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Li, Yalun

https://orcid.org/0000-0002-9052-8209

Mayo Clinic

Sichuan University

Citations 2

Osimertinib in previously EGFR-TKI treated non-small cell lung cancer (NSCLC) patients without T790M mutation: Real-world evidence.
Tazelaar, Henry D. , Li, Yalun , Peikert, Tobias, Leventakos, Konstantinos , Chiou, Shih‐Hwa , Luo, Yung‐Hung , Liu, Han , Wampfler, Jason A. , Tazelaar, Henry D. , Liu, Dan , Chen, Yuh‐Min , Yang, Yanan , Yang, Ping

Journal of Clinical Oncology | May 25, 2020 | Volume: 38 | Issue: 15_suppl | Pages: e21631-e21631

10.1200/jco.2020.38.15_suppl.e21631 Get It

e21631 Background: The efficacy of osimertinib in previously EGFR-TKI treated NSCLC patients without T790M mutation remains unclear in real-world practice. We investigated whether osimertinib can provide survival benefit in EGFR-mutant patients without T790M mutation after 1st/2nd generation TKI treatment. Methods: Between January 1, 2009, and March 31, 2019, 417 patients had stage III-IV NSCLC harboring EGFR mutation and 154 out of 417 patients receiving osimertinib as≥2nd-line EGFR-TKI treatment were identified at Mayo Clinic. The time to treatment failure of osimertinib was analyzed by the Kaplan-Meier (KM) estimates. The risk of death post diagnosis was analyzed by Cox proportional hazard models. Results: Among 417 EGFR-mutant patients, higher risk of death was found in patients with age above 65 years, non-adenocarcinoma, no surgery treatment, no radiation treatment, non-exon 19 deletion/exon 21 L858R mutation, higher ECOG PS (2-4), PD-L1 expression of 50% or more, bone metastasis, live metastasis, and adrenal metastasis (all p < 0.05). Moreover, osimertinib as ≥2nd-line TKI treatment in patients with or without T790M revealed lower risk of death compared to 1st/2nd generation TKI treatment without subsequent osimertinib (HR = 0.33; 0.46, and p = 0.0002; 0.0232, respectively). However, among patients receiving osimertinib as ≥2nd-line TKI treatment, patients with T790M did not have superior survival than those without (p = 0.2803). Among 154 patients receiving osimertinib, a higher risk of treatment failure for osimertinib was found in male (HR = 1.72; p = 0.0327), patients with 1st-line TKI duration ≤12 months (HR = 2.16; p = 0.0019), BMI drop > 10% (HR = 1.85; p = 0.0207), PD-L1 levels of 50% or more (HR = 4.28; p = 0.0008), and 1st-line TKI with afatinib (HR = 2.19; p = 0.0136). Nonetheless, osimertinib as ≥2nd-line TKI in patients without 790M mutation did not have higher risk of treatment failure than those with T790M (p = 0.1236). Conclusions: This is the first study to demonstrate that osimertinib can provide similar survival benefit in previously EGFR-TKI treated NSCLC patients without T790M mutation as those with T790M in real-world practice. Additionally, EGFR-mutant patients with PD-L1 expression ≥50% had a higher risk of treatment failure for osimertinib and worse overall survival than those with PD-L1 expression < 50% and may potentially gain benefit from optimizing treatment strategies including immunotherapy.
Efficient and Accurate Extracting of Unstructured EHRs on Cancer Therapy Responses for the Development of RECIST Natural Language Processing Tools: Part I, the Corpus
Li, Yalun , Wampfler, Jason A. , Rubinstein, Samuel M. , Tiryaki, Firat, Kumar, Ashok, Xu, Hua , Ashok, Kumar, Luo, Yung‐Hung , Warner, Jeremy L. , Yang, Ping

JCO Clinical Cancer Informatics | May 4, 2020 | Volume: No volume available | Issue: 4 | Pages: 383-391

10.1200/cci.19.00147 Get It

PURPOSE Electronic health records (EHRs) are created primarily for nonresearch purposes; thus, the amounts of data are enormous, and the data are crude, heterogeneous, incomplete, and largely unstructured, presenting challenges to effective analyses for timely, reliable results. Particularly, research dealing with clinical notes relevant to patient care and outcome is seldom conducted, due to the complexity of data extraction and accurate annotation in the past. RECIST is a set of widely accepted research criteria to evaluate tumor response in patients undergoing antineoplastic therapy. The aim for this study was to identify textual sources for RECIST information in EHRs and to develop a corpus of pharmacotherapy and response entities for development of natural language processing tools. METHODS We focused on pharmacotherapies and patient responses, using 55,120 medical notes (n = 72 types) in Mayo Clinic’s EHRs from 622 randomly selected patients who signed authorization for research. Using the Multidocument Annotation Environment tool, we applied and evaluated predefined keywords, and time interval and note-type filters for identifying RECIST information and established a gold standard data set for patient outcome research. RESULTS Key words reduced clinical notes to 37,406, and using four note types within 12 months postdiagnosis further reduced the number of notes to 5,005 that were manually annotated, which covered 97.9% of all cases (n = 609 of 622). The resulting data set of 609 cases (n = 503 for training and n = 106 for validation purpose), contains 736 fully annotated, deidentified clinical notes, with pharmacotherapies and four response end points: complete response, partial response, stable disease, and progressive disease. This resource is readily expandable to specific drugs, regimens, and most solid tumors. CONCLUSION We have established a gold standard data set to accommodate development of biomedical informatics tools in accelerating research into antineoplastic therapeutic response.