Evidence map›Paper›PMID 23105966›Full record

ArticleJournal of comparative effectiveness research2012

Prioritizing comparative effectiveness research for cancer diagnostics using a regional stakeholder approach.

Gregory Klein, Laura S Gold, Sean D Sullivan, Diana S M Buist, Scott Ramsey, Karma Kreizenbeck, Kyle Snell, Elizabeth Trice Loggers, Joseph Gifford, John B Watkins and 1 more

Abstract read
In one paragraph

Article in Journal of comparative effectiveness research, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing 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

6 citing papers in PubMed.

  1. Article
  2. Article
  3. Querying stakeholders to inform comparative effectiveness research.Journal of comparative effectiveness research · 2017
    Article
  4. A blood screening test for Alzheimer's disease.Alzheimer's & dementia (Amsterdam, Netherlands) · 2016
    Article
  5. Predictors of preoperative MRI for breast cancer: differences by data source.Journal of comparative effectiveness research · 2015
    Article
  6. 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

11 authors.

Gregory Klein
Laura S Gold
Sean D Sullivan
Diana S M Buist
Scott Ramsey
Karma Kreizenbeck
Kyle Snell
Elizabeth Trice Loggers
Joseph Gifford
John B Watkins
Larry Kessler

Funding

Risk-based Imaging Strategies to Improve Breast Cancer Surveillance OutcomesP01CA154292 · NCI · UNIVERSITY OF CALIFORNIA AT DAVIS · PI Diana L Miglioretti · 2011 to 2026
$52.9M
ADVancing Innovative Comparative Effectiveness research-cancer diagnostics ADVICERC2CA148433 · NCI · UNIVERSITY OF WASHINGTON · PI KESSLER, LARRY G, SULLIVAN, SEAN D · 2009 to 2009
$2.0M
ADVancing Innovative Comparative Effectiveness research-cancer diagnostics ADVICEUC2CA148433 · NCI · UNIVERSITY OF WASHINGTON · PI KESSLER, LARRY G, SULLIVAN, SEAN D · 2010 to 2010
$2.0M
NCI NIH HHS 1RC2CA148433-01NCI NIH HHS P01 CA154292NCI NIH HHS RC2 CA148433NCI NIH HHS UC2 CA148433
6 · The paper itself

Abstract

aimsThis paper describes our process to engage regional stakeholders for prioritizing comparative effectiveness research (CER) in cancer diagnostics. We also describe a novel methodology for incorporating stakeholder data and input to inform the objectives of selected CER studies. MATERIALS &

methodsAs an integrated component to establishing the infrastructure for community-based CER on diagnostic technologies, we have assembled a regional stakeholder group composed of local payers, clinicians and state healthcare representatives to not only identify and prioritize CER topics most important to the western Washington State region, but also to inform the study design of selected research areas. A landscape analysis process combining literature searches, expert consultations and stakeholder discussions was used to identify possible CER topics in cancer diagnostics. Stakeholders prioritized the top topics using a modified Delphi/group-nominal method and a standardized evaluation criteria framework to determine a final selected CER study area. Implementation of the selected study was immediate due to a unique American Recovery and Reinvestment Act funding structure involving the same researchers and stakeholders in both the prioritization and execution phases of the project. Stakeholder engagement was enhanced after study selection via a rapid analysis of a subset of payers' internal claims, coordinated by the research team, to obtain summary data of imaging patterns of use. Results of this preliminary analysis, which we termed an 'internal analysis,' were used to determine with the stakeholders the most important and feasible study objectives.

resultsStakeholders identified PET and MRI in cancers including breast, lung, lymphoma and colorectal as top priorities. In an internal analysis of breast cancer imaging, summary data from three payers demonstrated utilization rates of advanced imaging increased between 2002 and 2009 in the study population, with a great deal of variability in use between different health plans. Assessing whether breast MRI affects treatment decisions was the top breast cancer study objective selected by the stakeholders. There were other high-priority research areas including whether MRI use improved survival that were not deemed feasible with the length of follow-up time following MRI adoption.

conclusionContinuous stakeholder engagement greatly enhanced their enthusiasm for the project. We believe CER implementation will be more successful when undertaken by regional stakeholders.

Indexed as

Comparative Effectiveness ResearchHealth PlanningBreast NeoplasmsDelivery of Health Care, IntegratedFinancial ManagementHumansMagnetic Resonance ImagingNeoplasmsPositron-Emission TomographyTomography, X-Ray ComputedWashington

Identifiers

PMID23105966
PMCPMC3480224

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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.