Evidence map›Paper›PMID 40027276›Full record

ArticleContemporary clinical trials communications2025

Real-world enrollment for a prospective clinico-genomic database using a pragmatic technology-enabled platform.

Alexia Exarchos, Ariel B Bourla, Maneet Kaur, Katja Schulze, Sophia Maund, Yi Cao, Yihua Zhao, Elizabeth H Williams, Sarah C Gaffey, Richard Zuniga and 6 more

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Contemporary clinical trials communications, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. Article
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

16 authors.

Alexia ExarchosGenentech, Inc., South San Francisco, CA, USA.
Ariel B BourlaFlatiron Health, Inc., New York, NY, USA.
Maneet KaurFlatiron Health, Inc., New York, NY, USA.
Katja SchulzeGenentech, Inc., South San Francisco, CA, USA.
Sophia MaundGenentech, Inc., South San Francisco, CA, USA.
Yi CaoGenentech, Inc., South San Francisco, CA, USA.
Yihua ZhaoFlatiron Health, Inc., New York, NY, USA.
Elizabeth H WilliamsFoundation Medicine, Inc., Cambridge, MA, USA.
Sarah C GaffeyFoundation Medicine, Inc., Cambridge, MA, USA.
Richard ZunigaNew York Cancer & Blood Specialists, New York, NY, USA.
Shaily LakhanpalAlabama Oncology, Birmingham, AL, USA.
Vladan AnticF. Hoffmann-La Roche Ltd, Basel, Switzerland.
Michelle DoralGenentech, Inc., South San Francisco, CA, USA.
Johanna SyGenentech, Inc., South San Francisco, CA, USA.
Neal J MeropolFlatiron Health, Inc., New York, NY, USA.
Anne C ChiangYale School of Medicine, New Haven, CT, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Discovery and incorporation of predictive and prognostic biomarkers enhance outcomes for patients with cancer. Clinico-genomic datasets, which retrospectively link real-world clinical data to tumor sequencing data, are important resources for biomarker research, which has historically relied on robust research infrastructures exclusive to large academic centers. The objective was to evaluate the feasibility of a pragmatic, technology-enabled platform at community-based research sites for development of a prospective clinico-genomic database supported by centralized electronic health record (EHR)-based patient ascertainment and data processing. Methods: Adults with stage IV or recurrent metastatic non-small cell lung cancer or extensive-stage small-cell lung cancer were enrolled at 23 US sites upon initiating a standard line of therapy. Enrollment rates were estimated from eligible populations at individual centers. Clinical data from routinely collected EHR documentation were centrally processed and normalized for quality control. Serial blood samples at pre-specified timepoints (baseline, during treatment and at disease progression/end of therapy) were used for circulating tumor DNA (ctDNA) genomic profiling. Results: Between December 2019 and May 2021, 944 patients enrolled, representing ≈25 % of eligible patients. Eight-hundred seventeen of 944 (87 %), 406 of 606 (67 %) and 398 of 852 (47 %) participants provided qualifying samples for ctDNA testing at baseline, during treatment and at disease progression/end of therapy, respectively. Samples were provided at all three timepoints by 35 % of participants. Conclusion: A community-based oncology patient cohort was rapidly enrolled, creating a real-world clinico-genomic dataset. This pragmatic study platform has potential research applications where prospective real-world data may contribute to evidence generation.

Indexed as

Circulating tumor DNAElectronic health recordsFeasibility studyLung neoplasmsProspective study

Identifiers

PMID40027276
PMCPMC11869879

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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.