Developing and validating a novel metabolic tumor volume risk stratification system for supplementing non-small cell lung cancer staging

Pu, Yonglin; Zhang, James; Liu, Haiyan; Appelbaum, Daniel; Meng, Jianfeng; Penney, Bill C.

doi:10.1007/s00259-018-4059-3

Cited by 13 publications

(12 citation statements)

References 31 publications

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“…However, the predictive power of combining the 18 F-FDG PET parameters from both primary tumor and metastatic nodes has not been well investigated. Although some studies have combined the 18 F-FDG PET volumetric parameters from the primary tumor and metastatic lesions, these study cohorts mixed locoregional disease cases with distant metastatic cases [35][36][37][38]. Thus, the results of these studies cannot be applied to patients with locoregional disease due to the diverse prognoses of patients with M0 or M1 diseases.…”

Section: Discussionmentioning

confidence: 99%

Prognostic Value of Combing Primary Tumor and Nodal Glycolytic–Volumetric Parameters of 18F-FDG PET in Patients with Non-Small Cell Lung Cancer and Regional Lymph Node Metastasis

et al. 2021

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We investigated whether the combination of primary tumor and nodal 18F-FDG PET parameters predict survival outcomes in patients with nodal metastatic non-small cell lung cancer (NSCLC) without distant metastasis. We retrospectively extracted pre-treatment 18F-FDG PET parameters from 89 nodal-positive NSCLC patients (stage IIB–IIIC). The Cox proportional hazard model was used to identify independent prognosticators of overall survival (OS) and progression-free survival (PFS). We devised survival stratification models based on the independent prognosticators and compared the model to the American Joint Committee on Cancer (AJCC) staging system using Harrell’s concordance index (c-index). Our results demonstrated that total TLG (the combination of primary tumor and nodal total lesion glycolysis) and age were independent risk factors for unfavorable OS (p < 0.001 and p = 0.001) and PFS (both p < 0.001), while the Eastern Cooperative Oncology Group scale independently predicted poor OS (p = 0.022). Our models based on the independent prognosticators outperformed the AJCC staging system (c-index = 0.732 versus 0.544 for OS and c-index = 0.672 versus 0.521 for PFS, both p < 0.001). Our results indicate that incorporating total TLG with clinical factors may refine risk stratification in nodal metastatic NSCLC patients and may facilitate tailored therapeutic strategies in this patient group.

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Section: Discussionmentioning

confidence: 99%

Prognostic Value of Combing Primary Tumor and Nodal Glycolytic–Volumetric Parameters of 18F-FDG PET in Patients with Non-Small Cell Lung Cancer and Regional Lymph Node Metastasis

et al. 2021

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“…Several clinical and pathological characteristics have been considered as prognostic factors for survival outcomes. Recently multiple published studies have demonstrated that pretreatment tumor burden measured by PET/CT scan was highly correlated with treatment outcomes in LANSCLC patients receiving definitive CCRT [21][22][23]. Bradley et al [18] concluded that GTV determined by three-dimensional conformal radiotherapy (3DCRT) planning had great prognostic value for long-term survival and local control.…”

Section: Discussionmentioning

confidence: 99%

Developing and validating an integrated gross tumor volume (GTV)-TNM stratification system for supplementing unresectable locally advanced non-small cell lung cancer treated with concurrent chemoradiotherapy

Chen

Zhu

et al. 2020

Radiat Oncol

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Purpose The gross tumor volume (GTV) could be an independent prognostic factor for unresectable locally advanced non-small cell lung cancer (LANSCLC). We aimed to develop and validate a novel integrated GTV-TNM stratification system to supplement LANSCLC sub-staging in patients treated with concurrent chemoradiotherapy (CCRT). Methods We performed a retrospective review of 340 patients with unresectable LANSCLC receiving definitive CCRT. All included patients were divided into two randomized cohorts. Then the Kaplan–Meier method and Cox regression were calculated to access the prognostic value of the integrated GTV-TNM stratification system, which was further validated by the area under the receiver operating characteristic curve (AUC) score and F1-score. Results The optimal outcome-based GTV cut-off values (70 and 180 cm3) of the modeling cohort were used to determine each patient’s integrated GTV-TNM stratum in the whole cohort. Our results indicated that a lower integrated GTV-TNM stratum could had better overall survival and progression-free survival (all P < 0.001), which was recognized as an independent prognostic factor. Also, its prognostic value was robust in both the modeling and validation cohorts. Furthermore, the prognostic validity of the integrated GTV-TNM stratification system was validated by significantly improved AUC score (0.636 vs. 0.570, P = 0.027) and F1-score (0.655 vs. 0.615, P < 0.001), compared with TNM stage. Conclusions We proposed a novel integrated GTV-TNM stratification system to supplement unresectable LANSCLC sub-staging due to its prognostic value independent of TNM stage and other clinical characteristics, suggesting that it could be considered in individual treatment decision-making process.

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“…Although incorporating genetic or molecular information could perfectly improve the predictive value of this nomogram and provide more insights into this topic, our nomogram incorporates several valuable clinically available variables and is cheaper than molecular tests, making it a more economical and practical option for survival prediction. PET characteristics of these tumors, such as baseline metabolic tumor volume are innovative and valuable prognostic factors for NSCLC (37)(38)(39). Incorporating these characteristics would definitely make the nomogram more precise and meaningful.…”

Section: Discussionmentioning

confidence: 99%

Development and External Validation of a Nomogram for Predicting Survival in Patients With Stage IA Non-small Cell Lung Cancer ≤2 cm Undergoing Sublobectomy

Yang

Zhang

et al. 2019

Front. Oncol.

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Background: Postoperative prognosis of early stage non-small cell lung cancer (NSCLC) undergoing sublobectomy is heterogeneous. Therefore, we sought to construct a novel survival prediction model for stage IA NSCLC ≤2 cm undergoing sublobectomy.Methods: Based on the data from the Surveillance, Epidemiology, and End Results (SEER) program, we successfully determined and incorporated independent prognostic markers to construct the nomogram. Internal validation of the constructed nomogram was conducted through 1,000 bootstrap resamples. The constructed nomogram was further subjected to external validation with an independent cohort of patients from two Chinese institutions. The performance of the survival prediction model was assessed by concordance index, calibration plots, and risk subgroup classification.Results: A total of 3,238 patients from SEER registries (development cohort), as well as 769 patients from two Chinese institutions (validation cohort) was included. Gender, age, size, histologic type, grade, and examined lymph nodes count were identified as significant prognostic parameters. A novel nomogram was developed and externally validated. Concordance index of constructed nomogram was significantly better than that of the current TNM staging system. Calibration plots demonstrated an optimal consistency between the nomogram predicted and actual observed probability of survival. Survival curves of different risk subgroups within respective TNM stage demonstrated significant distinctions. Conclusion:We developed and externally validated a survival prediction model for patients with stage IA NSCLC ≤2 cm undergoing sublobectomy. This novel nomogram outperforms the conventional TNM staging system and could help clinicians in postoperative surveillance and future clinical trial design.

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Developing and validating a novel metabolic tumor volume risk stratification system for supplementing non-small cell lung cancer staging

Cited by 13 publications

References 31 publications

Prognostic Value of Combing Primary Tumor and Nodal Glycolytic–Volumetric Parameters of 18F-FDG PET in Patients with Non-Small Cell Lung Cancer and Regional Lymph Node Metastasis

Prognostic Value of Combing Primary Tumor and Nodal Glycolytic–Volumetric Parameters of 18F-FDG PET in Patients with Non-Small Cell Lung Cancer and Regional Lymph Node Metastasis

Developing and validating an integrated gross tumor volume (GTV)-TNM stratification system for supplementing unresectable locally advanced non-small cell lung cancer treated with concurrent chemoradiotherapy

Development and External Validation of a Nomogram for Predicting Survival in Patients With Stage IA Non-small Cell Lung Cancer ≤2 cm Undergoing Sublobectomy

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