Multivariable model for predicting 5-year survival in patients with EGFR-mutated non-small cell lung cancer treated with EGFR tyrosine kinase inhibitors: a retrospective study

被引:0
作者
Wang, Qi-An [1 ]
Tsai, I-Lin [2 ]
Lin, Chien-Yu [2 ]
Su, Po-Lan [2 ]
Lin, Chien-Chung [2 ,3 ,4 ]
Chang, John Wen-Cheng [5 ]
Huang, Chen-Yang [5 ]
Fang, Yueh-Fu [6 ]
Chang, Ching-Fu [5 ]
Kuo, Chih-Hsi Scott [6 ]
Hsu, Ping-Chih [6 ]
Yang, Cheng-Ta [6 ]
Wu, Chiao-En
机构
[1] Chang Gung Univ, Coll Med, Sch Tradit Chinese Med, Taoyuan, Taiwan
[2] Natl Cheng Kung Univ, Natl Cheng Kung Univ Hosp, Coll Med, Dept Internal Med, Tainan, Taiwan
[3] Natl Cheng Kung Univ, Natl Cheng Kung Univ Hosp, Inst Clin Med, Coll Med, Tainan, Taiwan
[4] Natl Cheng Kung Univ, Coll Med, Dept Biochem & Mol Biol, Tainan, Taiwan
[5] Chang Gung Univ, Chang Gung Mem Hosp Linkou, Coll Med, Div Hematol Oncol,Dept Internal Med, Taoyuan, Taiwan
[6] Chang Gung Univ, Chang Gung Mem Hosp Linkou, Coll Med,Div Thorac Oncol, Div Thorac Surg, Taoyuan, Taiwan
关键词
5-year survival; EGFR mutation; EGFR tyrosine kinase inhibitors; non-small-cell lung cancer; 1ST-LINE TREATMENT; PHASE-III; PROGNOSTIC-FACTORS; ASIAN PATIENTS; OPEN-LABEL; GEFITINIB; ADENOCARCINOMA; CHEMOTHERAPY; MUTATIONS; AFATINIB;
D O I
10.1177/17588359251321901
中图分类号
R73 [肿瘤学];
学科分类号
100214 ;
摘要
Background: Non-small-cell lung cancer (NSCLC) is the leading cause of cancer-related mortality worldwide. In Asian populations, epidermal growth factor receptor (EGFR) mutations are particularly prevalent, leading to the development of EGFR tyrosine kinase inhibitors (TKIs) to improve patient outcomes. While extensive research has been conducted on the prognosis of patients receiving EGFR-TKIs, the estimation of 5-year survival in this population remains an underexplored area. Objectives: This study aimed to provide real-world evidence and conduct a comprehensive analysis of the determinants influencing the 5-year survival rate in patients with EGFR-mutated NSCLC. Considering the factors identified in this study, a scoring system was developed to predict the likelihood of patients achieving this goal. Design: A retrospective cohort study utilizing a training cohort of 1,873 patients and a validation cohort of 484 patients. Methods: A logistic regression model was constructed to evaluate the weighting of factors and develop a scoring system. The Kaplan-Meier model estimated the overall survival probability, and patients were categorized into four risk groups based on their likelihood of five-year survival. The prediction performance of both the training and validation cohorts was evaluated using the area under the curve (AUC), accuracy, precision, sensitivity, specificity, and F1-score. Results: Results indicated that age > 65 years; performance score of 2-4; metastasis to the liver, brain, bone, or pleura; and poor disease control were associated with a decreased likelihood of 5-year survival. The estimated 5-year survival rate was 23.4% (odds ratio [OR]: 20.56; 95% confidence interval [CI]: 9.06-46.64; p < 0.0001), 16.1% (OR: 12.88; 95% CI: 5.82-28.49; p < 0.0001), 7.2% (OR: 5.23; 95% CI: 2.36-11.60; p < 0.0001), and 1.5% (OR: reference) for the low-risk, intermediate-risk, high-risk, and very-high-risk groups, respectively. The validation cohort further confirmed these findings, showing survival probabilities of 52.6% (OR: 96.67; 95% CI: 11.07-844.23; p < 0.0001), 21.3% (OR: 23.49; 95% CI: 3.13-176.46; p = 0.002), 14.9% (OR: 15.21; 95% CI: 2.03-114.25; p = 0.008), and 1.1% (OR: reference) for the low-risk, intermediate-risk, high-risk, and very-high-risk groups, respectively. The training cohort demonstrated an AUC of 0.79 (95% CI: 0.75-0.82) and a model quality score of 0.75, indicating good predictive performance. Calibration plots demonstrated a good fit for the scoring system. For the external validation cohort, the AUC, precision, sensitivity, and specificity were 0.71, 0.74, 0.35, 0.33, respectively. The model achieved an F1-score of 0.47, reflecting adequate performance in predicting 5-year survival probabilities. Conclusion: This study identified critical prognostic factors and developed a validated scoring system for estimating 5-year survival in patients with EGFR-mutated NSCLC receiving EGFR-TKIs. While the model demonstrated robust predictive performance within the study cohort, broader applicability beyond Taiwan may require further refinements and alternative study designs.
引用
收藏
页数:16
相关论文
共 50 条
[31]   Emerging drugs for EGFR-mutated non-small cell lung cancer [J].
Sukrithan, Vineeth ;
Deng, Lei ;
Barbar, Alexander ;
Cheng, Haiying .
EXPERT OPINION ON EMERGING DRUGS, 2019, 24 (01) :5-16
[32]   Subacute Cutaneous Lupus Erythematosus-Like Eruption Induced by EGFR -Tyrosine Kinase Inhibitor in EGFR-Mutated Non-small Cell Lung Cancer: A Case Report [J].
Ferro, Alessandra ;
Filoni, Angela ;
Pavan, Alberto ;
Pasello, Giulia ;
Guarneri, Valentina ;
Conte, PierFranco ;
Alaibac, Mauro ;
Bonanno, Laura .
FRONTIERS IN MEDICINE, 2021, 8
[33]   Efficacy of EGFR Tyrosine Kinase Inhibitors in Patients With EGFR-Mutated Non-Small-Cell Lung Cancer: A Meta-Analysis of 13 Randomized Trials [J].
Petrelli, Fausto ;
Borgonovo, Karen ;
Cabiddu, Mary ;
Barni, Sandro .
CLINICAL LUNG CANCER, 2012, 13 (02) :107-114
[34]   Downregulation of EGFR in a metastatic brain lesion of EGFR-mutated non-small cell lung cancer using a tyrosine kinase inhibitor: A case report [J].
Takagaki, Masatoshi ;
Kinoshita, Manabu ;
Nishino, Kazumi ;
Nakano, Masakazu ;
Adachi, Hiroko ;
Ueno, Morio ;
Kitamura, Masanori ;
Fujimoto, Yasunori ;
Tashiro, Kei ;
Tomita, Yasuhiko ;
Imamura, Fumio ;
Yoshimine, Toshiki .
ONCOLOGY LETTERS, 2017, 13 (04) :2085-2088
[35]   Capmatinib plus nazartinib in patients with EGFR-mutated non-small cell lung cancer [J].
Felip, Enriqueta ;
Metro, Giulio ;
Soo, Ross A. ;
Wolf, Juergen ;
Solomon, Benjamin J. ;
Tan, Daniel S. W. ;
Ardizzoni, Andrea ;
Lee, Dae Ho ;
Sequist, Lecia V. ;
Barlesi, Fabrice ;
Ponce-Aix, Santiago ;
Abreu, Delvys Rodriguez ;
Campelo, Maria Rosario Garcia ;
Sprauten, Mette ;
Djentuh, Leslie O'Sullivan ;
Smith, Nathalie ;
Jary, Aline ;
Belli, Riccardo ;
Glaser, Sabine ;
Zou, Mike ;
Cui, Xiaoming ;
Giovannini, Monica ;
Yang, James Chih-Hsin .
EUROPEAN JOURNAL OF CANCER, 2024, 208
[36]   Features of patients with advanced EGFR-mutated non-small cell lung cancer benefiting from immune checkpoint inhibitors [J].
Chen, Qian ;
Shang, Xiaoling ;
Liu, Ni ;
Ma, Xinchun ;
Han, Wenfei ;
Wang, Xiuwen ;
Liu, Yanguo .
FRONTIERS IN IMMUNOLOGY, 2022, 13
[37]   Effectiveness of EGFR tyrosine kinase inhibitors in advanced non-small cell lung cancer patients with uncommon EGFR mutations: A multicenter observational study [J].
Kanazu, Masaki ;
Mori, Masahide ;
Kimura, Madoka ;
Nishino, Kazumi ;
Shiroyama, Takayuki ;
Nagatomo, Izumi ;
Ihara, Shoichi ;
Komuta, Kiyoshi ;
Suzuki, Hidekazu ;
Hirashima, Tomonori ;
Kumagai, Toru ;
Imamura, Fumio .
THORACIC CANCER, 2021, 12 (01) :90-96
[38]   A Bayesian network meta-analysis of EGFR-tyrosine kinase inhibitor treatments in patients with EGFR mutation-positive non-small cell lung cancer [J].
Yin, Jianqiong ;
Huang, Jing ;
Ren, Min ;
Tang, Rui ;
Xie, Linshen ;
Xue, Jianxin .
CANCER PATHOGENESIS AND THERAPY, 2025, 3 (02) :135-146
[39]   Comparation of EGFR-TKI (EGFR tyrosine kinase inhibitors) combination therapy and osimertinib for untreated EGFR-mutated advanced non-small cell lung cancers: A systematic review and network meta-analysis [J].
Lei, Yang ;
Duan, Jia ;
Zhang, Qiong ;
Li, Qing .
MEDICINE, 2023, 102 (30) :E34483
[40]   Molecular characteristics and responses to EGFR tyrosine kinase inhibitors in non-small cell lung cancer patients with EGFR exon 19 insertions [J].
Li, Yang ;
Ni, Yunfeng ;
Lv, Feng ;
Shi, Yan ;
Chen, Yedan ;
Wu, Xiaoying ;
Pang, Jiaohui ;
Huang, Long ;
Shao, Yang ;
Wang, Tao ;
Min, Jie ;
Song, Yang .
BMC MEDICINE, 2025, 23 (01)