Evidence map›Paper›PMID 34762346›Full record

ArticleCurrent protocols2021

Preclinical Solid Tumor Models to Study Novel Therapeutics in Brain Metastases.

Mohini Singh, Ashish Dahal, Priscilla K Brastianos

Open access · greenAbstract read
In one paragraph

Article in Current protocols, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
0.3field-weighted citation impact, top 39% 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

1 citing paper in PubMed, 2 citations in OpenAlex.

  1. 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

3 authors at 1 institution in 1 country.

Mohini SinghCancer Center, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts.
Ashish DahalCancer Center, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts.
Priscilla K BrastianosCancer Center, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts.
Massachusetts General Hospital · US

Funding

Identification of genomic drivers of brain metastases in lung adenocarcinomaR01CA227156 · NCI · MASSACHUSETTS GENERAL HOSPITAL · PI BRASTIANOS, PRISCILLA KALIOPI, CARTER, SCOTT · 2018 to 2022
$3.5M
Using MRI and circulating tumor DNA to improve the interpretation of response to immunotherapy and targeted therapy in CNS metastasesR01CA244975 · NCI · MASSACHUSETTS GENERAL HOSPITAL · PI BRASTIANOS, PRISCILLA KALIOPI, GERSTNER, ELIZABETH · 2020 to 2024
$3.4M
Identification of genomic drivers of brain metastases in renal cell carcinomaR21CA220253 · NCI · MASSACHUSETTS GENERAL HOSPITAL · PI BRASTIANOS, PRISCILLA KALIOPI, CARTER, SCOTT · 2018 to 2019
$421k
NCI NIH HHS R01 CA227156NCI NIH HHS R01 CA244975NCI NIH HHS R21 CA220253
6 · The paper itself

Abstract

Metastases are the most common malignancy of the adult central nervous system and are becoming an increasingly troubling problem in oncology largely due to the lack of successful therapeutic options. The limited selection of treatments is a result of the currently poor understanding of the biological mechanisms of metastatic development, which in turn is difficult to achieve because of limited preclinical models that can accurately represent the clinical progression of metastasis. Described in this article are in vitro and in vivo model systems that are used to enhance the understanding of metastasis and to identify new therapies for the treatment of brain metastasis. © 2021 Wiley Periodicals LLC.

Indexed as

Brain NeoplasmsCentral Nervous SystemHumansMedical Oncologybrain metastasisdrug screeningimmunotherapyin vitro modelsin vivo modelspreclinical models

Identifiers

PMID34762346
PMCPMC8597918
OpenAlexW3211585417

What OpenQuestion holds

Textmetadata
LicenceTDM
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.