Modeling exposure-driven adverse events of EGFR TKIs in the treatment of patients with non-small cell lung cancer

Siegel RL, Miller KD, Wagle NS, Jemal A. Cancer statistics, 2023. CA Cancer J Clin. 2023;73:17–48.

Article  PubMed  Google Scholar 

Reck M, Rabe KF. Precision diagnosis and treatment for advanced non-small-cell lung cancer. N Engl J Med. 2017;377:849–61.

Article  CAS  PubMed  Google Scholar 

Midha A, Dearden S, McCormack R. EGFR mutation incidence in non-small-cell lung cancer of adenocarcinoma histology: a systematic review and global map by ethnicity (mutMapII). Am J Cancer Res. 2015;5:2892–911.

PubMed  PubMed Central  Google Scholar 

Sequist LV, Yang JC, Yamamoto N, O’Byrne K, Hirsh V, Mok T, et al. Phase III study of afatinib or cisplatin plus pemetrexed in patients with metastatic lung adenocarcinoma with EGFR mutations. J Clin Oncol. 2013;31:3327–34.

Article  CAS  PubMed  Google Scholar 

Jänne PA, Ou SI, Kim DW, Oxnard GR, Martins R, Kris MG, et al. Dacomitinib as first-line treatment in patients with clinically or molecularly selected advanced non-small-cell lung cancer: a multicentre, open-label, phase 2 trial. Lancet Oncol. 2014;15:1433–41.

Article  PubMed  Google Scholar 

Jänne PA, Yang JC, Kim DW, Planchard D, Ohe Y, Ramalingam SS, et al. AZD9291 in EGFR inhibitor-resistant non-small-cell lung cancer. N Engl J Med. 2015;372:1689–99.

Article  PubMed  Google Scholar 

Zhao YY, Li S, Zhang Y, Zhao HY, Liao H, Guo Y, et al. The relationship between drug exposure and clinical outcomes of non-small cell lung cancer patients treated with gefitinib. Med Oncol. 2011;28:697–702.

Article  CAS  PubMed  Google Scholar 

Tiseo M, Andreoli R, Gelsomino F, Mozzoni P, Azzoni C, Bartolotti M, et al. Correlation between erlotinib pharmacokinetics, cutaneous toxicity and clinical outcomes in patients with advanced non-small cell lung cancer (NSCLC). Lung Cancer. 2014;83:265–71.

Article  PubMed  Google Scholar 

Rodier T, Puszkiel A, Cardoso E, Balakirouchenane D, Narjoz C, Arrondeau J, et al. Exposure-response analysis of osimertinib in patients with advanced non-small-cell lung cancer. Pharmaceutics. 2022;14.

Swaisland HC, Smith RP, Laight A, Kerr DJ, Ranson M, Wilder-Smith CH, et al. Single-dose clinical pharmacokinetic studies of gefitinib. Clin Pharmacokinet. 2005;44:1165–77.

Article  CAS  PubMed  Google Scholar 

Hu P, Chen J, Liu D, Zheng X, Zhao Q, Jiang J. Development of population pharmacokinetics model of icotinib with non-linear absorption characters in healthy Chinese volunteers to assess the CYP2C19 polymorphism and food-intake effect. Eur J Clin Pharmacol. 2015;71:843–50.

Article  CAS  PubMed  Google Scholar 

Brown K, Comisar C, Witjes H, Maringwa J, de Greef R, Vishwanathan K, et al. Population pharmacokinetics and exposure-response of osimertinib in patients with non-small cell lung cancer. Br J Clin Pharmacol. 2017;83:1216–26.

Article  CAS  PubMed  PubMed Central  Google Scholar 

Kiang TK, Sherwin CM, Spigarelli MG, Ensom MH. Fundamentals of population pharmacokinetic modelling: modelling and software. Clin Pharmacokinet. 2012;51:515–25.

Article  CAS  PubMed  Google Scholar 

Kawata T, Higashimori M, Itoh Y, Tomkinson H, Johnson MG, Tang W, et al. Gefitinib exposure and occurrence of interstitial lung disease in Japanese patients with non-small-cell lung cancer. Cancer Chemother Pharm. 2019;83:849–58.

Article  CAS  Google Scholar 

Nakao K, Kobuchi S, Marutani S, Iwazaki A, Tamiya A, Isa S, et al. Population pharmacokinetics of afatinib and exposure-safety relationships in Japanese patients with EGFR mutation-positive non-small cell lung cancer. Sci Rep. 2019;9. 18202.

Article  CAS  PubMed  PubMed Central  Google Scholar 

Wang QQ, Yu SC, Qi X, Hu YH, Zheng WJ, Shi JX, et al. Overview of logistic regression model analysis and application. Zhonghua Yu Fang Yi Xue Za Zhi. 2019;53:955–60.

CAS  PubMed  Google Scholar 

Xiong X, Zhang Y, Wang Z, Zhou C, Yang P, Du X, et al. Simultaneous quantitative detection of afatinib, erlotinib, gefitinib, icotinib, osimertinib and their metabolites in plasma samples of patients with non-small cell lung cancer using liquid chromatography-tandem mass spectrometry. Clin Chim Acta. 2022;527:1–10.

Article  CAS  PubMed  Google Scholar 

Freiwald M, Schmid U, Fleury A, Wind S, Stopfer P, Staab A. Population pharmacokinetics of afatinib, an irreversible ErbB family blocker, in patients with various solid tumors. Cancer Chemother Pharmacol. 2014;73:759–70.

Article  CAS  PubMed  Google Scholar 

Chan Kwong AHP, Calvier EAM, Fabre D, Gattacceca F, Khier S. Prior information for population pharmacokinetic and pharmacokinetic/pharmacodynamic analysis: overview and guidance with a focus on the NONMEM PRIOR subroutine. J Pharmacokinet Pharmacodyn. 2020;47:431–46.

Article  PubMed  PubMed Central  Google Scholar 

Al-Huniti N, Feng Y, Yu JJ, Lu Z, Nagase M, Zhou D, et al. Tumor growth dynamic modeling in oncology drug development and regulatory approval: past, present, and future opportunities. CPT Pharmacomet Syst Pharmacol. 2020;9:419–27.

Article  CAS  Google Scholar 

Shah RR, Shah DR. Safety and tolerability of Epidermal Growth Factor Receptor (EGFR) tyrosine kinase inhibitors in oncology. Drug Saf. 2019;42:181–98.

Article  CAS  PubMed  Google Scholar 

Gadkar K, Friedrich C, Hurez V, Ruiz ML, Dickmann L, Kumar Jolly M, et al. Quantitative systems pharmacology model-based investigation of adverse gastrointestinal events associated with prolonged treatment with PI3-kinase inhibitors. CPT Pharmacomet Syst Pharmacol. 2022;11:616–27.

Article  CAS  Google Scholar 

Shulgin B, Kosinsky Y, Omelchenko A, Chu L, Mugundu G, Aksenov S, et al. Dose dependence of treatment-related adverse events for immune checkpoint inhibitor therapies: a model-based meta-analysis. Oncoimmunology. 2020;9:1748982.

Article  PubMed  PubMed Central  Google Scholar 

Zhang Z. Missing data imputation: focusing on single imputation. Ann Transl Med. 2016;4:9.

PubMed  PubMed Central  Google Scholar 

Kwak SK, Kim JH. Statistical data preparation: management of missing values and outliers. Korean J Anesthesiol. 2017;70:407–11.

Article  PubMed  PubMed Central  Google Scholar 

Aggarwal CC. An introduction to outlier analysis. In: Aggarwal CC, editor. Outlier analysis. Cham: Springer International Publishing; 2017, p. 1–34.

Singh V, Dwivedi SN, Deo SVS. Ordinal logistic regression model describing factors associated with extent of nodal involvement in oral cancer patients and its prospective validation. BMC Med Res Methodol. 2020;20:95.

Article  PubMed  PubMed Central  Google Scholar 

Nakamura T, Obata JE, Hirano M, Kitta Y, Fujioka D, Saito Y, et al. Predictive value of remnant lipoprotein for cardiovascular events in patients with coronary artery disease after achievement of LDL-cholesterol goals. Atherosclerosis. 2011;218:163–7.

Article  CAS  PubMed  Google Scholar 

Kim JH. Multicollinearity and misleading statistical results. Korean J Anesthesiol. 2019;72:558–69.

Article  PubMed  PubMed Central  Google Scholar 

Brant R. Assessing proportionality in the proportional odds model for ordinal logistic regression. Biometrics. 1990;46:1171–8.

Article  CAS  PubMed  Google Scholar 

David W, Hosmer SL. Assessing the fit of the model. In: Walter A. Shewhart SSW, editors. Applied logistic regression. John Wiley & Sons, Inc.; 2000. p 143–202.

Mandrekar JN. Receiver operating characteristic curve in diagnostic test assessment. J Thorac Oncol. 2010;5:1315–6.

Article  PubMed  Google Scholar 

Overgaard RV, Ingwersen SH, Tornøe CW. Establishing good practices for exposure-response analysis of clinical endpoints in drug development. CPT Pharmacomet Syst Pharmacol. 2015;4:565–75.

Article  CAS  Google Scholar 

Joel S, Owen JF-K. Simulation basics. In: Introduction to population pharmacokinetic/pharmacodynamic analysis with nonlinear mixed effects models. John Wiley & Sons, Inc.; 2014. p. 265–84.

Demirel OF, Willemain TR. Generation of simulation input scenarios using bootstrap methods. Journal Oper Res Soc. 2002;53:69–78.

Article  Google Scholar 

Shah DR, Shah RR, Morganroth J. Tyrosine kinase inhibitors: their on-target toxicities as potential indicators of efficacy. Drug Saf. 2013;36:413–26.

Article 

Comments (0)

No login
gif