Sex as an Independent Prognostic Factor in a Population-Based, Non-Small Cell Lung Cancer Cohort

Pitz, Marshall; Musto, Grace; Navaratnam, S.

doi:10.1155/2013/618691

Cited by 28 publications

(21 citation statements)

References 28 publications

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“…Studies evaluating the effect of gender on long‐term survival in lung cancer have shown that female patients had longer survival times than male patients . In the present study, male/female ratio was 2.3, and the survival time was longer in female patients than in male patients in line with the literature ( P < 0.0001).…”

Section: Discussionsupporting

confidence: 91%

Prognostic factors affecting survival in non‐small cell lung carcinoma patients with malignant pleural effusions

Kasapoğlu

Arınç

Güngör

et al. 2015

Clinical Respiratory J

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Section: Discussionsupporting

confidence: 91%

Prognostic factors affecting survival in non‐small cell lung carcinoma patients with malignant pleural effusions

Kasapoğlu

Arınç

Güngör

et al. 2015

Clinical Respiratory J

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“…The indicators are staging, grading, age, and histopathology. In the study by Pitz et al, [11] the survival rate and prognosis of women with lung adenocarcinoma were significantly better than those of men. In this study, statistical analysis showed that age was not an independent factor affecting prognosis, which was consistent with previous studies.…”

Section: Discussionmentioning

confidence: 99%

Exploring the survival prognosis of lung adenocarcinoma based on the cancer genome atlas database using artificial neural network

Jiang

2019

Medicine

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The aim of this study was to investigate the clinical factors affecting the survival prognosis of lung adenocarcinoma, and to establish a predictive model of survival prognosis of lung adenocarcinoma by artificial neural network. Download the cancer genome atlas (TCGA) database for lung adenocarcinoma research data, perform cox regression analysis and descriptive statistics on the obtained clinical data, draw the survival curve by Kaplan–Meier method, select the independent variables that are statistically significant for constructing the artificial neural networks (ANN) model, and establish artificial neural network model. The number of valid cases included in the study was 524, including 280 men and 244 women, with an age range of 33 to 88 years, mean age 66.87 years, and median progression-free survival (PFS) was 37.7 months. The median overall survival time (OS) was 41.1 months. Cox multivariate analysis showed that smoking history, tumor stage, and surgical margin resection status were independently associated with PFS, and tumor stage and surgical margin resection status were independently associated with OS. The accuracy of the established ANN model itself was predicted to be 65.8%. The accuracy of correctly predicting the prognosis of the predicted samples was 75.0%, and the area under the receiver operating characteristic curve was 0.712. The clinical prognostic factors of lung adenocarcinoma include: smoking history, tumor stage, and surgical margin resection status. The established ANN model can be used to predict the prognosis of lung adenocarcinoma.

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“…The most important unfavorable prognostic factors for lung cancer patients are advanced stage, weight loss, poor performance status non surgical treatment and male gender (Mould and Wiliams, 1982, Ramalingam et al, 1998, Radzikowska et al, 2002, Yang et al, 2001, Pitz et al, 2013. Caldarella et al reported that, among women, survival was significantly better for adenocarcinoma patients than for those with squamous cell carcinoma.…”

Section: Discussionmentioning

confidence: 99%

Lung Cancer in Women: A Single Institution Experience with 50 Patients

Babacan

Yücel²,

Kılıçkap³

et al. 2014

Asian Pacific Journal of Cancer Prevention

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Background: Lung cancer is the most common cause of cancer-related death worldwide. The incidence of lung cancer is aproximately 7-8 thousand percent in Turkish women. In this study, we aimed to evaluate the clinical, pathological properties and survival data of female patients with lung cancer who were treated in our center. Materials and Methods: From 2007 to 2012, 50 women with lung cancer were enrolled. Patient data were evaluated retrospectively. Results: The median age was 61 (40-81). Forty patients (80%) were diagnosed with non small cell lung cancer (NSCLC), 10 patients (20%) were small cell carcinoma (SCC). Twelve (24%) patients were smokers and 13 of 16 non-smokers had a history of exposure to asbestos. The most common histologic subtype was adenocarcinoma (46%) and this accounted for 71% in patients with exposure to asbestos. The most common initial Eastern Cooperative Oncology Group (ECOG) performance score was 1 (24 patients, 48%) and initial stage was IV (25 patients, 50%) in the study group. During the median 15 months (1-96 months) follow up period: 1 year overall survival (OS) was 68%, 2 year overall survival was 36% and the median survival time was 19 months. According to univariate analysis, poor ECOG performance status, advanced stage, anemia and weight loss at time of diagnosis were negative prognostic factors. However, adenocarcinoma sub-type was a positive prognostic factor. Conclusions: In this study NSCLC sub-type, poor ECOG performance score, advanced stage, anemia and weight loss were prognostic factors in Turkish women with lung cancer.

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Sex as an Independent Prognostic Factor in a Population-Based, Non-Small Cell Lung Cancer Cohort

Abstract: Females experienced a significantly better survival rate than males independent of treatment, age, year of diagnosis and histology. This was greatest in surgically treated patients and in those with adenocarcinoma.

Cited by 28 publications

References 28 publications

Prognostic factors affecting survival in non‐small cell lung carcinoma patients with malignant pleural effusions

Prognostic factors affecting survival in non‐small cell lung carcinoma patients with malignant pleural effusions

Exploring the survival prognosis of lung adenocarcinoma based on the cancer genome atlas database using artificial neural network

Lung Cancer in Women: A Single Institution Experience with 50 Patients

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