Risk analyses of N2 lymph-node metastases in patients with T1 non-small cell lung cancer: a multi-center real-world observational study in China

Correlation Between the Number of Pathological Risk Factors and Postoperative Prognosis in Patients with Stage I Lung Adenocarcinoma

BACKGROUND

Although visceral pleural invasion, lymphovascular invasion, tumor spread through air spaces, and poor differentiation are pathological risk factors associated with unfavorable prognosis in patients with lung adenocarcinoma, the cumulative impact of these factors on prognosis remains unclear.

METHODS

We enrolled 1532 patients with stage I lung adenocarcinoma. Patients were divided according to the number of risk factors as follows: Group A (without risk factors), Group B (one risk factor), and Group C (multiple risk factors). Moreover, we stratified patients into two subgroups based on tumor size (≤ 3 cm, 3-4 cm). Kaplan-Meier analysis was used to evaluate 5-year disease-free survival (DFS) and overall survival (OS).

RESULTS

Overall, 949, 404, and 179 patients were included in Groups A, B, and C, respectively. Group C had a larger tumor size and more cases of extrathoracic recurrence than the other groups. The 5-year DFS and OS gradually decreased across Groups A to C (DFS: 94.3%, 80.6%, and 64.3%, respectively, p < 0.001; OS: 97.2%, 92.7%, and 77%, respectively, p < 0.001). A similar trend was observed for tumors ≤ 3 cm in size (DFS: 95.2%, 83.2%, and 68.5%, respectively, p < 0.001; OS: 97.6%, 94.1%, and 79.6%, respectively, p < 0.001), but a less pronounced trend was observed for tumors between 3 and 4 cm in size (DFS: 72.1, 60.8, and 43.3%, respectively, p = 0.054; OS: 85.7, 82.1, and 64.7%, respectively, p = 0.16).

CONCLUSIONS

Postoperative survival worsened with increasing pathological risk factors in patients with stage I lung adenocarcinoma, especially those with tumor size ≤ 3 cm.

Lymph node metastasis and its risk factors in T1 lung adenocarcinoma

BACKGROUND

In this study, the focus was primarily on examining the occurrence of lymph node metastasis in T1 lung adenocarcinoma, while also analyzing the relationship between clinical variables such as imaging characteristics, pathological classifications, and lymph node metastasis.

METHODS

We retrospectively analyzed data from patients with T1 lung adenocarcinoma who underwent lobectomy and lymph node dissection between January 2016 and December 2019. Utilizing univariate and multivariate analyses, we assessed the associations between lymph node metastasis and various clinical factors, including imaging characteristics, lesion location and depth, and pathological subtypes.

RESULTS

Of the 433 patients with T1 lung adenocarcinoma, 139 had lymph node metastasis. Moreover, the incidence of node 1 (N1) lymph node, sequential, and node 2 (N2) skip metastases were 12.2%, 12.7%, and 7.2%, respectively. Univariate analysis revealed that tumor diameter, depth ratio, sex, invasive imaging features, and pathological subtype were significantly associated with lymph node metastasis. Multivariate analysis revealed that the tumor depth ratio, tumor diameter, pleural indentation or traction sign, nonvascular penetration sign, solid component, nonadherence, and micropapillary pathological subtype were risk factors for lymph node metastasis. In the multivariate analysis, the micropapillary pathological subtype was an independent risk factor for N2 skip metastasis.

CONCLUSIONS

In patients with clinical stage T1 lung adenocarcinoma, the risk of lymph node metastasis is higher for tumors located deep within the lung tissue with solid components, invasive preoperative imaging features, and larger diameters. For N2 skip lymph node metastasis, the micropapillary pathological subtype represents a significant high-risk factor.

Developing a primary tumor and lymph node 18F-FDG PET/CT-clinical (TLPC) model to predict lymph node metastasis of resectable T2-4 NSCLC

PURPOSE

The goal of this study was to investigate whether the combined PET/CT radiomic features of the primary tumor and lymph node could predict lymph node metastasis (LNM) of resectable non-small cell lung cancer (NSCLC) in stage T2-4.

METHODS

This retrospective study included 192 NSCLC patients who underwent tumor and node dissection between August 2016 and December 2017 and underwent ¹⁸F-fluorodeoxyglucose (¹⁸F-FDG) PET/CT scanning 1-3 weeks before surgery. In total, 192 primary tumors (> 3 cm) and 462 lymph nodes (LN > 0.5 cm) were analyzed. The pretreatment clinical features of these patients were recorded, and the radiomic features of their primary tumor and lymph node were extracted from PET/CT imaging. The Spearman's relevance combined with the least absolute shrinkage and selection operator was used for radiomic feature selection. Five independent machine learning models (multi-layer perceptron, extreme Gradient Boosting, light gradient boosting machine, gradient boosting decision tree, and support vector machine) were tested as classifiers for model development. We developed the following three models to predict LNM: tumor PET/CT-clinical (TPC), lymph PET/CT-clinical (LPC), and tumor and lymph PET/CT-clinical (TLPC). The performance of the models and the clinical node (cN) staging was evaluated using the ROC curve and confusion matrix analysis.

RESULTS

The ROC analysis showed that among the three models, the TLPC model had better predictive clinical utility and efficiency in predicting LNM of NSCLC (AUC = 0.93, accuracy = 85%; sensitivity = 0.93; specificity = 0.75) than both the TPC model (AUC = 0.54, accuracy = 50%; specificity = 0.38; sensitivity = 0.59) and the LPC model (AUC = 0.82, accuracy = 70%; specificity = 0.41; sensitivity = 0.92). The TLPC model also exhibited great potential in predicting the N2 stage in NSCLC (AUC = 0.94, accuracy = 79%; specificity = 0.64; sensitivity = 0.91).

CONCLUSION

The combination of CT and PET radiomic features of the primary tumor and lymph node showed great potential for predicting LNM of resectable T2-4 NSCLC. The TLPC model can non-invasively predict lymph node metastasis in NSCLC, which may be helpful for clinicians to develop more rational therapeutic strategies.

Preoperative risk factors of lymph node metastasis in clinical N0 lung adenocarcinoma of 3 cm or less in diameter

BACKGROUND

Lung adenocarcinoma is the most common subtype of non-small cell lung cancer. The surgical strategy of lymph node dissection is controversial because many more patients are diagnosed at an early stage in clinical practice.

METHODS

We retrospectively reviewed 622 clinical N0 lung adenocarcinoma patients with 3 cm or less in tumor size who underwent lobectomy or segmentectomy combined with lymph node dissection in our hospital from January 2017 to December 2019. We performed univariate and multivariate analyses to identify preoperative risk factors of lymph node metastasis.

RESULTS

Lymph node metastasis was found in 60 out of 622 patients. On univariate analysis, lymph node metastasis was linked to smoking history, preoperative CEA level, tumor size, tumor location (peripheral or central), consolidation/tumor ratio, pleural invasion, and pathologic type. However, only the preoperative CEA level, tumor size, and consolidation/tumor ratio were independent risk factors in multivariate analysis. The ROC curve showed that the cutoff value of tumor size was 1.7 cm. There was no lymph node metastasis in patients without risk factors.

CONCLUSIONS

The preoperative CEA level, tumor size, and consolidation/tumor ratio were independent risk factors of lymph node metastasis in clinical N0 lung adenocarcinoma with tumor size ≤ 3 cm. The lymph node metastasis rate was extremely low in clinical N0 lung adenocarcinoma patients without risk factors and lymph node dissection should be avoided in these patients to reduce surgical trauma.

Risk analysis in peripheral clinical T1 non-small cell lung cancer correlations between tumor-to-blood standardized uptake ratio on 18F-FDG PET-CT and primary tumor pathological invasiveness: a real-world observational study

BACKGROUND

Sublobar resection is not suitable for patients with pathological invasiveness [including lymph node metastasis (LNM), visceral pleural invasion (VPI), and lymphovascular invasion (LVI)] of peripheral clinical T1 (cT1) non-small cell lung cancer (NSCLC), while primary tumor maximum standardized uptake value (SUV_max) on ¹⁸F-FDG PET-CT is related to pathological invasiveness, the significance differed among different institutions is still challenging. This study explored the relationship between the tumor-to-blood standardized uptake ratio (SUR) of ¹⁸F-FDG PET-CT and primary tumor pathological invasiveness in peripheral cT1 NSCLC patients.

METHODS

This retrospective study included 174 patients with suspected lung neoplasms who underwent preoperative ¹⁸F-FDG PET-CT. We compared the differences of the clinicopathological variables, metabolic and morphological parameters in the pathological invasiveness and less-invasiveness group. We performed a trend test for these parameters based on the tertiles of SUR. The relationship between SUR and pathological invasiveness was evaluated by univariate and multivariate logistics regression models (included unadjusted, simple adjusted, and fully adjusted models), odds ratios (ORs), and 95% confidence intervals (95% CIs) were calculated. A smooth fitting curve between SUR and pathological invasiveness was produced by the generalized additive model (GAM).

RESULTS

Thirty-eight point five percent of patients had pathological invasiveness and tended to have a higher SUR value than the less-invasiveness group [6.50 (4.82-11.16) vs. 4.12 (2.04-6.61), P<0.001]. The trend of SUV_max, mean standardized uptake value (SUV_mean), metabolic tumor volume (MTV), total lesion glycolysis (TLG), mean CT value (CT_mean), size of the primary tumor, neuron-specific enolase (NSE), the incidence of LNM, adenocarcinoma (AC), and poor differentiation in the tertiles of SUR value were statistically significant (P were <0.001, <0.001, 0.010, <0.001, <0.001, 0.002, 0.033, <0.001, 0.002, and <0.001, respectively). Univariate analysis showed that the risk of pathological invasiveness increased significantly with increasing SUR [OR: 1.13 (95% CI: 1.06-1.21), P<0.001], and multivariate analysis demonstrated SUR, as a continuous variable, was still significantly related to pathological invasiveness [OR: 1.09 (95% CI: 1.01-1.18), P=0.032] after adjusting for confounding covariates. GAM revealed that SUR tended to be linearly and positively associated with pathological invasiveness and E-value analysis suggested robustness to unmeasured confounding.

CONCLUSIONS

SUR is linearly and positively associated with primary tumor pathological invasiveness independent of confounding covariates in peripheral cT1 NSCLC patients and could be used as a supplementary risk maker to assess the risk of pathological invasiveness.

Tumor size as a predictor for prognosis of patients with surgical IIIA-N2 non-small cell lung cancer after surgery

Background

The 8^th edition of the American Joint Committee on Cancer staging system for lung cancer made major revisions to T staging, especially the size division of stage II/III patients. However, the value of tumor size in the postoperative prognosis of IIIA–N2 non-small cell lung cancer (NSCLC) is seldom mentioned, and survival data of such patients should be re-evaluated according to the 8^th edition staging system.

Methods

Patients with IIIA-N2 NSCLC after surgery were identified in the Surveillance, Epidemiology, and End Results database (n=4,128). All patients were stratified according to tumor size, 5-year overall survival (OS) was then compared. Cox regression analysis was used to determine the value of size to discriminate patients with prognostic differences and establish a predictive nomogram system. Patients with IIIA-N2 NSCLC from our own institute (n=583) were used to validate the results.

Results

The prognosis of patients with tumor sizes of 0–2, 2–4 and 4–5 cm differed greatly from each other in the training cohort, with 5-year OS rates of 53.7%, 43.9% and 36.9% respectively (P<0.001), in the validation cohort, the rates were 54.1%, 38.4% and 33.8% respectively. Tumor size >2 cm was considered an independent risk factor compared to the ≤2 cm group in the Cox regression analysis: 2–4 cm (HR =1.25, 1.12–1.39; P<0.001), 4–5 cm (HR =1.51, 1.32–1.39; P<0.001), the validation cohort showed the same trend. The concordance index of the training set was 0.634 (0.622–0.646), while that of the validation set was 0.716 (0.686–0.746). The calibration plot showed optimal consistency between the nomogram predicted survival and observed survival.

Conclusions

Tumors with different sizes showed significant postoperative survival differences among patients with IIIA-N2 NSCLC. Tumor size should be considered when making surgery decisions in such patients, with tumor size ≤2 cm showing considerably better prognosis.

Development and validation of a preoperative noninvasive predictive model based on circular tumor DNA for lymph node metastasis in resectable non-small cell lung cancer

Background

Clinical lymph node staging in resectable non-small cell lung cancer (NSCLC) patients not only indicates prognosis, but also determines primary treatment strategy. The demand of noninvasive tool for preoperative lymph node metastasis prediction remains significant. This study aimed to develop and externally validate a preoperative noninvasive predictive model based on circular tumor DNA (ctDNA) for the lymph node metastasis in resectable NSCLC patients.

Methods

Resectable NSCLC patients in TRACERx cohort were included as training group. Potential preoperative noninvasively accessible predictors were incorporated into the development of a nomogram via multivariate logistic regression. The predictive model was externally validated by a similar cohort from our hospital.

Results

Overall, 58 patients from TRACERx cohort were included as training group and 37 patients from our hospital were included as external validation group. Variant allele frequency (VAF) level of ctDNA was significantly associated with lymph node metastasis (OR: 4.89, 95% CI: 1.22–19.54, P=0.03). The predictive model incorporating age, tumor size and VAF demonstrated satisfactory discrimination and calibration in both training group (AUC =0.77, 95% CI: 0.65–0.90, P=0.001) and external validation group (AUC =0.84, 95% CI: 0.70–0.99, P=0.005).

Conclusions

High VAF level in preoperative ctDNA may indicate lymph node metastasis of resectable NSCLC. And a preoperative noninvasive predictive model based on ctDNA for the lymph node metastasis in resectable NSCLC patients was developed and externally validated with satisfactory discrimination and calibration.