ArticleCell reports. Medicine2024
A predictive system comprising serum microRNAs and radiomics for residual retroperitoneal masses in metastatic nonseminomatous germ cell tumors.
Article in Cell reports. Medicine, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT07601672 (PRISTINE Trial), which is not on this map. Cited by 6 papers, 1 of them a synthesis that pooled it.
What it found
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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.
PRISTINE Trial: PRoton Beam Therapy In Seminoma - Toxicity INvestigation and Evaluation of Outcome
Who cites it
6 citing papers in PubMed, 1 synthesis or guideline pooled it.
- From Testis to Retroperitoneum: The Role of Radiomics and Artificial Intelligence for Primary Tumors and Nodal Disease in Testicular Cancer: A Systematic Review.Medicina (Kaunas, Lithuania) · 2026Pooled it
- MicroRNAs in oncology: a translational perspective in the era of AI.Nature reviews. Clinical oncology · 2026Review
- Machine Learning Model Integrating Computed Tomography Image-Derived Radiomics and Circulating miRNAs to Predict Residual Teratoma in Metastatic Nonseminoma Testicular Cancer.JCO clinical cancer informatics · 2025Article
- The diagnostic value of a breast cancer diagnosis model based on serum MiRNAs and serum tumor markers.World journal of surgical oncology · 2025Article
- Imaging genomics of cancer: a bibliometric analysis and review.Cancer imaging : the official publication of the International Cancer Imaging Society · 2025Review
- Case Report: Multidisciplinary discussion and management of a case involving a non-seminomatous germ cell tumor complicated by the presence of cancerous thrombus in the inferior vena cava.Frontiers in oncology · 2025Article
Corrections and comments
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Authors and funding
11 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Predicting the histopathology of residual retroperitoneal masses (RMMs) before post-chemotherapy retroperitoneal lymph node dissection in metastatic nonseminomatous germ cell tumors (NSGCTs) can guide individualized treatment and minimize complications. Previous single approach-based models perform poorly in validation. Herein, we introduce a machine learning model that evolves from a single-dimensional tumor diameter to incorporate high-dimensional radiomic features, with its effectiveness assessed using the macro-average area under the receiver operating characteristic curves (AUCs). In addition, we utilize more precise and specific microRNAs (miRNAs), not common clinical indicators, to construct an integrated radiomics-miRNA predictive system, achieving an AUC of 0.91 (0.80-0.99) in the prospective test set. We further develop a web-based dynamic nomogram for swift and precise calculation of the histopathological probabilities of RMMs based on radiomic scores and serum miRNA levels. The radiomics-miRNA integrated system offers a promising tool to select personalized treatments for patients with metastatic NSGCT.
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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.