Clinicoradiological findings associated with prognostic indicators of sarcomatoid-NSCLC: A multicenter analysis of 135 patients

Clinicoradiological findings associated with prognostic indicators of sarcomatoid-NSCLC: A multicenter analysis of 135 patients | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Clinicoradiological findings associated with prognostic indicators of sarcomatoid-NSCLC: A multicenter analysis of 135 patients Wenjian Tang, Yujin Yin, Chunju Wen, Jinsheng Huang, Bo Lan, Yuan Kang, and 13 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4725107/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Purpose: To assess clinical data and preoperative CT findings associated with prognosis in sarcomatoid-NSCLC (s-NSCLC) patients. Material and Methods: In this retrospective study, s-NSCLC patients who underwent contrast enhanced thoracic CT or PET/CT from January 2013 to June 2023 at three centers were enrolled. Clinicoradiological data, including sex, age, smoking history, TNM classification, tumor size, tumor location, calcification, vacuole/cavity, pleural invasion, low-attenuation area (LAA) ratio, hydrothorax, peritumoral ground-glass opacity (GGO), nodule or atelectasis and SUV max were calculated. Clinicoradiological findings associated with overall survival were evaluated by a multivariate Cox regression model. Results: A total of 135 with s-NSCLC were included. The s-NSCLC patients were more likely to be elderly male smokers. The mean age and tumor size at diagnosis was 62 years and 5.8 cm. The median survival time of patients with s-NSCLC was 9 (95% CI: 7, 11) months. The 1-, 3- and 5-year overall survival (OS) rates of the s-NSCLC patients were 28.9%, 11.9% and 5.9%, respectively. s-NSCLC is often peripherally locate (98/135, 70.4%). Calcification (19/135, 14.1%) and Vacuole/cavity (22/135, 16.2%) were rare in s-NSCLC lesions. Pleural invasion and hydrothorax was present in 75/135 (55.6%) and 36/135 (26.7%) of s-NSCLC patients. The s-NSCLC lesions usually present with LAA (87/135, 80.6%), the median LAA ratio was 30.8% (IQR: 10.6%, 50.7%). The SUV max of s-NSCLC lesions were 20.2 (IQR: 14.0, 23.9). Surgical treatment [hazard ratio (HR) = 0.518] was associated with decreased mortality, while peritumoral GGO, nodule or atelectasis (HR = 1.995) were associated with increased mortality. Conclusions: Peritumoral GGO, nodule or atelectasis is an independent risk indicator associated with poor prognosis, while complete surgical resection is essential for improving the prognosis in s-NSCLC patients. Pulmonary sarcomatoid carcinoma Non-small cell lung cancer Computed tomography Prognosis Figures Figure 1 Figure 2 Figure 3 Introduction Pulmonary sarcomatoid carcinoma is a rare subtype of non-small cell lung cancer (NSCLC) characterized by both epithelial and mesenchymal (> 10%) components and accounts for 0.4% of all lung malignancies [ 1 , 2 ]. Although sarcomatoid-NSCLC (s-NSCLC) have biphasic components, the tumors are of monoclonal origin and are differentiated from totipotent epithelial stem cells that undergo sarcomatous transformation [ 3 – 5 ]. Interestingly, sarcomatoid carcinoma is thought to be a final common pathway for carcinoma of epithelial origin: the majority of human carcinoma, if they proliferate unlimitedly without killing the host, theoretically develop into sarcomatoid carcinomas [ 6 ]. As a highly heterogeneity subtype, s-NSCLC is often diagnosed in an advanced stage, has a poor response to chemotherapy and therefore has a worse prognosis compared to other subtype of NSCLC [ 1 , 7 – 9 ]. Therefore, preoperative CT diagnosis of s-NSCLC is of great significance in clinical practice. Needle biopsy is the gold standard for diagnosis, but it is an invasive procedure. Thoracic CT scans are a noninvasive method for the routine detection of tumor lesions and are helpful for TNM classification during clinical management decisions. However, systematic reports on CT diagnosis of s-NSCLC are lacking. In previous studies, CT findings of s-NSCLC were first reported by Kim et al.[ 10 ], who reported that 8 of 10 patients had a low attenuation area (LAA). Subsequent research has consistently revealed that s-NSCLC often presence of LAA and peritumoral ground glass opacity (GGO). [ 11 – 13 ]. Given the rarity of s-NSCLC, the previous reports were constrained by a limited sample size. Our study based on multicenter data, the clinical and CT findings of s-NSCLC patients were analyzed to a) improve the accuracy of preoperative CT diagnosis and enhance our understanding of s-NSCLC; and b) explored the prognostic risk indicators associated with the clinicoradiological outcomes and provide reference for treatment decisions and prognostic evaluation. Materials and Methods Patients This retrospective study was approved by the institutional review board (IRB no. TY-ZKY2002-045-01) and the requirement for written informed consent was waived. s-NSCLC patients were collected at 3 institutions (institution 1: Southern Medical University Nanfang Hospital; institution 2: Ganzhou People's Hospital; institution 3: the First Affiliated Hospital of Gannan Medical University) from January 2013 to June 2023. The inclusion criteria were as follows: (1) the diagnosis was confirmed by light microscopic findings and immunohistochemistry; and (2) CT or/and 18 F-FDG PET/CT were performed before treatment. The exclusion criteria were as follows: (1) patients who underwent treatment before CT examination; (2) poor image quality or missing images and (3) lost to follow-up. Clinical data, including sex, age, smoking status and long-term follow-up, were reviewed and recorded by six of the authors (WT, CW, BL, JH, ZZ, JW). The tumors were classified and staged according to the 8th edition of the Tumor-Node-Metastasis (TNM) classification. The molecular subtypes of s-NSCLC were determined by next-generation sequencing. CT and PET/CT image acquisition CT images were obtained by using 64-detector row CT scanner (Somaton Definition AS + ; Siemens Healthineers), and 256-row multidetector CT scanner (Revolution CT; GE Healthcare and Brilliance iCT; Philips Medical systems) at 3 institutions. The CT scan protocol were as follows: the tube voltage was 100–120 kV, the tube current was automatically adjusted, the matrix was 512×512, the reconstructed slice thickness was 1.25 mm. Plain scan (PS), arterial phase (AP) and venous phase (VP) images were obtained. AP and VP scans were performed at 25 seconds and 60 seconds after contrast injection. PET/CT scans were performed on a Biograph 64 system (Siemens). After the patients had fasted for more than 6 hours, the 18F-FDG imaging agent 0.1–0.15 mCi/kg was intravenously injected. After 60 minutes of quiet rest, whole-body PET and CT were performed. The CT scan data were as follows: 120 kV, the tube current was automatically adjusted, the matrix was 512×512, 3 mm-thick axial slice. CT scan interpretation In this study, three radiologists (SL, ZL and YY) with more than 8 years of experience in chest CT diagnosis retrospectively reviewed the CT images and evaluated the tumor size, location, calcification, vacuole/cavity, pleural invasion, LAA, and peritumoral GGO, nodule (Fig. 1a) or atelectasis. Mediastinal window images were used for analysis (WW 350 Hu and WL 40 Hu). Three radiologists were blinded to the pathological findings. For surgical resection patients , pleural invasion was determined according to the pathological results. For needle biopsy patients, pleural invasion was considered if the boundary between the mass and visceral pleura was not clear on enhanced CT. In largest tumor layer, the largest tumor size was measured in the PACS. The parameters measured by the three radiologists were averaged. According to previous studies [ 10 , 13 , 14 ], LAA can be characterized by liquid or equal density on plain scans with no enhancement, while the peripheral solid component is significantly enhanced. Regions of interest (ROI) of the largest tumor area and largest LAA were outlined in the VP sequence. The LAA ratio was defined as the percentage of LAA to the tumor area (Fig. 1b-d). The final result was the mean value measured by three radiologists. The absence of GOO or GGO with a diameter <1cm in peritumoral area was considered as negative, while GGO (diameter ≥ 1cm) was considered as positive. In cases of disagreement, three radiologists reached a consensus through discussion. Statistical analysis The statistical analysis was performed using the SPSS version 23.0 (IBM Corp, Armonk, NY, USA) and R software (version 4.2.1, https://www.r-project.org/) for Windows. Normally distributed data are expressed as mean ± standard deviation, otherwise as median (interquartile range, IQR: M p25 , M p75 ). The Kaplan‒Meier method was used to calculate the median survival time. The overall survival time (OS) in s-NSCLC patients were analyzed by Log-Rank tests. Prognostic risk factors associated with OS were evaluated by a multivariate Cox regression model. P < 0.05 was considered to indicate statistical significance. Results Clinical and CT findings of s-NSCLC A total of 135 patients with s-NSCLC confirmed by postoperative pathology (55 patients) and needle biopsy (80 patients) were included. There were 108 males and 27 females in the s-NSCLC patients. The age of s-NSCLC group was 62 ± 10 (range 29-88). A total of 108 patients with s-NSCLC underwent enhanced CT scans. Twenty-eight patients with s-NSCLC underwent 18 F-FDG PET/CT. The mean tumor sizes were 5.8 ± 2.6 cm (range 2.0-14.5 cm). Smoking status accounted for 68.1% (92/135) of s-NSCLC patients. Ninety-eight cases located in peripheral and 37 cases located in central. Calcification (19/135, 14.1%) and Vacuole/cavity (22/135, 16.2%) were rare in s-NSCLC lesions. Among the 135 s-NSCLC patients, 75 (55.6%) had pleural invasion and 36 (26.7%) had hydrothorax. Peritumoral GOO, nodule or atelectasis were present in 31/135 (23.0%) of patients. Out of the 108 patients who underwent enhanced CT scans, 84 (77.8%) patients presented with LAA. The LAA ratios of s-NSCLC patients were 30.8% (IQR: 10.6%, 50.7%). On 18 F-FDG PET/CT, the SUV max of s-NSCLC ranged from 6.2 to 36.8, with median SUV max of 20.2 (IQR: 14.0, 23.9). TNM classification Among the s-NSCLC patients, 8 had stage I according to the TNM classification (IA 3 : 2, IB: 6), 20 had stage II (IIA: 10, IIB: 10), 59 had stage III (IIIA: 21, IIIB: 27, IIIC: 11) and 48 had stage IV. The tumor status was T1 in 4 patients (T1c), T2 in 36 patients (T2a: 17, T2b: 19), T3 in 39 patients and T4 in 56 patients. The nodal status was N0 in 40 patients, N1 in 7 patients, N2 in 58 patients, and N3 in 30 patients. The M1 in 48 patients and M0 in 87 patients. Long-term survival The median survival times of patients with s-NSCLC were 9 months (95% CI: 7, 11). The 1-year, 3-year and 5-year OS for s-NSCLC patients were 28.9%, 11.9% and 5.9%, respectively. (Figure 2a) Smoking status ( P = 0.037), tumor size ( P < 0.001), calcification ( P = 0.021), pleural invasion ( P < 0.001), Peritumoral GGO, nodule or atelectasis ( P < 0.001), hydrothorax ( P < 0.001), surgery ( P < 0.001), overall stage ( P < 0.001), T factor ( P < 0.001), N factor ( P = 0.006) and M factor ( P < .001) were significantly associated with OS in s-NSCLC patients, while sex ( P = 0.192), age ( P = 0.090), location ( P = 0.063), cavity or vacuole ( P = 0.088), PET/CT SUV max ( P = 0.711) found no evidence of differences associated with OS. The LAA ratio was not associated with prognosis of s-NSCLC ( P = 0.211) (Figure 3a-d for example). The eleven characteristics with significant differences ( P < 0.05) were included in the multivariate Cox model. Surgery ( P = 0.035, HR = 0.514 [95% CI: 0.285, 0.928]) and peritumoral GOO, nodule or atelectasis ( P = 0.038, HR = 1.995 [95% CI: 1.040, 3.829]) were found to be independently associated with prognosis (Figure 2b-c). Neither pleural invasion ( P = 0.496), hydrothorax ( P = 0.731), T factor ( P = 0.835), N factor ( P = 0.414), M factor ( P = 0.421) nor overall stage ( P = 0.172) was an independent risk factor for s-NSCLC (Table 1 in detail). Table 1. Univariate and multivariate analyses of overall survival in s-NCLCS patients. Characteristic Univariate Multivariate n P -value P -value HR 95% CI Clinical characteristics Sex (male vs. female) Age (＜60y vs. ≥60y) Smoking status (- vs. +) 108 vs. 27 50 vs. 85 43 vs. 92 0.192 0.090 0.037 0.056 Radiological findings Size (＜5cm vs. ≥5cm) Location (peripheral vs. central) Calcification (- vs. +) Cavity or vacuole (- vs. +) LAA (- vs. +) LAA ratio (＜10% vs. 10-50% vs. >50%) Pleural invasion (- vs. +) Peritumoral GGO, nodule or atelectasis (- vs. +) Hydrothorax (- vs. +) PET/CT SUV max (＜20 vs. ≥20) 56 vs. 79 98 vs. 37 116 vs. 19 113 vs. 22 24 vs. 84 26 vs. 54 vs. 28 60 vs. 75 104 vs. 31 99 vs. 36 14 vs. 14 < 0.001 0.063 0.021 0.088 0.211 0.360 < 0.001 < 0.001 < 0.001 0.711 0.056 0.374 0.496 0.038 0.731 1.995 1.040-3.829 Treatment Surgery (- vs. +) 80 vs. 55 < 0.001 0.035 0.518 0.282-0.954 TNM classification Overall stage (I-II vs. III vs. IV) T factor (T1-2 vs. T3 vs. T4) N factor (- vs. +) M factor (- vs. +) 28 vs.59 vs. 48 40 vs.39 vs. 56 40 vs. 95 87 vs. 48 < 0.001 < 0.001 0.006 < 0.001 0.172 0.835 0.414 0.421 n: number of patients; HR: hazard ratio; CI: confidence interval; LAA: low-attenuation area; GGO: ground-glass opacity Molecular findings of s-NSCLC Molecular alterations were detected in 15 patients with s-NSCLC. PD-L1 overexpression occurred in four patients. EGFR mutations were detected in 4 patients. KRAS mutations were detected in 3 patients. Both MET exon14 skipping (Figure 3e for example) and ALK mutations were found in 2 patients. The PIK3CA mutation was detected in one patient. The EGFR (exon19-del and exon21-L861Q) + PIK3CA (exon20-H12047R and exon9-E545K) fusion mutation was found in one patient. The ALK (exon23-L1187M) + TP53 (exon5-Y163C) fusion mutation was found in one patient. KRAS (exon2) + TP53 (exon4) missense mutation were found in one patient (Table 2 in detail). Table 2 Molecular findings and c linicoradiological data of s-NSCLC patients Case No. Age (y) Sex Smoking status Size (cm) LAA ratio Metastatic sites TNM stage Surgery Survival time (mo) Molecular findings 1 53 F - 4.1 0 Brain T2bN0M1b (IVA) - 17 (dead) EGFR exon21-L858R 2 56 F + 6.9 0.226 - T3N0M0 (IIB) + 12 (alive) EGFR (exon19-del and exon21-L861Q) + PIK3CA (exon20-H12047R and exon9-E545K) 3 48 F - 5.1 0.133 Pleural T3N2M1a (IVA) - 9 (dead) EGFR exon19-del 4 61 M + 5.7 0.87 Contralateral lung lobe, liver, and adrenal gland T4N3M1c (IVB) - 3 (dead) EGFR (exon21-L858R + exon20-T790M) 5 46 F - 5.2 0 - T3N2M0 (IIIB) + 24 (alive) ALK 6 75 M + 9.4 0.673 Liver T4N2M1b (IVA) - 5 (dead) ALK (exon23-L1187M) + TP53 (exon5-Y163C) 7 65 F - 8.7 0.368 Pleural T4N2M1a (IVA) - 7 (alive) EML4-ALK (exon6-exon20) 8 64 M + 7.8 - The left vertebral arch of lumbar 2 T4N2M1b (IVA) - 5 (dead) MET exon14 skipping 9 72 F - 4.5 0.224 Brain T2bN0M1b (IVA) - 2 (dead) MET exon14 skipping 10 88 M + 5.1 0.342 Liver T4N3M1b (IVA) - 1.5 (dead) PIK3CA(exon20-H12047R + exon9-E545K) 11 72 M + 6.4 0.87 - T4N2M0 (IIIB) - 2 (dead) PD-L1 overexpression 12 64 M - 4.8 0.544 Brain,bone and Adrenal gland T2bN3M1c (IVB) - 22 (alive) KRAS + PD-L1 overexpression 13 59 M + 2.3 0.464 - T4N3M0 (IIIC) - 11 (alive) KRAS (G12C) + PD-L1 overexpression 14 60 M - 5.0 - - T3N3M0 (IIIC) - 8 (dead) KRAS exon2 + TP53 exon4 + PD-L1 overexpression 15 70 M - 7.0 - Bone and muscles of the left thigh T3N1M1c (IVB) - 6 (dead) KRAS Note: (+) = present, (-) = absent Discussion According to the latest WHO classification of lung neoplasms in 2021, s-NSCLC can be categorized into three pathological subtypes: pleomorphic carcinoma (formed by spindle or/and giant cells), carcinosarcoma, and pulmonary blastoma [ 15 ]. s-NSCLC is a rare subtype of NSCLC but possesses distinct characteristics. Our study has shown that s-NSCLC patients were more likely to be male smokers, with a male-to-female ratio of 4:1. Among the s-NSCLC patients, the mean age at diagnosis was 62 years, and the mean tumor size was 5.8 cm. Median survival time of s-NSCLC patients was only 9 months (95% CI: 7, 11), 48/135 (35.6%) of s-NSCLC cases had stage IV disease at diagnosis and the 1-, 3- and 5-year OS rates in s-NSCLC patients were 28.9%, 11.9% and 5.9%, respectively. Our clinical findings are similar to previous studies [ 7 , 8 , 13 , 16 , 17 ], which reveals that these tumors are diagnosed at an advanced stage, leading to missed opportunities for surgical treatment. Our study revealed that surgical treatment was associated with decreased mortality, consistent with the findings of previous studies [ 14 , 19 ]. Interestingly, this study revealed that the TNM stage was not an independent risk factor for prognosis. Most s-NSCLC patients (96/135, 71.1%) in this study died within one year. Regardless of the TNM stage, this highly malignant tumor progresses rapidly, recurs postoperatively and early metastasis, leading to short-term mortality. In our study, preoperative CT findings showed that calcification (19 of 135, 14.1%) and vacuole/cavity (22 of 135, 16.3%) were rare in s-NSCLC patients, which was consistent with the findings of previous studies [ 12 , 16 ]. Previous studies have reported that s-NSCLC is prone to pleural invasion: Kim et al.[ 10 ] showed that pleural invasion occurred in 7/10 (70%) of s-NSCLC patients. In the study of Fujisaki et al. [ 13 ] found that pleural invasion was present in 19/44 (43%) of the patients. In our study, 75/135 (55.6%) of the s-NSCLC patients had pleural invasion. This may be due to the larger size of s-NSCLC: when the tumor is large enough, the pleural invasion is theoretically occurred. Our study revealed that the majority of s-NSCLC lesions presented with LAA (87 of 108, 80.6%). Kim et al. [ 10 ] reported that 8/10 (80%) of s-NSCLC lesions had LAA lesions. Fujisaki et al. [ 13 ] showed the presence of LAA in 40/44 (91%) of s-NSCLC patients, which was similar to the findings of our study. Furthermore, the median of LAA ratio was 30.8% in s-NSCLC patients. The pathological manifestations of LAA were mucinous degeneration, necrosis, and hemorrhage, suggesting that rapid proliferation exceeded the blood supply [ 10 , 12 ]. In previous studies, the LAA ratio was found to be an independent risk factor for s-NSCLC: LAA ratio > 25% was associated with shorter OS and disease-free survival than LAA ratio < 25% [ 13 ]. A study by Nishida et al. [ 12 ] reached a similar conclusion. However, the LAA ratio was not associated with OS in our study. In previous studies, all s-NSCLC patients included underwent surgical resection. However, in our study, the majority of patients with s-NSCLC were in an advanced stage. We analyzed surgical cases individually but did not find a correlation between LAA and prognosis, either. This may be due to the fact that s-NSCLC is prone to metastasis, and these lesions have not yet grown large enough to form LAA when distant metastasis occurs, leading to death in the short term. In our study, peritumoral GGO, nodule or atelectasis found to be independent risk indicators associated with prognosis in s-NSCLC patients. This distinctive CT findings indicates tumor invasion into surrounding tissues, bronchial involvement, and peritumoral metastasis, all of which are indicative of the tumor's high degree of aggressiveness and metastatic potential. Nishida et al. [ 12 ] discovered that GGO can be observed across all subtypes of s-NSCLC, the pathological features associated with GGO are hemorrhage, vascular invasion, and aerogenous metastases. However, this study did not found a relationship between GGO and prognosis. This could be attributed to the fact that the study focused solely on surgically treated cases, excluding those advanced-stage patients with more severe peritumoral invasion. Our study found that the SUV max was not associated with the prognosis in s-NSCLC patients. Our results are similar to those of Rapicetta et al. [ 18 ]. However, Kim et al.[ 19 ] pointed out that a high SUV max is associated with poor prognosis in s-NSCLC patients. Interestingly, the SUV max was useful for evaluating PD-L1 and KRAS expression in s-NSCLC [ 20 ]. The correlations among the SUV max , molecular findings and prognosis of s-NSCLC patients warrant further study. In recent years, the molecular targeted therapy and immunotherapy have attracted much attention in clinical applications among s-NSCLC patients. EGFR and ALK are well-known examples where appropriate tyrosine kinase inhibitor (TKI) therapy improves patient quality of life and survival [ 21 ]. EGFR mutations were detected in 16% of s-NSCLC patients, the EGFR exon21-L861Q mutation is a rare subtype and may benefit from afatinib [ 22 , 23 ]. Lococo F et al. [ 24 ] showed that TP53 gene mutations occur in 55% of s-NSCLC patients but are not the driver gene for s-NSCLC; the increased genetic instability of TP53 gene may lead to the occurrence of s-NSCLC. MET exon14 skipping mutation (31.8%) and high-level MET amplification (13.6%) was found in s-NSCLC patients, leading to epithelial-mesenchymal transformation of cells and resistance chemotherapy and TKIs [ 21 , 22 ]. Furthermore, MET exon14 skipping mutation and PD-L1 overexpression are considered crucial genetic events contributing to the sarcomatoid transformation of c-NSCLC [ 25 – 27 ], which revealed the importance of molecular targeted therapy and immunotherapy for s-NSCLC patients. KRAS mutations were found to be a marker of poor prognosis in s-NSCLC patients [ 24 ]. However, two patients in our study with KRAS (G12C) + PD-L1 overexpression had relatively long survival after targeted and immunotherapy therapy, this indicates that the combination of molecular targeted therapy and immunotherapy has achieved favorable benefits in this population. PIK3CA-H12047R expression alone cannot promote tumor formation but significantly enhances tumorigenesis initiated by KRAS, considered a direct effector that promotes KRAS-driven lung tumorigenesis [ 28 ]. The molecular findings in this study hold the potential to deepen our understanding of s-NSCLC. This study has several limitations. Firstly, this is a retrospective study and selection bias is inevitable, prospective and randomized study is still needed. Secondly, treatment were not included in the prognostic analysis. This retrospective study dates back more than 10 years, and the treatment guidelines have changed greatly. Prospective studies with uniform treatment standards are needed in the future. In conclusion, the presence of large intratumoral LAA ratio and peritumoral GGO, nodule or atelectasis were a distinctive CT sign for s-NSCLC. Moreover, Peritumoral GGO, nodule or atelectasis is an independent risk indicator associated with poor prognosis, while complete surgical resection is essential for improving the prognosis in s-NSCLC patients. However, the LAA ratio was not a prognostic indicator for s-NSCLC. These findings are helpful for preoperative CT diagnosis of s-NSCLC and provide a reference for clinical treatment strategies and prognostic evaluation. Abbreviations NSCLC non-small cell lung cancer s-NSCLC sarcomatoid-NSCLC LAA low attenuation area GGO ground-glass opacity 18F-FDG PET/CT 18F-fluoro-D-glucose positron emission tomography/computed tomography SUVmax maximum Standardized Uptake Value IQR interquartile range CI confidence interval OS overall survival HR hazard ratio. TKI tyrosine kinase inhibitor Declarations Acknowledgements Not applicable Author contributions Wenjian Tang, Jianping Zhong and Junyuan Zhong, study concept and design; All authors contributed to data collection or data curation; Wenjian Tang. Yujin Yin and Chunju Wen, data analysis and manuscript preparation; All authors read and approval of final manuscript. Funding This study has received funding from the National Natural Science Foundation of China (82160330), the Natural Science Foundation of Jiangxi Province (20202ACBL216006), the Ganzhou Health Commission Scientific Research Planning Project (GZWJW202402108), and the Ganzhou Health Commission Scientific Research Planning Project (GZWJW202402120). Data availability The datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request. Ethics approval and consent to participate The institutional review board of Ganzhou People’s Hospital (IRB no.TY-ZKY2022-045-01) approved the study and waived the requirement for written informed consent. All methods were carried out in accordance with Declaration of Helsinki. Competing interests The authors declare that they have no conflict of interest. References Yendamuri S, Caty L, Pine M, et al. Outcomes of sarcomatoid carcinoma of the lung: a Surveillance, Epidemiology, and End Results Database analysis. Surgery 2012;152(3):397-402. Pelosi G, Sonzogni A, De Pas T, et al. Review article: pulmonary sarcomatoid carcinomas: a practical overview. Int J Surg Pathol 2010;18(2):103-120. Takahashi K, Kohno T, Matsumoto S, et al. Clonality and heterogeneity of pulmonary blastoma from the viewpoint of genetic alterations: a case report. Lung Cancer 2007;57(1):103-8. de Kock L, Bah I, Brunet J, et al. Somatic DICER1 mutations in adult-onset pulmonary blastoma. 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Ann Oncol 2017;28(7):1417-1418. Green S, Trejo CL, McMahon M. PIK3CA(H1047R) Accelerates and Enhances KRAS(G12D)-Driven Lung Tumorigenesis. Cancer Res 2015;75(24):5378-5391. Additional Declarations No competing interests reported. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-4725107","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":327557709,"identity":"40872d9f-d8b8-4318-b149-ce8cef3ba07d","order_by":0,"name":"Wenjian Tang","email":"","orcid":"","institution":"Ganzhou People's Hospital, The Affiliated Ganzhou Hospital of Nanchang University","correspondingAuthor":false,"prefix":"","firstName":"Wenjian","middleName":"","lastName":"Tang","suffix":""},{"id":327557710,"identity":"295225dd-4b0f-4e0f-8111-aeb7fa483ef8","order_by":1,"name":"Yujin Yin","email":"","orcid":"","institution":"Ganzhou People's Hospital, The Affiliated Ganzhou Hospital of Nanchang University","correspondingAuthor":false,"prefix":"","firstName":"Yujin","middleName":"","lastName":"Yin","suffix":""},{"id":327557711,"identity":"0f0f2f7a-5b78-46e8-a140-d0bd156ee785","order_by":2,"name":"Chunju Wen","email":"","orcid":"","institution":"Ganzhou People's Hospital, The Affiliated Ganzhou Hospital of Nanchang University","correspondingAuthor":false,"prefix":"","firstName":"Chunju","middleName":"","lastName":"Wen","suffix":""},{"id":327557712,"identity":"3d318d65-fb6a-4a0a-a8a8-ee2d70dd3842","order_by":3,"name":"Jinsheng Huang","email":"","orcid":"","institution":"Ganzhou People's Hospital, The Affiliated Ganzhou Hospital of Nanchang University","correspondingAuthor":false,"prefix":"","firstName":"Jinsheng","middleName":"","lastName":"Huang","suffix":""},{"id":327557713,"identity":"cf733cab-4d37-4021-8c5f-19822d19a456","order_by":4,"name":"Bo Lan","email":"","orcid":"","institution":"Ganzhou People's Hospital, The Affiliated Ganzhou Hospital of Nanchang University","correspondingAuthor":false,"prefix":"","firstName":"Bo","middleName":"","lastName":"Lan","suffix":""},{"id":327557714,"identity":"1f122e96-0e28-422b-8998-ce7933821826","order_by":5,"name":"Yuan Kang","email":"","orcid":"","institution":"Ganzhou People's Hospital, The Affiliated Ganzhou Hospital of Nanchang University","correspondingAuthor":false,"prefix":"","firstName":"Yuan","middleName":"","lastName":"Kang","suffix":""},{"id":327557715,"identity":"b72ebb9f-f893-4f01-975c-6984aae48529","order_by":6,"name":"Zhiqiang Zhang","email":"","orcid":"","institution":"Ganzhou People's Hospital, The Affiliated Ganzhou Hospital of Nanchang University","correspondingAuthor":false,"prefix":"","firstName":"Zhiqiang","middleName":"","lastName":"Zhang","suffix":""},{"id":327557716,"identity":"b128a1ad-72d1-4881-9fb8-01253b49fe50","order_by":7,"name":"zhongjian Liao","email":"","orcid":"","institution":"Ganzhou People's Hospital, The Affiliated Ganzhou Hospital of Nanchang University","correspondingAuthor":false,"prefix":"","firstName":"zhongjian","middleName":"","lastName":"Liao","suffix":""},{"id":327557717,"identity":"6af8ac91-bf92-43a7-b506-4c2866ec2730","order_by":8,"name":"Zhen Wu","email":"","orcid":"","institution":"Ganzhou People's Hospital, The Affiliated Ganzhou Hospital of Nanchang University","correspondingAuthor":false,"prefix":"","firstName":"Zhen","middleName":"","lastName":"Wu","suffix":""},{"id":327557718,"identity":"3836515a-354e-4bcc-9e40-2d1095f6f6cc","order_by":9,"name":"Qing Chen","email":"","orcid":"","institution":"Ganzhou People's Hospital, The Affiliated Ganzhou Hospital of Nanchang University","correspondingAuthor":false,"prefix":"","firstName":"Qing","middleName":"","lastName":"Chen","suffix":""},{"id":327557719,"identity":"0750a7f5-f7be-4a56-98c4-542e9f632fe9","order_by":10,"name":"Jiawang Wei","email":"","orcid":"","institution":"Ganzhou People's Hospital, The Affiliated Ganzhou Hospital of Nanchang University","correspondingAuthor":false,"prefix":"","firstName":"Jiawang","middleName":"","lastName":"Wei","suffix":""},{"id":327557720,"identity":"a415c17e-c75c-4f74-b2a3-3ee28eb85f95","order_by":11,"name":"Jing Qiu","email":"","orcid":"","institution":"First Affiliated Hospital of Gannan Medical University","correspondingAuthor":false,"prefix":"","firstName":"Jing","middleName":"","lastName":"Qiu","suffix":""},{"id":327557721,"identity":"ff5a95d7-32fb-469b-bd15-36cf2643269b","order_by":12,"name":"Xingting Qiu","email":"","orcid":"","institution":"First Affiliated Hospital of Gannan Medical University","correspondingAuthor":false,"prefix":"","firstName":"Xingting","middleName":"","lastName":"Qiu","suffix":""},{"id":327557722,"identity":"ffce4daf-dfda-4ab6-bf12-2cff6ee93e24","order_by":13,"name":"Hua Chen","email":"","orcid":"","institution":"Ganzhou People's Hospital, The Affiliated Ganzhou Hospital of Nanchang University","correspondingAuthor":false,"prefix":"","firstName":"Hua","middleName":"","lastName":"Chen","suffix":""},{"id":327557723,"identity":"60fc81ae-d07b-484d-b26c-e2ea60c3a2fe","order_by":14,"name":"Shuhua Luo","email":"","orcid":"","institution":"Ganzhou People's Hospital, The Affiliated Ganzhou Hospital of Nanchang University","correspondingAuthor":false,"prefix":"","firstName":"Shuhua","middleName":"","lastName":"Luo","suffix":""},{"id":327557724,"identity":"9b5277f9-c40f-4db1-afae-2cd9996bfdfd","order_by":15,"name":"Jidong Peng","email":"","orcid":"","institution":"Ganzhou People's Hospital, The Affiliated Ganzhou Hospital of Nanchang University","correspondingAuthor":false,"prefix":"","firstName":"Jidong","middleName":"","lastName":"Peng","suffix":""},{"id":327557725,"identity":"0fd106c9-4edc-4810-b47a-cd3543255b91","order_by":16,"name":"Junyuan Zhong","email":"","orcid":"","institution":"Ganzhou People's Hospital, The Affiliated Ganzhou Hospital of Nanchang University","correspondingAuthor":false,"prefix":"","firstName":"Junyuan","middleName":"","lastName":"Zhong","suffix":""},{"id":327557726,"identity":"e3b72c4e-5420-4394-ae62-6247c5f5ab16","order_by":17,"name":"Ming Jia","email":"","orcid":"","institution":"Southern Medical University Nanfang Hospital","correspondingAuthor":false,"prefix":"","firstName":"Ming","middleName":"","lastName":"Jia","suffix":""},{"id":327557727,"identity":"bf26199f-a690-4bda-80f3-dd5fe2676e2f","order_by":18,"name":"Jianping Zhong","email":"data:image/png;base64,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","orcid":"","institution":"Ganzhou People's Hospital, The Affiliated Ganzhou Hospital of Nanchang University","correspondingAuthor":true,"prefix":"","firstName":"Jianping","middleName":"","lastName":"Zhong","suffix":""}],"badges":[],"createdAt":"2024-07-11 15:20:55","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4725107/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4725107/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":62217107,"identity":"40360fd3-89f2-476e-b814-e664a28928a3","added_by":"auto","created_at":"2024-08-11 11:52:20","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":872534,"visible":true,"origin":"","legend":"\u003cp\u003eCT and pathological findings of s-NSCLC. \u003cstrong\u003ea) \u003c/strong\u003eA 54-year-old male patient presented with GGO and multiple nodules below the lesion in the upper lobe of the right lung. Despite surgery treatment, the patient died at 8 months of follow-up. \u003cstrong\u003e(b) \u003c/strong\u003eMeasurement of the LAA ratio in the VP image. The LAA ratio was defined as the percentage of the largest low-attenuation area (green ring) to the largest tumor area (red ring). In this pleomorphic case, the LAA ratio was 61%. This is a 68-year-old female patient with stage T2aN0M0 died after 14 months of follow-up. \u003cstrong\u003e(c)\u003c/strong\u003e At low magnification, large areas of coagulative necrosis appeared in the center of the tumor (HE ×20). \u003cstrong\u003e(d)\u003c/strong\u003eAdenocarcinoma cells with mesenchymal transformation were observed at high magnification (HE ×200).\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-4725107/v1/2f97129d1bbb1f73a1b940af.png"},{"id":62216468,"identity":"6564ac07-c049-461b-9995-81fd7706d766","added_by":"auto","created_at":"2024-08-11 11:44:20","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":71992,"visible":true,"origin":"","legend":"\u003cp\u003eThe Kaplan‒Meier overall survival curves for s-NSCLC \u003cstrong\u003e(a)\u003c/strong\u003e, stratified by peritumoral GGO, nodule or atelectasis \u003cstrong\u003e(b)\u003c/strong\u003e and surgery \u003cstrong\u003e(c)\u003c/strong\u003e.\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-4725107/v1/28f9ab489d34c73bb1d918c4.png"},{"id":62216470,"identity":"feff7710-41ee-439d-b8ca-b1ffc7532e09","added_by":"auto","created_at":"2024-08-11 11:44:21","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":635446,"visible":true,"origin":"","legend":"\u003cp\u003eCase presentation of s-NSCLC patients\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e(a)-(b)\u003c/strong\u003e A 79-year-old man with a lesion in the left upper lobe of the lung invading the soft tissue of the chest wall and adjacent ribs. The lesion had a large LAA ratio (51.6%). Complete resection of the lesion and extended resection of the adjacent ribs were performed. The postoperative stage was T4N0M0. The patient was still alive at the 75-month follow-up.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e(c)-(d)\u003c/strong\u003e A 53-year-old female patient with carcinosarcoma and EGFR (exon21-L858R) mutation was confirmed by biopsy. The tumor lesion in the venous phase showed heterogeneous and delayed enhancement without the LAA. Brain MRI showed multiple ring-enhanced metastatic lesions. The PET/CT SUVmax of the lesion was 21.9. The patient died at 17 months of follow-up.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e(e)\u003c/strong\u003e A 64-year-old female with a MET 14 exon skipping mutation. The PET/CT SUVmax of the lesion was 36.8. A metastatic lesion was found in the left vertebral arch of lumbar 2 (red arrows with enlarged view). The patient died at 5 months of follow-up.\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-4725107/v1/7947326bdfb4b500b407cddc.png"},{"id":73900981,"identity":"850a9923-2bbc-4f30-889a-9ac7f470466c","added_by":"auto","created_at":"2025-01-15 17:23:47","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":2685385,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4725107/v1/727367c9-e77c-43f6-b24a-887efad1c8c0.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Clinicoradiological findings associated with prognostic indicators of sarcomatoid-NSCLC: A multicenter analysis of 135 patients","fulltext":[{"header":"Introduction","content":"\u003cp\u003ePulmonary sarcomatoid carcinoma is a rare subtype of non-small cell lung cancer (NSCLC) characterized by both epithelial and mesenchymal (\u0026gt;\u0026thinsp;10%) components and accounts for 0.4% of all lung malignancies [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. Although sarcomatoid-NSCLC (s-NSCLC) have biphasic components, the tumors are of monoclonal origin and are differentiated from totipotent epithelial stem cells that undergo sarcomatous transformation [\u003cspan additionalcitationids=\"CR4\" citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. Interestingly, sarcomatoid carcinoma is thought to be a final common pathway for carcinoma of epithelial origin: the majority of human carcinoma, if they proliferate unlimitedly without killing the host, theoretically develop into sarcomatoid carcinomas [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. As a highly heterogeneity subtype, s-NSCLC is often diagnosed in an advanced stage, has a poor response to chemotherapy and therefore has a worse prognosis compared to other subtype of NSCLC [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan additionalcitationids=\"CR8\" citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. Therefore, preoperative CT diagnosis of s-NSCLC is of great significance in clinical practice.\u003c/p\u003e \u003cp\u003eNeedle biopsy is the gold standard for diagnosis, but it is an invasive procedure. Thoracic CT scans are a noninvasive method for the routine detection of tumor lesions and are helpful for TNM classification during clinical management decisions. However, systematic reports on CT diagnosis of s-NSCLC are lacking. In previous studies, CT findings of s-NSCLC were first reported by Kim et al.[\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e], who reported that 8 of 10 patients had a low attenuation area (LAA). Subsequent research has consistently revealed that s-NSCLC often presence of LAA and peritumoral ground glass opacity (GGO). [\u003cspan additionalcitationids=\"CR12\" citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. Given the rarity of s-NSCLC, the previous reports were constrained by a limited sample size.\u003c/p\u003e \u003cp\u003eOur study based on multicenter data, the clinical and CT findings of s-NSCLC patients were analyzed to a) improve the accuracy of preoperative CT diagnosis and enhance our understanding of s-NSCLC; and b) explored the prognostic risk indicators associated with the clinicoradiological outcomes and provide reference for treatment decisions and prognostic evaluation.\u003c/p\u003e"},{"header":"Materials and Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\n \u003ch2\u003ePatients\u003c/h2\u003e\n \u003cp\u003eThis retrospective study was approved by the institutional review board (IRB no. TY-ZKY2002-045-01) and the requirement for written informed consent was waived.\u003c/p\u003e\n \u003cp\u003es-NSCLC patients were collected at 3 institutions (institution 1: Southern Medical University Nanfang Hospital; institution 2: Ganzhou People\u0026apos;s Hospital; institution 3: the First Affiliated Hospital of Gannan Medical University) from January 2013 to June 2023. The inclusion criteria were as follows: (1) the diagnosis was confirmed by light microscopic findings and immunohistochemistry; and (2) CT or/and \u003csup\u003e18\u003c/sup\u003eF-FDG PET/CT were performed before treatment. The exclusion criteria were as follows: (1) patients who underwent treatment before CT examination; (2) poor image quality or missing images and (3) lost to follow-up.\u003c/p\u003e\n \u003cp\u003eClinical data, including sex, age, smoking status and long-term follow-up, were reviewed and recorded by six of the authors (WT, CW, BL, JH, ZZ, JW). The tumors were classified and staged according to the 8th edition of the Tumor-Node-Metastasis (TNM) classification. The molecular subtypes of s-NSCLC were determined by next-generation sequencing.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec4\" class=\"Section2\"\u003e\n \u003ch2\u003eCT and PET/CT image acquisition\u003c/h2\u003e\n \u003cp\u003eCT images were obtained by using 64-detector row CT scanner (Somaton Definition AS\u003csub\u003e+\u003c/sub\u003e; Siemens Healthineers), and 256-row multidetector CT scanner (Revolution CT; GE Healthcare and Brilliance iCT; Philips Medical systems) at 3 institutions. The CT scan protocol were as follows: the tube voltage was 100\u0026ndash;120 kV, the tube current was automatically adjusted, the matrix was 512\u0026times;512, the reconstructed slice thickness was 1.25 mm. Plain scan (PS), arterial phase (AP) and venous phase (VP) images were obtained. AP and VP scans were performed at 25 seconds and 60 seconds after contrast injection.\u003c/p\u003e\n \u003cp\u003ePET/CT scans were performed on a Biograph 64 system (Siemens). After the patients had fasted for more than 6 hours, the 18F-FDG imaging agent 0.1\u0026ndash;0.15 mCi/kg was intravenously injected. After 60 minutes of quiet rest, whole-body PET and CT were performed. The CT scan data were as follows: 120 kV, the tube current was automatically adjusted, the matrix was 512\u0026times;512, 3 mm-thick axial slice.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec5\" class=\"Section2\"\u003e\n \u003ch2\u003eCT scan interpretation\u003c/h2\u003e\n \u003cp\u003eIn this study, three radiologists (SL, ZL and YY) with more than 8 years of experience in chest CT diagnosis retrospectively reviewed the CT images and evaluated the tumor size, location, calcification, vacuole/cavity, pleural invasion, LAA, and peritumoral GGO, nodule (Fig.\u0026nbsp;1a) or atelectasis. Mediastinal window images were used for analysis (WW 350 Hu and WL 40 Hu). Three radiologists were blinded to the pathological findings.\u003c/p\u003e\n \u003cp\u003eFor surgical resection \u003cspan class=\"InternalRef\"\u003epatients\u003c/span\u003e, pleural invasion was determined according to the pathological results. For needle biopsy patients, pleural invasion was considered if the boundary between the mass and visceral pleura was not clear on enhanced CT. In largest tumor layer, the largest tumor size was measured in the PACS. The parameters measured by the three radiologists were averaged.\u003c/p\u003e\n \u003cp\u003eAccording to previous studies [\u003cspan class=\"CitationRef\"\u003e10\u003c/span\u003e, \u003cspan class=\"CitationRef\"\u003e13\u003c/span\u003e, \u003cspan class=\"CitationRef\"\u003e14\u003c/span\u003e], LAA can be characterized by liquid or equal density on plain scans with no enhancement, while the peripheral solid component is significantly enhanced. Regions of interest (ROI) of the largest tumor area and largest LAA were outlined in the VP sequence. The LAA ratio was defined as the percentage of LAA to the tumor area (Fig.\u0026nbsp;1b-d). The final result was the mean value measured by three radiologists. The absence of GOO or GGO with a diameter \u0026lt;1cm in peritumoral area was considered as negative, while GGO (diameter\u0026thinsp;\u0026ge;\u0026thinsp;1cm) was considered as positive. In cases of disagreement, three radiologists reached a consensus through discussion.\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eStatistical analysis\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003eThe statistical analysis was performed using the SPSS version 23.0 (IBM Corp, Armonk, NY, USA) and R software (version 4.2.1, https://www.r-project.org/) for Windows.\u0026nbsp;Normally distributed data are expressed as\u0026nbsp;mean \u0026plusmn; standard deviation, otherwise as median (interquartile range, IQR: M\u003csub\u003ep25\u003c/sub\u003e,\u003csub\u003e\u0026nbsp;\u003c/sub\u003eM\u003csub\u003ep75\u003c/sub\u003e).\u0026nbsp;The Kaplan‒Meier method was used to calculate the median survival time. The overall survival time (OS) in s-NSCLC patients were analyzed by\u0026nbsp;\u003cem\u003eLog-Rank\u003c/em\u003e tests. Prognostic risk factors associated with OS were evaluated by a\u0026nbsp;multivariate\u0026nbsp;Cox regression model.\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003cem\u003eP\u0026nbsp;\u003c/em\u003e\u0026lt; 0.05 was considered to indicate statistical significance.\u003c/p\u003e\n\u003c/div\u003e"},{"header":"Results","content":"\u003cp\u003e\u003cstrong\u003eClinical and CT findings of s-NSCLC\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eA total of 135 patients with s-NSCLC confirmed by postoperative pathology (55 patients) and needle biopsy (80 patients) were included. There were 108 males and 27 females in the s-NSCLC patients. The age of s-NSCLC group was 62 \u0026plusmn; 10 (range 29-88).\u0026nbsp;A total of 108 patients with s-NSCLC underwent enhanced CT scans. Twenty-eight patients with s-NSCLC underwent \u003csup\u003e18\u003c/sup\u003eF-FDG PET/CT.\u003c/p\u003e\n\u003cp\u003eThe mean tumor sizes were 5.8 \u0026plusmn; 2.6 cm (range 2.0-14.5 cm). Smoking status accounted for 68.1% (92/135) of s-NSCLC patients. Ninety-eight cases located in peripheral and 37 cases located in central. Calcification (19/135, 14.1%) and Vacuole/cavity (22/135, 16.2%) were rare in s-NSCLC lesions. Among the 135 s-NSCLC patients, 75 (55.6%) had pleural invasion and 36 (26.7%) had hydrothorax. Peritumoral GOO, nodule or atelectasis were present in 31/135 (23.0%) of patients.\u003c/p\u003e\n\u003cp\u003eOut of the 108 patients who underwent enhanced CT scans, 84 (77.8%) patients presented with LAA. The LAA ratios of s-NSCLC patients were 30.8% (IQR: 10.6%, 50.7%). On \u003csup\u003e18\u003c/sup\u003eF-FDG PET/CT, the SUV\u003csub\u003emax\u003c/sub\u003e of s-NSCLC ranged from 6.2 to 36.8, with median SUV\u003csub\u003emax\u003c/sub\u003e of 20.2 (IQR: 14.0, 23.9).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTNM classification\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAmong the s-NSCLC patients, 8 had stage I according to the TNM classification (IA\u003csub\u003e3\u003c/sub\u003e: 2, IB: 6), 20 had stage II (IIA: 10, IIB: 10), 59 had stage III (IIIA: 21, IIIB: 27, IIIC: 11) and 48 had stage IV. The tumor status was T1 in 4 patients (T1c), T2 in 36 patients (T2a: 17, T2b: 19), T3 in 39 patients and T4 in 56 patients. The nodal status was N0 in 40 patients, N1 in 7 patients, N2 in 58 patients, and N3 in 30 patients. The M1 in 48 patients and M0 in 87 patients.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eLong-term survival\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe median survival times of patients with s-NSCLC were 9 months\u0026nbsp;(95% CI: 7, 11). The 1-year, 3-year and\u0026nbsp;5-year OS for s-NSCLC patients were 28.9%, 11.9% and 5.9%, respectively. (Figure 2a)\u003c/p\u003e\n\u003cp\u003eSmoking status (\u003cem\u003eP\u0026nbsp;\u003c/em\u003e= 0.037), tumor size (\u003cem\u003eP\u0026nbsp;\u003c/em\u003e\u0026lt; 0.001), calcification (\u003cem\u003eP\u0026nbsp;\u003c/em\u003e= 0.021), pleural invasion (\u003cem\u003eP\u0026nbsp;\u003c/em\u003e\u0026lt; 0.001), Peritumoral GGO, nodule or atelectasis (\u003cem\u003eP\u0026nbsp;\u003c/em\u003e\u0026lt; 0.001), hydrothorax (\u003cem\u003eP\u0026nbsp;\u003c/em\u003e\u0026lt; 0.001), surgery\u0026nbsp;(\u003cem\u003eP\u0026nbsp;\u003c/em\u003e\u0026lt; 0.001), overall stage (\u003cem\u003eP\u0026nbsp;\u003c/em\u003e\u0026lt; 0.001), T factor (\u003cem\u003eP\u0026nbsp;\u003c/em\u003e\u0026lt; 0.001), N factor (\u003cem\u003eP\u0026nbsp;\u003c/em\u003e= 0.006) and M factor (\u003cem\u003eP\u0026nbsp;\u003c/em\u003e\u0026lt; .001) were significantly associated with OS in s-NSCLC patients, while sex (\u003cem\u003eP\u0026nbsp;\u003c/em\u003e= 0.192), age (\u003cem\u003eP\u0026nbsp;\u003c/em\u003e= 0.090), location (\u003cem\u003eP\u0026nbsp;\u003c/em\u003e= 0.063), cavity or vacuole (\u003cem\u003eP\u0026nbsp;\u003c/em\u003e= 0.088), PET/CT SUV\u003csub\u003emax\u003c/sub\u003e (\u003cem\u003eP\u0026nbsp;\u003c/em\u003e= 0.711) found no evidence of differences associated with OS. The LAA ratio was not associated with prognosis of s-NSCLC (\u003cem\u003eP\u0026nbsp;\u003c/em\u003e= 0.211) (Figure 3a-d for example). The eleven characteristics with significant differences (\u003cem\u003eP\u0026nbsp;\u003c/em\u003e\u0026lt; 0.05) were included in the multivariate Cox model. Surgery (\u003cem\u003eP\u0026nbsp;\u003c/em\u003e= 0.035, HR = 0.514 [95% CI: 0.285, 0.928]) and peritumoral GOO, nodule or atelectasis (\u003cem\u003eP\u0026nbsp;\u003c/em\u003e= 0.038, HR = 1.995 [95% CI: 1.040, 3.829]) were found to be independently associated with prognosis (Figure 2b-c). Neither pleural invasion (\u003cem\u003eP\u0026nbsp;\u003c/em\u003e= 0.496), hydrothorax (\u003cem\u003eP\u0026nbsp;\u003c/em\u003e= 0.731), T factor (\u003cem\u003eP\u0026nbsp;\u003c/em\u003e= 0.835), N factor (\u003cem\u003eP\u0026nbsp;\u003c/em\u003e= 0.414), M factor (\u003cem\u003eP\u0026nbsp;\u003c/em\u003e= 0.421) nor overall stage (\u003cem\u003eP\u0026nbsp;\u003c/em\u003e= 0.172) was an independent risk factor for s-NSCLC (Table 1 in detail).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 1.\u003c/strong\u003e Univariate and multivariate analyses of overall survival in s-NCLCS patients.\u003c/p\u003e\n\u003cdiv align=\"Left\"\u003e\n \u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"699\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"36.48068669527897%\" valign=\"top\"\u003e\n \u003cp\u003eCharacteristic\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.878397711015737%\" valign=\"top\"\u003e\n \u003cp\u003eUnivariate\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.44206008583691%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.436337625178827%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cem\u003e\u0026nbsp;\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.160228898426324%\" valign=\"top\"\u003e\n \u003cp\u003eMultivariate\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.723891273247497%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cem\u003e\u0026nbsp;\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.878397711015737%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"36.48068669527897%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.878397711015737%\" valign=\"top\"\u003e\n \u003cp\u003en\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.44206008583691%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cem\u003eP\u003c/em\u003e-value\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.436337625178827%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cem\u003e\u0026nbsp;\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.160228898426324%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cem\u003eP\u003c/em\u003e-value\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.723891273247497%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cem\u003eHR\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.878397711015737%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cem\u003e95% CI\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"36.48068669527897%\" valign=\"top\"\u003e\n \u003cp\u003eClinical characteristics\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; Sex (male vs. female)\u003c/p\u003e\n \u003cp\u003eAge (＜60y vs.\u0026nbsp;\u0026ge;60y)\u003c/p\u003e\n \u003cp\u003eSmoking status (- vs. +)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.878397711015737%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e108 vs. 27\u003c/p\u003e\n \u003cp\u003e50 vs. 85\u003c/p\u003e\n \u003cp\u003e43 vs. 92\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.44206008583691%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e0.192\u003c/p\u003e\n \u003cp\u003e0.090\u003c/p\u003e\n \u003cp\u003e0.037\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.436337625178827%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.160228898426324%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e0.056\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.723891273247497%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.878397711015737%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"36.48068669527897%\" valign=\"top\"\u003e\n \u003cp\u003eRadiological findings\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; Size (＜5cm vs. \u0026ge;5cm)\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; Location (peripheral vs. central)\u003c/p\u003e\n \u003cp\u003eCalcification (- vs. +)\u003c/p\u003e\n \u003cp\u003eCavity or vacuole (- vs. +)\u003c/p\u003e\n \u003cp\u003eLAA (- vs. +)\u003c/p\u003e\n \u003cp\u003eLAA ratio (＜10% vs.\u0026nbsp;10-50% vs. \u0026gt;50%)\u003c/p\u003e\n \u003cp\u003ePleural invasion (- vs. +)\u003c/p\u003e\n \u003cp\u003ePeritumoral GGO, nodule or atelectasis\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;(- vs. +)\u003c/p\u003e\n \u003cp\u003eHydrothorax \u0026nbsp;(- vs. +)\u003c/p\u003e\n \u003cp\u003ePET/CT SUV\u003csub\u003emax\u003c/sub\u003e (＜20 vs. \u0026ge;20)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.878397711015737%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e56 vs. 79\u003c/p\u003e\n \u003cp\u003e98 vs. 37\u003c/p\u003e\n \u003cp\u003e116 vs. 19\u003c/p\u003e\n \u003cp\u003e113 vs. 22\u003c/p\u003e\n \u003cp\u003e24 vs. 84\u003c/p\u003e\n \u003cp\u003e26 vs. 54 vs. 28\u003c/p\u003e\n \u003cp\u003e60 vs. 75\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e104 vs. 31\u003c/p\u003e\n \u003cp\u003e99 vs. 36\u003c/p\u003e\n \u003cp\u003e14 vs. 14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.44206008583691%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026lt;\u0026nbsp;0.001\u003c/p\u003e\n \u003cp\u003e0.063\u003c/p\u003e\n \u003cp\u003e0.021\u003c/p\u003e\n \u003cp\u003e0.088\u003c/p\u003e\n \u003cp\u003e0.211\u003c/p\u003e\n \u003cp\u003e0.360\u003c/p\u003e\n \u003cp\u003e\u0026lt;\u0026nbsp;0.001\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026lt;\u0026nbsp;0.001\u003c/p\u003e\n \u003cp\u003e\u0026lt;\u0026nbsp;0.001\u003c/p\u003e\n \u003cp\u003e0.711\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.436337625178827%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.160228898426324%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e0.056\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e0.374\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e0.496\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e0.038\u003c/p\u003e\n \u003cp\u003e0.731\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.723891273247497%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e1.995\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.878397711015737%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e1.040-3.829\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"36.48068669527897%\" valign=\"top\"\u003e\n \u003cp\u003eTreatment\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; Surgery (- vs. +)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.878397711015737%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e80 vs. 55\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.44206008583691%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026lt;\u0026nbsp;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.436337625178827%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.160228898426324%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e0.035\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.723891273247497%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e0.518\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.878397711015737%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e0.282-0.954\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"36.48068669527897%\" valign=\"top\"\u003e\n \u003cp\u003eTNM classification\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; Overall stage (I-II vs. III vs. IV)\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; T factor (T1-2 vs. T3 vs. T4)\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; N factor (- vs. +)\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; M factor (- vs. +)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.878397711015737%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e28 vs.59 vs. 48\u003c/p\u003e\n \u003cp\u003e40 vs.39 vs. 56\u003c/p\u003e\n \u003cp\u003e40 vs. 95\u003c/p\u003e\n \u003cp\u003e87 vs. 48\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.44206008583691%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026lt;\u0026nbsp;0.001\u003c/p\u003e\n \u003cp\u003e\u0026lt;\u0026nbsp;0.001\u003c/p\u003e\n \u003cp\u003e0.006\u003c/p\u003e\n \u003cp\u003e\u0026lt;\u0026nbsp;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.436337625178827%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.160228898426324%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e0.172\u003c/p\u003e\n \u003cp\u003e0.835\u003c/p\u003e\n \u003cp\u003e0.414\u003c/p\u003e\n \u003cp\u003e0.421\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.723891273247497%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.878397711015737%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003en: number of patients; HR: hazard ratio; CI: confidence interval; LAA: low-attenuation area;\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eGGO: ground-glass opacity\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMolecular findings of s-NSCLC\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eMolecular alterations were detected in 15 patients with s-NSCLC. PD-L1 overexpression occurred in four patients. EGFR mutations were detected in 4 patients. KRAS mutations were detected in 3 patients. Both MET exon14 skipping (Figure 3e for example) and ALK mutations were found in 2 patients. The PIK3CA mutation was detected in one patient. The EGFR (exon19-del and exon21-L861Q) + PIK3CA (exon20-H12047R and exon9-E545K) fusion mutation was found in one patient. The ALK (exon23-L1187M) + TP53 (exon5-Y163C) fusion mutation was found in one patient. KRAS (exon2) + TP53 (exon4) missense mutation were found in one patient (Table 2 in detail).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 2\u0026nbsp;\u003c/strong\u003eMolecular findings\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003eand\u003cstrong\u003e\u0026nbsp;c\u003c/strong\u003elinicoradiological data of s-NSCLC patients\u003c/p\u003e\n\u003cdiv align=\"Left\"\u003e\n \u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"764\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"4.960835509138382%\"\u003e\n \u003cp\u003eCase No.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.960835509138382%\"\u003e\n \u003cp\u003eAge (y)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"2.480417754569191%\"\u003e\n \u003cp\u003eSex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.616187989556137%\" valign=\"top\"\u003e\n \u003cp\u003eSmoking\u003c/p\u003e\n \u003cp\u003estatus\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.960835509138382%\"\u003e\n \u003cp\u003eSize (cm)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.135770234986945%\"\u003e\n \u003cp\u003eLAA ratio\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.577023498694517%\" valign=\"top\"\u003e\n \u003cp\u003eMetastatic sites\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.577023498694517%\"\u003e\n \u003cp\u003eTNM stage\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.441253263707572%\" valign=\"top\"\u003e\n \u003cp\u003eSurgery\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.096605744125327%\" valign=\"top\"\u003e\n \u003cp\u003eSurvival time\u003c/p\u003e\n \u003cp\u003e(mo)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.193211488250654%\"\u003e\n \u003cp\u003eMolecular findings\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"4.960835509138382%\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.960835509138382%\"\u003e\n \u003cp\u003e53\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"2.480417754569191%\"\u003e\n \u003cp\u003eF\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.616187989556137%\" valign=\"top\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.960835509138382%\"\u003e\n \u003cp\u003e4.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.135770234986945%\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.577023498694517%\" valign=\"top\"\u003e\n \u003cp\u003eBrain\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.577023498694517%\"\u003e\n \u003cp\u003eT2bN0M1b (IVA)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.441253263707572%\" valign=\"top\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.096605744125327%\" valign=\"top\"\u003e\n \u003cp\u003e17 (dead)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.193211488250654%\"\u003e\n \u003cp\u003eEGFR exon21-L858R\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"4.960835509138382%\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.960835509138382%\"\u003e\n \u003cp\u003e56\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"2.480417754569191%\"\u003e\n \u003cp\u003eF\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.616187989556137%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e+\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.960835509138382%\"\u003e\n \u003cp\u003e6.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.135770234986945%\"\u003e\n \u003cp\u003e0.226\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.577023498694517%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.577023498694517%\"\u003e\n \u003cp\u003eT3N0M0 (IIB)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.441253263707572%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e+\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.096605744125327%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e12 (alive)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.193211488250654%\"\u003e\n \u003cp\u003eEGFR (exon19-del and exon21-L861Q) + PIK3CA (exon20-H12047R and exon9-E545K)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"4.960835509138382%\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.960835509138382%\"\u003e\n \u003cp\u003e48\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"2.480417754569191%\"\u003e\n \u003cp\u003eF\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.616187989556137%\" valign=\"top\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.960835509138382%\"\u003e\n \u003cp\u003e5.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.135770234986945%\"\u003e\n \u003cp\u003e0.133\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.577023498694517%\" valign=\"top\"\u003e\n \u003cp\u003ePleural\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.577023498694517%\"\u003e\n \u003cp\u003eT3N2M1a (IVA)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.441253263707572%\" valign=\"top\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.096605744125327%\" valign=\"top\"\u003e\n \u003cp\u003e9 (dead)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.193211488250654%\"\u003e\n \u003cp\u003eEGFR exon19-del\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"4.960835509138382%\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.960835509138382%\"\u003e\n \u003cp\u003e61\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"2.480417754569191%\"\u003e\n \u003cp\u003eM\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.616187989556137%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e+\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.960835509138382%\"\u003e\n \u003cp\u003e5.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.135770234986945%\"\u003e\n \u003cp\u003e0.87\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.577023498694517%\" valign=\"top\"\u003e\n \u003cp\u003eContralateral lung lobe, liver, and adrenal gland\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.577023498694517%\"\u003e\n \u003cp\u003eT4N3M1c (IVB)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.441253263707572%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.096605744125327%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e3 (dead)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.193211488250654%\"\u003e\n \u003cp\u003eEGFR (exon21-L858R + exon20-T790M)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"4.960835509138382%\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.960835509138382%\"\u003e\n \u003cp\u003e46\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"2.480417754569191%\"\u003e\n \u003cp\u003eF\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.616187989556137%\" valign=\"top\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.960835509138382%\"\u003e\n \u003cp\u003e5.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.135770234986945%\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.577023498694517%\" valign=\"top\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.577023498694517%\"\u003e\n \u003cp\u003eT3N2M0 (IIIB)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.441253263707572%\" valign=\"top\"\u003e\n \u003cp\u003e+\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.096605744125327%\" valign=\"top\"\u003e\n \u003cp\u003e24 (alive)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.193211488250654%\"\u003e\n \u003cp\u003eALK\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"4.960835509138382%\"\u003e\n \u003cp\u003e6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.960835509138382%\"\u003e\n \u003cp\u003e75\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"2.480417754569191%\"\u003e\n \u003cp\u003eM\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.616187989556137%\" valign=\"top\"\u003e\n \u003cp\u003e+\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.960835509138382%\"\u003e\n \u003cp\u003e9.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.135770234986945%\"\u003e\n \u003cp\u003e0.673\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.577023498694517%\" valign=\"top\"\u003e\n \u003cp\u003eLiver\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.577023498694517%\"\u003e\n \u003cp\u003eT4N2M1b (IVA)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.441253263707572%\" valign=\"top\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.096605744125327%\" valign=\"top\"\u003e\n \u003cp\u003e5 (dead)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.193211488250654%\"\u003e\n \u003cp\u003eALK (exon23-L1187M) + TP53 (exon5-Y163C)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"4.960835509138382%\"\u003e\n \u003cp\u003e7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.960835509138382%\"\u003e\n \u003cp\u003e65\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"2.480417754569191%\"\u003e\n \u003cp\u003eF\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.616187989556137%\" valign=\"top\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.960835509138382%\"\u003e\n \u003cp\u003e8.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.135770234986945%\"\u003e\n \u003cp\u003e0.368\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.577023498694517%\" valign=\"top\"\u003e\n \u003cp\u003ePleural\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.577023498694517%\"\u003e\n \u003cp\u003eT4N2M1a (IVA)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.441253263707572%\" valign=\"top\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.096605744125327%\" valign=\"top\"\u003e\n \u003cp\u003e7 (alive)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.193211488250654%\"\u003e\n \u003cp\u003eEML4-ALK (exon6-exon20)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"4.960835509138382%\"\u003e\n \u003cp\u003e8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.960835509138382%\"\u003e\n \u003cp\u003e64\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"2.480417754569191%\"\u003e\n \u003cp\u003eM\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.616187989556137%\" valign=\"top\"\u003e\n \u003cp\u003e+\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.960835509138382%\"\u003e\n \u003cp\u003e7.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.135770234986945%\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.577023498694517%\" valign=\"top\"\u003e\n \u003cp\u003eThe left vertebral arch of lumbar 2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.577023498694517%\"\u003e\n \u003cp\u003eT4N2M1b (IVA)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.441253263707572%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.096605744125327%\" valign=\"top\"\u003e\n \u003cp\u003e5 (dead)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.193211488250654%\"\u003e\n \u003cp\u003eMET exon14 skipping\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"4.960835509138382%\"\u003e\n \u003cp\u003e9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.960835509138382%\"\u003e\n \u003cp\u003e72\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"2.480417754569191%\"\u003e\n \u003cp\u003eF\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.616187989556137%\" valign=\"top\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.960835509138382%\"\u003e\n \u003cp\u003e4.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.135770234986945%\"\u003e\n \u003cp\u003e0.224\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.577023498694517%\" valign=\"top\"\u003e\n \u003cp\u003eBrain\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.577023498694517%\"\u003e\n \u003cp\u003eT2bN0M1b (IVA)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.441253263707572%\" valign=\"top\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.096605744125327%\" valign=\"top\"\u003e\n \u003cp\u003e2 (dead)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.193211488250654%\"\u003e\n \u003cp\u003eMET exon14 skipping\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"4.960835509138382%\"\u003e\n \u003cp\u003e10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.960835509138382%\"\u003e\n \u003cp\u003e88\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"2.480417754569191%\"\u003e\n \u003cp\u003eM\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.616187989556137%\" valign=\"top\"\u003e\n \u003cp\u003e+\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.960835509138382%\"\u003e\n \u003cp\u003e5.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.135770234986945%\"\u003e\n \u003cp\u003e0.342\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.577023498694517%\" valign=\"top\"\u003e\n \u003cp\u003eLiver\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.577023498694517%\"\u003e\n \u003cp\u003eT4N3M1b (IVA)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.441253263707572%\" valign=\"top\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.096605744125327%\" valign=\"top\"\u003e\n \u003cp\u003e1.5 (dead)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.193211488250654%\"\u003e\n \u003cp\u003ePIK3CA(exon20-H12047R + exon9-E545K)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"4.960835509138382%\"\u003e\n \u003cp\u003e11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.960835509138382%\"\u003e\n \u003cp\u003e72\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"2.480417754569191%\"\u003e\n \u003cp\u003eM\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.616187989556137%\" valign=\"top\"\u003e\n \u003cp\u003e+\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.960835509138382%\"\u003e\n \u003cp\u003e6.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.135770234986945%\"\u003e\n \u003cp\u003e0.87\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.577023498694517%\" valign=\"top\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.577023498694517%\"\u003e\n \u003cp\u003eT4N2M0 (IIIB)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.441253263707572%\" valign=\"top\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.096605744125327%\" valign=\"top\"\u003e\n \u003cp\u003e2 (dead)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.193211488250654%\"\u003e\n \u003cp\u003ePD-L1 overexpression\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"4.960835509138382%\"\u003e\n \u003cp\u003e12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.960835509138382%\"\u003e\n \u003cp\u003e64\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"2.480417754569191%\"\u003e\n \u003cp\u003eM\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.616187989556137%\" valign=\"top\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.960835509138382%\"\u003e\n \u003cp\u003e4.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.135770234986945%\"\u003e\n \u003cp\u003e0.544\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.577023498694517%\" valign=\"top\"\u003e\n \u003cp\u003eBrain,bone and Adrenal gland\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.577023498694517%\"\u003e\n \u003cp\u003eT2bN3M1c (IVB)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.441253263707572%\" valign=\"top\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.096605744125327%\" valign=\"top\"\u003e\n \u003cp\u003e22 (alive)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.193211488250654%\"\u003e\n \u003cp\u003eKRAS + PD-L1 overexpression\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"4.960835509138382%\"\u003e\n \u003cp\u003e13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.960835509138382%\"\u003e\n \u003cp\u003e59\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"2.480417754569191%\"\u003e\n \u003cp\u003eM\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.616187989556137%\" valign=\"top\"\u003e\n \u003cp\u003e+\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.960835509138382%\"\u003e\n \u003cp\u003e2.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.135770234986945%\"\u003e\n \u003cp\u003e0.464\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.577023498694517%\" valign=\"top\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.577023498694517%\"\u003e\n \u003cp\u003eT4N3M0 (IIIC)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.441253263707572%\" valign=\"top\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.096605744125327%\" valign=\"top\"\u003e\n \u003cp\u003e11 (alive)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.193211488250654%\"\u003e\n \u003cp\u003eKRAS (G12C) + PD-L1 overexpression\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"4.960835509138382%\"\u003e\n \u003cp\u003e14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.960835509138382%\"\u003e\n \u003cp\u003e60\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"2.480417754569191%\"\u003e\n \u003cp\u003eM\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.616187989556137%\" valign=\"top\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.960835509138382%\"\u003e\n \u003cp\u003e5.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.135770234986945%\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.577023498694517%\" valign=\"top\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.577023498694517%\"\u003e\n \u003cp\u003eT3N3M0 (IIIC)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.441253263707572%\" valign=\"top\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.096605744125327%\" valign=\"top\"\u003e\n \u003cp\u003e8 (dead)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.193211488250654%\"\u003e\n \u003cp\u003eKRAS exon2 + TP53 exon4 +\u003c/p\u003e\n \u003cp\u003ePD-L1 overexpression\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"4.960835509138382%\"\u003e\n \u003cp\u003e15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.960835509138382%\"\u003e\n \u003cp\u003e70\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"2.480417754569191%\"\u003e\n \u003cp\u003eM\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.616187989556137%\" valign=\"top\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.960835509138382%\"\u003e\n \u003cp\u003e7.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.135770234986945%\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.577023498694517%\" valign=\"top\"\u003e\n \u003cp\u003eBone and muscles of the left thigh\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.577023498694517%\"\u003e\n \u003cp\u003eT3N1M1c (IVB)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.441253263707572%\" valign=\"top\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.096605744125327%\" valign=\"top\"\u003e\n \u003cp\u003e6 (dead)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.193211488250654%\"\u003e\n \u003cp\u003eKRAS\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003eNote: (+) = present, (-) = absent\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eAccording to the latest WHO classification of lung neoplasms in 2021, s-NSCLC can be categorized into three pathological subtypes: pleomorphic carcinoma (formed by spindle or/and giant cells), carcinosarcoma, and pulmonary blastoma [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. s-NSCLC is a rare subtype of NSCLC but possesses distinct characteristics. Our study has shown that s-NSCLC patients were more likely to be male smokers, with a male-to-female ratio of 4:1. Among the s-NSCLC patients, the mean age at diagnosis was 62 years, and the mean tumor size was 5.8 cm. Median survival time of s-NSCLC patients was only 9 months (95% CI: 7, 11), 48/135 (35.6%) of s-NSCLC cases had stage IV disease at diagnosis and the 1-, 3- and 5-year OS rates in s-NSCLC patients were 28.9%, 11.9% and 5.9%, respectively. Our clinical findings are similar to previous studies [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e, \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e, \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e, \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e, \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e], which reveals that these tumors are diagnosed at an advanced stage, leading to missed opportunities for surgical treatment. Our study revealed that surgical treatment was associated with decreased mortality, consistent with the findings of previous studies [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e, \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]. Interestingly, this study revealed that the TNM stage was not an independent risk factor for prognosis. Most s-NSCLC patients (96/135, 71.1%) in this study died within one year. Regardless of the TNM stage, this highly malignant tumor progresses rapidly, recurs postoperatively and early metastasis, leading to short-term mortality.\u003c/p\u003e \u003cp\u003eIn our study, preoperative CT findings showed that calcification (19 of 135, 14.1%) and vacuole/cavity (22 of 135, 16.3%) were rare in s-NSCLC patients, which was consistent with the findings of previous studies [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e, \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. Previous studies have reported that s-NSCLC is prone to pleural invasion: Kim et al.[\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e] showed that pleural invasion occurred in 7/10 (70%) of s-NSCLC patients. In the study of Fujisaki et al. [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e] found that pleural invasion was present in 19/44 (43%) of the patients. In our study, 75/135 (55.6%) of the s-NSCLC patients had pleural invasion. This may be due to the larger size of s-NSCLC: when the tumor is large enough, the pleural invasion is theoretically occurred.\u003c/p\u003e \u003cp\u003eOur study revealed that the majority of s-NSCLC lesions presented with LAA (87 of 108, 80.6%). Kim et al. [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e] reported that 8/10 (80%) of s-NSCLC lesions had LAA lesions. Fujisaki et al. [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e] showed the presence of LAA in 40/44 (91%) of s-NSCLC patients, which was similar to the findings of our study. Furthermore, the median of LAA ratio was 30.8% in s-NSCLC patients. The pathological manifestations of LAA were mucinous degeneration, necrosis, and hemorrhage, suggesting that rapid proliferation exceeded the blood supply [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eIn previous studies, the LAA ratio was found to be an independent risk factor for s-NSCLC: LAA ratio\u0026thinsp;\u0026gt;\u0026thinsp;25% was associated with shorter OS and disease-free survival than LAA ratio\u0026thinsp;\u0026lt;\u0026thinsp;25% [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. A study by Nishida et al. [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e] reached a similar conclusion. However, the LAA ratio was not associated with OS in our study. In previous studies, all s-NSCLC patients included underwent surgical resection. However, in our study, the majority of patients with s-NSCLC were in an advanced stage. We analyzed surgical cases individually but did not find a correlation between LAA and prognosis, either. This may be due to the fact that s-NSCLC is prone to metastasis, and these lesions have not yet grown large enough to form LAA when distant metastasis occurs, leading to death in the short term.\u003c/p\u003e \u003cp\u003eIn our study, peritumoral GGO, nodule or atelectasis found to be independent risk indicators associated with prognosis in s-NSCLC patients. This distinctive CT findings indicates tumor invasion into surrounding tissues, bronchial involvement, and peritumoral metastasis, all of which are indicative of the tumor's high degree of aggressiveness and metastatic potential. Nishida et al. [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e] discovered that GGO can be observed across all subtypes of s-NSCLC, the pathological features associated with GGO are hemorrhage, vascular invasion, and aerogenous metastases. However, this study did not found a relationship between GGO and prognosis. This could be attributed to the fact that the study focused solely on surgically treated cases, excluding those advanced-stage patients with more severe peritumoral invasion.\u003c/p\u003e \u003cp\u003eOur study found that the SUV\u003csub\u003emax\u003c/sub\u003e was not associated with the prognosis in s-NSCLC patients. Our results are similar to those of Rapicetta et al. [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]. However, Kim et al.[\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e] pointed out that a high SUV\u003csub\u003emax\u003c/sub\u003e is associated with poor prognosis in s-NSCLC patients. Interestingly, the SUV\u003csub\u003emax\u003c/sub\u003e was useful for evaluating PD-L1 and KRAS expression in s-NSCLC [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]. The correlations among the SUV\u003csub\u003emax\u003c/sub\u003e, molecular findings and prognosis of s-NSCLC patients warrant further study.\u003c/p\u003e \u003cp\u003eIn recent years, the molecular targeted therapy and immunotherapy have attracted much attention in clinical applications among s-NSCLC patients. EGFR and ALK are well-known examples where appropriate tyrosine kinase inhibitor (TKI) therapy improves patient quality of life and survival [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]. EGFR mutations were detected in 16% of s-NSCLC patients, the EGFR exon21-L861Q mutation is a rare subtype and may benefit from afatinib [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e, \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]. Lococo F et al. [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e] showed that TP53 gene mutations occur in 55% of s-NSCLC patients but are not the driver gene for s-NSCLC; the increased genetic instability of TP53 gene may lead to the occurrence of s-NSCLC. MET exon14 skipping mutation (31.8%) and high-level MET amplification (13.6%) was found in s-NSCLC patients, leading to epithelial-mesenchymal transformation of cells and resistance chemotherapy and TKIs [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e, \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. Furthermore, MET exon14 skipping mutation and PD-L1 overexpression are considered crucial genetic events contributing to the sarcomatoid transformation of c-NSCLC [\u003cspan additionalcitationids=\"CR26\" citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e], which revealed the importance of molecular targeted therapy and immunotherapy for s-NSCLC patients. KRAS mutations were found to be a marker of poor prognosis in s-NSCLC patients [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]. However, two patients in our study with KRAS (G12C)\u0026thinsp;+\u0026thinsp;PD-L1 overexpression had relatively long survival after targeted and immunotherapy therapy, this indicates that the combination of molecular targeted therapy and immunotherapy has achieved favorable benefits in this population. PIK3CA-H12047R expression alone cannot promote tumor formation but significantly enhances tumorigenesis initiated by KRAS, considered a direct effector that promotes KRAS-driven lung tumorigenesis [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]. The molecular findings in this study hold the potential to deepen our understanding of s-NSCLC.\u003c/p\u003e \u003cp\u003eThis study has several limitations. Firstly, this is a retrospective study and selection bias is inevitable, prospective and randomized study is still needed. Secondly, treatment were not included in the prognostic analysis. This retrospective study dates back more than 10 years, and the treatment guidelines have changed greatly. Prospective studies with uniform treatment standards are needed in the future.\u003c/p\u003e \u003cp\u003eIn conclusion, the presence of large intratumoral LAA ratio and peritumoral GGO, nodule or atelectasis were a distinctive CT sign for s-NSCLC. Moreover, Peritumoral GGO, nodule or atelectasis is an independent risk indicator associated with poor prognosis, while complete surgical resection is essential for improving the prognosis in s-NSCLC patients. However, the LAA ratio was not a prognostic indicator for s-NSCLC. These findings are helpful for preoperative CT diagnosis of s-NSCLC and provide a reference for clinical treatment strategies and prognostic evaluation.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cp\u003eNSCLC \u0026nbsp; \u0026nbsp; \u0026nbsp; non-small cell lung cancer\u003c/p\u003e\n\u003cp\u003es-NSCLC \u0026nbsp; \u0026nbsp; \u0026nbsp;sarcomatoid-NSCLC\u003c/p\u003e\n\u003cp\u003eLAA \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;low attenuation area\u003c/p\u003e\n\u003cp\u003eGGO \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; ground-glass opacity\u003c/p\u003e\n\u003cp\u003e18F-FDG PET/CT \u0026nbsp; \u0026nbsp;18F-fluoro-D-glucose positron emission tomography/computed tomography\u003c/p\u003e\n\u003cp\u003eSUVmax \u0026nbsp; \u0026nbsp; \u0026nbsp;maximum Standardized Uptake Value\u003c/p\u003e\n\u003cp\u003eIQR \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;interquartile range\u003c/p\u003e\n\u003cp\u003eCI \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; confidence interval\u003c/p\u003e\n\u003cp\u003eOS \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; overall survival\u003c/p\u003e\n\u003cp\u003eHR \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; hazard ratio.\u003c/p\u003e\n\u003cp\u003eTKI \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;tyrosine kinase inhibitor\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003eAcknowledgements\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eNot applicable\u003c/p\u003e\n\u003cp\u003eAuthor contributions\u003c/p\u003e\n\u003cp\u003eWenjian Tang, Jianping Zhong and Junyuan Zhong, study concept and design; All authors contributed to data collection or data curation; Wenjian Tang. Yujin Yin and Chunju Wen, data analysis and manuscript preparation; All authors read and approval of final manuscript.\u003c/p\u003e\n\u003cp\u003eFunding\u003c/p\u003e\n\u003cp\u003eThis study has received funding from the National Natural Science Foundation of China (82160330), the Natural Science Foundation of Jiangxi Province (20202ACBL216006), the Ganzhou Health Commission Scientific Research Planning Project (GZWJW202402108), and the Ganzhou Health Commission Scientific Research Planning Project (GZWJW202402120).\u003c/p\u003e\n\u003cp\u003eData availability\u003c/p\u003e\n\u003cp\u003eThe datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request.\u003c/p\u003e\n\u003cp\u003eEthics approval and consent to participate\u003c/p\u003e\n\u003cp\u003eThe institutional review board of Ganzhou People\u0026rsquo;s Hospital (IRB no.TY-ZKY2022-045-01) approved the study and waived the requirement for written informed consent. All methods were carried out in accordance with Declaration of Helsinki.\u003c/p\u003e\n\u003cp\u003eCompeting interests\u003c/p\u003e\n\u003cp\u003eThe authors declare that they have no conflict of interest.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n \u003cli\u003eYendamuri S, Caty L, Pine M, et al. Outcomes of sarcomatoid carcinoma of the lung: a Surveillance, Epidemiology, and End Results Database analysis. Surgery 2012;152(3):397-402.\u003c/li\u003e\n \u003cli\u003ePelosi G, Sonzogni A, De Pas T, et al. Review article: pulmonary sarcomatoid carcinomas: a practical overview. Int J Surg Pathol 2010;18(2):103-120.\u003c/li\u003e\n \u003cli\u003eTakahashi K, Kohno T, Matsumoto S, et al. Clonality and heterogeneity of pulmonary blastoma from the viewpoint of genetic alterations: a case report. Lung Cancer 2007;57(1):103-8.\u003c/li\u003e\n \u003cli\u003ede Kock L, Bah I, Brunet J, et al. Somatic DICER1 mutations in adult-onset pulmonary blastoma. 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Preoperative CT findings and prognosis of pulmonary sarcomatoid carcinoma: comparison with conventional NSCLC of similar tumor size. BMC Med Imaging 2023;23(1):105.\u003c/li\u003e\n \u003cli\u003eNicholson AG, Tsao MS, Beasley MB, et al. The 2021 WHO Classification of Lung Tumors: Impact of Advances Since 2015 J Thorac Oncol. 2022;17(3):362-387.\u003c/li\u003e\n \u003cli\u003eGu L, Xu Y, Chen Z, Pan Y, Lu S. Clinical analysis of 95 cases of pulmonary sarcomatoid carcinoma. Biomed Pharmacother 2015;76:134-140.\u003c/li\u003e\n \u003cli\u003eManeenil K, Xue Z, Liu M, et al. Sarcomatoid Carcinoma of the Lung: The Mayo Clinic Experience in 127 Patients. Clin Lung Cancer 2018;19(3):e323-e333.\u003c/li\u003e\n \u003cli\u003eRapicetta C, Lococo F, Stefani A, et al. Primary Sarcomatoid Carcinoma of the Lung: Radiometabolic ((18)F-FDG PET/CT) Findings and Correlation with Clinico-Pathological and Survival Results. 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Ann Oncol 2017;28(7):1417-1418.\u003c/li\u003e\n \u003cli\u003eGreen S, Trejo CL, McMahon M. PIK3CA(H1047R) Accelerates and Enhances KRAS(G12D)-Driven Lung Tumorigenesis. Cancer Res 2015;75(24):5378-5391.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Pulmonary sarcomatoid carcinoma, Non-small cell lung cancer, Computed tomography, Prognosis","lastPublishedDoi":"10.21203/rs.3.rs-4725107/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4725107/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003ePurpose: \u003c/strong\u003eTo assess clinical data and preoperative CT findings associated with prognosis in sarcomatoid-NSCLC (s-NSCLC) patients.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMaterial and Methods: \u003c/strong\u003eIn this retrospective study, s-NSCLC patients who underwent contrast enhanced thoracic CT or PET/CT from January 2013 to June 2023 at three centers were enrolled. Clinicoradiological data, including sex, age, smoking history, TNM classification, tumor size, tumor location, calcification, vacuole/cavity, pleural invasion, low-attenuation area (LAA) ratio, hydrothorax, peritumoral ground-glass opacity (GGO), nodule or atelectasis and SUV\u003csub\u003emax\u003c/sub\u003e were calculated. Clinicoradiological findings associated with overall survival were evaluated by a multivariate Cox regression model.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults:\u003c/strong\u003e A total of 135 with s-NSCLC were included. The s-NSCLC patients were more likely to be elderly male smokers. The mean age and tumor size at diagnosis was 62 years and 5.8 cm. The median survival time of patients with s-NSCLC was 9 (95% CI: 7, 11) months. The 1-, 3- and 5-year overall survival (OS) rates of the s-NSCLC patients were 28.9%, 11.9% and 5.9%, respectively. s-NSCLC is often peripherally locate (98/135, 70.4%). Calcification (19/135, 14.1%) and Vacuole/cavity (22/135, 16.2%) were rare in s-NSCLC lesions. Pleural invasion and hydrothorax was present in 75/135 (55.6%) and 36/135 (26.7%) of s-NSCLC patients. The s-NSCLC lesions usually present with LAA (87/135, 80.6%), the median LAA ratio was 30.8% (IQR: 10.6%, 50.7%). The SUV\u003csub\u003emax\u003c/sub\u003e of s-NSCLC lesions were 20.2 (IQR: 14.0, 23.9). Surgical treatment [hazard ratio (HR) = 0.518] was associated with decreased mortality, while peritumoral GGO, nodule or atelectasis (HR = 1.995) were associated with increased mortality.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusions:\u003c/strong\u003e Peritumoral GGO, nodule or atelectasis is an independent risk indicator associated with poor prognosis, while complete surgical resection is essential for improving the prognosis in s-NSCLC patients.\u003c/p\u003e","manuscriptTitle":"Clinicoradiological findings associated with prognostic indicators of sarcomatoid-NSCLC: A multicenter analysis of 135 patients","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-08-11 11:44:16","doi":"10.21203/rs.3.rs-4725107/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"8005bbd9-4dee-4b0d-86b6-7a365d644b8a","owner":[],"postedDate":"August 11th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2025-01-15T17:23:12+00:00","versionOfRecord":[],"versionCreatedAt":"2024-08-11 11:44:16","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-4725107","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4725107","identity":"rs-4725107","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}