Abstract 1446
Background
Lung cancer accounts for one-quarter of all cancer deaths around the world. The identification of novel biomarkers from blood to differentiate tumors from normal tissue and to predict tumor behavior and patients’ survival is of great importance in clinical practice. We aimed to establish a nomogram with patients’ characteristics and all available hematological biomarkers for lung cancer patients.
Methods
All indexes were cataloged according to clinical significance. Principle component analysis (PCA) was used to reduce the dimensions. Each component was transformed into categorical variables based on recognized cut-off values from receiver operating characteristic (ROC) curve. Kaplan-Meier analysis with log-rank test was used to evaluate the prognostic value of each component. Multivariate analysis was used to determine the promising prognostic biomarkers. Five components were entered into a predictive nomogram. The model was subjected to bootstrap internal validation and to external validation with a separate cohort from Shandong Cancer Hospital. The predictive accuracy and discriminative ability were measured by concordance index (C index) and risk group stratification.
Results
Two hundred and fourty-eight patients were retrospectively analyzed in this study, with 134 in the Discovery Group and 114 in the Validation Group. Forty-seven indexes were sorted into 8 subgroups, and 20 principle components were extracted for further survival analysis. Via cox regression analysis, five components were significant and entered into predictive nomograms. The calibration curves for probability of 3-, and 5-year overall survival (OS) showed optimal agreement between nomogram prediction and actual observation. The new scoring system according to nomogram allowed significant distinction between survival curves within respective tumor-node-metastasis (TNM) subgroups.
Conclusions
A nomogram based on the clinical indexes was established for survival prediction of lung cancer patients, which can be used for treatment therapy selection and clinical care option. PCA makes big data analysis feasible.
Clinical trial identification
Editorial acknowledgement
Legal entity responsible for the study
The authors.
Funding
Has not received any funding.
Disclosure
All authors have declared no conflicts of interest.
Resources from the same session
603 - Mendelian Randomization Study of Alzheimer's Disease and Lung Cancer
Presenter: Huaqiang Zhou
Session: Poster Display session 1
Resources:
Abstract
4462 - Spanish registry of thoracic tumors (TTR): Interim analyses of comorbidities, risk associations, personal and family history of cancer
Presenter: Rafael Lopez Castro
Session: Poster Display session 1
Resources:
Abstract
3957 - Pleural effusion TGF-beta is highly diagnostic and prognostic in malignant pleural mesothelioma
Presenter: Paul Stockhammer
Session: Poster Display session 1
Resources:
Abstract
3583 - Immune microenvironment modulation by p14/ARF in Malignant Pleural Mesothelioma
Presenter: Giulia Pasello
Session: Poster Display session 1
Resources:
Abstract
4255 - Tumor Treating Fields plus chemotherapy for first-line malignant pleural mesothelioma (MPM): radiological responses in the STELLAR trial
Presenter: Federica Grosso
Session: Poster Display session 1
Resources:
Abstract
1803 - Effects of Tumor Treating Fields (TTFields; 150 kHz) and Cisplatin or Pemetrexed Combination Therapy on Mesothelioma cells In Vitro and In Vivo
Presenter: Mijal Munster
Session: Poster Display session 1
Resources:
Abstract
2660 - Real world use of systemic therapy in elderly patients with malignant pleural mesothelioma (MPM)
Presenter: Susana Cedres
Session: Poster Display session 1
Resources:
Abstract
3150 - Pemetrexed/Cisplatin versus Gemcitabine/Cisplatin as first-line treatment for Egyptian patients with malignant pleural mesothelioma
Presenter: Mohamed Alorabi
Session: Poster Display session 1
Resources:
Abstract
4319 - Accuracy of pathologic evaluation for thymic epithelial tumors in an Italian reference Centre
Presenter: Giulia Galli
Session: Poster Display session 1
Resources:
Abstract
4811 - Comprehensive genomic profiling of thymic carcinoma in a sample Chinese population
Presenter: Baohui Han
Session: Poster Display session 1
Resources:
Abstract