A prediction model for lymph node metastases using pathologic features in patients intraoperatively diagnosed as stage I non-small cell lung cancer

Pathological N1/N2 in Clinical Stage I Bronchogenic Carcinoma. Analysis From a Prospective Multicentre Database

OBJECTIVES

To determine the incidence of occult N1/N2 nodal metastases and associated risk factors in patients with non-small cell lung cancer no larger than 3cm and deemed cN0 by CT and PET-CT in a prospective, multicentre national database.

METHODS

Patients with a NSCLC no larger than 3cm, deemed cN0 by PET-CT and CT scan, who had undergone at least a lobectomy, were selected from a national multicentre database of 3533 patients who had undergone anatomic lung resection between 2016 and 2018. Clinical and pathological variables of patients with pN0 and patients with pN1/N2 were compared to identify factors associated with the presence of lymph node metastases. Chi² and the Mann-Whitney U test were used for categorical and numerical variables, respectively. All variables with p<0.2 in the univariate analysis were included in the multivariate logistic regression analysis.

RESULTS

The study included 1205 patients from the cohort. The incidence of occult pN1/N2 disease was 10.70% (95%CI, 9.01-12.58). The multivariable analysis revealed that the degree of differentiation, size, location (central or peripheral) and SUV of the tumour in PET, surgeon experience and number of lymph nodes resected were associated with occult N1/N2 metastases.

CONCLUSIONS

The incidence of occult N1/N2 in patients with bronchogenic carcinoma with cN0 tumours no larger than 3cm is no negligible. Data about the degree of differentiation, tumour size in CT scan, maximal uptake of the tumour in PET-CT, location (central or peripheral), number of lymph nodes resected and surgeon seniority is relevant in order to detect patients at risk.

Tumour-pleura relationship on CT is a risk factor for occult lymph node metastasis in peripheral clinical stage IA solid adenocarcinoma

OBJECTIVES

To investigate whether the tumour-pleura relationship on computed tomography (CT) is a risk factor for occult lymph node metastasis (OLNM) in peripheral clinical stage IA solid adenocarcinoma.

METHODS

A total of 232 patients were included in the study. The tumour-pleura relationship was divided into four types: type 1, the tumour was unrelated to the pleura; type 2, the tumour was not in contact with the pleura, and one or more linear or striated pleural tags were visible; type 3, the tumour was not in contact with the pleura, and one or more linear or striated pleural tags with soft tissue component at the pleural end were visible; and type 4, the tumour was in contact with the pleura. Univariate and multivariate logistic regression analyses were used to identify the predictive factors, including the tumour-pleura relationship, clinical factors, conventional CT findings, and pathology-reported visceral pleural invasion, for OLNM.

RESULTS

Type 3 and 4 tumour-pleura relationships were more likely to have visceral pleural invasion than type 1 and 2 tumour-pleura relationships (p < 0.001). Univariate and multivariate logistic regression analyses revealed that the type 3 or 4 tumour-pleura relationship (OR: 3.261, p = 0.026), carcinoembryonic antigen level (OR: 3.361, p = 0.006), cytokeratin 19 fragments level (OR: 2.539, p = 0.025), and mediastinal window tumour size (OR: 1.078, p = 0.020) were predictive factors for OLNM.

CONCLUSIONS

The type 3 or 4 tumour-pleura relationship is correlated with a greater risk of OLNM in peripheral clinical stage IA solid adenocarcinoma.

KEY POINTS

• The tumour-pleura relationship on CT is a risk factor for occult lymph node metastasis in peripheral clinical stage IA solid adenocarcinoma. • Other risk factors for OLNM include CEA level, CYFRA level, and mediastinal window tumour size. • Pathology-reported visceral pleural invasion is not a risk factor for OLNM.

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.

Integrative Predictive Models of Computed Tomography Texture Parameters and Hematological Parameters for Lymph Node Metastasis in Lung Adenocarcinomas

OBJECTIVES

The aims of the study were to integrate characteristics of computed tomography (CT), texture, and hematological parameters and to establish predictive models for lymph node (LN) metastasis in lung adenocarcinoma.

METHODS

A total of 207 lung adenocarcinoma cases with confirmed postoperative pathology and preoperative CT scans between February 2017 and April 2019 were included in this retrospective study. All patients were divided into training and 2 validation cohorts chronologically in the ratio of 3:1:1. The χ2 test or Fisher exact test were used for categorical variables. The Shapiro-Wilk test and Mann-Whitney U test were used for continuous variables. Logistic regression and machine learning algorithm models based on CT characteristics, texture, and hematological parameters were used to predict LN metastasis. The performance of the multivariate models was evaluated using a receiver operating characteristic curve; prediction performance was evaluated in the validation cohorts. Decision curve analysis confirmed its clinical utility.

RESULTS

Logistic regression analysis demonstrated that pleural thickening (P = 0.013), percentile 25th (P = 0.033), entropy gray-level co-occurrence matrix 10 (P = 0.019), red blood cell distribution width (P = 0.012), and lymphocyte-to-monocyte ratio (P = 0.049) were independent risk factors associated with LN metastasis. The area under the curve of the predictive model established using the previously mentioned 5 independent risk factors was 0.929 in the receiver operating characteristic analysis. The highest area under the curve was obtained in the training cohort (0.777 using Naive Bayes algorithm).

CONCLUSIONS

Integrative predictive models of CT characteristics, texture, and hematological parameters could predict LN metastasis in lung adenocarcinomas. These findings may provide a reference for clinical decision making.

Nomogram based on prognostic nutrition index and Chest CT imaging signs predicts lymph node metastasis in NSCLC patients

OBJECTIVE

To establish and validate a model capable of predicting lymph node metastasis (LNM) of non-small cell lung cancer (NSCLC) patients.

METHODS

Preoperative clinical and CT imaging data on patients with NSCLC undergoing surgery were retrospectively analyzed. A model was developed using a training cohort of 290 patients. The univariate analysis followed by dichotomous logistic regression was performed to estimate different risk factors of lymph node metastasis, and a nomogram was constructed. Using another testing cohort of 120 patients, the performance of the nomogram was validated using several evaluation methods and indices and evaluated including via the area under the curve (AUC), calibration curve, Hosmer-Lemeshow test and decision curve analysis (DCA).

RESULTS

CT-based imaging signs were important independent risk factors for lymph node metastasis in NSCLC patients. The possible risk factors also included four other independent risk factors through dichotomous logistic regression, i.e., age, SIRI, PNI and CEA, which were filtered and included in the nomogram. Nomogram yields AUC values of 0.828 [95% confidence interval (CI): 0.778-0.877] in the training cohort and 0.816 (95% CI: 0.737-0.895) in the validation cohort, respectively. The calibration curves showed high agreement in both the training and validation cohorts. At the threshold probability of 0-0.8, the nomogram increases the net outcomes compared to the treat-none and treat-all lines in the decision curve.

CONCLUSIONS

The nomogram based on the PNI and CT images signs holds promise as a novel and accurate tool for predicting the LNM in NSCLC patients and guiding intraoperative lymph node dissection.

Primary tumor location in lung cancer: the evaluation and administration

ABSTRACT

Lung cancer continues to be the leading cause of cancer-related death in the world, which is classically subgrouped into two major histological types: Non-small cell lung cancer (NSCLC) (85% of patients) and small-cell lung cancer (SCLC) (15%). Tumor location has been reported to be associated with the prognosis of various solid tumors. Several types of cancer often occur in a specific region and are more prone to spread to predilection locations, including colorectal cancer, prostate cancer, gastric cancer, ovarian cancer, cervical cancer, bladder cancer, lung tumor, and so on. Besides, tumor location is also considered as a risk factor for lung neoplasm with chronic obstructive pulmonary disease/emphysema. Additionally, the primary lung cancer location is associated with specific lymph node metastasis. And the recent analysis has shown that the primary location may affect metastasis pattern in metastatic NSCLC based on a large population. Numerous studies have enrolled the "location" factor in the risk model. Anatomy location and lobe-specific location are both important in prognosis. Therefore, it is important for us to clarify the characteristics about tumor location according to various definitions. However, the inconsistent definitions about tumor location among different articles are controversial. It is also a significant guidance in multimode therapy in the present time. In this review, we mainly aim to provide a new insight about tumor location, including anatomy, clinicopathology, and prognosis in patients with lung neoplasm.

Assessing Differences in Lymph Node Metastasis Based Upon Sex in Early Non-Small Cell Lung Cancer

BACKGROUNDS

Whether sex has any impact on the risk of lymph node (LN) metastasis (LNM) in patients with early-stage non-small cell lung cancer (NSCLC) remains controversial. Therefore, we aimed to objectively compared the risk of LNM between female and male patients with early-stage NSCLC so as to figure out whether sex-different extent of surgery may be justified for treating these patients.

METHODS

We retrospectively collected clinical data of patients undergoing lobectomy or segmentectomy with systematic hilar and mediastinal LN dissection for clinical stage IA peripheral NSCLC from June 2014 to April 2019. Both multivariate logistic regression analysis and propensity score-matched(PSM) analysis were applied to compare the risk of LNM between female and male patients.

RESULTS

We finally included a total of 660 patients for analysis. In the analysis of unmatched cohorts, there was no significant different rate of LNM (12.4% Vs 13.9%, P=0.556), hilar/intrapulmonary LNM (8.4% Vs 10.7%, P=0.318) and mediastinal LNM(7.9% Vs 7.5%, P=0.851) between female and male patients. In the multivariate analysis, sex was not found to be an independent predictor of LN in these patients. Moreover, in the analysis of well-matched cohorts generated by PSM analysis, there was still no significant different rate of LNM (13.8% Vs 13.4%, P=0.892), hilar/intrapulmonary LNM (9.1% Vs 11.2%, P=0.442) and mediastinal LNM (9.1% Vs 6.5%, P=0.289) between female and male patients.

CONCLUSIONS

Sex was not an independent predictor of LNM in early-stage NSCLC and there is no sufficient evidence justifying for sex-different extent of surgical resection for these patients.

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.

Risk factors of lobar lymph node metastases in non-primary tumor-bearing lobes among the patients of non-small-cell lung cancer

Purpose

Lobar lymph node metastases in non-primary tumor-bearing lobes (NTBL) are rarely reported. This study examined the risk factors of lobar lymph node metastasis in NTBL.

Methods

We retrospectively studied 301 patients with non-small-cell lung cancer (NSCLC) who underwent surgical pulmonary resection with systematic lymph node dissection plus extended lobar lymph node dissection of NTBL. Patients were classified into positive and negative NTBL groups. Unconditional logistic regression was used to identify the risk factors for lobar lymph node metastasis in NTBL.

Results

NTBL lobar lymph nodes were identified in 38 patients (12.6%). A higher proportion of adenocarcinomas occurred in the positive NTBL group compared to the negative NTBL group (73.7% vs. 46.4%, P = 0.01). Risk of NTBL lobar lymph node metastases was significantly elevated in the lower lobe of primary site compared to the upper lobe (OR = 2.61, 95% CI = 1.26–5.75, P = 0.01), and with adenocarcinomas compared to squamous cell carcinomas (OR = 2.75, 95% CI = 1.09–7.65, P = 0.04). No differences were observed when comparing left and right lobes. NTBL lobar lymph node metastasis was most often observed among patients with larger tumor size, N1/N2 nodal involvement, with lymph vascular invasion (LVI), and visceral pleural invasion (VPI).

Conclusion

NTBL lobar lymph node metastases occurred more often in patients with a primary NSCLC tumor in the lower lobe, with adenocarcinomas, larger tumor size, N1/N2 nodal involvement, LVI or VPI. Extended lymphadenectomy including NTBL nodes may be clinically advantageous when these risk factors are present.

Development of a nomogram for preoperative prediction of lymph node metastasis in non-small cell lung cancer: a SEER-based study

Background

Lymph node dissection is an important part of lung cancer surgery. Preoperational evaluation of lymph node metastases decides which dissection pattern should be chosen. The present study aimed to develop a nomogram to predict lymph node metastases on the basis of clinicopathological features of non-small cell lung cancer (NSCLC) patients.

Methods

A total of 35,138 patients diagnosed with NSCLC from 2010–2015 were selected from the Surveillance, Epidemiology, and End Results (SEER) database. Patients were randomly divided into training cohort and validation cohort. Possible risk factors were included and analyzed by logistic regression models. A nomogram was then constructed and validated.

Results

21.83% of all patients were confirmed with positive lymph node metastasis. Age at diagnosis, sex, stage, T status, tumor size, grade and laterality were identified as predicting factors for lymph node involvement. These variables were included to build the nomogram. The AUC of the model was 0.696 (95% CI, 0.617 to 0.775). The model was further validated in the validation set with AUC 0.693 (95% CI, 0.628 to 0.758). The model presented with good prediction accuracy in both training cohort and validation cohort.

Conclusions

We developed a convenient clinical prediction model for regional lymph node metastases in NSCLC patients. The nomogram will help physicians to determine which patients will receive the most benefit from lymph node dissection.

Can peritumoral radiomics increase the efficiency of the prediction for lymph node metastasis in clinical stage T1 lung adenocarcinoma on CT?

OBJECTIVES

To evaluate the efficiency of radiomics model on CT images of intratumoral and peritumoral lung parenchyma for preoperative prediction of lymph node (LN) metastasis in clinical stage T1 peripheral lung adenocarcinoma patients.

METHODS

Three hundred sixty-six peripheral lung adenocarcinoma patients with clinical stage T1 were evaluated using five CT scanners. For each patient, two volumes of interest (VOIs) on CT were defined as the gross tumor volume (GTV) and the peritumoral volume (PTV, 1.5 cm around the tumor). One thousand nine hundred forty-six radiomic features were obtained from each VOI, and then refined for reproducibility and redundancy. The refined features were investigated for usefulness in building radiomic signatures by mRMR feature ranking method and LASSO classifier. Multivariable logistic regression analysis was used to develop a radiomic nomogram incorporating the radiomic signature and clinical parameters. The prediction performance was evaluated on the validation cohort.

RESULTS

The radiomic signatures using the features of GTV and PTV showed a good ability in predicting LN metastasis with an AUC of 0.829 (95% CI, 0.745-0.913) and 0.825 (95% CI, 0.733-0.918), respectively. By incorporating the features of GTV and PTV, the AUC of radiomic signature increased to 0.843 (95% CI, 0.770-0.916). The AUC of radiomic nomogram was 0.869 (95% CI, 0.800-0.938).

CONCLUSIONS

Radiomic signatures of GTV and PTV both had a good prediction ability in the prediction of LN metastasis, and there is no significant difference of AUC between the two groups. The proposed nomogram can be conveniently used to facilitate the preoperative prediction of LN metastasis in T1 peripheral lung adenocarcinomas.

KEY POINTS

• Radiomics from peritumoral lung parenchyma increase the efficiency of the prediction for lymph node metastasis in clinical stage T1 lung adenocarcinoma on CT. • A radiomic nomogram was developed and validated to predict LN metastasis. • Different scan parameters on CT showed that radiomics signature had good predictive performance.