Evidence map›Paper›PMID 29420224›Full record

ReviewClinical cancer research : an official journal of the American Association for Cancer Research2018

Precision Oncology Decision Support: Current Approaches and Strategies for the Future.

Katherine C Kurnit, Ecaterina E Ileana Dumbrava, Beate Litzenburger, Yekaterina B Khotskaya, Amber M Johnson, Timothy A Yap, Jordi Rodon, Jia Zeng, Md Abu Shufean, Ann M Bailey and 7 more

Abstract readReview
In one paragraph

Review in Clinical cancer research : an official journal of the American Association for Cancer Research, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 37 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
37citing 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

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

  1. Pooled it
  2. Review
  3. Article
  4. Review
  5. Utilizing Patient-Derived Xenografts to Model Precision Oncology for Biliary Tract Cancer.Clinical cancer research : an official journal of the American Association for Cancer Research · 2025
    Article
  6. Review
  7. Article
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  20. Genomic, Transcriptomic, and Proteomic Profiling of Metastatic Breast Cancer.Clinical cancer research : an official journal of the American Association for Cancer Research · 2021
    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

17 authors.

Katherine C KurnitGynecologic Oncology and Reproductive Medicine, The University of Texas MD Anderson Cancer Center, Houston, Texas.
Ecaterina E Ileana DumbravaInvestigational Cancer Therapeutics, The University of Texas MD Anderson Cancer Center, Houston, Texas.
Beate LitzenburgerSheikh Khalifa Bin Zayed Al Nahyan Institute for Personalized Cancer Therapy, The University of Texas MD Anderson Cancer Center, Houston, Texas.
Yekaterina B KhotskayaSheikh Khalifa Bin Zayed Al Nahyan Institute for Personalized Cancer Therapy, The University of Texas MD Anderson Cancer Center, Houston, Texas.
Amber M JohnsonSheikh Khalifa Bin Zayed Al Nahyan Institute for Personalized Cancer Therapy, The University of Texas MD Anderson Cancer Center, Houston, Texas.
Timothy A YapInvestigational Cancer Therapeutics, The University of Texas MD Anderson Cancer Center, Houston, Texas.
Jordi RodonInvestigational Cancer Therapeutics, The University of Texas MD Anderson Cancer Center, Houston, Texas.
Jia ZengSheikh Khalifa Bin Zayed Al Nahyan Institute for Personalized Cancer Therapy, The University of Texas MD Anderson Cancer Center, Houston, Texas.
Md Abu ShufeanSheikh Khalifa Bin Zayed Al Nahyan Institute for Personalized Cancer Therapy, The University of Texas MD Anderson Cancer Center, Houston, Texas.
Ann M BaileySheikh Khalifa Bin Zayed Al Nahyan Institute for Personalized Cancer Therapy, The University of Texas MD Anderson Cancer Center, Houston, Texas.
Nora S SánchezSheikh Khalifa Bin Zayed Al Nahyan Institute for Personalized Cancer Therapy, The University of Texas MD Anderson Cancer Center, Houston, Texas.
Vijaykumar HollaSheikh Khalifa Bin Zayed Al Nahyan Institute for Personalized Cancer Therapy, The University of Texas MD Anderson Cancer Center, Houston, Texas.
John MendelsohnSheikh Khalifa Bin Zayed Al Nahyan Institute for Personalized Cancer Therapy, The University of Texas MD Anderson Cancer Center, Houston, Texas.
Kenna Mills ShawSheikh Khalifa Bin Zayed Al Nahyan Institute for Personalized Cancer Therapy, The University of Texas MD Anderson Cancer Center, Houston, Texas.
Elmer V BernstamSchool of Biomedical Informatics and Medical School, The University of Texas Health Science Center at Houston, Houston, Texas.
Gordon B MillsSheikh Khalifa Bin Zayed Al Nahyan Institute for Personalized Cancer Therapy, The University of Texas MD Anderson Cancer Center, Houston, Texas.
Funda Meric-BernstamInvestigational Cancer Therapeutics, The University of Texas MD Anderson Cancer Center, Houston, Texas. fmeric@mdanderson.org.

Funding

Tumor Evolution and Metastasis ProgramP30CA016672 · NCI · UNIVERSITY OF TX MD ANDERSON CAN CTR · PI Fabien Delerue · 1985 to 2026
$290.8M
Center for Clinical and Translational Sciences (CCTS)UL1TR000371 · NCATS · UNIVERSITY OF TEXAS HLTH SCI CTR HOUSTON · PI MCPHERSON, DAVID D · 2012 to 2016
$13.4M
Training of Academic Gynecologic OncologistsT32CA101642 · NCI · UNIVERSITY OF TX MD ANDERSON CAN CTR · PI ANIL K SOOD, Kathleen Schmeler · 2005 to 2026
$9.2M
Informatics to enable routine personalized cancer therapyU01CA180964 · NCI · UNIVERSITY OF TEXAS HLTH SCI CTR HOUSTON · PI BERNSTAM, ELMER V., MERIC-BERNSTAM, FUNDA · 2013 to 2015
$964k
NCATS NIH HHS UL1 TR000371NCI NIH HHS P30 CA016672NCI NIH HHS T32 CA101642NCI NIH HHS U01 CA180964
6 · The paper itself

Abstract

With the increasing availability of genomics, routine analysis of advanced cancers is now feasible. Treatment selection is frequently guided by the molecular characteristics of a patient's tumor, and an increasing number of trials are genomically selected. Furthermore, multiple studies have demonstrated the benefit of therapies that are chosen based upon the molecular profile of a tumor. However, the rapid evolution of genomic testing platforms and emergence of new technologies make interpreting molecular testing reports more challenging. More sophisticated precision oncology decision support services are essential. This review outlines existing tools available for health care providers and precision oncology teams and highlights strategies for optimizing decision support. Specific attention is given to the assays currently available for molecular testing, as well as considerations for interpreting alteration information. This article also discusses strategies for identifying and matching patients to clinical trials, current challenges, and proposals for future development of precision oncology decision support.

Indexed as

Decision Support Systems, ClinicalMedical OncologyPrecision MedicineBiomarkers, TumorClinical Trials as TopicComputational BiologyDecision TreesDisease ManagementDisease SusceptibilityGenetic Predisposition to DiseaseGenetic TestingGenomicsHumansMolecular Diagnostic TechniquesMolecular Targeted TherapyNeoplasmsBiomarkers, Tumor

Identifiers

PMID29420224
PMCPMC6004235

What OpenQuestion holds

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Read underepoch 390

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.