pleural, vascular, or lymphatic invasion (11). The 2015 World Health Organization (WHO) classification further clarified this by introducing the term “MIA”, distinguishing it as an intermediate stage between adenocarcinoma in situ (AIS) and invasive adenocarcinoma (12). MIA and AIS exhibit similar biological behaviors, both classified as early-stage lung cancers with no distant metastasis. Their low risk of recurrence beyond 5 years postsurgery differentiates them from other LUAD types (13). This precise definition has refined treatment strategies, allowing MIA, similarly to AIS, to be effectively treated with sublobar resection without the need for adjuvant therapy following complete resection. There has been no notable difference observed in the long-term recurrence-free survival rates or the risk of a second primary lung cancer after surgery between patients with MIA and those with AIS (14,15). Sublobar resection, particularly wedge resection, minimizes the damage associated with traditional lobectomy and lymph node dissection, preserving lung function and reducing complications (15,16). However, MIA, with its deeper tissue invasion, poses a higher risk of progression to invasive cancer than does AIS. Therefore, those with MIA require careful evaluation of the surgical scope and diligent postoperative follow-up.

In LUSC, a specific subtype such as “minimally invasive LUSC” has not been established between carcinoma in situ and invasive carcinoma. The latest WHO classification of lung tumors maintains a binary framework, distinguishing between LUSC in situ and invasive LUSC: once high-grade squamous intraepithelial lesions penetrate the basement membrane, they are classified as invasive carcinoma without intermediate stratification (7). This classification persists due to the distinct biological behavior of LUSC compared to LUAD. Unlike the lepidic growth pattern of LUAD, LUSC exhibits a “pushing-type”, solid mass invasion after breaching the basement membrane. This invasion is characterized by significant fibrous stromal reaction, keratin pearl formation, and focal necrosis (17). The absence of measurable invasive components complicates the identification of a reproducible indicator, such as an invasion depth ≤5 mm used in LUAD. Moreover, imaging-pathology correlation studies have revealed that even in pure-solid LUSC measuring ≤2 cm, there is a relatively high incidence of vascular invasion, vessel penetration, and lymph node metastasis. This indicates a higher invasiveness compared to LUAD of the same size, suggesting a “biological early jump” phenomenon. Consequently, capturing the microinvasive window pathologically is challenging, and clinically, these tumors do not benefit from the “subcentimeter means low-risk” advantage seen in adenocarcinoma (18). Despite these challenges, the concept of minimally invasive squamous cell carcinoma has being proposed in other tumors, such as cervical, skin, anus, and oral cancers, where it is associated with a relatively good prognosis (19-24). This suggests that introducing the concept of minimal invasion to LUSC is warranted.

For patients with early-stage LUSC, radical surgery remains the primary treatment, whereas advanced-stage cases typically require immunotherapy, chemotherapy, or a combination of both. Establishing a definition for minimal invasion in LUSC, akin to that in LUAD, could allow identification of a low-invasive group through use of combined imaging-pathology criteria. This would enable these patients to avoid the adverse effects of lobectomy, lymph node dissection, and adjuvant radiotherapy and chemotherapy. Consequently, surgical, radiochemotherapy, and immunological resources could be better allocated to high-risk patients, and the precision and clarity of treatment strategies for patients with LUSC could be enhanced. Therefore, in addition to advancing drug research and development, refining LUSC subtypes is crucial for minimizing damage from surgical and adjuvant therapy and improving patient prognosis. The lack of a “minimally invasive LUSC” concept currently hinders precise treatment efforts, and thus further refinement of the pathological diagnosis of LUSC is urgently needed to address this deficiency.

In our study, LUSC meeting the criteria of T1mi in SEER database were provisionally classified as “minimally invasive LUSC”. Analyzing collected data, we examined how various factors, including gender, affect the OS of patients with this lung cancer subtype. Additionally, we developed a survival prediction model to identify other factors that might be integral to defining minimally invasive LUSC and thus further refined the concept. We present this article in accordance with the TRIPOD reporting checklist (available at https://tlcr.amegroups.com/article/view/10.21037/tlcr-2026-0252/rc).

Methods

Data sources

The Surveillance, Epidemiology, and End Results Program (SEER) database (https://www.cancer.gov), overseen by the National Cancer Institute (NCI) of the United States, is a comprehensive cancer statistics project. Since 1973, it has gathered essential demographic data (age, gender, and race/ethnicity) on various cancer populations, along with information on cancer diagnosis dates, types, locations, treatment stages (surgery, radiotherapy, and chemotherapy), survival time, outcomes, and other clinical and pathological characteristics. This retrospective study utilized data from the SEER database, focusing on 654 patients diagnosed with minimally invasive LUSC between January 2018 and December 2020. The flowchart of data acquisition was shown in Figure 1. The study spanned 17 US states, accounting for 26.5% of the national population as per the 2020 census. The regions included the San Francisco-Oakland-Berkeley, CA Metropolitan Statistical Area, Connecticut, Hawaii, Iowa, New Mexico, Seattle (Puget Sound), Utah, metropolitan Atlanta, San Jose-Monterey, Los Angeles, Alaska Natives, and parts of Georgia, along with the rural areas of California, Kentucky, Louisiana, New Jersey, and Georgia. We analyzed 15 features: survival months (from lung cancer diagnosis), vital status, sex, age, year of diagnosis, race, origin, laterality, primary site, stage, total number of malignant tumors, clinical grade, radiation, chemotherapy, and systemic treatment and surgical sequence. This study was conducted in accordance with the Declaration of Helsinki and its subsequent amendments.

Figure 1 Flowchart of data acquisition. SEER, Surveillance, Epidemiology, and End Results Program; WHO, World Health Organization.

Statistical analysis

Statistical analyses were performed with SPSS version 25.0 (IBM Corp., Armonk, NY, USA) and R version 4.2.0 (The R Foundation for Statistical Computing, Vienna, Austria), with additional computations supported by EmpowerStats (X&Y Solutions Inc., Boston, MA, USA). Data visualization was performed with GraphPad Prism 9.0 (Dotmatics, Boston, MA, USA).

Continuous variables are presented as the mean ± standard deviation (SD), while categorical variables are presented as numbers and percentages. We employed the Fisher exact test or Pearson chi-squared test to compare baseline characteristics between groups. The log-rank (Mantel-Cox), Breslow (generalized Wilcoxon), and Tarone-Ware tests were employed to compare survival data distributions across groups.

Survival differences were analyzed via life tables, Kaplan-Meier estimates, univariate analysis, and stratified multivariate analysis. We conducted stratified multivariate analysis with various adjustment models, using sequence number as the exposure variable, with Model I being unadjusted. Model II was adjusted for variables including age, race, and diagnosis year. Model III was adjusted for variables including age, race, diagnosis year, origin, laterality, primary site, stage, clinical grade, total malignant tumors, radiation, chemotherapy, and systemic treatment and surgical sequence. The limited number of cases in certain categories led to missing values for some results. We created a survival prediction model using receiver operating characteristic (ROC) curve analysis. A P value of less than 0.05 was considered to indicate statistical significance.

Results

Survival curves of the different patient groups

The maximum follow-up period was 35 months. Over this period, 426 (65.14%) patients survived and 228 (34.86%) died. Figure 2A presents the OS curve for minimally invasive LUSC. Figure 2B presents a comparison of survival by gender and shows higher survival rates for females as compared to males. Figure 2C indicates that patients aged 60–69 years had the longest survival, while those over 80 years had the poorest outcomes. Figure 2D displays that survival differs markedly by race, being relatively favorable among the White but poor among the Asian or Pacific islander. Figure S1 presents additional stratified survival curves categorized by year of diagnosis, origin, laterality, primary site, stage, total number of malignant tumors, clinical grade, chemotherapy, systemic treatment and surgical sequence, and radiation.

Figure 2 Kaplan-Meier curve for the overall cohort and individual groups. LUSC, lung squamous cell carcinoma.

Baseline characteristics of participants and Kaplan-Meier curves of the different groups

To determine whether sex influences OS in patients with minimally invasive LUSC, we stratified patients into male (n=374, 57.19%) and female (n=280, 42.81%) groups. Table 1 summarizes the baseline data of the patients. Over the follow-up, 229 males (61.23%) and 197 females (70.36%) were alive, while 145 (38.77%) and 83 (29.64%) died, respectively; this difference in survival outcomes was statistically significant (P=0.02). Mean survival was 14.62±10.72 months for males and 16.28±9.94 months for females, which also represented a significant difference (P=0.03).

Univariate analysis results

Although male patients had a significantly shorter OS than did female patients when baseline characteristics were comparable according to the P value (P>0.05), multiple confounding factors could influence outcomes for minimally invasive LUSC. In addition to gender, studies have identified race, age, marital status, tumor grade, TNM stage, surgery, radiotherapy, and chemotherapy as independent predictors of survival in patients with LUSC (25,26). Tumor location is also significant; for instance, NSCLC centered in the main bronchi is associated with poorer survival, warranting heightened attention during diagnosis and treatment (27). Finally, advances in targeted therapies and immunotherapies implies that treatments—and thus prognoses—vary by year of diagnosis, making year of diagnosis an important determinant of survival.

Among various baseline characteristics, the standardized mean difference (SMD) of some data exceeds 0.1, indicating that the baseline data are not completely balanced. To minimize the effects of these potential confounders, we first performed univariate analyses, whose results are presented in Figure 3. Male patients had a hazard ratio (HR) of 1.44 [95% confidence interval (CI): 1.10–1.89; P=0.008]. With White patients serving as the reference, Asian or Pacific Islander patients had an HR of 1.83 (95% CI: 1.02–3.28; P=0.042). For laterality, with right-sided primary tumors serving as the reference, the group of other types of laterality had an HR of 6.83 (95% CI: 2.77–16.83; P<0.001). For primary site, with the upper lobe serving as the reference, tumors originating in the main bronchus had an HR of 4.58 (95% CI: 2.40–8.75; P<0.001), and the group of other types of primary site had an HR of 2.99 (95% CI: 1.57–5.70; P<0.001). For the stage groupings, with localized cancer serving as the reference, the distant metastasis group had an HR of 4.94 (95% CI: 3.63–6.73; P<0.001), and the regional metastasis group had an HR of 1.92 (95% CI: 1.35–2.72; P<0.001). Finally, with chemotherapy recipients serving as the reference, the nonchemotherapy or unknown group had an HR of 0.67 (95% CI: 0.50–0.90; P=0.008).

Figure 3 Univariate analysis of participants. (a), other races including Native American/Native Alaskan; (b), other laterality types including bilateral, single primary, nonpaired sites, and paired sites with unspecified laterality; (c), other types of primary site including overlapping lesion of the lung; (d), other radiation types including unspecified methods or sources, radioactive implants (including brachytherapy from 1988 onward), recommended treatments with unknown administration status, and refusals (from 1988 onward). CI, confidence interval; HR, hazard ratio.

Stratified multivariate analysis results

Figure 4 displays the outcomes of the stratified multivariate analysis. Thirteen of the above-mentioned factors were included, and each was stratified to reduce their confounding effects on the study outcome.

Figure 4 Stratified multivariable analysis of participants. Weighted by full-sample Mobile Examination Center exam weight. Outcome variable: vital status. Model I being unadjusted. Model II was adjusted for variables including age, race, and diagnosis year. Model III was adjusted for variables including age, race, diagnosis year, origin, laterality, primary site, stage, clinical grade, total malignant tumors, radiation, chemotherapy, and systemic treatment and surgical sequence. CI, confidence interval; HR, hazard ratio.

After adjustments were made for covariates in Model III, stratified multivariate analysis showed that males had an overall 40% higher risk of death than did females (HR =1.40, 95% CI: 1.06–1.85; P=0.02). This elevated risk persisted across several stratifications. In the age stratum, males aged 60–69 years had a 109% higher risk of death (HR =2.09, 95% CI: 1.08–4.04; P=0.03). In the race stratum, White males had a 45% higher risk of death (HR =1.45, 95% CI: 1.07–1.98; P=0.02). In the origin stratum, males in the non-Spanish-Hispanic-Latino group had a 43% higher risk (HR =1.43, 95% CI: 1.07–1.91; P=0.01). In the primary site stratum, males with tumors in the lower lobe of the lung faced a markedly 128% greater risk as compared to females (HR =2.28, 95% CI: 1.29–4.02, P=0.005). In the clinical grade stratum, males in the moderately differentiated group had a 131% higher mortality risk than did females (HR =2.31, 95% CI: 1.33–4.02; P=0.003). In the total number of malignant tumors stratum, males with a single tumor had a 61% higher risk of death than did females (HR =1.61, 95% CI: 1.09–2.35; P=0.02). When stratified by systemic treatment and surgical sequence, males had significantly higher mortality than did females in both the systemic therapy after surgery group and the no systemic therapy and/or surgical procedures group. The increase was particularly large in the systemic therapy after surgery group, with the mortality of males being 489% higher than that of females (HR =5.89, 95% CI: 1.37–25.40; P=0.02). In the no systemic therapy and/or surgical procedures group, males had a 39% higher risk than did females (HR =1.39, 95% CI: 1.04–1.86; P=0.03). In the chemotherapy stratum, males who underwent chemotherapy had a 216% higher mortality risk than did females (HR =3.16, 95% CI: 1.63–6.12; P<0.001). Conversely, in the >60 years age group, males had a 92% lower risk of death compared with females (HR =0.08, 95% CI: 0.01–0.78; P=0.03).

Analysis of the survival rate

Table 2 presents the 6-, 12-, 18-, 24-, 30-, and 35-month survival rates for patients with minimally invasive LUSC across several stratifications. When stratified by sex, female survival rates at 6, 12, 18, 24, 30, and 35 months were 85%, 78%, 71%, 67%, 61%, and 61%, respectively, while male survival rates were 81%, 69%, 63%, 54%, 49%, and 47%, respectively; when stratified by age group, patients aged <60 years had survival rates of 75%, 67%, 61%, 61%, 49%, and 49%, respectively, while those aged 60–69 years had rates of 88%, 76%, 71%, 65%, 61%, and 61%, respectively; moreover, patients aged 70–79 years had rates of 84%, 73%, 68%, 59%, 56%, and 51%, respectively, while patients ≥80 years had rates of 74%, 68%, 59%, 49%, 39%, and 39%, respectively. Survival rates for the other stratified groups are presented in Table 2.

Development and validation of the prediction model

To predict survival in patients with minimally invasive LUSC, 13 factors were incorporated into a nomogram (Figure 5). Summing the scores for these variables yields an estimate of the patients’ survival probability 14 months after diagnosis. As shown in Figure 6, the area under the curve (AUC) of this prediction model was 0.73.

Figure 5 Prediction model based on survival analysis. Categorical variables were coded numerically for age (1 for under 60 years, 2 for 60–69 years, 3 for 70–79 years, and 4 for 80 years and above), sex (1 for female and 2 for male), race (1 for White, 2 for Black, 3 for Asian or Pacific Islander, and 4 for others), origin (1 for Spanish-Hispanic-Latino and 2 for non-Spanish-Hispanic-Latino), laterality (1 for right, 2 for left, and 3 for others), primary site (1 for upper lobe, 2 for middle lower lobe, 3 for lower lobe, 4 for main bronchus, and 5 for others), stage (1 for localized, 2 for regional, and 3 for distant), total number of malignant tumors (1 for one, 2 for two, 3 for three, and 4 for four or more), clinical grade (1 for well differentiated, 2 for moderately differentiated, 3 for poorly differentiated, 4 for undifferentiated, and 5 for unknown), radiation (1 for beam radiation, 2 for unknown, and 3 for others), chemotherapy (1 for chemotherapy and 2 for no/unknown), and systemic treatment and surgical sequence (1 for no systemic therapy and/or surgical procedures, 2 for systemic therapy after surgery, and 3 for systemic therapy before surgery).

Figure 6 ROC curve of the prediction model. AUC, area under the curve; ROC, receiver operating characteristic.

Discussion

The study analyzed the survival of 654 patients with minimally invasive LUSC. The study first used Kaplan-Meier curves to characterize OS in the cohort. Patients were then stratified by 13 variables to compare survival in different strata, and survival probabilities at multiple time points were determined for each stratum. Building on that initial analysis, we further investigated the influence of gender on prognosis using univariate and stratified multivariate analyses, and we found that male patients had a higher risk of death than did female patients. Finally, we developed a survival prediction model to estimate individual mortality risk in this population.

Gender is an important direct or indirect factor of mortality and survival in patients with cancer across multiple tumor types (28-36). The OS of patients with LUSC is generally poor, but it is unclear whether gender influences outcomes in this population. Islam et al. conducted a study on patients with unresectable lung cancer and reported a survival advantage for females over males (median survival: 16 vs. 12 months) after adjustment for covariates. The benefit was significant for LUAD (HR =0.64, 95% CI: 0.46–0.90; P=0.01) and LUSC (HR =0.52, 95% CI: 0.32–0.85; P=0.009). Females exhibited improved survival across different treatment types: supportive care only (HR =0.53, 95% CI: 0.36–0.78, P=0.001), chemotherapy (HR =0.54, 95% CI: 0.35–0.83; P=0.005), and radiotherapy (HR =0.33, 95% CI: 0.13–0.88; P=0.03). By contrast, no significant gender difference was evident among patients who received concurrent chemoradiotherapy (37). The study by Islam et al. examined demographic factors (sex, age, and education) and clinical variables (histologic subtype and treatment modality). However, because the data were from a single center with limited clinical covariates and relatively short follow-up, the findings have limited generalizability. Similarly, another study on the postoperative survival of patients with lung cancer reported that the OS among male patients with non-adenocarcinoma was significantly worse than that of females (5-year survival rate: 53.1% vs. 59.3%; P=0.04) (38). In contrast, Warwick et al. found no gender difference in postoperative survival among patients with LUSC (P=0.20), a result that persisted after propensity score matching (P=0.90) (39). Their study enrolled 2,233 male and 1,979 female patients (median survival 2.78 years; range 0–13 years), had an extended follow-up period, and used the UK National Strategic Tracing Service to ensure complete follow-up. However, significant imbalances in age (P<0.001) and forced expiratory volume in 1 second (P<0.001) remained after propensity matching, which could have biased the survival analysis.

Compared with these aforementioned studies, our work further restricted the cohort to those with minimally invasive LUSC; moreover, we used 13 variables for patient-level analysis and deeper data mining, yielding a more precisely defined study population. After the baseline characteristics were balanced, the OS was relatively worse in male patients than in female patients. Univariate analysis showed that race, laterality, stage, and chemotherapy were each independent prognostic factors in the assessment of gender’s effect on survival in patients with minimally invasive LUSC; therefore, these variables constitute potential confounders. To reduce their influence, we applied additional data processing to estimate gender-specific survival effects. Through stratified multivariate analyses that mitigated confounding, we found that males with minimally invasive LUSC had a 40% higher risk of mortality than did females (HR =1.40, 95% CI: 1.06–1.85; P=0.02), which was consistent with the two prior analyses. Moreover, this disparity was further amplified for multiple strata, including age 60–69 years, White race, non-Spanish-Hispanic-Latino race, lower lobe of the lung location, moderately differentiated tumors, single tumor, receipt of systemic therapy after surgery, absence of systemic therapy and/or surgical procedures, and receipt of chemotherapy. In contrast, in the under 60 years group, males had a 92% lower mortality risk compared to females, likely due to hormonal differences. Research indicates that estrogen and its receptors can facilitate NSCLC progression through various mechanisms (40-43). The higher estrogen level differences in younger patients may explain the higher mortality risk in females. We assessed patient survival at 6, 12, 18, 24, 30, and 35 months, providing a more dynamic view of mortality risk over time as compared to studies that have examined only median survival or a single time point. In addition to completing a survival analysis, we developed a nomogram that assigns weighted scores to 13 variables to predict 14-month survival in patients with minimally invasive LUSC and visualize the results. The model demonstrated good discriminatory performance for 14-month survival, achieving an AUC of 0.73.

This work proposes, for the first time, a provisional definition of “minimally invasive LUSC”. Historically, the notion of minimal invasion has mainly been applied to LUAD, and we propose extending this concept, cautiously and systematically, to LUSC. Because patients with LUSC have a relatively poor prognosis and LUSC lacks precise subclassification, introducing this category provides a novel, clinically relevant perspective on its taxonomy. This concept will refine the classification framework for LUSC, address deficiencies in this research area, and constitutes a substantive innovation. In our study, we evaluated 13 variables and analyzed patient survival across demographics, clinicopathological features, and treatment factors. This multidimensional design could capture a broader range of prognostic determinants as compared to previous on this subject and improve control for confounding. We applied a rigorous strategy from univariate analysis to multivariate analysis, stratifying and adjusting key covariates such as age sequentially. This granular analytical strategy allowed for a systematic assessment of the impact of gender on patient survival outcomes and facilitates the translation of gender differences into precise intervention strategies. These advances not only help enhance the precision of clinical treatments but also provide robust scientific support for the formal proposition of the minimally invasive LUSC concept in the future.

The nomogram developed in this study demonstrates that survival in patients with minimally invasive LUSC is determined by a multifaceted interplay of factors. Beyond gender, the model highlights that tumor-specific variables—such as laterality, primary site, stage and clinical grade—and nontumor factors, including treatment modality and race, are particularly dominant predictors with effect sizes that exceed that of gender. This finding underscores that gender serves as a meaningful independent variable, yet its clinical impact is relatively modest compared to these more robust prognostic indicators. Notably, unlike patients with MIA, which is typically associated with extremely high survival and negligible metastatic potential, the cohort of patients with minimally invasive LUSC in this study had an OS of 65.14% during follow-up, with 99 (15.14%) cases of regional metastasis and 87 (13.30%) of distant metastasis. This striking disparity indicates that the morphological criteria defining MIA in LUAD may be insufficient for LUSC. Given the substantial biological and pathogenic differences, the diagnostic criteria for minimally invasive LUSC should be significantly more stringent than those for LUAD and specifically tailored to its distinct aggressiveness. This study involved several limitations that should be addressed. First, we employed a retrospective analysis of a database, which provides limited statistical power. Second, the sample size was relatively small, which may cause potential overfitting, and the investigation was still in the exploratory stage; therefore, additional cases are needed to strengthen the findings. Third, the maximum patient follow-up was 35 months, which restricts conclusions regarding long-term survival. Fourth, there were still some confounding factors unadjusted, such as smoking and hormone levels. Fifth, the selection process for non-surgical patients classified as T1mi relies on clinical staging, the accuracy of which is limited. To address these issues, future studies will recruit patients from additional centers, increase the sample size, and incorporate relevant covariates such as smoking status and hormone levels. We will also extend follow-up duration to improve the study’s clinical validity and translational relevance.

To define minimally invasive LUSC, it is essential to identify the transitional stage between carcinoma in situ and invasive carcinoma. The greatest challenge lies in defining the invasion of LUSC and the rapidity of its progression. Given the difficulty in defining the boundaries of infiltration, perhaps the depth of infiltration can be identified more clearly and accurately through methods such as three-dimensional pathological reconstruction, immunohistochemical-assisted markers, and digital pathological-assisted diagnosis. Moreover, to address the rapid progression of LUSC, the “minimal invasion” of LUSC can be more strictly defined through multi-dimensional evaluations such as dynamic monitoring with liquid biopsy and molecular marker detection. If the term “minimally invasive LUSC” can be formally defined, then clinicians may adopt the treatment model of MIA. For patients with minimally invasive LUSC, clinicians can draw on the mature experience in MIA and prioritize lung segment resection or wedge resection for eligible patients. This approach can precisely remove the tumor lesion while preserving the healthy lung tissue, reduce the occurrence of complications, and shorten the hospital stay. During the surgical process, this can also be used as a basis to simplify the scope of lymph node dissection in a targeted manner. For instance, for patients without high-risk factors, only lymph nodes at the N1 stations should be sampled to avoid serious complications such as recurrent laryngeal nerve injury and chylothorax caused by systematic dissection. In addition, this definition and the low recurrence rate of those also provide a scientific basis for the downgrading of postoperative adjuvant therapy. Consequently, the number of postoperative adjuvant treatments, including chemotherapy and radiotherapy, can be minimized, which can avoid adverse effects such as immunosuppression and radiation pneumonitis, thus alleviating the financial burden on patients’ families.

Conclusions

Based an analysis of the SEER database, this study established the concept of minimally invasive LUSC and identified gender as an independent factor associated with patient survival, with male patients having a significantly shorter OS than female patients. A predictive model was constructed to actively promote the formal proposal of a minimally invasive LUSC concept and to provide a basis for individualized survival assessment and treatment decision-making for patients with this condition.

Acknowledgments

We extend our gratitude to the participants for their valuable time and dedication during the data collection and analysis process. Additionally, we acknowledge the significant support provided by the esteemed Hu Jian Workstation in Taizhou, Zhejiang.

The abstract of this manuscript was showcased as a poster at the 2025 World Conference on Lung Cancer (WCLC) and subsequently published in the conference proceedings of the Journal of Thoracic Oncology (JTO) [https://www.jto.org/article/S1556-0864(25)02249-X/abstract].

Footnote

Reporting Checklist: The authors have completed the TRIPOD reporting checklist. Available at https://tlcr.amegroups.com/article/view/10.21037/tlcr-2026-0252/rc

Peer Review File: Available at https://tlcr.amegroups.com/article/view/10.21037/tlcr-2026-0252/prf

Funding: This study was supported by grants from the National Key Research and Development Program of China (No. 2022YFC2407303) and the Zhejiang Provincial Research Center for Lung Tum or Diagnosis and Treatment Technology (No. JBZX-202007).

Conflicts of Interest: All authors have completed the ICMJE uniform disclosure form (available at https://tlcr.amegroups.com/article/view/10.21037/tlcr-2026-0252/coif). All authors report grants from the National Key Research and Development Program of China (No. 2022YFC2407303) and the Zhejiang Provincial Research Center for Lung Tum or Diagnosis and Treatment Technology (No. JBZX-202007). The authors have no other conflicts of interest to declare.

Ethical Statement: The authors are accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved. This study was conducted in accordance with the Declaration of Helsinki and its subsequent amendments.

Open Access Statement: This is an Open Access article distributed in accordance with the Creative Commons Attribution-NonCommercial-NoDerivs 4.0 International License (CC BY-NC-ND 4.0), which permits the non-commercial replication and distribution of the article with the strict proviso that no changes or edits are made and the original work is properly cited (including links to both the formal publication through the relevant DOI and the license). See: https://creativecommons.org/licenses/by-nc-nd/4.0/.

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