Predictive Factors for Lymph Node Metastasis in Clinical Stage IA Lung Adenocarcinoma

Computed tomography characteristics of cN0 primary non-small cell lung cancer predict occult lymph node metastasis

RATIONALE

Occult lymph node metastasis (OLNM) is frequently found in patients with resectable non-small cell lung cancer (NSCLC), despite using diagnostic methods recommended by guidelines.

OBJECTIVES

To evaluate the risk of OLNM in NSCLC patients using the radiologic characteristics of the primary tumor on computed tomography (CT).

METHODS

We retrospectively reviewed clinicopathologic features of 2042 clinical T1-4N0 NSCLC patients undergoing curative intent pulmonary resection. Unique radiological features (i.e., air-bronchogram throughout the whole tumor, heterogeneous ground-glass opacity (GGO), mainly cystic appearance, endobronchial location), percentage of solid portion, and shape of tumor margin were analyzed via a stepwise approach. We used multivariable logistic regression to assess the relationship between OLNM and tumor characteristics.

RESULTS

Compared with the other unique features, endobronchial tumors were associated with the highest risk of OLNM (OR = 3.9, 95% confidence interval (CI) = 2.29-6.62), and heterogeneous GGO and mainly cystic tumors were associated with a low risk of OLNM. For tumors without unique features, the percentage of the solid portion was measured, and solid tumors were associated with OLNM (OR = 2.49, 95% CI = 1.86-3.35). Among part-solid tumors with solid proportion > 50%, spiculated margin, and peri-tumoral GGO were associated with OLNM.

CONCLUSIONS

The risk of OLNM could be assessed using radiologic characteristics on CT. This could allow us to adequately select optimal candidates for invasive nodal staging procedures (INSPs) and complete systematic lymph node dissection.

CLINICAL RELEVANCE STATEMENT

These data may be helpful for clinicians to select appropriate candidates for INSPs and complete surgical systematic lymph node dissection in NSCLC patients.

KEY POINTS

Lymph node metastasis status plays a key role in both prognostication and treatment planning. Solid tumors, particularly endobronchial tumors, were associated with occult lymph node metastasis (OLNM). The risk of OLNM can be assessed using radiologic characteristics acquired from CT images.

The diagnosis and management of multiple ground-glass nodules in the lung

The prevalence of low-dose CT (LDCT) in lung cancer screening has gradually increased, and more and more lung ground glass nodules (GGNs) have been detected. So far, a consensus has been reached on the treatment of single pulmonary ground glass nodules, and there have been many guidelines that can be widely accepted. However, at present, more than half of the patients have more than one nodule when pulmonary ground glass nodules are found, which means that different treatment methods for nodules may have different effects on the prognosis or quality of life of patients. This article reviews the research progress in the diagnosis and treatment strategies of pulmonary multiple lesions manifested as GGNs.

Tumor distance from the mediastinum predicts N2 upstaging in clinical stage I lower-lobe non-small cell lung cancer

OBJECTIVE

Pulmonary lymphatic drainage of the lower lobe into the mediastinal lymph nodes includes not only the pathway via the hilar lymph nodes but also the pathway directly into the mediastinum via the pulmonary ligament. This study aimed to determine the association between the distance from the mediastinum to the tumor and the frequency of occult mediastinal nodal metastasis (OMNM) in patients with clinical stage I lower-lobe non-small cell lung cancer (NSCLC).

METHODS

Between April 2007 and March 2022, data of patients who underwent anatomical pulmonary resection and mediastinal lymph node dissection for clinical stage I radiological pure-solid lower-lobe NSCLC were retrospectively reviewed. In computed tomography axial sections, the ratio of the distance from the inner edge of the lung to the inner margin of the tumor within the lung width of the affected lung was defined as the inner margin ratio. Patients were divided into 2 groups based on whether the inner margin ratio was ≤0.50 (inner-type) or >0.50 (outer-type), and the association between inner margin ratio status and clinicopathological findings was assessed.

RESULTS

In total, 200 patients were enrolled in the study. OMNM frequency was 8.5%. More inner-type than outer-type patients had OMNM (13.2% vs 3.2%; P = .012) and skip N2 metastasis (7.5% vs 1.1%; P = .038). Multivariable analysis revealed that the inner margin ratio was the only independent preoperative predictor of OMNM (odds ratio, 4.72; 95% CI, 1.31-17.07; P = .018).

CONCLUSIONS

Tumor distance from the mediastinum was the most important preoperative predictor of OMNM in patients with lower-lobe NSCLC.

The role of adenocarcinoma subtypes and immunohistochemistry in predicting lymph node metastasis in early invasive lung adenocarcinoma

BACKGROUND

Identifying lymph node metastasis areas during surgery for early invasive lung adenocarcinoma remains challenging. The aim of this study was to develop a nomogram mathematical model before the end of surgery for predicting lymph node metastasis in patients with early invasive lung adenocarcinoma.

METHODS

In this study, we included patients with invasive lung adenocarcinoma measuring ≤ 2 cm who underwent pulmonary resection with definite pathology at Qilu Hospital of Shandong University from January 2020 to January 2022. Preoperative biomarker results, clinical features, and computed tomography characteristics were collected. The enrolled patients were randomized into a training cohort and a validation cohort in a 7:3 ratio. The training cohort was used to construct the predictive model, while the validation cohort was used to test the model independently. Univariate and multivariate logistic regression analyses were performed to identify independent risk factors. The prediction model and nomogram were established based on the independent risk factors. Recipient operating characteristic (ROC) curves were used to assess the discrimination ability of the model. Calibration capability was assessed using the Hosmer-Lemeshow test and calibration curves. The clinical utility of the nomogram was assessed using decision curve analysis (DCA).

RESULTS

The overall incidence of lymph node metastasis was 13.23% (61/461). Six indicators were finally determined to be independently associated with lymph node metastasis. These six indicators were: age (P < 0.001), serum amyloid (SA) (P = 0.008); carcinoma antigen 125 (CA125) (P = 0. 042); mucus composition (P = 0.003); novel aspartic proteinase of the pepsin family A (Napsin A) (P = 0.007); and cytokeratin 5/6 (CK5/6) (P = 0.042). The area under the ROC curve (AUC) was 0.843 (95% CI: 0.779-0.908) in the training cohort and 0.838 (95% CI: 0.748-0.927) in the validation cohort. the P-value of the Hosmer-Lemeshow test was 0.0613 in the training cohort and 0.8628 in the validation cohort. the bias of the training cohort corrected C-index was 0.8444 and the bias-corrected C-index for the validation cohort was 0.8375. demonstrating that the prediction model has good discriminative power and good calibration.

CONCLUSIONS

The column line graphs created showed excellent discrimination and calibration to predict lymph node status in patients with ≤ 2 cm invasive lung adenocarcinoma. In addition, the predictive model has predictive potential before the end of surgery and can inform clinical decision making.

Clinical Outcome of Stereotactic Body Radiotherapy in Patients with Early-Stage Lung Cancer with Ground-Glass Opacity Predominant Lesions: A Single Institution Experience

PURPOSE

The detection rate of early-stage lung cancer with ground-glass opacity (GGO) has increased, and stereotactic body radiotherapy (SBRT) has been suggested as an alternative to surgery in inoperable patients. However, reports on treatment results are limited. Therefore, we performed a retrospective study to investigate the clinical outcome after SBRT in patients with early-stage lung cancer with GGO-predominant tumor lesions at a single institution.

MATERIALS AND METHODS

This study included 89 patients with 99 lesions who were treated with SBRT for lung cancer with GGO-predominant lesions that had a consolidation-to-tumor ratio of ≤0.5 at Asan Medical Center between July 2016 and July 2021. A median total dose of 56.0 Gy (range, 48.0-60.0) was delivered using 10.0-15.0 Gy per fraction.

RESULTS

The overall follow-up period for the study was median 33.0 months (range, 9.9 to 65.9 months). There was 100% local control with no recurrences in any of the 99 treated lesions. Three patients had regional recurrences outside of the radiation field, and three had distant metastasis. The 1-year, 3-year, and 5-year overall survival rates were 100.0%, 91.6%, and 82.8%, respectively. Univariate analysis revealed that advanced age and a low level of diffusing capacity of the lungs for carbon monoxide were significantly associated with overall survival. There were no patients with grade ≥3 toxicity.

CONCLUSION

SBRT is a safe and effective treatment for patients with GGO-predominant lung cancer lesions and is likely to be considered as an alternative to surgery.

Deep learning-powered 3D segmentation derives factors associated with lymphovascular invasion and prognosis in clinical T1 stage non-small cell lung cancer

Background

Lymphovascular invasion (LVI) is an invasive biologic behavior that affects the treatment and prognosis of patients with early-stage lung cancer. This study aimed to identify LVI diagnostic and prognostic biomarkers using deep learning-powered 3D segmentation with artificial intelligence (AI) technology.

Methods

Between January 2016 and October 2021, we enrolled patients with clinical T1 stage non-small cell lung cancer (NSCLC). We used commercially available AI software (Dr. Wise system, Deep-wise Corporation, China) to extract quantitative AI features of pulmonary nodules automatically. Dimensionality reduction was achieved through least absolute shrinkage and selection operator regression; subsequently, the AI score was calculated.Then, the univariate and multivariate analysis was further performed on the AI score and patient baseline parameters.

Results

Among 175 enrolled patients, 22 tested positive for LVI at pathology review. Based on the multivariate logistic regression results, we incorporated the AI score, carcinoembryonic antigen, spiculation, and pleural indentation into the nomogram for predicting LVI. The nomogram showed good discrimination (C-index = 0.915 [95% confidence interval: 0.89-0.94]); moreover, calibration of the nomogram revealed good predictive ability (Brier score = 0.072). Kaplan-Meier analysis revealed that relapse-free survival and overall survival were significantly higher among patients with a low-risk AI score and without LVI than those among patients with a high-risk AI score (p = 0.008 and p = 0.002, respectively) and with LVI (p = 0.013 and p = 0.008, respectively).

Conclusions

Our findings indicate that a high-risk AI score is a diagnostic biomarker for LVI in patients with clinical T1 stage NSCLC; accordingly, it can serve as a prognostic biomarker for these patients.

Lymph Node Metastases in Surgically Resected Solitary Ground-Glass Opacities: A Two-Center Retrospective Cohort Study and Pooled Literature Analysis

BACKGROUND

An increasing body of evidence supports the noninferiority of sublobar resection compared with lobectomy in terms of survival for patients with early-stage lung cancer with ground-glass opacities (GGOs). However, few studies have focused on the incidence of lymph node (LN) metastases in these patients. We aimed to analyze N1 and N2 lymph node involvement in patients with non-small cell lung cancer (NSCLC) with GGO components stratified with different consolidation tumor ratio (CTR).

PATIENTS AND METHODS

We performed two-center studies by retrospectively reviewing a total of 864 patients with NSCLC with semisolid or pure GGO manifestation (diameter ≤ 3 cm). Clinicopathologic features and outcomes were analyzed. We also reviewed 35 studies to characterize the patient with NSCLC population with the GGO manifestation.

RESULTS

In both cohorts, there was no LN involvement for pure GGO NSCLC, while solid predominant GGO exhibited a relatively high LN involvement rate. On the basis of a pooled literature analysis, the incidence of pathologic mediastinal LN was 0% and 3.8% for pure and semisolid GGOs, respectively. GGO NSCLCs with CTR ≤ 0.5 also had rare LN involvement (0.1%).

CONCLUSIONS

From two cohorts and pooled literature analysis, LN involvement was not observed in patients with pure GGO, and very few patients with semisolid GGO NSCLC with CTR ≤ 0.5 had LN involvement, revealing that it may be unnecessary to perform lymphadenectomy for pure GGOs, while mediastinal lymph node sampling (MLNS) is enough for semisolid GGOs with CTR ≤ 0.5. For the patients with GGO CTR > 0.5, mediastinal lymphadenectomy (MLD) or MLNS should be considered.

Tumour location predicts occult N1 nodal metastasis in clinical stage I non-small-cell lung cancer

OBJECTIVES

Pathological lymph node metastases are often observed in patients with clinical N0 lung cancer. Identifying preoperative predictors of occult hilar nodal metastasis (OHNM) is important in determining the surgical procedure in patients with clinical stage I non-small-cell lung cancer. This study aimed to determine the frequency and predictors of OHNM by tumour location in these patients.

METHODS

Between April 2007 and May 2019, data of patients who underwent lobectomy or segmentectomy for clinical stage I pure-solid non-small-cell lung cancer were retrospectively reviewed. The ratio of the distance from the pulmonary hilum to the proximal side of the tumour to the distance from the pulmonary hilum to the visceral pleural surface through the centre of the tumour, named 'distance ratio (DR)', was calculated. The relationship of the DR with clinicopathological findings and prognosis was discussed.

RESULTS

A total of 357 patients were enrolled. OHNM frequency was 14.6%. Patients were divided into 2 groups based on whether the DR was ≤0.67 (central type) or >0.67 (peripheral type). The frequency of OHNM was significantly higher in the DR ≤0.67 group (21.5% vs 7.4%; P < 0.001). Multivariable analysis revealed that DR was the only independent preoperative predictor of OHNM (odds ratio, 3.63; 95% confidence interval, 1.83-7.18; P < 0.001).

CONCLUSIONS

The frequency of OHNM was significantly lower in peripheral-type lung cancer; therefore, tumour location was the most important preoperative predictor of OHNM.

The comparison of Lobe-Specific or Systematic Mediastinal Lymph Node Dissection for Early-Stage Lung Adenocarcinoma With Consolidation Tumor Ratio Over 0.5

INTRODUCTION

Surgery is the most effective treatment for early-stage lung cancer. This study will propose a personalized plan for mediastinal lymph node dissection in early-stage lung adenocarcinoma to reduce the risk of surgery and improve the quality of life.

METHODS

This study retrospectively analyzed the patients underwent lobectomy and lymph node dissection in the Department of Thoracic Surgery, Zhongshan Hospital, Fudan University. Clinical stage I lung adenocarcinoma patients with solid component ratio (CTR) between 0.5 and 1 were included. Patients were divided into systematic (S-MLND) and lobe-specific (L-MLND) mediastinal lymph node dissection groups. The days of hospitalization, the presence or absence of complications, the recurrence-free survival rate, and the overall survival rate were calculated to evaluate the postoperative quality and operation risk of the patients.

RESULTS

210 patients (138 L-MLND and 72 S-MLND) were included. 2 lymph node metastases appeared in the S-MLND group while none in the L-MLND group (P = .049). No differences were shown in age, tumor site, size, solid component, degree of tumor invasion, and stage. The proportion of patients with severe postoperative cough and the length of hospital stay in the L-MLND group decreased. The 5-year OS of the entire cohort was 98.1%, 98.6% in L-MLND, compared with 97.2% in S-MLND; RFS was 94.8%, 95.7% in L-MLND, compared with 93.0% in S-MLND.

CONCLUSION

For cIA lung adenocarcinoma, according to the Thin-slice CT within 1 month before the operation, if the main lesion was less than 3 cm and CTR over 0.5, L-MLND is as effective as S-MLND.

Mathematical models for intraoperative prediction of metastasis to regional lymph nodes in patients with clinical stage I non-small cell lung cancer

It remains challenging to determine the regions of metastasis to lymph nodes during operation for clinical stage I non-small cell lung cancer (NSCLC). This study aimed to establish intraoperative mathematical models with nomograms for predicting the hilar-intrapulmonary node metastasis (HNM) and the mediastinal node metastasis (MNM) in patients with clinical stage I NSCLC. The clinicopathological variables of 585 patients in a derivation cohort who underwent thoracoscopic lobectomy with complete lymph node dissection were retrospectively analyzed for their association with the HNM or the MNM. After analyzing the variables, we developed multivariable logistic models with nomograms to estimate the risk of lymph node metastasis in different regions. The predictive efficacy was then validated in a validation cohort of 418 patients. It was confirmed that carcinoembryonic antigen (>5.75 ng/mL), CYFRA211 (>2.85 ng/mL), the maximum diameter of tumor (>2.75 cm), tumor differentiation (grade III), bronchial mucosa and cartilage invasion, and vascular invasion were predictors of HNM, and carcinoembryonic antigen (>8.25 ng/mL), CYFRA211 (>2.95 ng/mL), the maximum diameter of tumor (>2.75 cm), tumor differentiation (grade III), bronchial mucosa and cartilage invasion, vascular invasion, and visceral pleural invasion were predictors of MNM. The validation of the prediction models based on the above results demonstrated good discriminatory power. Our predictive models are helpful in the decision-making process of specific therapeutic strategies for the regional lymph node metastasis in patients with clinical stage I NSCLC.

Construction and Evaluation of a Preoperative Prediction Model for Lymph Node Metastasis of cIA Lung Adenocarcinoma Using Random Forest

Background

Lymph node metastasis (LNM) is the main route of metastasis in lung adenocarcinoma (LA), and preoperative prediction of LNM in early LA is key for accurate medical treatment. We aimed to establish a preoperative prediction model of LNM of early LA through clinical data mining to reduce unnecessary lymph node dissection, reduce surgical injury, and shorten the operation time.

Methods

We retrospectively collected imaging data and clinical features of 1121 patients with early LA who underwent video-assisted thoracic surgery at the First Hospital of China Medical University from 2004 to 2021. Logistic regression analysis was used to select variables and establish the preoperative diagnosis model using random forest classifier (RFC). The prediction results from the test set were used to evaluate the prediction performance of the model.

Results

Combining the results of logistic analysis and practical clinical application experience, nine clinical features were included. In the random forest classifier model, when the number of nodes was three and the n-tree value is 500, we obtained the best prediction model (accuracy = 0.9769), with a positive prediction rate of 90% and a negative prediction rate of 98.69%.

Conclusion

We established a preoperative prediction model for LNM of early LA using a machine learning random forest method combined with clinical and imaging features. More excellent predictors may be obtained by refining imaging features.

Reclassifying the International Association for the Study of Lung Cancer Residual Tumor Classification According to the Extent of Nodal Dissection for NSCLC: One Size Does Not Fit All

INTRODUCTION

The extent of nodal assessment may require risk-based adjustments in NSCLC. We reclassified the International Association for the Study of Lung Cancer Residual tumor classification according to the extent of nodal dissection and evaluated its long-term prognosis by tumor stage and histologic subtype.

METHODS

We reclassified 5117 patients who underwent resection for clinical stages I to III NSCLC and had complete or uncertain resection by International Association for the Study of Lung Cancer classification into the following 3 groups according to compliance with three components (N1, N2, and subcarinal node) of systematic nodal dissection criteria: fully compliant group (FCG), partially compliant group (PCG), and noncompliant group (NCG). Recurrence-free survival (RFS) and overall survival (OS) were compared.

RESULTS

Of the 5117 patients, 2806 (55%), 1959 (38%), and 359 (7%) were FCG, PCG, and NCG, respectively. PCG and NCG were more likely to be of lower clinical stage and adenocarcinoma with lepidic component than FCG. The 5-year RFS and OS were significantly better in NCG than in FCG or PCG (RFS, 86% versus 70% or 74%, p < 0.001; OS, 90% versus 80% or 83%, p < 0.001). In particular, NCG had better RFS and OS than FCG or PCG in clinical stage I and in lepidic-type adenocarcinoma.

CONCLUSIONS

In early stage NSCLC with low-risk histologic subtype, a less rigorous nodal assessment was not associated with a worse prognosis. Although surgeons should continue to aim for complete resection and thorough nodal assessment, a uniform approach to the extent and invasiveness of nodal assessment may need to be reconsidered.

Results in mediastinal lymph node staging of surgical lung cancer: Data from the prospective cohort of the Spanish Video-Assisted Thoracic Surgery Group

OBJECTIVES

The objective of this study was to assess the diagnostic performance of combined computerised tomography (CT) and positron emission tomography (PET) in mediastinal staging of surgical lung cancer based on data obtained from the prospective cohort of the Spanish Group for Video-Assisted Thoracic Surgery (GEVATS).

METHODS

A total of 2782 patients underwent surgery for primary lung carcinoma. We analysed diagnostic success in mediastinal lymph node staging (cN2) using CT and PET. Bivariate and multivariate analyses were performed of the factors involved in this success. The risk of unexpected pN2 disease was analysed for cases in which an invasive testing is recommended: cN1, the tumour centrally located or the tumour diameter >3 cm.

RESULTS

The overall success of CT together with PET was 82.9% with a positive predictive value of 0.21 and negative predictive value of 0.93. If the tumour was larger than 3 cm and for each unit increase in mediastinal SUVmax, the probability of success was lower with OR 0.59 (0.44-0.79) and 0.71 (0.66-0.75), respectively. In the video-assisted thoracic surgery (VATS) approach, the probability of success was higher with OR 2.04 (1.52-2.73). The risk of unexpected pN2 increased with the risk factors cN1, the tumour centrally located or the tumour diameter >3 cm: from 4.5% (0 factors) to 18.8% (3 factors) but did not differ significantly as a function of whether invasive testing was performed.

CONCLUSIONS

CT and PET together have a high negative predictive value. The overall success of the staging is lower in the case of tumours >3 cm and high mediastinal SUVmax, and it is higher when VATS is performed. The risk of unexpected pN2 is higher if the disease is cN1, the tumour centrally located or the tumour diameter >3 cm but does not vary significantly as a function of whether patients have undergone invasive testing.

Differences in the prognostic implication of ground-glass opacity on CT according to pathological nodal status in lung cancers treated with lobectomy or pneumonectomy

OBJECTIVES

To clarify the prognostic significance of a ground-glass opacity (GGO) component according to T category and pathological nodal status in patients with resectable non-small cell lung cancer (NSCLC).

METHODS

Patients who underwent lobectomy or pneumonectomy for NSCLC between July 2010 and December 2017 were retrospectively included. Patients were divided into GGO and solid groups based on the presence of a GGO component on CT. The effects on survival of interactions between GGO and (a) pathological nodal status (pN) and (b) cT category were evaluated using Cox regression.

RESULTS

Out of 1545 patients, 548 were classified into the GGO group (pN0: 457, pN1/2: 91) and 997 into the solid group (pN0: 660, pN1/2: 337). There were interactions between the presence of GGO and pathological nodal status on 5-year disease-free survival (DFS; p = .006) and 5-year overall survival (OS; p = .02). In multivariate analysis, better survival of patients in the GGO group than in the solid group was observed only in pN0 category (adjusted hazard ratio [HR], 0.63 for 5-year DFS; p = .002 and 0.47 for 5-year OS; p = .002), but not in pN1/2 category. Moreover, in those with pN0 category, the favorable prognostic value of GGO was limited to those with cT1 category for 5-year DFS (adjusted HR, 0.48; p < .001) and those with cT1/2 category for 5-year OS (adjusted HR, 0.37; p = .002).

CONCLUSIONS

GGO was a favorable predictor of survival only in patients with pN0 category, showing an advantage in DFS for those with cT1 category and OS for those with cT1/2 category.

KEY POINTS

• The presence of ground-glass opacity was associated with a favorable prognosis, only in pathological node-negative patients (5-year disease-free survival, p = .002; 5-year overall survival, p = .002). • Within pathological node-negative patients, the effect of ground-glass opacity on 5-year disease-free survival was valid in patients with cT1 category (adjusted hazard ratio, 0.48; 95% confidence interval, 0.32-0.72; p < .001), but not in patients with cT2 or above category. • Within pathological node-negative patients, the effect of ground-glass opacity on 5-year overall survival was valid in patients with cT1/2 category (adjusted hazard ratio, 0.37; 95% confidence interval, 0.20-0.68; p = .002), but not in patients with cT3/4 category.

Consolidation Tumor Ratio Combined With Pathological Features Could Predict Status of Lymph Nodes of Early-Stage Lung Adenocarcinoma

INTRODUCTION

Stage IA lung adenocarcinoma manifested as part-solid nodules (PSNs), has attracted immense attention owing to its unique characteristics and the definition of its invasiveness remains unclear. We sought to develop a nomogram for predicting the status of lymph nodes of this kind of nodules.

METHODS

A total of 2,504 patients between September 2018 to October 2020 with part-solid nodules in our center were reviewed. Their histopathological features were extracted from paraffin sections, whereas frozen sections were reviewed to confirm the consistency of frozen sections and paraffin sections. Univariate and multivariate logistic regression analyses and Akaike information criterion (AIC) variable selection were performed to assess the risk factors of lymph node metastasis and construct the nomogram. The nomogram was subjected to bootstrap internal validation and external validation. The concordance index (C-index) was applied to evaluate the predictive accuracy and discriminative ability.

RESULTS

We enrolled 215 and 161 eligible patients in the training cohort and validation cohort, respectively. The sensitivity between frozen and paraffin sections on the presence of micropapillary/solid subtype was 78.4%. Multivariable analysis demonstrated that MVI, the presence of micropapillary/solid subtype, and CTR >0.61 were independently associated with lymph node metastasis (p < 0.01). Five risk factors were integrated into the nomogram. The nomogram demonstrated good accuracy in estimating the risk of lymph node metastasis, with a C-index of 0.945 (95% CI: 0.916-0.974) in the training cohort and a C-index of 0.975 (95% CI: 0.954-0.995) in the validation cohort. The model's calibration was excellent in both cohorts.

CONCLUSION

The nomogram established showed excellent discrimination and calibration and could predict the status of lymph nodes for patients with ≤3 cm PSNs. Also, this prediction model has the prediction potential before the end of surgery.

Prediction of lymph node metastasis of clinical stage IA non-small cell lung cancer based on the tumor volume doubling time

PURPOSE

To investigate whether the volume doubling time is a preoperative predictor of lymph node metastasis of clinical stage IA non-small cell lung cancer (NSCLC).

METHODS

The subjects of this retrospective study were 204 patients who underwent lobectomy and mediastinal lymph node dissection for clinical stage IA NSCLC. We analyzed the relationship between lymph node metastasis and clinicopathological factors, including the volume doubling time.

RESULTS

Lymph node metastasis developed in 24 (11.8%) patients. Multivariable analysis identified consolidation diameter (Odds ratio = 1.407; 95% confidence interval, 1.007-1.966, p = 0.046) and the solid-part tumor volume doubling time (Odds ratio = 0.982; 95% confidence interval, 0.973-0.991, p < 0.001) as independent predictors of lymph node metastasis. The combination of a larger consolidation diameter (> 1.9 cm) and a shorter solid-part tumor volume doubling time (< 132 days) had sensitivity, specificity, and accuracy of 79.2%, 94.4%, and 92.6%, respectively.

CONCLUSIONS

The consolidation diameter and solid-part tumor volume doubling time can be useful preoperative predictors of lymph node metastasis of clinical stage IA NSCLC.

Deep Learning for Prediction of N2 Metastasis and Survival for Clinical Stage I Non-Small Cell Lung Cancer

Background Preoperative mediastinal staging is crucial for the optimal management of clinical stage I non-small cell lung cancer (NSCLC). Purpose To develop a deep learning signature for N2 metastasis prediction and prognosis stratification in clinical stage I NSCLC. Materials and Methods In this retrospective study conducted from May 2020 to October 2020 in a population with clinical stage I NSCLC, an internal cohort was adopted to establish a deep learning signature. Subsequently, the predictive efficacy and biologic basis of the proposed signature were investigated in an external cohort. A multicenter diagnostic trial (registration number: ChiCTR2000041310) was also performed to evaluate its clinical utility. Finally, on the basis of the N2 risk scores, the instructive significance of the signature in prognostic stratification was explored. The diagnostic efficiency was quantified with the area under the receiver operating characteristic curve (AUC), and the survival outcomes were assessed using the Cox proportional hazards model. Results A total of 3096 patients (mean age ± standard deviation, 60 years ± 9; 1703 men) were included in the study. The proposed signature achieved AUCs of 0.82, 0.81, and 0.81 in an internal test set (n = 266), external test cohort (n = 133), and prospective test cohort (n = 300), respectively. In addition, higher deep learning scores were associated with a lower frequency of EGFR mutation (P = .04), higher rate of ALK fusion (P = .02), and more activation of pathways of tumor proliferation (P < .001). Furthermore, in the internal test set and external cohort, higher deep learning scores were predictive of poorer overall survival (adjusted hazard ratio, 2.9; 95% CI: 1.2, 6.9; P = .02) and recurrence-free survival (adjusted hazard ratio, 3.2; 95% CI: 1.4, 7.4; P = .007). Conclusion The deep learning signature could accurately predict N2 disease and stratify prognosis in clinical stage I non-small cell lung cancer. © RSNA, 2021 Online supplemental material is available for this article. See also the editorial by Park and Lee in this issue.

What Should Thoracic Surgeons Consider during Surgery for Ground-Glass Nodules?: Lymph Node Dissection

Thoracic surgeons need to be aware of several important points regarding intraoperative lymph node dissection during surgery for non-small cell lung cancer with ground-glass opacities. The first point relates to the need for lymph node dissection during sublobar resection. Since even patients undergoing sublobar resection may benefit from lymph node dissection, it should be selectively performed according to adequate indications, which require further study. Second, there seems to be no difference in postoperative morbidity between systematic sampling and systematic dissection, but the survival benefit from systematic dissection remains unclear. The results of randomized controlled trials on this topic are conflicting, and their evidence is jeopardized by a high risk of bias in terms of the study design. Therefore, further randomized controlled trials with a sound design should investigate this issue. Third, more favorable survival outcomes tend to be positively associated with the number of examined lymph nodes. Minimum requirements for the number of examined lymph nodes in non-small cell lung cancer should be defined in the future. Finally, lobe-specific lymph node dissection does not have a negative prognostic impact. It should not be routinely performed, but it can be recommended in selected patients with smaller, less invasive tumors. Results from an ongoing randomized controlled trial on this topic should be awaited.

Lymph node metastasis and predictive factors in clinical stage IA squamous cell carcinoma of the lung based on radiological findings

OBJECTIVES

We aimed to clarify the incidence of lymph node (LN) metastasis and its predictive factors in clinical stage IA squamous cell carcinoma (SqCC) based on radiological classification to provide surgical indications for segmentectomy.

METHODS

We retrospectively reviewed 192 patients with clinical stage IA SqCC who underwent complete resection with lobectomy and LN dissection at our institution between 2003 and 2019. To evaluate the incidence of LN metastasis from the perspective of indications for segmentectomy, we classified them into outer and inner groups based on the location of the tumor in the radiological findings.

RESULTS

Regarding tumor location, 123 patients had tumors in the outer location and 69 patients had tumors in the inner location. The incidence of LN metastasis was 6% in clinical stage IA SqCC, which included 6% in the outer location and 7% in the inner location (p = 0.669). In the outer location, all LN metastases were in N1 (6%); whereas in the inner location, the incidence of N1 and N2 metastasis were 6% and 1%, respectively. Only tumors sized > 2.0 cm were found to be significantly associated with LN metastasis in clinical stage IA SqCC.

CONCLUSIONS

We demonstrated that the incidence of LN metastasis in clinical stage IA SqCC was comparable to that of the previously reported clinical stage IA NSCLC. The incidence of LN metastasis in the outer location was similar to that in the inner location. Tumor size was only a significant factor affecting LN metastasis in clinical stage IA SqCC.

Integrative nomogram of intratumoral, peritumoral, and lymph node radiomic features for prediction of lymph node metastasis in cT1N0M0 lung adenocarcinomas

Radiomics studies to predict lymph node (LN) metastasis has only focused on either primary tumor or LN alone. However, combining radiomics features from multiple sources may reflect multiple characteristic of the lesion thereby increasing the discriminative performance of the radiomic model. Therefore, the present study intends to evaluate the efficiency of integrative nomogram, created by combining clinical parameters and radiomics features extracted from gross tumor volume (GTV), peritumoral volume (PTV) and LN, for the preoperative prediction of LN metastasis in clinical cT1N0M0 adenocarcinoma. A primary cohort of 163 patients (training cohort, 113; and internal validation cohort, 50) and an external validation cohort of 53 patients with clinical stage cT1N0M0 were retrospectively included. Features were extracted from three regions of interests (ROIs): GTV; PTV (5.0 mm around the tumor) and LN on pre-operative contrast enhanced computed tomography (CT). LASSO logistic regression method was used to build radiomic signatures. Multivariable regression analysis was used to build a nomogram. The performance of the nomogram was assessed with respect to its calibration, discrimination, and clinical usefulness. The discriminative performance of nomogram was validated both internally and externally. The radiomic signatures using the features of GTV, PTV and LN showed a good ability in predicting LN metastasis with an area under the curve (AUC) of 0.74 (95% CI 0.60–0.88), 0.72 (95% CI 0.57–0.87) and 0.64 (95% CI 0.48–0.80) respectively in external validation cohort. The integration of different signature together further increases the discriminatory ability: GTV + PTV (GPTV): AUC 0.75 (95% CI 0.61–0.89) and GPTV + LN: AUC 0.76 (95% CI 0.61–0.91) in external validation cohort. An integrative nomogram of clinical parameters and radiomic features demonstrated further increase in discriminatory ability with AUC of 0.79 (95% CI 0.66–0.93) in external validation cohort. The nomogram showed good calibration. Decision curve analysis demonstrated that the radiomic nomogram was clinically useful. The integration of information from clinical parameters along with CT radiomics information from GTV, PTV and LN was feasible and increases the predictive performance of the nomogram in predicting LN status in cT1N0M0 adenocarcinoma patients suggesting merit of information integration from multiple sources in building prediction model.

The prognostic utility of the histologic subtype of stage I lung adenocarcinoma may be diminished when using only the invasive component to determine tumor size for tumor node metastasis (TNM) staging

Background

Histologic subtypes were considered prognostic factors in early-stage lung adenocarcinoma in the 7^th edition of the tumor node metastasis (TNM) staging system (TNM-7). However, the T-staging system has changed and now measures only the size of the invasive component to determine tumor size. The aim of this study was to determine whether the histologic subtype is still a prognostic factor in the 8^th edition of the TNM staging system (TNM-8).

Methods

From 2010 to 2017, 788 patients who underwent curative surgery for stage I lung adenocarcinoma according to TNM-8 were analyzed retrospectively. Survival rates were compared among predominant patterns of adenocarcinoma. Prognostic factors were analyzed according to risk factors for recurrence in stage I lung adenocarcinoma.

Results

The 5-year recurrence-free survival rates among predominant histologic subtypes were statistically different, especially between the lepidic/acinar/papillary group and the micropapillary/solid group. Total tumor size was not significantly different between the two groups, but invasive component size was different (1.5 vs. 2.3 cm, P<0.001). In the multivariate analysis that adopted total tumor size as a variable, visceral pleural invasion (VPI), lymphovascular invasion (LVI), and micropapillary-predominant adenocarcinoma were significant predictors for recurrence. Conversely, adenocarcinoma subtypes were not significant risk factors for recurrence in the multivariate analysis that adopted invasive component size as a variable.

Conclusions

The importance of adenocarcinoma subtype for prognosis may be reduced when only the invasive component of a tumor is used to determine tumor size, as described in the TNM-8 staging system.

Extent of mediastinal nodal dissection in stage I non-small cell lung cancer with a radiological pure-solid appearance

BACKGROUND

Radiological pure-solid lung cancer denotes a high invasive nature compared to one that is part-solid. Mediastinal lymph nodal dissection (mLND) is a standard surgical procedure for nodal management in lung cancer surgery, however, the prognostic impact of the extent of mLND in pure-solid lung cancer is still unknown.

METHODS

We reviewed 459 patients with c-stage I radiological pure-solid lung cancer that underwent pulmonary lobectomy with mLND. Pure-solid was defined as a tumor showing only a consolidation without any ground glass opacity. The extent of mLND was classified into lobe-specific (L-mLND) and systematic (S-mLND). Prognostic significance of mLND was assessed by a multivariable analysis using propensity-score matching. Survivals were calculated by Kaplan-Meier methods using log-rank test.

RESULTS

Pathological nodal metastasis was found in 127 (27.6%) patients (hilar: 52 (11.3%), mediastinal: 75 (16.3%)). L-mLND was performed in 278 (61%) patients. A multivariable analysis did not show the survival difference for the extent of mLND (p = 0.266). The 5-year overall survival (OS) was not significantly different between S-mLND and L-mLND (74.3% vs. 72.7%, p = 0.712), which was similar even in 114 propensity-score matched pairs (78.8% vs. 79.9%, p = 0.665). While S-mLND showed a trend for survival benefit compared to L-mLND provided that the tumor showed higher standardized uptake value (SUVmax) (5y-OS: 70.0% vs. 59.2%, p = 0.093).

CONCLUSIONS

Prognostic impact of L-mLND was similar to S-mLND in c-stage I radiological pure-solid lung cancers in the propensity-score matched comparison. Among them, higher SUVmax value might be a promising indicator to decide the extent of mediastinal lymphadenectomy.

Choice of Treatment for Patients With Non-small-cell Lung Cancer >5 cm Between Surgery Alone and Surgery Plus Adjuvant Radiotherapy

Background: According to the lung cancer staging project, T2b (>5–7 cm) and T3 (>7 cm) non-small cell lung cancers (NSCLC) should be reclassified into T3 and T4 groups. The objective of this study was to evaluate the effect of surgery alone or surgery plus adjuvant radiation (SART) on survival of node-negative patients with NSCLC >5 cm.

Methods: We identified 4557 N0 patients with NSCLC >5 cm in the Surveillance, Epidemiology, and End Results database from 2004 to 2014. Overall survival (OS) and cancer–specific survival (CSS) were compared among patients who underwent surgery alone and SART. The proportional hazards model was applied to evaluate multiple prognostic factors.

Results: 1,042 and 525 patients who underwent surgery alone and SART, respectively were enrolled after propensity-score matching. OS and CSS favored surgery alone rather than SART. Multivariate analysis showed that the number of lymph nodes examined more than six was associated with better OS and CSS for NSCLC >5 cm, especially in patients treated with surgery alone. Lobectomy should be recommended as the primary option for NSCLC >5 to 7 cm, whereas its superiority was not significant over sublobectomy for NSCLC >7 cm.

Conclusion: Surgery alone should be recommended as the first choice for patients with NSCLC >5 cm. The number of examined lymph nodes should be more than six in patients with NSCLC >5 cm, especially for those who undergo surgery alone. For patients with NSCLC >7 cm who could not tolerate lobectomy, sublobectomy might be an alternative surgical procedure.

Is the size of the lepidic component negligible when measuring the size of the tumor to determine the stage of lung adenocarcinoma?

Background

After applying the 8th edition of the TNM staging system, the invasive component size, not total tumor size, began to be used as a T descriptor for the stage. The aim of this study was to evaluate whether the size of the lepidic component can be negligible when using only the invasive component size as the T descriptor.

Methods

From 2010 to 2018, 613 consecutive patients were diagnosed as having stage IA lung adenocarcinoma and underwent anatomical lobectomy at a tertiary hospital. Pathologic specimens and medical records were reviewed retrospectively. Statistical analyses were conducted to find out whether the recurrence of stage IA lung adenocarcinoma was more affected by total tumor size (including lepidic component size) or invasive component size.

Results

The 5-year recurrence-free survival (RFS) rates of stage 0, stage IA1, stage IA2, and stage IA3 were 100%, 98.4%, 89.1%, and 81.7%, respectively. In multivariate analysis, total tumor size was not a risk factor for recurrence, whereas invasive component size was a significant risk factor for recurrence (Hazard ratio =1.658, P=0.043). In subgroup analysis, 5-year RFS rates of large lung adenocarcinoma (total tumor size >3 cm) and others (total tumor size ≤3 cm) in the same invasive component size group (stage IA2 and stage IA3) were not statistically different.

Conclusions

Invasive component size was a risk factor for recurrence of stage IA lung adenocarcinoma, while total tumor size was not a risk factor. Therefore, it seems to be appropriate to ignore the size of the lepidic component.

Surgical Consideration Based on Lymph Nodes Spread Patterns in Patients with Peripheral Right Middle Non-small Cell Lung Cancer 3 cm or Less

BACKGROUND

The optimal extent of lung resection and lymph nodes dissection for peripheral early-stage right middle non-small cell lung cancer (NSCLC) still remains controversial. In this study, we analyzed the patterns of lymph nodes metastasis (LNM) of patients with peripheral right middle NSCLC ≤ 3 cm, aiming to provide evidences for surgical choice for early-stage peripheral right middle lobe NSCLC.

METHODS

We retrospectively investigated the clinical and pathological data of patients diagnosed with peripheral right middle lobe NSCLC ≤ 3 cm between January 2015 and December 2019. The LNM patterns were analyzed by tumor size.

RESULTS

A total of 60 patients were included for analysis. The tumor size was preoperatively divided as follows: ≤ 1 cm (13 patients); > 1 cm but ≤ 2 cm (36 patients); > 2 cm but ≤ 3 cm (11 patients). Fifty-four patients were categorized as N0 group, 1 patient as N1 group, and 5 patients as N2 group. In the upper zone, 3 patients were found to have LNM. In the subcarinal zone, another 3 patients had LNM. But the lymph nodes of all these patients were negative in the lower zone. In station 10, 1 patient (1.67%) was found to have LNM, while in station 11-13, 2 patients (3.33%) were found to have LNM.

CONCLUSION

For the right middle lobe peripheral NSCLC ≤ 1 cm, sublobar resection with lymph node sampling may be a feasible treatment. For cancers > 1 cm but ≤ 2 cm, lobectomy with lobe-specific lymph node dissection (especially station 2R and 4R) may be a preferred choice. For tumors > 2 cm but ≤ 3 cm, lobectomy with systematic lymph node dissection may still be the standard of care.

Predicting benign, preinvasive, and invasive lung nodules on computed tomography scans using machine learning

OBJECTIVE

The study objective was to investigate if machine learning algorithms can predict whether a lung nodule is benign, adenocarcinoma, or its preinvasive subtype from computed tomography images alone.

METHODS

A dataset of chest computed tomography scans containing lung nodules was collected with their pathologic diagnosis from several sources. The dataset was split randomly into training (70%), internal validation (15%), and independent test sets (15%) at the patient level. Two machine learning algorithms were developed, trained, and validated. The first algorithm used the support vector machine model, and the second used deep learning technology: a convolutional neural network. Receiver operating characteristic analysis was used to evaluate the performance of the classification on the test dataset.

RESULTS

The support vector machine/convolutional neural network-based models classified nodules into 6 categories resulting in an area under the curve of 0.59/0.65 when differentiating atypical adenomatous hyperplasia versus adenocarcinoma in situ, 0.87/0.86 with minimally invasive adenocarcinoma versus invasive adenocarcinoma, 0.76/0.72 atypical adenomatous hyperplasia + adenocarcinoma in situ versus minimally invasive adenocarcinoma, 0.89/0.87 atypical adenomatous hyperplasia + adenocarcinoma in situ versus minimally invasive adenocarcinoma + invasive adenocarcinoma, and 0.93/0.92 atypical adenomatous hyperplasia + adenocarcinoma in situ + minimally invasive adenocarcinoma versus invasive adenocarcinoma. Classifying benign versus atypical adenomatous hyperplasia + adenocarcinoma in situ + minimally invasive adenocarcinoma versus invasive adenocarcinoma resulted in a micro-average area under the curve of 0.93/0.94 for the support vector machine/convolutional neural network models, respectively. The convolutional neural network-based methods had higher sensitivities than the support vector machine-based methods but lower specificities and accuracies.

CONCLUSIONS

The machine learning algorithms demonstrated reasonable performance in differentiating benign versus preinvasive versus invasive adenocarcinoma from computed tomography images alone. However, the prediction accuracy varies across its subtypes. This holds the potential for improved diagnostic capabilities with less-invasive means.

Risk Factors for Occult Lymph Node Metastasis in Peripheral Non-Small Cell Lung Cancer with Invasive Component Size 3 cm or Less

BACKGROUND

In the seventh edition TNM staging system for lung cancer, a high maximum standardized uptake value (SUVmax) on positron emission tomography was regarded as a risk factor for occult lymph node metastasis in clinical T1N0 non-small cell lung cancer (NSCLC). However, in the eighth edition TNM classification, tumors are classified according to the size of the invasive component only, and those with invasive component size ≤3 cm are diagnosed as stage T1. The aim of this study was to reassess the risk factors for occult lymph node metastasis under the eighth edition TNM classification for lung cancer.

METHODS

From 2010 to 2017, 553 patients with clinical N0 peripheral NSCLC with invasive component size ≤3 cm underwent anatomical lobectomy with systematic lymph node dissection. We analyzed these cases retrospectively to identify risk factors for postoperative nodal upstaging.

RESULTS

Among 553 study patients, 54 (9.8%) had nodal upstaging after surgery. In multivariate analysis adopting the eighth edition TNM classification for lung cancer, serum carcinoembryonic antigen (CEA) level (hazard ratio [HR] = 1.113, p = 0.002), invasive component size (HR = 2.398, p = 0.004), visceral pleural invasion (HR = 2.901, p = 0.005), and lymphatic invasion (HR = 9.336, p < 0.001) were significant risk factors for nodal upstaging, but SUVmax was not.

CONCLUSION

SUVmax is not a predictor of nodal upstaging in clinical N0 peripheral NSCLC with invasive component size ≤3 cm under the eighth edition TNM classification for lung cancer. Significant risk factors of occult lymph node metastasis are serum CEA level, tumor invasive component size, visceral pleural invasion, and lymphatic invasion.

The Effect of Resection Margin Distance and Invasive Component Size on Recurrence After Sublobar Resection in Patients With Small (≤2 Cm) Lung Adenocarcinoma

BACKGROUND

When performing sublobar resection for lung cancer, the margin distance should exceed the tumor size. However, instead of total tumor size, the 8th edition TNM staging system has adopted the size of invasive component for the T stage. The aim of this study was to determine whether the prognosis was satisfactory when the resection margin distance was greater than the invasive component size instead of the total tumor size.

METHODS

From 2008 to 2017, 193 consecutive patients were diagnosed with lung adenocarcinoma (invasive component size ≤2 cm) and underwent sublobar resection. We analyzed risk factors for recurrence using clinicopathological factors including margin/invasive component ratio (resection margin distance/invasive component size).

RESULTS

Mean tumor size was 1.4 (±0.5) cm and the mean invasive component size was 0.8 cm (±0.5). In the multivariate analysis, neither resection margin distance (cm) nor margin/tumor ratio (resection margin distance/tumor size) was significant risk factors for recurrence. On the other hand, the margin/invasive component ratio (hazard ratio =0.035, p = 0.043) and the SUVmax (hazard ratio =1.993, p = 0.033) were significant risk factors for recurrence.

CONCLUSIONS

When sublobar resection is performed for small (invasive component size ≤2 cm) adenocarcinomas of the lung, the resection margin distance should be larger than the invasive component size. Sublobar resection is not an appropriate treatment for lung adenocarcinoma with high SUVmax.

Elevated preoperative CEA is associated with subclinical nodal involvement and worse survival in stage I non-small cell lung cancer: a systematic review and meta-analysis

BACKGROUND

The standard for clinical staging of lung cancer is the use of CT and PET scans, however, these may underestimate the burden of the disease. The use of serum tumor markers might aid in the detection of subclinical advanced disease. The aim of this study is to review the predictive value of tumor markers in patients with clinical stage I NSCLC.

METHODS

A comprehensive search was performed using the Medline, EMBASE, Scopus data bases. Abstracts included based on the following inclusion criteria: 1) adult ≥18 years old, 2) clinical stage I NSCLC, 3) Tumor markers (CEA, SCC, CYFRA 21-1), 4) further imaging or procedure, 5) > 5 patients, 6) articles in English language. The primary outcome of interest was utility of tumour markers for predicting nodal involvement and oncologic outcomes in patients with clinical stage I NSCLC. Secondary outcomes included sub-type of lung cancer, procedure performed, and follow-up duration.

RESULTS

Two hundred seventy articles were screened, 86 studies received full-text assessment for eligibility. Of those, 12 studies were included. Total of 4666 patients were involved. All studies had used CEA, while less than 50% used CYFRA 21-1 or SCC. The most common tumor sub-type was adenocarcinoma, and the most frequently performed procedure was lobectomy. Meta-analysis revealed that higher CEA level is associated with higher rates of lymph node involvement and higher mortality.

CONCLUSION

There is significant correlation between the CEA level and both nodal involvement and survival. Higher serum CEA is associated with advanced stage, and poor prognosis. Measuring preoperative CEA in patient with early stage NSCLC might help to identify patients with more advanced disease which is not detected by CT scans, and potentially identify candidates for invasive mediastinal lymph node staging, helping to select the most effective therapy for patients with potentially subclinical nodal disease. Further prospective studies are needed to standardize the use of CEA as an adjunct for NSCLC staging.

Nodal recurrences after stereotactic body radiotherapy for early stage non-small-cell lung cancer

Lobectomy is considered the standard of care for early stage non-small-cell lung cancer. However, for those patients who remain unfit to undergo surgery due to advanced age, poor performance status, comorbidities, poor pulmonary reserve or a combination of these are now treated with stereotactic body radiation therapy (SBRT). Due to its noninvasive nature, lower cost, lower toxicity, reduced recovery time and equivalent efficacy, even medically operable patients are attracted to the option of SBRT despite the lack of level I evidence. Thus, studying the incidence and patterns of recurrence after SBRT help in understanding the magnitude of the problem, risk factors associated with the different patterns of recurrence, and aid in devising strategies to prevent them in future. Nodal recurrences are not uncommon after SBRT and can potentially lead to further seeding for distant metastases and ultimately poor survival. This review is aimed at reviewing the published data on the incidence of nodal recurrences after SBRT and compare it to surgery, identify potential risk factors for recurrence, salvage treatment options and prevention strategies.

[Progress in Survival Prognosis of Segmentectomy for Early-stage Non-small Cell Lung Cancer]

Surgery is currently the most appropriate treatment for early-stage non-small cell lung cancer (NSCLC). Increasing unilateral or bilateral multiple primary lung cancer being found, segmentectomy has attracted wide attention for its unique advantages in the treatment for such tumors. Ground glass opacity dominant early-stage NSCLC is associated with a good prognosis and can be cured by segmentectomy, however, the treatment of solid-dominant NSCLC remains controversial owing to the invasive nature. With the in-depth study on the lymph node metastasis pathway, radiological characteristics and molecular biology of NSCLC, a large part of solid nodules with certain characteristics can also be cured by segmentectomy. This paper reviews the research status and progress about the indication of segmentectomy.
.

Treatment options for pulmonary multifocal ground glass opacity type adenocarcinoma: Surgery combine thermal ablation?

Objectives

To retrospectively analyze the clinical results of the treatment of pulmonary multifocal adenocarcinoma presenting as ground glass opacity (GGO) by surgery and thermal ablation.

Methods

87 GGO-type pulmonary adenocarcinomas of 48 patients (14 males and 34 females; mean age: 59.7 years old ±9.9, range: 33–79 years old) had been treated from March 2015 to March 2019. Treatment means included 43 wedge resections, 7 segmentectomy, 17 lobectomies, and 20 thermal ablations. The indication selected for treatment means, safety, and local tumor progression rate were evaluated.

Results

No operation-related death occurred in all patients. 42 times of surgery were performed and 67 carcinomas were resected in 42 patients. 23 times of single-port Video-assisted thoracoscopic surgery (VATS), 8 times of two-port VATS and 11 times of three-port VATS were performed in total. There were 2 cases of air leak (exceeding 1 week), 1 case of chylothorax and 1 case of massive pleural effusion. Time duration of surgery was between 60 and 300mins (mean: 167mins). Intra-operative blood loss was between 5 and 300 ​mL (mean: 44 ​mL). Time of chest drainage was between 2 and 23d (mean 4.9d). Chest drainage volume was between 14 and 4633 ​mL (mean: 872 ​mL). Post-operation LOS (length of stay) was between 3 and 25d (mean: 6.2d). 15 times of thermal ablation were performed (1 case of air leak) and 20 carcinomas were ablated in 14 patients. The ablation time was between 30 and 120min (mean: 43min); post-operation LOS was between 1 and 10d (mean: 3.5d). During the mean follow-up period (16 months ​± ​13) (range: 5–60 months), no local tumor progression occurred.

Conclusions

Surgery and thermal ablation are safe and effective options for the treatment of pulmonary multifocal GGO-type adenocarcinoma.

[Diagnosis and Treatment of Pulmonary Multifocal Ground-glass Nodules]

In recent years, with the development of the high resolution computed tomography (HRCT) screening program for lung cancer, the multifocal ground-glass nodule (GGN) has been discovered more and more. Because there are still many uncertainties in the diagnosis and treatment of multifocal GGN in lung, this paper reviews the clinical concerns such as the follow-up interval and time, the relationship between main focus and other focuses, diagnosis, treatment and follow-up of residual nodules.

Recent and Current Advances in FDG-PET Imaging within the Field of Clinical Oncology in NSCLC: A Review of the Literature

Lung cancer is the leading cause of cancer-related deaths around the world, the most common type of which is non-small-cell lung cancer (NSCLC). Computed tomography (CT) is required for patients with NSCLC, but often involves diagnostic issues and large intra- and interobserver variability. The anatomic data obtained using CT can be supplemented by the metabolic data obtained using fluorodeoxyglucose F 18 (FDG) positron emission tomography (PET); therefore, the use of FDG-PET/CT for staging NSCLC is recommended, as it provides more accuracy than either modality alone. Furthermore, FDG-PET/magnetic resonance imaging (MRI) provides useful information on metabolic activity and tumor cellularity, and has become increasingly popular. A number of studies have described FDG-PET/MRI as having a high diagnostic performance in NSCLC staging. Therefore, multidimensional functional imaging using FDG-PET/MRI is promising for evaluating the activity of the intratumoral environment. Radiomics is the quantitative extraction of imaging features from medical scans. The chief advantages of FDG-PET/CT radiomics are the ability to capture information beyond the capabilities of the human eye, non-invasiveness, the (virtually) real-time response, and full-field analysis of the lesion. This review summarizes the recent advances in FDG-PET imaging within the field of clinical oncology in NSCLC, with a focus on surgery and prognostication, and investigates the site-specific strengths and limitations of FDG-PET/CT. Overall, the goal of treatment for NSCLC is to provide the best opportunity for long-term survival; therefore, FDG-PET/CT is expected to play an increasingly important role in deciding the appropriate treatment for such patients.

Procedure-specific prognostic impact of micropapillary subtype may guide resection strategy in small-sized lung adenocarcinomas: a multicenter study

Background:

Limited resection has gradually become an acceptable treatment for lung adenocarcinomas (ADCs) presenting as ground-glass nodules (GGNs). However, its role in lung ADCs presenting as pure solid nodules (PSN) remains unclear. In this study, we aimed to identify potential candidates for limited resection in lung ADCs presenting as PSN.

Methods:

We retrospectively reviewed 772 patients from seven hospitals with lung ADCs ⩽2 cm, presenting as PSN on computed tomography scans, who had undergone surgery between 2009 and 2013. Histological subtypes were listed in 5% increments. To investigate the value of histological subtypes in surgical decision making, five pathologists prospectively evaluated the feasibility of identifying histological subtypes using frozen section (FS) in two cohorts.

Results:

The percentage of micropapillary (MIP) subtype had a striking impact on recurrence-free survival (RFS) and overall survival (OS) for lung ADCs ⩽2 cm presenting as PSNs. In multivariable Cox analysis, segmentectomy was significantly associated with worse RFS and OS in patients with MIP >5% than lobectomy, but not in those with MIP ⩽5%. With wedge resection, worse RFS and OS were observed in patients with MIP >5% and those with MIP ⩽5% than lobectomy. The sensitivity and specificity for detecting MIP by FS were 74.2% and 85.6%, respectively, with substantial inter-rater agreement.

Conclusion:

Segmentectomy and lobectomy had similar oncological outcomes in patients with lung ADCs ⩽2 cm presenting as PSN with MIP ⩽5%. Randomized trials are necessary to validate the feasibility of intraoperative FS to choose candidates for segmentectomy.

Low Galectin-3 Expression Level in Primary Tumors Is Associated with Metastasis in T1 Lung Adenocarcinoma

BACKGROUND AND OBJECTIVE

Although nodal and distant metastasis is rare in T1 lung adenocarcinoma, it is related to poor clinical prognosis. Association between galectin-3 (Gal-3) expression level, and clinical outcome of T1 lung adenocarcinoma has not been clarified.

METHODS

From January 2009 to December 2014, 74 patients with surgically resected T1 lung adenocarcinoma were enrolled in this retrospective cohort study. Patient outcomes were followed up until December 2019. Gal-3 expression level in primary tumors was assessed immunohistochemically and evaluated based on the staining intensity and percentage. Patient characteristics and correlation between Gal-3 expression level and clinical outcomes were reviewed.

RESULTS

Low Gal-3 expression was associated with increased metastatic events (p = 0.03), especially distant metastasis (p = 0.007), and mortality rate (p = 0.04). Kaplan-Meier analysis revealed that high Gal-3 expression level was associated with favorable recurrence-free survival in T1 lung adenocarcinoma (log-rank p = 0.048) and T1a (≤ 2 cm, American Joint Committee on Cancer (AJCC) 7th edition) lung adenocarcinoma (log-rank p = 0.043). Gal-3 expression along with tumor size showed a larger area under curve (AUC) than tumor size alone for predicting metastatic events (AUC = 0.747 vs. 0.681) and recurrence (AUC = 0.813 vs. 0.766) in T1a lung adenocarcinoma in the receiver-operating characteristic curve.

CONCLUSION

Low Gal-3 expression level in primary tumors was remarkably associated with increased metastatic events and reduced recurrence-free survival in T1 lung adenocarcinoma. We suggest that Gal-3 expression level in addition to tumor size may potentially be stronger than tumor size alone in predicting metastasis in T1a lung adenocarcinoma patients.

Development and evaluation of a venous computed tomography radiomics model to predict lymph node metastasis from non-small cell lung cancer

The objective of this study was to develop a venous computed tomography (CT)-based radiomics model to predict the lymph node metastasis (LNM) in patients with non-small cell lung cancer (NSCLC). A total of 411 consecutive patients with NSCLC underwent tumor resection and lymph node (LN) dissection from January 2018 to September 2018 in our hospital. A radiologist with 20 years of diagnostic experience retrospectively reviewed all CT scans and classified all visible LNs into LNM and non-LNM groups without the knowledge of pathological diagnosis. A logistic regression model (radiomics model) in classification of pathology-confirmed NSCLC patients with and without LNM was developed on radiomics features for NSCLC patients. A morphology model was also developed on qualitative morphology features in venous CT scans. A training group included 288 patients (99 with and 189 without LNM) and a validation group included 123 patients (42 and 81, respectively). The receiver operating characteristic curve was performed to discriminate LNM (+) from LNM (-) for CT-reported status, the morphology model and the radiomics model. The area under the curve value in LNM classification on the training group was significantly greater at 0.79 (95% confidence interval [CI]: 0.77-0.81) by use of the radiomics model (build by best 10 features in predicting LNM) compared with 0.51 by CT-reported LN status (P < .001) or 0.66 (95% CI: 0.64-0.68) by morphology model (build by tumor size and spiculation) (P < .001). Similarly, the area under the curve value on the validation group was 0.73 (95% CI: 0.70-0.76) by the radiomics model, compared with 0.52 or 0.63 (95% CI: 0.60-0.66) by the other 2 (both P < .001). A radiomics model shows excellent performance for predicting LNM in NSCLC patients. This predictive radiomics model may benefit patients to get better treatments such as an appropriate surgery.

Preoperative predictors of lymph node metastasis in clinical T1 adenocarcinoma

Background

The subcategory “solid component of tumor” is a new criterion of tumor categories in the updated eighth edition of the TNM classification. Nevertheless, the predictors of lymph node metastasis among patients with clinical T1 adenocarcinoma, based on the TNM classification 8^th edition, remain unclear. This study aimed to identify the preoperative predictors of lymph node metastasis in clinical T1 adenocarcinoma by comparing clinicopathological characteristics between the groups with and without lymph node metastasis.

Methods

We performed a retrospective observational single-center study at the Sendai Kousei Hospital. From January 2012 to September 2019, we included 515 patients who underwent curative lobectomy or segmentectomy and mediastinal lymph node dissection among those with clinical T1 adenocarcinoma according to the UICC-TNM staging 8^th edition. They were divided into two groups: those with lymph node metastasis (positive group) and those without (negative group). The clinicopathological factors were retrospectively analyzed and compared between the groups.

Results

In univariate analysis, carcinoembryonic antigen (>5.0 ng/mL) (P=0.0007), maximum standardized uptake (>3.5) (P<0.0001), clinical T factor (T1c) (P<0.0001), and consolidation tumor ratio (>0.85) (P<0.0001) were significant predictors of lymph node metastasis. Multivariate analysis revealed that maximum standardized uptake SUVmax (>3.5) (odds ratio =10.4, P<0.0001) was independently associated with lymph node metastasis. In univariate analysis, carcinoembryonic antigen (>5.0) (P=0.048) was the only predictor of lymph node metastasis among patients of cT1b, while no parameters were identified as significant predictors among patients of cT1c.

Conclusions

SUVmax and CEA are useful preoperative predictors of lymph node metastases in patients with clinical T1 adenocarcinoma, stratified to T1b and T1c, based on the 8^th TNM classification.

A cross-modal 3D deep learning for accurate lymph node metastasis prediction in clinical stage T1 lung adenocarcinoma

OBJECTIVES

The evaluation of lymph node (LN) status by radiologists based on preoperative computed tomography (CT) lacks high precision for early lung cancer patients; erroneous evaluations result in inappropriate therapeutic plans and increase the risk of complications. This study aims to develop a cross-modal 3D neural network based on CT images and prior clinical knowledge for accurate prediction of LN metastasis in clinical stage T1 lung adenocarcinoma.

PATIENTS AND METHODS

Five hundred one lung adenocarcinoma patients with clinical stage T1 were enrolled. Data including: corresponding 3D nodule-centered patches of CT; prior clinical features; and pathological labels of LN status were obtained. We proposed a cross-modal deep learning system, which can successfully incorporate prior clinical knowledge and CT images into a 3D neural network to predict LN metastasis. We trained and validated our system with 401 cases and tested its performance with 100 cases. The result was compared with that of the logistic regression integration model, the single deep learning model without prior clinical knowledge integration, radiomics method, and manual evaluation by radiologists.

RESULTS

The model proposed DensePriNet achieved an AUC of 0.926, which is significantly higher than the logistic regression integration model (0.904) single deep learning model (0.880), and radiomics method (0.891). The Matthews Correlation Coefficient (MCC) of DensePriNet (0.705) was significantly higher than manual classification by one senior radiologist (0.534) and one junior radiologist (0.416), respectively.

CONCLUSION

The performance of the single deep learning method is significantly higher than the radiomics method and the radiologists, and integration of prior clinical knowledge into the deep learning model enhance the diagnostic precision of LN status and facilitate the application of precision medicine.

Minimizing residual occult nodal metastasis in NSCLC: recent advances, current status and controversies

Introduction: Nodal involvement in lung cancer is a significant determinant of prognosis and treatment management. New evidence exists regarding the management of occult lymph node metastasis and residual disease in the fields of imaging, mediastinal staging, and operative management.Areas covered: This review summarizes the latest body of knowledge on the identification and management of occult lymph node metastasis in NSCLC. We focus on tumor-specific characteristics; imaging modalities; invasive mediastinal staging; and operative management including, technique, degree of resection, and lymph node examination.Expert opinion: Newly identified risk-factors associated with nodal metastasis including tumor histology, location, radiologic features, and metabolic activity are not included in professional societal guidelines due to the heterogeneity of their reporting and uncertainty on how to adopt them into practice. Imaging as a sole diagnostic method is limited. We recommend confirmation with invasive mediastinal staging. EBUS-FNA is the best initial method, but adoption has not been uniform. The diagnostic algorithm is less certain for re-staging of mediastinal nodes after neoadjuvant therapy. Mediastinal node sampling during lobectomy remains the gold-standard, but evidence supports the use of minimally invasive techniques. More study is warranted regarding sublobar resection. No consensus exists regarding lymph node examination, but new evidence supports reexamination of current quality metrics.

Minor components of micropapillary and solid subtypes in lung invasive adenocarcinoma (≤ 3 cm): PET/CT findings and correlations with lymph node metastasis

OBJECTIVE

To investigate the PET/CT findings in lung invasive adenocarcinoma with minor components of micropapillary or solid contents and its association with lymph node metastasis.

MATERIALS AND METHODS

A total of 506 lung invasive adenocarcinoma (≤ 3 cm) patients who underwent a PET/CT examination and resection surgery were included. According to the proportion of solid/micropapillary components, the patients were classified into three groups: solid/micropapillary-negative (SMPN) (n = 258), solid/micropapillary-minor (SMPM; > 5% not predominant) (n = 158) and solid/micropapillary-predominant (SMPP; > 5% most dominant) (n = 90). The patients' PET/CT findings, including SUVmax, MTV, TLG and CT characteristics, and other clinical factors were compared by one-way ANOVA test. Logistic regression analysis was done to identify the most predictive findings for lymph node metastasis.

RESULTS

The value of SUVmax, MTV, TLG and tumor size was highest in SMPP group, followed by SMPM and SMPN group (P < 0.001).The areas under the curve for SUVmax, MTV and TLG for node metastasis were 0.822, 0.843 and 0.835, respectively. Univariate analysis found that the SMPP and SMPM group had more lymph node metastasis than the SMPN group (P < 0.001). Furthermore, the lymph node metastasis group had higher CEA, SUVmax, MTV, TLG, tumor size and more pleural invasion (P < 0.001). Logistic regression analysis found that SMPP pathological type, SMPM pathological type, higher CEA and male patients were risk factors for lymph node metastasis (P < 0.01).

CONCLUSIONS

Lung invasive adenocarcinoma with micropapillary or solid contents had higher SUVmax, MTV, TLG and tumor size and was associated with lymph node metastasis, even if they were not predominant.

CT-based radiomics signature for the stratification of N2 disease risk in clinical stage I lung adenocarcinoma

Background

Risk stratification of N2 disease is vital for selecting candidates to receive invasive mediastinal staging modalities. In this study, we aimed to stratify the risk of N2 metastasis in clinical stage I lung adenocarcinoma using radiomics analysis.

Methods

Two datasets of patients with clinical stage I lung adenocarcinoma who underwent lung resection were included (training dataset, 880; validation dataset, 322). Using PyRadiomics, 1,078 computed tomography (CT)-based radiomics features were extracted after semi-automated lung nodule segmentation. In order to predict N2 status, a radiomics signature was constructed after selecting the optimal radiomics feature subset by sequentially applying minimum-redundancy-maximum-relevance and least absolute shrinkage and selection operator (LASSO) techniques. Its performance was validated in the validation dataset.

Results

The incidences of N2 metastasis were 8.4% and 7.1% in the training and validation datasets, respectively. Unsupervised cluster analysis revealed that radiomics features significantly correlated with lymph node status and pathological subtypes. For N2 disease prediction, five radiomics features were selected to establish the radiomics signature, which showed a significantly better predictive performance than clinical factors (P<0.001). The area under the receiver operating characteristic curve was 0.81 (0.77-0.86) and 0.69 (0.63-0.75) for radiomics signature and clinical factors, respectively, in the training dataset, and 0.82 (0.71-0.92) and 0.64 (0.52-0.75), respectively, in the validation dataset.

Conclusions

The established CT-based radiomics signature could stratify the risk of N2 metastasis in clinical stage I lung adenocarcinoma, thus assisting clinicians in making patient-specific mediastinal staging strategy.

Development of a predictive radiomics model for lymph node metastases in pre-surgical CT-based stage IA non-small cell lung cancer

OBJECTIVES

To develop and validate predictive models using clinical parameters, radiomic features and a combination of both for lymph node metastasis (LNM) in pre-surgical CT-based stage IA non-small cell lung cancer (NSCLC) patients.

METHODS

This retrospective study included 649 pre-surgical CT-based stage IA NSCLC patients from our hospital. One hundred and thirty-eight (21 %) of the 649 patients had LNM after surgery. A total of 396 radiomic features were extracted from the venous phase contrast enhanced computed tomography (CECT). The training group included 455 patients (97 with and 358 without LNM) and the testing group included 194 patients (41 with and 153 without LNM). The least absolute shrinkage and selection operator (LASSO) algorithm was used for radiomic feature selection. The random forest (RF) was used for model development. Three models (a clinical model, a radiomics model, and a combined model) were developed to predict LNM in early stage NSCLC patients. The area under the receiver operating characteristic (ROC) curve (AUC) value and decision curve analysis were used to evaluate the performance in LNM status (with or without LNM) using the three models.

RESULTS

The ROC analysis (also decision curve analysis) showed predictive performance for LNM of the radiomics model (AUC values for training and testing, respectively 0.898 and 0.851) and of the combined model (0.911 and 0.860, respectively). Both performed better than the clinical model (0.739 and 0.614, respectively; delong test p-values both<0.001).

CONCLUSION

A radiomics model using the venous phase of CE-CT has potential for predicting LNM in pre-surgical CT-based stage IA NSCLC patients.

Prognosis of upstaged N1 and N2 disease after curative resection in patients with clinical N0 non-small cell lung cancer

Background

Nodal upstaging occasionally occurs after curative resection in clinical N0 non-small cell lung cancer (NSCLC). The purpose of this study was to evaluate the prognosis of clinical N0 NSCLC (T1-2, tumor size 5 cm or smaller) after upstaging to pathologic N1 or N2.

Methods

From 2005 to 2015, 676 consecutive patients were diagnosed with clinical T1-2N0 NSCLC and underwent curative resection. Among these, tumors were upstaged to N1 in 46 patients and to N2 in 24 patients. We analyzed the prognosis of upstaged tumors. For comparison of prognosis between nodal upstaging groups and others in the same stage, patients with preoperative pathologically proven N1 (n=31) and N2 (n=55) NSCLC were included in the study.

Results

A total of 70 patients (10.4%) had nodal upstaging after curative resection of clinical N0 NSCLC. Upstaging to N1 occurred in 46 patients and upstaging to N2 occurred in 24 patients. The 5-year disease-specific survival rate was not statistically different between the upstaged and non-upstaged N1/N2 groups in N1 disease (73.3% vs. 70.5%, P=0.247) or in N2 disease (58.9% vs. 50.7%, P=0.283). Multivariate analysis showed that nodal upstaging was not a significant prognostic factor in N1 or N2 NSCLC (hazard ratio =0.385, P=0.235; hazard ratio =0.677, P=0.458).

Conclusions

Postoperative nodal upstaging from clinical T1-2N0 NSCLC was not a significant prognostic factor in the same stage. Therefore, surgical treatment of clinical T1-2N0 lung cancer diagnosed by imaging without preoperative pathologic lymph node staging can be a treatment option.

Prognosis after wedge resection in patients with 8th edition TNM stage IA1 and IA2 non-small cell lung cancer

Background

According to the 8^th edition TNM classification for non-small cell lung cancer (NSCLC), tumor stage (T) is determined by the maximum size of the invasive component, without the lepidic component, and the T category has been further subdivided. We investigated the indications for wedge resection using the 8^th edition TNM staging system, which measures only the size of the invasive component in tumor size.

Methods

We compared 5-year disease-free survival (DFS) rates in 429 consecutive patients with 8^th edition stage IA1 and IA2 NSCLC who underwent lobectomy or wedge resection from 2007 to 2017. We also analyzed the risk factors for recurrence after surgical resection.

Results

There were no significant differences in clinicopathological factors or 5-year DFS in patients with stage IA1 disease (5-year DFS 95.0%, lobectomy, vs. 91.6%, wedge resection; P=0.435). For patients with stage IA2 tumors, the 5-year DFS was 88.3% after lobectomy and 74.0% after wedge resection (P=0.118). There were significant differences in clinicopathological characteristics between lobectomy and wedge resection groups in stage IA2 NSCLC. On multivariate analysis, serum CEA level [hazard ratio (HR) =1.040, P=0.046] and lymphovascular invasion (HR =2.664, P=0.027), but not wedge resection, were significant risk factors for recurrence in stage IA2 NSCLC. On multivariate analysis for recurrence risk after wedge resection in stage IA1 and stage IA2 NSCLC, only the width of the resection margin was associated with recurrence.

Conclusions

Wedge resection may be an acceptable procedure in stage IA1 NSCLC. When performing wedge resection, it is necessary to ensure a sufficient resection margin distance.

Novel approach for predicting occult lymph node metastasis in peripheral clinical stage I lung adenocarcinoma

Background

Occult nodal metastasis results in a poor prognosis for lung cancer patients. The aim of this study was to develop an efficient approach for predicting occult nodal metastasis in peripheral clinical stage I lung adenocarcinoma.

Methods

Data for 237 peripheral clinical stage I lung adenocarcinoma patients who underwent complete resection were retrospectively reviewed. Univariate and multivariate analyses were performed to investigate predictors of occult nodal metastasis. Kaplan-Meier analysis was performed for survival.

Results

Occult nodal metastasis was detected in 26/237 (11.0%) patients. Nodule type, tumor SUVmax, whole tumor size, solid tumor size, and preoperative serum carcinoembryonic antigen (CEA) were identified as preoperative predictors of occult nodal metastasis (all P<0.05). Solid tumor size (P<0.001) and preoperative serum CEA (P=0.004) were identified as independent predictors on multivariate analysis. A prediction model was established using the independent predictors. The occult nodal metastasis rate was 2.4% with solid tumor size ≤2.3 cm (low-risk group), 17.0% with solid tumor size >2.3 cm and CEA ≤5 ng/mL (moderate-risk group), and 56.0% with solid tumor size >2.3 cm and CEA >5 ng/mL (high-risk group). The occult nodal metastasis rate was significantly higher in papillary-predominant (11.0%) and solid-predominant subtypes (28.6%; P=0.001). Patients having a micropapillary component had a significantly higher occult nodal metastasis rate (24.2%) compared with no micropapillary component (P=0.007). Histological subtype with micropapillary component and all preoperative predictors were significant prognostic factors affecting disease-free survival (DFS) (all P<0.05).

Conclusions

A novel approach to predict occult nodal metastasis was developed for peripheral clinical stage I lung adenocarcinoma. It would be helpful for selecting candidates for stereotactic ablative radiotherapy (SABR) or wedge resection and mediastinoscopy or endobronchial ultrasound transbronchial needle aspiration (EBUS-TBNA). Complete nodal dissection should be performed for moderate to high-risk patients or patients with poor histologic subtypes.