Clinical characteristics of T2 stage NSCLC patients in different groups
Variations in clinical characteristics between the MBI/(P/ATL) and non-MBI/(P/ATL) groups were prominently attributed to the diameter linked to the T2 stage (Table 1). Notable disparities existed in gender distribution, with the MBI/(P/ATL) group demonstrating a higher proportion of males (58.4%/55.3% vs. 53.4%) and a heightened occurrence of Squamous Cell Carcinoma (46.0%/40.8% vs. 32.7%). Significantly, a larger proportion of primary sites in the main bronchus were identified in the MBI/(P/ATL) group (14.1%/7.8% vs. 1.7%), accompanied by a more advanced histologic grading (p<0.001).
The MBI/(P/ATL) group, especially the P/ATL subgroup, exhibited higher incidences of lymph nodes (N0: 41.8%/34.0% vs. 53.0%). Regarding treatment modalities, the MBI/(P/ATL) group displayed a stronger propensity to undergo chemotherapy (48.0%/51.1% vs. 41.7%) and radiation therapy (43.2%/46.8% vs. 38.2%). Compared to MBI/None group, the incidence of surgery was markedly lower in the P/ATL subgroup (26.5% vs. 49.9%/46.1%). Moreover, we counted those who underwent surgery and found that compared to surgery alone, the MBI/(P/ATL) group experienced a much higher proportion of preoperative induction therapy or postoperative adjuvant therapy than the non-MBI/(P/ATL) group (41.3%/54.7% vs. 36.6%).
In relation to tumor diameter, the non-MBI/(P/ATL) group had a larger diameter due to the incorporation of cases surpassing 3cm. In general, profound differences in clinical characteristics were observed between the groups, with the MBI/(P/ATL) group manifesting extensive disparities, especially within the P/ATL subgroup, compared to the non-MBI/(P/ATL) group.
Through KaplanMeier survival analysis, it was discerned that the OS for the MBI (Diameter>3) group was adversely impacted in comparison to the non-MBI/(P/ATL) group (p=0.012) (Fig.1A). Notably, regardless of the diameter size, the OS for the non-MBI/(P/ATL) group was significantly superior to that of the P/ATL group (p<0.0001) (Fig.1B).
KaplanMeier analysis of patients with different T2 types of NSCLC. (A,B) KaplanMeier analysis of overall survival (OS) in the Pneumonia or Atelectasis (P/ATL) and Main Bronchus Infiltration (MBI) groups versus the groups without P/ATL and MBI, prior to propensity score matching (PSM). (C,D) KaplanMeier analysis of OS in the P/ATL and MBI groups versus the non-MBI and P/ATL groups following PSM. (E,F) KaplanMeier analysis of cancer-specific survival (CSS) in the P/ATL and MBI groups versus the non-MBI and P/ATL groups after PSM.
Given the pronounced heterogeneity in clinical characteristics among the three groups, we adopted the Propensity Score Matching (PSM) method to mitigate the impact of diverse background variables, thereby harmonizing potential prognostic factors between the P/ATL and MBI groups compared to the non-MBI/(P/ATL) group. This approach ensured that the p-values from t-tests or chi-square tests for all clinical characteristics between the respective groups exceeded 0.1, indicating a balanced comparison (Supplementary data 1). Following this adjustment, we analyzed OS and cancer-specific survival (CSS) using the KM method for the P/ATL vs. None groups and the MBI vs. None groups, respectively. Our findings revealed that the P/ATL group exhibited a significantly poorer prognosis than the None group, with p of 0.00015 for OS and 0.00021 for CSS (Fig.1C,E). Conversely, the MBI group's prognosis was marginally inferior compared to the None group, with p of 0.037 for OS and 0.016 for CSS (Fig.1D,F).
Our findings indicate that at the T2 stage, both the MBI and P/ATL groups demonstrate an elevated risk for lymph node metastasis. To ascertain whether MBI and P/ATL act as independent risk factors for these lymph node metastase, we employed a multifactorial logistic regression analysis. The results illuminated those individuals in the MBI/(P/ATL) group had a notably higher risk of lymph node metastasis compared to those in the non-MBI/(P/ATL) group. In detail, MBI was found to be an independent risk factor for lymph node metastasis (OR=1.69, 95% CI 1.551.85, p<0.001), as was P/ATL (OR=2.10, 95% CI 1.932.28, p<0.001) (Table 2).
To evaluate the optimal treatment for NSCLC patients with two specific types of T2 tumors, we integrated seven treatment modalities: None, Radiation Therapy Alone, Chemotherapy Alone, Radiation+Chemotherapy, Surgery Alone, Initial Surgery Followed by Adjuvant Treatment, and Induction Therapy Followed by Surgery. We conducted a multifactorial Cox regression analysis of OS to assess the prognostic impact of these treatments in patients with P/ATL and MBI, respectively, using Surgery Alone as the reference group (Table 3). The results indicated that surgical treatments significantly outperformed both Radiotherapy Alone and Chemotherapy Alone, as well as the combination of Radiotherapy and Chemotherapy, in both subgroups. Specifically, in patients with MBI, Initial Surgery Followed by Adjuvant Treatment (HR=0.77, 95% CI 0.670.90, p=0.001) and Induction Therapy Followed by Surgery (HR=0.65, 95% CI 0.480.87, p=0.003) were significantly more effective than Surgery Alone. Conversely, for patients with P/ATL, neither Initial Surgery Followed by Adjuvant Treatment (HR=1.17, 95% CI 0.991.37, p=0.067) nor Induction Therapy Followed by Surgery (HR=1.05, 95% CI 0.781.40, p=0.758) showed any advantage over Surgery Alone.
Given the limited therapeutic options for patients with distant metastases, we analyzed the KM survival with different therapeutic strategies for patients with P/ATL and MBI at stages N0-1M0 and N2-3M0, respectively. In patients with MBI at the N2-3M0 stage, preoperative Induction Therapy significantly improved prognosis, illustrating a marked enhancement in outcomes. For the N0-1M0 stage in MBI patients, while there was a clear improvement in median survival with preoperative Induction Therapy, this improvement did not reach statistical significance. Additionally, postoperative Adjuvant Therapy substantially improved outcomes over Surgery Alone for MBI patients across both N0-1M0 and N2-3M0 stages (Fig.2A,B). Conversely, these treatments did not yield significant benefits for patients with P/ATL (Fig.2C,D). Moreover, in both subgroups for the N0-1M0 stage, prognosis following Surgery Alone was significantly better than with Chemoradiotherapy, whereas at the N2-3M0 stage, Surgery Alone did not show superiority over Chemoradiotherapy in terms of prognosis (Fig.2).
KaplanMeier analysis comparing the effectiveness of various treatment modalities in patients with Main Bronchus Infiltration (MBI) or Pneumonia/Atelectasis (P/ATL) based on nodal involvement. (A) Overall Survival (OS) associated with different treatment approaches in MBI patients classified as N0-1M0. (B) OS associated with different treatment approaches in MBI patients classified as N2-3M0. (C) OS associated with different treatment approaches in P/ATL patients classified as N0-1M0. (D) OS associated with different treatment approaches in P/ATL patients classified as N2-3M0.
Given the potential notable disparities in clinicopathologic variables and prognoses across the MBI and P/ATL subgroups, we aimed to delve deeper into the varying impacts that different factors might exhibit on mortality within these subgroups. Accordingly, multifactorial logistic regression was applied to analyze the 5-year OS rate within the MBI and P/ATL subgroups. In the MBI group, sex, histologic type, grade, age, N stage, M stage, site, marital status and treatment type were identified as independent factors associated with 5-year OS. In the P/ATL group, histologic type, grade, age, race, N stage, M stage and treatment type were recognized as independent factors associated with 5-year OS (Supplementary data 2).
We incorporated the factors independently correlated with 5-year OS from the MBI and P/ATL groups for prognostic modeling. The patients were randomized into training and test data groups at a 7:3 ratio. Subsequently, the best parameters for each model were adjusted and training was conducted within the training set to optimize performance. In the validation set, we performed ROC and DCA analyses of MBI and P/ATL groups for all models (Fig.3A,B). The XGBoost model also demonstrated optimal AUC with 0.814 and 0.853 respectively in both MBI and P/ATL groups, and the DCA curves further affirmed that the XGBoost model secures a higher net benefit compared to other models across varying threshold ranges (Fig.3C,D). The specific performance of each model in the test set is shown in Supplementary Data 3. In addition, we performed the Delong test and found that the XGBoost model significantly outperforms the rest of the models in both MBI and P/ATL (Supplementary Data 4).
Receiver Operating Characteristic Curve (ROC) and Decision Curve Analysis (DCA) analyses of Main Bronchus Infiltration (MBI) and Pneumonia/Atelectasis (P/ATL) groups. (A) ROC curves for each model in the MBI group. (B) ROC curves for each model in the P/ATL group. (C) DCA curves for each model in the MBI group. (D) DCA curves for each model in the P/ATL group.
Consequently, the calibration curves for the XGBoost model in both the MBI and P/ATL groups within the test set were also plotted, revealing commendable predictive performance of the model (Fig.4A,B). Additionally, we scrutinized the importance scores of the variables in both models (Fig.4C,D).
Calibration curves and feature significance plots of the XGBoost model for Main Bronchus Infiltration (MBI) and Pneumonia/Atelectasis (P/ATL) groups. (A) Calibration curve of the XGBoost model for the MBI group. (B) Calibration curve of the XGBoost model for the P/ATL group. (C) Feature significance plot of the XGBoost model for the MBI group. (D) Feature significance plot of the XGBoost model for the P/ATL group.
To assist researchers and clinicians in utilizing our prognostic model, we developed user-friendly web applications for stage T2 NSCLC MBI and P/ATL groups (Fig.5A,B), respectively. The web interface allows users to input clinical features of new samples, and the application can then help predict survival probabilities and survival status based on the patient's information. And the model can help clinicians to develop appropriate treatment strategies for this subgroup of patients by first selecting other parameters of a particular patient and focusing on the change of their 5-year survival by adjusting different treatments. For example, a 6574year old male with T2N3M0 stage lung adenocarcinoma, graded as grade III located in the upper lobe of a married MBI patient, his 5-year OS was 19.07% if he received Chemoradiotherapy, 23.83% if he received only surgery, and 5-year OS if he received Induction therapy followed by surgery was 35.51%, and 31.28% for those who received Initial surgery followed by adjuvant treatment.
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