Evidence map›Paper›PMID 20589539›Full record

ReviewMedical oncology (Northwood, London, England)2011

An eight-year snapshot of geospatial cancer research (2002-2009): clinico-epidemiological and methodological findings and trends.

Dina N Kamel Boulos, Ramy R Ghali, Ezzeldin M Ibrahim, Maged N Kamel Boulos, Philip AbdelMalik

Abstract readReview
PubMed Publisher
In one paragraph

Review in Medical oncology (Northwood, London, England), 2011. 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. Contribution of Geographic Location to Disparities in Ovarian Cancer Treatment.Journal of the National Comprehensive Cancer Network : JNCCN · 2019
    Article
  4. Article
  5. Geospatial and Temporal Analysis of Thyroid Cancer Incidence in a Rural Population.Thyroid : official journal of the American Thyroid Association · 2015
    Article
  6. Article
  7. Article
  8. Who does not receive treatment for cancer?Journal of oncology practice · 2013
    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

5 authors.

Dina N Kamel BoulosDepartment of Community, Environmental and Occupational Medicine, Faculty of Medicine, Ain Shams University, Abbassia, Cairo, Egypt.
Ramy R Ghali
Ezzeldin M Ibrahim
Maged N Kamel Boulos
Philip AbdelMalik

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Geographic information systems (GIS) offer a very rich toolbox of methods and technologies, and powerful research tools that extend far beyond the mere production of maps, making it possible to cross-link and study the complex interaction of disease data and factors originating from a wide range of disparate sources. Despite their potential indispensable role in cancer prevention and control programmes, GIS are underrepresented in specialised oncology literature. The latter has provided an impetus for the current review. The review provides an eight-year snapshot of geospatial cancer research in peer-reviewed literature (2002-2009), presenting the clinico-epidemiological and methodological findings and trends in the covered corpus (93 papers). The authors concluded that understanding the relationship between location and cancer/cancer care services can play a crucial role in disease control and prevention, and in better service planning, and appropriate resource utilisation. Nevertheless, there are still barriers that hinder the wide-scale adoption of GIS and related technologies in everyday oncology practice.

Indexed as

Geographic Information SystemsHumansNeoplasms

Identifiers

What OpenQuestion holds

Textmetadata
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.