Prognostic Value of Clinical Staging According to TNM in Patients With SCLC: A Real-World Surveillance Epidemiology and End-Results Database Analysis

Arriola, Edurne; Trigo, José; Gastaldo, A. Sánchez; Navarro, Alejandro; Pérez, C. Fernández; Crama, Leonardo; Aix, Santiago Ponce

doi:10.1016/j.jtocrr.2021.100266

Cited by 7 publications

(5 citation statements)

References 15 publications

(18 reference statements)

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“…LS-SCLC comprises most patients with 8 th edition tumor, node, metastasis (TNM) stage I-IIIB and some with stage IIIC, while ES-SCLC includes the balance of patients with stage IIIC and all patients with stage IV disease ( 4 ). Between 60% and 70% of patients with SCLC are diagnosed with ES-SCLC ( 3 , 5 , 6 ), and approximately 95% of ES-SCLC cases are classified as TNM stage IV ( 7 ). Prognosis for ES-SCLC has remained poor over the past 20 years ( 8 – 10 ), with a median survival interval of 7–12 months, two-year survival rate of <5%, and five-year survival rate of 1%-2% ( 2 , 6 , 11 , 12 ); however, higher survival rates have been observed in some cohorts.…”

Section: Introductionmentioning

confidence: 99%

Real-world predictors of survival in patients with extensive-stage small-cell lung cancer in Manitoba, Canada: a retrospective cohort study

Dawe,

Rittberg,

Syed

et al. 2023

Front. Oncol.

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BackgroundExtensive-stage small-cell lung cancer (ES-SCLC) is an incurable cancer with poor prognosis in which characteristics predictive of long-term survival are debated. The utility of agents such as immune checkpoint inhibitors highlights the importance of identifying key characteristics and treatment strategies that contribute to long-term survival and could help guide therapeutic decisions.ObjectiveThis real-world analysis examines the characteristics, treatment patterns, and clinical outcomes of patients receiving chemotherapy without immunotherapy for ES-SCLC in Manitoba, Canada.MethodsA retrospective cohort study assessed patient characteristics, treatment, and survival duration (short: <6 months; medium: 6–24 months; long: >24 months) using the Manitoba Cancer Registry and CancerCare Manitoba records. Eligible patients were aged >18 years with cytologically confirmed ES-SCLC diagnosed between January 1, 2004, and December 31, 2018, and received cytotoxic chemotherapy (CT). The one-, two-, and five-year probabilities of overall survival (OS) were assessed relative to patient, disease, and treatment characteristics using Kaplan-Meier methods and Cox proportional hazards models.ResultsThis analysis included 537 patients. Cisplatin was used in 56.1% of patients, 45.6% received thoracic radiotherapy (RT), and few received prophylactic cranial irradiation (PCI). In the overall cohort, one-, two- and five-year OS rates were 26%, 8%, and 3%, respectively. For patients with Eastern Cooperative Oncology Group Performance Status (ECOG PS) 0, OS rates at one, two, and five years were 43%, 17%, and 10%, respectively, vs. 27%, 8%, and 2% for those with ECOG PS 1–2, and 16%, 3%, and 3% for those with ECOG PS 3–4. In long-term survivors, ECOG PS scores were lower and abnormal laboratory test results were less frequent. Overall, 74.4% of long-term survivors received thoracic RT and 53.5% received PCI. Known poor prognostic factors – including brain/liver metastases, high lactate dehydrogenase (LDH), abnormal sodium, and low hemoglobin levels – were less common but still seen in long-term survivors.ConclusionAlthough rare, patients with ES-SCLC may experience long-term survival with CT ± thoracic RT ± PCI. Factors predicting long-term survival include traditional prognostic factors such as ECOG PS, LDH level, and receipt of thoracic RT or PCI. These findings support current treatment algorithms for ES-SCLC and provide baseline survival estimates to assess the real-world impact of adding immune checkpoint inhibitors in the future.

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Section: Introductionmentioning

confidence: 99%

Real-world predictors of survival in patients with extensive-stage small-cell lung cancer in Manitoba, Canada: a retrospective cohort study

Dawe,

Rittberg,

Syed

et al. 2023

Front. Oncol.

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“…However, within each stage group, there is much variation; some individuals advance their illness quickly, while others live for a very long time without experiencing a recurrence. Therefore, finding patient and tumor-related features is necessary to categorize patients according to their stage and individually tailor their treatments ( 119 ).…”

Section: Additional Factors As Prognostic Indicators For Lung Cancermentioning

confidence: 99%

Serum cytokine levels and other associated factors as possible immunotherapeutic targets and prognostic indicators for lung cancer

Zhao

Jia²,

Zhang³

2023

Front. Oncol.

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Lung cancer is one of the most prevalent cancer types and the leading cause of cancer-related deaths worldwide. Non-small cell lung cancer (NSCLC) accounts for 80-85% of all cancer incidences. Lung cancer therapy and prognosis largely depend on the disease’s degree at the diagnosis time. Cytokines are soluble polypeptides that contribute to cell-to-cell communication, acting paracrine or autocrine on neighboring or distant cells. Cytokines are essential for developing neoplastic growth, but they are also known to operate as biological inducers following cancer therapy. Early indications are that inflammatory cytokines such as IL-6 and IL-8 play a predictive role in lung cancer. Nevertheless, the biological significance of cytokine levels in lung cancer has not yet been investigated. This review aimed to assess the existing literature on serum cytokine levels and additional factors as potential immunotherapeutic targets and lung cancer prognostic indicators. Changes in serum cytokine levels have been identified as immunological biomarkers for lung cancer and predict the effectiveness of targeted immunotherapy.

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“…The TNM staging according to the AJCC guidelines was used to guide clinical decision-making and prognosis evaluation. However, a previous study [3] had shown that the applicability of TNM staging to assess extensive-stage small-cell lung cancer (ES-SCLC) prognosis in clinical practice remains uncertain. Therefore, it is necessary to search for more reliable biomarkers to predict the prognosis of ES-SCLC, to accurately guide clinical treatment.…”

Section: Introductionmentioning

confidence: 99%

Risk Stratification and Overall Survival Prediction in extensive stage Small Cell Lung Cancer after chemotherapy with immunotherapy Based on CT Radiomics

Wang,

Chen,

Chen

et al. 2024

Preprint

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Purpose The prognosis of extensive-stage small cell lung cancer is usually poor. In this study, a combined model based on pre-treatment CT radiomics and clinical features was constructed to predict the OS of extensive-stage small cell lung cancer after chemotherapy with immunotherapy. Methods Clinical data of 111 patients with extensive stage small-cell lung cancer who received first-line immunotherapy combined with chemotherapy in our hospital from December 2019 to December 2021 were retrospectively collected. Finally, 93 patients were selected for inclusion in the study, and CT images were obtained through PACS system before treatment. All patients were randomly divided into a training set (n = 66) and a validation set (n = 27). Images were imported into ITK-SNAP to outline areas of interest, and Python software was used to extract radiomics features. A total of 1781 radiomics features were extracted from each patient's images. The feature dimensions were reduced by MRMR and LASSO methods, and the radiomics features with the greatest predictive value were screened. The weight coefficient of radiomics features was calculated, and the linear combination of the feature parameters and the weight coefficient was used to calculate Radscore. Univariate cox regression analysis was used to screen out the factors significantly associated with prognosis from the radiomics and clinical features, and multivariate cox regression analysis was performed to establish the prognosis prediction model of extensive stage small cell lung cancer. Results The degree of metastases was selected as a significant clinical prognostic factor by univariate cox regression analysis. Seven radiomics features with significance were selected by LASSO-COX regression analysis, and the Radscore was calculated according to the coefficient of the radiomics features. An alignment diagram survival prediction model was constructed by combining Radscore with the number of metastatic lesions. The study population was stratified into those who survived less than 11 months, and those with a greater than 11 month survival. The C-index was 0.722 (se = 0.044) and 0.68(se = 0.074) in the training and the validation sets, respectively. The Log_rank test results of the combination model were as follows: training set: p < 0.0001, validation set: p = 0.00042. Conclusion In this study, a combined model based on radiomics and clinical features could predict OS in patients with extensive stage small cell lung cancer after chemotherapy with immunotherapy, which could help guide clinical treatment strategies.

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Prognostic Value of Clinical Staging According to TNM in Patients With SCLC: A Real-World Surveillance Epidemiology and End-Results Database Analysis

Cited by 7 publications

References 15 publications

Real-world predictors of survival in patients with extensive-stage small-cell lung cancer in Manitoba, Canada: a retrospective cohort study

Real-world predictors of survival in patients with extensive-stage small-cell lung cancer in Manitoba, Canada: a retrospective cohort study

Serum cytokine levels and other associated factors as possible immunotherapeutic targets and prognostic indicators for lung cancer

Risk Stratification and Overall Survival Prediction in extensive stage Small Cell Lung Cancer after chemotherapy with immunotherapy Based on CT Radiomics

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