A Nomogram to Predict Brain Metastases of Resected Non-Small Cell Lung Cancer Patients

Zhang, Fanrong; Zheng, Weihui; Liu, Ying; Wu, Junzhou; Wu, Shaoyuan; Ma, Shenglin; Su, Dan

doi:10.1245/s10434-016-5206-3

Cited by 59 publications

(52 citation statements)

References 25 publications

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“…A multicenter retrospective study showed a high serum NSE level was an independent determinant of poor survival in patients with NSCLC with BM . NSE was identified as a significant predictive factor based on the stage I‐III NSCLC‐resected patients in the study by Zhang . In Ji's study, increased NSE and CA125 levels are both independent risk factors for BM .…”

Section: The Levels Of Tumor Markersmentioning

confidence: 94%

“…For operable NSCLC, the incidence of brain metastases in patients with adenocarcinoma was 2.86 times higher than that in non‐adenocarcinoma patients (95% CI: 1.58‐5.16, P = 0.001) . Adenocarcinoma was also reported to be one of the predictive factors for BM (RR: 3.39; 95% CI: 1.78‐6.46 and P = 0.0002) in a group of stage I‐III NSCLC patients .…”

Section: Pathologymentioning

confidence: 96%

“…However, several studies failed to prove the T and N statuses were predictive factors . The reasons underlying this difference need to be further explored.…”

Section: T and N Statuses And Tumor Stagesmentioning

confidence: 98%

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Risk factors for brain metastases in patients with non–small‐cell lung cancer

Wang

et al. 2018

Cancer Medicine

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Brain metastases (BM) are severe incidents in patients with non–small‐cell lung cancer (NSCLC). The controversial value of prophylactic cranial irradiation (PCI) in NSCLC in terms of survival benefit prompted us to explore the possible risk factors for BM in NSCLC and identify the potential population most likely to benefit from PCI. Risk factors for brain metastases in NSCLC are reviewed in this article. Identifying patients with a higher risk of BM could possibly increase the benefit of PCI while reducing the discomfort and risks caused by unnecessary invasive procedures in the NSCLC patient population. Future studies might focus on finding a solid basis for the prediction of the occurrence of brain metastases and for the therapeutic decision on the use of PCI.

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Section: The Levels Of Tumor Markersmentioning

confidence: 94%

Section: Pathologymentioning

confidence: 96%

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Risk factors for brain metastases in patients with non–small‐cell lung cancer

Wang

et al. 2018

Cancer Medicine

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“…Several trials have shown that PCI is effective in reducing brain metastasis for NSCLC patients; however, there is no survival advantage [7]. The effort to identify lung cancer patients with high risk for developing brain metastasis would be able to avoid excessive treatment for patients with less aggressive tumors and increase the benefits of PCI [8, 9]. In addition, the identification of high risk patients for developing brain metastasis could also be used to establish an optimal follow-up strategy for detecting brain relapse.…”

Section: Discussionmentioning

confidence: 99%

“…However, the value of this approach in the management of non-small cell lung cancer (NSCLC) patients is still in doubt [7]. Hence, defining the predictive factors for brain metastasis development and identifying high risk lung adenocarcinoma patients who will benefit from PCI is meaningful [8–10]. …”

Section: Introductionmentioning

confidence: 99%

Combining Carcinoembryonic Antigen and Platelet to Lymphocyte Ratio to Predict Brain Metastasis of Resected Lung Adenocarcinoma Patients

Wang

Bian

Xia

et al. 2017

BioMed Research International

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We aimed to evaluate the role of pretreatment carcinoembryonic antigen (CEA) and platelet to lymphocyte ratio (PLR) in predicting brain metastasis after radical surgery for lung adenocarcinoma patients. The records of 103 patients with completely resected lung adenocarcinoma between 2013 and 2014 were reviewed. Clinicopathologic characteristics of these patients were assessed in the Cox proportional hazards regression model. Brain metastasis occurred in 12 patients (11.6%). On univariate analysis, N2 stage (P = 0.013), stage III (P = 0.016), increased CEA level (P = 0.006), and higher PLR value (P = 0.020) before treatment were associated with an increased risk of developing brain metastasis. In multivariate model analysis, CEA above 5.2 ng/mL (P = 0.014) and PLR ≥ 120 (P = 0.036) remained as the risk factors for brain metastasis. The combination of CEA and PLR was superior to CEA or PLR alone in predicting brain metastasis according to the receiver operating characteristic (ROC) curve analysis (area under ROC curve, AUC 0.872 versus 0.784 versus 0.704). Pretreatment CEA and PLR are independent and significant risk factors for occurrence of brain metastasis in resected lung adenocarcinoma patients. Combining these two factors may improve the predictability of brain metastasis.

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A nomogram to predict outcomes of lung cancer patients after pneumonectomy based on 47 indicators

et al. 2020

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Aims We aimed to establish a nomogram for lung cancer using patients' characteristics and potential hematological biomarkers. Methods Principle component analysis was used to reduce the dimensions of the data, and each component was transformed into categorical variables based on cutoff values obtained using the X‐tile software. Multivariate analysis was used to determine potential prognostic biomarkers. Five components were used in the predictive nomogram. Internal validation of the model was performed by bootstrapping of samples, while external validation was performed on a separate cohort from Shandong Cancer Hospital. The predictive accuracy of the model was measured by concordance index and risk group stratification. Decision curve analysis was performed to evaluate the net benefit of the models. Results One hundred patients in the Discovery group and 111 patients in the Validation group were retrospectively analyzed in this study. Forty‐seven indexes were sorted into eight subgroups. Five components based on cox regression analysis were enrolled into the predictive nomogram. The nomogram prediction of the probability of 3‐ and 5‐year overall survival was in great concordance with the actual observations. Of interest, the nomogram allowed better risk stratification of patients and better accuracy in predicting patients' survival compared with pathological tumor‐node‐metastasis staging system. Conclusion A nomogram was established for prognosis of lung cancer, which can be used for treatment selection and clinical care management.

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A Nomogram to Predict Brain Metastases of Resected Non-Small Cell Lung Cancer Patients

Abstract: The nomogram developed in this study demonstrated its discrimination capability for predicting 3- and 5-year occurrence of brain metastases, and can be used to identify high-risk patients.

Cited by 59 publications

References 25 publications

Risk factors for brain metastases in patients with non–small‐cell lung cancer

Risk factors for brain metastases in patients with non–small‐cell lung cancer

Combining Carcinoembryonic Antigen and Platelet to Lymphocyte Ratio to Predict Brain Metastasis of Resected Lung Adenocarcinoma Patients

A nomogram to predict outcomes of lung cancer patients after pneumonectomy based on 47 indicators

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