A Retrospective Evaluation of Chemotherapy Regimens in Unselected Patients with Metastatic Non-Small Cell Lung Cancer

Badawy, Ahmed Ashour; Omar, Abdelsattar M.; Arafat, Waleed; Khedr, Gehan; Bae, Suk Joo; Grant, Stefan C.

doi:10.4236/jct.2018.93029

Cited by 6 publications

(6 citation statements)

References 17 publications

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“…32,33 NSCLC patients with distant metastasis are closely related to significantly reduced OS. 34 A previous study reported that LUAD occupied about 50% of all the lung cancer patients with bone metastasis. 35 LUAD individuals also displayed a 2.86-fold higher risk of brain metastases occur compared with other types of NSCLC individuals.…”

Section: Discussionmentioning

confidence: 98%

Development and Validation of a Prognostic Model to Predict Overall Survival for Lung Adenocarcinoma: A Population-Based Study From the SEER Database and the Chinese Multicenter Lung Cancer Database

Wang

Chang

et al. 2022

Technol Cancer Res Treat

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Background: Lung adenocarcinoma (LUAD) is the most common subtype of non-small-cell lung cancer (NSCLC). The aim of our study was to determine prognostic risk factors and establish a novel nomogram for lung adenocarcinoma patients. Methods: This retrospective cohort study is based on the Surveillance, Epidemiology, and End Results (SEER) database and the Chinese multicenter lung cancer database. We selected 22,368 eligible LUAD patients diagnosed between 2010 and 2015 from the SEER database and screened them based on the inclusion and exclusion criteria. Subsequently, the patients were randomly divided into the training cohort (n = 15,657) and the testing cohort (n = 6711), with a ratio of 7:3. Meanwhile, 736 eligible LUAD patients from the Chinese multicenter lung cancer database diagnosed between 2011 and 2021 were considered as the validation cohort. Results: We established a nomogram based on each independent prognostic factor analysis for 1-, 3-, and 5-year overall survival (OS) . For the training cohort, the area under the curves (AUCs) for predicting the 1-, 3-, and 5-year OS were 0.806, 0.856, and 0.886. For the testing cohort, AUCs for predicting the 1-, 3-, and 5-year OS were 0.804, 0.849, and 0.873. For the validation cohort, AUCs for predicting the 1-, 3-, and 5-year OS were 0.86, 0.874, and 0.861. The calibration curves were observed to be closer to the ideal 45° dotted line with regard to 1-, 3-, and 5-year OS in the training cohort, the testing cohort, and the validation cohort. The decision curve analysis (DCA) plots indicated that the established nomogram had greater net benefits in comparison with the Tumor-Node-Metastasis (TNM) staging system for predicting 1-, 3-, and 5-year OS of lung adenocarcinoma patients. The Kaplan–Meier curves indicated that patients’ survival in the low-risk group was better than that in the high-risk group ( P < .001). Conclusion: The nomogram performed very well with excellent predictive ability in both the US population and the Chinese population.

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Section: Discussionmentioning

confidence: 98%

Development and Validation of a Prognostic Model to Predict Overall Survival for Lung Adenocarcinoma: A Population-Based Study From the SEER Database and the Chinese Multicenter Lung Cancer Database

Wang

Chang

et al. 2022

Technol Cancer Res Treat

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“…As for our univariate dissection, we discovered an essential link with metastasis to the liver, adrenal glands and central nervous system, bringing about a worse prognosis of survival. Liver involvement has been shown to have a worse prognosis in different studies (Ashour Badawy et al, 2018;Liu et al, 2021). As for other researches, the bone involvement was associated with prognosis among the patients with EGFR mutations receiving TKI (LeVasseur et al, 2016;Knapp et al, 2022).…”

Section: Discussionmentioning

confidence: 81%

To establish a prognostic model of epidermal growth factor receptor mutated non-small cell lung cancer patients based on Least Absolute Shrinkage and Selection Operator regression

Li,

Zhang

2023

European Journal of Cancer Prevention

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Background There is currently a shortage of effective diagnostic tools that are used for identifying long-term survival among non-small cell lung cancer (NSCLC) patients with epidermal growth factor receptor (EGFR) mutations. This research utilized the development of a prognostic model to assist clinicians in forecasting the survival over 24 months. Methods In Phase III and IV those patients who were diagnosed with EGFR mutation from January 2018 to June 2022 were enrolled into the lung cancer group of Thoracic Surgery Department of Hebei Provincial People’s Hospital. Long-run survival was stated as survival for 24 months after being diagnosed. A multivariate prognostic pattern was constructed by means of internal validation and binary logistic regression by bootstrapping. One nomogram was created with a view to boosting the explanation and applicability of the pattern. Results A total of 603 patients with EGFR mutation were registered. Elements linked to the whole survival beyond 24 months were age (OR 6.15); female (OR 1.79); functional status (ECOG 0–1) (OR 5.26); Exon 20 insertion mutation deletion (OR 2.08); No central nervous system metastasis (OR 2.66), targeted therapy (OR 0.43); Immunotherapy (OR 0.24). The model has good internal validation. Conclusion Seven pretreatment clinicopathological variables predicted survival over 24 months. That pattern owns a great discriminative capability. It is hypothesized that this pattern is capable of assisting in selecting the optimal treatment sequence for NSCLC patients with EGFR mutations.

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“…These results are also supported by other studies. Badawy et al [28] investigated the effects of the metastatic site on the OS of patients with stage IV NSCLC. They found a statistically significant decrease in OS in patients with liver, adrenal and abdominal lymph node metastasis.…”

Section: Discussionmentioning

confidence: 99%

Integrated 18F-FDG PET/CT parameter defines metabolic oligometastatic non-small cell lung cancer

Zhao

et al. 2022

Nuclear Medicine Communications

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AimsThe purpose of this study was to define metabolic oligometastatic non-small cell lung cancer (NSCLC) by using the number of metastatic lesions and 18 F-FDG PET/ CT parameters. MethodsOne hundred twenty-four newly diagnosed stage IV NSCLC patients who received pretreatment 18 F-FDG PET/CT examination were retrospectively analyzed. The maximum standardized uptake value (SUV max ) of primary and metastatic lesions and the collected clinical parameters were fed into the univariate and multivariate Cox proportional hazard model. Survival analysis was performed using Kaplan-Meier and log-rank test. ResultsIn univariate analysis, the results revealed that histology, metastatic organ numbers, adrenal gland metastasis, SUVmax of both primary and metastatic lesions, lactate dehydrogenase, systemic treatment, and local treatment were significantly correlated with overall survival of stage IV NSCLC patients. Multivariate analysis demonstrated that SUVmax of primary lesions and systemic treatment were independent risk factors of stage IV NSCLC patients. The addition of primary lung cancer SUVmax to traditional method (only count the numbers of metastasis lesions) enhanced the identification of oligometastatic NSCLC and the C-index increased from 0.601 to 0.693. ConclusionWe developed a method for the definition of metabolic oligometastatic NSCLC, which combined the number of organs involved, the number of metastatic lesions, and the SUV max of primary lung cancer. Nucl Med Commun 43: 1026

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A Retrospective Evaluation of Chemotherapy Regimens in Unselected Patients with Metastatic Non-Small Cell Lung Cancer

Cited by 6 publications

References 17 publications

Development and Validation of a Prognostic Model to Predict Overall Survival for Lung Adenocarcinoma: A Population-Based Study From the SEER Database and the Chinese Multicenter Lung Cancer Database

Development and Validation of a Prognostic Model to Predict Overall Survival for Lung Adenocarcinoma: A Population-Based Study From the SEER Database and the Chinese Multicenter Lung Cancer Database

To establish a prognostic model of epidermal growth factor receptor mutated non-small cell lung cancer patients based on Least Absolute Shrinkage and Selection Operator regression

Integrated 18F-FDG PET/CT parameter defines metabolic oligometastatic non-small cell lung cancer

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