Different distant metastasis patterns based on tumor size could be found in extensive-stage small cell lung cancer patients: a large, population-based SEER study

Patterns of distant metastasis and survival outcomes in de novo metastatic breast cancer according to age groups

Background

Is de novo metastatic breast cancer (dnMBC) the same disease in the elderly as in younger breast cancer remains unclear. This study aimed to determine the metastatic patterns and survival outcomes in dnMBC according to age groups.

Methods

We included patients from the Surveillance Epidemiology and End Results program. Chi-square test, multivariate logistic regression analyses, and multivariate Cox regression models were used for statistical analyses.

Results

A total of 17719 patients were included. There were 3.6% (n=638), 18.6% (n=3290), 38.0% (n=6725), and 39.9% (n=7066) of patients aged <35, 35-49, 50-64, and ≥65 years, respectively. Older patients had a significantly higher risk of lung metastasis and a significantly lower risk of liver metastasis. There were 19.1%, 25.6%, 30.9%, and 35.7% of patients with lung metastasis in those aged <35, 35-49, 50-64, and ≥65 years, respectively. Moreover, the proportion of liver metastasis was 37.6%, 29.5%, 26.3%, and 19.2%, respectively. Age was the independent prognostic factor associated with breast cancer-specific survival (BCSS) and overall survival (OS). Those aged 50-64 years had significantly inferior BCSS (P<0.001) and OS (P<0.001) than those aged <35 years. Patients aged ≥65 years also had significantly lower BCSS (P<0.001) and OS (P<0.001) than those aged <35 years. However, similar outcomes were found between those aged 35-49 and <35 years.

Conclusion

Our study suggests that different age groups may affect the metastatic patterns among patients with dnMBC and the survival of younger patients is more favorable than those of older patients.

Regional lymph node recurrence after stereotactic body radiation therapy for lung cancer: Patterns of recurrence, treatment approaches, and clinical outcomes (KROG 21-09)

PURPOSE

To present the multi-institutional data on patterns of recurrence, treatment approaches, and clinical outcomes for regional lymph node (LN) recurrence after stereotactic body radiation therapy (SBRT) for primary lung cancer.

MATERIALS AND METHODS

The medical records of 114 patients who experienced regional LN recurrence as the first recurrence after lung SBRT were retrospectively reviewed. Patterns of recurrence were classified as local recurrence, regional recurrence, and distant metastasis. Clinical outcomes including progression-free survival (PFS) and overall survival (OS) were analyzed.

RESULTS

Half of the patients had regional LN recurrence only. The most common simultaneous recurrence was distant metastasis (38.6 %). Common sites of regional recurrence were ipsilateral hilar (47.2 %), ipsilateral upper mediastinal (40.6 %), and subcarinal (42.5 %) LN stations. 24 (21.1 %) patients underwent salvage radiation therapy (RT), and 44 (38.6 %) patients underwent palliative treatment. Better OS was observed in the salvage RT group (p = 0.025). The 1-year PFS and OS rates were 27.7 % and 55.2 %, respectively, with salvage RT, 14.0 % and 39.9 %, respectively, with palliative treatment, and 22.8 % and 26.8 %, respectively, with no additional treatment. Multivariate analysis showed that salvage RT (PFS, HR 0.463, p = 0.050; OS, HR 0.312, p = 0.002), palliative treatment (PFS, HR 0.436, p = 0.013; OS, HR 0.553, p = 0.050), and simultaneous distant metastasis (PFS, HR 2.335, p = 0.005; OS, HR 1.726, p = 0.054) affected clinical outcomes.

CONCLUSION

Many cases of regional LN recurrence are confined to the locoregional area of patients, and appropriate treatment can improve the prognosis of these patients.

Deep learning of bone metastasis in small cell lung cancer: A large sample-based study

Introduction

Bone is a common metastatic site for small cell lung cancer (SCLC). Bone metastasis (BM) in patients have are known to show poor prognostic outcomes. We explored the epidemiological characteristics of BM in SCLC patients and create a new deep learning model to predict outcomes for cancer-specific survival (CSS) and overall survival (OS).

Materials and Methods

Data for SCLC patients diagnosed with or without BM from 2010 to 2016 were retrieved from the Surveillance, Epidemiology, and End Results (SEER) database. Univariate and multivariate Cox proportional hazards regression models were used to evaluate the effects of prognostic variables on OS and CSS. Through integration of these variables, nomograms were created for the prediction of CSS and OS rates at 3-month,6- month,and 12-month. Harrell's coordination index, calibration curves,and time- dependent ROC curves were used to assess the nomograms' accuracy. Decision tree analysis was used to evaluate the clinical application value of the established nomogram.

Results

In this study, 4201 patients were enrolled. Male sex, tumor size 25 but <10, brain and liver metastases, as well as chemotherapy were associated with a high risk for BM. Tumor size, Age, N stage, gender, liver metastasis, radiotherapy as well as chemotherapy were shown to be prognostic variables for OS, and the prognostic variables for CSS were added to the tumor number in addition. Based on these results, nomograms for CSS and OS were established separately. Internal as well as external validation showed that the C-index, calibration cuurve and DCA had good constructive correction effect and clinical application value. Decision tree analysis further confirmed the prognostic factors of OS and CSS.

Discussion

The nomogram and decision tree models developed in this study effectively guided treatment decisions for SCLC patients with BM. The creation of prediction models for BM SCLC patients may be facilitated by deep learning models.

Correlation between tumor diameter, distant metastasis site, and survival in extensive stage small cell lung cancer

Background

Small cell lung cancer (SCLC) is a malignant disease that spreads quickly. There is limited research on the relationship between tumor diameter and distant metastatic patterns in extensive stage small cell lung cancer (ES-SCLC). This study aimed to investigate the relationship between tumor diameter, distant metastasis site, and survival in extensive stage small cell lung cancer.

Method

Patients over the age of 18 who applied to Ankara Atatürk Chest Diseases and Thoracic Surgery Training and Research Hospital with the diagnosis of small cell lung cancer and distant organ metastasis between January 2015 and December 2019 were retrospectively analyzed.

Results

The study comprised a total of 178 patients, with 12 women (6.7%) and 166 men (93.3%) participating. The patient was followed for a period of 1 to 36 months, with a median value of 7 months. The univariate model showed that pancreatic metastasis, single metastasis, tumor diameter, and tumor N stage had a significant (p = 0.003, p = 0.001, p = 0.013, p = 0.001, respectively) effect on survival. The N stage III group’s expected life expectancy [6.8 months (5.8–7.7)] was considerably (p = 0.000) lower than the N stage I–II groups [11.2 months (8.8–13.4)]. The predicted life expectancy for the group with pancreatic metastasis [4.1 months (2.6–5.5)] was significantly (p = 0.001) shorter than that of the group without pancreatic metastasis [8.9 months (7.6–10.1)]. The predicted life expectancy for the group with tumor size > 7 cm [6.7 months (5.4–8.0)] was significantly shorter than that of the group with tumor size of 0–3 cm [10.9 months (7.3–14.6)] (p = 0.019) and 3–7 cm [9.2 months (7.5–11)] (p = 0.023).

Conclusion

The authors of this study found that pancreatic metastasis, single metastasis, tumor diameter, and tumor N stage can be used as independent predictive factors for the survival of SCLC patients.

The prognostic risk stratification model for metastatic small-cell lung cancer: An analysis of the SEER database

Distant metastases of small-cell lung cancer (DM-SCLC) is an important factor in the selection of treatment strategies. In this study, we established a nomogram to predict DM-SCLC and determine the benefit of radiotherapy (RT) for DM-SCLC. We analyzed DM-SCLC prognosis based on surveillance, epidemiology, and end result database (SEER) data. A comprehensive and practical nomogram that predicts the overall survival (OS) of DM-SCLC was constructed and the results were compared with the 7th edition of the American Joint Committee on Cancer (AJCC) TNM stage system. A concordance index (C-index) and receiver operating characteristic plot were generated to evaluate the nomogram discrimination. The calibration was evaluated with a calibration plot, and its effectiveness was evaluated by a decision curve analysis (DCA). A score was assigned to each variable, and a total score was established for the risk stratification model. A total of 13,403 DM-SCLC patients were included. Eight characteristic variables were identified as independent prognostic variables. The C-index of the validation and training cohorts was 0.716 and 0.734, respectively. The area under the receiver operating characteristic curve (AUC) values of the nomogram used to predict 1-, 2-, and 3-year OS were 0.751, 0.744, and 0.786 in the validation cohorts (0.761, 0.777, 0.787 in the training cohorts), respectively. The calibration curve of 1-, 2-, 3-year survival rates showed that the prediction of the nomogram was in good agreement with the actual observation. The nomogram exhibited higher clinical utility after evaluation with the 1-, 2-, 3-year DCA compared with the AJCC stage system. A predictive nomogram and risk stratification model have been constructed to evaluate the prognosis of DM-SCLC effectively and accurately. This nomogram may provide a reference for prognosis stratification and treatment decisions.

Machine Learning for the Prediction of Synchronous Organ-Specific Metastasis in Patients With Lung Cancer

Background

This study aimed to develop an artificial neural network (ANN) model for predicting synchronous organ-specific metastasis in lung cancer (LC) patients.

Methods

A total of 62,151 patients who diagnosed as LC without data missing between 2010 and 2015 were identified from Surveillance, Epidemiology, and End Results (SEER) program. The ANN model was trained and tested on an 75/25 split of the dataset. The receiver operating characteristic (ROC) curves, area under the curve (AUC) and sensitivity were used to evaluate and compare the ANN model with the random forest model.

Results

For distant metastasis in the whole cohort, the ANN model had metrics AUC = 0.759, accuracy = 0.669, sensitivity = 0.906, and specificity = 0.613, which was better than the random forest model. For organ-specific metastasis in the cohort with distant metastasis, the sensitivity in bone metastasis, brain metastasis and liver metastasis were 0.913, 0.906 and 0.925, respectively. The most important variable was separate tumor nodules with 100% importance. The second important variable was visceral pleural invasion for distant metastasis, while histology for organ-specific metastasis.

Conclusions

Our study developed a “two-step” ANN model for predicting synchronous organ-specific metastasis in LC patients. This ANN model may provide clinicians with more personalized clinical decisions, contribute to rationalize metastasis screening, and reduce the burden on patients and the health care system.

Diagnostic and prognostic nomograms for bone metastasis in small cell lung cancer

Objective

Patients with bone metastasis (BM) of small cell lung cancer (SCLC) have a poor prognosis. We aimed to identify predictors and prognostic factors in patients with BM of SCLC and construct nomograms to predict BM.

Methods

We retrospectively analyzed 18,187 cases from the Surveillance, Epidemiology, and End Results database reported between 2010 and 2016. Differences in overall survival (OS) and cancer-specific survival (CSS) were evaluated after propensity score matching. Independent predictors for BM and prognostic factors for patients with BM of SCLC were determined using univariate and multivariate regression analyses. Two nomograms were constructed and evaluated using C-statistics.

Results

BM was observed in 4014 (22.07%) patients. Kaplan–Meier survival analysis revealed significant differences between BM and non-BM groups. The median OS for patients with and without BM was 6 and 7 months, respectively. The median CSS for patients with and without BM was 9 and 13 months, respectively. Age, sex, tumor size, N stage, chemotherapy, surgery, radiotherapy, and liver/brain/lung metastases were related to BM and independent prognostic factors for OS and CSS. Diagnostic and prognostic nomograms were generated.

Conclusion

Our nomograms predicted the incidence of BM and the 5-month survival rate of patients with SCLC and BM.

Risk and prognostic nomograms for colorectal neuroendocrine neoplasm with liver metastasis: a population-based study

PURPOSE

Liver metastasis (LM) significantly shortens the survival time of colorectal neuroendocrine neoplasms (NENs) patients. This research aimed to explore risk and prognostic factors in colorectal NENs patients with LM and develop nomograms for predicting the risk of LM and survival probability quantitatively.

METHODS

A total of 9926 colorectal NENs patients registered in the Surveillance, Epidemiology, and End Results (SEER) database between 2010 and 2017 were included. Risk factors for LM in colorectal NENs patients were identified by multivariate logistic regression analysis. Potential prognostic factors for colorectal NENs patients with LM were identified by multivariable Cox regression analysis. Nomograms were constructed for quantifying the probability of LM occurrence and survival.

RESULTS

At diagnosis, 8.7% of colorectal NENs patients suffered LM, with 1-, 3-, and 5-year cancer-specific survival (CSS) rates of 44.3%, 26.5%, and 18.0%, respectively. Factors associated with LM occurrence included gender, age at diagnosis, primary tumor location, carcinoembryonic antigen (CEA), histological differentiation, T stage, and N stage. Age at diagnosis, race, histological differentiation, N stage, tumor size, primary tumor location, primary site surgery, and extraliver metastasis were prognostic factors of cancer-specific mortality. The area under the receiver operating characteristics (ROC) curve of the nomogram for predicting LM was 0.888 (95% CI: 0.877-0.898), and the C-index of the nomogram for estimating CSS probability was 0.705 (95% CI: 0.682-0.729).

CONCLUSIONS

This research identified the risk and prognostic factors in colorectal NENs patients with LM. The nomograms constructed by this study can be convenient tools for facilitating clinical decision-making.

A novel model for extrapleural cavity metastasis assessment in patients with lung cancer

Aim: To investigate the clinical value of tumor markers in extrapleural tumor metastasis assessment of newly diagnosed lung cancer patients. Materials & methods: This study retrospectively analyzed 306 patients diagnosed with lung cancer accompanied by tumor metastasis. Patients were grouped into extrapleural tumor metastasis and intrapleural tumor metastasis. Seven serum tumor markers were included for analysis. Results: The area under curves of receiver operating characteristic curve based on binning decision tree algorithm were above 0.8 in both training and validation sets. A scorecard with a score below 3 suggested extrapleural tumor metastasis in newly diagnosed lung cancer patients. Conclusion: The serum tumor marker-derived model is a convenient and fast approach for extrapleural cavity metastasis assessment, which may provide positive implications in newly diagnosed lung cancer patients.

Association of Race, Socioeconomic Factors, and Treatment Characteristics With Overall Survival in Patients With Limited-Stage Small Cell Lung Cancer

IMPORTANCE

It has been established that disparities in race and socioeconomic status are associated with outcomes of non-small cell lung cancer. However, it remains unknown whether this extends to stage I, II, or III small cell lung cancer (SCLC), or limited-stage SCLC (L-SCLC).

OBJECTIVE

To investigate the associations of race, socioeconomic factors, and treatment characteristics with survival among patients with L-SCLC.

DESIGN, SETTING, AND PARTICIPANTS

Demographic information for patients with L-SCLC diagnosed between 2004 and 2014 was obtained from the National Cancer Database. The follow-up end point is death or last follow-up (date of last contact). Patients were divided into 5 mutually exclusive cohorts by race. Data analysis was performed in October 2019.

MAIN OUTCOMES AND MEASURES

Cox proportional hazards models were used to calculate univariable and multivariable models. Multivariable analyses were conducted to assess the associations of race and socioeconomic factors with risk-adjusted outcomes. Overall survival between groups was depicted by Kaplan-Meier curves.

RESULTS

Of 72 409 patients analyzed (median [range] age, 67.0 [23.0-90.0] years), 40 289 (55.6%) were women. The distribution of disease stage was 10 619 patients (14.7%) with stage I disease, 7689 patients (10.6%) with stage II disease, and 54 101 patients (74.7%) with stage III disease. The median (range) duration of follow-up was 8.2 (2.4-15.8) months. Compared with White patients, the hazard of death decreased to 0.92 (95% CI, 0.89-0.95; P < .001) for African American patients and 0.83 (95% CI, 0.77-0.91; P < .001) for Asian patients. The difference in median survival among different racial groups was significant only among those with stage III SCLC. Other factors associated with better survival were female sex, high income, high education, private insurance, diagnostic confirmation by positive cytological analysis, increase in number of sampled regional lymph nodes, and earlier stage at diagnosis.

CONCLUSIONS AND RELEVANCE

This analysis highlights disparities in race and socioeconomic factors associated with outcomes of L-SCLC. Racial minorities, including African American and Asian patients, have better survival than White patients for L-SCLC after adjustment for sociodemographic factors.

Efficacy and safety of PD-1/PD-L1 inhibitor plus chemotherapy versus chemotherapy alone as first-line treatment for extensive-stage small cell lung cancer: A systematic review and meta-analysis

BACKGROUND

Immunotherapy has afforded new treatment options for extensive small cell lung cancer (ES-SCLC). However, reports on the effectiveness of immune checkpoint inhibitors (ICIs) combined with chemotherapy on survival in ES-SCLC patients are inconsistent. Therefore, we conducted a meta-analysis on the efficacy and safety of ICI combined with chemotherapy for ES-SCLC.

METHODS

We searched for randomized controlled clinical trials related to first-line treatment of ES-SCLC with ICI combined with chemotherapy in PUBMED, ESMO, ASCO, and WCLC since 2018. The primary outcome was overall survival (OS).

RESULTS

Four studies were included. Compared to chemotherapy alone, ICI in combination with chemotherapy as first-line treatment reduced the risk of death (hazard ratio [HR]: 0.76; 95% CI: 0.68-0.86; P < 0.00001) and disease progression (HR: 0.76; 95% CI: 0.68-0.84; P < 0.00001). The objective response rate (ORR) with ICI plus chemotherapy was significantly higher than that with chemotherapy alone (HR: 1.10; 95% CI: 1.02-1.19, P = 0.01). The duration of response (DoR) rate at one year was also better with ICI plus chemotherapy (HR: 3.46; 95% CI: 2.24-5.33; P < 0.00001). Security analysis revealed that the incidence of immune-mediated adverse events (imAEs) (HR: 3.77; 95% CI: 1.99-7.15, P < 0.0001) and grade 3/4 imAEs (HR: 7.01; 95% CI: 2.48-19.81; P = 0.0002) increased significantly with ICI plus chemotherapy.

CONCLUSIONS

ICI combined with chemotherapy as first-line treatment can significantly improve the OS and progression-free survival (PFS) of ES-SCLC patients, but the toxicity caused by immunotherapy should be carefully considered.

KEY POINTS

Significant findings of the studyOur meta-analysis shows that PD-L1/PD-1 plus chemotherapy can significantly improve the OS and PFS of ES-SCLC patients when used as first-line therapy.

WHAT THIS STUDY ADDS

This study fills gaps regarding the efficacy of immunotherapy combined with chemotherapy as first-line treatment for ES-SCLC, and provides better evidence for the use of PD-L1/PD-1 immunotherapy plus chemotherapy for patients with ES-SCLC.

Characteristics and risk differences of different tumor sizes on distant metastases of hepatocellular carcinoma: A retrospective cohort study in the SEER database

INTRODUCTION

A typical feature of hepatocellular carcinoma (HCC) is growth with metastasis to distant organs, which is associated with poor survival. Whether tumor size can predict distant metastases in HCC remains unclear.

METHODS

We identified 29,170 HCC patients with or without distant metastases between 2010 and 2016 in the Surveillance, Epidemiology and End Results database. According to an optimal cutoff value of tumor size (58 mm) for predicting distant metastases using Youden's index, patients were categorized into groups of tumor size ≤30 cm, 30-58 mm, and ≥58 mm.

RESULTS

Tumor size had a significantly positive correlation with distant metastases (r = 0.245, P < 0.001). Among patients with distant metastasis, the most common metastasis site was lung (39.3%), followed by bone (30.0%), and brain (2.0%). Incidence of distant metastases in patients with tumor ≥58 mm was 5.7 times (22.8%/4.0%) that of patients with tumors ≤30 mm and 2.9 times (22.8%/7.9%) that of patients with tumors 30-58 mm. Multivariate analyses showed that compared with ≤30 mm, tumor size ≥58 mm was an independent risk predictor of overall distant metastases (OR, 5.200; 95% CI, 4.635-5.834; P<0.001), lung (OR, 6.036; 95% CI, 5.006-7.278; P<0.001); bone (OR, 3.365; 95% CI, 2.781-4.071; P<0.001); and brain metastasis (OR, 1.905; 95% CI, 1.023-3.547; P<0.05).

CONCLUSIONS

Tumor size ≥58 mm is significantly associated with HCC distant metastases. In clinical practice, patients with tumors ≥58 mm may benefit from timely identification of distant metastases.