Evidence map›Paper›PMID 31603516›Full record

ArticleNeuro-oncology2020

A prognostic model to personalize monitoring regimes for patients with incidental asymptomatic meningiomas.

Abdurrahman I Islim, Ruwanthi Kolamunnage-Dona, Midhun Mohan, Richard D C Moon, Anna Crofton, Brian J Haylock, Nitika Rathi, Andrew R Brodbelt, Samantha J Mills, Michael D Jenkinson

Abstract read
In one paragraph

Article in Neuro-oncology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 51 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
51citing papers in PubMed, 3 pooled it
–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

51 citing papers in PubMed, 3 syntheses or guidelines pooled it.

  1. Pooled it
  2. Pooled it
  3. Guideline
  4. [Frequent neurosurgically treatable diseases in geriatric patients].Zeitschrift fur Gerontologie und Geriatrie · 2026
    Review
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  6. Article
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  8. Article
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  13. Article
  14. Malignant Meningiomas: From Diagnostics to Treatment.Diagnostics (Basel, Switzerland) · 2025
    Review
  15. Article
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  18. Article
  19. Review
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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

10 authors.

Abdurrahman I IslimInstitute of Translational Medicine, University of Liverpool, Liverpool, UK.
Ruwanthi Kolamunnage-DonaInstitute of Translational Medicine, University of Liverpool, Liverpool, UK.
Midhun MohanSchool of Medicine, University of Liverpool, Liverpool, UK.
Richard D C MoonSchool of Medicine, University of Liverpool, Liverpool, UK.
Anna CroftonDepartment of Neurosurgery, The Walton Centre NHS Foundation Trust, Liverpool, UK.
Brian J HaylockDepartment of Clinical Oncology, The Clatterbridge Cancer Centre NHS Foundation Trust, Wirral, UK.
Nitika RathiDepartment of Neuropathology, The Walton Centre NHS Foundation Trust, Liverpool, UK.
Andrew R BrodbeltDepartment of Neurosurgery, The Walton Centre NHS Foundation Trust, Liverpool, UK.
Samantha J MillsDepartment of Neuroradiology, The Walton Centre NHS Foundation Trust, Liverpool, UK.
Michael D JenkinsonInstitute of Translational Medicine, University of Liverpool, Liverpool, UK.

Funding

Department of Health 12/173/14Medical Research Council G0400615Medical Research Council MR/M013227/1
6 · The paper itself

Abstract

backgroundAsymptomatic meningioma is a common incidental finding with no consensus on the optimal management strategy. We aimed to develop a prognostic model to guide personalized monitoring of incidental meningioma patients.

methodsA prognostic model of disease progression was developed in a retrospective cohort (2007-2015), defined as: symptom development, meningioma-specific mortality, meningioma growth or loss of window of curability. Secondary endpoints included non-meningioma-specific mortality and intervention.

resultsIncluded were 441 patients (459 meningiomas). Over a median of 55 months (interquartile range, 37-80), 44 patients had meningioma progression and 57 died (non-meningioma-specific). Forty-four had intervention (at presentation, n = 6; progression, n = 20; nonprogression, n = 18). Model parameters were based on statistical and clinical considerations and included: increasing meningioma volume (hazard ratio [HR] 2.17; 95% CI: 1.53-3.09), meningioma hyperintensity (HR 10.6; 95% CI: 5.39-21.0), peritumoral signal change (HR 1.58; 95% CI: 0.65-3.85), and proximity to critical neurovascular structures (HR 1.38; 95% CI: 0.74-2.56). Patients were stratified based on these imaging parameters into low-, medium- and high-risk groups and 5-year disease progression rates were 3%, 28%, and 75%, respectively. After 5 years of follow-up, the risk of disease progression plateaued in all groups. Patients with an age-adjusted Charlson comorbidity index ≥6 (eg, an 80-year-old with chronic kidney disease) were 15 times more likely to die of other causes than to receive intervention at 5 years following diagnosis, regardless of risk group.

conclusionsThe model shows that there is little benefit to rigorous monitoring in low-risk and older patients with comorbidities. Risk-stratified follow-up has the potential to reduce patient anxiety and associated health care costs.

Indexed as

Decision Support Systems, ClinicalAdultAgedAged, 80 and overClinical Decision-MakingCohort StudiesDisease ProgressionFemaleHumansIncidental FindingsMaleMeningeal NeoplasmsMeningiomaMiddle AgedPrecision MedicinePrognosisasymptomaticincidentalmeningiomaprognosisrisk score

Identifiers

PMID31603516
PMCPMC7032634

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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.