Evidence map›Paper›PMID 37370865›Full record

ArticleCancers2023

Relevance of the Updated Recursive Partitioning Analysis (U-RPA) Classification in the Contemporary Care of Patients with Brain Metastases.

Camilo E Fadul, Guneet Sarai, Joseph A Bovi, Alissa A Thomas, Wendy Novicoff, Roger Anderson, Ryan F Amidon, Samantha Schuetz, Rohit Singh, Amy Chang and 3 more

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Cancers, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing 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

6 citing papers in PubMed.

  1. Article
  2. Review
  3. Article
  4. Article
  5. Article
  6. The role of microRNAs in brain metastasis.Journal of neuro-oncology · 2024
    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

13 authors.

Camilo E FadulDivision of Neuro-Oncology, Department of Neurology, University of Virginia School of Medicine, Charlottesville, VA 22908, USA.ORCID 0000-0001-7459-7661
Guneet SaraiDivision of Neuro-Oncology, Department of Neurology, University of Virginia School of Medicine, Charlottesville, VA 22908, USA.
Joseph A BoviDepartment of Radiation Oncology, The Medical College of Wisconsin, Milwaukee, WI 53222, USA.
Alissa A ThomasDepartment of Neurological Sciences, University of Vermont Larner College of Medicine, Burlington, VT 05405, USA.
Wendy NovicoffDepartment of Public Health Sciences and Orthopedic Surgery, University of Virginia School of Medicine, Charlottesville, VA 22908, USA.
Roger AndersonPopulation Sciences, University of Virginia School of Medicine, Charlottesville, VA 22908, USA.
Ryan F AmidonDepartment of Radiation Oncology, The Medical College of Wisconsin, Milwaukee, WI 53222, USA.ORCID 0000-0002-3857-2667
Samantha SchuetzDepartment of Neurological Sciences, University of Vermont Larner College of Medicine, Burlington, VT 05405, USA.
Rohit SinghDivision of Hematology and Oncology, University of Vermont Larner College of Medicine, Burlington, VT 05405, USA.ORCID 0000-0003-2740-9386
Amy ChangDepartment of Neurological Sciences, University of Vermont Larner College of Medicine, Burlington, VT 05405, USA.
Ryan D GentzlerDivision of Hematology and Oncology, Department of Medicine, University of Virginia School of Medicine, Charlottesville, VA 22908, USA.
Elizabeth M GaughanDivision of Hematology and Oncology, Department of Medicine, University of Virginia School of Medicine, Charlottesville, VA 22908, USA.
Jason P SheehanDepartment of Neurological Surgery, University of Virginia School of Medicine, Charlottesville, VA 22908, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Patients with brain metastases (BMETS) need information about the prognosis and potential value of treatment options to make informed therapeutic decisions, but tools to predict survival in contemporary practice are scarce. We propose an Updated Recursive Partitioning Analysis (U-RPA) instrument to predict survival and benefit from brain-directed treatment (BDT) of contemporary patients. This was a retrospective analysis of patients with BMETS treated between 2017 and 2019. With survival as the primary endpoint, we calculated the U-RPA and generated estimates using Kaplan-Meier curves and hazard ratios. Of 862 eligible patients, 752 received BDT and 110 received best supportive care (BSC). Median overall survival with BDT and BSC was 9.3 and 1.3 months, respectively. Patients in RPA class 1, 2A, 2B and 3 who underwent BDT had median survival of 28.1, 14.7, 7.6 and 3.3 months, respectively. The median survival for patients in RPA 3 who received BDT (

Indexed as

brain-directed treatmentbrain metastasesKarnofsky performance statusprognosisrecursive partitioning analysisstereotactic radiosurgerywhole brain radiation therapy

Identifiers

PMID37370865
PMCPMC10297002

What OpenQuestion holds

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Registered trials

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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.