Abstract
Objective: To investigate risk factors for locoregional recurrence (LRR) of pathologic stage IIIA-N2 non-small cell lung cancer (pIIIA-N2 NSCLC) and construct a prediction model for risk score to determine a patient’s risk for LRR and guide the selection of postoperative radiotherapy (PORT). Methods: The clinical, pathologic, and biological data of 107 patients with pIIIA-N2 NSCLC treated at Fujian Provincial Hospital between May 2012 and December 2018 were analyzed retrospectively. None of the patients had positive surgical margins, and none received preoperative treatment or PORT. The Kaplan-Meier method was used for a univariate analysis of possible factors for locoregional recurrence-free survival (LRFS). The Cox regression model was used in a multivariate analysis to identify independent risk factors for LRFS, which were used to construct a prediction model for risk score. The concordance index was calculated to evaluate discrimination. Results: The median follow-up time was 31.2 months. During the follow-up, 69 (64.5%) patients had LRR and/or distant metastasis (DM). Among them, 46 (43%) patients had LRR (with or without DM), and 56 (52.3%) patients had DM (with or without LRR). The 1-year LRFS, distant metastasis-free survival, disease-free survival, and overall survival rates were 78.2%, 78%, 69.8%, and 90.2%, respectively; the 3-year rates were 50.6%, 41.2%, 31.2%, and 66.3%, respectively. Multivariate analysis showed that surgical approach (hazard ratio [HR], 0.348; 95% confidence interval [CI], 0.175-0.693; P = 0.003), metastatic N2 lymph node ratio (HR, 3.597; 95% CI, 1.832-7.062; P = 0.000), epidermal growth factor receptor status (HR, 3.666; 95% CI, 1.724-7.797; P = 0.001), and lymphocyte-to-monocyte ratio (HR, 2.364; 95% CI, 1.221-4.574; P = 0.011) were independent risk factors for LRFS. These independent risk factors were used to construct a prediction model for risk score and stratify patients into the low-risk group (risk score: 0-2), medium-risk group (risk score: 3-5), and high-risk group (risk score: 6-13). The 1-year LRFS rates of these groups were 91.9%, 85.3%, and 54.6%, respectively; the 3-year LRFS rates were 71.4%, 57.3%, and 13.6%, respectively. These between-group differences were significant (P = 0.000). The prediction model showed good discrimination (concordance index = 0.747, 95% CI, 0.678-0.816). Conclusion: Our prediction model for risk score based on characteristics of pIIIA-N2 NSCLC patients may help clinicians predict a patient’s risk for LRR. Further investigations of PORT with patients in different risk groups are warranted.
Keywords: Non-small cell lung cancer, pathologic stage IIIA-N2 disease, locoregional recurrence, risk factors, prediction model
Introduction
Lung cancer has the highest morbidity and mortality of malignant tumors worldwide [1]. Non-small cell lung cancer (NSCLC) accounts for approximately 85% of all lung cancers [2]. In accordance with the 2009 lung cancer staging of the International Association for the Study of Lung Cancer (IASLC), pathologic stage IIIA-N2 (pIIIA-N2) NSCLC is defined as primary NSCLC with subcarinal and/or ipsilateral mediastinal lymph node metastasis (including T1-3N2M0) that is diagnosed by pathologic examination of a surgical specimen in patients with no preoperative induction therapy [3]. pIIIA-N2 NSCLC is locally advanced NSCLC and encompasses a group of heterogeneous diseases with distinct clinical, pathologic, and biological characteristics as well as significant variation in treatment response and outcomes. The 5-year survival rate is 24.1% to 47.4% [4-10]. Surgery is the main treatment for pIIIA-N2 NSCLC, and postoperative locoregional recurrence (LRR) and/or distant metastasis (DM) are the main causes of treatment failure and adverse prognosis. Several randomized clinical trials and meta-analyses have shown that platinum-based adjuvant chemotherapy increases the survival rate of patients with pIIIA-N2 NSCLC [11-13]. However, the LRR rate is still as high as 40% to 50% even after surgery and adjuvant chemotherapy [6,14]. Therefore, postoperative radiotherapy (PORT) is often recommended to reduce LRR. However, researchers still debate its benefit on survival [15-19]. There are no prospective phase III study data on whether PORT improves survival. Some studies show that for locally advanced NSCLC, improved local control is related to longer overall survival (OS) [20,21], suggesting that reducing LRR may improve OS. These data indicate that in addition to better radiotherapy equipment and technology, LRR risk stratification of pIIIA-N2 NSCLC and proper selection of the patient population indicated for PORT will help reduce LRR, improve local control, and extend survival.
Some studies on the effective predictors of LRR risk in patients with pIIIA-N2 NSCLC have focused on clinical and pathologic factors, including age [22], smoking [23], pathologic type [24], tumor differentiation [22], microscopic margin status [25], pathologic T staging [26], clinical N status [9,23], number of mediastinal lymph node stations involved [9,22,24], the region of mediastinal lymph node involvement [8,26], skip metastasis [26-28], metastatic lymph node ratio (LNR) [22,23], extranodal extension [29,30], and number of N1 lymph nodes involved [25,26]. However, these studies reached different conclusions, so further research is needed on the predictive value of these factors. Previous studies have shown that the status of the tumor biomarker epidermal growth factor receptor (EGFR) gene [31,32]; preoperative systemic inflammation biomarkers such as the neutrophil-to-lymphocyte ratio (NLR) [33], platelet-to-lymphocyte ratio (PLR) [34], and lymphocyte-to-monocyte ratio (LMR) [35]; and preoperative prognostic nutritional index (PNI) [PNI = serum albumin (g/L) + 5 × lymphocyte count (/nL)] [36] are related to postoperative recurrence of NSCLC. However, no studies have been conducted to investigate the relationship between these biomarkers and LRR of pIIIA-N2 NSCLC.
In this study, we analyzed the relationship between clinical, pathologic, and biological factors and LRR and constructed a prediction model for risk score to help clinicians identify a patient’s risk for LRR and guide the selection of PORT.
Patients and methods
Patient selection
The clinical, pathologic, and biological data of NSCLC patients who underwent surgery at Fujian Provincial Hospital between May 2012 and December 2018 were screened retrospectively. Eligible patients were selected based on the inclusion and exclusion criteria. Inclusion criteria included: (1) undergoing lung resection + lymph node dissection; (2) negative margins; (3) NSCLC diagnosed based on postoperative pathologic examination according to the 2015 World Health Organization Classification of Lung Cancer [37]; (4) pT1-3N2M0, stage IIIA according to the IASLC tumor, node, metastasis (TNM) classification (Edition 7) [38]; and (5) Eastern Cooperative Oncology Group Performance Status score 0 to 1. Exclusion criteria included: (1) positive visual or microscopic margins; (2) small cell carcinoma or mixed non-small and small cell carcinoma based on postoperative pathologic examination; (3) preoperative anti-tumor therapy such as radiotherapy, chemotherapy, or PORT; (4) history of malignancy; (5) concurrent second primary tumor or second primary tumor during follow-up; (6) perioperative death; or (7) incomplete follow-up data. In the end, a total of 107 patients were included in this study. The study was approved by the hospital ethics committee, and patients provided written informed consent.
Before surgery, the patients underwent a series of exams, including hematological examination, enhanced chest computed tomography (CT), enhanced upper-abdomen CT or abdominal ultrasonography, enhanced brain CT or magnetic resonance imaging (MRI), whole-body bone scan, and bronchoscopy, as well as positron emission tomography (PET)-CT in some cases. We reviewed electronic medical records, imaging data, pathologic reports, and blood tests to collect data for this study. We referenced the IASLC lymph node map (2009) to map the N1 and N2 lymph nodes [39]. Specifically, the N1 lymph nodes include five groups of lymph nodes from stations 10 to 14, and the N2 lymph nodes include nine groups of lymph nodes from stations 1 to 9. The N2 lymph nodes cover the superior mediastinum, aortopulmonary window, subcarinal region, and inferior mediastinum. Regional N2 metastasis was defined as metastasis to the superior mediastinum or the aortopulmonary window of an upper-left-lobe tumor, metastasis to the superior mediastinum of an upper-right-lobe tumor, metastasis to the superior mediastinum or subcarinal region of a middle-right-lobe tumor, or metastasis to the subcarinal region or inferior mediastinum of a lower-left- or lower-right-lobe tumor. Non-regional N2 metastasis was defined as metastasis to the subcarinal region or inferior mediastinum of an upper-left- or upper-right-lobe tumor, metastasis to the inferior mediastinum of a middle-right-lobe tumor, metastasis to the superior mediastinum or the aortopulmonary window of a lower-left-lobe tumor, or metastasis to the superior mediastinum of a lower-right-lobe tumor. Clinical N1 (cN1) and N2 (cN2) were determined mainly based on imaging studies and criteria, including short diameter of lymph nodes ≥ 1 cm and lymph nodes with visibly high metabolism on PET-CT (maximum standardized uptake value > 2.5).
Treatments
All patients underwent lung resection and lymph node dissection by thoracotomy or video-assisted thoracoscopic surgery (VATS). A total of 90 patients underwent lobectomy, nine underwent bilobectomy, three underwent pneumonectomy, four underwent sleeve resection, and one underwent wedge resection. Moreover, 39 patients underwent systemic lymph node dissection, which included three stations of N1 lymph nodes and three stations of N2 lymph nodes (including station 7 lymph nodes), along with the surrounding adipose tissue. Among the other 68 patients, fewer than three stations of N2 lymph nodes were dissected in six patients, fewer than three stations of N1 lymph nodes were dissected in 61 patients. In the last patient, three stations of N2 lymph nodes were dissected, but station 7 lymph nodes were untouched, and fewer than three groups of N1 lymph nodes were dissected. After surgery, 81 patients underwent adjuvant chemotherapy for a median of 4 cycles (range 1-6 cycles) with a platinum-based regime combined with third-generation chemotherapy drugs. Moreover, 10 patients received targeted EGFR-tyrosine kinase inhibitors (TKIs) therapy (gefitinib [Iressa]: n = 9; erlotinib [Tarceva]: n = 1). Sixteen patients did not receive postoperative adjuvant therapy due to poor performance status or patient refusal.
Follow-up
A postoperative follow-up assessment was generally performed every 3 months during the first 2 years, every 6 months during years 3-5, and then every year after year 5. Follow-up procedures included physical examination, serum tumor markers, chest CT, and abdominal CT or ultrasonography. Moreover, patients with suspected brain and bone metastasis underwent brain CT or MRI and whole-body bone scan. Patients with no signs of brain or bone metastasis underwent brain CT or MRI and whole-body bone scan every year. The follow-up time (months) was defined as the time from surgery to LRR, DM, death, or last follow-up. The outcome measures were LRR, DM, and death. Data related to no recurrence, no metastasis, non-cancer-related death, and survival at the last follow-up were censored data. LRR was defined as tumor recurrence at stumps and/or regional lymph nodes, including hilar, mediastinal, and supraclavicular lymph nodes. Intrapulmonary metastasis in the affected lung was not considered LRR. DM was defined as non-regional tumor recurrence, including metastases to cervical lymph nodes, the contralateral lung, pleura, brain, bone, liver, or adrenal glands. Tumor recurrence and metastasis were diagnosed mainly based on imaging studies, and suspected recurrence and metastasis were confirmed with pathologic examination or imaging studies over time.
Statistical analysis
SPSS version 20 software (IBM Co., Armonk, NY, USA) was used for data analysis. Locoregional recurrence-free survival (LRFS) was defined as the time from surgery to the first LRR or the last follow-up. Distant metastasis-free survival (DMFS) was defined as the time from surgery to the first DM or the last follow-up. Disease-free survival (DFS) was defined as the time from surgery to the first recurrence, last follow-up, or all-cause death. OS was defined as the time from surgery to all-cause death or last follow-up. Descriptive statistics were used to summarize tumor biomarkers, preoperative systemic inflammation biomarkers, and other clinical and pathologic characteristics. The Kaplan-Meier method was used to analyze LRFS, DMFS, DFS, and OS and to plot survival curves. The optimal cutoff values of the number of lymph nodes dissected, the number of metastatic lymph nodes, metastatic LNR, pathologic tumor size, Ki67, NLR, PLR, LMR, and PNI were determined using the X-tile software [40]. The Kaplan-Meier method was used for univariate analysis of possible factors for LRFS, and the log-rank sum test was run to analyze the difference in LRFS. Significant variables identified with univariate analysis were incorporated into the Cox regression model for multivariate analysis to identify independent risk factors for LRFS. All tests were two-tailed, and P<0.05 was considered statistically significant. The multivariate Cox regression model was used to estimate the regression coefficient of each independent risk factor and calculate the additive risk score. The Harrell’s concordance index (C-index) was calculated to evaluate the discrimination ability of the prediction model.
Results
Clinical, pathologic, and biological characteristics
Among the 107 patients with pIIIA-N2 NSCLC, 59 (55.1%) were men and 48 (44.9%) were women (male:female ratio: 1.23:1). The median age of the patients was 61 years (range 29-80 years). Most patients had peripheral lung cancer (88, 82.2%). Before surgery, 46 patients (43%) had clinical node negativity (cN0), 11 (10.3%) had cN1, and 50 (46.7%) had cN2. Most patients underwent VATS (65, 60.7%), and 17 patients (15.9%) were converted to thoracotomy during operation due to interference from lymph nodes and/or extensive thoracic adhesions. Most patients underwent lobectomy (90, 84.1%), and one patient (0.9%) underwent wedge reception due to advanced age. The median total number of lymph nodes dissected, N2 lymph nodes dissected, and N1 lymph nodes dissected was 23, 15, and 6. The median total numbers of lymph node stations dissected, N2 lymph node stations dissected, and N1 lymph node stations dissected were 6, 4, and 2. The median total numbers of metastatic lymph nodes, metastatic N2 lymph nodes, and metastatic N1 lymph nodes were 4, 2, and 1. Most patients had adenocarcinoma (70, 65.4%), followed by squamous cell carcinoma (19, 17.8%). A total of 84 patients (78.5%) underwent EGFR gene testing; the results showed that 42 patients (39.3%) had one mutant EGFR and one wild type EGFR allele. EGFR status was unknown in the other 23 patients (21.5%). The median tumor size was 3.5 cm. Before surgery, the median concentrations of albumin, neutrophils, lymphocytes, monocytes, and platelets were 44 g/L, 4.2 × 109/L, 1.9 × 109/L, 0.41 × 109/L, and 244 × 109/L. After surgery, 81 patients (75.7%) received platinum-based double-drug chemotherapy, and 10 (9.3%) received targeted EGFR-TKIs therapy. The detailed clinical, pathologic, and biological characteristics are presented in Table 1.
Table 1.
Baseline characteristics of all enrolled patients
| Characteristic | No. of patients (n = 107) |
|---|---|
| Age (years), median (range) | 61 (29~80) |
| Gender, n (%) | |
| Male | 59 (55.1) |
| Female | 48 (44.9) |
| Smoking history, n (%) | |
| No | 74 (69.2) |
| Yes | 33 (30.8) |
| ECOG PS, n (%) | |
| 0 | 46 (43) |
| 1 | 61 (57) |
| Laterality, n (%) | |
| Left | 37 (34.6) |
| Right | 70 (65.4) |
| Location of primary tumor, n (%) | |
| Left upper lobe | 23 (21.5) |
| Left lower lobe | 14 (13.1) |
| Right upper lobe | 35 (32.7) |
| Right middle lobe | 13 (12.1) |
| Right lower lobe | 22 (20.6) |
| Tumor gross type, n (%) | |
| Central-type | 19 (17.8) |
| Peripheral-type | 88 (82.2) |
| N clinical stastus, n (%) | |
| cN0 | 46 (43.0) |
| cN1 | 11 (10.3) |
| cN2 | 50 (46.7) |
| Surgical approach, n (%) | |
| Thoracotomy | 25 (23.4) |
| VATS | 65 (60.7) |
| VATS conversion to Thoracotomy | 17 (15.9) |
| Extent of surgical resection, n (%) | |
| Wedge resection | 1 (0.9) |
| Lobectomy | 90 (84.1) |
| Bilobectomy | 9 (8.4) |
| Pneumonectomy | 3 (2.8) |
| Sleeve resection | 4 (3.7) |
| Adjuvant therapy, n (%) | |
| Not performed | 16 (15.0) |
| Platinum-based chemotherapy | 81 (75.7) |
| Targeted EGFR-TKIs therapy | 10 (9.3) |
| Dissection of LNs, n (%) | |
| Non-SLND | 68 (63.6) |
| SLND | 39 (36.4) |
| Total no. of stations dissected, median (range) | 6 (3~9) |
| No. of N2 stations dissected, median (range) | 4 (1~6) |
| No. of N1 stations dissected, median (range) | 2 (1~4) |
| Total no. of LNs dissected, median (range) | 23 (5~60) |
| No. of N2 LNs dissected, median (range) | 15 (2~56) |
| No. of N1 LNs dissected, median (range) | 6 (2~27) |
| Total no. of metastatic LNs, median (range) | 4 (1~35) |
| No. of metastatic N2 LNs, median (range) | 2 (1~28) |
| No. of metastatic N1 LNs, median (range) | 1 (0~11) |
| Total LNR (%), median (range) | 20 (2.2~89.7) |
| N2-LNR (%), median (range) | 17.4 (2.5~100) |
| N1-LNR (%), median (range) | 25 (0~100) |
| No. of metastatic N2 stations, n (%) | |
| Single | 39 (36.4) |
| Multiple | 68 (63.6) |
| No. of metastatic N2 regions, n (%) | |
| Single | 84 (78.5) |
| Multiple | 23 (21.5) |
| Distribution of Metastatic N2 regions, n(%) | |
| Regional | 82 (76.6) |
| Non-regional | 25 (23.4) |
| Subcarinal LNs metastasis, n (%) | |
| No | 61 (57.0) |
| Yes | 46 (43.0) |
| Skip N2 metastasis, n (%) | |
| No | 75 (70.1) |
| Yes | 32 (29.9) |
| Pathologic tumor size (cm), median (range) | 3.5 (0.7~15) |
| Pathologic T stage, n (%) | |
| pT1 | 24 (22.4) |
| pT2 | 74 (69.2) |
| pT3 | 9 (8.4) |
| Histologic subtype, n (%) | |
| Squamous cell carcinoma | 19 (17.8) |
| Adenocarcinoma | 70 (65.4) |
| Large cell carcinoma | 5 (4.7) |
| Adenosquamous carcinoma | 6 (5.6) |
| Others | 7 (6.5) |
| Visceral pleural invasion, n (%) | |
| No | 43 (40.2) |
| Yes | 64 (59.8) |
| Lymphovascular invasion, n (%) | |
| No | 81 (75.7) |
| Yes | 26 (24.3) |
| Neurological invasion, n (%) | |
| No | 100 (93.5) |
| Yes | 7 (6.5) |
| Tumor necrosis, n (%) | |
| No | 78 (72.9) |
| Yes | 29 (27.1) |
| Ki67, n (%) | |
| <50% | 65 (60.7) |
| ≥ 50% | 29 (27.1) |
| Unknown | 13 (12.1) |
| EGFR status, n (%) | |
| Mutation | 42 (39.3) |
| Exon18 G719X | 1 (0.9) |
| Exon19 del | 17 (15.9) |
| Exon20 ins | 2 (1.9) |
| Exon21 L858R | 21 (19.6) |
| Exon20 T790M and Exon21 L858R | 1 (0.9) |
| Wild-type | 42 (39.3) |
| Unknown | 23 (21.5) |
| Blood cell count/Biochemistry | |
| Albumin (g/L), median (range) | 44 (34~50.5) |
| Neutrophil count (10^9/L), median (range) | 4.2 (1.7~10.7) |
| Lymphocyte count (10^9/L), median (range) | 1.9 (0.7~7.1) |
| Monocyte count (10^9/L), median (range) | 0.41 (0.18~1.15) |
| Platelet count (10^9/L), median (range) | 244 (128~450) |
| Nutrition/inflammation index | |
| NLR, median (range) | 2.09 (0.71~8.82) |
| PLR, median (range) | 128.82 (33.66~308.57) |
| LMR, median (range) | 4.4 (1.63~12.38) |
| PNI, median (range) | 53.5 (38.5~81.5) |
Abbreviations: ECOG: eastern cooperative oncology group, PS: performance status, VATS: video-assisted thoracoscopic surgery, EGFR: epidermal growth factor receptor, TKIs: tyrosine kinase inhibitors, SLND: systemic lymph node dissection, LNs: lymph nodes, LNR: lymph node ratio, NLR: neutrophil-to-lymphocyte ratio, PLR: platelet-to-lymphocyte ratio, LMR: lymphocyte-to-monocyte ratio, PNI: prognostic nutritional index.
Patterns of first recurrence and the distribution of recurrence sites
The median follow-up time was 31.2 months. During follow-up, 69 patients (64.5%) had LRR and/or DM, of whom 13 patients (18.8%) had only LRR, 23 (33.3%) had only DM, and 33 (47.8%) had both LRR and DM. A total of 46 patients (43%) had LRR (with or without DM), which occurred within 1 year of surgery in 22 patients (47.8%) and within 3 years of surgery in 41 patients (89.1%). Mediastinal lymph nodes were the most common recurrence site (39, 84.8%), followed by hilar lymph nodes (12, 26.1%), supraclavicular lymph nodes (11, 23.9%), and stumps (11, 23.9%). A total of 56 patients (52.3%) had DM (with or without LRR), which occurred within 1 year of surgery in 22 patients (39.3%) and within 3 years of surgery in 50 patients (89.3%). The most common metastatic sites were lung (23, 41.1%) and brain (16, 28.6%), followed by bone (9, 16.1%), pleura (8, 14.3%), adrenal gland (7, 12.5%), liver (6, 10.7%), non-regional lymph nodes (2, 3.6%), kidney (1, 1.8%), and spleen (1, 1.8%) (Table 2).
Table 2.
Patterns of First recurrence and Distribution of Recurrence sites
| Item | No. of patients |
|---|---|
| Patterns of First recurrence, n (%) | |
| Locoregional recurrence alone | 13 (18.8) |
| Distant metastasis alone | 23 (33.3) |
| Both | 33 (47.8) |
| Sites of Locoregional recurrence, n (%) | |
| Mediastinal LNs | 39 (84.8) |
| Hilar LNs | 12 (26.1) |
| Supraclavicular LNs | 11 (23.9) |
| Stump | 11 (23.9) |
| Sites of Distant metastasis, n (%) | |
| Lung | 23 (41.1) |
| Brain | 16 (28.6) |
| Bone | 9 (16.1) |
| Pleura | 8 (14.3) |
| Adrenal | 7 (12.5) |
| Liver | 6 (10.7) |
| Non-regional LNs | 2 (3.6) |
| Kidney | 1 (1.8) |
| Spleen | 1 (1.8) |
Abbreviations: LNs: lymph nodes.
Survival analysis
The patients were followed up through July 10, 2019. The median LRFS, DMFS, DFS, and OS were 17, 19.6, 16.3, and 31.2 months, respectively. The 1-year LRFS, DMFS, DFS, and OS rates were 78.2%, 78%, 69.8%, and 90.2%, respectively; the 3-year rates were 50.6%, 41.2%, 31.2%, and 66.3%, respectively (Figure 1).
Figure 1.
Kaplan-Meier curve for LRFS, DMFS, DFS, OS of pIIIA-N2 NSCLC patients.
Univariate and multivariate analysis of the risk factors for LRFS
Univariate and multivariate analysis were conducted to identify LRFS-related clinical, pathologic, and biological factors. The optimal cut-off values of the total number of lymph nodes dissected, the number of N2 lymph nodes dissected, the number of N1 lymph nodes dissected, the total number of metastatic lymph nodes, the number of metastatic N2 lymph nodes, the number of metastatic N1 lymph nodes, total LNR, N2-LNR, N1-LNR, pathologic tumor size, Ki67, NLR, PLR, LMR and PNI were determined using the X-tile. The results were 24, 16, 7, 5, 3, 2, 36.4%, 38.9%, 75%, 5 cm, 50%, 2.39, 252, 4.69 and 43.5, respectively (Figure 2). Univariate analysis showed that surgical approach (χ2 = 14.983, P = 0.001; Figure 3A), extent of surgical resection (χ2 = 10.207, P = 0.037), pathologic tumor size (χ2 = 4.627, P = 0.031), tumor necrosis (χ2 = 6.979, P = 0.008), the total number of metastatic lymph nodes (χ2 = 9.977, P = 0.002), total LNR (χ2 = 6.051, P = 0.014), N2-LNR (χ2 = 6.544, P = 0.011; Figure 3B), the number of metastatic N1 lymph nodes (χ2 = 3.923, P = 0.048), cN2 (χ2 = 13.702, P<0.001), cN1 (χ2 = 6.098, P = 0.014), EGFR status (χ2 = 11.328, P = 0.003; Figure 3C), NLR (χ2 = 6.194, P = 0.013), and LMR (χ2 = 7.376, P = 0.007; Figure 3D) were risk factors for LRFS (Table 3). Significant factors identified by univariate analysis were incorporated into the Cox regression model for multivariate analysis. The results showed that surgical approach, N2-LNR, EGFR status, and LMR were independent risk factors for LRFS. VATS (hazard ratio [HR], 0.348; 95% confidence interval [CI], 0.175-0.693; P = 0.003) was associated with a higher LRFS rate, while N2-LNR ≥ 38.9% (HR 3.597; 95% CI, 1.832-7.062; P = 0.000), wild-type EGFR (HR 3.666; 95% CI, 1.724-7.797; P = 0.001), and LMR<4.69 (HR 2.364; 95% CI, 1.221-4.574; P = 0.011) were associated with a lower LRFS rate (Table 4).
Figure 2.
X-tile analyses of LRFS were performed using patients’ data to determine the optimal cut-off values for the number of lymph nodes dissected, the number of metastatic lymph nodes, LNR, pathologic tumor size, Ki67, NLR, PLR, LMR and PNI. The optimal cut-off values highlighted by the black circles in left panels are shown in histograms of the entire cohort (middle panels), and Kaplan-Meier plots are displayed in right panels. The optimal cut-off values for the total number of lymph nodes dissected, the number of N2 lymph nodes dissected, the number of N1 lymph nodes dissected, the total number of metastatic lymph nodes, the number of metastatic N2 lymph nodes, the number of metastatic N1 lymph nodes, total LNR, N2-LNR, N1-LNR, pathologic tumor size, Ki67, NLR, PLR, LMR and PNI were 24, 16, 7, 5, 3, 2, 36.4%, 38.9%, 75%, 5 cm, 50%, 2.39, 2.52, 4.69 and 43.5, respectively.
Figure 3.
Kaplan-Meier curve for LRFS of pIIIA-N2 NSCLC patients stratified by surgical approach, N2-LNR, EGFR status, and LMR. A. Kaplan-Meier curve for LRFS stratified by surgical approach (P = 0.001). B. Kaplan-Meier curve for LRFS stratified by N2-LNR (P = 0.011). C. Kaplan-Meier curve for LRFS of pIIIA-N2 NSCLC patients stratified by EGFR status (P = 0.003). D. Kaplan-Meier curve for LRFS of pIIIA-N2 NSCLC patients stratified by LMR (P = 0.007).
Table 3.
Risk factors: univariate analysis
| Characteristic | No. of patients | LRFS (%) | |||
|---|---|---|---|---|---|
|
| |||||
| 1-year | 3-year | χ2 | P-value | ||
| Age (years) | 1.649 | 0.199 | |||
| <65 | 66 | 72 | 45.1 | ||
| ≥ 65 | 41 | 84.7 | 57.4 | ||
| Gender | 2.804 | 0.094 | |||
| Male | 59 | 66.2 | 46.1 | ||
| Female | 48 | 89.7 | 56.9 | ||
| Smoking history | 2.918 | 0.088 | |||
| No | 74 | 88.9 | 56.5 | ||
| Yes | 33 | 61.5 | NA | ||
| ECOG PS | 5.416 | 0.200 | |||
| 0 | 46 | 85.7 | 61.8 | ||
| 1 | 61 | 71.5 | 40.6 | ||
| Laterality | 0.804 | 0.370 | |||
| Left | 37 | 80.8 | 53.5 | ||
| Right | 70 | 75.8 | 46.7 | ||
| Location of primary tumor | 0.098 | 0.952 | |||
| Upper lobe | 58 | 78 | 48.2 | ||
| Middle lobe | 13 | 66.5 | 23.4 | ||
| Lower lobe | 36 | 77.6 | 48.2 | ||
| Tumor gross type | 1.891 | 0.169 | |||
| Central-type | 19 | 56.4 | 35.9 | ||
| Peripheral-type | 88 | 81.2 | 51.9 | ||
| Surgical approach | 14.893 | 0.001 | |||
| Thoracotomy | 25 | 55.6 | 17.4 | ||
| VATS | 65 | 86.2 | 64.4 | ||
| VATS conversion to Thoracotomy | 17 | 67.2 | 27.6 | ||
| Extent of surgical resection | 10.207 | 0.037 | |||
| Lobectomy | 90 | 79.7 | 55.9 | ||
| Wedge resection | 1 | NA | NA | ||
| Bilobectomy | 9 | 55.9 | NA | ||
| Pneumonectomy | 3 | 45.4 | NA | ||
| Sleeve resection | 4 | 33.3 | NA | ||
| Adjuvant therapy | 5.288 | 0.071 | |||
| Not performed | 16 | 58.5 | 29 | ||
| Platinum-based chemotherapy | 81 | 76.4 | 49.1 | ||
| EGFR-TKIs targeted therapy | 10 | NA | 83.3 | ||
| Dissection of LNs | 0.321 | 0.571 | |||
| Non-sLND | 68 | 78.5 | 53.9 | ||
| sLND | 39 | 73.4 | NA | ||
| Total no. of LNs dissected | 3.747 | 0.053 | |||
| <24 | 60 | 78.5 | 58.6 | ||
| ≥ 24 | 47 | 74 | 34.9 | ||
| Total no. of metastatic LNs | 9.977 | 0.002 | |||
| <5 | 60 | 84.3 | 62.7 | ||
| ≥ 5 | 47 | 68.1 | 25.9 | ||
| Total LNR | 6.051 | 0.014 | |||
| <36.4% | 80 | 80.1 | 55.6 | ||
| ≥ 36.4% | 27 | 69.1 | 18.2 | ||
| No. of N2 LNs dissected | 0.509 | 0.476 | |||
| <16 | 55 | 72.8 | 55 | ||
| ≥ 16 | 52 | 80.8 | 45.5 | ||
| No. of metastatic N2 LNs | 3.348 | 0.067 | |||
| <3 | 57 | 78.2 | 56.4 | ||
| ≥ 3 | 50 | 76.5 | 36.5 | ||
| N2-LNR | 6.544 | 0.011 | |||
| <38.9% | 79 | 82.5 | 55.7 | ||
| ≥ 38.9% | 28 | 62.1 | 26.8 | ||
| No. of N1 LNs dissected | 0.042 | 0.837 | |||
| <7 | 55 | 81 | 52.3 | ||
| ≥ 7 | 52 | 73.5 | 48.6 | ||
| No. of metastatic N1 LNs | 3.923 | 0.048 | |||
| <2 | 59 | 82.3 | 61.3 | ||
| ≥ 2 | 48 | 71.6 | 35 | ||
| N1-LNR | 1.813 | 0.178 | |||
| <75% | 95 | 79.7 | 51.8 | ||
| ≥ 75% | 12 | 61.5 | 28.8 | ||
| No. of metastatic N2 stations | 0.047 | 0.829 | |||
| Single | 39 | 77 | 42.6 | ||
| Multiple | 68 | 76.9 | 51.7 | ||
| No. of metastatic N2 regions | 1.192 | 0.275 | |||
| Single | 84 | 78.4 | 53.5 | ||
| Multiple | 23 | 74 | NA | ||
| Distribution of Metastatic N2 regions | 1.207 | 0.272 | |||
| Regional | 82 | 77.9 | 53.8 | ||
| Non-regional | 25 | 75.8 | NA | ||
| Subcarinal LNs metastasis | 0.078 | 0.780 | |||
| No | 61 | 80.5 | 50.1 | ||
| Yes | 46 | 74.2 | 44 | ||
| Skip N2 metastasis | 1.018 | 0.313 | |||
| No | 75 | 75 | 42.6 | ||
| Yes | 32 | 80.3 | 60.5 | ||
| Clinical N2 | 13.702 | <0.001 | |||
| No | 57 | 88.9 | 69.5 | ||
| Yes | 50 | 63.9 | 30.2 | ||
| Pathologic tumor size (cm) | 4.627 | 0.031 | |||
| <5 | 79 | 80.9 | 59.6 | ||
| ≥ 5 | 28 | 63.3 | 29.7 | ||
| Pathologic T stage | 3.676 | 0.159 | |||
| 1 | 24 | 88.3 | NA | ||
| 2 | 74 | 74.8 | 52.1 | ||
| 3 | 9 | 55.5 | 20 | ||
| Histologic subtype | 0.342 | 0.558 | |||
| Non-squamous cell carcinoma | 88 | 77.6 | 51.7 | ||
| Squamous cell carcinoma | 19 | 71.8 | 41.4 | ||
| Visceral pleural invasion | 0.105 | 0.746 | |||
| No | 43 | 80.5 | 48 | ||
| Yes | 64 | 74.1 | 52.1 | ||
| Tumor necrosis | 6.979 | 0.008 | |||
| No | 78 | 83 | 58.2 | ||
| Yes | 29 | 59.6 | 25.6 | ||
| Lymphovascular invasion | 0.472 | 0.492 | |||
| No | 81 | 81.7 | 50.8 | ||
| Yes | 26 | 63 | NA | ||
| Neurological invasion | 1.117 | 0.290 | |||
| No | 100 | 77 | 49.4 | ||
| Yes | 7 | NA | NA | ||
| Ki67 | 1.722 | 0.423 | |||
| <50% | 65 | 81.8 | 49.5 | ||
| ≥ 50% | 29 | 64.1 | 42.3 | ||
| Unknown | 13 | 75.8 | NA | ||
| EGFR status | 11.328 | 0.003 | |||
| Mutation | 42 | 90.5 | 62.9 | ||
| Wild-type | 42 | 58.5 | 30.9 | ||
| Unknown | 23 | 80.7 | 53 | ||
| NLR | 6.194 | 0.013 | |||
| <2.39 | 63 | 79.2 | 62.8 | ||
| ≥ 2.39 | 44 | 72.9 | NA | ||
| PLR | 1.275 | 0.259 | |||
| <252 | 103 | 78.4 | 51.3 | ||
| ≥ 252 | 4 | 48.2 | NA | ||
| LMR | 7.376 | 0.007 | |||
| ≥ 4.69 | 46 | 84.8 | 63.9 | ||
| <4.69 | 61 | 69.1 | 35.3 | ||
| PNI | 1.404 | 0.236 | |||
| <43.5 | 4 | 50 | NA | ||
| ≥ 43.5 | 103 | 77.2 | 52 | ||
Abbreviations: ECOG: eastern cooperative oncology group, PS: performance status, VATS: video-assisted thoracoscopic surgery, EGFR: epidermal growth factor receptor, TKIs: tyrosine kinase inhibitors, SLND: systemic lymph node dissection, LNs: lymph nodes, LNR: lymph node ratio, NLR: neutrophil-to-lymphocyte ratio, PLR: platelet-to-lymphocyte ratio, LMR: lymphocyte-to-monocyte ratio, PNI: prognostic nutritional index, NA: not available.
Table 4.
Risk factors: multivariate analysis
| Characteristic | Beta | SE | Wald | P-value | HR (95% CI) |
|---|---|---|---|---|---|
| Surgical approach | |||||
| Thoracotomy | 1.000 | ||||
| VATS | -1.056 | 0.351 | 9.033 | 0.003 | 0.348 (0.175-0.693) |
| VATS conversion to Thoracotomy | -0.654 | 0.450 | 2.109 | 0.146 | 0.520 (0.215-1.257) |
| N2-LNR | |||||
| <38.9% | 1.000 | ||||
| ≥ 38.9% | 1.280 | 0.344 | 13.837 | 0.000 | 3.597 (1.832-7.062) |
| EGFR status | |||||
| Mutation | 1.000 | ||||
| Wild-type | 1.299 | 0.385 | 11.387 | 0.001 | 3.666 (1.724-7.797) |
| Unknown | 0.211 | 0.443 | 0.227 | 0.634 | 1.235 (0.518-2.941) |
| LMR | |||||
| ≥ 4.69 | 1.000 | ||||
| <4.69 | 0.860 | 0.337 | 6.521 | 0.011 | 2.364 (1.221-4.574) |
Abbreviations: VATS: video-assisted thoracoscopic surgery, LNR: lymph node ratio, EGFR: epidermal growth factor receptor, LMR: lymphocyte-to-monocyte ratio, HR: hazard ratio, CI: confidence interval.
Construction of a prediction model for LRR risk score in patients with pIIIA-N2 NSCLC
We incorporated the independent risk factors identified by multivariate analysis into a prediction model for LRR risk score. The additive risk score was calculated based on the regression coefficient of each independent risk factor (Table 5). We used X-tile to stratify the 107 patients into the low-risk group (risk score: 0-2; 37, 34.6%), medium-risk group (risk score: 3-5; 28, 26.2%), and high-risk group (risk score: 6-13; 42, 39.2%). The Kaplan-Meier method was used to plot LRFS curves, which showed that a lower risk level was associated with longer LRFS. In the low-, medium-, and high-risk groups, the 1-year LRFS rates were 91.9%, 85.3%, and 54.6%, respectively; and the 3-year LRFS rates were 71.4%, 57.3%, and 13.6%, respectively. These between-group differences were significant (P = 0.000) (Figure 4; Table 6). By internal bootstrap validation, the C-index was 0.747 (95% CI, 0.678-0.816), indicating good discrimination of the prediction model.
Table 5.
Risk factor calculation
| Characteristic | P-value | HR (95% CI) | Score |
|---|---|---|---|
| Surgical approach | |||
| Thoracotomy | 1.000 | 3 | |
| VATS | 0.003 | 0.348 (0.175-0.693) | 0 |
| VATS conversion to Thoracotomy | 0.146 | 0.520 (0.215-1.257) | 0 |
| N2-LNR | |||
| <38.9% | 1.000 | 0 | |
| ≥ 38.9% | 0.000 | 3.597 (1.832-7.062) | 4 |
| EGFR status | |||
| Mutation | 1.000 | 0 | |
| Wild-type | 0.001 | 3.666 (1.724-7.797) | 4 |
| Unknown | 0.634 | 1.235 (0.518-2.941) | 0 |
| LMR | |||
| ≥ 4.69 | 1.000 | 0 | |
| <4.69 | 0.011 | 2.364 (1.221-4.574) | 2 |
Abbreviations: VATS: video-assisted thoracoscopic surgery, LNR: lymph node ratio, EGFR: epidermal growth factor receptor, LMR: lymphocyte-to-monocyte ratio, HR: hazard ratio, CI: confidence interval.
Figure 4.
Kaplan-Meier curve for LRFS of pIIIA-N2 NSCLC patients with different risk groups (P = 0.000).
Table 6.
Risk group stratification and comparison of LRFS rate according to risk classification
| Risk group | Risk score | No. of patients | 1-year LRFS | 3-year LRFS | Reference | P-value |
|---|---|---|---|---|---|---|
| Low-risk group | 0~2 | 37 | 91.9% | 71.4% | Vs. high risk | 0.000 |
| Medium-risk group | 3~5 | 28 | 85.3% | 57.3% | Vs. low risk | 0.149 |
| High-risk group | 6~13 | 42 | 54.6% | 13.6% | Vs. medium risk | 0.002 |
Discussion
In this retrospective study, we analyzed the clinical, pathologic, and biological data of 107 patients with pIIIA-N2 NSCLC. Our pertinent findings are summarized as follows. First, the LRR rate was 43%, which was similar to previous literature reports (6, 14). Nearly 50% (22/46) of LRR cases occurred within 1 year of surgery. Second, the 1-year LRFS, DMFS, DFS, and OS rates were 78.2%, 78%, 69.8%, and 90.2%, respectively, and the 3-year rates were 50.6%, 41.2%, 31.2%, and 66.3%, respectively. Surgical approach, N2-LNR, EGFR status, and LMR were shown to be independent risk factors for LRFS. Third, we constructed a prediction model for risk score based on the four independent risk factors to predict a patient’s risk for LRR.
VATS has been used in clinical practice since the 1990s. In 2006, the National Comprehensive Cancer Network guidelines started to recommend VATS as a practical surgical approach for early-stage NSCLC, thereby affirming the value of VATS. With ongoing improvements to medical devices and equipment and as surgeons gain more experience and skill with VATS, VATS is increasingly used to treat locally advanced NSCLC. Several studies have shown that VATS is safe and practical for locally advanced NSCLC [41-45], with similar DFS and OS performance as for thoracotomy [43-45]. However, few studies have been conducted to investigate the role of surgical approach in postoperative LRFS in patients with locally advanced NSCLC. This study showed that surgical approach was an independent risk factor for LRFS. The 1- and 3-year LRFS rates were higher in the VATS group than in the thoracotomy group (86.2% vs. 55.6%, 64.4% vs. 17.4%; P = 0.001). Tumor recurrence was closely related to the resection range. Both VATS and thoracotomy achieved R0 resection, with no significant difference in the range or extent of lymph node dissection. VATS was associated with lower LRR risk, which was probably related to EGFR status and LMR, because a higher proportion of patients in the VATS group (relative to the thoracotomy group) had EGFR mutation and a high LMR, both favorable prognostic factors for LRR (Table 7).
Table 7.
N2-LNR, EGFR status, LMR and lymph node dissection conditions of the two groups
| Characteristic | Thoracotomy Group | VATS Group | χ2 | P-value |
|---|---|---|---|---|
| N2-LNR, n (%) | 1.336 | 0.248 | ||
| ≥ 38.9% | 4 (16) | 18 (27.7) | ||
| <38.9% | 21 (84) | 47 (72.3) | ||
| EGFR status, n (%) | 12.687 | <0.001 | ||
| Wild-type | 13 (52) | 18 (27.7) | ||
| Mutation | 2 (8) | 34 (52.3) | ||
| LMR, n (%) | 5.769 | 0.016 | ||
| <4.69 | 20 (80) | 34 (52.3) | ||
| ≥ 4.69 | 5 (20) | 31 (47.7) | ||
| Total no. of stations dissected, median (range) | 6 (3~9) | 6 (3~9) | ||
| Total no. of LNs dissected, median (range) | 23 (10~60) | 23 (5~40) | ||
| No. of N2 stations dissected, median (range) | 4 (1~6) | 4 (2~6) | ||
| No. of N2 LNs dissected, median (range) | 15 (6~56) | 15 (2~30) | ||
| No. of N1 stations dissected, median (range) | 2 (1~4) | 2 (1~3) | ||
| No. of N1 LNs dissected, median (range) | 6 (2~27) | 6 (2~14) |
Abbreviations: LNR: lymph node ratio, EGFR: epidermal growth factor receptor, LMR: lymphocyte-to-monocyte ratio.
While the number of metastatic lymph nodes is considered an important predictor of survival and prognosis [6,46-49], it is associated with the number of lymph nodes examined in the surgical specimen, the extent of lymph node dissection during surgery, and pathologic sectioning. These problems can be avoided by using LNR, which makes LNR a better prognostic predictor. LNR has been used to predict the OS of patients with pIIIA-N2 NSCLC [50-52], but few researchers have looked at the role of LNR in LRFS. LNR includes total LNR, N2-LNR, and N1-LNR. No unified cut-off value has been established for LNR, and different values have been used in different studies. Feng et al. [23] used 20% as the cut-off value for LNR (≤ 20% vs. > 20%), but they did not specify the type of LNR investigated. Wei et al. [22] advocated an N2-LNR cut-off value of 1/3 (≤ 1/3 vs. > 1/3). Both studies showed that LNR was an independent risk factor for LRFS and that high LNR was an adverse prognostic factor, but neither study described the method used to determine the cut-off value. In this study, we used X-tile to determine the cut-off value of N2-LNR (38.9%) with the minimum P value in the log-rank sum test. Survival analysis showed that the 1- and 3-year LRFS rates were significantly lower in the N2-LNR ≥ 38.9% group than in the N2-LNR<38.9% group (62.1% vs. 82.5%, 26.8% vs. 55.7%; P = 0.011). N2-LNR was independently correlated with LRFS in patients with pIIIA-N2 NSCLC (HR = 3.597, P = 0.000), while the number of metastatic N2 nodes and the number of N2 nodes dissected were not correlated with LRFS, suggesting that LNR is a better predictor of LRR risk in patients with pIIIA-N2 NSCLC. These cut-off values of LNR are clinically relevant, although large, multicenter, and prospective studies are needed to validate the results. Further research is also needed to identify the most clinically relevant LNR.
EGFR status is an excellent predictor of patient prognosis and response to EGFR-TKI therapy in patients with unresectable advanced NSCLC, and EGFR mutation is related to a better treatment response and prognosis [53-56]. However, researchers are still debating the extent to which EGFR status predicts postoperative recurrence in NSCLC patients. Takamochi et al. analyzed the data of 939 patients with lung adenocarcinoma and found that the RFS rate was significantly higher in patients with EGFR mutation than in patients with wild-type EGFR [31]. A multicenter retrospective analysis of 1155 patients with pN0-1 lung adenocarcinoma showed that the RFS rate was significantly lower in patients with EGFR mutation than in patients with wild-type EGFR [32]. A multicenter matched cohort study showed that EGFR status was unrelated to postoperative RFS in NSCLC patients [57]. A subsequent meta-analysis [58] and the study by Zhu et al. [48] reached similar conclusions. This is the first study to investigate the role of EGFR status in LRFS in patients with pIIIA-N2 NSCLC. We analyzed the predictive value of EGFR status for LRR in patients with pIIIA-N2 NSCLC. The results showed that 1- and 3-year LRFS rates were lower in patients with wild-type EGFR than in patients with EGFR mutation (58.5% vs. 90.5%, 30.9% vs. 62.9%; P = 0.003) and that EGFR status was an independent risk factor for LRFS (HR = 3.666, P = 0.001), suggesting that the risk of postoperative LRR was higher in patients with wild-type EGFR than in patients with EGFR mutation.
Inflammation is closely related to tumor growth, development, invasion, and metastasis [59]. As a peripheral blood indicator of systemic inflammation status, LMR is a proven prognostic predictor for many malignancies, including lung cancer [60]. For lung cancer, most studies have focused on the relationship between LMR and OS, and few investigated the relationship between LMR and postoperative recurrence in NSCLC patients [61,62]. LMR is related to postoperative occurrence in NSCLC patients, and a low LMR is an adverse prognostic factor [35]; however, the role of LMR in LRR in patients with pIIIA-N2 NSCLC is unknown. The current study was first to investigate the clinical value of preoperative LMR in predicting LRR in patients with pIIIA-N2 NS-CLC. We used X-tile to determine the optimal cut-off value of LMR (4.69) with the minimum P value from the log-rank sum test for LRFS analysis and found that the 1- and 3-year LRFS rates were significantly lower in the low-LMR group (LMR<4.69) than in the high-LMR group (LMR ≥ 4.69) (69.1% vs. 84.8%, 35.3% vs. 63.9%; P = 0.007) and that LMR was an independent risk factor for LRFS (HR = 2.364, P = 0.011), suggesting that a low LMR was associated with high LRR risk. LMR may be used as a biomarker to predict LRR in patients with pIIIA-N2 NSCLC. Moreover, LMR can be measured with blood samples and is cost-effective. Nevertheless, data on the predictive value of LMR for LRR in patients with pIIIA-N2 NSCLC are still limited, and large, multicenter, prospective studies are needed to further validate the clinical value and cut-off value of LMR.
A prediction model plays an important role in guiding individualized treatment. Two previous studies [25,63] have constructed prediction models based on relevant clinical and pathologic factors to guide the selection of PORT in patients with pIIIA-N2 NSCLC. However, none of the models incorporate biological indicators, even though test samples for these biomarkers are easy to collect in clinical practice. In this study, we constructed a new prediction model that may be more accurate and useful than previous models by incorporating relevant clinical, pathologic, and biological factors. Its C-index is 0.747 (95% CI, 0.678-0.816), indicating good discrimination of the new prediction model. We categorize risk into low-, medium-, and high-risk groups. If the patient’s estimated risk for LRR is low, the clinicians may select regular follow-up, whereas high-risk estimates may support being actively recommended PORT, because high-risk patients may benefit most from PORT. For medium-risk estimates, it may be necessary to weigh the advantages and disadvantages and consider the economics, physical condition and treatment willingness of patients before making the PORT decision. However, prospective studies are needed to investigate PORT in these patients.
As far as we know, this is the first study to construct a prediction model for risk score including clinical, pathologic, and biological factors in patients with pIIIA-N2 NSCLC. However, our study had some limitations. First, it was a single-center, retrospective study, thus the sample size was small and it may had selection bias. Second, the median follow-up time was 31.2 months, with only short- to intermediate-term survival data. Studies with a longer follow-up time are needed to investigate long-term survival. Third, our prediction model was based on the results of a single-center population-based study. We did only internal verification of the prediction model. However, there were certain difficulties in collecting case data from other centers, so no external validation was done. In the future, we will collect data from other centers to further validate our model.
Conclusion
The surgical approach (VATS vs. thoracotomy), N2-LNR (≥ 38.9% vs. <38.9%), EGFR status (wild-type vs. mutation), and LMR (<4.69 vs. ≥ 4.69) are significantly related to LRR in patients with pIIIA-N2 NSCLC. The prediction model for risk score based on the four independent risk factors may help identify a patient’s risk for LRR and play an important role in guiding individualized treatment. Further research is needed to validate the clinical value of this model to further improve it and benefit more patients.
Acknowledgements
This work was supported by the Leading Project of Fujian Science and Technology Department (Grant No. 2019Y0055).
Disclosure of conflict of interest
None.
References
- 1.Bray F, Ferlay J, Soerjomataram I, Siegel RL, Torre LA, Jemal A. Global cancer statistics 2018: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries. CA Cancer J Clin. 2018;68:394–424. doi: 10.3322/caac.21492. [DOI] [PubMed] [Google Scholar]
- 2.Travis WD, Brambilla E, Riely GJ. New pathologic classification of lung cancer: relevance for clinical practice and clinical trials. J. Clin. Oncol. 2013;31:992–1001. doi: 10.1200/JCO.2012.46.9270. [DOI] [PubMed] [Google Scholar]
- 3.Detterbeck FC, Boffa DJ, Tanoue LT. The new lung cancer staging system. Chest. 2009;136:260–271. doi: 10.1378/chest.08-0978. [DOI] [PubMed] [Google Scholar]
- 4.Iwasaki A, Shirakusa T, Miyoshi T, Hamada T, Enatsu S, Maekawa S, Hiratsuka M. Prognostic significance of subcarinal station in non-small cell lung cancer with T1-3 N2 disease. Thorac Cardiovasc Surg. 2006;54:42–46. doi: 10.1055/s-2005-865828. [DOI] [PubMed] [Google Scholar]
- 5.Dai H, Hui Z, Ji W, Liang J, Lu J, Ou G, Zhou Z, Feng Q, Xiao Z, Chen D, Zhang H, Yin W, He J, Wang L. Postoperative radiotherapy for resected pathological stage IIIA-N2 non-small cell lung cancer: a retrospective study of 221 cases from a single institution. Oncologist. 2011;16:641–650. doi: 10.1634/theoncologist.2010-0343. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 6.Yoo C, Yoon S, Lee DH, Park SI, Kim DK, Kim YH, Kim HR, Choi SH, Kim WS, Choi CM, Jang SJ, Song SY, Kim SS, Choi EK, Lee JC, Suh C, Lee JS, Kim SW. Prognostic significance of the number of metastatic pN2 lymph nodes in stage iiia-n2 non-small-cell lung cancer after curative resection. Clin Lung Cancer. 2015;16:e203–212. doi: 10.1016/j.cllc.2015.04.004. [DOI] [PubMed] [Google Scholar]
- 7.Nakagiri T, Sawabata N, Funaki S, Inoue M, Kadota Y, Shintani Y, Okumura M. Validation of pN2 sub-classifications in patients with pathological stage IIIA N2 non-small cell lung cancer. Interact Cardiovasc Thorac Surg. 2011;12:733–738. doi: 10.1510/icvts.2010.249896. [DOI] [PubMed] [Google Scholar]
- 8.Kim DW, Yun JS, Song SY, Na KJ. The prognosis according to patterns of mediastinal International Trialist Association (ANITA) randomized trial. Int J Radiat Oncol Biol Phys. 2008;72:695–701. doi: 10.1016/j.ijrobp.2008.01.044. [DOI] [PubMed] [Google Scholar]
- 9.Ichinose Y, Kato H, Koike T, Tsuchiya R, Fujisawa T, Shimizu N, Watanabe Y, Mitsudomi T, Yoshimura M. Overall survival and local recurrence of 406 completely resected stage IIIa-N2 non-small cell lung cancer patients: questionnaire survey of the Japan Clinical Oncology Group to plan for clinical trials. Lung Cancer. 2001;34:29–36. doi: 10.1016/s0169-5002(01)00207-0. [DOI] [PubMed] [Google Scholar]
- 10.Inoue M, Sawabata N, Takeda S, Ohta M, Ohno Y, Maeda H. Results of surgical intervention for p-stage IIIA (N2) non-small cell lung cancer: acceptable prognosis predicted by complete resection in patients with single N2 disease with primary tumor in the upper lobe. J Thorac Cardiovasc Surg. 2004;127:1100–1106. doi: 10.1016/j.jtcvs.2003.09.012. [DOI] [PubMed] [Google Scholar]
- 11.Arriagada R, Bergman B, Dunant A, Le Chevalier T, Pignon JP, Vansteenkiste J. Cisplatin-based adjuvant chemotherapy in patients with completely resected non-small-cell lung cancer. N Engl J Med. 2004;350:351–360. doi: 10.1056/NEJMoa031644. [DOI] [PubMed] [Google Scholar]
- 12.Douillard JY, Rosell R, De Lena M, Carpagnano F, Ramlau R, Gonzáles-Larriba JL, Grodzki T, Pereira JR, Le Groumellec A, Lorusso V, Clary C, Torres AJ, Dahabreh J, Souquet PJ, Astudillo J, Fournel P, Artal-Cortes A, Jassem J, Koubkova L, His P, Riggi M, Hurteloup P. Adjuvant vinorelbine plus cisplatin versus observation in patients with completely resected stage IB-IIIA non-small-cell lung cancer (Adjuvant Navelbine International Trialist Association [ANITA] ): a randomised controlled trial. Lancet Oncol. 2006;7:719–727. doi: 10.1016/S1470-2045(06)70804-X. [DOI] [PubMed] [Google Scholar]
- 13.Arriagada R, Auperin A, Burdett S, Higgins JP, Johnson DH, Le Chevalier T, Le Pechoux C, Parmar MK, Pignon JP, Souhami RL, Stephens RJ, Stewart LA, Tierney JF, Tribodet H, van Meerbeeck J. Adjuvant chemotherapy, with or without postoperative radiotherapy, in operable non-small-cell lung cancer: two meta-analyses of individual patient data. Lancet. 2010;375:1267–1277. doi: 10.1016/S0140-6736(10)60059-1. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 14.Shen WY, Ji J, Zuo YS, Pu J, Xu YM, Zong CD, Tao GZ, Chen XF, Ji FZ, Zhou XL, Han JH, Wang CS, Yi JG, Su XL, Zhu WG. Comparison of efficacy for postoperative chemotherapy and concurrent radiochemotherapy in patients with IIIA-pN2 non-small cell lung cancer: an early closed randomized controlled trial. Radiother Oncol. 2014;110:120–125. doi: 10.1016/j.radonc.2013.10.008. [DOI] [PubMed] [Google Scholar]
- 15.Douillard JY, Rosell R, De Lena M, Riggi M, Hurteloup P, Mahe MA. Impact of postoperative radiation therapy on survival in patients with complete resection and stage I, II, or IIIA non-small-cell lung cancer treated with adjuvant chemotherapy: the adjuvant Navelbine International Trialist Association (ANITA) randomized trial. Int J Radiat Oncol Biol Phys. 2008;72:695–701. doi: 10.1016/j.ijrobp.2008.01.044. [DOI] [PubMed] [Google Scholar]
- 16.Lung Cancer Study Group. Effects of postoperative mediastinal radiation on completely resected stage II and stage III epidermoid cancer of the lung. N Engl J Med. 1986;315:1377–1381. doi: 10.1056/NEJM198611273152202. [DOI] [PubMed] [Google Scholar]
- 17.Postoperative radiotherapy in non-small-cell lung cancer: systematic review and meta-analysis of individual patient data from nine randomised controlled trials. PORT Meta-analysis Trialists Group. Lancet. 1998;352:257–263. [PubMed] [Google Scholar]
- 18.Lally BE, Zelterman D, Colasanto JM, Haffty BG, Detterbeck FC, Wilson LD. Postoperative radiotherapy for stage II or III non-small-cell lung cancer using the surveillance, epidemiology, and end results database. J. Clin. Oncol. 2006;24:2998–3006. doi: 10.1200/JCO.2005.04.6110. [DOI] [PubMed] [Google Scholar]
- 19.Billiet C, Decaluwé H, Peeters S, Vansteenkiste J, Dooms C, Haustermans K, De Leyn P, De Ruysscher D. Modern post-operative radiotherapy for stage III non-small cell lung cancer may improve local control and survival: a meta-analysis. Radiother Oncol. 2014;110:3–8. doi: 10.1016/j.radonc.2013.08.011. [DOI] [PubMed] [Google Scholar]
- 20.Machtay M, Bae K, Movsas B, Paulus R, Gore EM, Komaki R, Albain K, Sause WT, Curran WJ. Higher biologically effective dose of radiotherapy is associated with improved outcomes for locally advanced non-small cell lung carcinoma treated with chemoradiation: an analysis of the Radiation Therapy Oncology Group. Int J Radiat Oncol Biol Phys. 2012;82:425–434. doi: 10.1016/j.ijrobp.2010.09.004. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 21.Machtay M, Paulus R, Moughan J, Komaki R, Bradley JE, Choy H, Albain K, Movsas B, Sause WT, Curran WJ. Defining local-regional control and its importance in locally advanced non-small cell lung carcinoma. J Thorac Oncol. 2012;7:716–722. doi: 10.1097/JTO.0b013e3182429682. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 22.Wei W, Zhou J, Zhang Q, Liao DH, Liu QD, Zhong BL, Liang ZB, Zhang YC, Jiang R, Liu GY, Xu CY, Li Zhou H, Zhu SY, Yang N, Jiang W, Liu ZG. Postoperative intensity-modulated radiation therapy reduces local recurrence and improves overall survival in III-N2 non-small-cell lung cancer: a single-center, retrospective study. Cancer Med. 2020;9:2820–2832. doi: 10.1002/cam4.2937. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 23.Feng W, Zhang Q, Fu XL, Cai XW, Zhu ZF, Yang HJ, Xiang JQ, Zhang YW, Chen HQ. The emerging outcome of postoperative radiotherapy for stage IIIA (N2) non-small cell lung cancer patients: based on the three-dimensional conformal radiotherapy technique and institutional standard clinical target volume. BMC Cancer. 2015;15:348. doi: 10.1186/s12885-015-1326-6. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 24.Noël G, Mazeron JJ. A randomized trial of postoperative adjuvant therapy in patients with completely resected stage II or IIIa non-small-cell lung cancer. Cancer Radiother. 2001;5:195–196. doi: 10.1016/s1278-3218(00)00066-4. [DOI] [PubMed] [Google Scholar]
- 25.Sawyer TE, Bonner JA, Gould PM, Foote RL, Deschamps C, Trastek VF, Pairolero PC, Allen MS, Shaw EG, Marks RS, Frytak S, Lange CM, Li H. The impact of surgical adjuvant thoracic radiation therapy for patients with nonsmall cell lung carcinoma with ipsilateral mediastinal lymph node involvement. Cancer. 1997;80:1399–1408. doi: 10.1002/(sici)1097-0142(19971015)80:8<1399::aid-cncr6>3.0.co;2-a. [DOI] [PubMed] [Google Scholar]
- 26.Sawyer TE, Bonner JA, Gould PM, Foote RL, Deschamps C, Trastek VF, Pairolero PC, Allen MS, Lange CM, Li H. Effectiveness of postoperative irradiation in stage IIIA non-small cell lung cancer according to regression tree analyses of recurrence risks. Ann Thorac Surg. 1997;64:1402–1407. doi: 10.1016/S0003-4975(97)00908-9. discussion 1407-1408. [DOI] [PubMed] [Google Scholar]
- 27.Isaka M, Kojima H, Takahashi S, Omae K, Ohde Y. Risk factors for local recurrence after lobectomy and lymph node dissection in patients with non-small cell lung cancer: implications for adjuvant therapy. Lung Cancer. 2018;115:28–33. doi: 10.1016/j.lungcan.2017.11.014. [DOI] [PubMed] [Google Scholar]
- 28.Zhang B, Zhao L, Yuan Z, Pang Q, Wang P. The influence of the metastasis pattern of mediastinal lymph nodes on the postoperative radiotherapy’s efficacy for the IIIA-pN2 non-small-cell lung cancer: a retrospective analysis of 220 patients. Onco Targets Ther. 2016;9:6161–6169. doi: 10.2147/OTT.S103565. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 29.Moretti L, Yu DS, Chen H, Carbone DP, Johnson DH, Keedy VL, Putnam JB Jr, Sandler AB, Shyr Y, Lu B. Prognostic factors for resected non-small cell lung cancer with pN2 status: implications for use of postoperative radiotherapy. Oncologist. 2009;14:1106–1115. doi: 10.1634/theoncologist.2009-0130. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 30.Liu W, Shao Y, Guan B, Hao J, Cheng X, Ji K, Wang K. Extracapsular extension is a powerful prognostic factor in stage IIA-IIIA non-small cell lung cancer patients with completely resection. Int J Clin Exp Pathol. 2015;8:11268–11277. [PMC free article] [PubMed] [Google Scholar]
- 31.Takamochi K, Oh S, Matsunaga T, Suzuki K. Prognostic impacts of EGFR mutation status and subtype in patients with surgically resected lung adenocarcinoma. J Thorac Cardiovasc Surg. 2017;154:1768–1774.e1. doi: 10.1016/j.jtcvs.2017.06.062. [DOI] [PubMed] [Google Scholar]
- 32.Ito M, Miyata Y, Tsutani Y, Ito H, Nakayama H, Imai K, Ikeda N, Okada M. Positive EGFR mutation status is a risk of recurrence in pN0-1 lung adenocarcinoma when combined with pathological stage and histological subtype: A retrospective multi-center analysis. Lung Cancer. 2020;141:107–113. doi: 10.1016/j.lungcan.2020.01.018. [DOI] [PubMed] [Google Scholar]
- 33.Takahashi Y, Horio H, Hato T, Harada M, Matsutani N, Morita S, Kawamura M. Prognostic significance of preoperative neutrophil-lymphocyte ratios in patients with stage I non-small cell lung cancer after complete resection. Ann Surg Oncol. 2015;22(Suppl 3):S1324–1331. doi: 10.1245/s10434-015-4735-5. [DOI] [PubMed] [Google Scholar]
- 34.Wang YQ, Zhi QJ, Wang XY, Yue DS, Li K, Jiang RC. Prognostic value of combined platelet, fibrinogen, neutrophil to lymphocyte ratio and platelet to lymphocyte ratio in patients with lung adenosquamous cancer. Oncol Lett. 2017;14:4331–4338. doi: 10.3892/ol.2017.6660. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 35.Hu P, Shen H, Wang G, Zhang P, Liu Q, Du J. Prognostic significance of systemic inflammation-based lymphocyte- monocyte ratio in patients with lung cancer: based on a large cohort study. PLoS One. 2014;9:e108062. doi: 10.1371/journal.pone.0108062. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 36.Okada S, Shimada J, Kato D, Tsunezuka H, Teramukai S, Inoue M. Clinical significance of prognostic nutritional index after surgical treatment in lung cancer. Ann Thorac Surg. 2017;104:296–302. doi: 10.1016/j.athoracsur.2017.01.085. [DOI] [PubMed] [Google Scholar]
- 37.Travis WD, Brambilla E, Nicholson AG, Yatabe Y, Austin JHM, Beasley MB, Chirieac LR, Dacic S, Duhig E, Flieder DB, Geisinger K, Hirsch FR, Ishikawa Y, Kerr KM, Noguchi M, Pelosi G, Powell CA, Tsao MS, Wistuba I WHO Panel. The 2015 World Health Organization classification of lung tumors: impact of genetic, clinical and radiologic advances since the 2004 classification. J Thorac Oncol. 2015;10:1243–1260. doi: 10.1097/JTO.0000000000000630. [DOI] [PubMed] [Google Scholar]
- 38.Groome PA, Bolejack V, Crowley JJ, Kennedy C, Krasnik M, Sobin LH, Goldstraw P. The IASLC lung cancer staging project: validation of the proposals for revision of the T, N, and M descriptors and consequent stage groupings in the forthcoming (seventh) edition of the TNM classification of malignant tumours. J Thorac Oncol. 2007;2:694–705. doi: 10.1097/JTO.0b013e31812d05d5. [DOI] [PubMed] [Google Scholar]
- 39.Rusch VW, Asamura H, Watanabe H, Giroux DJ, Rami-Porta R, Goldstraw P. The IASLC lung cancer staging project: a proposal for a new international lymph node map in the forthcoming seventh edition of the TNM classification for lung cancer. J Thorac Oncol. 2009;4:568–577. doi: 10.1097/JTO.0b013e3181a0d82e. [DOI] [PubMed] [Google Scholar]
- 40.Camp RL, Dolled-Filhart M, Rimm DL. X-tile: a new bio-informatics tool for biomarker assessment and outcome-based cut-point optimization. Clin Cancer Res. 2004;10:7252–7259. doi: 10.1158/1078-0432.CCR-04-0713. [DOI] [PubMed] [Google Scholar]
- 41.Fan J, Yao J, Wang Q, Chang Z. Safety and feasibility of uniportal video-assisted thoracoscopic surgery for locally advanced non-small cell lung cancer. J Thorac Dis. 2016;8:3543–3550. doi: 10.21037/jtd.2016.12.12. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 42.Gonfiotti A, Bongiolatti S, Bertolaccini L, Viggiano D, Solli P, Droghetti A, Bertani A, Crisci R, Voltolini L. Thoracoscopic lobectomy for locally advanced-stage non-small cell lung cancer is a feasible and safe approach: analysis from multi-institutional national database. J Vis Surg. 2017;3:160. doi: 10.21037/jovs.2017.09.06. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 43.Zhong C, Yao F, Zhao H. Clinical outcomes of thoracoscopic lobectomy for patients with clinical N0 and pathologic N2 non-small cell lung cancer. Ann Thorac Surg. 2013;95:987–992. doi: 10.1016/j.athoracsur.2012.10.083. [DOI] [PubMed] [Google Scholar]
- 44.Chen K, Wang X, Yang F, Li J, Jiang G, Liu J, Wang J. Propensity-matched comparison of video-assisted thoracoscopic with thoracotomy lobectomy for locally advanced non-small cell lung cancer. J Thorac Cardiovasc Surg. 2017;153:967–976.e962. doi: 10.1016/j.jtcvs.2016.12.008. [DOI] [PubMed] [Google Scholar]
- 45.Zhang L. Short- and long-term outcomes in elderly patients with locally advanced non-small-cell lung cancer treated using video-assisted thoracic surgery lobectomy. Ther Clin Risk Manag. 2018;14:2213–2220. doi: 10.2147/TCRM.S175846. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 46.Wang S, Ma Z, Yang X, Wang Y, Xu Y, Xia W, Chen R, Qiu M, Jiang F, Yin R, Xu L, Xu K. Choice of postoperative radiation for stage IIIA pathologic N2 non-small cell lung cancer: impact of metastatic lymph node number. Radiat Oncol. 2017;12:207. doi: 10.1186/s13014-017-0946-1. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 47.Kou P, Wang H, Lin J, Zhang Y, Yu J. Male patients with resected IIIA-N2 non-small-cell lung cancer may benefit from postoperative radiotherapy: a population-based survival analysis. Future Oncol. 2018;14:2371–2381. doi: 10.2217/fon-2018-0326. [DOI] [PubMed] [Google Scholar]
- 48.Zhu Y, Fu L, Jing W, Kong L, Yu J. Radiotherapy for patients with completely resected pathologic IIIA(N2) non-small-cell lung cancer: a retrospective analysis. Cancer Manag Res. 2019;11:10901–10908. doi: 10.2147/CMAR.S197245. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 49.Yuan C, Tao X, Zheng D, Pan Y, Ye T, Hu H, Xiang J, Zhang Y, Chen H, Sun Y. The lymph node status and histologic subtypes influenced the effect of postoperative radiotherapy on patients with N2 positive IIIA non-small cell lung cancer. J Surg Oncol. 2019;119:379–387. doi: 10.1002/jso.25308. [DOI] [PubMed] [Google Scholar]
- 50.Tamura M, Matsumoto I, Saito D, Yoshida S, Takata M, Takemura H. Lymph node ratio as a prognostic factor in patients with pathological N2 non-small cell lung cancer. World J Surg Oncol. 2016;14:295. doi: 10.1186/s12957-016-1048-5. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 51.Deng W, Xu T, Xu Y, Wang Y, Liu X, Zhao Y, Yang P, Liao Z. Survival patterns for patients with resected N2 non-small cell lung cancer and postoperative radiotherapy: a prognostic scoring model and heat map approach. J Thorac Oncol. 2018;13:1968–1974. doi: 10.1016/j.jtho.2018.08.2021. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 52.Shang X, Li Z, Lin J, Wang H, Wang Z. PLNR ≤ 20% may be a benefit from PORT for patients with IIIA-N2 NSCLC: a large population-based study. Cancer Manag Res. 2018;10:3561–3567. doi: 10.2147/CMAR.S173856. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 53.Mitsudomi T, Morita S, Yatabe Y, Negoro S, Okamoto I, Tsurutani J, Seto T, Satouchi M, Tada H, Hirashima T, Asami K, Katakami N, Takada M, Yoshioka H, Shibata K, Kudoh S, Shimizu E, Saito H, Toyooka S, Nakagawa K, Fukuoka M. Gefitinib versus cisplatin plus docetaxel in patients with non-small-cell lung cancer harbouring mutations of the epidermal growth factor receptor (WJTOG3405): an open label, randomised phase 3 trial. Lancet Oncol. 2010;11:121–128. doi: 10.1016/S1470-2045(09)70364-X. [DOI] [PubMed] [Google Scholar]
- 54.Rosell R, Carcereny E, Gervais R, Vergnenegre A, Massuti B, Felip E, Palmero R, Garcia-Gomez R, Pallares C, Sanchez JM, Porta R, Cobo M, Garrido P, Longo F, Moran T, Insa A, De Marinis F, Corre R, Bover I, Illiano A, Dansin E, de Castro J, Milella M, Reguart N, Altavilla G, Jimenez U, Provencio M, Moreno MA, Terrasa J, Muñoz-Langa J, Valdivia J, Isla D, Domine M, Molinier O, Mazieres J, Baize N, Garcia-Campelo R, Robinet G, Rodriguez-Abreu D, Lopez-Vivanco G, Gebbia V, Ferrera-Delgado L, Bombaron P, Bernabe R, Bearz A, Artal A, Cortesi E, Rolfo C, Sanchez-Ronco M, Drozdowskyj A, Queralt C, de Aguirre I, Ramirez JL, Sanchez JJ, Molina MA, Taron M, Paz-Ares L. Erlotinib versus standard chemotherapy as first-line treatment for European patients with advanced EGFR mutation-positive non-small-cell lung cancer (EURTAC): a multicentre, open-label, randomised phase 3 trial. Lancet Oncol. 2012;13:239–246. doi: 10.1016/S1470-2045(11)70393-X. [DOI] [PubMed] [Google Scholar]
- 55.Wu YL, Zhou C, Hu CP, Feng J, Lu S, Huang Y, Li W, Hou M, Shi JH, Lee KY, Xu CR, Massey D, Kim M, Shi Y, Geater SL. Afatinib versus cisplatin plus gemcitabine for first-line treatment of Asian patients with advanced non-small-cell lung cancer harbouring EGFR mutations (LUX-Lung 6): an open-label, randomised phase 3 trial. Lancet Oncol. 2014;15:213–222. doi: 10.1016/S1470-2045(13)70604-1. [DOI] [PubMed] [Google Scholar]
- 56.Ramalingam SS, Vansteenkiste J, Planchard D, Cho BC, Gray JE, Ohe Y, Zhou C, Reungwetwattana T, Cheng Y, Chewaskulyong B, Shah R, Cobo M, Lee KH, Cheema P, Tiseo M, John T, Lin MC, Imamura F, Kurata T, Todd A, Hodge R, Saggese M, Rukazenkov Y, Soria JC. Overall survival with osimertinib in untreated, EGFR-mutated advanced NSCLC. N Engl J Med. 2020;382:41–50. doi: 10.1056/NEJMoa1913662. [DOI] [PubMed] [Google Scholar]
- 57.Matsumura Y, Suzuki H, Ohira T, Shiono S, Abe J, Sagawa M, Sakurada A, Katahira M, Machida Y, Takahashi S, Okada Y. Matched-pair analysis of a multi-institutional cohort reveals that epidermal growth factor receptor mutation is not a risk factor for postoperative recurrence of lung adenocarcinoma. Lung Cancer. 2017;114:23–30. doi: 10.1016/j.lungcan.2017.09.003. [DOI] [PubMed] [Google Scholar]
- 58.He Q, Xin P, Zhang M, Jiang S, Zhang J, Zhong S, Liu Y, Guo M, Chen X, Xia X, Pan Z, Guo C, Cai X, Liang W, He J. The impact of epidermal growth factor receptor mutations on the prognosis of resected non-small cell lung cancer: a meta-analysis of literatures. Transl Lung Cancer Res. 2019;8:124–134. doi: 10.21037/tlcr.2019.03.14. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 59.Candido J, Hagemann T. Cancer-related inflammation. J Clin Immunol. 2013;33(Suppl 1):S79–84. doi: 10.1007/s10875-012-9847-0. [DOI] [PubMed] [Google Scholar]
- 60.Nishijima TF, Muss HB, Shachar SS, Tamura K, Takamatsu Y. Prognostic value of lymphocyte-to-monocyte ratio in patients with solid tumors: a systematic review and meta-analysis. Cancer Treat Rev. 2015;41:971–978. doi: 10.1016/j.ctrv.2015.10.003. [DOI] [PubMed] [Google Scholar]
- 61.Li W, Ma G, Wu Q, Deng Y, Liu Y, Wang J. Prognostic value of lymphocyte-to-monocyte ratio among Asian lung cancer patients: a systematic review and meta-analysis. Oncotarget. 2017;8:110606–110613. doi: 10.18632/oncotarget.20574. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 62.Wang Y, Huang D, Xu WY, Wang YW, Che GW. Prognostic value of pretreatment lymphocyte-to-monocyte ratio in non-small cell lung cancer: a meta-analysis. Oncol Res Treat. 2019;42:523–531. doi: 10.1159/000501726. [DOI] [PubMed] [Google Scholar]
- 63.Hui Z, Dai H, Liang J, Lv J, Zhou Z, Feng Q, Xiao Z, Chen D, Zhang H, Yin W, Wang L. Selection of proper candidates with resected pathological stage IIIA-N2 non-small cell lung cancer for postoperative radiotherapy. Thorac Cancer. 2015;6:346–353. doi: 10.1111/1759-7714.12186. [DOI] [PMC free article] [PubMed] [Google Scholar]