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Serial cfDNA assessment of response and resistance to EGFR-TKI for patients with EGFR-L858R mutant lung cancer from a prospective clinical trial

Overview of attention for article published in Journal of Hematology & Oncology, September 2016
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Title
Serial cfDNA assessment of response and resistance to EGFR-TKI for patients with EGFR-L858R mutant lung cancer from a prospective clinical trial
Published in
Journal of Hematology & Oncology, September 2016
DOI 10.1186/s13045-016-0316-8
Pubmed ID
Authors

Qing Zhou, Jin-Ji Yang, Zhi-Hong Chen, Xu-Chao Zhang, Hong-Hong Yan, Chong-Rui Xu, Jian Su, Hua-Jun Chen, Hai-Yan Tu, Wen-Zhao Zhong, Xue-Ning Yang, Yi-Long Wu

Abstract

Detecting epidermal growth factor receptor (EGFR) activating mutations in plasma could guide EGFR-tyrosine kinase inhibitor (EGFR-TKI) treatment for advanced non-small cell lung cancer (NSCLC). However, dynamic quantitative changes of plasma EGFR mutations during the whole course of EGFR-TKI treatment and its correlation with clinical outcomes were not determined. The aim of this study was to measure changes of plasma EGFR L858R mutation during EGFR-TKI treatment and to determine its correlation with the response and resistance to EGFR-TKI. This study was a pre-planned exploratory analysis of a randomized phase III trial conducted from 2009 to 2014 comparing erlotinib with gefitinib in advanced NSCLC harboring EGFR mutations in tumor (CTONG0901). Totally, 256 patients were enrolled in CTONG0901 and randomized to receive erlotinib or gefitinib. One hundred and eight patients harbored L858R mutation in their tumors and 80 patients provided serial blood samples as pre-planned scheduled. Serial plasma L858R was detected using quantitative polymerase chain reaction. Dynamic types of plasma L858R were analyzed using Ward's hierarchical clustering method. Progression-free survival (PFS) and overall survival (OS) were compared between different types. As a whole, the quantity of L858R decreased and reached the lowest level at the time of best response to EGFR-TKI. After the analysis of Ward's hierarchical clustering method, two dynamic types were found. In 61 patients, L858R increased to its highest level when disease progressed (ascend type), while in 19 patients, L858R maintained a stable level when disease progressed (stable type). Median PFS was 11.1 months (95 % CI, 6.6-15.6) and 7.5 months (95 % CI, 1.4-13.6) in patients with ascend and stable types, respectively (P = 0.023). Median OS was 19.7 months (95 % CI, 16.5-22.9) and 16.0 months (95 % CI, 13.4-18.5), respectively (P = 0.050). This is the first report finding two different dynamic types of plasma L858R mutation during EGFR-TKI treatment based on a prospective randomized study. Different dynamic types were correlated with benefits from EGFR-TKI. The impact of plasma L858R levels at disease progression on subsequent treatment strategy needs further exploration. ClinicalTrials.gov, NCT01024413.

Twitter Demographics

The data shown below were collected from the profile of 1 tweeter who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 43 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Ireland 1 2%
Unknown 42 98%

Demographic breakdown

Readers by professional status Count As %
Researcher 9 21%
Student > Master 7 16%
Other 5 12%
Student > Ph. D. Student 5 12%
Student > Bachelor 4 9%
Other 5 12%
Unknown 8 19%
Readers by discipline Count As %
Medicine and Dentistry 13 30%
Biochemistry, Genetics and Molecular Biology 5 12%
Agricultural and Biological Sciences 4 9%
Nursing and Health Professions 3 7%
Pharmacology, Toxicology and Pharmaceutical Science 3 7%
Other 3 7%
Unknown 12 28%

Attention Score in Context

This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 20 September 2016.
All research outputs
#6,381,797
of 8,409,255 outputs
Outputs from Journal of Hematology & Oncology
#233
of 371 outputs
Outputs of similar age
#178,463
of 253,630 outputs
Outputs of similar age from Journal of Hematology & Oncology
#14
of 21 outputs
Altmetric has tracked 8,409,255 research outputs across all sources so far. This one is in the 13th percentile – i.e., 13% of other outputs scored the same or lower than it.
So far Altmetric has tracked 371 research outputs from this source. They receive a mean Attention Score of 2.4. This one is in the 21st percentile – i.e., 21% of its peers scored the same or lower than it.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 253,630 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 17th percentile – i.e., 17% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 21 others from the same source and published within six weeks on either side of this one. This one is in the 19th percentile – i.e., 19% of its contemporaries scored the same or lower than it.