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ShareScore release 0.9.0
Dataset results
9 results for “Pituitary tumours”
Epidemiology of Pituitary Tumours: Prevalence of Associated Neoplasia
ClinicalTrials.gov study NCT03973450. IPD Sharing: NO. Countries: 1. Publications: 13.
Genetics of Endocrine Tumours - Familial Isolated Pituitary Adenoma - FIPA
ClinicalTrials.gov study NCT00461188. IPD Sharing: Not stated. Countries: 1. Publications: 7.
Postop Pain Management in Pituitary Tumour Patients
ClinicalTrials.gov study NCT06353529. IPD Sharing: UNDECIDED. Countries: 1. Publications: 5.
Medication for acromegaly reduces expression of MUC16, MACC1 and GRHL2 in pituitary neuroendocrine tumour tissue
GEO Series GSE160195. Homo sapiens. 12 samples. Type: Expression profiling by high throughput sequencing.
Ga-68-DOTATOC -PET in the Management of Pituitary Tumours
ClinicalTrials.gov study NCT02419664. IPD Sharing: Not stated. Countries: 1. Publications: 0.
Follow-up Evaluation of Photo-Dynamic Therapy for Pituitary Tumours
ClinicalTrials.gov study NCT02632084. IPD Sharing: Not stated. Countries: 1. Publications: 0.
Extended Support for Persons With Pituitary Tumours After Surgery
ClinicalTrials.gov study NCT03927183. IPD Sharing: NO. Countries: 1. Publications: 0.
Validation of a clinicopathological classification for predicting outcomes of pituitary tumours: retrospective cohort study in a pituitary tumour centre of excellence, 2013–2023
<p><strong>Simple Summary:</strong> This retrospective study aims to classify a series of pituitary neuroendocrine tumours (PitNETs), typified according to the WHO 2017 recommendations, using Trouillas et al.’s clinicopathological classification from 2013. We analysed 166 patients who underwent PitNET surgery from 2013 to 2023. The tumours were identified according to the gene and immunohistochemistry expression of pituitary transcription factors and adenohypophyseal hormones. The PitNETs were graded based on the invasion observed in MRI and the Ki-67 index. The study found that grade 2a and 2b tumours, T2 signal intensity ratio (SIR), and silent corticotroph tumours were associated with lower progression-free survival rates. Tumour volume and T2 SIR were independent predictors of recurrence/progression, with a T2 SIR of 2 or more showing a significantly higher risk. These findings emphasise the prognostic value of the five-grade classification and underscore the importance of radiological evaluation for managing PitNETs.</p> <p> </p> <p><strong>Abstract: </strong>Immunostaining of transcription factors allows a more exact classification of pituitary neuroendocrine tumours (PitNETs), but not a better prediction of their clinical behaviour. This retrospective, single-centre study aims to classify a series of PitNETs using Trouillas et al.’s clinicopathological classification from 2013. We analysed 166 patients undergoing PitNET surgery in 2013–2023. Tumours were identified according to the gene and immunohistochemical expression of PitNET transcription factors plus adenohypophyseal hormones. Tumours were classified according to a grading system based on MRI invasion and Ki-67 index. Eighty-one (48.8%) patients had grade 2a tumours; 71 (42.8%), grade 1a; 8 (4.8%), 2b; and 6 (3.6%), 1b. At a mean follow-up of 57.8 (standard deviation 30) months, 13.9% (n=23) showed recurrence/progression; independent predictors of recurrence were tumour volume (p=0.031) and T2 signal intensity ratio (SIR) (p<0.001). This risk was 18.6-fold higher for a T2 SIR of 2 or more. Grade 2a and 2b tumours, T2 SIR, and silent corticotroph adenomas (SCAs) were associated with lower progression-free survival. Our results add more evidence to the prognostic value of the five-grade PitNET classification and suggest higher clinical surveillance of patients with SCAs is warranted. The MRI findings highlight the increasing value of radiological evaluation for managing PitNETs.</p>
Transcriptomic effects of medical treatment on gene expression of growth hormone secreting pituitary neruoendocrine tumour biology
GEO Series GSE200175. Rattus norvegicus; Homo sapiens. 165 samples. Type: Expression profiling by high throughput sequencing.
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OpenNeuro
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