Clinical stage II non-small cell lung cancer: can we “just give adjuvant therapy”?

Introduction

Non-small cell lung cancer (NSCLC) remains the leading cause of cancer-related mortality worldwide, with clinical stage II (cII) disease representing a critical point for potential curative treatment (1,2). Historically, cII NSCLC has been treated with anatomic lung resection, with adjuvant platinum-based chemotherapy demonstrating survival benefits (3-9). Advances in perioperative multimodal therapy, specifically related to immunotherapy and targeted therapy, have reshaped treatment paradigms in resectable lung cancer, offering both neoadjuvant and adjuvant approaches to improve survival (10-14).

Despite these advances, the optimal sequencing and timing of therapy remain points of debate. Treatment approaches for cII NSCLC, in particular, vary widely with concern that these patients may never receive guideline-suggested systemic therapy. Uptake rates of adjuvant therapy (AT) are low in even clinical trial settings, such as IMPOWER010 and ALCHEMIST (15,16). The potential for disparities in clinical practice and patient access to care is thus apparent (17-20). This becomes an important consideration during surgical planning: should neoadjuvant approaches be more strongly considered if AT is not consistently administered?

Currently, limited data exist on real-world clinical staging accuracy, treatment patterns, and oncologic outcomes in cII NSCLC, particularly regarding predictors for and survival after pathological upstaging. This study focuses on cII NSCLC as it represents a pivotal decision point in early-stage lung cancer management. Patients at this stage are typically candidates for surgical resection, yet AT decisions remain variable despite demonstrated survival benefits. This analysis aims to clarify current utilization patterns and associated outcomes within this critical subgroup by investigating a contemporary cohort to evaluate the sociodemographic, clinical, and pathological characteristics of cII NSCLC patients undergoing surgical resection. We assess the accuracy of clinical staging, rates, and predictors of AT uptake, and survival outcomes in this population. We hypothesize that disparities exist in adjuvant uptake and that outcomes are worse in patients that are pathologically upstaged who do not receive adjuvant treatment. We present this article in accordance with the STROBE reporting checklist (available at https://jtd.amegroups.com/article/view/10.21037/jtd-2025-669/rc).

Methods

Data source

The study utilized the National Cancer Database (NCDB), a comprehensive, hospital-based oncology registry jointly sponsored by the American College of Surgeons and the American Cancer Society (21). The NCDB captures over 70% of newly diagnosed cancer cases in the United States (U.S.) at Commission on Cancer-accredited cancer centers. All data in the NCDB are deidentified and adhere to requirements by the Health Insurance Portability and Accountability Act. The NCDB has not verified the analysis used in this paper and is not responsible for the conclusions derived.

Study population and design

A retrospective cohort study was conducted using the NCDB (version 2019). We included patients with cII NSCLC by the American Joint Committee on Cancer (AJCC) 8^th Edition who underwent surgical resection and were diagnosed between 2015 and 2019 (22). The cohort was stratified into two groups based on receipt of AT after upfront surgical resection. Patients of other clinical stages, those who did not undergo surgical resection, and those with missing clinical staging or treatment data were excluded (Figure 1). Pathological staging variables were used to assess upstaging or downstaging following surgery.

Figure 1 Consort diagram of study cohort. NSCLC, non-small cell lung cancer.

The following patient demographic information, clinical characteristics, and treatment data were included: age, sex, Charlson-Deyo Comorbidity Index (CCI), race, ethnicity, type of treating facility, insurance status, facility location, education level indicator (percent of adults in zip code who did not complete high school education), income level (using quartiles of household income for the patient’s area of residence proportioned by income ranges among all U.S. zip codes), clinical stage group, clinical tumor stage (T stage) and node stage (N stage), extent of resection, surgical approach, lymphovascular invasion (LVI), resection margins, regional nodes examined and positive, histologic grade, pathologic stage, pathologic T and N stages, 30-day postoperative unplanned readmissions, 30- and 90-day postoperative mortality, and vital status (23). A list of the NCDB variables used in the study is included (Table S1). A complete-case approach was utilized to account for missing data in the clinical staging or treatment variables, assuming data were missing at random.

Study objectives

Our primary objective was to identify predictors of AT delivery in cII patients following upfront surgery. Our secondary objectives were to assess the accuracy of clinical staging for cII NSCLC by analyzing rates of pathological upstaging and downstaging, identify geographic trends of adjuvant delivery, and evaluate the association of AT with survival in propensity-matched cohorts stratified by pathological upstaging.

Statistical analysis

To study associations between patients who received AT vs. those who only underwent surgical resection, baseline patient demographic, socioeconomic, and clinical characteristics were compared, with continuous variables presented as medians with interquartile ranges (IQRs) or means with standard deviations (SDs), and categorical variables as frequencies and percentages. The same analysis was completed for cohorts who were upstaged and not upstaged after surgical resection. Group comparisons were performed using Chi-squared tests for categorical variables and t-tests or Mann-Whitney U tests for continuous variables, depending on the data distribution. Geospatial trends in AT delivery were analyzed using the Chloropleth R Maps package on R Studio for data visualization.

A multivariable logistic regression model using stepwise backward elimination (P=0.10 for stepwise removal) was employed to identify factors associated with AT delivery. The covariates included in the analysis were age, sex, race, ethnicity, CCI, insurance status, hospital setting, facility type, pathologic stage, pathologic nodal status, LVI, surgical margins, geographic location, and grade adjusted by clinical stage. Goodness-of-fit was assessed with the Hosmer-Lemeshow test (P>0.05) and multicollinearity was evaluated.

Propensity score matching (PSM) was performed to compare survival between the two groups to control for confounding factors (Figure S1). After performing matching, the Kaplan-Meier method was utilized to estimate survival curves with 5-year overall survival (OS), defining OS as time from surgical resection to date of death or last contact. The Kaplan-Meier curves for AT vs. surgical resection were compared using the log-rank test. Cox proportional hazards regression was performed to estimate all-cause mortality hazard ratios (HRs) with 95% confidence intervals (CIs). A subgroup analysis was then performing by stratifying the cohort to compare OS in patients that were upstaged to those that were not by receipt of AT.

Statistical significance was set at P<0.05 for all analyses and all tests were two-sided. All statistical analyses were conducted using SPSS (version 29.0.2.0; IBM Corporation, Armonk, NY) and R Core Team (version 4.2.2; R Foundation for Statistical Computing, Vienna, Austria). PSM was performed in R using the MatchIt package.

Ethical statement

This research was conducted in accordance with the Declaration of Helsinki and its subsequent amendments, and was approved by the Albert Einstein College of Medicine Institutional Review Board (No. 2013-2570). Since all the data in this study were de-identified, the requirement for informed consent was waived on December 1^st, 2022.

Results

A total of 17,674 patients with cII NSCLC underwent surgical resection between 2015 and 2019, with 728 (4.1%) receiving neoadjuvant therapy while the remainder (n=16,946, 95.9%) underwent upfront surgery (Figure 1). Of the total upfront resection cohort included in the study, 8,620 patients (50.9%) received AT, while 8,326 (49.1%) only underwent surgical resection. In this cohort, 62.2% of the population was 65 years or older (n=10,538), 52.2% the population was male (n=8,841), 81.6% had 0 or 1 comorbidities (n=13,834), and 87% were White (n=14,748). Demographic and baseline characteristics of the cohort, stratified by receipt of AT, are summarized in Table 1. Patients who received AT were significantly younger (median age: 67 vs. 71 years), more likely to have fewer comorbidities (CCI 0–1: 83.1% vs. 80.1%, P<0.001), more likely to have private insurance (32.7% vs. 22.9%, P<0.001), and to reside in metropolitan areas (80.3% vs. 78.8%, P=0.02). In terms of oncologic characteristics, 49.1% of patients were clinical stage IIA (n=8,313) and 50.4% were IIB (n=8,540). Figure 2 displays the geographic distribution of AT utilization with the highest rates of AT in the Middle Atlantic region (Table S2).

Figure 2 Geographic trends in adjuvant delivery for NSCLC. NSCLC, non-small cell lung cancer.

Treatment characteristics and operative outcomes by AT receipt are summarized in Table 2. Patients who received AT were more likely to have undergone lobectomy (94.2% vs. 91.3%) and less likely sublobar resection (4.7% vs. 7.7%, P<0.001). They also had a significantly higher incidence of LVI (38.7% vs. 23.2%, P<0.001), positive resection margins (9.1% vs. 5.8%, P<0.001), and more extensive nodal evaluation, with >10 regional lymph nodes examined in 64.8% vs. 55.3% (P<0.001).

Postoperative outcomes showed that the 30- and 90-day mortality rates were lower in the AT group compared to the non-AT group (30-day mortality: 0% vs. 4.1%, P<0.001; 90-day mortality: 0.7% vs. 7.5%, P<0.001). The rate of unplanned 30-day readmission was also lower in patients receiving AT (3.0% vs. 4.9%, P<0.001). Median follow-up time was 40.5 months for the surgical resection group and 43.7 months for the AT group.

Table S3 presents demographic characteristics stratified by pathologic upstaging, which occurred in 23.3% of the cohort. Upstaged patients were more likely to be male (23.9% vs. 22.5%, P=0.03) and Black or Asian (24.4%, 28.6% vs. White: 22.9%, P=0.02). Of those who underwent upfront surgery with pathologic stage II–IV, only 58.4% (n=8,240/14,116) received AT (P<0.001). Over 80% of the cohort (n=14,116) was pathologic stage II or higher.

A multivariable logistic regression model assessing factors associated with AT was conducted, presented in Table S4. Female sex [adjusted odds ratio (aOR) =1.12; 95% CI: 1.02–1.23; P=0.02] and receiving care at an academic institution (aOR =1.13; 95% CI: 1.02–1.24; P=0.02) were associated with a higher likelihood of AT, while older age (aOR =0.50; 95% CI: 0.44–0.56; P<0.001), more comorbidities (aOR =0.85; 95% CI: 0.75–0.96; P=0.01), public insurance (aOR =0.83; 95% CI: 0.73–0.94; P=0.002), and rural settings (aOR =0.85; 95% CI: 0.75–0.96; P=0.01) were less likely to receive AT. Variables included in multivariable logistic regression are presented in Figure 3.

Figure 3 Multivariable logistic regression model assessing associations with receipt to AT after surgical resection in cII cohort. Variables included in analysis: age, sex, race, ethnicity, CCI, insurance, hospital setting, facility type, pathologic stage, pathologic nodal status, LVI, surgical margins, geographic location, and grade adjusted by clinical stage. Variables removed from equation through backward stepwise elimination: ethnicity. AT, adjuvant therapy; CCI, Charlson-Deyo Comorbidity Index; cII, clinical stage II; LVI, lymphovascular invasion; ref, reference.

Figure 4A presents the PSM survival analysis, comparing AT and surgical resection cohorts with 4,658 patients in each arm. There were no differences in the adjusted covariates after matching (Figure S1). In the matched cohort, patients who underwent AT had a longer 5-year OS compared to surgical resection (62.2% vs. 52.2%, log-rank P value <0.001). The HR for all-cause mortality without AT was 1.44 (95% CI: 1.34–1.54; P<0.001). Figure 4B presents a subgroup analysis further stratifying survival outcomes based on pathologic upstaging status. Among patients who were upstaged after resection, those who received AT exhibited improved OS compared to surgical resection (5-year OS: 45.6% vs. 34.4%).

Figure 4 Survival analysis in propensity-matched cohort of patients. (A) Survival analysis in propensity-matched cohort of patients receiving AT vs. S. PSM covariates: age, sex, race, ethnicity, CCI, insurance, LVI, path stage, and path nodal status. (B) Subgroup analysis of survival outcomes in propensity-matched cohorts of patients receiving AT vs. S in upstaged and not upstaged patients. AT, adjuvant therapy; CCI, Charlson-Deyo Comorbidity Index; CI, confidence interval; LVI, lymphovascular invasion; No., number; non-adj, non-adjuvant; OS, overall survival; S, surgical resection; yr, year.

Discussion

This study highlights insights into the management of cII NSCLC, with a focus on treatment patterns, pathological staging, and survival outcomes. Despite advances in multimodal therapies, the majority of cII patients underwent upfront surgery, with less than 5% receiving neoadjuvant therapy. Among those eligible for adjuvant treatment, over 40% did not receive it, which was associated with poorer survival. These findings underscore persistent challenges in ensuring adherence to optimal treatment pathways and identify areas for improvement in the care of patients with cII NSCLC, highlighting a critical need to improve the uptake of neoadjuvant therapy and AT in patients with cII NSCLC, given the well-established benefits of these perioperative treatments.

Despite guideline recommendations, a significant proportion of patients do not receive these therapies, suggesting disparities in implementation that may compromise outcomes. This analysis further identifies specific demographic and clinical populations that are less likely to receive recommended adjuvant regimes. Understanding these inequities is essential for informing targeted strategies to improve treatment delivery, ensure equitable care, and ultimately enhance survival outcomes in this population.

The underutilization of AT remains a critical issue. In this study, less than 60% of eligible patients (path stage II–IV) received adjuvant treatment (24,25). The 5-year OS improvement observed in the AT group illustrates the importance of this treatment, especially for those pathologically upstaged. Factors such as older age, socioeconomic status, and treatment at non-academic centers were associated with lower likelihood of receiving AT, reflecting systemic disparities that require intervention. During the study period, the utilization of AT remained relatively stable. Although minor year-to-year fluctuations were observed, there was no consistent upward trend. Notably, the onset of the coronavirus disease 2019 (COVID-19) pandemic in the later years of the dataset may have affected treatment delivery patterns.

Given low rates of adjuvant uptake, neoadjuvant and perioperative strategies must also be considered in this setting. Trials such as CheckMate 816 have demonstrated the superiority of neoadjuvant chemoimmunotherapy in improving pathological response and survival outcomes compared to surgery alone and additional perioperative trials have supported the benefits of systemic therapies before and after surgery (10). However, real-world studies reveal significant barriers to the adoption of neoadjuvant therapy, including concerns about treatment-related delays, logistical challenges, and lack of standardization in treatment protocols (26).

The accuracy of clinical staging observed in this study aligns with prior research indicating significant rates of pathological upstaging after surgery (27). Nearly a quarter (23.3%) of patients were pathologically upstaged, highlighting the limitations of clinical staging, particularly in detecting nodal involvement or micrometastases (27). Predictors of upstaging, such as LVI and clinical node positivity, have been consistently reported in the literature, suggesting the need for improved imaging and diagnostic modalities to refine preoperative staging (28). Identifying patients at higher risk for upstaging can inform preoperative discussions about the potential benefit of neoadjuvant therapy, which may improve disease management when adjuvant treatment is less reliably administered. The development of standardized care pathways and multidisciplinary tumor boards can ensure that eligible patients are consistently referred for neoadjuvant therapy or AT.

Addressing systemic disparities, such as geographic and socioeconomic barriers, will be crucial in improving access to comprehensive oncologic care. Initiatives to address potential barriers to care, such as patient navigation programs and value-based care models, can help reduce inequities and improve outcomes for all patients with cII NSCLC. To address challenges in return to oncologic therapy at Montefiore Einstein, a program called BRONx-TEAM (Building Reliable Oncology Navigation, To Ensure Adjuvant Management), is proposing an intervention through a navigation pathway, patient engagement, and identification of barriers to care in the local population (29).

Limitations

This study has several limitations inherent to its retrospective design and utilization of the NCDB. First, the NCDB lacks detailed clinical information such as molecular biomarker data, specific regimens of ATs, and toxicity profiles, which could provide more nuanced insights into treatment decisions and outcomes. Second, while the database captures a large proportion of U.S. cancer cases, it does not include information on treatment intent, patient adherence, or reasons for treatment deviations. Additionally, with new emerging therapies changing treatment paradigms for both neoadjuvant therapy and AT, changes have been made rapidly within the past few years. Of the total cohort, 362 patients (2.1%) received immunotherapy as a first-line treatment. As evidence supporting perioperative immunotherapy and targeted therapies continues to grow, future iterations of the NCDB may provide more granular data to evaluate the integration and outcomes of these modalities in the adjuvant setting.

Furthermore, the use of PSM mitigates but does not eliminate the possibility of residual confounding, as unmeasured variables, such as physician expertise or institutional resources, may influence treatment selection and outcomes. We acknowledge that surgical procedure type and histologic subtype are important prognostic factors for post-operative recurrence. These variables were not included in the PSM which may affect the interpretation of treatment effect estimates. The relatively low proportion of patients receiving neoadjuvant therapy limits the generalizability of findings about this treatment modality. Finally, the NCDB does not capture disease-specific survival or recurrence data, which could provide a more comprehensive assessment of the impact of treatment strategies on long-term outcomes. Despite these limitations, the study’s large, nationally representative cohort provides insights into treatment patterns and their association with survival in cII NSCLC.

Conclusions

This study provides valuable insights into the real-world management of cII NSCLC, highlighting significant gaps in adjuvant delivery, with disparities in uptake and a significant impact on survival outcomes. Pathologic upstaging remains common and treatment adherence to adjuvant and neoadjuvant protocols is low. These findings underscore the need for systemic efforts to improve care, ensure equitable access to therapies, and optimize outcomes for patients with cII NSCLC. Future prospective studies are needed to address these gaps and validate the findings in more granular datasets to evaluate interventions aimed at increasing the adoption of neoadjuvant therapy and exploring the reasons behind non-adherence to AT.

Acknowledgments

This study was presented at the STS Annual Meeting in Los Angeles, CA, USA in January 2025.

Footnote

Reporting Checklist: The authors have completed the STROBE reporting checklist. Available at https://jtd.amegroups.com/article/view/10.21037/jtd-2025-669/rc

Data Sharing Statement: Available at https://jtd.amegroups.com/article/view/10.21037/jtd-2025-669/dss

Peer Review File: Available at https://jtd.amegroups.com/article/view/10.21037/jtd-2025-669/prf

Funding: This research was funded by a NIH grant for R.J. (No. 5T32CA200561-10).

Conflicts of Interest: All authors have completed the ICMJE uniform disclosure form (available at https://jtd.amegroups.com/article/view/10.21037/jtd-2025-669/coif). N.P.C. reports consulting/advisory board fees from AstraZeneca, research support from Bristol Myers Squib, and BMS Foundation, and grants from AstraZeneca, AATS Foundation, and LUNGevity Foundation. B.M.S. received consulting/advisory board fees from AstraZeneca, Roche/Genentech, Pfizer, Merck/MSD, Bristol Myers Squib, and Regeneron; and research support from Bristol Myers Squib and BMS Foundation. He is on boards of the Lung Cancer Research Foundation and LUNGevity. The other authors have no 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 research was conducted in accordance with the Declaration of Helsinki and its subsequent amendments, and was approved by the Albert Einstein College of Medicine Institutional Review Board (No. 2013-2570). Since all the data in this study were de-identified, the requirement for informed consent was waived on December 1^st, 2022.

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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