Metastasis Patterns and Prognosis of Octogenarians with NSCLC: A Population-based Study

Identification of lung adenocarcinoma subtypes and a prognostic signature based on activity changes of the hallmark and immunologic gene sets

Background

Lung adenocarcinoma (LUAD) has a complex tumor heterogeneity. Our research attempts to clearness LUAD subtypes and build a reliable prognostic signature according to the activity changes of the hallmark and immunologic gene sets.

Methods

According to The Cancer Genome Atlas (TCGA) - LUAD dataset, changes in marker and immune gene activity were analyzed, followed by identification of prognosis-related differential gene sets (DGSs) and their related LUAD subtypes. Survival analysis, correlation with clinical characteristics, and immune microenvironment assessment for subtypes were performed. Moreover, the differentially expressed genes (DEGs) between different subtypes were identified, followed by the construction of a prognostic risk score (RS) model and nomogram model. The tumor mutation burden (TMB) and tumor immune dysfunction and exclusion (TIDE) of different risk groups were compared.

Results

Two LUAD subtypes were determined according to the activity changes of the hallmark and immunologic gene sets. Cluster 2 had worse prognosis, more advanced tumor and clinical stages than cluster 1. Moreover, a prognostic RS signature was established using two LUAD subtype-related DEGs, which could stratify patients at different risk levels. Nomogram model incorporated RS and clinical stage exerted good prognostic performance in LUAD patients. A shorter survival time and higher TMB were observed in the high-risk patients.

Conclusions

Our findings revealed that our constructed prognostic signature could exactly predict the survival status of LUAD cases, which was helpful in predicting the prognosis and guiding personalized therapeutic strategies for LUAD.

Prognostic factors and survival prediction of resected non-small cell lung cancer with ipsilateral pulmonary metastases: a study based on the Surveillance, Epidemiology, and End Results (SEER) database

BACKGROUND

Prognostic factors and survival outcomes of non-small cell lung cancer (NSCLC) with Ipsilateral pulmonary metastasis (IPM) are not well-defined. Thus, this study intended to identify the prognostic factors for these patients and construct a predictive nomogram model.

METHODS

One thousand, seven hundred thirty-two patients with IPM identified between 2000 to 2019 were from the Surveillance, Epidemiology, and End Results (SEER) database. Independent prognostic factors were identified using multivariate Cox regression analyses. Nomograms were constructed to predict the overall survival (OS), C-index, the area under the curve (AUC), and the calibration curve to determine the predictive accuracy and discrimination; the decision curve analysis was used to confirm the clinical utility.

RESULTS

Patients were randomly divided into training (n = 1213) and validation (n = 519) cohorts. In the training cohort, the multivariable analysis demonstrated that age, sex, primary tumor size, N status, number of regional lymph nodes removed, tumor grade, and chemotherapy were independent prognostic factors for IPM. We constructed a 1-year, 3-year, and 5-year OS prediction nomogram model using independent prognostic factors. The C-index of this model for OS prediction was 0.714 (95% confidence interval [CI], 0.692 to 0.773) in the training cohort and 0.695 (95% CI, 0.660 to 0.730) in the validation cohort. Based on the AUC of the receiver operating characteristic analysis, calibration plots, and decision curve analysis, we concluded that the prognosis model of IPM exhibited excellent performance. Patients with total nomogram points greater than 96 were considered high-risk.

CONCLUSION

We constructed and internally validated a nomogram to predict 1-year, 3-year, and 5-year OS for NSCLC patients with IPM according to independent prognostic factors. This nomogram demonstrated good calibration, discrimination, clinical utility, and practical decision-making effects for the prognosis of NSCLC patients with IPM.

Survival Outcomes of Sublobectomy and Lobectomy in Elderly Patients with Peripheral Solid-Dominant Non-small Cell Lung Cancer

BACKGROUND

According to the JCOG0802 study, there were many non-cancer-related deaths in the lobectomy group. Meanwhile, the median age of the enrolled patients in the JCOG0802 study was 67 years old. Whether this difference in perioperative outcomes and survival outcomes is related to age remains unknown. We aim to investigate whether the sublobectomy was comparable to lobectomy in elderly (≥ 75 years old) patients with peripheral solid-dominant [50% ≤ consolidation tumor ratio (CTR) ≤ 1] and diameter ≤ 2 cm non-small cell lung cancer (NSCLC).

METHODS

We retrospectively included 10,830 patients who underwent surgery treatment at two large-volume medical centers, Taizhou Hospital of Zhejiang Province and Shanghai Chest Hospital, from January 2016 to January 2018. Of these, 164 patients aged ≥ 75 years, tumor ≤ 2 cm, and 50% ≤ CTR ≤ 1 who received lobectomy or sublobectomy were included in our study. The perioperative outcomes, survival analyses, analysis of death patterns, tumor recurrence patterns, and Cox regression analyses were performed.

RESULTS

On perioperative outcomes, sublobectomy was associated with a shorter operation time (p < 0.001), and in terms of survival outcomes, the 5-year overall survival (OS, p = 0.85) and 5-year disease-free surivial (DFS, p = 0.58) did not differ significantly between the two groups. The Cox regression analyses showed that CTR value, visceral pleural infiltration, and smoking were independent risk factors for worse OS. Furthermore, tumor recurrence pattern and death patterns between the two groups did not differ significantly.

CONCLUSIONS

Sublobectomy could achieve superior perioperative outcomes and equivalent oncological efficacy in comparison with lobectomy in elderly patients (≥ 75 years old) with peripheral solid-dominant and diameter ≤ 2 cm NSCLC.

Development and validation of nomograms to predict early death for elderly lung cancer patients

Background

Due to the aging of society, the average age of LC (lung cancer) patients has increased in recent years. The purpose of this study was to determine the risk factors and develop nomograms to predict the probability of early death (dead in three months) for elderly (≥ 75 years old) LC patients.

Methods

Data of elderly LC patients were obtained from the SEER database by using the SEER stat software. All patients were randomly divided into a training cohort and a validation cohort in a ratio of 7:3. The risk factors of all-cause early and cancer-specific early death were identified by univariate logistic regression and backward stepwise multivariable logistic regression in the training cohort. Then, risk factors were used to construct nomograms. The performance of nomograms was validated by receiver operating curves (ROC), calibration curves, and decision curve analysis (DCA) in the training cohort and validation cohort.

Results

A total of 15,057 elderly LC patients in the SEER database were included in this research and randomly divided into a training cohort (n = 10,541) and a validation cohort (n = 4516). The multivariable logistic regression models found that there were 12 independent risk factors for the all-cause early death and 11 independent risk factors for the cancer-specific early death of the elderly LC patients, which were then integrated into the nomograms. The ROC indicated that the nomograms exhibited high discriminative ability in predicting all-cause early (AUC in training cohort = 0.817, AUC in validation cohort = 0.821) and cancer-specific early death (AUC in training cohort = 0.824, AUC in validation cohort = 0.827). The calibration plots of the nomograms were close to the diagonal line revealing that there was good concordance between the predicted and practical early death probability in the training and validation cohort. Moreover, the results of DCA analysis indicated that the nomograms had good clinical utility in predicting early death probability.

Conclusion

The nomograms were constructed and validated to predict the early death probability of elderly LC patients based on the SEER database. The nomograms were expected to have high predictive ability and good clinical utility, which may help oncologists develop better treatment strategies.

The Effect of immunotherapy on oligometastatic non-small cell lung cancer patients by sites of metastasis

Introduction

The efficacy of immunotherapy for treatment of patients with oligometastatic non-small cell lung cancer (NSCLC) at different metastatic sites remains controversial. We investigated the effect of different metastatic sites on immunotherapy for oligometastatic NSCLC following local treatment (LT).

Methods

We retrospectively analyzed patients with oligometastatic NSCLC from the latest 2018 registry on the SEER Stat software (8.3.9. Version) and a Chinese single-center cohort. The effects of immunotherapy on OS (overall survival) and CSS (cancer specific survival) were estimated for patients with different metastatic sites.

Results

A total of 483 patients in the SEER-18 database and 344 patients in the single-center cohort were included. Immunotherapy was significantly correlated with improved OS (SEER: Hazard ratio 0.754, 95% CI 0.609–0.932; P=0.044; China: Hazard ratio 0.697, 95% CI 0.542–0.896; P=0.005) and CSS (SEER: Hazard ratio 0.743, 95% CI 0.596–0.928; P=0.009; China: Hazard ratio 0.725, 95% CI 0.556–0.945; P=0.018). Subgroup analysis showed that OS was improved after immunotherapy in the BRM (SEER: Hazard ratio 0.565, 95% CI 0.385–0.829; P=0.004; China: Hazard ratio 0.536, 95% CI 0.312–0.920; P=0.024) and MOM (SEER: Hazard ratio 0.524, 95% CI 0.290–0.947; P=0.032; China: Hazard ratio 0.469, 95% CI 0.235–0.937; P=0.032) subgroups, but not in the BOM (SEER: P=0.334; China: P=0.441), LIM (SEER: P=0.301; China: P=0.357), or OTM (SEER: P=0.868; China: P=0.489) subgroups.

Conclusions

This study showed that immunotherapy conferred survival benefits on patients with oligometastatic NSCLC. Our subgroup analysis suggested that patients with oligometastatic NSCLC in the brain or multiple organs may particularly benefit from aggressive front-line therapies.

A novel epithelial-mesenchymal transition (EMT)-related gene signature of predictive value for the survival outcomes in lung adenocarcinoma

Lung adenocarcinoma (LUAD) is a remarkably heterogeneous and aggressive disease with dismal prognosis of patients. The identification of promising prognostic biomarkers might enable effective diagnosis and treatment of LUAD. Aberrant activation of epithelial-mesenchymal transition (EMT) is required for LUAD initiation, progression and metastasis. With the purpose of identifying a robust EMT-related gene signature (E-signature) to monitor the survival outcomes of LUAD patients. In The Cancer Genome Atlas (TCGA) database, least absolute shrinkage and selection operator (LASSO) analysis and cox regression analysis were conducted to acquire prognostic and EMT-related genes. A 4 EMT-related and prognostic gene signature, comprising dickkopf-like protein 1 (DKK1), lysyl oxidase-like 2 (LOXL2), matrix Gla protein (MGP) and slit guidance ligand 3 (SLIT3), was identified. By the usage of datum derived from TCGA database and Western blotting analysis, compared with adjacent tissue samples, DKK1 and LOXL2 protein expression in LUAD tissue samples were significantly higher, whereas the trend of MGP and SLIT3 expression were opposite. Concurrent with upregulation of epithelial markers and downregulation of mesenchymal markers, knockdown of DKK1 and LOXL2 impeded the migration and invasion of LUAD cells. Simultaneously, MGP and SLIT3 silencing promoted metastasis and induce EMT of LUAD cells. In the TCGA-LUAD set, receiver operating characteristic (ROC) analysis indicated that our risk model based on the identified E-signature was superior to those reported in literatures. Additionally, the E-signature carried robust prognostic significance. The validity of prediction in the E-signature was validated by the three independent datasets obtained from Gene Expression Omnibus (GEO) database. The probabilistic nomogram including the E-signature, pathological T stage and N stage was constructed and the nomogram demonstrated satisfactory discrimination and calibration. In LUAD patients, the E-signature risk score was associated with T stage, N stage, M stage and TNM stage. GSEA (gene set enrichment analysis) analysis indicated that the E-signature might be linked to the pathways including GLYCOLYSIS, MYC TARGETS, DNA REPAIR and so on. In conclusion, our study explored an innovative EMT based prognostic signature that might serve as a potential target for personalized and precision medicine.

The nomograms for predicting overall and cancer-specific survival in elderly patients with early-stage lung cancer: A population-based study using SEER database

Purpose

Lung cancer is the leading cause of death from cancer and the number of operable elderly lung cancer patients is increasing, with advanced age being associated with a poorer prognosis. However, there is no easy and comprehensive prognostic assessment method for these patients.

Methods

Clinicopathological data of patients aged 65 years or older with TNM stage I-II lung cancer from 2004 to 2018 were downloaded from the SEER database. Patients from 2004 to 2015 were randomized into a training group (n = 16,457) and a validation group (n = 7,048). Data from 2016 to 2018 (n = 6,231) were used for external validation. Two nomogram prognostic models were created after independent prognostic factors connected to both overall survival (OS) and cancer-specific survival (CSS) in the training set by using univariate and multivariate Cox proportional hazards regression analysis. In turn, overall survival (OS) and cancer-specific survival (CSS) were predicted for patients at 1, 3, and 5 years. Based on the concordance index (C-index), calibration curves, area under the receiver operating characteristics (ROC) curve (AUC), the time-dependent area under the ROC curve, the validity, accuracy, discrimination, predictive ability, and clinical utility of the models were evaluated. Decision curve analysis (DCA) was used to assess the clinical value of the models.

Results

A total of 29,736 patients were included. Univariate and multivariate analyses suggested that age, race, gender, marriage, disease grade, AJCC stage, T-stage, surgery, radiotherapy, chemotherapy, and tumor size were independent risk factors for patient prognosis. These 11 variables were included in nomogram to predict OS and CSS of patients. C-indexes of OS for the training, validation and external validation sets were 0.730 (95% CI, 0.709-0.751), 0.734 (95% CI, 0.722-0.746), and 0.750 (95% CI, 0.734-0.766), respectively. The AUC results for the training and validation sets indicated good accuracy for this nomogram. The calibration curves demonstrated a high degree of concordance between actual and anticipated values, and the DCA demonstrated that the nomograms had better clinical application than the traditional TNM staging approach.

Conclusion

This study identified risk factors for survival in operable elderly lung cancer patients and established a new column line graph for predicting OS and CSS in these patients. The model has good clinical application and can be a good clinical decision-making tool for physicians and patients.

Palliative radiotherapy of bone metastases in octogenarians: How do the oldest olds respond? Results from a tertiary cancer center with 288 treated patients

BACKGROUND

Accompanied by the demographic change, the number of octogenarian cancer patients with bone metastases will increase in the future. Palliative radiotherapy constitutes an effective analgesic treatment; however, as pain perception and bone metabolism change with increasing age, the analgesic efficacy of radiotherapy may be altered in elderly patients. We therefore investigated the treatment outcomes of palliative radiotherapy for bone metastases in octogenarians.

METHODS

Patients between 80 and 89 years undergoing radiotherapy for bone metastases between 2009 and 2019 at a tertiary cancer center were analyzed for patterns-of-care, pain response and overall survival (OS). Logistic regression analyses were carried out to examine parameters associated with pain response, and Cox analyses were conducted to reveal prognostic parameters for OS.

RESULTS

A total of 288 patients with 516 irradiated lesions were included in the analysis. The majority (n = 249, 86%) completed all courses of radiotherapy. Radiotherapy led to pain reduction in 176 patients (61%) at the end of treatment. Complete pain relief at the first follow-up was achieved in 84 patients (29%). Bisphosphonate administration was significantly associated with higher rates of pain response at the first follow-up (p < 0.05). Median OS amounted to 9 months, and 1-year, 2-year and 3-year OS were 43%, 28% and 17%. In the multivariate analysis, ECOG (p < 0.001), Mizumoto score (p < 0.01) and Spinal Instability Neoplastic Score (SINS) (p < 0.001) were independent prognosticators for OS.

CONCLUSION

Palliative radiotherapy for bone metastases constitutes a feasible and effective analgesic treatment in octogenarian patients. ECOG, Mizumoto score and SINS are prognosic variables for survival and may aid treatment decisions regarding radiotherapy fractionation in this patient group. Single-fraction radiotherapy with 8 Gy should be applied for patients with uncomplicated bone metastases and poor prognosis. Prospective trials focusing on quality of life of these very old cancer patients with bone metastases are warranted to reveal the optimal radiotherapeutic management for this vulnerable population.

Age-dependent genomic characteristics and their impact on immunotherapy in lung adenocarcinoma

BACKGROUND

The incidence of lung cancer tends to be younger, and adenocarcinoma is the main histological type. Even patients with the same tumor type may have significant differences in clinical features, tumor microenvironment and genomic background at different ages. Immune checkpoint inhibitors (ICIs) have been shown to improve clinical outcomes in patients with lung adenocarcinoma (LUAD). However, differences in ICI efficacy between older and younger patients are unknown. Our study aimed to explore the relationship between age and immunotherapy in LUAD.

METHODS

In our study, 1313 resected LUAD patients in our hospital were divided into young (age ≤ 50) and old groups (age > 50), and the clinical characteristic differences between them were analyzed. Of these, next-generation sequencing (NGS) was performed on the 311 cases. In addition, immune-related signatures of 508 LUAD patients were analyzed by TCGA RNA expression data. Then, we validated genomic and clinical information of 270 LUAD samples in the MSKCC cohort.

RESULTS

ERBB2 and EGFR gene mutations were significantly different between the two groups, and the gene mutation number in the old group was significantly higher than that in the young group. In addition, immune-related signatures of LUAD patients were analyzed by TCGA RNA expression data, which indicated that the patients in the old group might have a better immune microenvironment. Then, we validated the MSKCC cohort and found that the TMB of the old group was significantly higher than that of the young group, and the OS of immunotherapy was longer in the old group.

CONCLUSION

Our study was the first to analyze the differences in the genomic landscape and immune-related biomarkers between the young and old groups of LUAD patients and found that the old group had a better efficacy of immunotherapy, providing a reference for the study design and treatment of patients with LUAD.

Construction and validation of prognostic nomograms for elderly patients with metastatic non-small cell lung cancer

BACKGROUND

Metastatic non-small cell lung cancer (NSCLC) is mostly seen in older patients and is associated with poor prognosis. There is no reliable method to predict the prognosis of elderly patients (≥60 years old) with metastatic NSCLC. The aim of our study was to develop and validate nomograms which accurately predict survival in this group of patients.

METHODS

NSCLC patients diagnosed between 2010 and 2015 were all identified from the Surveillance, Epidemiology, and End Results (SEER) database. Nomograms were constructed by significant clinicopathological variables (p < 0.05) selected in multivariate Cox analysis regression.

RESULTS

A total of 9584 patients met the inclusion criteria and were randomly allocated in the training (n = 6712) and validation (n = 2872) cohorts. In training cohort, independent prognostic factors included age, gender, race, grade, tumor site, pathology, T stage, N stage, radiotherapy, surgery, chemotherapy, and metastatic site (p < 0.05) for lung cancer-specific survival (LCSS) and overall survival (OS) were identified by the Cox regression. Nomograms for predicting 1-, 2-, and 3-years LCSS and OS were established and showed excellent predictive performance with a higher C-index than that of the 7th TNM staging system (LCSS: training cohort: 0.712 vs. 0.534; p < 0.001; validation cohort: 0.707 vs. 0.528; p < 0.001; OS: training cohort: 0.713 vs. 0.531; p < 0.001; validation cohort: 0.710 vs. 0.528; p < 0.001). The calibration plots showed good consistency from the predicted to actual survival probabilities both in training cohort and validation cohort. Moreover, the decision curve analysis (DCA) achieved better net clinical benefit compared with TNM staging models.

CONCLUSIONS

We established and validated novel nomograms for predicting LCSS and OS in elderly patients with metastatic NSCLC with desirable discrimination and calibration ability. These nomograms could provide personalized risk assessment for these patients and assist in clinical decision.

Histone Modification in NSCLC: Molecular Mechanisms and Therapeutic Targets

Lung cancer is the leading cause of cancer mortality in both genders, with non-small cell lung cancer (NSCLC) accounting for about 85% of all lung cancers. At the time of diagnosis, the tumour is usually locally advanced or metastatic, shaping a poor disease outcome. NSCLC includes adenocarcinoma, squamous cell carcinoma, and large cell lung carcinoma. Searching for novel therapeutic targets is mandated due to the modest effect of platinum-based therapy as well as the targeted therapies developed in the last decade. The latter is mainly due to the lack of mutation detection in around half of all NSCLC cases. New therapeutic modalities are also required to enhance the effect of immunotherapy in NSCLC. Identifying the molecular signature of NSCLC subtypes, including genetics and epigenetic variation, is crucial for selecting the appropriate therapy or combination of therapies. Epigenetic dysregulation has a key role in the tumourigenicity, tumour heterogeneity, and tumour resistance to conventional anti-cancer therapy. Epigenomic modulation is a potential therapeutic strategy in NSCLC that was suggested a long time ago and recently starting to attract further attention. Histone acetylation and deacetylation are the most frequently studied patterns of epigenetic modification. Several histone deacetylase (HDAC) inhibitors (HDIs), such as vorinostat and panobinostat, have shown promise in preclinical and clinical investigations on NSCLC. However, further research on HDIs in NSCLC is needed to assess their anti-tumour impact. Another modification, histone methylation, is one of the most well recognized patterns of histone modification. It can either promote or inhibit transcription at different gene loci, thus playing a rather complex role in lung cancer. Some histone methylation modifiers have demonstrated altered activities, suggesting their oncogenic or tumour-suppressive roles. In this review, patterns of histone modifications in NSCLC will be discussed, focusing on the molecular mechanisms of epigenetic modifications in tumour progression and metastasis, as well as in developing drug resistance. Then, we will explore the therapeutic targets emerging from studying the NSCLC epigenome, referring to the completed and ongoing clinical trials on those medications.

Octogenarians may benefit from stage-specific small cell lung cancer treatment

BACKGROUND

Our study investigates treatment profiles in octogenarian patients with small cell lung cancer (SCLC) and assesses each treatment's role in a stage-specific manner.

METHODS

Patient data from individuals with SCLC aged 80 years and older between 1988 and 2015 in the Surveillance, Epidemiology, and End Results Program (SEER) database were extracted. Cancer-specific survival (CSS) between patients with no treatment and different treatment groups were compared by the Kaplan-Meier method, with stratifications by stage. Cox Proportional Hazard model further identified independent prognostic factors.

RESULTS

A total of 7,290 patients were included in this study. Notably, 3,358 (46.1%) patients did not receive active treatment. Compared with the no active treatment group, the CSS of patients who received treatment was significantly improved (median 6 vs. 0 months, P<0.001) and further validated in stage subgroups. Chemotherapy combined with local therapy was associated with the best CSS in regional and distant disease stages, with the hazard ratios (HR) and 95% confidence intervals (CI) being 0.30 (0.26-0.34) and 0.27 (0.25-0.30), respectively. Local therapy only appeared to confer better oncological outcomes (HR =0.33; 95% CI: 0.25-0.42) than chemotherapy only (HR =0.37; 95% CI: 0.29-0.47) in the localized disease stage.

CONCLUSIONS

Although nearly half of octogenarians with SCLC did not receive active treatment in the real clinical setting, these patients may benefit from treatment. Chemotherapy combined with local therapy may provide the best treatment choice in octogenarians with advanced SCLC, while local therapy appears to play a more critical role in treating those with early-stage disease.

Surgical Survival Benefits With Different Metastatic Patterns for Stage IV Extrathoracic Metastatic Non-Small Cell Lung Cancer: A SEER-Based Study

Background:

With the knowledge of oligometastases, primary surgery plays an increasingly vital role in metastatic non-small cell lung cancer. We aimed to evaluate the survival benefit of primary surgery based on metastatic patterns.

Materials and Methods:

The selected patients with stage IV extrathoracic metastatic (m1b) non-small cell lung cancer between 2010 and 2015 were included in a retrospective cohort study from the Surveillance, Epidemiology, and End Results (SEER) database. Multiple imputation was used for the missing data. Patients were divided into 2 groups depending on whether surgery was performed. After covariate balancing propensity score (CBPS) weighting, multivariate Cox regression models and Kaplan-Meier survival curve were built to identify the survival benefit of different metastatic patterns.

Results:

Surgery can potentially increase the overall survival (OS) (adjusted HR: 0.68, P < 0.001) of non-small cell lung cancer. The weighted 3-year OS in the surgical group was 16.9%, compared with 7.8% in the nonsurgical group. For single organ metastasis, surgery could improve the survival of metastatic non-small cell lung cancer. Meanwhile, no significant survival improvements in surgical group were observed in patients with multiple organ metastases.

Conclusion:

The surgical survival benefits for extrathoracic metastatic non-small cell lung cancer could be divided by metastatic pattern.

Predictors for survival in patients with bone metastasis of small cell lung cancer: A population-based study

The objective of the current study is to analyze the clinical and demographic characteristics of patients with bone metastasis of small cell lung cancer (SCLC) and explore their survival predictors.We retrospectively extracted patients with bone metastasis of SCLC from the Surveillance, Epidemiology, and End Results database. We applied Cox regression analyses to identify independent survival predictor of overall survival (OS) and cancer-specific survival (CSS). Only significant predictors from univariable analysis were included for multivariable Cox analysis. Kaplan-Meier method was used to evaluate survival differences between groups by the log-rank test.A total of 5120 patients with bone metastasis of SCLC were identified and included for survival analysis. The 1-year OS and CSS rates of bone metastasis of SCLC were 19.8% and 21.4%, respectively. On multivariable analysis, gender, age, radiotherapy, chemotherapy, liver metastasis, brain metastasis, insurance status, and marital status independently predicted OS and CSS. There was no significant difference of OS and CSS in terms of race and tumor size.Independent predictors of survival were identified among patients with bone metastasis of SCLC, which could be valuable to clinicians in treatment decision. Patients with bone metastasis of SCLC may benefit from radiotherapy and chemotherapy.

Metastatic patterns and prognosis of young lung cancer patients: a population-based study by age

Background

We aimed to examine the different metastatic patterns and corresponding survival outcomes between all ages of young (aged <60 years) and elderly lung cancer patients.

Methods

Lung cancer patients from the Surveillance, Epidemiology, and End Results (SEER) database between 2010 and 2015 were divided into a young and elderly group. The young group was subdivided into four consecutive subgroups. Baseline characteristics were analyzed by the Chi-square test. Survival differences were evaluated by Kaplan-Meier curves and Cox proportional hazards models.

Results

Of the total 200,362 lung cancer patients, 155,348 were elderly patients and 45,014 were young patients, including 3,461 aged <45 years, 5,697 aged 45–49 years, 13,645 aged 50–54 years, and 22,211 aged 55–59 years. Compared with elderly lung cancer patients, extrathoracic metastases were significantly more frequent in each younger group, irrespective of the site and number of extrathoracic metastatic organs. Regardless of metastasis patterns, young ages were independent prognostic factors of lung cancer-specific survival (LCSS) [<45 years: hazard ratio (HR): 0.70; 45–49 years: HR: 0.87; 50–54 years: HR: 0.90; 55–59 years: HR: 0.93, all P values were <0.001]. In each age subgroup, patients with multi-organ extrathoracic metastasis had the worst LCSS.

Conclusions

Young lung cancer patients across all ages were at increased risk of extrathoracic metastasis, especially multi-organ patterns, but had a reduced risk of lung cancer-related death compared to elderly patients. Regular and meticulous monitoring of potential metastasized organs is required in young lung cancer patients throughout the follow-up period.

Clinical efficacy and safety of maintenance therapy for advanced non-small cell lung cancer: a retrospective real-world study

BACKGROUND

The clinical efficacy and safety of maintenance therapy (MT) for patients with advanced non-small cell lung cancer (NSCLC) have not been determined in the real word. This retrospective study of real-world data analyzed these issues in patients with advanced NSCLC and stable or responsive tumors after 4-6 cycles of first-line chemotherapy.

METHODS

We classified 158 patients into MT (34 IIIB and 37 IV stage) and non-MT (47 IIIB and 40 IV stage) groups and then compared the clinical outcomes of progression-free survival (PFS) and overall survival (OS). The influences of maintaining chemotherapy or targeted drugs, regimens, and duration on PFS were also investigated. Prognostic factors for OS were identified by univariate and multivariate analyses.

RESULTS

Among the patients, 71 received MT and 87 did not. The median PFS and OS were significantly prolonged in the MT group than non-MT group (5.6 and 14.2 vs. 2.8 and 9.8 months, respectively; both p < 0.0001). The PFS was extended when patients were maintained with targeted drugs compared with chemotherapy, > 4 cycles of chemotherapy, and targeted drugs for > 3 months (all P < 0.0001). Patients with adenocarcinoma and without distant metastasis derived a better OS benefit from MT (P = 0.041 and P = 0.037, respectively). Multivariate analysis revealed that female sex and MT were independent prognostic factors for extended OS (P = 0.039 and P < 0.0001, respectively). The major adverse events of MT comprised tolerable hematological toxicity and gastrointestinal reactions.

CONCLUSIONS

MT was advantageous and tolerable for patients with advanced NSCLC, especially those with adenocarcinomas without distant metastasis who were treated with targeted drugs, which was an independent prognostic factor for OS.

The incidence, risk factors and predictive nomograms for early death of lung cancer with synchronous brain metastasis: a retrospective study in the SEER database

BACKGROUND

The prognosis of lung cancer with synchronous brain metastasis (LCBM) is very poor, and patients often die within a short time. However, little is known about the early mortality and related factors in patients with LCBM.

METHODS

Patients diagnosed with LCBM between 2010 and 2016 were enrolled from the Surveillance, Epidemiology, and End Result (SEER) database. Univariate and multivariate logistic regression analysis were used to identify significant independent prognostic factors, which were used to construct nomograms of overall and cancer-specific early death. Then, the prediction ability of the model was verified by receiver operating characteristic (ROC) curve. At last, the clinical application value of the model was tested through decision curve analysis (DCA).

RESULTS

A total of 29,902 patients with LCBM were enrolled in this study. Among them, 13,275 (44.4%) patients had early death, and 11,425 (38.2%) cases died of lung cancer. The significant independent risk factors for overall and cancer-specific early death included age, race, gender, Gleason grade, histological type, T stage, N stage, bone metastasis, liver metastasis and marital status, which were used to construct the nomogram. The ROC curve demonstrated good predictive ability and clinical application value. The areas under the curve (AUC) of the training group was 0.793 (95% CI: 0.788-0.799) and 0.794 (95% CI: 0.788-0.799), in the model of overall and cancer-specific early death respectively. And the AUC of the validation group were 0.803 (95% CI: 0.788-0.818) and 0.806 (95% CI: 0.791-0.821), respectively. The calibration plots of the model showed that the predicted early death is consistent with the actual value. The DCA analysis indicated a good clinical application value of this model.

CONCLUSIONS

We established a comprehensive nomogram to predict early death in lung cancer patients with synchronous brain metastases. Nomograms may help oncologists develop better treatment strategies, such as clinical trials and hospice care.