Evidence map›Paper›PMID 36634297›Full record

SynthesisJCO precision oncology2023

Programmatic Precision Oncology Decision Support for Patients With Gastrointestinal Cancer.

Rachel B Keller, Tali Mazor, Lynette Sholl, Andrew J Aguirre, Harshabad Singh, Nilay Sethi, Adam Bass, Ankur K Nagaraja, Lauren K Brais, Emma Hill and 33 more

Abstract readSystematic Review
In one paragraph

Synthesis in JCO precision oncology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed, 1 pooled it
–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

9 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Article
  3. Article
  4. Article
  5. Article
  6. Review
  7. Review
  8. Oncogenic Drivers and Therapeutic Vulnerabilities in KRAS Wild-Type Pancreatic Cancer.Clinical cancer research : an official journal of the American Association for Cancer Research · 2023
    Article
  9. 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

43 authors.

Rachel B KellerDepartment of Medical Oncology, Dana-Farber Cancer Institute & Harvard Medical School, Boston, MA.ORCID 0000-0001-6138-9257
Tali MazorDepartment of Data Science, Dana-Farber Cancer Institute, Boston, MA.ORCID 0000-0002-0138-9615
Lynette ShollCenter for Advanced Molecular Diagnostics, Brigham & Women's Hospital & Harvard Medical School, Boston, MA.ORCID 0000-0002-9532-9735
Andrew J AguirreDepartment of Medical Oncology, Dana-Farber Cancer Institute & Harvard Medical School, Boston, MA.ORCID 0000-0002-0701-6203
Harshabad SinghDepartment of Medical Oncology, Dana-Farber Cancer Institute & Harvard Medical School, Boston, MA.ORCID 0000-0001-6295-2013
Nilay SethiDepartment of Medical Oncology, Dana-Farber Cancer Institute & Harvard Medical School, Boston, MA.ORCID 0000-0002-3748-7559
Adam BassDepartment of Medical Oncology, Dana-Farber Cancer Institute & Harvard Medical School, Boston, MA.
Ankur K NagarajaDepartment of Medical Oncology, Dana-Farber Cancer Institute & Harvard Medical School, Boston, MA.
Lauren K BraisDepartment of Medical Oncology, Dana-Farber Cancer Institute & Harvard Medical School, Boston, MA.ORCID 0000-0003-1069-0407
Emma HillDepartment of Medical Oncology, Dana-Farber Cancer Institute & Harvard Medical School, Boston, MA.
Connor HennesseyDepartment of Medical Oncology, Dana-Farber Cancer Institute & Harvard Medical School, Boston, MA.ORCID 0000-0002-5579-1220
Margaret CusickDepartment of Medical Oncology, Dana-Farber Cancer Institute & Harvard Medical School, Boston, MA.
Catherine Del Vecchio FitzDepartment of Data Science, Dana-Farber Cancer Institute, Boston, MA.ORCID 0000-0002-9554-411X
Zachary ZwieslerDepartment of Data Science, Dana-Farber Cancer Institute, Boston, MA.
Ethan SiegelDepartment of Data Science, Dana-Farber Cancer Institute, Boston, MA.ORCID 0000-0003-4333-3510
Andrea OvalleDepartment of Data Science, Dana-Farber Cancer Institute, Boston, MA.
Pavel TrukhanovDepartment of Data Science, Dana-Farber Cancer Institute, Boston, MA.ORCID 0000-0002-4942-5451
Jason HanselDepartment of Data Science, Dana-Farber Cancer Institute, Boston, MA.
Geoffrey I ShapiroDepartment of Medical Oncology, Dana-Farber Cancer Institute & Harvard Medical School, Boston, MA.ORCID 0000-0002-3331-4095
Thomas A AbramsDepartment of Medical Oncology, Dana-Farber Cancer Institute & Harvard Medical School, Boston, MA.ORCID 0000-0003-3101-1573
Leah H BillerDepartment of Medical Oncology, Dana-Farber Cancer Institute & Harvard Medical School, Boston, MA.
Jennifer A ChanDepartment of Medical Oncology, Dana-Farber Cancer Institute & Harvard Medical School, Boston, MA.
James M ClearyDepartment of Medical Oncology, Dana-Farber Cancer Institute & Harvard Medical School, Boston, MA.ORCID 0000-0001-7213-3951
Steven M CorselloDepartment of Medical Oncology, Dana-Farber Cancer Institute & Harvard Medical School, Boston, MA.ORCID 0000-0002-9929-3709
Andrea C EnzingerDepartment of Medical Oncology, Dana-Farber Cancer Institute & Harvard Medical School, Boston, MA.ORCID 0000-0001-7502-8081
Peter C EnzingerDepartment of Medical Oncology, Dana-Farber Cancer Institute & Harvard Medical School, Boston, MA.
Robert J MayerDepartment of Medical Oncology, Dana-Farber Cancer Institute & Harvard Medical School, Boston, MA.
Nadine J McClearyDepartment of Medical Oncology, Dana-Farber Cancer Institute & Harvard Medical School, Boston, MA.ORCID 0000-0003-2377-8301
Jeffrey A MeyerhardtDepartment of Medical Oncology, Dana-Farber Cancer Institute & Harvard Medical School, Boston, MA.ORCID 0000-0002-1120-0898
Kimmie NgDepartment of Medical Oncology, Dana-Farber Cancer Institute & Harvard Medical School, Boston, MA.ORCID 0000-0003-0631-1494
Anuj K PatelDepartment of Medical Oncology, Dana-Farber Cancer Institute & Harvard Medical School, Boston, MA.ORCID 0000-0002-7045-6957
Kimberley J PerezDepartment of Medical Oncology, Dana-Farber Cancer Institute & Harvard Medical School, Boston, MA.ORCID 0000-0002-5745-2994
Osama E RahmaDepartment of Medical Oncology, Dana-Farber Cancer Institute & Harvard Medical School, Boston, MA.ORCID 0000-0001-7302-5805
Douglas A RubinsonDepartment of Medical Oncology, Dana-Farber Cancer Institute & Harvard Medical School, Boston, MA.
Jeffrey S WischDepartment of Medical Oncology, Dana-Farber Cancer Institute & Harvard Medical School, Boston, MA.
Matthew B YurgelunDepartment of Medical Oncology, Dana-Farber Cancer Institute & Harvard Medical School, Boston, MA.ORCID 0000-0002-6184-9273
Michael J HassettDepartment of Medical Oncology, Dana-Farber Cancer Institute & Harvard Medical School, Boston, MA.ORCID 0000-0003-0754-3510
Laura MacConaillCenter for Advanced Molecular Diagnostics, Brigham & Women's Hospital & Harvard Medical School, Boston, MA.ORCID 0000-0002-0220-4715
Deborah SchragDepartment of Medical Oncology, Dana-Farber Cancer Institute & Harvard Medical School, Boston, MA.
Ethan CeramiDepartment of Data Science, Dana-Farber Cancer Institute, Boston, MA.
Brian M WolpinDepartment of Medical Oncology, Dana-Farber Cancer Institute & Harvard Medical School, Boston, MA.ORCID 0000-0002-0455-1032
Jonathan A NowakCenter for Advanced Molecular Diagnostics, Brigham & Women's Hospital & Harvard Medical School, Boston, MA.ORCID 0000-0002-0943-7407
Marios GiannakisDepartment of Medical Oncology, Dana-Farber Cancer Institute & Harvard Medical School, Boston, MA.ORCID 0000-0001-9012-6982

Funding

Integration of early genetic alterations and inflammation in gastroesophageal premalignancyK08DK120930 · NIDDK · DANA-FARBER CANCER INST · PI SETHI, NILAY · 2019 to 2023
$790k
NIDDK NIH HHS K08 DK120930
6 · The paper itself

Abstract

purposeWith the growing number of available targeted therapeutics and molecular biomarkers, the optimal care of patients with cancer now depends on a comprehensive understanding of the rapidly evolving landscape of precision oncology, which can be challenging for oncologists to navigate alone.

methodsWe developed and implemented a precision oncology decision support system, GI TARGET, (Gastrointestinal Treatment Assistance Regarding Genomic Evaluation of Tumors) within the Gastrointestinal Cancer Center at the Dana-Farber Cancer Institute. With a multidisciplinary team, we systematically reviewed tumor molecular profiling for GI tumors and provided molecularly informed clinical recommendations, which included identifying appropriate clinical trials aided by the computational matching platform MatchMiner, suggesting targeted therapy options on or off the US Food and Drug Administration-approved label, and consideration of additional or orthogonal molecular testing.

resultsWe reviewed genomic data and provided clinical recommendations for 506 patients with GI cancer who underwent tumor molecular profiling between January and June 2019 and determined follow-up using the electronic health record. Summary reports were provided to 19 medical oncologists for patients with colorectal (n = 198, 39%), pancreatic (n = 124, 24%), esophagogastric (n = 67, 13%), biliary (n = 40, 8%), and other GI cancers. We recommended ≥ 1 precision medicine clinical trial for 80% (406 of 506) of patients, leading to 24 enrollments. We recommended on-label and off-label targeted therapies for 6% (28 of 506) and 25% (125 of 506) of patients, respectively. Recommendations for additional or orthogonal testing were made for 42% (211 of 506) of patients.

conclusionThe integration of precision medicine in routine cancer care through a dedicated multidisciplinary molecular tumor board is scalable and sustainable, and implementation of precision oncology recommendations has clinical utility for patients with cancer.

Indexed as

Gastrointestinal NeoplasmsPrecision MedicineGenomicsHumansMedical OncologyMolecular Diagnostic Techniques

Identifiers

PMID36634297
PMCPMC9929103

What OpenQuestion holds

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LicenceCC BY
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Registered trials

None linked

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.