Reconsidering N component of cancer staging for T1-2N0-2M0 small-cell lung cancer: a retrospective study based on multicenter cohort.

BACKGROUND: The current nodal (pN) classification still has limitations in stratifying the prognosis of small cell lung cancer (SCLC) patients with pathological classifications T1-2N0-2M0. Thus. This study aimed to develop and validate a modified nodal classification based on a multicenter cohort. MATERIALS AND METHODS: We collected 1156 SCLC patients with pathological classifications T1-2N0-2M0 from the Surveillance, Epidemiology, and End Results database and a multicenter database in China. The X-tile software was conducted to determine the optimal cutoff points of the number of examined lymph nodes (ELNs) and lymph node ratio (LNR). The Kaplan-Meier method, the Log-rank test, and the Cox regression method were used in this study. We classified patients into three pathological N modification categories, new pN#1 (pN0-#ELNs > 3), new pN#2 (pN0-#ELNs ≤ 3 or pN1-2-#LNR ≤ 0.14), and new pN#3 (N1-2-#LNR > 0.14). The Akaike information criterion (AIC), Bayesian Information Criterion, and Concordance index (C-index) were used to compare the prognostic, predictive ability between the current pN classification and the new pN component. RESULTS: The new pN classification had a satisfactory effect on survival curves (Log-rank P < 0.001). After adjusting for other confounders, the new pN classification could be an independent prognostic indicator. Besides, the new pN component had a much more accurate predictive ability in the prognostic assessment for SCLC patients of pathological classifications T1-2N0-2M0 compared with the current pN classification in the SEER database (AIC: 4705.544 vs. 4731.775; C-index: 0.654 vs. 0.617, P < 0.001). Those results were validated in the MCDB from China. CONCLUSIONS: The multicenter cohort developed and validated a modified nodal classification for SCLC patients with pathological category T1-2N0-2M0 after surgery. Besides, we propose that an adequate lymph node dissection is essential; surgeons should perform and consider the situation of ELNs and LNR when they evaluate postoperative prognoses of SCLC patients.

The postoperative prognosis of skip-N2 metastasis is favorable in small-cell lung carcinoma patients with pathological N2 classification: a propensity-score-adjusted retrospective multicenter study.

Background: The study on skip-N2 metastasis in small-cell lung cancer (SCLC) is lacking. Therefore, this study aimed to explore the prognostic significance of skip-N2 metastasis based on a multicenter cohort. Methods: We collected 176 SCLC patients with pathological categories T1-4N1-2M0 from four hospitals in China. Survival curves were drawn through the Kaplan-Meier method and compared by the log-rank test. The Cox regression method was used to calculate the hazard ratio (HR) and 95% confidence interval of the characteristics for cancer-specific survival (CSS). Two propensity-score methods were used to reduce the bias, including the inverse probability of treatment weighting (IPTW) and propensity-score matching (PSM). Results: This multicenter database included 64 pN1 patients, 63 non-skip-N2 cases, and 49 skip-N2 cases. Skip-N2 and the non-skip-N2 patients had gap CSS rates (skip-N2 no versus yes: 41.0% versus 62.0% for 1-year CSS, 32.0% versus 46.0% for 2-year CSS, and 20.0% versus 32.0% for 3-year CSS). After PSM, there were 32 pairs of patients to compare survival differences between N2 and skip-N2 diseases, and 34 pairs of patients to compare prognostic gaps between N1 and skip-N2 diseases, respectively. The results of IPTW and PSM both suggested that skip-N2 cases had better survival outcomes than the non-skip-N2 cases (IPTW-adjusted HR = 0.578; PSM-adjusted HR = 0.510; all log-rank p < 0.05). Besides, the above two analytic methods showed no difference in prognoses between pN1 and skip-N2 diseases (all log-rank p > 0.05). Conclusions: Skip-N2 patients were confirmed to have a better prognosis than non-skip-N2 patients. Besides, there was no survival difference between pN1 and skip-N2 cases. Therefore, we propose that the next tumor-node-metastasis staging system needs to consider the situation of skip metastasis with lymph nodes in SCLC.

A clinical risk model for assessing the survival of patients with stage IA-IIA non-small cell lung cancer after surgery.

Background: The survival of patients with stage IA-IIA non-small cell lung cancer (NSCLC) after surgery is heterogeneous. This study aimed to construct a prognostic risk model to predict the overall survival (OS) of these patients. Methods: Data from patients (n=9,914) from the Surveillance Epidemiology and End Results (SEER) database were analyzed. The cases were randomly divided into the training and the validation groups. Patients from the Shanghai Pulmonary Hospital (n=270) were also included as an external cohort. Independent significant factors affecting survival in the training cohort were used to construct a nomogram. The precision was evaluated using the concordance index (C-index) and calibration plots. The X-tile software was used to confirm the optimal cut-off value to classify the patients. Results: Sex, age at diagnosis, tumor size, visceral pleura invasion (VPI), tumor grade, and the number of examined lymph nodes were deemed independent prognostic factors and were selected to establish the nomogram. The C-indices of the nomogram for predicting OS were 0.671 [95% confidence interval (CI): 0.653-0.689] in the training group, and 0.668 (95% CI: 0.650-0.687) and 0.707 (95% CI: 0.651-0.763) in the validation and the testing groups, respectively. The cut-off value of risk points was 106.0, which stratified the patients into high-risk and low-risk groups. The high-risk patients had shorter 5-year OS than low-risk patients (P<0.001). Conclusions: The established nomogram could evaluate the survival in patients with stage IA-IIA NSCLC after surgery and may provide prognostic information for clinicians to make decisions in the management of adjuvant therapy.

The characterization of tumor microenvironment infiltration and the construction of predictive index based on cuproptosis-related gene in primary lung adenocarcinoma.

Objective: We aimed to use the cancer genome atlas and gene expression omnibus databases to explore the characterization of tumor microenvironment (TME) infiltration and construct a predictive index of prognosis and treatment effect based on cuproptosis-related genes (CRGs) in primary lung adenocarcinoma (LUAD). Methods: We described the alterations of CRGs in 954 LUAD samples from genetic and transcriptional fields and evaluated their expression patterns from three independent datasets. We identified two distinct molecular subtypes and found that multi-layer CRG alterations were correlated with patient clinicopathological features, prognosis, and TME cell infiltrating characteristics. Then, a cuproptosis scoring system (CSS) for predicting the prognosis was constructed, and its predictive capability in LUAD patients was validated. Results: Two molecular subtypes of cuproptosis (Copper Genes cluster A and cluster B) in LUAD were identified. Copper Genes cluster B had better survival than those with Copper Genes cluster A (p <0.01). Besides, we found that the infiltration of activated CD4+ T cells, natural killer T cells, and neutrophils was stronger in cluster A than in cluster B. Then, we constructed a highly accurate CSS to predict the prognosis, targeted therapy effect, and immune response. Compared with the low-CSS subgroup, the mutations of the TP53, MUC16, and TTN genes were more common in the high-CSS subgroup, while the mutation of TP53, TTN, and CSMD3 genes were more common in the low-CSS subgroup than in high-CSS subgroup. The low-score CSS group had an inferior survival than high-score CSS group (p <0.01). In addition, CSS presented good ability to predict the immune response (area under curve [AUC], 0.726). Moreover, AZD5363 and AZD8186 were the inhibitors of AKT and PI3K, respectively, and had lower IC50 and AUC in the low-score CSS group than it in the high-score CSS group. Conclusions: CRGs are associated with the development, TME, and prognosis of LUAD. Besides, a scoring system based on CRGs can predict the efficacy of targeted drugs and immune response. These findings may improve our understanding of CRGs in LUAD and pave a new path for the assessment of prognosis and the development of more effective targeted therapy and immunotherapy strategies.

The Clinical and Prognostic Characteristics of Primary Salivary Gland-Type Carcinoma in the Lung: A Population-Based Study.

This study aimed to explore the clinical and prognostic characteristics of primary salivary gland-type carcinoma (SGC). The entire cohort from the Surveillance, Epidemiology, and End Results database was used to calculate the SGC proportion. In total, 253,096 eligible patients, including 165,715 adenocarcinomas (ADCs), 87,062 squamous cell carcinomas (SCCs), and 319 SGCs, were selected to perform survival analyses. The data of 42 SGC patients from our hospital showed postoperative survival. Overall survival (OS) curves for different histological and surgical types were presented. The proportion of primary SGCs was 0.8 per 1000 patients. Patients with age ≤ 64 years old had a much higher proportion of SGC than those patients with age >64 years old. After adjusting for other confounders, among ADCs, SCCs, and SGC, SGCs had the best prognosis (HR 0.361, p < 0.001). Moreover, the 5-year OS rates of SGC patients were 55% and 7% in the group with surgery or without surgery, respectively (p < 0.001). The data of 42 patients from our hospital also showed a good survival of SGCs. Lobectomy improved the survival of SGCs significantly (adjusted HR 0.439, p = 0.016). In conclusion, pulmonary SGCs had the best prognosis among ADCs, SCCs, and SGCs. In addition, lobectomy could further improve the prognostic outcomes of SGCs.

The Construction and Validation of Nomogram to Predict the Prognosis with Small-Cell Lung Cancer Followed Surgery.

This study constructed and validated a prognostic model to evaluate the survival of small-cell lung cancer (SCLC) patients following surgery, and shed light on the strategy of postoperative radiotherapy. A total of 882 patients from Shanghai Pulmonary Hospital and the Surveillance, Epidemiology and End Results database after lung resection were selected. Multivariable Cox analysis was used to identify the indicators affecting long-term survival in patients. A nomogram was constructed to predict the prognosis of eligible patients. Indices of concordance (C-index) was used to access the predictive ability of cancer-specific survival (CSS) for the prognostic model. CSS discrimination in the prognostic model was comparable in the training and validation cohorts (C-index = 0.637[NORAD-T], 0.660[NORAD-V], 0.656[RAD] and 0.627[our hospital], respectively. Stratification based on the cutoff value of the nomogram yielded low- and high-risk subgroups in four cohorts. For patients in the high-risk group, postoperative radiotherapy was considered a survival-promoting strategy (unadjusted HR 0.641, 95% CI 0.469-0.876, p = 0.0046). In the low-risk group, however, the implementation of radiotherapy barely had an influence on CSS. In conclusion, the nomogram we constructed and validated could predict the prognosis of SCLC patients followed surgery and identify high-risk patients who were likely to benefit from postoperative radiotherapy.

The Difference and Significance of Parietal Pleura Invasion and Rib Invasion in Pathological T Classification With Non-Small Cell Lung Cancer.

Objective: This study was to explore the difference and significance of parietal pleura invasion and rib invasion in pathological T classification with non-small cell lung cancer. Methods: A total of 8681 patients after lung resection were selected to perform analyses. Multivariable Cox analysis was used to identify the mortality differences in patients between parietal pleura invasion and rib invasion. Eligible patients with chest wall invasion were re-categorized according to the prognosis. Cancer-specific survival curves for different pathological T (pT) classifications were presented. Results: There were 466 patients considered parietal pleura invasion, and 237 patients served as rib invasion. Cases with rib invasion had poorer survival than those with the invasion of parietal pleura (adjusted hazard ratio [HR]= 1.627, P =0.004). In the cohort for parietal pleura invasion, patients with tumor size ≤5cm reached more satisfactory survival outcomes than patients with tumor size >5cm (unadjusted HR =1.598, P =0.006). However, there was no predictive difference in the cohort of rib invasion. The results of the multivariable analysis revealed that the mortality with parietal pleura invasion plus tumor size ≤5cm were similar to patients with classification pT3 (P =0.761), and patients for parietal pleura invasion plus tumor size >5cm and pT4 had no stratified survival outcome (P =0.809). Patients identified as rib invasion had a poorer prognosis than patients for pT4 (P =0.037). Conclusions: Rib invasion has a poorer prognosis than pT4. Patients with parietal pleura invasion and tumor size with 5.1-7.0cm could be appropriately up-classified from pT3 to pT4.

Incidence and survival analyses for occult lung cancer between 2004 and 2015: a population-based study.

BACKGROUND: This study aimed to investigate the incidence and long-term survival outcomes of occult lung cancer between 2004 and 2015. METHODS: A total of 2958 patients were diagnosed with occult lung cancer in the 305,054 patients with lung cancer. The entire cohort was used to calculate the crude incidence rate. Eligible 52,472 patients (T1-xN0M0, including 2353 occult lung cancers) were selected from the entire cohort to perform survival analyses after translating T classification according to the 8th TNM staging system. Cancer-specific survival curves for different T classifications were presented. RESULTS: The crude incidence rate of occult lung cancer was 1.00 per 100 patients, and it was reduced between 2004 and 2015 [1.4 per 100 persons in 2004; 0.6 per 100 persons in 2015; adjusted risk ratio = 0.437, 95% confidence interval (CI) 0.363-0.527]. In the survival analysis, there were 2206 death events in the 2353 occult lung cancers. The results of the multivariable analysis revealed that the prognoses with occult lung cancer were similar to patients with stage T3N0M0 (adjusted hazard ratio = 1.054, 95% CI 0.986-1.127, p = 0.121). Adjusted survival curves presented the same results. In addition, adjusted for other confounders, female, age ≤ 72 years, surgical treatment, radiotherapy, adenocarcinoma, and non-squamous and non-adenocarcinoma non-small cell carcinoma were independent protective prognostic factors (all p < 0.05). CONCLUSIONS: Occult lung cancer was uncommon. However, the cancer-specific survival of occult lung cancer was poor, therefore, we should put the assessment of its prognoses on the agenda. Timely surgical treatment and radiotherapy could improve survival outcomes for those patients. Besides, we still need more research to confirm those findings.