ArticleEuropean journal of nuclear medicine and molecular imaging2018
Article in European journal of nuclear medicine and molecular imaging, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 43 papers, 1 of them a synthesis that pooled 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.
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
43 citing papers in PubMed, 1 synthesis or guideline pooled it, 78 citations in OpenAlex.
- Pooled it
- First-in-human evaluation of [Annals of medicine · 2026Article
- Performance ofMolecular imaging and radionuclide therapy · 2025Article
- PSMA-PET-derived distance features as biomarkers for predicting outcomes in primary prostate cancer post-radical prostatectomy.Cancer imaging : the official publication of the International Cancer Imaging Society · 2025Article
- Preclinical Evaluation of a Novel PSMA-Targeted AgentTomography (Ann Arbor, Mich.) · 2025Article
- Diagnostic value ofCancer biology & therapy · 2024Article
- Baseline Ga-68 PSMA PET-Derived Primary Tumor Parameters in Patients with Prostate Cancer and Their Association with Clinical Risk Stratification and Clinicopathologic Features.World journal of nuclear medicine · 2024Article
- The Relationship between D'Amico and ISUP Risk Classifications andCurrent oncology (Toronto, Ont.) · 2024Article
- Towards a 'clicked' PSMA targeting gene delivery bioconjugate-polyplex for prostate cancer.RSC advances · 2024Article
- A Comprehensive Analysis of VolumetricMolecular imaging and radionuclide therapy · 2024Article
- Predictive value of volumetric parameters based onFrontiers in oncology · 2024Article
- "One Method to Label Them All": A Single Fully Automated Protocol for GMP-CompliantCurrent radiopharmaceuticals · 2024Article
- Error mitigation enables PET radiomic cancer characterization on quantum computers.European journal of nuclear medicine and molecular imaging · 2023Article
- Inspired by novel radiopharmaceuticals: Rush hour of nuclear medicine.Chinese journal of cancer research = Chung-kuo yen cheng yen chiu · 2023Article
- Up-to-Date Imaging and Diagnostic Techniques for Prostate Cancer: A Literature Review.Diagnostics (Basel, Switzerland) · 2023Review
- Article
- Radiometallation and photo-triggered release of ready-to-inject radiopharmaceuticals from the solid phase.Chemical science · 2023Article
- Article
- Targeted Radiation and Immune Therapies-Advances and Opportunities for the Treatment of Prostate Cancer.Pharmaceutics · 2023Review
- The efficacy ofFrontiers in oncology · 2023Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
13 authors at 2 institutions in 2 countries.
Funding
Abstract
purposeThe purpose of this study was to investigate the performance of
methodsFifty newly diagnosed patients with prostate cancer as confirmed by needle biopsy were continuously included, 40 in a train set and ten in a test set.
resultsIn the train set, 30/40 (75%) patients had high-risk prostate cancer and 10/40 (25%) patients had low-to-moderate-risk prostate cancer; in the test set, 8/10 (80%) patients had high-risk prostate cancer while 2/10 (20%) had low-intermediate risk prostate cancer. The univariate logistic regression model established with SUVmax, iPSMA-TV and iTL-PSMA could all effectively predict high-risk prostate cancer; the AUC of ROC were 0.843, 0.802 and 0.900, respectively. Based on the test set, the sensitivity and specificity of each model were 87.5% and 50% for SUVmax, 62.5% and 100% for iPSMA-TV, and 87.5% and 100% for iTL-PSMA, respectively. The iPSMA-TV and iTL-PSMA-based predictive model could predict the metastatic risk of prostate cancer, the AUC of ROC was 0.863 and 0.848, respectively, but the SUVmax-based prediction model could not predict metastatic risk.
conclusionsSemi-quantitative analysis indexes of
Indexed as
Identifiers
What 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.