Novel biologic factors correlated to visceral pleural invasion in early-stage non-small cell lung cancer less than 3 cm

Integrating radiomics features and CT semantic characteristics for predicting visceral pleural invasion in clinical stage Ia peripheral lung adenocarcinoma

OBJECTIVES

The aim of this study was to non-invasively predict the visceral pleural invasion (VPI) of peripheral lung adenocarcinoma (LA) highly associated with pleura of clinical stage Ia based on preoperative chest computed tomography (CT) scanning.

METHODS

A total of 537 patients diagnosed with clinical stage Ia LA underwent resection and were stratified into training and validation cohorts at a ratio of 7:3. Radiomics features were extracted using PyRadiomics software following tumor lesion segmentation and were subsequently filtered through spearman correlation analysis, minimum redundancy maximum relevance, and least absolute shrinkage and selection operator regression analysis. Univariate and multivariable logistic regression analyses were conducted to identify independent predictors. A predictive model was established with visual nomogram and independent sample validation, and evaluated in terms of area under the receiver operating characteristic curve (AUC).

RESULTS

The independent predictors of VPI were identified: pleural attachment (p < 0.001), pleural contact angle (p = 0.019) and Rad-score (p < 0.001). The combined model showed good calibration with an AUC of 0.843 (95% confidence intervals (CI 0.796, 0.882), in contrast to 0.757 (95% CI 0.724, 0.785; DeLong's test P < 0.001) and 0.715 (95% CI 0.688, 0.746; DeLong's test P < 0.001) when only radiomics or CT semantic features were utilized separately. For validation group, the accuracy of combined prediction model was reasonable with an AUC of 0.792 (95% CI 0.765, 0.824).

CONCLUSION

Our predictive model, which integrated radiomics features of primary tumors and peritumoral CT semantic characteristics, offers a non-invasive method for evaluating VPI in patients with clinical stage Ia LA. Additionally, it provides prognostic information and supports surgeons in making more personalized treatment decisions.

Development and validation of a nomogram for predicting visceral pleural invasion in patients with early-stage non-small cell lung cancer

Background

Visceral pleural invasion (VPI) is associated with a poor outcome in early-stage non-small cell lung cancer (NSCLC). Preoperative prediction of VPI could have an impact on surgical planning. The aim of this study was to establish a nomogram model based on computed tomography (CT) features to predict VPI in early-stage NSCLC.

Methods

This study is a retrospective review of patients enrolled with surgically pathologically confirmed NSCLC between December 2019 and June 2022. Patients were divided into training and testing cohorts at a ratio of 7:3. Clinicopathologic and radiologic characteristics such as types of tumor pleura relationships (types I-V) were recorded. Multivariable logistic regression analysis was used to identify independent risk factors for VPI, and the optimized variables were used to build a nomogram model. Model performance was evaluated with receiver operating characteristic (ROC) curves and calibration curves. The clinical utility of the nomogram was determined using decision curve analysis (DCA).

Results

Of the 766 patients [56.9% female patients; median age, 59 years; interquartile range (IQR): 53, 66] with early-stage NSCLC, VPI was confirmed in 250 patients (32.6%). There were 536 individuals in the training cohort (172 with VPI and 364 without VPI), and 230 individuals in the testing cohort (78 with VPI and 152 without VPI). The preoperative CT features related to VPI were tumor pleura relationship of type I and type III, solid, maximum diameter of tumor, lobulation, and lymphadenopathy. There was good discriminative power in the nomogram that included these six features. The training and testing cohorts' areas under the ROC curve (AUCs) were 0.815 and 0.825, respectively, with well-fitting calibration curves. DCA demonstrated that the nomogram was clinically useful.

Conclusions

The nomogram established with the identified CT features has the potential to assist with the prediction of VPI preoperatively in early-stage NSCLC and facilitate the selection of a rational treatment strategy.

Using the length of pleural tag to predetermine pleural invasion by lung adenocarcinomas

Introduction

Pleural contact is present when the underlying pathology of the pleural tag (PT) involves the pleura. This study aimed to preoperatively predict PI by lung adenocarcinomas (ACCs) with PT, exploring CT imaging parameters indicative of PT consisting of pleura and tumor invasiveness.

Methods

This single-center, retrospective study included 84 consecutive patients diagnosed with solid ACCs with PT, who underwent resection at our hospital between May 2019 and July 2023. CT imaging parameters analyzed included: LPT (the length of PT), defined as the shortest distance from the tumor edge to the retracted pleura. Patients were divided into PI -ve group and PI +ve group according to PI status. Regression analyses were used to determine predictive factors for PI.

Results

The study evaluated 84 patients (mean age, 62.0 ± 13.8 years; 45 females) pathologically diagnosed with ACCs with PT on CT. Multivariate regression analysis identified tumor size (OR 1.18, 95% CI 1.09-1.29, p = 0.000), LPT (OR 0.48, 95% CI 0.25-0.91, p = 0.03) and multiple PTs to multiple types of pleura (OR 3.58, 95% CI 1.13-11.20, p = 0.03) as independent predictors for PI. The combination of these CT features improved the predictive performance for preoperatively identifying PI, achieving high specificity and moderate accuracy. The sensitivity of predicting PI with only LPT < 3 mm was 96.9%.

Conclusion

This study determined that LPT is effective for predetermining PI in ACCs with PT.

Baseline computed tomography imaging findings could assist in early diagnosis of visceral pleural invasion for newly discovered early subpleural non-small cell lung cancer: T1 or T2

Background

Preoperative accurate visceral pleural infiltration (VPI) diagnosis for T1-size non-small cell lung cancer (NSCLC) is significant for clinical decision-making. The study aimed to explore the diagnostic efficacy of computed tomography (CT) imaging features and serum biomarkers in diagnosing VPI in newly discovered subpleural NSCLC ≤3 cm.

Methods

There were 447 patients with NSCLC ≤3 cm retrospectively enrolled and assigned to the VPI group (n=81) and the non-VPI group (n=366) based on elastic fiber staining results. The serum biomarkers and CT imaging features were obtained for each subject. Univariate and multivariate analyses were used to identify the independent predictors for VPI. Area under the receiver operating characteristic (ROC) curve (AUC) was used to evaluate the diagnostic performance of each independent predictor and combined predictors in predicting VPI, with performance compared using the DeLong test.

Results

For tumor biomarkers, the VPI group had a significantly higher percentage of cases with abnormal carcino-embryonic antigen (CEA) level, cytokeratin 19 fragment (CYFRA21-1) level, and pro-gastrin-releasing peptide (ProGRP) level than that of the non-VPI group (P<0.001, P=0.003, P=0.004). However, in multivariate analysis, only the lesion-pleura relationship patterns type Ia [odds ratio (OR) =20.689; 95% confidence interval (CI): 5.058-84.622; P<0.001], type Ib (OR =5.155; 95% CI: 1.178-22.552; P=0.03), type II (OR =7.154; 95% CI: 1.733-29.53; P=0.007) with type III as reference, solid lesion density (OR =9.954; 95% CI: 4.976-19.911; P<0.001) with part-solid density as reference were identified as the independent predictors for VPI. In predicting VPI, the combined model (AUC =0.885) significantly outperformed models based on lesion density (AUC =0.833) and lesion-pleura relationship patterns (AUC =0.655) (all P<0.001).

Conclusions

The CT predictors for VPI in patients with subpleural NSCLC (≤3 cm) were lesion density and lesion-pleura relationship patterns (pleural attachment and indentation), but not serum tumor biomarkers.

Diagnosis, treatment, and prognosis of stage IB non-small cell lung cancer with visceral pleural invasion

With the increasing implementation of early lung cancer screening and the increasing emphasis on physical examinations, the early-stage lung cancer detection rate continues to rise. Visceral pleural invasion (VPI), which denotes the tumor's breach of the elastic layer or reaching the surface of the visceral pleura, stands as a pivotal factor that impacts the prognosis of patients with non-small cell lung cancer (NSCLC) and directly influences the pathological staging of early-stage cases. According to the latest 9th edition of the TNM staging system for NSCLC, even when the tumor diameter is less than 3 cm, the final T stage remains T2a if VPI is present. There is considerable controversy within the guidelines regarding treatment options for stage IB NSCLC, especially among patients exhibiting VPI. Moreover, the precise determination of VPI is important in guiding treatment selection and prognostic evaluation in individuals with NSCLC. This article aims to provide a comprehensive review of the current status and advancements in studies pertaining to stage IB NSCLC accompanied by VPI.

CT-based radiomics nomogram for predicting visceral pleural invasion in peripheral T1-sized solid lung adenocarcinoma

The preoperative assessment of visceral pleural invasion (VPI) in patients with early lung adenocarcinoma is vital for surgical treatment. This study aims to develop and validate a CT-based radiomics nomogram to predict VPI in peripheral T1-sized solid lung adenocarcinoma. A total of 203 patients were selected as subjects, and were divided into a training cohort (n=141; scanned with Brilliance iCT256, Brilliance 64, Somatom Force, and Optima CT660) and a test cohort (n=62; scanned with Somatom Definition AS+). Radiomics characteristics were extracted from CT images. Variance thresholding, SelectKBest, and least absolute shrinkage and selection operator (LASSO) method were applied to determine optimum characteristics to construct the radiomic signature (radscore). After multivariate logistic regression analysis, a nomogram was structured regarding clinical factors, conventional CT features, and radscore. The nomogram property was tested based on its area under the curve (AUC). The nomogram based on the radscore and two conventional CT features (tumor pleura relationship and lymph node enlargement) showed high discrimination with an AUC of 0.877 (95% CI: 0.820-0.935) and 0.837 (95% CI: 0.737-0.937) in the training and test cohorts, respectively. The calibration curve and decision curve analysis showed good consistency and high clinical value of the nomogram. In conclusion, The CT-based radiomics nomogram was helpful in predicting VPI in peripheral T1-sized solid lung adenocarcinoma.

Correlations between iodine uptake, invasive CT features and pleural invasion in adenocarcinomas with pleural contact

Pleural contact in lung cancers does not always imply pleural invasion (PI). This study was designed to determine whether specific invasive CT characteristics or iodine uptake can aid in the prediction of PI. The sample population comprised patients with resected solid lung adenocarcinomas between April 2019 and May 2022. All participants underwent a contrast enhanced spectral CT scan. Two proficient radiologists independently evaluated the CT features and iodine uptake. Logistic regression analyses were employed to identify predictors for PI, via CT features and iodine uptake. To validate the improved diagnostic efficiency, accuracy analysis and ROC curves were subsequently used. A two-tailed P value of less than 0.05 was considered statistically significant. We enrolled 97 consecutive patients (mean age, 61.8 years ± 10; 48 females) in our study. The binomial logistic regression model revealed that a contact length > 10 mm (OR 4.80, 95% CI 1.92, 11.99, p = 0.001), and spiculation sign (OR 2.71, 95% CI 1.08, 6.79, p = 0.033) were independent predictors of PI, while iodine uptake was not. Enhanced sensitivity (90%) and a greater area under the curve (0.73) were achieved by integrating the two aforementioned CT features in predicting PI. We concluded that the combination of contact length > 10 mm and spiculation sign can enhance the diagnostic performance of PI.

Multivariate analysis based on the maximum standard unit value of 18F-fluorodeoxyglucose positron emission tomography/computed tomography and computed tomography features for preoperative predicting of visceral pleural invasion in patients with subpleural clinical stage IA peripheral lung adenocarcinoma

PURPOSE

Preoperative prediction of visceral pleural invasion (VPI) is important because it enables thoracic surgeons to choose appropriate surgical plans. This study aimed to develop and validate a multivariate logistic regression model incorporating the maximum standardized uptake value (SUVmax) and valuable computed tomography (CT) signs for the non-invasive prediction of VPI status in subpleural clinical stage IA lung adenocarcinoma patients before surgery.

METHODS

A total of 140 patients with subpleural clinical stage IA peripheral lung adenocarcinoma were recruited and divided into a training set (n = 98) and a validation set (n = 42), according to the positron emission tomography/CT examination temporal sequence, with a 7:3 ratio. Next, VPI-positive and VPI-negative groups were formed based on the pathological results. In the training set, the clinical information, the SUVmax, the relationship between the tumor and the pleura, and the CT features were analyzed using univariate analysis. The variables with significant differences were included in the multivariate analysis to construct a prediction model. A nomogram based on multivariate analysis was developed, and its predictive performance was verified in the validation set.

RESULTS

The size of the solid component, the consolidation-to-tumor ratio, the solid component pleural contact length, the SUVmax, the density type, the pleural indentation, the spiculation, and the vascular convergence sign demonstrated significant differences between VPI-positive (n = 40) and VPI-negative (n = 58) cases on univariate analysis in the training set. A multivariate logistic regression model incorporated the SUVmax [odds ratio (OR): 1.753, P = 0.002], the solid component pleural contact length (OR: 1.101, P = 0.034), the pleural indentation (OR: 5.075, P = 0.041), and the vascular convergence sign (OR: 13.324, P = 0.025) as the best combination of predictors, which were all independent risk factors for VPI in the training group. The nomogram indicated promising discrimination, with an area under the curve value of 0.892 [95% confidence interval (CI), 0.813-0.946] in the training set and 0.885 (95% CI, 0.748-0.962) in the validation set. The calibration curve demonstrated that its predicted probabilities were in acceptable agreement with the actual probability. The decision curve analysis illustrated that the current nomogram would add more net benefit.

CONCLUSION

The nomogram integrating the SUVmax and the CT features could non-invasively predict VPI status before surgery in subpleural clinical stage IA lung adenocarcinoma patients.

Predictive Value of 18 F-FDG PET/MRI for Pleural Invasion in Solid and Subsolid Lung Adenocarcinomas Smaller Than 3 cm

BACKGROUND

Positron emission tomography (PET)/MRI combines the characteristics of metabolism imaging and high soft tissue resolution, and could provide high diagnostic efficacy for assessment of pleural invasion (PI) of lung cancer.

PURPOSE

To investigate the application of ¹⁸ F-fluorodeoxyglucose (FDG) PET/MRI for predicting PI of lung cancer with the maximum diameter ≤3 cm.

STUDY TYPE

Prospective.

POPULATION

A total of 44 patients with non-small cell lung cancer (NSCLC), age from 39 to 79 years old, including 19 (56.82%) females.

FIELD STRENGTH/SEQUENCE

A 3-T, hybrid PET/MRI including axial fast spin echo respiratory-triggered T2 fat-suppressed imaging (T2FS) and echo planar imaging diffusion-weighted imaging (DWI).

ASSESSMENT

The maximum standardized uptake value (SUVmax) of all lesions was measured on PET images. Localized effusion outside the contact between the nodules and the pleura on T2FS and signal at the contact between the nodules and the pleura on DWI were evaluated by experienced physicians through visual assessment of the MRI sequences.

STATISTICAL TESTS

Three models (models 1-3) were developed, incorporating CT, CT and PET, PET and MRI features, and Lasso regression was used in feature selection. The receiver operating characteristic (ROC) curve for PI diagnosis was visualized for each model, and the area under the curve (AUC) was calculated. The DeLong test was used to compare the different AUCs. A P value < 0.05 was considered statistically significant.

RESULTS

The AUC of models 1-3 was 0.762, 0.829, and 0.915, respectively. The DeLong test showed a statistically significant difference between the AUCs of model 1 vs. model 3, while the differences between the AUCs of model 1 vs. model 2 (P = 0.253) and model 2 vs. model 3 (P = 0.075) were not statistically significant.

DATA CONCLUSION

¹⁸ F-FDG PET/MRI might show high predictive value for lung adenocarcinoma smaller than 3 cm with PI.

EVIDENCE LEVEL

1 TECHNICAL EFFICACY: Stage 2.

The Value of 18F-FDG PET/CT in the Diagnosis of Tuberculous Pleurisy and in the Differential Diagnosis between Tuberculous Pleurisy and Pleural Metastasis from Lung Adenocarcinoma

Objectives

This study aims to investigate the diagnostic value of 18F-FDG PET/CT in tuberculous pleurisy (TBP) and the differential diagnostic value of 18F-FDG PET/CT between TBP and pleural metastasis from lung adenocarcinoma (PMLAC).

Materials and Methods

The features of pleura on PET and hybrid CT were retrospectively studied in 20 patients with TBP and 32 patients with PMLAC. The ROC curve was used to evaluate the diagnostic effectiveness of these indices for TBP and PMLAC, and binary logistic regression analysis was conducted to identify independent predictors of TBP and PMLAC.

Results

There were significant differences in pleural 18F-FDG uptake pattern on PET (P=0.001), pleural morphology pattern on CT (P=0.002), the maximum diameter of the pleural nodule (P=0.001), and interlobular fissure nodule (P=0.001) between TBP and PMLAC groups. The diffused pleural FDG uptake type on PET (odds ratio (OR) = 6.0, 95% CI 2.216–16.248, P=0.001) and the lamellar pleural thickening type on CT (OR = 4.4, 95% CI 2.536–7.635, P=0.001) were independent predictors of TBP, with 60% and 55% sensitivity, 96.6% and 90.6% specificity, and 82.7% and 77.0% accuracy. The combined diagnostic sensitivity, specificity, and accuracy for TBP were 70%, 87.5%, and 80.8%. The mixed pleural FDG uptake type on PET (OR = 5.106, 95% CI 2.024–12.879, P=0.001), the mixed pleural thickening type on CT (OR = 2.289, 95% CI 1.442–3.634, P=0.001), and the maximum diameter of the pleural nodule (OR = 1.027, 95% CI 1.012–1.042, P=0.001) were independent predictors of PMLAC, with 78.1%, 71.9%, and 87.5% sensitivity, 85%, 80%, and 85% specificity, and 80.8%, 75%, and 86.5% accuracy. The combined diagnostic sensitivity, specificity, and accuracy for PMLAC were 96.9%, 85%, and 90.4%.

Conclusions

18F-FDG PET/CT is of great clinical value in the diagnosis of TBP and in the differential diagnosis between TBP and PMLAC.

Rethinking the Selection of Pathological T-Classification for Non-Small-Cell Lung Cancer in Varying Degrees of Visceral Pleural Invasion: A SEER-Based Study

Background

The T classification of non-small-cell lung cancer (NSCLC) was upgraded from T1 to T2 when accompanied by visceral pleural invasion (VPI). However, the association between VPI and prognostic outcomes was obscure in NSCLC patients with ≤3 cm tumor size (TS), which leaded the controversy of selection of T classification. The goal was to evaluate the effect of VPI on the prognosis of NSCLC with ≤ 3cm TS and present a modified T classification.

Methods

A total of 14,934 NSCLC patients without distant metastasis were recruited through a retrospective study in the SEER database. The effect of VPI on lung cancer specific survival (LCSS) was evaluated using survival curve and COX regression analysis in NSCLC patients with ≤3 cm TS.

Results

Although there was no difference of the LCSS of PL0 and PL1 patients with ≤2 cm TS in patients without lymph node (LN) metastasis, the LCSS was lower in PL2 patients than those in PL0 (T1a: p < 0.001; T1b: p = 0.001). Moreover, the LCSS was decreased in PL1 and PL2 patients with 2-3 cm TS compared with PL0 (T1c: PL1, p < 0.001; PL2, p = 0.009) of patients without LN metastasis. No difference of LCSS was observed in patients with LN metastasis between PL0 with PL1 and PL2.

Conclusion

In NSCLC patients without LN metastasis and TS ≤ 2 cm, tumor with PL1 should remain defined as T1, tumor with PL2 should be defined as T2. However, 2-3 cm TS patients with PL1 or PL2 should both defined as T2. Meanwhile, ≤3 cm TS patients with LN metastasis can be regarded as T1, whether NSCLC patients accompanied with PL1 or PL2.

Is lobectomy superior to sub-lobectomy in non-small cell lung cancer with pleural invasion? A population-based competing risk analysis

Background

Pleural invasion (PL) has been regarded as an unfavorable prognostic factor for non-small cell lung cancer (NSCLC). But there was no agreement on the optimal surgical extent in NSCLC patients with PL. We aimed to compare the survival outcomes of lobectomy and sub-lobectomy in these patients.

Method

2717 patients were included in the Surveillance, Epidemiology, and End Results (SEER) database and divided into the lobectomy and sub-lobectomy groups. The propensity score matching (PSM) and competing risk analysis were implemented. Then the predictive nomogram was constructed and validated.

Results

2230 Patients received lobectomy while the other 487 patients underwent sub-lobectomy. After 1:1 PSM, the cumulative incidence of cancer-specific death (CSD) was lower in the lobectomy group compared with the sub-lobectomy group (1-year: 12% vs. 15%; 3-year: 30% vs. 37%, 5-year: 34% vs. 45%, P = 0.04). According to the subgroup analysis, the patients who underwent lobectomy suffered lower CSD in the N0–1 stage, adenocarcinoma, and PL-2 cohort (p < 0.05). And there was a significant relationship between the sub-lobectomy group and CSD in the multivariate competing risks regression analysis (HR, 1.26; 95%CI, 1.02–1.56; P = 0.034). Furthermore, a competing event nomogram was constructed to assess the 1-, 3-, and 5-year chances of CSD based on the variables from the multivariate analysis. The 1-, 3-, 5-year area under the receiver operating characteristic curve (AUC) values were 0.720, 0.706, and 0.708 in the training cohort, and 0.738, 0.696, 0.680 in the validation cohorts, respectively. And calibration curves demonstrated ideal consistency between the predicted and observed probabilities of CSD.

Conclusion

Lobectomy should be considered the preferred surgery compared to sub-lobectomy for NSCLC patients with PL. The proposed nomograms presented great prediction ability for these patients.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12885-022-09634-w.

The value of CT radiomics features to predict visceral pleural invasion in ≤3 cm peripheral type early non-small cell lung cancer

OBJECTIVE

To investigate predictive value of CT-based radiomics features on visceral pleural invasion (VPI) in ≤3.0 cm peripheral type early non-small cell lung cancer (NSCLC).

METHODS

A total of 221 NSCLC cases were collected. Among them, 115 are VPI-positive and 106 are VPI-negative. Using a stratified random sampling method, 70% cases were assigned to training dataset (n = 155) and 30% cases (n = 66) were assigned to validation dataset. First, CT findings, imaging features, clinical data and pathological findings were retrospectively analyzed, the size, location and density characteristics of nodules and lymph node status, the relationship between lesions and pleura (RAP) were assessed, and their mean CT value and the shortest distance between lesions and pleura (DLP) were measured. Next, the minimum redundancy-maximum relevance (mRMR) and least absolute shrinkage and selection operator (LASSO) features were extracted from the imaging features. Then, CT imaging prediction model, texture feature prediction model and joint prediction model were built using multifactorial logistic regression analysis method, and the area under the ROC curve (AUC) was applied to evaluate model performance in predicting VPI.

RESULTS

Mean diameter, density, fractal relationship with pleura, and presence of lymph node metastasis were all independent predictors of VPI. When applying to the validation dataset, the CT imaging model, texture feature model, and joint prediction model yielded AUC = 0.882, 0.824 and 0.894, respectively, indicating that AUC of the joint prediction model was the highest (p < 0.05).

CONCLUSION

The study demonstrates that the joint prediction model containing CT morphological features and texture features enables to predict the presence of VPI in early NSCLC preoperatively at the highest level.

The modification of T description according to visceral pleural invasion and tumor size from 3.1 cm to 4.0 cm in non-small cell lung cancer: A retrospective analysis based on the SEER database

OBJECTIVES

As a poor prognostic factor, visceral pleural invasion (VPI) was incorporated into non-small cell lung cancer (NSCLC) staging system. For modifying the T description of NSCLC, the prognostic value of VPI was assessed.

MATERIALS AND METHODS

From 2010-2015, data on stage pT2N0M0 NSCLC patients with tumor size (TS) from 3.1 cm to 5.0 cm who received surgery from the Surveillance, Epidemiology, and End Results (SEER) database were enrolled retrospectively. Propensity score matching was utilized to balance the baseline factors according to different TS intervals. Overall survival (OS) was assessed by the Kaplan-Meier method and log-rank test. Univariate and multivariate analysis were applied to identify the prognostic factors. The risk factors of VPI were calculated by logistic regression model.

RESULT

The sum of 4005 resected stage pT2N0M0 NSCLC patients with TS from 3.1 cm to 5.0 cm were recruited, which had 1084 patients with VPI and 2921 patients without VPI respectively. As TS interval of 3.1-4.0 cm, the 5-year OS of patients without VPI was significantly better than those with VPI (62.6 % vs 58.7 %, P = 0.015), while the 5-year OS of patients with VPI and TS interval of 3.1-4.0 cm had no significant difference compared with patients whose TS interval of 4.1-5.0 cm (58.7 % vs 58.8 %, P = 0.918). Logistic regressive analysis manifested that older age, female, worse differentiation grade and larger TS had higher incidence of VPI (OR = 1.01, 1.25, 1.25, 1.16, respectively; P < 0.05 for all).

CONCLUSION

This study underlined the prognostic effect of VPI and suggested that early-stage NSCLC with VPI and TS interval of 3.1-4.0 cm could be appropriately upstaged from pT2a (stage pIB) to pT2b (modified stage pIIA).

Sublobectomy versus lobectomy for long-term survival outcomes of early-stage non-small cell lung cancer with a tumor size ≤2 cm accompanied by visceral pleural invasion: a SEER population-based study

Background

The optimal surgical strategy for early-stage non-small cell lung cancer (NSCLC) with visceral pleural invasion (VPI) remains unclear. Due to limited prospective comparative data for these surgical modalities, the objective of the current study was to compare the long-term survival outcomes of sublobectomy (Sub) versus lobectomy (Lob) for NSCLC with a tumor size ≤2 cm and VPI.

Methods

Patients with early-stage NSCLC characterized by VPI diagnosed between 2004 and 2013 were identified from the Surveillance, Epidemiology, and End Results (SEER) program. The baseline demographic and cancer characteristics, treatment information as well as survival outcome data were extracted from the SEER database, and confounders were balanced by propensity score matching (PSM) and inverse probability of treatment weighting (IPTW) analyses. Lung disease-specific survival (DSS) and overall survival (OS) rates were compared with Cox proportional hazards (PH) regression models based on the unmatched cohort, the propensity-based matched cohort, and the IPTW cohort.

Results

Of the 1,386 patients enrolled, 1,000 (72.15%) and 386 (27.85%) underwent lobectomy and sublobectomy, respectively. The 5-year DSS rate was 78.64% for the lobectomy group and 59.47% for the sublobectomy group. Cox regression models demonstrated that the operation type (Sub vs. Lob) was an independent prognostic factor for early-stage NSCLC with VPI based on the three different cohorts. Patients who underwent lobectomy showed better long-term DSS and OS rates than those treated with sublobectomy after PSM [DSS: hazard ratio (HR) 0.689, 95% confidence interval (CI): 0.490–0.968, P=0.032; OS: HR 0.723, 95% CI: 0.549–0.953, P=0.021]. The IPTW analysis yielded similar results.

Conclusions

Lobectomy showed superior long-term survival compared with sublobectomy in patients with early-stage NSCLC with a tumor size ≤2 cm and VPI.

Impact of visceral pleural invasion on the association of extent of lymphadenectomy and survival in stage I non-small cell lung cancer

Visceral pleural invasion (VPI) has been identified as an adverse prognostic factor for non‐small cell lung cancer (NSCLC). Accurate nodal staging for NSCLC correlates with improved survival, but it is unclear whether tumors with VPI require a more extensive lymph nodes (LNs) dissection to optimize survival. We aimed to evaluate the impact of VPI status on the optimal extent of LNs dissection in stage I NSCLC, using the Surveillance, Epidemiology, and End Results (SEER) database. We identified 9297 surgically treated T1‐2aN0M0 NSCLC patients with at least one examined LNs. Propensity score matching was conducted to balance the baseline clinicopathologic characteristics between the VPI group and non‐VPI group. Log‐rank tests along with Cox proportional hazards regression methods were performed to evaluate the impact of extent of LNs dissection on survival. VPI was correlated with a significant worse survival, but there was no significant difference in survival rate between PL1 and PL2. Patients who underwent sublobectomy had slightly decreased survival than those who underwent lobectomy. Pathologic LNs examination was significantly correlated with survival. Examination of 7‐8 LNs and 14‐16 LNs conferred the lowest hazard ratio for T1‐sized/non‐VPI tumors (stage IA) and T1‐sized/VPI tumors (stage IB), respectively. The optimal extent of LNs dissection varied by VPI status, with T1‐sized/VPI tumors (stage IB) requiring a more extensive LNs dissection than T1‐sized/non‐VPI tumors (stage IA). These results might provide guidelines for surgical procedure in early stage NSCLC.