Evidence map›Paper›PMID 25195986›Full record

ReviewInternational journal of radiation oncology, biology, physics2014

Considerations for observational research using large data sets in radiation oncology.

Reshma Jagsi, Justin E Bekelman, Aileen Chen, Ronald C Chen, Karen Hoffman, Ya-Chen Tina Shih, Benjamin D Smith, James B Yu

Abstract readReview
In one paragraph

Review in International journal of radiation oncology, biology, physics, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 33 papers.

0numbers the graph read from it
0cells of the map it votes in
33citing 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

33 citing papers in PubMed.

  1. Trial
  2. Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. Contracture Severity at Hospital Discharge in Children: A Burn Model System Database Study.Journal of burn care & research : official publication of the American Burn Association · 2021
    Article
  8. Observational
  9. Article
  10. Article
  11. Article
  12. Article
  13. An Overview of Lung and Breast Cancer Using the National Cancer Database.Asian Pacific journal of cancer prevention : APJCP · 2020
    Article
  14. Article
  15. Article
  16. Observational
  17. Review
  18. Review
  19. Review
  20. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

8 authors.

Reshma JagsiDepartment of Radiation Oncology, University of Michigan, Ann Arbor, Michigan. Electronic address: rjagsi@med.umich.edu.
Justin E BekelmanDepartments of Radiation Oncology and Medical Ethics and Health Policy, University of Pennsylvania Perelman School of Medicine, Philadelphia, Pennsylvania.
Aileen ChenDepartment of Radiation Oncology, Harvard Medical School, Boston, Massachusetts.
Ronald C ChenDepartment of Radiation Oncology, University of North Carolina at Chapel Hill School of Medicine, Chapel Hill, North Carolina.
Karen HoffmanDepartment of Radiation Oncology, Division of Radiation Oncology, The University of Texas MD Anderson Cancer Center, Houston, Texas.
Ya-Chen Tina ShihDepartment of Medicine, Section of Hospital Medicine, The University of Chicago, Chicago, Illinois.
Benjamin D SmithDepartment of Radiation Oncology, Division of Radiation Oncology, and Department of Health Services Research, The University of Texas MD Anderson Cancer Center, Houston, Texas.
James B YuYale School of Medicine, New Haven, Connecticut.

Funding

Innovative methods for modeling longitudianl medical costsR01HS020263 · AHRQ · UNIVERSITY OF VIRGINIA · PI LIU, LEI · 2011 to 2015
$2.0M
Monoclonal Antibodies in Cancer Care: Is Underinsurance An Access Barrier?R01HS018535 · AHRQ · UNIVERSITY OF TX MD ANDERSON CAN CTR · PI SHIH, YA-CHEN TINA · 2009 to 2012
$1.4M
Effectiveness of Radiotherapy for Prostate CancerK07CA163616 · NCI · UNIVERSITY OF PENNSYLVANIA · PI BEKELMAN, JUSTIN · 2012 to 2016
$875k
Technology Diffusion & Cost-Effectiveness of Mammography Screening in Older WomenR21CA165092 · NCI · UNIVERSITY OF TX MD ANDERSON CAN CTR · PI SHEN, YU, SHIH, YA-CHEN TINA · 2011 to 2012
$395k
AHRQ HHS R01 HS020263NCI NIH HHS K07 CA163616NCI NIH HHS K07-CA163616NCI NIH HHS R21 CA165092NCI NIH HHS R21CA165092
6 · The paper itself

Abstract

The radiation oncology community has witnessed growing interest in observational research conducted using large-scale data sources such as registries and claims-based data sets. With the growing emphasis on observational analyses in health care, the radiation oncology community must possess a sophisticated understanding of the methodological considerations of such studies in order to evaluate evidence appropriately to guide practice and policy. Because observational research has unique features that distinguish it from clinical trials and other forms of traditional radiation oncology research, the International Journal of Radiation Oncology, Biology, Physics assembled a panel of experts in health services research to provide a concise and well-referenced review, intended to be informative for the lay reader, as well as for scholars who wish to embark on such research without prior experience. This review begins by discussing the types of research questions relevant to radiation oncology that large-scale databases may help illuminate. It then describes major potential data sources for such endeavors, including information regarding access and insights regarding the strengths and limitations of each. Finally, it provides guidance regarding the analytical challenges that observational studies must confront, along with discussion of the techniques that have been developed to help minimize the impact of certain common analytical issues in observational analysis. Features characterizing a well-designed observational study include clearly defined research questions, careful selection of an appropriate data source, consultation with investigators with relevant methodological expertise, inclusion of sensitivity analyses, caution not to overinterpret small but significant differences, and recognition of limitations when trying to evaluate causality. This review concludes that carefully designed and executed studies using observational data that possess these qualities hold substantial promise for advancing our understanding of many unanswered questions of importance to the field of radiation oncology.

Indexed as

ChecklistDatabases, FactualNeoplasmsRadiation OncologyRegistriesComparative Effectiveness ResearchDiffusion of InnovationHealth Care CostsHealth Services ResearchHealth SurveysInsurance Claim ReviewMedicareNomogramsObservational Studies as TopicProfessional PracticePropensity Score

Identifiers

PMID25195986
PMCPMC4159773

What OpenQuestion holds

Textmetadata
LicenceTDM
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.