Evidence map›Paper›PMID 18682893›Full record

ArticleJournal of neuro-oncology2008

Low-grade gliomas in older patients: a retrospective analysis of prognostic factors.

Nader Pouratian, Melike Mut, Jay Jagannathan, M Beatriz Lopes, Mark E Shaffrey, David Schiff

Abstract read
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In one paragraph

Article in Journal of neuro-oncology, 2008. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.

0numbers the graph read from it
0cells of the map it votes in
14citing 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

14 citing papers in PubMed.

  1. Article
  2. Review
  3. Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. Prognosis of older patients with low-grade glioma: A retrospective study.Integrative cancer science and therapeutics · 2017
    Article
  9. Review
  10. Review
  11. Management of low-grade glioma.Current neurology and neuroscience reports · 2010
    Review
  12. Article
  13. Article
  14. Low-grade gliomas.Current treatment options in oncology · 2009
    Review
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

6 authors.

Nader PouratianDepartment of Neurological Surgery, University of Virginia, Box 800212, Charlottesville, VA 22908-0212, USA. np5k@virginia.edu
Melike Mut
Jay Jagannathan
M Beatriz Lopes
Mark E Shaffrey
David Schiff

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Low-grade gliomas (LGG) are increasingly being diagnosed in older patients (>or=60 years). The rising incidence is incompletely understood but demands an analysis of the natural history and prognostic factors to determine if there are differences compared to younger populations. We retrospectively review a consecutive series of 20 older patients who presented between 1991 and 2004 with LGG to characterize the presentation, management, outcomes, and prognostic factors in older patients with LGG. Median follow-up was 27.3 months. Thirty-five percent of patients harboured oligodendrogliomas. Patients presented in equal numbers with seizure, focal neurological deficit, and mental status change. Median overall survival (OS) was 27.3 months. Patients who survive beyond 2 years experience prolonged periods of progression-free survival. Younger age, seizure presentation, and radiation treatment were prognostic of OS on multivariate analysis. Similarities with previous reports of LGG suggest that age should not affect the management of LGG patients. Prospective studies of older patients with LGG are needed to further characterize the optimum management of these patients.

Indexed as

GeriatricsAgedAged, 80 and overFemaleFollow-Up StudiesGliomaHumansMaleMiddle AgedPrognosisRetrospective StudiesSurvival Analysis

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.