Abstract

Background: This study aims to identify clinical and pathological factors associated with spread through air spaces (STAS) positivity in patients with non-small cell lung cancer.

Methods: Between September 2001 and November 2024, a total of 380 patients (279 males, 101 females; mean age: 61.6±10.1 years; range, 20 to 87 years) who were diagnosed with primary lung cancer and underwent surgical resection were retrospectively analyzed. Demographic, clinical, and pathological data of the patients were collected and their association with STAS positivity was evaluated.

Results: A higher preoperative monocyte count was significantly associated with STAS positivity (0.73±0.63 vs. 0.58±0.22; p=0.003; odds ratio=5.57; 95% confidence interval: 1.76-17.6). Pathological N1 and N2 stages, along with increased maximum standardized uptake value (SUVmax) in the lymph nodes, were related to STAS positivity. In the multivariate analysis, only adenocarcinoma histology and elevated monocyte count were found to be independently associated with STAS positivity.

Conclusion: Adenocarcinoma histology and increased preoperative monocyte levels are independent predictors of STAS in patients with non-small cell lung cancer. Elevated SUVmax values in the lymph nodes may indicate a potential association with STAS positivity. These findings may be a guide for preoperative risk stratification and individualized treatment planning in clinical practice.

Lung cancer is a major cause of cancer-related mortality and one of the most prevalent forms of cancer worldwide. Key factors contributing to lung cancer development include active smoking, passive smoke exposure, and other potential environmental risk factors. There are two main subgroups of lung cancer: small cell lung cancer (SCLC) and non-small cell lung cancer (NSCLC). The NSCLC group has the potential to provide a higher life expectancy with early diagnosis of surgical treatment, thereby improving the patient's quality of life.

The phenomenon spread through air spaces (STAS) of lung cancer is a recent development that has garnered significant interest in the field of oncology. It refers to the presence of tumor cells in the air spaces of the lung parenchyma, extending beyond the primary tumor. This phenomenon is evident in various forms of lung cancer, particularly adenocarcinoma, squamous cell carcinoma, and SCLC.[1-3] The identification of STAS has significant implications for prognosis and treatment strategies, as its presence is often associated with more aggressive disease and poorer outcomes. Therefore, understanding STAS and its effect on lung cancer progression is essential for developing effective therapeutic approaches and improving patient survival rates.

Accurate prediction of STAS is essential, as it directly affects patient prognosis and treatment strategies. By determining the presence and extent of STAS, healthcare professionals can customize their therapeutic approaches, leading to a more effective management of NSCLC. Understanding STAS can offer valuable insights into the biological behavior of tumors, which may lead to the development of new treatments and better patient outcomes. In the present study, we, therefore, aimed to investigate the value of predicting the STAS in NSCLC and to develop a tool which could provide reliable data to accurately predict STAS in this patient population.

Methods

This single-center, retrospective study was conducted at İstanbul University-Cerrahpaşa, Cerrahpaşa Faculty of Medicine, Department of Thoracic Surgery between September 2001 and November 2024. Initially, a total of 1,166 patients who were diagnosed with primary lung cancer and subsequently underwent surgical resection were screened. Inclusion criteria were as follows: h aving a histologically confirmed diagnosis of NSCLC, undergoing lobectomy, segmentectomy, or wedge resection, and having complete STAS data. Patients were excluded if they were not diagnosed with NSCLC or previously received neoadjuvant therapy. Finally, a total of 380 patients (279 males, 101 females; mean age: 61.6±10.1 years; range, 20 to 87 years) who met the inclusion criteria were enrolled. Demographic, clinical, and pathological characteristics were documented, and their association with STAS positivity was evaluated. A written informed consent was obtained from each patient. The study protocol was approved by the İstanbul University-Cerrahpaşa Non-Interventional Clinical Research Ethics Committee (date: 05.02.2025, no: 2025/71). The study was conducted in accordance with the principles of the Declaration of Helsinki.

Statistical analysis
Statistical analysis was performed using the IBM SPSS version 28.0 software (IBM Corp., Armonk, NY, USA). Descriptive data were expressed in mean ± standard deviation (SD), median (minmax) or number and frequency, where applicable. The distribution of variables was checked using the Kolmogorov-Smirnov and Shapiro-Wilk tests. Independent sample t-test was used to analyze quantitative independent data showing a normal distribution. The Mann-Whitney U test was used to analyze quantitative independent data showing a non-normal distribution. The chi-square test was used in the analysis of qualitative independent data. The effect level and cut-off value were calculated using the receiver operating characteristic (ROC) curve. Univariate and multivariate analyses were carried out to identify the predictive value of STAS. A p value of <0.05 was considered statistically significant.

Results

The most common diagnosis was adenocarcinoma, which was identified in 216 (56.8%) patients, and 310 (81.6%) patients were staged as N0 (Table 1). The STAS positivity was detected in 188 (49.5%) patients, which was higher in patients with an adenocarcinoma (62.2% vs. 34.5%, p<0.0001; odds ratio [OR]= 3.12, 95% confidence interval [CI]: 2.04- 4.76). Lower rates of excessive phlegm reported by patients were detected in the STAS-positive group (6.9% vs. 1 6.7%, p =0.003) ( Figure 1 ). T he m ean preoperative monocyte counts were also higher in STAS-positive patients (0.73±0.63 vs. 0.58±0.22, p=0.003; OR= 5.57, 95% CI: 1.76-17.6) (Table 2, Figure 2).

Table 1. Patient characteristics

Figure 1. The STAS excessive phlegm rate was significantly (p<0.05) lower than that in the STAS negative group.
STAS: Spread through air spaces.

Figure 2. In the group with STAS monocyte value, It was significantly (p<0.05) higher than the STAS negative group.
STAS: Spread through air spaces.

Table 2. Demographics and laboratory findings between the STAS-positive and-negative groups

Pathological N1 and N2 stages (Figure 3), as well as a higher maximum standardized uptake value (SUVmax) of lymph nodes (Figures 4 and 5), were found to be associated with STAS positivity (Table 3). Multivariate analysis confirmed adenocarcinoma histopathology, and a higher monocyte count were independently associated with STAS (Table 3). In the multivariate analysis, the SUVmax o f t he l ymph nodes was not found to be statistically significant. Additionally, distinguishing STAS-positive and STAS-negative patients with SUVmax of lymph nodes (area under the curve [AUC]=0.592 [0.525-0.660)]) and a cut-off value of 1.0 (AUC=0.587 (0.519-0.655]) showed moderate effectiveness (Figure 6).

Figure 3. Only the N1 ratio was significantly (p<0.05) higher in the STAS group than in the STAS negative group.
STAS: Spread through air spaces.

Figure 4. In the STAS group, the SUV N value was significantly (p<0.05) higher than that in the STAS negative group.
SUV: Standardized uptake value; N: Lymph nodes; STAS: Spread through air spaces.

Figure 5. This graph illustrates the positive correlation between the SUV and probability of STAS, showing how the likelihood increases as the SUV value increases.
SUV: Standardized uptake value; N: Lymph nodes; STAS: Spread through air spaces.

Table 3. Univariate and multivariate analysis

Figure 6. According to the ROC curve, the test demonstrated limited accuracy, as the AUC was calculated to be 0.592.
AUC: Area under the curve; PV: Predictive value; SUV: Standardized uptake value; N: Lymph nodes; ROC: Receiver operating characteristic.

Discussion

Spread through air spaces is a new histopathological marker which seems to be an indicator of aggressive tumor behavior and a higher probability of lymph node metastasis.[1] Tumors with STAS display clusters or single tumor cells extending into the air spaces, which correlate with lymphatic invasion and nodal involvement.[2,3]

The relationship between STAS, lymph node, and positron emission tomography/computed tomography (PET/CT) positivity in lung cancer is critical for understanding prognosis and treatment strategies. In general, STAS is recognized as an emerging pattern of tumor invasion that correlates significantly with poor outcomes in lung adenocarcinoma, including high recurrence rates and decreased overall survival (OS), primarily in patients undergoing limited resections.[4]

Various studies have established that patients with STAS-positive tumors often present with a more advanced disease state, which is reflected through imaging diagnoses and histopathological assessments, underlining the necessity for precise preoperative modalities to determine the extent of disease involvement.[5] In the present study, we investigated clinical and pathological factors associated with STAS positivity in patients with NSCLC. Our study results showed that STAS positivity was significantly higher in patients with an adenocarcinoma than in those with nonadenocarcinoma histopathology.

In addition, the results revealed a significantly higher SUVmax in the lymph nodes of the STASpositive group. This finding reinforces the role of SUVmax in predicting STAS in lung cancer based in the univariate analyses. However, SUVmax was not found to be a significant predictor in the multivariate analysis.

In recent years, PET/CT has significantly advanced the evaluation of lung cancer, particularly for assessing nodal involvement and staging accuracy.[6,7] It assists in differentiating between benign and malignant nodal diseases, which is essential for determining the appropriate surgical approach and adjunct therapies.[8] The significance of PET/CT in nodal staging cannot be overstated, as it supports the determination of whether patients can be considered for curative resection or require neoadjuvant therapy.[9]

The metabolic characteristics of tumors, as measured by glucose uptake on PET/CT, provide insights into tumor biology that are not readily available through conventional imaging. Specifically, the correlation between increased metabolic tumor burden and the presence of STAS has been corroborated by various studies, where higher levels of glucose uptake corresponded with poor prognostic markers, including more extensive lymphatic involvement.[10,11] This relationship underscores the importance of integrating STAS evaluation with metabolic imaging to enhance overall prediction models for patient prognosis. Moreover, the interplay between STAS and lymph node pathology further elucidates the complex dynamics of tumor spread and its diagnostic implications. Several studies have indicated that STAS not only facilitates local invasion, but also compromises the accuracy of lymph node imaging.[12] The presence of STAS often coincides with atypical lymph node findings, complicating treatment decisions, wherein positive PET findings can reflect STAS-induced activity rather than discrete metastatic disease. Therefore, a comprehensive evaluation which incorporates histopathological and imaging data may be required to achieve optimal understanding of patient conditions.

In their study, Jin et al.[13] developed a model using dual-delta deep learning and radiomics to predict STAS in primary lung cancer, demonstrating high accuracy in distinguishing between STASpositive and STAS-negative cases. This supports our finding that higher SUVmax is associated with STAS positivity. Similarly, Wang et al.[14] created a nomogram for predicting STAS in patients with lung adenocarcinoma and identified SUVmax as a significant predictive factor. These findings suggest that the SUVmax is a valuable marker for identifying STAS in patients with lung cancer. In addition, Gao et al.[15] developed a model using 2 -[18F] FDG PET/CT to predict tumor STAS in Stage 1 lung adenocarcinoma. Their findings showed that a higher SUVmax indicated a greater likelihood of STAS, underscoring the role of metabolic activity in assessing tumor invasiveness.

Advanced imaging techniques which integrate artificial intelligence (AI) and machine learning can also play a role in enhancing predictive accuracy and lymph node involvement. This can also be applied to STAS. These models can efficiently analyze threedimensional imaging data to better delineate STASassociated activity and conventional metastatic pathways.[11] As the understanding of STAS improves alongside advancements in imaging technology, the potential for developing more robust predictive algorithms has become apparent. The application of integrated PET/CT in the preoperative setting facilitates the identification of appropriate biopsy sites, thereby affecting the management of lung cancer at early stages where surgical options are limited.[16] This integration is particularly relevant in early-stage disease, where histological assessment of lymph nodes and surrounding parenchyma is paramount for curative treatment intent. In this context, studies suggest that patients with STAS on imaging often require a different strategic approach while considering surgical options, reflecting the need for dynamic decision-making based on imaging findings.

Taken together, the interconnections between STAS, lymph node pathology, and PET/CT positivity highlight a multifaceted approach to lung cancer diagnosis. The recognition of STAS as a significant prognostic factor necessitates a sophisticated and integrative approach to imaging, wherein PET/CT serves as an invaluable tool for navigating complex clinical landscapes, albeit with caution regarding potential diagnostic pitfalls. Collaborative efforts to refine imaging modalities, emphasize multidisciplinary evaluations, and implement advanced predictive models could improve patient outcomes in lung cancer management.

Furthermore, the link between systemic inflammation, indicated by peripheral blood monocyte counts, and STAS in lung cancer is a significant area of research with important prognostic implications. Monocytes, which develop into tumorassociated macrophages (TAMs), influence the tumor microenvironment (TME) and affect immune evasion, angiogenesis, and metastasis. The STAS as identified by micropapillary clusters, solid nests, or single cancer cells in the air spaces beyond the primary tumor serves as a marker of aggressive disease in adenocarcinoma and squamous cell carcinoma.[17] In our study, a possibly high relationship between higher SUVmax values and STAS positivity were found in STAS-positive patients in the preoperative period. This finding synthesis highlights mechanistic and prognostic connections between these factors.

In the multivariate analysis, our results confirmed that a higher monocyte count was independently associated with STAS. Elevated peripheral blood monocyte count is strongly associated with poor lung cancer outcomes. Yoshida et al.[18] showed that preoperative monocyte counts could independently predict recurrence in patients with Stage I lung adenocarcinoma, and these counts were correlated with the incidence of STAS. This evidence suggests that monocytes not only reflect systemic inflammation, but also directly contribute to tumor cell migration and invasion. Similarly, Hu et al.[19] reported that NSCLC with high monocyte counts experienced reduced OS and progression-free survival (PFS) when treated with bevacizumab, highlighting the role of monocytes in worsening patient outcomes. Monocytes contribute to an immunosuppressive TME by differentiating into dendritic cells (DCs) or TAMs, and these processes are often disrupted in cancer. Hu et al.[20] reported that impaired DC differentiation in tumors could lead to ineffective antigen presentation and T-cell activation.

Given the fact that STAS is becoming an independent prognostic factor, it is increasingly being recognized as a key predictor of recurrence and mortality in lung cancer. Lu et al.[21] identified it as an independent predictor of recurrence and lung cancer-specific death in squamous cell carcinoma. Yildirim et al.[22] found that patients with resected adenocarcinoma with STAS had lower PFS and OS. Additionally, Tian et al.[17] linked STAS to higher local recurrence rates, particularly in patients with elevated monocyte counts, suggesting that systemic inflammation might enhance STAS's aggressive nature.

Monocyte count also serves as an important dynamic biomarker. Yin et al.[23] linked elevated monocytes to increased granulocyte colonystimulating factor (G-CSF) levels, connecting myeloid activation to inflammation-related tumor progression. High postoperative monocyte levels could predict poor outcomes, as reported by Hai et al.,[24] who found that these levels were correlated with worse features and higher recurrence in lung adenocarcinoma.

Several studies have shown that the neutrophilto- lymphocyte ratio (NLR) and monocyte-tolymphocyte ratio (MLR) enhance prognostic assessments. Combining these ratios with STAS status may improve risk stratification, as suggested by Karampitsakos et al.,[25] who recommended integrating systemic inflammatory markers with clinicopathological data for better adjuvant therapy decisions.

In the current study, our findings have potential evidence to suggest that SUVmax and peripheral blood monocyte count can be used as predictive markers for STAS in lung cancer. The significant relationship between higher SUVmax of lymph nodes and the positivity of STAS observed in our study highlights the potential of PET/CT scans to guide clinical decision-making and tailor treatment strategies, as well as to predict recurrence in lung cancer patients.

Nonetheless, this study has several limitations, including its single-center, retrospective nature and the relatively small sample size. Additionally, although PET/CT is a valuable diagnostic tool, it may fail to detect small STAS-driven metastases, underscoring the necessity of pathological confirmation for accurate diagnosis. Furthermore, the assessment of STAS positivity may vary depending on the interpreting pathologist, potentially leading to under-reporting in some cases.

In conclusion, the relationship between monocyte count and spread through air spaces reveals a complex interplay between systemic inflammation and local tumor biology which contributes to poor outcomes. Elevated monocyte levels can lead to immunosuppression, promote angiogenesis, and facilitate metastasis, whereas spread through air spaces indicates tumor invasiveness. Future research should focus on the underlying molecular mechanisms, such as granulocyte colony-stimulating factor signaling and monocyte plasticity, and explore therapies targeting myeloid cells to reduce spread through air spaces-related recurrences.

Our study results demonstrated a potential link between higher SUVmax in lymph nodes and spread through air spaces positivity in patients with nonsmall cell lung cancer. Preoperative mediastinal lymph node staging is indispensable to ensure accurate staging and optimal treatment planning. In our clinic, mediastinoscopy is routinely performed as a part of this staging process. This meticulous approach not only improves the precision of surgical interventions, but also contributes to better patient outcomes by tailoring treatment strategies to individual needs. Patients with elevated SUVmax, particularly those with adenocarcinoma and higher preoperative monocyte counts, are more likely to exhibit spread through air spaces. This highlights the potential of lymph node SUVmax as a marker for identifying spread through air spaces, aiding risk assessment, surgical planning, and personalized treatment. Future research should involve larger multi-center studies and incorporate advanced imaging and molecular analyses to validate these findings. This approach can enhance the effectiveness of lung cancer management and improve patient outcomes.

Data Sharing Statement: The data that support the findings of this study are available from the corresponding author upon reasonable request.

Author Contributions: Have given substantial contributions to the literature search, data collection, study design, analysis of data: B.K., M.A., Ö.F.S., L.C.; Manuscript preparation and review of manuscript: B.K. H.V.K.; Analysis interpretation of the data and review of manuscript: E.E., AT.; Revised it critically: K.K., A.T., E.E. All authors have participated to drafting the manuscript. All authors read and approved the final version of the manuscript.

Conflict of Interest: The authors declared no conflicts of interest with respect to the authorship and/or publication of this article.

Funding: The authors received no financial support for the research and/or authorship of this article.

References

1) Travis WD, Eisele M, Nishimura KK, Aly RG, Bertoglio P, Chou TY, et al. The International Association for the Study of Lung Cancer (IASLC) staging project for lung cancer: Recommendation to introduce spread through air spaces as a histologic descriptor in the ninth edition of the TNM classification of lung cancer. Analysis of 4061 pathologic stage I NSCLC. J Thorac Oncol 2024;19:1028-51. doi: 10.1016/j.jtho.2024.03.015.

2) Dagher S, Sulaiman A, Bayle-Bleuez S, Tissot C, Grangeon- Vincent V, Laville D, et al. Spread Through Air Spaces (STAS) is an independent prognostic factor in resected lung squamous cell carcinoma. Cancers (Basel) 2022;14:2281. doi: 10.3390/cancers14092281.

3) Aly RG, Rekhtman N, Li X, Takahashi Y, Eguchi T, Tan KS, et al. Spread Through Air Spaces (STAS) is prognostic in atypical carcinoid, large cell neuroendocrine carcinoma, and small cell carcinoma of the lung. J Thorac Oncol 2019;14:1583-93. doi: 10.1016/j.jtho.2019.05.009.

4) Falay O, Selcukbiricik F, Tanju S, Erus S, Kapdagli M, Cesur E, et al. The prediction of spread through air spaces with preoperative 18F-FDG PET/CT in cases with primary lung adenocarcinoma, its effect on the decision for an adjuvant treatment and its prognostic role. Nucl Med Commun 2021;42:922-7. doi: 10.1097/MNM.0000000000001414.

5) Cheng YF, Huang JY, Lin CH, Lin SH, Wang BY. The prognostic value of positron emission tomography/computed tomography in clinical stage I Lung cancer patients: A propensity-match analysis. J Clin Med 2024;13. doi: 10.3390/ jcm13082416.

6) Liu C, Wang YF, Wang P, Guo F, Zhao HY, Wang Q, et al. Predictive value of multiple imaging predictive models for spread through air spaces of lung adenocarcinoma: A systematic review and network meta?analysis. Oncol Lett 2024;27:122. doi: 10.3892/ol.2024.14255.

7) Allen T, Hilu J, Amin M. False Positive Positron Emission Tomography/Computed Tomography (PET/CT) requiring biopsy for proper staging of lung cancer. Cureus 2023;15:e34497. doi: 10.7759/cureus.34497.

8) Iga N, Sonobe H, Mizuno D, Nishi H. Assessment of intrathoracic lymph nodes by FDG PET/CT in patients with asbestos-related lung cancer. J Thorac Dis 2021;13:5925-32. doi: 10.21037/jtd-21-974.

9) Wang BY, Hung WH, Huang JY, Chen HC, Lin CH, Lin SH, et al. The prognostic value of PET/CT in clinical stage I lung cancer patients: A propensity-match analysis. 2019.

10) Yin Q, Wang H, Cui H, Wang W, Yang G, Qie P, et al. Meta-analysis of association between CT-based features and tumor spread through air spaces in lung adenocarcinoma. J Cardiothorac Surg 2020;15:243. doi: 10.1186/s13019-020- 01287-9.

11) Wang XY, Zhao YF, Yang L, Liu Y, Yang YK, Wu N. Correlation analysis between metabolic tumor burden measured by positron emission tomography/computed tomography and the 2015 World Health Organization classification of lung adenocarcinoma, with a risk prediction model of tumor spread through air spaces. Transl Cancer Res 2020;9:6412-22. doi: 10.21037/tcr-20-1934.

12) Kim SK, Kim TJ, Chung MJ, Kim TS, Lee KS, Zo JI, et al. Lung adenocarcinoma: CT features associated with spread through air spaces. Radiology 2018;289:831-40. doi: 10.1148/ radiol.2018180431.

13) Jin W, Shen L, Tian Y, Zhu H, Zou N, Zhang M, et al. Improving the prediction of Spreading Through Air Spaces (STAS) in primary lung cancer with a dynamic dual-delta hybrid machine learning model: A multicenter cohort study. Biomark Res 2023;11:102. doi: 10.1186/s40364-023-00539-9.

14) Wang Y, Lyu D, Cheng C, Zhou T, Tu W, Xiao Y, et al. Preoperative nomogram for predicting spread through air spaces in clinical-stage IA non-small cell lung cancer using (18)F-fluorodeoxyglucose positron emission tomography/ computed tomography. J Cancer Res Clin Oncol 2024;150:185. doi: 10.1007/s00432-024-05674-w.

15) Gao Z, An P, Li R, Wu F, Sun Y, Wu J, et al. Development and validation of a clinic-radiological model to predict tumor spread through air spaces in stage I lung adenocarcinoma. Cancer Imaging 2024;24:25. doi: 10.1186/s40644-024- 00668-w.

16) Masai K, Sakurai H, Sukeda A, Suzuki S, Asakura K, Nakagawa K, et al. Prognostic impact of margin distance and tumor spread through air spaces in limited resection for primary lung cancer. J Thorac Oncol 2017;12:1788-97. doi: 10.1016/j.jtho.2017.08.015.

17) Tian Y, Feng J, Jiang L, Ning J, Gu Z, Huang J, et al. Integration of clinicopathological and mutational data offers insight into lung cancer with tumor spread through air spaces. Ann Transl Med 2021;9:985. doi: 10.21037/atm-21-2256.

18) Yoshida C, Kadota K, Ishikawa R, Go T, Haba R, Yokomise H. Preoperative monocyte count is a predictor of recurrence after stage I lung adenocarcinoma resection. Interact Cardiovasc Thorac Surg 2022;34:1081-8. doi: 10.1093/icvts/ ivac005.

19) Hu P, Shen H, Wang G, Zhang P, Liu Q, Du J. Prognostic significance of systemic inflammation-based lymphocytemonocyte ratio in patients with lung cancer: Based on a large cohort study. PLoS One 2014;9:e108062. doi: 10.1371/ journal.pone.0108062.

20) Hu S, Zou Z, Li H, Zou G, Li Z, Xu J, et al. The preoperative peripheral blood monocyte count is associated with liver metastasis and overall survival in colorectal cancer patients. PLoS One 2016;11:e0157486. doi: 10.1371/journal. pone.0157486.

21) Lu S, Tan KS, Kadota K, Eguchi T, Bains S, Rekhtman N, et al. Spread through Air Spaces (STAS) is an independent predictor of recurrence and lung cancer-specific death in squamous cell carcinoma. J Thorac Oncol. 2017;12:223-34. doi: 10.1016/j.jtho.2016.09.129.

22) Yildirim S, Alan O, Yuksel Yasar Z, Kaya T, Akdag G, Kinikoglu O, et al. Prognostic impact and clinical features of spread through air spaces in operated lung cancer: Realworld analysis. Medicina (Kaunas) 2024;60. doi: 10.3390/ medicina60081374.

23) Yin W, Lv J, Yao Y, Zhao Y, He Z, Wang Q, et al. Elevations of monocyte and neutrophils, and higher levels of granulocyte colony-stimulating factor in peripheral blood in lung cancer patients. Thorac Cancer 2021;12:2680-90. doi: 10.1111/1759- 7714.14103.

24) Hai Y, Chen N, Wu W, Wang Z, Lin F, Guo C, et al. High postoperative monocyte indicates inferior Clinicopathological characteristics and worse prognosis in lung adenocarcinoma or squamous cell carcinoma after lobectomy. BMC Cancer 2018;18:1011. doi: 10.1186/s12885-018-4909-1.

25) Karampitsakos T, Spagnolo P, Mogulkoc N, Wuyts WA, Tomassetti S, Bendstrup E, et al. Lung cancer in patients with idiopathic pulmonary fibrosis: A retrospective multicentre study in Europe. Respirology 2023;28:56-65. doi: 10.1111/ resp.14363.