Evidence map›Paper›PMID 25300908›Full record

ReviewJournal of neuro-oncology2015

Mouse models of primary central nervous system lymphomas: tools for basing funding and therapeutic strategies.

Rym Ben Abdelwahed Bagga, Sabrina Donnou, Jérémie Cosette, Catherine Sautès-Fridman, Mahjoub Aouni, Sylvain Fisson

Abstract readReview
PubMed Publisher
In one paragraph

Review in Journal of neuro-oncology, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
–field-weighted citation impact, top 84% 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

4 citing papers in PubMed, 6 citations in OpenAlex.

  1. Article
  2. Article
  3. Review
  4. Long-term in vivo microscopy of CAR T cell dynamics during eradication of CNS lymphoma in mice.Proceedings of the National Academy of Sciences of the United States of America · 2019
    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

6 authors at 5 institutions in 2 countries.

Rym Ben Abdelwahed BaggaInstitut National de la Santé et de la Recherche Médicale (INSERM), UMRS 872, Centre de Recherche des Cordeliers, 75006, Paris, France, rym.abdelwahed@yahoo.fr.
Sabrina Donnou
Jérémie Cosette
Catherine Sautès-Fridman
Mahjoub Aouni
Sylvain Fisson
Genethon (France) · FRCentre de Recherche des Cordeliers · FRDélégation Paris 5 · FRUniversité d'Évry Val-d'Essonne · FRUniversity of Monastir · TN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Primary central nervous system lymphomas (PCNSL) include ocular and cerebral lymphomas and are rare aggressive malignancies with poor prognoses. Compared with other lymphomas, they are a challenge for clinicians and scientists, for diagnosis and therapeutic progress and their prognosis remains unsatisfactory, because of the lack of molecular and biological knowledge. Indeed, several limitations of human sample present a major obstacle to the identification of the particular microenvironment of the sanctuary sites where these tumor cells grow. In addition, the generally poor overall condition and performance status of patients with PCNSL limit their participation in prospective trials. Therefore, animal models of PCNSL are essential for tumor microenvironment characterization and for antitumor response studying. In this review, we have compiled the B-and T-cell PCNSL mouse models that are used to improve our understanding of the lymphoma microenvironment, tropism and migration and to investigate novel therapeutic strategies.

Indexed as

AnimalsCentral Nervous System NeoplasmsDisease Models, AnimalHumansLymphomaMice

Identifiers

PMID25300908
OpenAlexW2094000650

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.