Targeted Therapy for Non-Small Cell Lung Cancer.

Lung cancer is a heterogeneous disease, and the availability of comprehensive genomic profiling has allowed for the characterization of its molecular subtypes. This has increased the ability to deliver "personalized medicines" by tailoring therapies to target driver mutations in a patient's cancer. The development of targeted therapies for non-small cell lung cancer (NSCLC) has helped define the era of precision medicine throughout oncology. This article aims to contextualize recent research and provide an updated summary of targeted therapies available for patients with NSCLC. With practitioners and clinical researchers in mind, we note standard of care therapies, important approvals, practice guidelines, and treatments in development. The first section discusses mutations in the epidermal growth factor receptor (EGFR) gene, and the second section examines rearrangements in the anaplastic lymphoma kinase (ALK) and ROS1 fusions. Finally, we explore the rarer molecular alterations in BRAF, RET, MET, HER2, and KRAS. Given the many available therapies, it is important to understand the molecular alterations in NSCLC, and how to target them.

Non-small cell lung cancer clinical trials requiring biopsies with biomarker-specific results for enrollment provide unique challenges.

BACKGROUND: Clinical trials in lung cancer increasingly require patients to provide fresh tumor tissue as a prerequisite to enrollment. The effects of this requirement on enrollment rates, enrollment durations, and patient selection have not been fully elucidated. METHODS: The authors retrospectively reviewed data generated by patients who consented to 1 or more interventional lung cancer clinical trials at the University of California-Los Angeles Jonsson Comprehensive Cancer Center between January 2013 and December 2014. Trials were considered to require a biopsy when enrollment was conditional on the procurement of tissue without intervening therapy between procurement and enrollment. RESULTS: In total, 311 patients underwent 368 screening incidents for 1 or more of 19 trials. Trials that required a new biopsy had a longer median screening duration (34 vs 14 days) than trials that did not require a biopsy (P < .001). Trials that required a biopsy had a greater screen failure rate (49.1% vs 26.5%; P < .001), which was largely driven by patients who did not undergo the required biopsy or lacked the required biomarker. Worsening performance status led to the majority of screen failures (56.5%) among biomarker-eligible patients. CONCLUSIONS: Although the scientific benefits of obtaining a new biopsy and requiring specific results for trial enrollment are clear, these requirements lead to a lengthening of the screening period, which, in some patients, is associated with clinical decline before enrollment. Implications for the interpretation of data from studies of this design should be explored. Cancer 2017;123:4800-7. © 2017 American Cancer Society.

Low Concordance of Patient-Reported Outcomes With Clinical and Clinical Trial Documentation.

PURPOSE: Health care research increasingly relies on assessment of data extracted from electronic medical records (EMRs). Clinical trial adverse event (AE) logs and patient-reported outcomes (PROs) are sources of data often available in the context of specific research projects. The aim of this study was to evaluate the extent of data concordance from these sources. PATIENTS AND METHODS: Patients enrolled in clinical trials or receiving standard treatment for lung cancer (n = 62) completed validated questionnaires on physical and psychological symptoms at up to three assessment points. Temporally matched documentation was extracted from EMR notes and, for clinical trial participants (n = 41), AE logs. Evaluated data included symptom assessment, vital signs, medication logs, and laboratory values. Agreement (positive, negative) and Cohen's κ coefficients were calculated to assess concordance of symptoms among sources, with PROs considered the gold standard. RESULTS: Patient-reported weight loss correlated significantly with clinical measurements ( t = 2.90; P = .02), and average number of PROs correlated negatively with albumin concentration, supporting PROs as the gold standard. Comparisons of PROs versus EMR yielded poor concordance across 11 physical symptoms, anxiety, and depressive symptoms (all κ < 0.40). Providers under-reported the presence of each symptom in the EMR compared with PROs. AE logs showed similarly poor concordance with PROs (all κ < 0.40, except shortness of breath). Negative agreement among sources was higher than positive agreement for all symptoms except pain. CONCLUSION: There was poor concordance between EMR notes and AE logs with PROs. Findings suggest that EMR notes and AE logs may not be reliable sources for capturing physical and psychological symptoms experienced by patients with lung cancer, supporting use of PRO assessments in oncology practices.

Evaluating Casama: Contextualized semantic maps for summarization of lung cancer studies.

OBJECTIVE: It is crucial for clinicians to stay up to date on current literature in order to apply recent evidence to clinical decision making. Automatic summarization systems can help clinicians quickly view an aggregated summary of literature on a topic. Casama, a representation and summarization system based on "contextualized semantic maps," captures the findings of biomedical studies as well as the contexts associated with patient population and study design. This paper presents a user-oriented evaluation of Casama in comparison to a context-free representation, SemRep. MATERIALS AND METHODS: The effectiveness of the representation was evaluated by presenting users with manually annotated Casama and SemRep summaries of ten articles on driver mutations in cancer. Automatic annotations were evaluated on a collection of articles on EGFR mutation in lung cancer. Seven users completed a questionnaire rating the summarization quality for various topics and applications. RESULTS: Casama had higher median scores than SemRep for the majority of the topics (p≤ 0.00032), all of the applications (p≤ 0.00089), and in overall summarization quality (p≤ 1.5e-05). Casama's manual annotations outperformed Casama's automatic annotations (p = 0.00061). DISCUSSION: Casama performed particularly well in the representation of strength of evidence, which was highly rated both quantitatively and qualitatively. Users noted that Casama's less granular, more targeted representation improved usability compared to SemRep. CONCLUSION: This evaluation demonstrated the benefits of a contextualized representation for summarizing biomedical literature on cancer. Iteration on specific areas of Casama's representation, further development of its algorithms, and a clinically-oriented evaluation are warranted.

Treatment-Related Adverse Events Predict Improved Clinical Outcome in NSCLC Patients on KEYNOTE-001 at a Single Center.

We retrospectively analyzed non-small cell lung cancer (NSCLC) patients from a single center treated with pembrolizumab on the KEYNOTE-001 trial and evaluated the association between treatment-related adverse events (trAEs) and clinical outcomes. Investigators reported AEs on trial and graded them according to Common Terminology Criteria for Adverse Events v4.0, labeling them as unlikely, possibly, or probably treatment-related. AEs labeled as possibly/probably related were considered trAEs for this analysis. The relationship between the incidence of a trAE and clinical outcomes was evaluated. Ninety-seven NSCLC patients treated on KEYNOTE-001 at the University of California, Los Angeles were evaluated. Ten percent (85/826) of AEs were trAEs, occurring in 40% (39/97) of patients. The most frequent trAEs were rash (21% patients), fatigue (6% patients), and hypothyroidism (6% patients). The 39 patients that experienced a trAE had increased objective response rate (ORR, 38.5%), progression-free survival (PFS: median, 248 days), and overall survival (OS: median, 493 days), compared with the 58 patients that did not (ORR: 8.9%, PFS: median 60 days, OS: median 144.5 days). The observed association between trAEs and improved clinical outcome persisted when using Cox proportional hazards regression models to assess the confounding effect of covariates and mitigate guarantee-time bias. The association also remained when data were substratified by grade, degree of association, and treatment-related select AE designation. This single-center analysis revealed that trAEs predicted for improved clinical outcome with pembrolizumab, and when controlling for guarantee-time bias and plausible confounders, this association remained. This observed relationship adds to our understanding of anti-PD-1 therapy and could aid clinicians in identifying patients most likely to benefit from therapy. Cancer Immunol Res; 6(3); 288-94. ©2018 AACR.

Representing and extracting lung cancer study metadata: study objective and study design.

This paper describes the information retrieval step in Casama (Contextualized Semantic Maps), a project that summarizes and contextualizes current research papers on driver mutations in non-small cell lung cancer. Casama׳s representation of lung cancer studies aims to capture elements that will assist an end-user in retrieving studies and, importantly, judging their strength. This paper focuses on two types of study metadata: study objective and study design. 430 abstracts on EGFR and ALK mutations in lung cancer were annotated manually. Casama׳s support vector machine (SVM) automatically classified the abstracts by study objective with as much as 129% higher F-scores compared to PubMed׳s built-in filters. A second SVM classified the abstracts by epidemiological study design, suggesting strength of evidence at a more granular level than in previous work. The classification results and the top features determined by the classifiers suggest that this scheme would be generalizable to other mutations in lung cancer, as well as studies on driver mutations in other cancer domains.