Heterogeneous prognosis and adjuvant chemotherapy in pathological stage I non-small cell lung cancer patients

Factors influencing postoperative recurrence of early-stage non-small cell lung cancer

PURPOSE

This study aims to explain the factors that may influence recurrence after surgical resection for early non-small cell lung cancer (NSCLC).

METHODS

A retrospective analysis was made of 302 patients who underwent lung resection for stage I-IIA NSCLC in our clinic between January 2014 and August 2021.

RESULTS

The recurrence rate was higher in patients with squamous cell carcinoma (SCC) than in those with adenocarcinoma (AC) (p = 0.004). Disease-free survival (DFS) was shorter in SCC (p = 0.004). According to histopathological subtypes, the presence of lymphovascular invasion (LVI), vascular invasion (VI), visceral pleural invasion (VPI) and tumor spread through air spaces (STAS) caused an increased risk of recurrence ((p = 0.004), (p = 0.001), (p = 0.047), (p = < 0.001)) and shorter DFS ((p = 0.002), (p = < 0.001), (p = 0.038), (p = < 0.001)). LVI and VI was more common in patients with distant recurrence (p = 0.020, p = 0.002), while the STAS was more common with locoregional recurrence (p = 0.003).

CONCLUSION

The presence of LVI, VI, VPI, and STAS are negative risk factors for recurrence and DFS in all patients and in patients with AC. In patients with SCC, the diagnosis of SCC itself and the presence of STAS were risk factors for recurrence and DFS. Moreover, the risk of distant recurrence is higher in the presence of LVI or VI, and the risk of locoregional recurrence in the presence of STAS is higher.

Prognostic significance and survival benefits of postoperative adjuvant chemotherapy in patients with stage IA lung adenocarcinoma with non-predominant micropapillary components

BACKGROUND

The prognostic significance of adjuvant chemotherapy (ACT) for patients with stage IA micropapillary non-predominant (MPNP) lung adenocarcinoma (LUAD) remains unknown. This study aimed to investigate the effects of postoperative ACT in patients with stage IA MPNP-LUAD.

METHODS

A total of 149 patients with pathological stage IA MPNP-LUAD who underwent surgery at our center were retrospectively analyzed. Propensity score matching (PSM) analysis was conducted to reduce potential selection bias. Kaplan-Meier analyses were used to assess the impact of ACT on recurrence-free survival (RFS), overall survival (OS), and disease-specific survival (DSS). Subgroup analyses were performed for the survival outcomes based on the percentage of micropapillary components. Cox proportional hazards regression analyses were applied to identify risk factors associated with survival.

RESULTS

The receipt or non-receipt of postoperative ACT had no significant effect on RFS, OS, and DSS among all enrolled patients with stage IA MPNP-LUAD (P > 0.05). For patients with a micropapillary component > 5%, the 5-year rates of RFS, OS, and DSS were significantly higher in the ACT group compared to the observation group, both before and after PSM (P < 0.05). However, the differences between the two groups were not significant for patients with a micropapillary component ≤ 5% (P > 0.05). The resection range (HR = 0.071; 95% CI: 0.020-0.251; P < 0.001), tumor size (HR = 2.929; 95% CI: 1.171-7.330; P = 0.022), and ACT (HR = 0.122; 95% CI: 0.037-0.403; P = 0.001) were identified as independent prognostic factors for RFS through Cox regression analysis.

CONCLUSION

Patients with stage IA MPNP-LUAD who have a micropapillary component greater than 5% might benefit from postoperative ACT, while those with a micropapillary component ≤ 5% did not appear to derive the same benefit from postoperative ACT.

Adjuvant chemotherapy in pathological node-negative non-small cell lung cancer

Non-small cell lung cancer (NSCLC) is associated with a poor survival rate, even for patients with early-stage cancer. Identifying patients with pathological N0 NSCLC who may benefit from adjuvant chemotherapy treatment after surgery is essential. We conducted a retrospective cohort study used data from the Surveillance, Epidemiology, and End Results database and included 26,380 patients with pathological N0 NSCLC after surgery between January 2018, and December 2019. Among 26,380 patients, 24,273 patients received surgery alone and the other 2107 patients received surgery plus adjuvant chemotherapy. After 1:1 propensity score matching, both groups contained 2107 patients. Adjuvant chemotherapy did not show significantly better 24-month survival in T2aN0 NSCLC patients (83.41% vs. 82.91%, p = 0.067), although it did for T2bN0 patients (86.36% vs. 81.70%, p = 0.028). Poorly-differentiated NSCLC remained a high-risk factor for pT2N0, and adjuvant chemotherapy provided better 24-month survival after matching (86.36% vs. 81.70%, p = 0.029). In conclusion, when treating pN0 NSCLC, adjuvant chemotherapy had a beneficial effect when the tumor size was larger than 4 cm. The effect when the tumor size was between 3 and 4 cm was not remarkable. Poorly-differentiated NSCLC was a high-risk factor in the pT2N0 stage.

[A Review on Pathological High-risk Factors and Postoperative Adjuvant Chemotherapy in Stage IA Lung Adenocarcinoma]

The survival rate needs to be improved in early stage non-small cell lung cancer patients. The risk of recurrence is relatively high in invasive adenocarcinoma patients with a solid or micropapillary component, lymphovascular invasion or tumor spread through air spaces. Systemic treatment options including radical surgical resection should be explored for this population. Adjuvant chemotherapy is not recommended for patients in stage IA in current guidelines. This article is a review on the research progress of the above pathological high-risk factors and the role of adjuvant chemotherapy in patients with pathological high-risk factors in stage IA lung adenocarcinoma.
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Characterization of the MicroRNA Cargo of Extracellular Vesicles Isolated from a Pulmonary Tumor-Draining Vein Identifies miR-203a-3p as a Relapse Biomarker for Resected Non-Small Cell Lung Cancer

In resected non-small cell lung cancer (NSCLC), post-surgical recurrence occurs in around 40% of patients, highlighting the necessity to identify relapse biomarkers. An analysis of the extracellular vesicle (EV) cargo from a pulmonary tumor-draining vein (TDV) can grant biomarker identification. We studied the pulmonary TDV EV-miRNAome to identify relapse biomarkers in a two-phase study (screening and validation). In the screening phase, a 17-miRNA relapse signature was identified in 18 selected patients by small RNAseq. The most expressed miRNA from the signature (EV-miR-203a-3p) was chosen for further validation. Pulmonary TDV EV-miR-203a-3p was studied by qRT-PCR in a validation cohort of 70 patients, where it was found to be upregulated in relapsed patients (p = 0.0194) and in patients with cancer spread to nearby lymph nodes (N+ patients) (p = 0.0396). The ROC curve analysis showed that TDV EV-miR-203a-3p was able to predict relapses with a sensitivity of 88% (AUC: 0.67; p = 0.022). Moreover, patients with high TDV EV-miR-203a-3p had a shorter time to relapse than patients with low levels (43.6 vs. 97.6 months; p = 0.00703). The multivariate analysis showed that EV-miR-203a-3p was an independent, predictive and prognostic post-surgical relapse biomarker. In conclusion, pulmonary TDV EV-miR-203a-3p is a promising new relapse biomarker for resected NSCLC patients.

A risk classification system predicting the cancer-specific survival for postoperative stage IB non-small-cell lung cancer patients without lymphovascular and visceral pleural invasion

BACKGROUND

This study aims to formulate a risk classification system predicting the cancer-specific survival (CSS) for postoperative stage IB NSCLC patients without lymphovascular (LVI) and visceral pleural (VPI) invasion to guide treatment decision making and assist patient counseling.

METHOD

A total of 4,238 patients were included in this study. Patients were randomly divided into training and validation cohorts (7:3). The risk factors were identified by Cox regression. Concordance index (C-index), calibration curves, and Decision Curve Analyses (DCAs) were used to evaluate the performance of nomogram. We applied X-tile to calculate the optimal cut-off points and develop a risk classification system. The Kaplan-Meier method was conducted to evaluate CSS in different risk groups, and the significance was evaluated by log-rank test.

RESULT

Among the 4,238 patients, 1,014(23.9%) suffered cancer-specific death. In the training cohort, univariable and multivariable Cox regression analyses revealed that age, gender, pathological subtype, grade, tumor size, the number of removed lymph nodes and surgical type were significantly associated with CSS. According to these results, the nomogram was formulated. The C-index of the prediction model was 0.755 in the training cohort (95%CI: 0.733-0.777) and 0.726 (95%CI: 0.695-0.757) in the validation cohort. The calibration curves in training and validation cohort exhibited good agreement between the predictions and actual observations. The Decision Curve Analyses (DCAs) showed net benefit can be achieved for nomogram. A risk classification system was further constructed that could perfectly classify patients into three risk groups.

CONCLUSION

In this study, we constructed a nomogram to support individualized evaluation of CSS and a risk classification system to identify patients in the different risk groups in stage IB NSCLC patients without LVI and VPI. These tools could be useful in guiding treatment decision making and assisting patient counseling.

Overall Survival Analyses following Adjuvant Chemotherapy or Nonadjuvant Chemotherapy in Patients with Stage IB Non-Small-Cell Lung Cancer

Background

Adjuvant chemotherapy (ACT) can improve prognosis for stages II-IIIA patients with non-small-cell lung cancer (NSCLC), but its implication in stage I patients is still an intractable puzzle. This study aims to seek ACT candidates for stage IB NSCLC and establish a nomogram to predict overall survival (OS) of specific patient for clinician's decision.

Method

We performed a retrospective study on 16,765 patients (ACT group: n = 2,187; non-ACT group: n = 14,578) from the Surveillance, Epidemiology, and End Results (SEER) database. Overall survival was assessed in two groups. We performed propensity-score matching for risk adjustment. The risk factors were identified and used to create nomogram. Concordance index (C-index), Hosmer–Lemeshow test, and calibration were applied to evaluate model performance. To further evaluate the influence of tumor size on the selection of potential ACT candidates for patients with stage IB NSCLC, subgroup analyses were executed.

Result

Survival analysis for the entire study cohort showed that ACT had better OS than non-ACT (HR = 0.800, CI: (0.751–0.851), P < 0.0001). In matched cohort, ACT also presented better OS than non-ACT (HR = 0.775, CI: (0.704–0.853), P < 0.0001). Univariate and multivariate Cox regression analysis revealed that eight prognostic factors, including gender, age, grade, pathological subtype, tumor size, visceral pleural invasion, surgical procedure, and the number of removed lymph nodes, were significantly correlated with OS. The nomogram was further constructed based on these prognostic factors. The C-index of nomogram was 0.639 (95%CI: 0.632–0.646). The Hosmer–Lemeshow test, and calibration presented good congruence between the predictions and actual observations. Subgroup analyses of tumor size group showed that ACT shared similar OS to non-ACT in NSCLC patients with tumor size ≤20 mm (P > 0.05). However, for NSCLC patients with 20 mm < size ≤30 mm (HR = 0.845, 95%CI (0.724–0.986), P=0.032) and 30 mm < size ≤40 mm (HR = 0.912, 95%CI (0.833–1.000), P=0.049), ACT associated with better OS.

Conclusion

In this study, we found that ACT had better OS than non-ACT in patients with stage IB NSCLC. The nomogram provided an individual prediction of OS for patients after surgical resection. Patients with tumor size >20 mm and ≤40 mm may be potential candidates for ACT.

Nomogram to Predict Cancer Specific Survival in Patients with Pathological Stage IA Non-small Cell Lung Cancer

We identified the prognostic factors of resected stage IA non-small cell lung cancer (NSCLC) and developed a nomogram, with purpose of defining the high-risk population who may need closer follow-up or more intensive care. Eligible stage IA NSCLC cases from the Surveillance, Epidemiology, and End Results (SEER) database and the Sun Yat-sen University Cancer Center (SYSUCC) were included. Stage IB NSCLCs were also included for evaluating the risk stratification efficacy. Cancer specific survival (CSS) was compared between groups. Statistically significant factors from multivariate analysis were entered into the nomogram. The performance of the nomogram was evaluated by concordance index (C-index) and calibration plots. A total of 23,112 NSCLC cases (SEER stage IA training cohort, N=7,777; SEER stage IA validation cohort, N=7,776; SEER stage IB cohort, N=7,559) from the SEER database were included. 1,304 NSCLC cases (SYSUCC stage IA validation cohort, N=684; SYSUCC stage IB cohort, N=620) from the SYSUCC were also included. Younger age, female, lobectomy, well differentiated, smaller size and more examined lymph nodes were identified as favorable prognostic factors. A nomogram was established. The C-index was 0.68 (95%CI, 0.67-0.69), 0.66 (95% CI, 0.64-0.68) and 0.66 (95% CI, 0.61-0.71) for the SEER training cohort, SEER validation cohort and SYSUCC validation cohort. A risk classification system was constructed to stratify stage IA NSCLC into low-risk subgroup and high-risk subgroup. The CSS curves of these two subgroups showed statistically significant distinctions. This nomogram delivered a prognostic prediction for stage IA NSCLC and may aid individual clinical practice.

Could tumor spread through air spaces benefit from adjuvant chemotherapy in stage I lung adenocarcinoma? A multi-institutional study

Background:

The benefit of adjuvant chemotherapy (ACT) remains unknown for patients with stage I lung adenocarcinoma (ADC) with spread through air spaces (STAS). This study investigated the effect of adjuvant chemotherapy in stage I ADC/STAS-positive patients.

Methods:

A total of 3346 patients with stage I ADC from five institutions in China were identified from 2009 to 2013, of whom 1082 were diagnosed with STAS (32.3%). By using the Kaplan–Meier method and Cox proportional hazard regression model, we explored the impact of STAS on prognosis, and determined if the use of adjuvant chemotherapy was associated with improved outcomes in patients with stage I ADC/STAS-positive. A validation cohort was also included in this study.

Results:

Patients with stage I ADC/STAS-positive in the primary cohort had unfavorable overall survival (OS) and disease-free survival (DFS). A multivariate Cox regression model confirmed the survival disadvantages of STAS in patients with stage I ADC [OS: hazards ratio (HR) = 1.877, 95% confidence interval (CI): 1.579–2.231; p < 0.001; DFS: HR = 1.895, 95% CI: 1.614–2.225; p < 0.001]. Lobectomy was associated with better OS and DFS than sublobar resection (SR) in both stage IA and IB ADC/STAS-positive. Similar results were observed in the validation cohort. For patients with stage IB ADC/STAS-positive, ACT was revealed as an independent factor for favorable survival (OS: HR = 0.604, 95% CI: 0.397–0.919; p = 0.018; DFS: HR = 0.565, 95% CI: 0.372–0.858; p = 0.007). However, among patients with stage IA ADC/STAS-positive, ACT was associated with improved outcomes only for those undergoing SR (OS: HR = 0.787, 95% CI: 0.359–0.949; p = 0.034; DFS: HR = 0.703, 95% CI: 0.330–0.904; p = 0.029).

Conclusion:

The presence of STAS was correlated with poor prognosis in patients with stage I ADC. Our study suggested that ACT might be considered for patients with stage IB ADC/STAS-positive and those with stage IA ADC/STAS-positive who underwent SR.

Machine learning-based histological classification that predicts recurrence of peripheral lung squamous cell carcinoma

BACKGROUND

Cancer tissue is composed of both a cancer cell component and a stromal component. The aim of this study was to investigate if the component ratio predicts a prognosis for lung squamous cell carcinoma (SqCC) patients by using a machine learning method.

METHODS

A total of 135 peripheral SqCC cases (tumor size: 3-5 cm) were enrolled in this study. The areas of the cancer cell component, the necrotic component, and the stromal component were accurately measured via a machine learning method. Each case was divided into the following three subtypes: 1) predominant cancer cell, 2) predominant necrosis, and 3) predominant stroma. The study examined if a particular subtype had prognostic significance.

RESULTS

The number of cases per subtype of predominant cancer cell, predominant necrosis, and predominant stroma was 59, 6, and 70, respectively. Patients with the predominant stroma subtype had a significantly shorter recurrence free survival (RFS) than did those with the predominant cancer cell subtype (5-yr RFS: 42.3 % vs. 84.3 %,p < 0.01). Also, in pathological stage I patients, the 5-year RFS rate for the predominant stroma subtype was significantly shorter (5-yr RFS: 64.3 % vs. 88.4 %, p < 0.01). In the multivariate analysis of p-stage I patients, the predominant stroma subtype was confirmed to be an independent prognostic factor for RFS (p < 0.01).

CONCLUSION

Using machine learning, the study confirmed that the predominant stroma subtype was an independent factor for RFS, suggesting that the ratio of the stromal component correlates with the malignant potential of SqCC.

Optimal Lymph Node Examination and Adjuvant Chemotherapy for Stage I Lung Cancer

OBJECTIVE

To determine the optimal number of lymph nodes (LNs) examined and the role of adjuvant chemotherapy in stage I lung cancer.

METHODS

The National Cancer Database was queried for surgically treated patients with pathologic stage I lung cancer between 2006 and 2014 (N = 65,438). The optimal LN numbers were determined in the multivariate Cox model and were further validated in the cohort with clinical stage I disease (N = 117,112) in terms of nodal upstaging and prognostic stratification. The role of adjuvant chemotherapy in patients with suboptimal staging (number of LNs examined was less than than the optimum) was evaluated in each T stage.

RESULTS

The number of LNs examined correlated with tumor size (p < 0.001). There were increasing survival benefits with each additional LN examined-up to eight, nine, 10, and 11 nodes for patients with T1a, T1b, T1c, and T2a, respectively. Validation from the cohort with clinically staged disease showed that the threshold of eight to 11 LNs was an independent predictor of nodal upstaging (OR = 1.706, 95% confidence interval [CI] 1.608-1.779) and survival outcome (hazard ratio = 0.890, 95% CI: 0.865-0.916). After propensity matching, adjuvant chemotherapy was associated with improved survival in patients with stage T2a disease having suboptimal staging (hazard ratio = 0.841, 95% CI: 0.714-0.990), but not in patients with stage T1a to T1c disease.

CONCLUSION

LN evaluation was important for accurate staging and adequate treatment, and examinations of an increasing number of nodes for progressively higher T components (i.e., eight, nine, 10, and 11 nodes for T1a, T1b, T1c, and T2a tumors, respectively) seemed crucial to predict upstaging and survival outcomes. Adjuvant chemotherapy might be beneficial to patients with stage T2a disease who have suboptimal nodal staging.

Targeted next-generation sequencing reveals recurrence-associated genomic alterations in early-stage non-small cell lung cancer

Purpose

The identification of genomic alterations related to recurrence in early-stage non-small cell lung cancer (NSCLC) patients may help better stratify high-risk individuals and guide treatment strategies. This study aimed to identify the molecular biomarkers of recurrence in early-stage NSCLC.

Results

Of the 42 tumors evaluable for genomic alterations, TP53 and EGFR were the most frequent alterations with population frequency 52.4% and 50.0%, respectively. Fusion genes were detected in four patients, which had lower mutational burden and relatively better genomic stability. EGFR mutation and fusion gene were mutually exclusive in this study. CDKN2A, FAS, SUFU and SMARCA4 genomic alterations were only observed in the relapsed patients. Increased copy number alteration index was observed in early relapsed patients. Among these genomic alterations, early-stage NSCLCs harboring CDKN2A, FAS, SUFU and SMARCA4 genomic alterations were found to be significantly associated with recurrence. Some of these new findings were validated using The Cancer Genome Atlas (TCGA) dataset.

Conclusions

The genomic alterations of CDKN2A, FAS, SUFU and SMARCA4 in early-stage NSCLC are found to be associated with recurrence, but confirmation in a larger independent cohort is required to define the clinical impact.

Materials and Methods

Paired primary tumor and normal lung tissue samples were collected for targeted next-generation sequencing analysis. A panel targets exons for 440 genes was used to assess the mutational and copy number status of selected genes in three clinically relevant groups of stage I/II NSCLC patients: 1) Early relapse; 2) Late relapse; and 3) No relapse.

A more sensitive detection of micrometastases of NSCLC in lymph nodes using the one-step nucleic acid amplification (OSNA) method

BACKGROUND

Detection of tumor cells in lymph nodes (LNs) removed during the treatment of pulmonary tumor by radical surgery is limited by the possibilities of standard histopathological methods. The goal of this study was to obtain more accurate pTNM status by a more sensitive detection of micrometastases in LNs.

METHODS

A total of 885 LNs, an average of 13.8 LNs per patient, were removed during 64 surgeries. LNs from the same zone were pooled together as a group, five groups of LNs were examined in each patient. A total of 320 groups of LNs were examined. One-step nucleic acid amplification (OSNA) method was compared to standard histopathological examination with haematoxylin-eosin (H&E) staining and CK19 immunohistochemistry, specifically by an ultimate analysis of all intraoperatively removed LNs.

RESULTS

Identical results for H&E and OSNA examinations were recorded in 286 groups of LNs (89.4%). In total, positive examinations were recorded in 27 groups of LNs (8.4%) using the OSNA method, which were H&E negative. In seven groups of LNs (2.2%), the H&E examination was positive, while OSNA method produced negative results.

CONCLUSIONS

The OSNA examination led to a higher pTNM stage classification in 14 (21.9%) patients. The clinical significance remains the subject of follow-up research.

The role of Thyroid Transcription Factor-1 and Tumor differentiation in Resected Lung Adenocarcinoma

To investigate the role of thyroid transcription factor-1 (TTF-1) and tumor differentiation in resected lung adenocarcinoma. A total of 520 patients with clinical early stage lung adenocarcinoma who underwent surgical resection were reviewed retrospectively. Clinical data and outcomes were evaluated with an average follow-up of 117 months. The results were validated via lung cancer cell line studies. The clinical parameters did not differ between relapse and nonrelapse patients. Exceptions were tumor differentiation, lymphovascular space invasion, F¹⁸-fluorodeoxyglucose maximum standard uptake value, tumor size, and pathological stage (p < 0.001). Poor tumor differentiation was the independent prognostic factor (odds ratio: 2.937, p = 0.026). The expression of TTF-1 was correlated with tumor differentiation in resected lung adenocarcinoma patients (p < 0.001). Five-year survival was 60.0% for score 1 TTF-1 expression patients, 80.1% for score 2 TTF-1 expression patients, and 86.1% for score 3 TTF-1 expression group patients. The lung cancer cell line study of knockdown and overexpression of TTF-1 revealed TTF-1 mediated High Mobility Group AT-Hook 2 (HMGA2) protein involved with epithelium-mesenchymal transformation. The chromatin immunoprecipitation revealed TTF-1 regulated HMGA2 via direct binding. TTF-1/HMGA2 axis was associated with tumor differentiation and mediated the aggressiveness of the tumor and prognosis.

Prediction of recurrence in early stage non-small cell lung cancer using computer extracted nuclear features from digital H&E images

Identification of patients with early stage non-small cell lung cancer (NSCLC) with high risk of recurrence could help identify patients who would receive additional benefit from adjuvant therapy. In this work, we present a computational histomorphometric image classifier using nuclear orientation, texture, shape, and tumor architecture to predict disease recurrence in early stage NSCLC from digitized H&E tissue microarray (TMA) slides. Using a retrospective cohort of early stage NSCLC patients (Cohort #1, n = 70), we constructed a supervised classification model involving the most predictive features associated with disease recurrence. This model was then validated on two independent sets of early stage NSCLC patients, Cohort #2 (n = 119) and Cohort #3 (n = 116). The model yielded an accuracy of 81% for prediction of recurrence in the training Cohort #1, 82% and 75% in the validation Cohorts #2 and #3 respectively. A multivariable Cox proportional hazard model of Cohort #2, incorporating gender and traditional prognostic variables such as nodal status and stage indicated that the computer extracted histomorphometric score was an independent prognostic factor (hazard ratio = 20.81, 95% CI: 6.42–67.52, P < 0.001).

Nomograms for predicting recurrence and survival of invasive pathological stage IA non-small cell lung cancer treated by video assisted thoracoscopic surgery lobectomy

BACKGROUND

A considerable portion of pathological stage (p-stage) IA non-small cell lung cancer (NSCLC) patients suffered from death and recurrence after video assisted thoracoscopic surgery (VATS) lobectomy. The purpose of our study was to develop nomograms to predict which subgroup patients were more likely to suffer from recurrence or death.

METHODS

Data of invasive p-stage IA NSCLC patients who underwent VATS lobectomy at Peking University People's Hospital from September 2006 to April 2014 were analyzed. Multivariate Cox proportional hazards regression was used to develop nomograms. The performance of the nomograms was evaluated by Harrell's concordance index (C-index), calibration plots and risk group stratification.

RESULTS

A total of 422 patients with NSCLC of invasive p-stage IA were included in the study. The median follow-up time was 40 months. Age [hazards ratio (HR) =1.067, 95% confidential interval (CI): 1.006-1.131], lymphovascular invasion (LVI) (HR=4.062, 95% CI: 1.278-12.912) and differentiation (HR =5.747, 95% CI: 2.151-15.353) were independent prognostic factors to predict overall survival (OS). Tumor diameter (HR =3.299, 95% CI: 1.814-6.001), LVI (HR =3.260, 95% CI: 1.221-8.708) and differentiation (HR =3.607, 95% CI: 1.776-7.327) were independent predictors of recurrence free survival (RFS). The nomogram for predicting OS demonstrated stronger discriminatory power than the 7th and 8th T stage systems (C-index: 0.894 for the nomogram, 0.700 for the 7th T stage and 0.742 for the 8th T stage). Likewise, the C-index of the nomogram for predicting RFS was higher than that of the 7th and 8th T stage systems (0.838 for the nomogram, 0.670 for the 7th T stage and 0.723 for the 8th T stage).

CONCLUSIONS

We developed nomograms that could predict individual accurate prognosis for invasive p-stage IA NSCLC patients after VATS lobectomy. Risk stratification by the nomograms might guide further adjuvant chemotherapy and follow-up.