Tags

Type your tag names separated by a space and hit enter

Development and validation of nomograms for predicting survival probability of patients with advanced adenocarcinoma in different EGFR mutation status.
PLoS One 2019; 14(8):e0220730Plos

Abstract

INTRODUCTION

Molecular markers are important variables in the selection of treatment for cancer patients and highly associated with their survival. Therefore, a nomogram that can predict survival probability by incorporating epidermal growth factor receptor mutation status and treatments for patients with advanced adenocarcinoma would be highly valuable. The aim of the study is to develop and validate a novel nomogram, incorporating epidermal growth factor receptor mutation status and treatments, for predicting 1-year and 2-year survival probability of patients with advanced adenocarcinoma.

MATERIAL AND METHODS

Data on 13,043 patients between June 1, 2011, and December 31, 2014 were collected. Seventy percent of them were randomly assigned to the training cohort for nomogram development, and the remaining 30% assigned to the validation cohort. The most important factors for constructing the nomogram were identified using multivariable Cox regression analysis. The discriminative ability and calibration of the nomograms were tested using C-statistics, calibration plots, and Kaplan-Meier curves.

RESULTS

In the training cohort, 1-year and 2-year OS were 52.8% and 28.5% in EGFR(-) patients, and 73.9% and 44.1% in EGFR(+) patients, respectively. In EGFR(+) group, factors selected were age, gender, congestive heart failure, renal disease, number of lymph node examined, tumor stage, surgical intervention, radiotherapy, first-line chemotherapy, ECOG performance status, malignant pleural effusion, and smoking. In EGFR(-) group, factors selected were age, gender, myocardial infarction, cerebrovascular disease, chronic pulmonary disease, number of lymph node examined, tumor stage, surgical intervention, radiotherapy, ECOG performance status, malignant pleural effusion, and a history of smoking. Two nomograms show good accuracy in predicting OS, with a concordance index of 0.83 in EGFR(+) and of 0.88 in EGFR(-).

CONCLUSIONS

The survival prediction models can be used to make individualized predictions with different EGFR mutation status and a useful tool for selecting regimens for treating advanced adenocarcinoma.

Authors+Show Affiliations

Institute of Health Policy and Management, College of Public Health, National Taiwan University, Taipei, Taiwan.National Research Institute of Chinese Medicine, Ministry of Health and Welfare, Taipei, Taiwan. Institute of Hospital and Health Care Administration, National Yang-Ming University, Taipei, Taiwan.School of Health Care Administration, Taipei Medical University, Taipei, Taiwan.Departments of Oncology, National Taiwan University Cancer Center, National Taiwan University, Taipei, Taiwan. Department of Internal Medicine, College of Medicine, National Taiwan University, Taipei, Taiwan.Institute of Health Policy and Management, College of Public Health, National Taiwan University, Taipei, Taiwan.

Pub Type(s)

Journal Article

Language

eng

PubMed ID

31419239

Citation

Chen, Hsi-Chieh, et al. "Development and Validation of Nomograms for Predicting Survival Probability of Patients With Advanced Adenocarcinoma in Different EGFR Mutation Status." PloS One, vol. 14, no. 8, 2019, pp. e0220730.
Chen HC, Tan EC, Liao CH, et al. Development and validation of nomograms for predicting survival probability of patients with advanced adenocarcinoma in different EGFR mutation status. PLoS ONE. 2019;14(8):e0220730.
Chen, H. C., Tan, E. C., Liao, C. H., Lin, Z. Z., & Yang, M. C. (2019). Development and validation of nomograms for predicting survival probability of patients with advanced adenocarcinoma in different EGFR mutation status. PloS One, 14(8), pp. e0220730. doi:10.1371/journal.pone.0220730.
Chen HC, et al. Development and Validation of Nomograms for Predicting Survival Probability of Patients With Advanced Adenocarcinoma in Different EGFR Mutation Status. PLoS ONE. 2019;14(8):e0220730. PubMed PMID: 31419239.
* Article titles in AMA citation format should be in sentence-case
TY - JOUR T1 - Development and validation of nomograms for predicting survival probability of patients with advanced adenocarcinoma in different EGFR mutation status. AU - Chen,Hsi-Chieh, AU - Tan,Elise Chia-Hui, AU - Liao,Chih-Hsien, AU - Lin,Zhong-Zhe, AU - Yang,Ming-Chin, Y1 - 2019/08/16/ PY - 2019/04/02/received PY - 2019/07/22/accepted PY - 2019/8/17/entrez PY - 2019/8/17/pubmed PY - 2019/8/17/medline SP - e0220730 EP - e0220730 JF - PloS one JO - PLoS ONE VL - 14 IS - 8 N2 - INTRODUCTION: Molecular markers are important variables in the selection of treatment for cancer patients and highly associated with their survival. Therefore, a nomogram that can predict survival probability by incorporating epidermal growth factor receptor mutation status and treatments for patients with advanced adenocarcinoma would be highly valuable. The aim of the study is to develop and validate a novel nomogram, incorporating epidermal growth factor receptor mutation status and treatments, for predicting 1-year and 2-year survival probability of patients with advanced adenocarcinoma. MATERIAL AND METHODS: Data on 13,043 patients between June 1, 2011, and December 31, 2014 were collected. Seventy percent of them were randomly assigned to the training cohort for nomogram development, and the remaining 30% assigned to the validation cohort. The most important factors for constructing the nomogram were identified using multivariable Cox regression analysis. The discriminative ability and calibration of the nomograms were tested using C-statistics, calibration plots, and Kaplan-Meier curves. RESULTS: In the training cohort, 1-year and 2-year OS were 52.8% and 28.5% in EGFR(-) patients, and 73.9% and 44.1% in EGFR(+) patients, respectively. In EGFR(+) group, factors selected were age, gender, congestive heart failure, renal disease, number of lymph node examined, tumor stage, surgical intervention, radiotherapy, first-line chemotherapy, ECOG performance status, malignant pleural effusion, and smoking. In EGFR(-) group, factors selected were age, gender, myocardial infarction, cerebrovascular disease, chronic pulmonary disease, number of lymph node examined, tumor stage, surgical intervention, radiotherapy, ECOG performance status, malignant pleural effusion, and a history of smoking. Two nomograms show good accuracy in predicting OS, with a concordance index of 0.83 in EGFR(+) and of 0.88 in EGFR(-). CONCLUSIONS: The survival prediction models can be used to make individualized predictions with different EGFR mutation status and a useful tool for selecting regimens for treating advanced adenocarcinoma. SN - 1932-6203 UR - https://www.unboundmedicine.com/medline/citation/31419239/Development_and_validation_of_nomograms_for_predicting_survival_probability_of_patients_with_advanced_adenocarcinoma_in_different_EGFR_mutation_status L2 - http://dx.plos.org/10.1371/journal.pone.0220730 DB - PRIME DP - Unbound Medicine ER -