Clinical applicability of staging small cell lung cancer according to the seventh edition of the TNM staging system

Development and validation of nomogram prognostic model for early-stage T1-2N0M0 small cell lung cancer: A population-based analysis

Background

Survival outcomes of early-stage T1-2N0M0 small cell lung cancer (SCLC) patients differ widely, and the existing Veterans Administration Lung Study Group (VALSG) or TNM staging system is inefficient at predicting individual prognoses. In our study, we developed and validated nomograms for individually predicting overall survival (OS) and lung cancer-specific survival (LCSS) in this special subset of patients.

Methods

Data on patients diagnosed with T1-2N0M0 SCLC between 2000 and 2015 were extracted from the Surveillance, Epidemiology, and End Results (SEER) database. All enrolled patients were split into a training cohort and a validation cohort according to the year of diagnosis. Using multivariable Cox regression, significant prognostic factors were identified and integrated to develop nomograms for 1-, 3-, and 5-year OS and LCSS prediction. The prognostic performance of our new model was measured by the concordance index (C-index) and calibration curve. We compared our latest model and the 8th AJCC staging system using decision curve analyses (DCA). Kaplan-Meier survival analyses were applied to test the application of the risk stratification system.

Results

A total of 1,147 patients diagnosed from 2000 to 2011 were assigned to the training cohort, and 498 cases that were diagnosed from 2012 to 2015 comprised the validation cohort. Age, surgery, lymph node removal (LNR), and chemotherapy were independent predictors of LCSS. The variables of sex, age, surgery, LNR, and chemotherapy were identified as independent predictors of OS. The above-mentioned prognostic factors were entered into the nomogram construction of OS and LCSS. The C-index of this model in the training cohort was 0.663, 0.702, 0.733, and 0.658, 0.702, 0.733 for predicting 1-, 3-, and 5-year OS and LCSS, respectively. Additionally, in the validation cohort, there were 0.706, 0.707, 0.718 and 0.712, 0.691, 0.692. The calibration curve showed accepted prediction accuracy between nomogram-predicted survival and actual observed survival, regardless of OS or LCSS. In addition, there were significant distinctions in the survival curves of OS and LCSS between different risk groups stratified by prognostic scores. Compared with the 8th AJCC staging system, our new model also improved net benefits.

Conclusions

We developed and validated novel nomograms for individual prediction of OS and LCSS, integrating the characteristics of patients and tumors. The model showed superior reliability and may help clinicians make treatment strategies and survival predictions for early-stage T1-2N0M0 SCLC patients.

Neuronal survival factor VGF promotes chemoresistance and predicts poor prognosis in lung cancers with neuroendocrine feature

High-grade neuroendocrine tumors (NETs) of the lung consist of small-cell lung cancer (SCLC) and large-cell neuroendocrine carcinoma (LCNEC). Both exhibit aggressive malignancy with poor prognosis. The transformation of lung adenocarcinoma (ADC) to SCLC or LCNEC also contributes to acquired resistance to epidermal growth factor receptor (EGFR)-tyrosine kinase inhibitors (TKIs). Despite initially being responsive to chemotherapy, high-grade NET patients inevitably develop drug resistance; thus, novel therapeutic targets are urgently needed for these patients. This study reported that VGF (nerve growth factor inducible), a factor mainly expressed in neurons during neural development, is highly expressed in SCLC and LCNEC as well as in a subset of ADCs, whereas targeting VGF attenuates cancer cell growth and tumor formation. High VGF expression was associated with advanced stage SCLC and predicted poor prognosis in lung ADC. In addition, EGFR-TKI selection enriched VGF expression in TKI-resistant ADC under epigenetic control. The VGF locus possessed the HDAC1 binding site, and treatment of ADC cells with the HDAC1 inhibitor induced VGF expression. High VGF expression was associated with chemoresistance, and silencing VGF induced BMF and BCL2L11 expression and rendered lung cancer cells sensitive to chemotherapy drugs. These findings suggested the potential of VGF as a prognostic factor and therapeutic target in lung cancers with neuroendocrine feature. This article is protected by copyright. All rights reserved.

Development and Validation of a Nomogram Prognostic Model for Resected Limited-Stage Small Cell Lung Cancer Patients

Background

In this study, we developed and validated nomograms for predicting the survival in surgically resected limited-stage small cell lung cancer (SCLC) patients.

Methods

The SCLC patients extracted from the Surveillance, Epidemiology, and End Results database between 2000 and 2014 were reviewed. Significant prognostic factors were identified and integrated to develop the nomogram using multivariable Cox regression. The model was then validated internally by bootstrap resampling, and externally using an independent SCLC cohort diagnosed between 2000 and 2015 at our institution. The prognostic performance was measured by the concordance index (C-index) and calibration curve.

Results

A total of 1006 resected limited-stage SCLC patients were included in the training cohort. Overall, 444 cases from our institution constituted the validation cohort. Seven prognostic factors were identified and entered into the nomogram construction. The C-indexes of this model in the training cohort were 0.723, 0.722, and 0.746 for predicting 1-, 3-, and 5-year overall survival (OS), respectively, and 0.816, 0.710, and 0.693, respectively, in the validation cohort. The calibration curve showed optimal agreement between nomogram-predicted survival and actual observed survival. Additionally, significant distinctions in survival curves between different risk groups stratified by prognostic scores were also observed. The proposed nomogram was then deployed into a website server for convenient application.

Conclusions

We developed and validated novel nomograms for individual prediction of survival for resected limited-stage SCLC patients. These models perform better than the previously widely used staging system and may offer clinicians instructions for strategy making and the design of clinical trials.

Supplementary Information

The online version of this article (10.1245/s10434-020-09552-w) contains supplementary material, which is available to authorized users.

Prognostic Value of 18F-FDG-PET Parameters in Patients with Small Cell Lung Cancer: A Meta-Analysis and Review of Current Literature

Many studies have suggested a prognostic value of one or several positron emission tomography (PET) parameters in patients with small cell lung cancer (SCLC). However, studies are often small, and there is a considerable interstudy disagreement about which PET parameters have a prognostic value. The objective of this study was to perform a review and meta-analysis to identify the most promising PET parameter for prognostication. PubMed^®, Cochrane, and Embase^® were searched for papers addressing the prognostic value of any PET parameter at any treatment phase with any endpoint in patients with SCLC. Pooled hazard ratios (HRs) were calculated by a random effects model for the prognostic value of the baseline maximum standardized uptake value (SUV_max) and metabolic tumor volume (MTV). The qualitative analysis included 38 studies, of these, 19 studies were included in the meta-analyses. The pooled results showed that high baseline MTV was prognostic for overall survival (OS) (HR: 2.83 (95% confidence interval [CI]: 2.00–4.01) and progression-free survival (PFS) (HR: 3.11 (95% CI: 1.99–4.90)). The prognostic value of SUV_max was less pronounced (OS: HR: 1.50 (95% CI: 1.17–1.91); PFS: HR: 1.24 (95% CI: 0.94–1.63)). Baseline MTV is a strong prognosticator for OS and PFS in patients with SCLC. MTV has a prognostic value superior to those of other PET parameters, but whether MTV is superior to other prognosticators of tumor burden needs further investigation.

Prognostic Value of a Nomogram Based on the Dynamic Albumin-to-Alkaline Phosphatase Ratio for Patients with Extensive-Stage Small-Cell Lung Cancer

Purpose

Small-cell lung cancer (SCLC) is known as the characteristics of high invasion, rapid progression, and poor prognosis. Therefore, identification of patients with high risk of progression and death is critical to improve the survival of patients with extensive-stage SCLC (ES-SCLC). This study was designed to determine the prognostic importance of the albumin-to-alkaline phosphatase ratio (AAPR) in the survival of patients with ES-SCLC and to develop a nomogram based on AAPR dynamics for ES-SCLC prognosis.

Patients and Methods

Characteristics were reviewed from 300 patients with ES-SCLC. Training and validation cohorts included 200 and 100 patients, respectively. We applied univariate and multivariate Cox models to assess the prognostic value of AAPR for ES-SCLC. The nomogram for progression-free survival (PFS) and overall survival (OS) of ES-SCLC patients was developed based on the multivariate survival analysis of the training cohort. External validation of the established nomogram was performed using the validation cohort.

Results

N3 stage, thoracic radiotherapy, and post-AAPR were the independent factors identified for PFS. T stage, thoracic radiotherapy, and high post-AAPR were the independent risk factors identified for death. The prognostic nomogram was established by integrating the independent significant factors for PFS and OS in the training cohort with the c-indices of 0.675 and 0.662, respectively, and validated in the validation cohort. The nomogram had superior prognosis prediction ability than did TNM stage. Decision curve analysis (DCA) also indicated clinical net benefits from the nomogram.

Conclusion

AAPR was valuable for prognosis prediction in patients with ES-SCLC and was recommended to be dynamically evaluated to guide patient treatment. Additionally, the nomogram covering post-AAPR accurately predicted individual survival probability.

The impact of quantitative CT-based tumor volumetric features on the outcomes of patients with limited stage small cell lung cancer

INTRODUCTION

Limited stage small cell lung cancer (LS-SCLC) has a poor prognosis. Additional prognostic markers are needed for risk-stratification and treatment intensification. This study compares quantitative CT-based volumetric tumor measurements versus International Association for the Study of Lung Cancer (IASLC) TNM staging to predict outcomes.

MATERIALS & METHODS

A cohort of 105 patients diagnosed with LS-SCLC and treated with chemoradiation (CRT) from 2000 to 2013 were analyzed retrospectively. Patients were staged by the Union for International Cancer Control (UICC) TNM Classification, 8th edition. Tumor volumes and diameters were extracted from radiation planning CT imaging. Univariable and multivariable models were used to analyze relationships between CT features and overall survival (OS), locoregional recurrence (LRR), in-field LRR, any progression, and distant metastasis (DM).

RESULTS

Median follow-up was 21.3 months. Two-year outcomes were as follows: 38% LRR, 31% in-field LRR, 52% DM, 62% any progression, and 47% OS (median survival 16.5 months). On univariable analysis, UICC T-stage and N-stage were not associated with any clinical outcome. UICC overall stage was only statistically associated with in-field LRR. One imaging feature (3D maximum tumor diameter) was found to be significantly associated with LRR (HR 1.10, p = 0.003), in-field LRR (HR 1.10, p = 0.007), DM (HR 1.10, p = 0.02), any progression (HR 1.10, p = 0.008), and OS (HR 1.10, p = 0.03). On multivariable analysis, this feature remained significantly associated with all outcomes.

CONCLUSION

For LS-SCLC, quantitative CT-based volumetric tumor measurements were significantly associated with outcomes after CRT and may be better predictors of outcome than TNM stage.

Exosomal long non-coding RNA DLX6-AS1 as a potential diagnostic biomarker for non-small cell lung cancer

Distal-less homeobox 6 antisense RNA 1 (DLX6-AS1) is upregulated in various solid tumors and serves a critical role in the tumorigenesis of cancer. However, to the best of our knowledge, the expression of circulating DLX6-AS1 and its role in the diagnosis of non-small cell lung cancer (NSCLC) have not been previously clarified. The aim of the present study was to investigate the expression and clinical significance of circulating DLX6-AS1 using reverse transcription-quantitative PCR in serum and exosomes derived from patients with NSCLC and healthy donors. The diagnostic value of circulating DLX6-AS1 was identified by receiver operating characteristic curve (ROC) analysis. First, it was revealed that the expression levels of DLX6-AS1 were significantly increased in tumor tissues compared with in adjacent normal tissues. In addition, DLX6-AS1 was highly expressed in NSCLC cell lines compared with in BEAS-2B cells. DLX6-AS1-knockdown inhibited cell proliferation and migration in vitro. It was subsequently demonstrated that the serum DLX6-AS1 level was significantly higher in patients with NSCLC compared with in healthy controls. Additionally, the higher DLX6-AS1 expression was associated with advanced disease stage, positive lymph node metastasis and poor tumor differentiation of NSCLC. ROC analysis demonstrated that the sensitivity and specificity of DLX6-AS1 were higher than those of CYFRA21-1, which is a serum marker for NSCLC. Finally, exosomal DLX6-AS1 expression was increased in patients with NSCLC compared with in healthy controls. The present data implied that circulating DLX6-AS1 was mainly incorporated into exosomes, providing a novel potential diagnostic marker for NSCLC.

Survival Outcomes for Patients with Surgical and Non-Surgical Treatments in Stages I-III Small-Cell Lung Cancer

Objectives: Chemotherapy and radiation therapy are the standard treatments for patients with small-cell lung cancer (SCLC). However, recent studies suggest that patients with limited stage (I-III) SCLC may benefit from surgical treatment. This study was performed to evaluate the survival outcomes of surgery for stage I-III SCLC.

Methods: This analysis used data from the Surveillance, Epidemiology, and End Results (SEER) database. All stage I-III (excluding N3 and Nx) SCLC patients received a diagnosis between 2004 and 2014. Overall survival (OS) and lung cancer-specific survival (LCSS) were determined by Kaplan-Meier analysis and compared using the log-rank test. A Cox proportional hazard model identified relevant survival variables.

Results: A total of 4,780 histologically confirmed patients were identified from the SEER database, comprising 1,018 patients (21.3%) with stage I disease; 295 (6.2%) with stage II; and 3,467 (72.5%) with stage III disease. Among all of the patients, 520 had been treated with surgery, the majority (n = 344; 66.2%) of whom had stage I disease. The hazard ratio (HR) for OS and LCSS, in patients who underwent surgery, according to stage were as follows: OS, 0.369 and LCSS, 0.335 in stage I; OS, 0.549 and LCSS, 0.506 in stage II; and OS, 0.477 and LCSS, 0.456 in stage III (all p < 0.001). Patients who underwent surgery had significantly better OS, and lobectomy was associated with the best outcome.

Conclusions: Surgical resection was associated with significantly improved OS outcomes and should be considered in the management of stage I-III SCLC.

Role of microRNA-4458 in patients with non-small-cell lung cancer

Incidence and progression of non-small-cell lung cancer (NSCLC) is a multi-factor, multi-step process. The present study investigated the association between the expression level of microRNA (miR)-4458 in NSCLC and paracarcinoma liver tissues and survival rates, and studied the biological functions of miR-4458 at the cellular and protein level. NSCLC and paracarcinoma tissues were sequenced using a miR expression chip. The association between miR-4458 expression and tumor-node-metastasis staging, total survival rate and relapse-free survival rate was analyzed. miR-4458 was subjected to target gene prediction. The target protein of cyclin D1 (CCND1) was verified with western blot analysis, immunohistochemistry and a luciferase reporter assay. The relative level of miR-4458 in paracarcinoma tissues of 9 NSCLC patients decreased from 2.38 to 0.65 (P<0.001). Total five-year survival rates of the high-expression miR-4458 group (29.21%) significantly exceeded that of the low-expression group (14.37%) (P=0.025). The viability of human lung carcinoma A549 and H460 cells transfected with miR-4458 decreased significantly compared with cells transfected with a normal control (blank control plasmid) within 72 h (P<0.001). The percentage of A549 and H460 cells transfected with a miR-4458 mimic at the cell cycle stage G0/G1 was 69.94±8.05 and 68.15±7.75%, respectively. The percentages increased significantly compared with the control group (46.06±6.93 for A549 cells; 45.22±7.24 for H640 cells; P<0.001). CCND1 mRNA was downregulated significantly in H460 cells 72 h subsequent to the addition of miR-4458 mimics (P<0.001). The activity of mutant-CCND1 altered slightly, while the fluorescence intensity of the wild-type-CCND1 group decreased significantly following the addition of miR-4458 mimics. In conclusion, miR-4458 was expressed at low levels in lung cancer tissues, and it arrested cells in vitro at stage G0/G1 and inhibited cell proliferation. Therefore, miR-4458 may participate in the onset of lung cancer as a suppressor gene by inhibiting CCND1.

The IASLC Lung Cancer Staging Project: Methodology and Validation Used in the Development of Proposals for Revision of the Stage Classification of NSCLC in the Forthcoming (Eighth) Edition of the TNM Classification of Lung Cancer

INTRODUCTION

Stage classification provides a consistent language to describe the anatomic extent of disease and is therefore a critical tool in caring for patients. The Staging and Prognostic Factors Committee of the International Association for the Study of Lung Cancer developed proposals for revision of the classification of lung cancer for the eighth edition of the tumor, node, and metastasis (TNM) classification, which takes effect in 2017.

METHODS

An international database of 94,708 patients with lung cancer diagnosed in 1999-2010 was assembled. This article describes the process and statistical methods used to refine the lung cancer stage classification.

RESULTS

Extensive analysis allowed definition of tumor, node, and metastasis categories and stage groupings that demonstrated consistent discrimination overall and within multiple different patient cohorts (e.g., clinical or pathologic stage, R0 or R-any resection status, geographic region). Additional analyses provided evidence of applicability over time, across a spectrum of geographic regions, histologic types, evaluative approaches, and follow-up intervals.

CONCLUSIONS

An extensive analysis has produced stage classification proposals for lung cancer with a robust degree of discriminatory consistency and general applicability. Nevertheless, external validation is encouraged to identify areas of strength and weakness; a sound validation should have discriminatory ability and be based on an independent data set of adequate size and sufficient follow-up with enough patients for each subgroup.

The Highest Metabolic Activity on FDG PET Is Associated With Overall Survival in Limited-Stage Small-Cell Lung Cancer

We evaluated the prognostic value of F-fluorodeoxyglucose positron emission tomography (FDG PET) parameters for limited-stage small-cell lung cancer (LS-SCLC).We retrospectively enrolled 59 LS-SCLC patients who underwent pretreatment FDG PET/CT. Various PET parameters were measured in all malignant lesions, and we recorded the highest maximum standardized uptake value (SUVmax), and sum of metabolic tumor volume (MTVsum) and total lesion glycolysis (TLGsum). The relationship between the highest SUVmax and volumetric PET parameters was evaluated. The prognostic significances of PET parameters and clinical variables were assessed using Cox's proportional hazard regression analysis. Overall survival (OS) and progression-free survival (PFS) were assessed by the Kaplan-Meier method.The SUVmax of the highest metabolic lesion had a significant positive correlation with MTVsum and TLGsum (P < 0.001). Upon multivariate analysis, the highest SUVmax was an independent predictor of OS (1 unit increase, hazard ratio [HR]: 1.133, P = 0.003) and MTVsum was a significant prognostic factor of PFS (10-cm increase, HR: 1.027, P = 0.034) after adjusting for age, sex, performance status, tumor stage, and treatment modality. The highest SUVmax was a prognostic factor for PFS with marginal significance (1 unit increase, HR: 1.078, P = 0.053). Patients with higher SUVmax (≥11) were also characterized by a significantly shorter median OS (P < 0.001) and PFS (P = 0.002) compared with patients with lower SUVmax.The highest SUVmax is an independent prognostic factor for survival in LS-SCLC patients. Therefore, the highest SUVmax might be a possible imaging biomarker for risk stratification in LS-SCLC. A further study in a large cohort is needed to validate the prognostic significance of the parameter.

Prognostic value of fluorine-18 fludeoxyglucose positron emission tomography parameters differs according to primary tumour location in small-cell lung cancer

OBJECTIVE

To investigate the prognostic value of fluorine-18 fludeoxyglucose (FDG) positron emission tomography (PET) parameters for small-cell lung cancer (SCLC), according to the primary tumour location, adjusted by conventional prognostic factors.

METHODS

From 2008 to 2013, we enrolled consecutive patients with histologically proven SCLC, who had undergone FDG-PET/CT prior to initial therapy. The primary tumour location was categorized into central or peripheral types. PET parameters and clinical variables were evaluated using univariate and multivariate analysis.

RESULTS

A total of 69 patients were enrolled in this study; 28 of these patients were categorized as having the central type and 41 patients as having the peripheral type. In univariate analysis, stage, serum neuron-specific enolase, whole-body metabolic tumour volume (WB-MTV) and whole-body total lesion glycolysis (WB-TLG) were found to be significant in both types of patients. In multivariate analysis, the independent prognostic factor was found to be stage in the central type, but WB-MTV and WB-TLG in the peripheral type. Kaplan-Meier analysis demonstrated that patients with peripheral type with limited disease and low WB-MTV or WB-TLG showed significantly better overall survival than all of the other groups (p < 0.0083).

CONCLUSION

The FDG-PET volumetric parameters were demonstrated to be significant and independent prognostic factors in patients with peripheral type of SCLC, while stage was the only independent prognostic factor in patients with central type of SCLC.

ADVANCES IN KNOWLEDGE

FDG-PET is a non-invasive method that could potentially be used to estimate the prognosis of patients, especially those with peripheral-type SCLC.

Predicting the prognosis of lung cancer: the evolution of tumor, node and metastasis in the molecular age-challenges and opportunities

The tumor, node and metastasis (TNM) classification of malignant tumors was proposed by Pierre Denoit in the mid-20(th) century to code the anatomic extent of tumors. Soon after, it was accepted by the Union for International Cancer Control and by the American Joint Committee on Cancer, and published in their respective staging manuals. Till 2002, the revisions of the TNM classification were based on the analyses of a database that included over 5,000 patients, and that was managed by Clifton Mountain. These patients originated from North America and almost all of them had undergone surgical treatment. To overcome these limitations, the International Association for the Study of Lung Cancer proposed the creation of an international database of lung cancer patients treated with a wider range of therapeutic modalities. The changes introduced in the 7(th) edition of the TNM classification of lung cancer, published in 2009, derived from the analysis of an international retrospective database of 81,495 patients. The revisions for the 8(th) edition, to be published in 2016, will be based on a new retrospective and prospective international database of 77,156 patients, and will mainly concern tumor size, extrathoracic metastatic disease, and stage grouping. These revisions will improve our capacity to indicate prognosis and will make the TNM classification more robust. In the future the TNM classification will be combined with non-anatomic parameters to define prognostic groups to further refine personalized prognosis.

Treatment of small cell lung cancer

Treatment of small cell lung cancer (SCLC) remains a significant challenge for the oncologists. Attempts to improve the results of first-line treatment have all failed so far and no real progress has been made in last years, emphasizing the need for novel strategies of treatment and the development of validated biomarkers. Patients with limited disease and good performance status should be considered for concomitant chemoradiotherapy, followed by prophylactic cranial irradiation. Patients with extensive disease should be treated with a platinum-based chemotherapy (cisplatin or carboplatin); chest radiotherapy can be considered in patients achieving extra-thoracic complete response and prophylactic cranial irradiation is recommended for patients responsive to initial chemotherapy. A large number of molecular-targeted drugs and immunomodulators are currently in clinical development: however, only a better understanding of molecular biology of SCLC and the identification of molecular markers predictive of response to targeted agents will lead to advances in the treatment of SCLC.