Skip to main page content
Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
. 2019 Aug 16;14(8):e0220730.
doi: 10.1371/journal.pone.0220730. eCollection 2019.

Development and Validation of Nomograms for Predicting Survival Probability of Patients With Advanced Adenocarcinoma in Different EGFR Mutation Status

Affiliations
Free PMC article

Development and Validation of Nomograms for Predicting Survival Probability of Patients With Advanced Adenocarcinoma in Different EGFR Mutation Status

Hsi-Chieh Chen et al. PLoS One. .
Free PMC article

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.

Conflict of interest statement

The authors have declared that no competing interests exist.

Figures

Fig 1
Fig 1. Prediction probability nomograms (1-year and 2-year).
(A) EGFR mutation positive (EGFR(+)) patients. (B) EGFR wide-type (EGFR(-)) patients.
Fig 2
Fig 2. Survival probability (according to quartiles of total points) for 1-year survival.
(A) EGFR mutation positive (EGFR(+)) patients. (B) EGFR wild-type (EGFR(-)) patient. The quartiles of EGFR mutation positive patients is defined as follows: quartile 1: 0 to 177 points; quartile 2: 178–207 points; quartile 3: 208–236 points; quartile 4: ≧237 points. The quartiles of EGFR wild-type patients defined as follows: quartile 1: 0 to 156 points; quartile 2: 157–182 points; quartile 3: 183–210 points; quartile 4:≧211 points.
Fig 3
Fig 3. Calibration of nomograms.
Calibration curves of the nomogram. (A) 1-year survival probability of EGFR(+) patients. (B) 2-year survival probability of EGFR (+) patients. (C) 1-year probability of EGFR(-) patients. (D) 2-year survival probability of EGFR (-) patient. The calibration curves were close to the 45-degres line.

Similar articles

See all similar articles

References

    1. American Cancer Society. Cancer facts and figures 2016: American Cancer Society; [cited 2017 Octorber 26]. Available from: http://www.cancer.org/Research/CancerFactsStatistics/cancerfactsfigures2016/cancerfactsandfigures2016.
    1. American Cancer Society. What is non-small cell lung cancer? American Cancer Society [cited 2017 October 6]. Available from: http://www.cancer.org/cancer/lungcancer-non-smallcell/detailedguide/non-small-cell-lung-cancer-what-is-non-small-cell-lung-cancer.
    1. Ettinger DS, Akerley W, Bepler G, Blum MG, Chang A, Cheney RT, et al. Non-small cell lung cancer. Journal of the National Comprehensive Cancer Network: JNCCN. 2010;8(7):740–801. Epub 2010/08/04. . - PubMed
    1. Yang P, Allen MS, Aubry MC, Wampfler JA, Marks RS, Edell ES, et al. Clinical features of 5,628 primary lung cancer patients: experience at Mayo Clinic from 1997 to 2003. Chest. 2005;128(1):452–62. Epub 2005/07/09. 10.1378/chest.128.1.452 . - DOI - PubMed
    1. Moons KG, Royston P, Vergouwe Y, Grobbee DE, Altman DG. Prognosis and prognostic research: what, why, and how? BMJ (Clinical research ed). 2009;338:b375 Epub 2009/02/25. 10.1136/bmj.b375 . - DOI - PubMed

Publication types

Grant support

This study was supported by the Taiwan Ministry of Science and Technology (Grant No: MOST 105-2410-H-002-215 to M-CY). However, the funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
Feedback