ArticleCancers2022
Prognostic Evaluation of Metastatic Castration Resistant Prostate Cancer and Neuroendocrine Prostate Cancer with [
Article in Cancers, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 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
6 citing papers in PubMed, 13 citations in OpenAlex.
- The Role of PET Tracers in Small-Cell Prostate Cancer (SCPC): An Overview in Clinical and Preclinical Settings.Cancers · 2026Review
- Neuroendocrine prostate cancer (NEPC) in focus: state of the art and future prospectives.Discover oncology · 2026Review
- Article
- Intrapatient Intermetastatic Heterogeneity Determined by Triple-Tracer PET Imaging in mCRPC Patients and Correlation to Survival: The 3TMPO Cohort Study.Journal of nuclear medicine : official publication, Society of Nuclear Medicine · 2024Observational
- PET/CT and Conventional Imaging for the Assessment of Neuroendocrine Prostate Cancer: A Systematic Review.Cancers · 2023Review
- Beyond fluorodeoxyglucose: Molecular imaging of cancer in precision medicine.CA: a cancer journal for cliniciansReview
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
8 authors at 1 institution in 1 country.
Funding
Abstract
Objectives: Prostate cancer is well known to express high levels of somatostatin receptors and preliminary data suggests that PET imaging with the somatostatin analog, [68Ga]Ga-DOTATATE, may allow for whole body staging of patients with metastatic castration resistant prostate cancer (mCRPC) and neuroendocrine prostate cancer (NePC). This study explores the utility of [68Ga]Ga-DOTATATE PET-CT to identify metastatic deposits in men with mCRPC and NePC and prognosticate disease progression. Methods: [68Ga]Ga-DOTATATE PET-CT was performed in 17 patients with mCRPC and of those, 2/17 had NePC. A semiquantitative analysis with standardized uptake values (SUV) (e.g., SUVmax, SUVmean) was performed for each metastatic lesion and reference background tissues. [68Ga]Ga-DOTATATE uptake in metastatic deposits was further classified as: mild (less than liver), moderate (up to liver average), or marked (greater than liver). Serial prostate-specific antigen measurements and patient survival were followed up to 3 years after PET imaging to assess response to standard of care treatment. Results: All patients had at least one metastatic lesion with identifiable [68Ga]Ga-DOTATATE uptake. Marked [68Ga]Ga-DOTATATE uptake was found in 7/17 patients, including both NePC patients, and all were non-responders to systemic therapy and died within the follow up period, with a mean time to death of 8.1 months. Three patients had mild [68Ga]Ga-DOTATATE uptake, and all were responders to systemic therapy and were alive 36 months after [68Ga]Ga-DOTATATE imaging. Conclusions: [68Ga]Ga-DOTATATE is able to identify mCRPC and NePC metastatic deposits, and lesions with [68Ga]Ga-DOTATATE uptake > liver may portend poor outcomes in patients with mCRPC.
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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.