ArticleScientific reports2022
Data mining analyses for precision medicine in acromegaly: a proof of concept.
Article in Scientific reports, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 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
10 citing papers in PubMed, 24 citations in OpenAlex.
- Approach to the patient: precision medicine-guided evaluation and treatment of acromegaly.The Journal of clinical endocrinology and metabolism · 2026Review
- Systems biology integration of miR-mRNA profiles identifies steroid refractoriness mechanisms and biomarker candidates in ulcerative colitis.Biochemistry and biophysics reports · 2026Article
- Review
- Current treatment landscape of acromegaly.The Journal of clinical endocrinology and metabolism · 2026Review
- Adenoma receptors and histologic characteristics determining management outcomes.The Journal of clinical endocrinology and metabolism · 2026Review
- Somatostatin receptors in pituitary somatotroph adenomas as predictors of response to somatostatin receptor ligands: A pathologist's perspective.Brain pathology (Zurich, Switzerland) · 2025Review
- EndoCompass Project: Research Roadmap for Pituitary and Neuroendocrine Tumor Endocrinology.Hormone research in paediatrics · 2025Review
- Current and Future Advances in Surgical Therapy for Pituitary Adenoma.Endocrine reviews · 2023Article
- Prolactin and Growth Hormone Signaling and Interlink Focused on the Mammosomatotroph Paradigm: A Comprehensive Review of the Literature.International journal of molecular sciences · 2023Review
- Leukocyte Telomere Length and Neuregulin-4 Levels in Female Patients with Acromegaly: The Relationship between Disease Activity and Body Fat Distribution.Journal of clinical medicine · 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
25 authors at 17 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Predicting which acromegaly patients could benefit from somatostatin receptor ligands (SRL) is a must for personalized medicine. Although many biomarkers linked to SRL response have been identified, there is no consensus criterion on how to assign this pharmacologic treatment according to biomarker levels. Our aim is to provide better predictive tools for an accurate acromegaly patient stratification regarding the ability to respond to SRL. We took advantage of a multicenter study of 71 acromegaly patients and we used advanced mathematical modelling to predict SRL response combining molecular and clinical information. Different models of patient stratification were obtained, with a much higher accuracy when the studied cohort is fragmented according to relevant clinical characteristics. Considering all the models, a patient stratification based on the extrasellar growth of the tumor, sex, age and the expression of E-cadherin, GHRL, IN1-GHRL, DRD2, SSTR5 and PEBP1 is proposed, with accuracies that stand between 71 to 95%. In conclusion, the use of data mining could be very useful for implementation of personalized medicine in acromegaly through an interdisciplinary work between computer science, mathematics, biology and medicine. This new methodology opens a door to more precise and personalized medicine for acromegaly patients.
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.