Evidence map›Paper›PMID 30460629›Full record

ArticleJournal of neuro-oncology2019

The impact of traveling distance and hospital volume on post-surgical outcomes for patients with glioblastoma.

Christian Lopez Ramos, Michael G Brandel, Jeffrey A Steinberg, Arvin R Wali, Robert C Rennert, David R Santiago-Dieppa, Reith R Sarkar, J Scott Pannell, James D Murphy, Alexander A Khalessi

Abstract read
PubMed Publisher
In one paragraph

Article in Journal of neuro-oncology, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 25 papers.

0numbers the graph read from it
0cells of the map it votes in
25citing papers in PubMed
2.8field-weighted citation impact, top 9% of its field
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

25 citing papers in PubMed, 48 citations in OpenAlex.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. Review
  8. Article
  9. Association of area deprivation index (ADI) with demographics and postoperative outcomes in pediatric brain tumor patients.Child's nervous system : ChNS : official journal of the International Society for Pediatric Neurosurgery · 2024
    Observational
  10. Article
  11. Article
  12. Article
  13. Article
  14. Article
  15. Article
  16. Article
  17. Article
  18. Article
  19. Article
  20. Observational
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

10 authors at 1 institution in 1 country.

Christian Lopez RamosDepartment of Neurosurgery, University of California, San Diego, La Jolla, CA, USA.ORCID http://orcid.org/0000-0002-5832-4046
Michael G BrandelDepartment of Neurosurgery, University of California, San Diego, La Jolla, CA, USA.
Jeffrey A SteinbergDepartment of Neurosurgery, University of California, San Diego, La Jolla, CA, USA.
Arvin R WaliDepartment of Neurosurgery, University of California, San Diego, La Jolla, CA, USA.
Robert C RennertDepartment of Neurosurgery, University of California, San Diego, La Jolla, CA, USA.
David R Santiago-DieppaDepartment of Neurosurgery, University of California, San Diego, La Jolla, CA, USA.
Reith R SarkarDepartment of Radiation Medicine and Applied Sciences, University of California, San Diego, La Jolla, CA, USA.
J Scott PannellDepartment of Neurosurgery, University of California, San Diego, La Jolla, CA, USA.
James D MurphyDepartment of Radiation Medicine and Applied Sciences, University of California, San Diego, La Jolla, CA, USA.
Alexander A KhalessiDepartment of Neurosurgery, University of California, San Diego, La Jolla, CA, USA. akhalessi@ucsd.edu.
University of California San Diego · US

Funding

National Institutes of Health TL1TR001443
6 · The paper itself

Abstract

backgroundHigh-volume hospitals are associated with improved outcomes in glioblastoma (GBM). However, the impact of travel burden to high-volume centers is poorly understood. We examined post-operative outcomes between GBM patients that underwent treatment at local, low-volume hospitals with those that traveled long distances to high-volume hospitals.

methodsThe National Cancer Database was queried for GBM patients that underwent surgery (2010-2014). We established two cohorts: patients in the lowest quartile of travel distance and volume (Short-travel/Low-Volume: STLV) and patients in the highest quartile of travel and volume (Long-travel/High-Volume: LTHV). Outcomes analyzed were 30-day, 90-day mortality, overall survival, 30-day readmission, and hospital length of stay.

resultsOf 35,529 cases, STLV patients (n = 3414) traveled a median of 3 miles (Interquartile range [IQR] 1.8-4.2) to low-volume centers (5 [3-7] annual cases) and LTHV patients (n = 3808) traveled a median of 62 miles [44.1-111.3] to high-volume centers (48 [42-71]). LTHV patients were younger, had lower Charlson scores, largely received care at academic centers (84.4% vs 11.9%), were less likely to be minorities (8.1% vs 17.1%) or underinsured (6.9% vs 12.1), and were more likely to receive trimodality therapy (75.6% vs 69.2%; all p < 0.001). On adjusted analysis, LTHV predicted improved overall survival (HR 0.87, p = 0.002), decreased 90-day mortality (OR 0.72, p = 0.019), lower 30-day readmission (OR 0.42, p < 0.001), and shorter hospitalizations (RR 0.79, p < 0.001).

conclusionsGlioblastoma patients who travel farther to high-volume centers have superior post-operative outcomes compared to patients who receive treatment locally at low-volume centers. Strategies that facilitate patient travel to high-volume hospitals may improve outcomes.

Indexed as

Health Services AccessibilityAgedBrain NeoplasmsFemaleGlioblastomaHospitals, High-VolumeHospitals, Low-VolumeHumansKaplan-Meier EstimateMaleMiddle AgedPostoperative PeriodTravelTreatment OutcomeGlioblastomaHospital volumeOutcomesSurvivalTravel distance

Identifiers

PMID30460629
OpenAlexW2901808559

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.