ArticleCancer discovery2018
BLU-667 Targets RET-Altered Cancers.
Article in Cancer discovery, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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.
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.
Who cites it
3 citing papers in PubMed.
- Oncogenic and drug-sensitive RET mutations in human epithelial ovarian cancer.Journal of experimental & clinical cancer research : CR · 2020Article
- Thyroid Cancer in the Pediatric Population.Genes · 2019Review
- Profile of alectinib for the treatment of ALK-positive non-small cell lung cancer (NSCLC): patient selection and perspectives.OncoTargets and therapy · 2019Review
Corrections and comments
- Comment on
Authors and funding
0 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Findings from a phase I study indicate that the investigational RET inhibitor BLU-667 is safe and well tolerated, inducing good responses in patients with RET-altered medullary thyroid cancer or non-small cell lung cancer.
Indexed as
Identifiers
29657136What OpenQuestion holds
Registered trials
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.