ArticleClinical cancer research : an official journal of the American Association for Cancer Research2023
Shedding Light on PARP Inhibitor Response through Functional Imaging.
Article in Clinical cancer research : an official journal of the American Association for Cancer Research, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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
1 citing paper in PubMed, 2 citations in OpenAlex.
- Navigating PARP Inhibitor Resistance in Ovarian Cancer: Bridging Mechanistic Insights To Clinical Translation.Current treatment options in oncology · 2025Review
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Authors and funding
2 authors at 1 institution in 1 country.
Funding
Abstract
Functional PET imaging using a PARP inhibitor (PARPi) analog may serve as an early, dynamic biomarker of response to PARPi therapy in high-grade serous ovarian cancer. Clinically, this could help to rapidly identify PARPi nonresponders, thereby maximizing efficacy and avoiding toxicities of futile treatments. See related article by Pantel et al., p. 1515.
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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.