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Research Paper

Mutation abundance affects the therapeutic efficacy of EGFR-TKI in patients with advanced lung adenocarcinoma: A retrospective analysis

, , , , , , , , & show all
Pages 687-694 | Received 10 Nov 2017, Accepted 03 Mar 2018, Published online: 13 Apr 2018

Figures & data

Figure 1. Flow diagram of patients enrolled in the study.

Figure 1. Flow diagram of patients enrolled in the study.

Table 1. Baseline demographic and clinical characteristics.

Table 2. The association between PFS and mutation abundance after EGFR-TKI therapy.

Table 3. Risk factors to PFS by univariate analysis.

Figure 2. The cut-off value of EGFR (exon19 and exon21) mutation abundance with ROC curve analysis.

Figure 2. The cut-off value of EGFR (exon19 and exon21) mutation abundance with ROC curve analysis.

Table 4. The cut-off value of EGFR mutation abundance to the PFS by ROC analysis.

Table 5. Cox regression survival analysis of correlations between EGFR mutation abundance cut-off values and PFS by after adjusting the influence of age, gender and other general factors.

Figure 3. Survival analysis of the effects of EGFR-TKI A) first line or B) non-first line treatments on high and low EGFR mutation abundance NSCLC patients.

Figure 3. Survival analysis of the effects of EGFR-TKI A) first line or B) non-first line treatments on high and low EGFR mutation abundance NSCLC patients.

Table 6. The distribution of EGFR mutation sites and mutation abundance in 861 patients.

Figure 4. Kaplan-Meier curves for median PFS in high and low mutation abundance patients with A) exon 19 deletions or exon 21 mutations, B) exon 19 deletions and C) exon 21 mutations.

Figure 4. Kaplan-Meier curves for median PFS in high and low mutation abundance patients with A) exon 19 deletions or exon 21 mutations, B) exon 19 deletions and C) exon 21 mutations.
Supplemental material

2017CBT10825R-s02.doc

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