Evidence map›Paper›PMID 32719846›Full record

ArticleDatabase : the journal of biological databases and curation2020

OPTIK: a database for understanding catchment areas to guide mobilization of cancer center assets.

Dinesh Pal Mudaranthakam, Lisa M Harlan-Williams, Roy A Jensen, Hanluen Kuo, Vandita Garimella, Ronald C Chen, Matthew S Mayo, Hope Krebill

Abstract read
In one paragraph

Article in Database : the journal of biological databases and curation, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing 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

9 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. A National Map of NCI-Designated Cancer Center Catchment Areas on the 50th Anniversary of the Cancer Centers Program.Cancer epidemiology, biomarkers & prevention : a publication of the American Association for Cancer Research, cosponsored by the American Society of Preventive Oncology · 2022
    Article
  8. 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

8 authors.

Dinesh Pal MudaranthakamDepartment of Biostatistics & Data Science, University of Kansas Medical Center, Mail Stop 1026, 3901 Rainbow Blvd., Kansas City, KS 66160 USA.
Lisa M Harlan-WilliamsThe University of Kansas Cancer Center, University of Kansas Medical Center, 3901 Rainbow Blvd., Kansas City, KS 66160 USA.
Roy A JensenThe University of Kansas Cancer Center, University of Kansas Medical Center, 3901 Rainbow Blvd., Kansas City, KS 66160 USA.
Hanluen KuoThe University of Kansas Cancer Center, University of Kansas Medical Center, 3901 Rainbow Blvd., Kansas City, KS 66160 USA.
Vandita GarimellaDepartment of Biostatistics & Data Science, University of Kansas Medical Center, Mail Stop 1026, 3901 Rainbow Blvd., Kansas City, KS 66160 USA.
Ronald C ChenThe University of Kansas Cancer Center, University of Kansas Medical Center, 3901 Rainbow Blvd., Kansas City, KS 66160 USA.
Matthew S MayoDepartment of Biostatistics & Data Science, University of Kansas Medical Center, Mail Stop 1026, 3901 Rainbow Blvd., Kansas City, KS 66160 USA.
Hope KrebillThe University of Kansas Cancer Center, University of Kansas Medical Center, 3901 Rainbow Blvd., Kansas City, KS 66160 USA.

Funding

Transgenic & Gene-Targeting Shared ResourceP30CA168524 · NCI · UNIVERSITY OF KANSAS MEDICAL CENTER · PI ROY A. JENSEN · 2012 to 2026
$40.1M
NCI NIH HHS P30 CA168524
6 · The paper itself

Abstract

An increasingly diversified demographic landscape in rural and urban America warrants the attention of The University of Kansas Cancer Center (KU Cancer Center) researchers, clinicians, outreach staff and administrators as the institution assesses ways to reach its expansive, bi-state catchment area. Within the counties of the KU Cancer Center catchment area, patient level and public health data are available and categorized by varying geographic regional boundaries. Multiple data sources and different data collection processes complicate summarizing catchment area data. A curated data warehouse that retrieves and structures the data, with a common denominator, can support meaningful use of the data in a standard and consistent format. The KU Cancer Center built a data warehouse to Organize and Prioritize Trends to Inform KU Cancer Center (OPTIK), which functions to streamline the process of synthesizing data regarding Kansas and Missouri demographics, cancer risk factors and incidence and mortality rates. OPTIK standardizes these diverse data sources to enable analyses of the cancer burden at local, regional and national levels while upholding a strict standard of patient privacy. The OPTIK database enables researchers to use available data and create heat maps and other visualizations to aid in funding proposals, presentations and research activities. Furthermore, using knowledge provided by OPTIK, the KU Cancer Center is able to prioritize action items for research and outreach and more effectively communicate the impact of those efforts.

Indexed as

Cancer Care FacilitiesCatchment Area, HealthDatabases, FactualData VisualizationNeoplasmsHumans

Identifiers

PMID32719846
PMCPMC7491207

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.