Evidence map›Paper›PMID 30964529›Full record

ArticleJAMA2019

Association of Patient Characteristics and Tumor Genomics With Clinical Outcomes Among Patients With Non-Small Cell Lung Cancer Using a Clinicogenomic Database.

Gaurav Singal, Peter G Miller, Vineeta Agarwala, Gerald Li, Gaurav Kaushik, Daniel Backenroth, Anala Gossai, Garrett M Frampton, Aracelis Z Torres, Erik M Lehnert and 18 more

Erratum issued Registry-linked trialOpen access · bronzeAbstract read
In one paragraph

Article in JAMA, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. It is linked to trial NCT05853887 (iNUDGE), which is not on this map. Cited by 346 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
346citing papers in PubMed, 1 pooled it
53.4field-weighted citation impact, top 1% of its field
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.

NCT05853887 naactive not recruitingnot on this mapstarted 2023, after this paper: background citation

iNUDGE: INtegration of liqUiD Biopsy Based Next Generation Gene sEquencing in Newly Diagnosed NSCLC - A Stepped Wedge Cluster Randomized Clinical Trial

TypeinterventionalSponsorCharu AggarwalRan2023 to 2026Enrolled260ConditionsNon Small Cell Lung Cancer Metastatic, Newly Diagnosed NSCLC, Non-Squamous Non-Small Cell Neoplasm of LungArmsiNUDGE
3 · Its place in the literature

Who cites it

346 citing papers in PubMed, 1 synthesis or guideline pooled it, 551 citations in OpenAlex.

  1. Diagnostic accuracy of next-generation sequencing (NGS) for identifying actionable mutations in advanced non-small cell lung cancer: Systematic Review and Meta-Analysis.Clinical & translational oncology : official publication of the Federation of Spanish Oncology Societies and of the National Cancer Institute of Mexico · 2026
    Pooled it
  2. LRP1b Loss Predicts Sensitivity to Immunotherapy in Patients with NSCLC: An Analysis of the Phase III CheckMate-026 Randomized Trial.Clinical cancer research : an official journal of the American Association for Cancer Research · 2025
    Trial
  3. Trial
  4. Article
  5. Article
  6. Role of ctDNA Tumor Fraction in Selecting Immunotherapy-Based Regimens in Advanced Non-Small Cell Lung Cancer.Clinical cancer research : an official journal of the American Association for Cancer Research · 2026
    Article
  7. Observational
  8. First-line versus second-line use of selpercatinib in treatment of RET fusion-positive advanced non-small cell lung cancer: a cost-effectiveness analysis.Clinical & translational oncology : official publication of the Federation of Spanish Oncology Societies and of the National Cancer Institute of Mexico · 2026
    Article
  9. Article
  10. SPEN inactivation drives resistance to androgen receptor pathway inhibitors in metastatic prostate cancer.Clinical cancer research : an official journal of the American Association for Cancer Research · 2026
    Article
  11. Article
  12. Article
  13. Article
  14. The Pan-Tumor Landscape of Gene Amplifications and Copy Number Amplification Ratio for Established and Emerging Clinical Targets.Clinical cancer research : an official journal of the American Association for Cancer Research · 2026
    Article
  15. Article
  16. Article
  17. Observational
  18. Article
  19. Article
  20. Article

286 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

28 authors at 6 institutions in 1 country.

Gaurav SingalFoundation Medicine Inc, Cambridge, Massachusetts.
Peter G MillerDepartment of Medical Oncology, Dana Farber Cancer Institute, Boston, Massachusetts.
Vineeta AgarwalaFlatiron Health Inc, New York, New York.
Gerald LiFoundation Medicine Inc, Cambridge, Massachusetts.
Gaurav KaushikFoundation Medicine Inc, Cambridge, Massachusetts.
Daniel BackenrothFlatiron Health Inc, New York, New York.
Anala GossaiFlatiron Health Inc, New York, New York.
Garrett M FramptonFoundation Medicine Inc, Cambridge, Massachusetts.
Aracelis Z TorresFlatiron Health Inc, New York, New York.
Erik M LehnertFoundation Medicine Inc, Cambridge, Massachusetts.
David BourqueFoundation Medicine Inc, Cambridge, Massachusetts.
Claire O'ConnellFlatiron Health Inc, New York, New York.
Bryan BowserFlatiron Health Inc, New York, New York.
Thomas CaronFlatiron Health Inc, New York, New York.
Ezra BaydurFlatiron Health Inc, New York, New York.
Kathi Seidl-RathkopfFlatiron Health Inc, New York, New York.
Ivan IvanovFlatiron Health Inc, New York, New York.
Garrett Alpha-CobbFoundation Medicine Inc, Cambridge, Massachusetts.
Ameet GuriaFoundation Medicine Inc, Cambridge, Massachusetts.
Jie HeFoundation Medicine Inc, Cambridge, Massachusetts.
Shannon FrankFlatiron Health Inc, New York, New York.
Allen C NunnallyVoyager Therapeutics, Cambridge, Massachusetts.
Mark BaileyFoundation Medicine Inc, Cambridge, Massachusetts.
Ann JaskiwFlatiron Health Inc, New York, New York.
Dana FeuchtbaumFlatiron Health Inc, New York, New York.
Nathan NussbaumFlatiron Health Inc, New York, New York.
Amy P AbernethyFlatiron Health Inc, New York, New York.
Vincent A MillerFoundation Medicine Inc, Cambridge, Massachusetts.
Flatiron Health (United States) · USFoundation Medicine (United States)Brigham and Women's Hospital · USDana-Farber Cancer Institute · USNew York University · USVoyager Therapeutics (United States) · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Importance: Data sets linking comprehensive genomic profiling (CGP) to clinical outcomes may accelerate precision medicine. Objective: To assess whether a database that combines EHR-derived clinical data with CGP can identify and extend associations in non-small cell lung cancer (NSCLC). Design, Setting, and Participants: Clinical data from EHRs were linked with CGP results for 28 998 patients from 275 US oncology practices. Among 4064 patients with NSCLC, exploratory associations between tumor genomics and patient characteristics with clinical outcomes were conducted, with data obtained between January 1, 2011, and January 1, 2018. Exposures: Tumor CGP, including presence of a driver alteration (a pathogenic or likely pathogenic alteration in a gene shown to drive tumor growth); tumor mutation burden (TMB), defined as the number of mutations per megabase; and clinical characteristics gathered from EHRs. Main Outcomes and Measures: Overall survival (OS), time receiving therapy, maximal therapy response (as documented by the treating physician in the EHR), and clinical benefit rate (fraction of patients with stable disease, partial response, or complete response) to therapy. Results: Among 4064 patients with NSCLC (median age, 66.0 years; 51.9% female), 3183 (78.3%) had a history of smoking, 3153 (77.6%) had nonsquamous cancer, and 871 (21.4%) had an alteration in EGFR, ALK, or ROS1 (701 [17.2%] with EGFR, 128 [3.1%] with ALK, and 42 [1.0%] with ROS1 alterations). There were 1946 deaths in 7 years. For patients with a driver alteration, improved OS was observed among those treated with (n = 575) vs not treated with (n = 560) targeted therapies (median, 18.6 months [95% CI, 15.2-21.7] vs 11.4 months [95% CI, 9.7-12.5] from advanced diagnosis; P < .001). TMB (in mutations/Mb) was significantly higher among smokers vs nonsmokers (8.7 [IQR, 4.4-14.8] vs 2.6 [IQR, 1.7-5.2]; P < .001) and significantly lower among patients with vs without an alteration in EGFR (3.5 [IQR, 1.76-6.1] vs 7.8 [IQR, 3.5-13.9]; P < .001), ALK (2.1 [IQR, 0.9-4.0] vs 7.0 [IQR, 3.5-13.0]; P < .001), RET (4.6 [IQR, 1.7-8.7] vs 7.0 [IQR, 2.6-13.0]; P = .004), or ROS1 (4.0 [IQR, 1.2-9.6] vs 7.0 [IQR, 2.6-13.0]; P = .03). In patients treated with anti-PD-1/PD-L1 therapies (n = 1290, 31.7%), TMB of 20 or more was significantly associated with improved OS from therapy initiation (16.8 months [95% CI, 11.6-24.9] vs 8.5 months [95% CI, 7.6-9.7]; P < .001), longer time receiving therapy (7.8 months [95% CI, 5.5-11.1] vs 3.3 months [95% CI, 2.8-3.7]; P < .001), and increased clinical benefit rate (80.7% vs 56.7%; P < .001) vs TMB less than 20. Conclusions and Relevance: Among patients with NSCLC included in a longitudinal database of clinical data linked to CGP results from routine care, exploratory analyses replicated previously described associations between clinical and genomic characteristics, between driver mutations and response to targeted therapy, and between TMB and response to immunotherapy. These findings demonstrate the feasibility of creating a clinicogenomic database derived from routine clinical experience and provide support for further research and discovery evaluating this approach in oncology.

Indexed as

Databases, GeneticElectronic Health RecordsImmunotherapyMutationAgedBiomarkers, TumorCarcinoma, Non-Small-Cell LungDatasets as TopicFemaleGene Expression ProfilingGenomicsGenotypeHumansLung NeoplasmsMaleMedical Record LinkageBiomarkers, TumorPDCD1 protein, humanProgrammed Cell Death 1 Receptor

Identifiers

PMID30964529
PMCPMC6459115
OpenAlexW2938929416

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Registered trials

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.