Evidence map›Paper›PMID 32639928›Full record

ArticleJCO oncology practice2021

Evaluation of Omics-Based Strategies for the Management of Advanced Lung Cancer.

Ravi Salgia, Isa Mambetsariev, Rebecca Pharaon, Jeremy Fricke, Angel Ray Baroz, Iztok Hozo, Chen Chen, Marianna Koczywas, Erminia Massarelli, Karen Reckamp and 1 more

Abstract read
In one paragraph

Article in JCO oncology practice, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

7 citing papers in PubMed.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

11 authors.

Ravi SalgiaDepartment of Medical Oncology and Therapeutics Research, City of Hope, Duarte, CA.
Isa MambetsarievDepartment of Medical Oncology and Therapeutics Research, City of Hope, Duarte, CA.
Rebecca PharaonDepartment of Medical Oncology and Therapeutics Research, City of Hope, Duarte, CA.
Jeremy FrickeDepartment of Medical Oncology and Therapeutics Research, City of Hope, Duarte, CA.
Angel Ray BarozDepartment of Medical Oncology and Therapeutics Research, City of Hope, Duarte, CA.
Iztok HozoDepartment of Mathematics, Indiana University Northwest, Gary, IN.
Chen ChenApplied AI and Data Science, City of Hope, Duarte, CA.
Marianna KoczywasDepartment of Medical Oncology and Therapeutics Research, City of Hope, Duarte, CA.
Erminia MassarelliDepartment of Medical Oncology and Therapeutics Research, City of Hope, Duarte, CA.
Karen ReckampDepartment of Medical Oncology and Therapeutics Research, City of Hope, Duarte, CA.
Benjamin DjulbegovicDepartment of Hematology and Hematopoietic Cell Transplantation, City of Hope, Duarte, CA.

Funding

Transgenic Mouse FacilityP30CA033572 · NCI · CITY OF HOPE/BECKMAN RESEARCH INSTITUTE · PI John Charles Williams · 1985 to 2026
$86.3M
Project 2: Targeting Cooperative Phenotypes Common in Spatial HeterogeneityU54CA209978 · NCI · UNIVERSITY OF UTAH · PI MOOS, PHILIP J · 2017 to 2021
$10.5M
Novel approach to attenuate small cell lung cancer growth and metastasisR01CA218545 · NCI · UNIVERSITY OF NEBRASKA MEDICAL CENTER · PI NASSER, MOHD WASIM · 2018 to 2022
$2.6M
NCI NIH HHS P30 CA033572NCI NIH HHS R01 CA218545NCI NIH HHS U54 CA209978
6 · The paper itself

Abstract

purposeOmic-informed therapy is being used more frequently for patients with non-small-cell lung cancer (NSCLC) being treated on the basis of evidence-based decision-making. However, there is a lack of a standardized framework to evaluate those decisions and understand the association between omics-based management strategies and survival among patients. Therefore, we compared outcomes between patients with lung adenocarcinoma who received omics-driven targeted therapy versus patients who received standard therapeutic options. PATIENTS AND

methodsThis was a retrospective study of patients with advanced NSCLC adenocarcinoma (N = 798) at City of Hope who received genomic sequencing at the behest of their treating oncologists. A thoracic oncology registry was used as a clinicogenomic database to track patient outcomes.

resultsOf 798 individuals with advanced NSCLC (median age, 65 years [range, 22-99 years]; 60% white; 50% with a history of smoking), 662 patients (83%) had molecular testing and 439 (55%) received targeted therapy on the basis of the omic-data. A fast-and-frugal decision tree (FFT) model was developed to evaluate the impact of omics-based strategy on decision-making, progression-free survival (PFS), and overall survival (OS). We calculated that the overall positive predictive value of the entire FFT strategy for predicting decisions regarding the use of tyrosine kinase inhibitor-based targeted therapy was 88% and the negative predictive value was 96%. In an adjusted Cox regression analysis, there was a significant correlation with survival benefit with the FFT omics-driven therapeutic strategy for both PFS (hazard ratio [HR], 0.56; 95% CI, 0.42 to 0.74;

conclusionAmong patients with advanced NSCLC who received care in the academic oncology setting, omics-driven therapy decisions directly informed treatment in patients and was correlated with better OS and PFS.

Indexed as

Adenocarcinoma of LungCarcinoma, Non-Small-Cell LungLung NeoplasmsAgedHumansProtein Kinase InhibitorsRetrospective StudiesProtein Kinase Inhibitors

Identifiers

PMID32639928
PMCPMC8258019

What OpenQuestion holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.