Computed tomography characteristics of lung adenocarcinomas with epidermal growth factor receptor mutation: A propensity score matching study

Prediction of EGFR mutations in non-small cell lung cancer: a nomogram based on 18F-FDG PET and thin-section CT radiomics with machine learning

Background

This study aimed to develop and validate radiomics-based nomograms for the identification of EGFR mutations in non-small cell lung cancer (NSCLC).

Methods

A retrospective analysis was performed on 313 NSCLC patients, who were randomly divided into training (n = 250) and validation (n = 63) groups. Radiomic features were extracted from 18F-fluorodeoxyglucose positron emission tomography (18F-FDG PET) and thin-section computed tomography (CT) scans. After selecting optimal radiomic features, four machine learning algorithms, including logistic regression (LR), random forest (RF), support vector machine (SVM), and extreme gradient boosting (XGBoost), were used to develop and validate radiomics models. A combined model, incorporating the Rad score from the best performing radiomics model with clinical and radiological features, was then formulated. Finally, the integrated nomogram was generated. Its predictive performance and clinical utility were evaluated using receiver operating characteristic curves, calibration curves, and decision curve analysis.

Results

Among the radiomics models, the RF model showed the best performance with AUCs of 0.785 (95% CI, 0.726-0.844) and 0.776 (95% CI, 0.662-0.889) in the training and validation groups, respectively. The AUCs of the clinical and radiological models in both groups were 0.711 (95% CI, 0.645-0.776) and 0.758 (95% CI, 0.627-0.890), and 0.632 (95% CI, 0.564-0.699) and 0.677 (95% CI, 0.531-0.822), respectively. The combined model achieved the highest AUCs of 0.872 (95% CI, 0.829-0.915) and 0.831 (95% CI, 0.723-0.940) in the training and validation groups, respectively. The DeLong test confirmed the superiority of the combined model over the other three models. Both the calibration curve and the DCA indicated that the radiomics nomogram was consistent and clinically useful.

Conclusions

Radiomics combined with machine learning and based on 18F-FDG PET/CT images can effectively determine EGFR mutation status in NSCLC patients. Radiomics-based nomograms provide a non-invasive and visually intuitive prediction tool for screening NSCLC patients with EGFR mutations in a clinical setting.

CT and MRI bimodal radiomics for predicting EGFR status in NSCLC patients with brain metastases: A multicenter study

BACKGROUND

Leveraging the radiomics information from non-small cell lung cancer (NSCLC) primary lesion and brain metastasis (BM) to develop and validate a bimodal radiomics nomogram that can accurately predict epidermal growth factor receptor (EGFR) status.

METHODS

A total of 309 NSCLC patients with BM from three independent centers were recruited. Among them, the patients of Center I were randomly allocated into the training and internal test cohorts in a 7:3 ratio. Meanwhile, the patients from Center Ⅱ and Center Ⅲ collectively constitute the external test cohort. All chest CT and brain MRI images of each patient were obtained for image registration and sequence combination within a single modality. After image preprocessing, 1037 radiomics features were extracted from each single sequence. Six machine learning algorithms were used to construct radiomics signatures for CT and MRI respectively. The best CT and MRI radiomics signatures were fitted to establish the bimodal radiomics nomogram for predicting the EGFR status.

RESULTS

The contrast-enhanced (CE) eXtreme gradient boosting (XG Boost) and T2-weighted imaging (T2WI) + T1-weighted contrast-enhanced imaging (T1CE) random forest models were chosen as the radiomics signature representing primary lesion and BM. Both models were found to be independent predictors of EGFR mutation. The bimodal radiomics nomogram, which incorporated CT radiomics signature and MRI radiomics signature, demonstrated a good calibration and discrimination in the internal test cohort [area under curve (AUC), 0.866; 95 % confidence intervals (CI), 0.778-0.950) and the external test cohort (AUC, 0.818; 95 % CI, 0.691-0.938).

CONCLUSIONS

Our CT and MRI bimodal radiomics nomogram could timely and accurately evaluate the likelihood of EGFR mutation in patients with limited access to necessary materials, thus making up for the shortcoming of plasma sequencing and promoting the advancement of precision medicine.

Predictive value of spectral computed tomography parameters for EGFR gene mutation in non-small-cell lung cancer

AIM

To explore the predictive value of morphological signs and quantitative parameters from spectral CT for EGFR gene mutations in intermediate and advanced non-small-cell lung cancer (NSCLC).

MATERIALS AND METHODS

This retrospective observational study included patients with intermediate or advanced NSCLC at Xinjiang Medical University Affiliated Tumor Hospital between January 2017 and December 2019. The patients were divided into the EGFR gene mutation-positive and -negative groups.

RESULTS

Seventy-nine patients aged 60.75 ± 9.66 years old were included: 32 were EGFR mutation-positive, and 47 were negative. There were significant differences in pathological stage (P<0.001), tumor diameter (P=0.019), lobulation sign, intrapulmonary metastasis, mediastinal lymph node metastasis, distant metastasis (P<0.001), bone metastasis (P<0.001), arterial phase normalized iodine concentration (NIC) (P=0.001), venous phase NIC (P=0.001), slope of the energy spectrum curve (λ) (P<0.001), and CT value at 70 keV in arterial phase (P=0.004) and venous phase (P=0.003) between the EGFR mutation-positive and -negative patients. The multivariable logistic regression analysis showed that intrapulmonary metastasis, distant metastasis, venous phase NIC, venous phase λ, and pathological stage were independent factors predicting EGFR gene mutations, with high diagnostic power (AUC = 0.975, 91.5% sensitivity, and 90.6% specificity).

CONCLUSION

The pathological stage and the spectral CT parameters of intrapulmonary metastasis, distant metastasis, venous phase NIC, and venous phase λ might pre-operatively predict EGFR gene mutations in intermediate and advanced NSCLC.

Correlation of CT features of lung adenocarcinoma with sex and age

This study aimed to retrospectively examine the computed tomography (CT) features of lung adenocarcinoma across different demographic groups. Preoperative chest CT findings from 1266 surgically resected lung adenocarcinoma cases were retrospectively analyzed. Lung adenocarcinomas were categorized based on CT characteristics into pure ground glass (pGGO), nodule-containing ground glass opacity (mGGO), and pure solid without containing ground glass opacity (pSD). These categories were correlated with sex, age, EGFR status, and five histopathological subtypes. The diameters of pGGO, mGGO, and pSD significantly increased across all patient groups (P < 0.05). Males exhibited a significantly higher proportion of pSD than females (P = 0.002). The mean diameters of pGGO and pSD were significantly larger in males than in females (P = 0.0017 and P = 0.043, respectively). The frequency of pGGO was higher in the younger age group (≤ 60 years) compared to the older group (> 60 years) for both males (P = 0.002) and females (P = 0.027). The frequency of pSD was higher in the older age group for both sexes. A linear correlation between age and diameter was observed in the entire cohort as well as in the male and female groups (P < 0.0001 for all groups). EGFR mutations were less frequent in pSD compared to pGGO (P = 0.0002) and mGGO (P < 0.0001). The frequency of lesions containing micropapillary components increased from pGGO to mGGO and pSD (P < 0.0001 for all). The frequency of lesions containing solid components also increased from pGGO to mGGO and pSD (P = 0.045, P < 0.0001, and P < 0.0001, respectively). The CT features of lung adenocarcinoma exhibit differences across genders and age groups. Male gender and older age are risk factors for lung adenocarcinoma growth.

Distinct mutational features across preinvasive and invasive subtypes identified through comprehensive profiling of surgically resected lung adenocarcinoma

Lung adenocarcinoma (LUAD) is a heterogeneous disease. Our study aimed to understand the unique molecular features of preinvasive to invasive LUAD subtypes. We retrospectively analyzed the clinical, histopathological, and molecular data of 3,254 Chinese patients with preinvasive lesions (n = 252), minimally invasive adenocarcinomas (n = 479), and invasive LUAD (n = 2,523). Molecular data were elucidated using a targeted 68-gene next-generation sequencing panel. Our findings revealed four preinvasive lesion-predominant gene mutations, including MAP2K1 insertion-deletions (indels), BRAF non-V600E kinase mutations, and exon 20 insertions (20ins) in both EGFR and ERBB2, which we referred to as mutations enriched in AIS (MEA). The detection rate of MEA in invasive tumors was relatively lower. MAP2K1 missense mutations, which were likely passenger mutations, co-occurred with oncogenic driver mutations, while small indels were mutually exclusive from other genes regardless of the invasion level. BRAF non-V600E kinase-mutant invasive adenocarcinomas (IAC) had significantly higher mutation rates in tumor suppressor genes but lower frequency of co-occurring oncogenic driver mutations than non-kinase-mutant IAC, suggesting the potential oncogenic activity of BRAF non-V600E kinase mutations albeit weaker than BRAF V600E. Moreover, similar to the extremely low frequency of MAP2K1 indels in IAC, BRAF non-V600E kinase domain mutations co-occurring with TSC1 mutations were exclusively found in preinvasive lesions. Compared with EGFR L858R and exon 19 deletion, patients with preinvasive lesions harboring 20ins in either EGFR or ERBB2 were significantly younger, while those with IAC had similar age. Furthermore, our study demonstrated distinct mutational features for subtypes of oncogene mutations favored by different invasion patterns in adenocarcinomas. In conclusion, our data demonstrate distinct mutational features between preinvasive lesions and invasive tumors with MEA, suggesting the involvement of MEA in the early stages of tumorigenesis. Further pre-clinical studies are required to establish the role of these genes in the malignant transformation of LUAD.

Clinical and Radiological Characteristics to Differentiate Between EGFR Exon 21 and Exon 19 Mutations in Patients With Lung Adenocarcinoma: A Systematic Literature Review and Meta-Analysis

Epidermal Growth Factor Receptor (EGFR) mutations in lung adenocarcinoma have been previously associated with specific clinical characteristics and Computed Tomography (CT) patterns. However, associations among individual EGFR mutations have not been evaluated. We aim to differentiate if the most common EGFR mutations (exon 21 and 19) are related to specific clinical characteristics or CT patterns. A systematic review and meta-analysis of 5 databases were conducted with literature from January 2002 to July 2021. Eligible studies were of an experimental or observational design that included lung adenocarcinoma patients with confirmed EGFR exon mutations (21 and 19) and associated clinical characteristics and CT imaging patterns. Quality was assessed using the QUADAS-2 tool. The association between clinical and CT patterns and EGFR exon mutations 21 and 19 was evaluated using odds ratios (OR) and then pooled and analyzed with a fixed or random-effects model. This study follows the preferred reporting items for systematic review and meta-analysis (PRISMA) guidelines. A total of 12 retrospective diagnostic accuracy studies were included. Pooled analysis showed that characteristics such as absence of smoking status (OR 1.29 [95% CI 0.97 - 1.70]), and female sex (OR 1.23 [95% CI 0.83 - 1.82]); and CT patterns such as Ground Glass Opacities (GGO) (OR 1.03 [95% CI 0.78 -1.34]), air bronchogram (OR 0.78 [95% CI 0.44 -1.39]), pleural retraction (OR 0.83 [95% CI 0.53 - 1.28]), and spiculation (OR 0.80 [95% CI 0.48 - 1.31]) were not significantly associated to a specific mutation. Specific EGFR exon 21 and 19 mutations cannot be differentiated through characteristics (absence of smoking status and female sex) or radiological patterns (GGO, air bronchogram, pleural retraction, and speculation). There is limited data to assess if early disease stage or vascular convergence aids in differentiating exon 21 from 19 mutations in patients with lung adenocarcinoma.

Molecular typing of lung adenocarcinoma with computed tomography and CT image-based radiomics: a narrative review of research progress and prospects

Objective

The purpose of this paper was to perform a narrative review of current research evidence on conventional computed tomography (CT) imaging features and CT image-based radiomic features for predicting gene mutations in lung adenocarcinoma and discuss how to translate the research findings to guide future practice.

Background

Lung cancer, especially lung adenocarcinoma, is the leading cause of cancer-related deaths. With advances in the diagnosis and treatment of lung adenocarcinoma with the emergence of molecular testing, the prediction of oncogenes and even drug resistance gene mutations have become key to individualized and precise clinical treatment in order to prolong survival and improve quality of life. The progress of imageological examination includes the development of CT and radiomics are promising quantitative methods for predicting different gene mutations in lung adenocarcinoma, especially common mutations, such as epidermal growth factor receptor (EGFR) mutation, anaplastic lymphoma kinase (ALK) mutation and Kirsten rat sarcoma viral oncogene (KRAS) mutation.

Methods

The PubMed electronic database was searched along with a set of terms specific to lung adenocarcinoma, radiomics (including texture analysis), CT, computed tomography, EGFR, ALK, KRAS, rearranging transfection (RET) rearrangement and c-ros oncogene 1 (ROS-1), v-raf murine sarcoma viral oncogene homolog B1 (BRAF), and human epidermal growth factor receptor 2 (HER2) mutations et al. This review has been reported in compliance with the Narrative Review checklist guidelines. From each full-text article, information was extracted regarding a set of terms above.

Conclusions

Research on the application of conventional CT features and CT image-based radiomic features for predicting the gene mutation status of lung adenocarcinoma is still in a preliminary stage. Noninvasively determination of mutation status in lung adenocarcinoma before targeted therapy with conventional CT features and CT image-based radiomic features remains both hopes and challenges. Before radiomics could be applied in clinical practice, more work needs to be done.

Clinical and CT patterns to predict EGFR mutation in patients with non-small cell lung cancer: A systematic literature review and meta-analysis

Purpose

This study aims to determine if the presence of specific clinical and computed tomography (CT) patterns are associated with epidermal growth factor receptor (EGFR) mutation in patients with non-small cell lung cancer.

Methods

A systematic literature review and meta-analysis was carried out in 6 databases between January 2002 and July 2021. The relationship between clinical and CT patterns to detect EGFR mutation was measured and pooled using odds ratios (OR). These results were used to build several mathematical models to predict EGFR mutation.

Results

34 retrospective diagnostic accuracy studies met the inclusion and exclusion criteria. The results showed that ground-glass opacities (GGO) have an OR of 1.86 (95%CI 1.34 −2.57), air bronchogram OR 1.60 (95%CI 1.38 – 1.85), vascular convergence OR 1.39 (95%CI 1.12 – 1.74), pleural retraction OR 1.99 (95%CI 1.72 – 2.31), spiculation OR 1.42 (95%CI 1.19 – 1.70), cavitation OR 0.70 (95%CI 0.57 – 0.86), early disease stage OR 1.58 (95%CI 1.14 – 2.18), non-smoker status OR 2.79 (95%CI 2.34 – 3.31), female gender OR 2.33 (95%CI 1.97 – 2.75). A mathematical model was built, including all clinical and CT patterns assessed, showing an area under the curve (AUC) of 0.81.

Conclusions

GGO, air bronchogram, vascular convergence, pleural retraction, spiculated margins, early disease stage, female gender, and non-smoking status are significant risk factors for EGFR mutation. At the same time, cavitation is a protective factor for EGFR mutation. The mathematical model built acts as a good predictor for EGFR mutation in patients with lung adenocarcinoma.

•

GGO, air bronchogram, vascular convergence, pleural retraction, and spiculated margins, are risk factors for EGFR mutation.

•

Early disease stage, female gender and non-smoking status are risk factors for EGFR mutation.

•

Cavitation is a protective factor for EGFR mutation.

Prognosis of epidermal growth factor receptor-mutated stage I lung adenocarcinoma with radiologically solid features

OBJECTIVES

The prognostic role of the epidermal growth factor receptor (EGFR) mutation remains controversial, especially in early-stage lung adenocarcinoma with a solid appearance. We evaluated the oncological outcomes of clinical stage I (c-stage I) radiologically invasive lung adenocarcinoma by EGFR mutation status.

METHODS

Between 2008 and 2013, the data from 463 surgically resected c-stage I radiologically invasive, i.e. solid-dominant lung adenocarcinomas subjected to EGFR mutant analysis, were evaluated. Oncological outcomes were assessed using multivariable Cox regression analysis. Recurrence-free survival (RFS) was estimated using Kaplan-Meier analysis and the log-rank test.

RESULTS

A total of 229 (49%) samples harboured the EGFR-mutant adenocarcinoma. Overall, the 5-year RFS did not differ significantly between the EGFR-mutant and EGFR wild-type groups (67.3% vs 64.9%; P = 0.639). However, among the clinical T1c/T2a tumour subset (n = 177), a multivariable Cox hazard model revealed that radiologically pure-solid tumour (P = 0.024), EGFR-mutant (P = 0.027) and pathological stage II/III (P < 0.001) were significant predictors of a poor RFS. Furthermore, in the c-T1c/T2a radiologically pure-solid lung adenocarcinoma subset, the EGFR-mutant group showed marginally lower 5-year RFS compared to that with the EGFR wild-type group (n = 134; 34.9% vs 53.0%; P = 0.062). Among them, multivariable Cox regression analysis revealed that EGFR mutant (P = 0.037) and pathological stage II/III (P = 0.011) were independently and significantly prognostic for worse RFS.

CONCLUSIONS

Among the c-stage I radiologically invasive lung adenocarcinomas, the EGFR mutation-positive type was correlated with an increased risk of recurrence in the c-T1c/T2a radiologically pure-solid tumour subset. When considering the prognostic value of EGFR mutations in early-stage lung adenocarcinoma, it is necessary to stratify them based on the presence of a ground-glass opacity component.

Lung cancer and epithelial-mesenchymal transition

Lung cancer (LC) is a leading cause of cancer-related death worldwide. Epithelial-mesenchymal transition (EMT) is a well-known phenomenon that promotes the invasive and metastatic capabilities of LC. Especially, EMT is assumed to be a pivotal mechanism for tumor cell invasion and metastasis, thereby limiting the efficacy of surgery and medical treatments, resulting in poor patient prognoses. Thus, the elucidation and reversal of EMT could provide changes in therapeutic strategies for LC. To overcome the limitations of currents treatment regimens for LC, it is important for surgeons to be familiar with this complex tumor characteristic. In this review, the activating signaling pathways underlying EMT and the associated tumor phenotypes are briefly described.

Relationship between epidermal growth factor receptor mutations and CT features in patients with lung adenocarcinoma

AIM

The purpose of this study was to investigate the relationship between epidermal growth factor receptor (EGFR) mutation status and computed tomography (CT) features in patients with lung adenocarcinoma.

MATERIALS AND METHODS

A total of 483 patients with lung adenocarcinoma diagnosed between January 2015 and April 2020 were included in this study. All patients underwent a preoperative chest CT, and a total of 31 detailed CT features were quantified. The mutation status of EGFR exon 18-21 was detected by a polymerase chain reaction (PCR)-based amplified refractory mutation system. Student's t and Fisher's exact or chi-square tests were used to compare continuous and categorical variables, respectively. Least absolute shrinkage and selection operator (LASSO) regularisation was used to determine the optimal combination of CT features and clinical characteristics to predict the EGFR mutation status. The model was tested using a validation set consisting of 120 patients.

RESULTS

EGFR mutations were found in 249 (51.6%) of 483 patients with lung adenocarcinoma. Univariate analysis showed that 14 CT features and two clinical characteristics correlated significantly with the EGFR mutation status. Smoking history, long-axis diameter, bubble-like lucency, pleural retraction, thickened bronchovascular bundles, and peripheral emphysema were independent predictors of the EGFR mutation status, according to LASSO regularisation. In the training and verification cohorts, the areas under the curve of the prediction model were 0.766 and 0.745, respectively.

CONCLUSIONS

CT features of patients with lung adenocarcinoma can help predict the EGFR mutation status.

Nomogram based on preoperative CT imaging predicts the EGFR mutation status in lung adenocarcinoma

•

Tyrosine kinase inhibitors (TKIs) provide clinical benefits to the lung cancer patients with epidermal growth factor receptor (EGFR) mutations.

•

Non-invasively determine EGFR mutation status in patients before targeted therapy remains a challenge.

•

The personalized nomogram model of CT features and clinical risk factors can easily and noninvasively predict the EGFR mutation status before surgery.

Tyrosine kinase inhibitors (TKIs) provide clinical benefits to the lung cancer patients with epidermal growth factor receptor (EGFR) mutations. However, non-invasively determine EGFR mutation status in patients before targeted therapy remains a challenge. This study aimed to develop and validate a nomogram for preoperative prediction of EGFR mutation status in patients with lung adenocarcinoma. The medical records of 403 patients with lung adenocarcinoma confirmed by histology from January 2016 to June 2020 were retrospectively collected. We combined CT features and clinical risk factors and used them to build a prediction nomogram. The performance of the nomogram was evaluated in terms of calibration, discrimination, and clinical usefulness. The nomogram was further validated in an independent external cohort. Finally, a nomogram that contained CT features and clinical risk factors, which could conveniently and non-invasively predict EGFR mutation status in patients with lung adenocarcinoma before surgery.

Epidermal growth factor receptor mutations in lung adenocarcinoma: associations between dual-energy spectral CT measurements and histologic results

OBJECTIVE

To analyze the relationship between dual-energy spectral CT and epidermal growth factor receptor (EGFR) mutation status in patients with lung adenocarcinoma.

METHODS

The quantitative parameters of spectral CT were analyzed in 208 patients with lung adenocarcinoma. The quantitative parameters including CT_40keV and CT_70keV values, effective atomic number (Zeff), iodine concentration (IC), water concentration (WC), and the slope of the spectral curve (λ _HU) were calculated. Statistical analysis was used to determine the clinical characteristics and quantitative parameters for the diagnosis of EGFR-mutation status. The ROC curves were used to calculate diagnostic efficiency.

RESULTS

Sex (p = 0.027) and smoking history (p = 0.019) differed significantly according to the EGFR-mutation status. Spectral CT quantitative parameters (CT_40keV and CT_70keV values, λ _HU, Zeff and IC) differed significantly between the EGFR mutant and the EGFR wild-type groups (p < 0.05) during the arterial phase (AP) and venous phase (VP). However, WC was not statistically different between the two groups (p > 0.05). ROC curve analysis revealed the combination of the significantly different quantitative parameters provided the best diagnostic performance for determining the EGFR-mutation status (AUC: 76.0%) in the AP, while the AUC during the VP was 75.6%.

CONCLUSION

The quantitative parameters of dual-energy spectral CT have potential value for identifying the EGFR-mutation status.

Prognostic impact of preoperative FDG-PET positive lymph nodes in lung cancer

BACKGROUND

2-[¹⁸F] Fluoro-D-deoxyglucose positron emission tomography (FDG-PET) is an appropriate diagnostic procedure for staging lung cancer. However, accurate evaluation of lymph node (LN) metastases by PET is controversial owing to false-positive/-negative FDG uptake results. The prognostic significance of both false-negative and false-positive LNs on FDG-PET remains to be determined.

METHODS

A total of 235 patients with lung cancer were retrospectively analyzed. Maximum standardized uptake values (SUVmax) of the lymph nodes were compared with pathological LN metastases to correlate PET findings with clinicopathological variables and patients' outcomes.

RESULTS

When SUVmax ≥ 4 was defined as PET-positive for LN metastasis, sensitivity, specificity, and accuracy were 46.0%, 79.5%, and 72.3%, respectively. False-negative cases and pathological n0 cases were significantly younger, had primary tumors that were smaller or lower SUVmax, and adenocarcinomas compared with false-positive and pathological n⁺ cases. The difference in survival time between patients with abnormal FDG uptake in the LN and those without was larger than that between pathological LN metastases and no pathological metastases in patients with adenocarcinoma. Multivariate analysis by the Cox proportional hazard model identified smoker, EGFR/ALK negative and LN positive on PET as significant adverse prognostic factors, rather than pathological n-stage.

CONCLUSIONS

Abnormal FDG uptake in the LN is an important prognostic factor. Increased glucose metabolism on FDG-PET appears to be a more efficient postoperative prognostic marker than pathological n-stage in patients with lung cancer.

Comparative postoperative outcomes of GGN-dominant vs single lesion lung adenocarcinomas

Background

Multiple synchronous ground glass nodules (GGNs) are known to be malignant, however, they tend to progress slowly. Multiple synchronous lesions in the same patient which show different characteristics must be treated individually.

Methods

This was a retrospective review of 34 lung adenocarcinoma patients with multiple synchronous GGNs in an Asian population. One hundred twenty-seven single lung adenocarcinoma patients were included for comparison purposes. The follow-up period was 5 years for all patients.

Results

The 5-year overall survival (OS) patients with multiple lesions did not differ from that of the patients with single lesions to a statistically significant extent (Single: 81.8% vs. Multiple: 88.2%, P = 0.3602). Dominant tumors (DTs) with a ground glass component and consolidation were divided into three categories based on the consolidation-to-tumor ratio on radiological imaging. No significant differences were observed among the three DT categories. Twenty-four patients had unresected GGNs, while a progression of the unresected GGN occurred in 10 of these cases. The OS and disease-free survival (DFS) curves of patients with and without GGN progression did not differ to a statistically significant extent (OS: 80% vs. 92.9%, P = 0.3870; DFS: 80% vs. 100%, P = 0.0977).

Conclusions

The outcomes were best predicted by the stage of the DT. After surgery patients require a careful follow-up because unresected GGNs may show progression. At the same time, the increase in residual lesions and the appearance of new GGNs were not related to OS. The management of such patients should be determined according to the DT with the worst prognosis.

Clinicopathological and Prognostic Significance of EML4-ALK Rearrangement in Patients with Surgically Resected Lung Adenocarcinoma: A Propensity Score Matching Study

Objective

The echinoderm microtubule-associated protein-like 4-anaplastic lymphoma kinase (EML4-ALK) fusion gene is a key oncogenic driver in non-small cell lung cancer (NSCLC). This study analyzed the clinicopathological characteristics and prognostic significance of EML4-ALK fusion gene in patients with surgically resected adenocarcinoma.

Methods

The clinicopathological characteristics of 1056 consecutive patients with surgically resected stage I-IIIA adenocarcinoma were collected from February 2014 to October 2014, and EML4-ALK rearrangement was detected using real-time polymerase chain reaction (RT-PCR) technology. To compare the imaging and pathological features, a propensity score matching (PSM) method was performed. The follow-up information was collected to evaluate the long-term outcomes of patients with EML4-ALK rearrangement.

Results

The prevalence of EML4-ALK rearrangement was 6.6% in 1056 consecutive patients. A total of 70 EML4-ALK-positive and 210 EML4-ALK-negative patients were identified after PSM. Imaging and pathological analyses showed that EML4-ALK rearrangement was significantly associated with less ground-glass opacity (GGO) (adjusted OR=1.38, 95% CI=1.03-1.85, P_trend =0.029) and higher prevalence of non-invasive mucinous adenocarcinoma mucin-laden adenocarcinomas (non-IMA MLA, adjusted OR=6.79, 95% CI=2.69-17.17, P<0.001). EML4-ALK rearrangement was found to be an unfavorable prognostic factor for disease-free survival (DFS) in female patients (HR=2.26, 95% CI=1.13-4.53, P=0.021).

Conclusion

Our results suggest that adenocarcinomas harboring EML4-ALK fusion gene exhibit specific radiological and pathological characteristics compared with EML4-ALK-negative adenocarcinomas. In female patients, EML4-ALK rearrangement was associated with shorter DFS.

The prognostic implications of EGFR mutation and ALK rearrangement for the long-term outcomes of patients with resected lung adenocarcinomas

Background

To investigate the prognostic impact of epidermal growth factor receptor (EGFR) mutation and anaplastic lymphoma kinase (ALK) rearrangement for the overall survival (OS) of patients with surgically treated lung adenocarcinomas.

Methods

A total of 689 patients with stage I–III lung adenocarcinomas (male:female = 334:355; median age, 64 years) underwent complete surgical resection between 2007 and 2013. The prognostic impact of EGFR mutation and ALK rearrangement on OS was analyzed using Cox regression analysis. Certain clinicopathological prognostic factors (i.e., age, sex, smoking status, nodule type, solid portion size, pathologic stage, adenocarcinoma subtype, and history of adjuvant chemotherapy) were included for adjustments of the hazard ratio (HR).

Results

EGFR mutation was observed in 438 patients (64%) and ALK rearrangement was seen in 28 patients (4%). Multivariable‐adjusted Cox regression demonstrated that the prognostic effect of EGFR mutation on OS differed by age (HR, exp.[−5.199 + 0.064^*age]). The adjusted HR for EGFR mutation was 0.14 (95% CI: 0.05–0.36; P < 0.001) at 50 years, 0.26 (95% CI: 0.15–0.46; P < 0.001) at 60 years, and 0.50 (95% CI: 0.31–0.81; P = 0.005) at 70 years. However, the effect of ALK rearrangement on OS was without statistical significance (P > 0.05).

Conclusions

EGFR mutation was independently prognostic of the long‐term outcomes of patients with surgically treated lung adenocarcinomas. A more favorable prognostic effect was seen in younger than in older patients. ALK rearrangement was not associated with OS.