ReviewMetabolites2019
Steroidomics for the Prevention, Assessment, and Management of Cancers: A Systematic Review and Functional Analysis.
Review in Metabolites, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 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
8 citing papers in PubMed, 15 citations in OpenAlex.
- A multi-omics-empowered framework for precision diagnosis and treatment of lysosomal diseases.Journal of pharmaceutical analysis · 2025Review
- Steroid Hormones as Modulators of Emotional Regulation in Male Urogenital Cancers.International journal of behavioral medicine · 2023Article
- Circulating adrenal 11-oxygenated androgens are associated with clinical outcome in endometrial cancer.Frontiers in endocrinology · 2023Article
- In Silico Prediction of Steroids and Triterpenoids as Potential Regulators of Lipid Metabolism.Marine drugs · 2021Review
- Current progress in metabolomics of gestational diabetes mellitus.World journal of diabetes · 2021Review
- Breast Cancer: Targeting of Steroid Hormones in Cancerogenesis and Diagnostics.International journal of molecular sciences · 2021Review
- Toward a Standardized Strategy of Clinical Metabolomics for the Advancement of Precision Medicine.Metabolites · 2020Review
- Components of the human-specific, p53-mediated "kill switch" tumor suppression mechanism are usurped by human tumors, creating the possibility of therapeutic exploitation.Cancer drug resistance (Alhambra, Calif.) · 2019Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
11 authors at 3 institutions in 1 country.
Funding
Abstract
Steroidomics, an analytical technique for steroid biomarker mining, has received much attention in recent years. This systematic review and functional analysis, following the PRISMA statement, aims to provide a comprehensive review and an appraisal of the developments and fundamental issues in steroid high-throughput analysis, with a focus on cancer research. We also discuss potential pitfalls and proposed recommendations for steroidomics-based clinical research. Forty-five studies met our inclusion criteria, with a focus on 12 types of cancer. Most studies focused on cancer risk prediction, followed by diagnosis, prognosis, and therapy monitoring. Prostate cancer was the most frequently studied cancer. Estradiol, dehydroepiandrosterone, and cortisol were mostly reported and altered in at least four types of cancer. Estrogen and estrogen metabolites were highly reported to associate with women-related cancers. Pathway enrichment analysis revealed that steroidogenesis; androgen and estrogen metabolism; and androstenedione metabolism were significantly altered in cancers. Our findings indicated that estradiol, dehydroepiandrosterone, cortisol, and estrogen metabolites, among others, could be considered oncosteroids. Despite noble achievements, significant shortcomings among the investigated studies were small sample sizes, cross-sectional designs, potential confounding factors, and problematic statistical approaches. More efforts are required to establish standardized procedures regarding study design, analytical procedures, and statistical inference.
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.