Skip to main content
NCBI home page
Translational Oncology logoLink to Translational Oncology
. 2019 Apr 25;12(6):852–858. doi: 10.1016/j.tranon.2019.04.004

Comparison of T790M Acquisition Between Patients Treated with Afatinib and Gefitinib as First-Line Therapy: Retrospective Propensity Score Matching Analysis

Byung Woo Yoon *, Jae Hoon Kim †, Seung Hyeon Lee ‡, Chang-Min Choi *, Jin Kyung Rho §, Shinkyo Yoon *, Dae Ho Lee *, Sang-We Kim *, Tae-Won Jang †,⁎, Jae Cheol Lee *,⁎
PMCID: PMC6484288  PMID: 31030101

Abstract

Afatinib, a second-generation, irreversible pan-HER inhibitor, shows better suppression of T790M-positive lung cancer cells than gefitinib in preclinical studies. However, whether the effect of afatinib on T790M acquisition differs from that of gefitinib when used clinically as first-line therapy remains unclear. To reaffirm the preclinical efficacy of afatinib on T790M-positive lung cancer cells, H1975 cells and established PC-9 cells resistant to gefitinib and erlotinib by T790M were used. In total, 398 patients with second biopsy at progression with stage IIIB/IV non–small cell lung cancer with EGFR mutation, treated with afatinib or gefitinib as first-line therapy, were retrospectively reviewed. Propensity score matching was used to balance covariates. Afatinib inhibited the growth of lung cancer cells with low T790M allele frequencies, which are resistant to gefitinib, but not those with high T790M allele frequencies. Afatinib and gefitinib showed similar efficacy in terms of progression-free survival (PFS) (11.5 vs 13.4 months, P = .08) and overall survival (OS) (29.3 vs 28.5 months, P = .76). T790M patients had better PFS and OS than those without T790M. There was no significant difference in the cumulative T790M acquisition ratio over time between afatinib and gefitinib (48.8% vs 59.3%, P = .317). The median time to acquire T790M was 12.9 months for afatinib and 15.7 months for gefitinib (P = .342). Although afatinib inhibited the growth of lung cancer cells with low T790M allele frequencies in preclinical studies, this could not be translated into clinical efficacy in terms of lowering the rate or delaying the time of T790M acquisition.

Introduction

Afatinib is a second-generation potent EGFR-TKI that covalently binds to all homo- and heterodimers formed by the members of the HER family, such as EGFR, HER2, ErbB3, and ErbB4 [1]. In both cell-free kinase and cell proliferation assays, afatinib shows much better inhibitory activity on EGFR harboring L858R/T790M mutations compared to first-generation EGFR-TKIs [1], [2], [3], [4]. Research shows that the activity of afatinib on the T790M mutation was lower than that on single sensitizing mutations such as L858R or E19del, but it remained within a range that indicated similar effectiveness [5]. In addition, afatinib reduced tumor volume by approximately half in transgenic mice with L858R/T790M mutation-driven cancer [2].

Although afatinib was expected to overcome acquired resistance to first-generation EGFR-TKI, it failed to show an overall survival (OS) benefit over placebo in patients with advanced EGFR-mutant lung cancer following previous EGFR-TKI therapy [6]. This discordance with preclinical data might be explained by amplification of T790M. The irreversible EGFR-TKIs were initially effective in vitro and in vivo against EGFR mutant tumors containing T790M, while resistance arose when T790M was amplified over time [7]. The efficacy of afatinib on T790M seems to be dependent on the T790M allele frequency, not just positivity of T790M. This implies that the clinical activity of afatinib could also vary according to the T790M allele frequency. The improvement of progression-free survival (PFS), tumor response rate, and disease-related symptoms in the LUX-Lung 1 clinical trial [6] despite no OS benefit could be understood in a similar context.

Therefore, we assumed that afatinib may reduce the rate or delay the time of T790M acquisition during first-line EGFR-TKI therapy because the T790M amplification that decreases afatinib efficacy probably occurs in the later phase. Accordingly, retrospective studies revealed that the T790M acquisition by afatinib (20.0%) was lower than that by gefitinib (52.8%) or erlotinib (44.6%) [8]. However, this is controversial due to contradictory reports showing that the frequency of T790M at the time of progression was not different according to the type of EGFR-TKIs [9], [10].

In this study, we reaffirmed the preclinical activity of afatinib using EGFR-mutant lung cancer cells with different T790M allele frequencies and examined whether the cumulative ratio of T790M over time or the median time to acquire T790M differed between patients treated with afatinib and gefitinib as first-line therapy.

Material and Methods

Cell Culture and Reagents

The H1975 cell line was obtained from the American Type Culture Collection (Rockville, MD). The PC-9 cells were kindly provided by Dr. Kazuto Nishio (National Cancer Center Hospital, Tokyo, Japan). PC-9/GR (gefitinib-resistant cell line) and PC/ER (erlotinib-resistant cell line) have been established in previous studies [11], [12]. Cells were cultured in RPMI1640 medium containing 10% FBS, 100 U/ml penicillin, and 100 mg/ml streptomycin (Invitrogen, Carlsbad, CA) at 37°C in an atmosphere of 5% CO2. Tests for mycoplasma contamination were negative. Afatinib was purchased from Selleck Chemicals (Houston, TX).

Cell Viability Assay

Cells (5 × 103) were seeded in 96-well sterile plastic plates, incubated overnight, and then treated with the drugs. After 72 hours, 15 μl 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide (MTT) solution (5 mg/ml) was added to each well, and the plates were incubated for 4 hours. Crystalline formazan was solubilized by adding 100 μl of 10% (w/v) sodium dodecyl sulfate and incubating for 24 hours, after which absorbance at 595 nm was spectrophotometrically recorded using a microplate reader. The results were representative of at least three independent experiments, with the error bars signifying standard deviation (SD). The IC50 values were calculated using the GraphPad Prism software (La Jolla, CA). To validate the long-term effects of afatinib, cells were treated with afatinib for 72 hours, and the medium was replaced with drug-free medium. After incubation for 5 days, attached cells were stained with a 0.2% trypan blue solution containing 50% methanol.

T790M Mutation Analysis

Peptide nucleic acid (PNA)–mediated PCR clamping assay (PNACLamp EGFR Mutation Detection kit, PANAGENE Inc., Dadjeon, Korea) was used to detect T790M mutation. The detection of T790M mutation was performed as previously described [11].

Study Population

This retrospective study was approved by the Institutional Review Board at the University of Ulsan, Asan Medical Center (2018-0541). The flow diagram of patient enrollment is illustrated in Figure 1A. From January 2008 to December 2017, 418 patients with locally advanced or metastatic adenocarcinomas of the lung underwent second biopsy after progression during first-line therapy with either gefitinib or afatinib at Asan Medical Center, Seoul, Korea, and Koshin University, Busan, Korea. A total of 398 patients whose second biopsy results were available were included in this study. Clinical information, such as age, gender, lung cancer staging according to AJCC 7th edition, first biopsy EGFR mutation type and second biopsy T790M status, OS, and PFS during TKI therapy, was retrospectively reviewed using electronic medical records.

Figure 1.

Figure 1

Open in a new tab

The process of patient enrollment in the study. (a) A total of 418 patients with second biopsies were identified, and 20 were transferred to another hospital. There were 398 eligible patients, where 41 were treated with afatinib and 357 received gefitinib. Propensity score matching resulted in 164 patients. (b) The propensity score before matching has an uneven distribution between afatinib and gefitinib; however, after matching, the distribution ratio between each score value becomes 1:3 between afatinib and gefitinib.

Propensity Score Matching

Of the 398 patients, 41 were on afatinib and 357 on gefitinib. Due to the discrepancy in patient baseline characteristics (Table 1), we used propensity score (PS) matching to identify similar baseline characteristics treated with afatinib or gefitinib. The matching was based on age, gender, AJCC 7th edition stage for lung cancer, and EGFR mutation type, with a ratio of 1:3 for afatinib versus gefitinib. The PS matching yielded 164 patients with no statistical difference in age, gender, stage, and first biopsy EGFR status.

Table 1.

Clinical Characteristics of 398 Patients with Adenocarcinoma of the Lung, with Second Biopsies After TKI Medication in the Presence of EGFR Mutation and Its Propensity Score–Matched Results

Before Propensity Score Matching (n = 418)
 After Propensity Score Matching (n = 164)
Characteristics Afatinib Gefitinib P Value Afatinib Gefitinib P Value
N 41 357 41 123
Age mean ± SD 59.2 ± 12.3 59.8 ± 10.8 .737 59.2 ± 12.3 60.9 ± 11.5 .417
Gender .047 .928
 Male 21 (51.2%) 122 (34.2%) 21 (51.2%) 66 (53.7%)
 Female 20 (48.8%) 235 (65.8%) 20 (48.8%) 58 (46.3%)
Stage .080 .992
 IIIB 7 (17.1%) 93 (25.1%) 7 (17.1%) 21 (17.1%)
 IVA 7 (17.1%) 95 (26.6%) 7 (17.1%) 20 (16.3%)
 IVB 27 (65.9%) 169 (47.3%) 27 (65.9%) 82 (66.7%)
1st biopsy
EGFR mutations		 .324 .506
 E19del 27 (65.9%) 212 (59.4%) 27 (65.9%) 88 (71.5%)
 L858R 11 (26.8%) 131 (36.7%) 11 (26.8%) 31 (25.2%)
 Others 3 (7.3%) 14 (3.9%) 3 (7.3%) 4 (3.3%)
T790M (+) 20 (48.8%) 146 (40.9%) .422 20 (48.8%) 73 (59.3%) .317
Open in a new tab

Statistical Analysis

Statistical analysis was performed using R 3.5.1. To minimize the differences of baseline characteristics, PS matching was applied with optimal matching, implemented with the MatchIt [13] and optmatch [14] packages in R. Comparisons between two groups were performed using the t test for continuous data, and Pearson's chi-square test for categorical data. Cumulative distribution of T790M mutation over time was presented, and the P value was calculated using Pearson's chi-square test for the ratio, while the time to onset was calculated using Mann-Whitney-Wilcoxon test. The Kaplan-Meier method was used to plot OS and PFS according to the medication and the T790M status. The log-rank test was used to compare survival curves to calculate the P value. Subgroup analysis of OS and PFS and T790M status was performed using a univariate Cox proportional-hazard model. Univariate Cox analysis was performed to calculate hazard ratios (HRs) and 95% confidence interval (CI) along P values, where a two-tailed P value of <.05 was set as statistically significant. P values lower than .2 in univariate Cox analysis were included in the multivariate Cox analysis, where P values of <.05 were set as significant. The above was implemented with the survival [15] package in R.

Results

The Effect of Afatinib on the Growth of EGFR-Mutant Lung Cancer Cells with Different T790M Allele Frequencies

Gefitinib- and erlotinib-resistant cells were established as in previous studies [16], [17]. In a similar study [17], PC-9/GR (H) and PC-9/ER (H) cells showed increased T790M allele frequencies, and they also were more resistant to afatinib compared to PC-9/GR (L) and PC-9/ER (L) (Figure 2, A-C). These results suggest that the activity of afatinib on T790M-containing cells differs according to T790M allele frequency.

Figure 2.

Figure 2

Open in a new tab

The efficacy of afatinib according to T790M mutation allele frequencies. (a) Cells were treated with afatinib, and sensitivity to afatinib was determined by MTT assay. (b) Cells were treated with 0.1 μM afatinib for 72 hours, and the medium was replaced with drug-free medium. After incubation for 5 days, attached cells were stained with trypan blue solution. (c) T790M mutation from each cell was detected by using PNACLamp EGFR Mutation Detection kit. The rate of T790M mutation was displayed as copies/reaction.

Elapsed Time Effect of Pharmacological Pressure on the Positivity of T790M

A male patient receiving gefitinib for 2 years developed resistance, and the first rebiopsy with PNA clamping assay showed T790M-negative results, although enough tumor cells were retrieved for analysis (Figure 3). His symptoms were very mild because only primary lung mass grew without any new lesions. Hence, we continued the administration of gefitinib for another 1 year and took the second rebiopsy when his respiratory symptoms, such as cough and dyspnea, were aggravated with further growth of lung mass. Interestingly, T790M turned out to be positive on the same test, and his disease responded well to subsequent osimertinib. Increased T790M allele frequency over time might affect the test result in this case.

Figure 3.

Figure 3

Open in a new tab

A case showing the different results of T790M by the same test over time with continued EGFR-TKI beyond progression. Increased T790M allele frequency would result in the positivity of T790M on second rebiopsy.

Baseline Characteristics of Patients After Propensity Matching

We retrospectively reviewed the medical records of 398 patients: those who had at least more than two biopsies, the second biopsy performed after progression of the disease, while on TKI treatment with an initial EGFR mutation. The baseline characteristics in the prematched and pos-matched cohorts are presented in Table 1. Before PS matching, female/male ratio, disease stage, and type of EGFR mutation were not equal between afatinib and gefitinib groups. After PS matching, the female proportion in the gefitinib group changed from 65.8% to 46.3% (P = .928). The stages of that group were also adjusted (stage IIIB from 25.7% to 17.1%, stage IVA from 26.3% to 16.3%, and stage IVB from 47.3% to 66.7%). The types of EGFR mutation in the gefitinib group were also matched (P = .506) with E19del from 59.4% to 71.5%, and L858R from 37.7% to 25.2%. Distribution of patient characteristics before and after PS matching is illustrated in Figure 1B and Supplemental Figure 1, where Raw Treated (afatinib) and Raw Control (gefitinib) have different density distribution histograms, while Matched Treated (afatinib) and Matched Control (gefitinib) have similar density distribution histograms.

The Comparison of T790M Acquisition in Afatinib and Gefitinib Groups

The cumulative T790M acquisition ratios for afatinib and gefitinib were 48.8% and 59.3%, respectively (P = .317). The median time to acquire T790M was 12.9 months for afatinib, while it was 15.7 months for gefitinib (P = .342) (Figure 4A). The forest plot using subgroup analysis shows there was no statistically significant factor involved in determining T790M mutation on either medication. However, there was a slight trend of lower rates of T790M mutation in afatinib, with an HR of 4.77 [95% CI 0.63-36.31, P = .13] in the L858R mutation group for gefitinib (Figure 4B).

Figure 4.

Figure 4

Open in a new tab

T790M mutation results by afatinib and gefitinib. (a) Cumulative ratio of T790M mutation over time for afatinib and gefitinib is plotted, where each ratio plateaus at 48.8% and 59.3% for afatinib and gefitinib, respectively. (b) The forest plot for T790M mutation subgroup analysis using univariate Cox analysis. There is no statistically significant factor causing increased rate or delayed time of T790M mutation.

Survival According to Drugs and the Status of T790M

The median OS was 29.3 months in the afatinib group and 28.5 months in the gefitinib group, respectively, with an HR of 0.77 [95% CI 0.55-1.55, P = .76] (Figure 5A). The median PFS was 11.5 months for the afatinib group and 13.4 months for the gefitinib group, respectively, with an HR of 0.73 [95% CI 0.51-1.04, P = .08] (Figure 5B). Regardless of used drugs, the median OS and PFS were better in T790M-positive patients: OS—21.2 months [95% CI 15.9-29.3 months] versus 36.1 months [95% CI 29.7-60.8 months], HR of 0.48 [95% CI 0.32-0.71, P = .002] (Figure 5C); PFS—8.1 months [95% CI 6.6-13.0 months] versus 13.7 months [95% CI 12.6-15.7 months], HR of 0.68 [95% CI 0.50-0.93, P = .015] (Figure 5D).

Figure 5.

Figure 5

Open in a new tab

Kaplan-Meier survival plots for OS and PFS. (a) OS is compared between afatinib and gefitinib treatment. (b) PFS is compared between afatinib and gefitinib treatment. (c) OS is compared between those with or without T790M mutation. (d) PFS is compared between those with or without T790M mutation.

Discussions

Our case demonstrates that pharmacological pressure for selection and amplification over time might raise the initial test-negative level of T790M to the level detectable by the same test. The positive response to osimertinib verified the authenticity of T790M-mediated resistance in this patient. We can clearly see this phenomenon in cell line studies (Figure 2). Engelman et al. established gefitinib-resistant cells (H3255/GR) by prolonged exposure to gefitinib in gefitinib-sensitive mother cells (H3255) [18]. Initial direct sequencing of H3255/GR could not detect T790M, while a highly sensitive HPLC-based technique confirmed the presence of T790M. In our cell line models, we did not detect T790M in PC-9/GR or ER (L) by direct sequencing, which has low sensitivity (Figure 2C). However, T790M was detected using the more sensitive pyrosequencing method or by direct sequencing of PC-9/GR or ER (H), which provides greater T790M amplification. Semiquantitative pyrosequencing revealed that PC-9/GR and ER (L) had around 14% T790M, while more than 50% T790M was found in PC-9/GR or ER (H) [17]. Hence, we concluded that the positivity of T790M is decided by both the test sensitivity and T790M allele frequency. Taken together, these findings raise the clinically difficult question of whether later retesting is required for initial T790M test-negative patients while keeping EGFR-TKI, despite disease progression, like in our case. This question is currently difficult to answer, but it seems worth trying, at least in asymptomatic or mildly symptomatic patients presenting slow disease progression because changing to cytotoxic chemotherapy is the only option in these patients and second-line chemotherapy is usually not so effective. In addition, the slowly growing tumor is more likely to harbor T790M.

Some preclinical experiments [1], [2], [3], [4], including ours, indicated that afatinib could be more effective than gefitinib in the clinical setting. However, there were no significant differences between afatinib and gefitinib in terms of PFS and OS in our study. PFS of around 11.5 months and OS of around 29 months by EGFR-TKI in our study were similar to those reported in other studies [19], [20], [21], [22], [23], [24]. As expected, both survival indices were better for patients with T790M-mediated resistance, reflecting the slow-growing nature of T790M-positive lung cancer (Figure 5, C and D). In multivariate Cox analysis (Supplemental Figures 2 and 3), the poor prognostic factors, which had statistically significant effects on OS, were male sex [HR = 1.65, 95% CI 1.07-2.56, P = .03] and stage IVb [HR = 3.02, 95% CI 1.47-6.24, P < .01], whereas the types of EGFR mutation did not affect survival (Figure 5 and Supplemental Figure 3), which was also observed in another recent study using propensity score matching [25].

The results are important in a therapeutic setting because there is a possibility that afatinib is effective in T790M-positive lung cancer detected by sensitive techniques, mostly used at present if amplification is not accompanied. Ercan et al. depicted this situation in their study [7]. Actually, our study was initiated by the question of whether it can be translated into clinics. Disappointingly, afatinib did not show any statistically significant difference compared to gefitinib in terms of cumulative ratio of T790M and median time to T790M acquisition, although the afatinib group did present a slightly longer time and slightly higher rate for T790M acquisition (Figure 5B), with an HR of 4.77 [95% CI 0.63-36.31, P = .13]. Further, we could not find any significant factors determining T790M acquisition while on afatinib or gefitinib.

One limitation of our study is the small number of patients in the afatinib group. Afatinib has more side effects than gefitinib [23], [26], [27], [28], [29], which affect the clinician's choice of EGFR-TKIs. There is a tendency to favor gefitinib in female patients who are more concerned about skin problems [29] and less drug tolerability in real-world practice, which seems to be the reason why more female patients are included in the gefitinib group. EGFR mutations are more common in female patients, and therefore, the number of patients treated with afatinib came to be relatively small. From Table 1, it was evident that direct comparison despite uneven baseline characteristics between two groups might cause biased analysis, so the process of PS matching was needed. However, due to the small size of the afatinib group, even with a 1:3 ratio assigned to gefitinib, approximately 66% of the gefitinib data was discarded. This led to significantly less statistical power in our analysis. To overcome this issue, more patients need to be enrolled in the afatinib group in the following investigations.

In conclusion, afatinib has the inhibitory effect on the growth of the lung cancer cells with low T790M frequency. However, it could not be translated into the clinical efficacy to lower the rate or delay the time of T790M acquisition.

Funding

This study was supported by a grant of the Korea Health Technology R&D Project through the Korea Health Industry Development Institute (KHIDI), funded by the Ministry of Health & Welfare, Republic of Korea (grant HI15C0516 to J.C.L.) and a grant (2018-709 to J.C.L.) from the Asan Institute for Life Sciences, Seoul, Korea.

Footnotes

Conflict of interest: none.

Appendix A

Supplementary data to this article can be found online at https://doi.org/10.1016/j.tranon.2019.04.004.

Contributor Information

Tae-Won Jang, Email: jangtw22@hanmail.net.

Jae Cheol Lee, Email: jclee@amc.seoul.kr.

Appendix A. Supplementary material

Supplemental Figure 1. Propensity score matching results. (A) Raw Treated is afatinib group before matching and (B) Raw Control is gefitinib group before matching status. The distribution of the histogram is different between afatinib and gefitinib. (C) Matched Treated is afatinib group after matching and (D) Matched Control is gefitinib group after 1:3 matching. The distribution of the histogram is similar between afatinb and gefitinib. Supplemental Figure 2. OS hazard ratio, calculated by multivariate Cox analysis. Supplemental Figure 3. PFS hazard ratio, calculated by multivariate Cox analysis

mmc1.pptx (173.3KB, pptx)

References

  • 1.Solca F, Dahl G, Zoephel A, Bader G, Sanderson M, Klein C, Kraemer O, Himmelsbach F, Haaksma E, Adolf GR. Target binding properties and cellular activity of afatinib (BIBW 2992), an irreversible ErbB family blocker. J Pharmacol Exp Ther. 2012;343(2):342–350. doi: 10.1124/jpet.112.197756. [DOI] [PubMed] [Google Scholar]
  • 2.Li D, Ambrogio L, Shimamura T, Kubo S, Takahashi M, Chirieac LR, Padera RF, Shapiro GI, Baum A, Himmelsbach F. BIBW2992, an irreversible EGFR/HER2 inhibitor highly effective in preclinical lung cancer models. Oncogene. 2008;27(34):4702–4711. doi: 10.1038/onc.2008.109. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 3.Regales L, Gong Y, Shen R, de Stanchina E, Vivanco I, Goel A, Koutcher JA, Spassova M, Ouerfelli O, Mellinghoff IK. Dual targeting of EGFR can overcome a major drug resistance mutation in mouse models of EGFR mutant lung cancer. J Clin Investig. 2009;119(10):3000–3010. doi: 10.1172/JCI38746. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 4.Sos ML, Rode HB, Heynck S, Peifer M, Fischer F, Kluter S, Pawar VG, Reuter C, Heuckmann JM, Weiss J. Chemogenomic profiling provides insights into the limited activity of irreversible EGFR inhibitors in tumor cells expressing the T790M EGFR resistance mutation. Cancer Res. 2010;70(3):868–874. doi: 10.1158/0008-5472.CAN-09-3106. [DOI] [PubMed] [Google Scholar]
  • 5.Hirsh V. Next-generation covalent irreversible kinase inhibitors in NSCLC: focus on afatinib. BioDrugs. 2015;29(3):167–183. doi: 10.1007/s40259-015-0130-9. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 6.Miller VA, Hirsh V, Cadranel J, Chen YM, Park K, Kim SW, C Zhou WC Su, Wang M, Sun Y. Afatinib versus placebo for patients with advanced, metastatic non-small-cell lung cancer after failure of erlotinib, gefitinib, or both, and one or two lines of chemotherapy (LUX-Lung 1): a phase 2b/3 randomised trial. Lancet Oncol. 2012;13(5):528–538. doi: 10.1016/S1470-2045(12)70087-6. [DOI] [PubMed] [Google Scholar]
  • 7.Ercan D, Zejnullahu K, Yonesaka K, Xiao Y, Capelletti M, Rogers A, Lifshits E, Brown A, Lee C, Christensen JG. Amplification of EGFR T790M causes resistance to an irreversible EGFR inhibitor. Oncogene. 2010;29(16):2346–2356. doi: 10.1038/onc.2009.526. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 8.Nosaki K, Satouchi M, Kurata T, Yoshida T, Okamoto I, Katakami N, Imamura F, Tanaka K, Yamane Y, Yamamoto N. Re-biopsy status among non-small cell lung cancer patients in Japan: A retrospective study. Lung Cancer. 2016;101:1–8. doi: 10.1016/j.lungcan.2016.07.007. [DOI] [PubMed] [Google Scholar]
  • 9.Tanaka K, Nosaki K, Otsubo K, Azuma K, Sakata S, Ouchi H, Morinaga R, Wataya H, Fujii A, Nakagaki N. Acquisition of the T790M resistance mutation during afatinib treatment in EGFR tyrosine kinase inhibitor-naive patients with non-small cell lung cancer harboring EGFR mutations. Oncotarget. 2017;8(40):68123–68130. doi: 10.18632/oncotarget.19243. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 10.Kaburagi T, Kiyoshima M, Nawa T, Ichimura H, Saito T, Hayashihara K, Yamada H, Satoh H, Endo T, Inage Y. Acquired EGFR T790M mutation after relapse following EGFR-TKI therapy: a population-based multi-institutional study. Anticancer Res. 2018;38(5):3145–3150. doi: 10.21873/anticanres.12577. [DOI] [PubMed] [Google Scholar]
  • 11.Lee Y, Park S, Kim WS, Lee JC, Jang SJ, Choi J, Choi CM. Correlation between progression-free survival, tumor burden, and circulating tumor DNA in the initial diagnosis of advanced-stage EGFR-mutated non-small cell lung cancer. Thorac Cancer. 2018;9(9):1104–1110. doi: 10.1111/1759-7714.12793. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 12.Rho JK, Choi YJ, Jeon BS, Choi SJ, Cheon GJ, Woo SK, Kim HR, Kim CH, Choi CM, Lee JC. Combined treatment with silibinin and epidermal growth factor receptor tyrosine kinase inhibitors overcomes drug resistance caused by T790M mutation. Mol Cancer Ther. 2010;9(12):3233–3243. doi: 10.1158/1535-7163.MCT-10-0625. [DOI] [PubMed] [Google Scholar]
  • 13.Ho DE, Kosuke I, King G, Stuart EA. MatchIt: nonparametric preprocessing for parametric causal inference. J Stat Softw. 2011;42(8) [Google Scholar]
  • 14.Hansen BB, Klopfer SO. Optimal full matching and related designs via network flows. J Comput Graph Stat. 2006;15(3):609–627. [Google Scholar]
  • 15.Therneau TM, Grambsch PM. Springer; New York: 2000. Modeling survival data: extending the Cox model, Stat Biol Health. [xiii, 350 p] [Google Scholar]
  • 16.Rho JK, Choi YJ, Lee JK, Ryoo BY, Na II, Yang SH, Lee SS, Kim CH, Yoo YD, Lee JC. The role of MET activation in determining the sensitivity to epidermal growth factor receptor tyrosine kinase inhibitors. Mol Cancer Res. 2009;7(10):1736–1743. doi: 10.1158/1541-7786.MCR-08-0504. [DOI] [PubMed] [Google Scholar]
  • 17.Park JH, Choi YJ, Kim SY, Lee JE, Sung KJ, Park S, Kim WS, Song JS, Choi CM, Sung YH. Activation of the IGF1R pathway potentially mediates acquired resistance to mutant-selective 3rd-generation EGF receptor tyrosine kinase inhibitors in advanced non-small cell lung cancer. Oncotarget. 2016;7(16):22005–22015. doi: 10.18632/oncotarget.8013. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 18.Engelman JA, Mukohara T, Zejnullahu K, Lifshits E, Borras AM, Gale CM, Naumov GN, Yeap BY, Jarrell E, Sun J. Allelic dilution obscures detection of a biologically significant resistance mutation in EGFR-amplified lung cancer. J Clin Invest. 2006;116(10):2695–2706. doi: 10.1172/JCI28656. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 19.Sequist LV, Yang JC, Yamamoto N, O'Byrne K, Hirsh V, Mok T, Geater SL, Orlov S, Tsai CM, Boyer M. Phase III study of afatinib or cisplatin plus pemetrexed in patients with metastatic lung adenocarcinoma with EGFR mutations. J Clin Oncol. 2013;31(27):3327–3334. doi: 10.1200/JCO.2012.44.2806. [DOI] [PubMed] [Google Scholar]
  • 20.Campo M, Gerber D, Gainor JF, Heist RS, Temel JS, Shaw AT, Fidias P, Muzikansky A, Engelman JA, Sequist LV. Acquired resistance to first-line afatinib and the challenges of prearranged progression biopsies. J Thorac Oncol. 2016;11(11):2022–2026. doi: 10.1016/j.jtho.2016.06.032. [DOI] [PubMed] [Google Scholar]
  • 21.Yang JC, Shih JY, Su WC, Hsia TC, Tsai CM, Ou SH, Yu CJ, Chang GC, Ho CL, Sequist LV. Afatinib for patients with lung adenocarcinoma and epidermal growth factor receptor mutations (LUX-Lung 2): a phase 2 trial. Lancet Oncol. 2012;13(5):539–548. doi: 10.1016/S1470-2045(12)70086-4. [DOI] [PubMed] [Google Scholar]
  • 22.Wu SG, Liu YN, Tsai MF, Chang YL, Yu CJ, Yang PC, Yang JC, Wen YF, Shih JY. The mechanism of acquired resistance to irreversible EGFR tyrosine kinase inhibitor-afatinib in lung adenocarcinoma patients. Oncotarget. 2016;7(11):12404–12413. doi: 10.18632/oncotarget.7189. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 23.Park K, Tan EH, O'Byrne K, Zhang L, Boyer M, Mok T, Hirsh V, Yang JC, Lee KH, Lu S. Afatinib versus gefitinib as first-line treatment of patients with EGFR mutation-positive non-small-cell lung cancer (LUX-Lung 7): a phase 2B, open-label, randomised controlled trial. Lancet Oncol. 2016;17(5):577–589. doi: 10.1016/S1470-2045(16)30033-X. [DOI] [PubMed] [Google Scholar]
  • 24.Paz-Ares L, Tan EH, O'Byrne K, Zhang L, Hirsh V, Boyer M, Yang JC, Mok T, Lee KH, Lu S. Afatinib versus gefitinib in patients with EGFR mutation-positive advanced non-small-cell lung cancer: overall survival data from the phase IIb LUX-Lung 7 trial. Ann Oncol. 2017;28(2):270–277. doi: 10.1093/annonc/mdw611. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 25.Zhuo M, Zheng Q, Zhao J, Wu M, An T, Wang Y, Li J, Wang S, Zhong J, Yang X. Survival difference between EGFR Del19 and L858R mutant advanced non-small cell lung cancer patients receiving gefitinib: a propensity score matching analysis. Chin J Cancer Res. 2017;29(6):553–560. doi: 10.21147/j.issn.1000-9604.2017.06.10. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 26.Kohler J, Schuler M. Afatinib, erlotinib and gefitinib in the first-line therapy of EGFR mutation-positive lung adenocarcinoma: a review. Onkologie. 2013;36(9):510–518. doi: 10.1159/000354627. [DOI] [PubMed] [Google Scholar]
  • 27.Yang Z, Hackshaw A, Feng Q, Fu X, Zhang Y, Mao C, Tang J. Comparison of gefitinib, erlotinib and afatinib in non-small cell lung cancer: A meta-analysis. Int J Cancer. 2017;140(12):2805–2819. doi: 10.1002/ijc.30691. [DOI] [PubMed] [Google Scholar]
  • 28.Passaro A, Di Maio M, Del Signore E, Gori B, de Marinis F. management of nonhematologic toxicities associated with different EGFR-TKIs in advanced NSCLC: a comparison analysis. Clin Lung Cancer. 2014;15(4):307–312. doi: 10.1016/j.cllc.2014.04.006. [DOI] [PubMed] [Google Scholar]
  • 29.Lacouture ME, Schadendorf D, Chu CY, Uttenreuther-Fischer M, Stammberger U, O'Brien D, Hauschild A. Dermatologic adverse events associated with afatinib: an oral ErbB family blocker. Expert Rev Anticancer Ther. 2013;13(6):721–728. doi: 10.1586/era.13.30. [DOI] [PubMed] [Google Scholar]

Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

Supplemental Figure 1. Propensity score matching results. (A) Raw Treated is afatinib group before matching and (B) Raw Control is gefitinib group before matching status. The distribution of the histogram is different between afatinib and gefitinib. (C) Matched Treated is afatinib group after matching and (D) Matched Control is gefitinib group after 1:3 matching. The distribution of the histogram is similar between afatinb and gefitinib. Supplemental Figure 2. OS hazard ratio, calculated by multivariate Cox analysis. Supplemental Figure 3. PFS hazard ratio, calculated by multivariate Cox analysis

mmc1.pptx (173.3KB, pptx)

Articles from Translational Oncology are provided here courtesy of Neoplasia Press

RESOURCES