Sellar Masses: An Epidemiological Study
Bibliographic record
Abstract
BACKGROUND: Sellar masses (SM) are mostly benign growths of pituitary or nonpituitary origin that are increasingly encountered in clinical practice. To date, no comprehensive population-based study has reported the epidemiology of SM from North America. AIM: To determine the epidemiology of SM in the province of Nova Scotia, Canada. METHODS: Data from all pituitary-related referrals within the province were prospectively collected in interlinked computerized registries starting in November 2005. We conducted a retrospective analysis on all patients with SM seen within the province between November 2005 and December 2013. RESULTS: A total of 1107 patients were identified, of which 1005 were alive and residing within the province. The mean age at presentation was 44.6±18 years, with an overall female preponderance (62%) and a population prevalence rate of 0.1%. Of patients with SM, 837 (83%) had pituitary adenomas and 168 (17%) had nonpituitary lesions. The relative prevalence and standardized incidence ratio, respectively, of various SM were: nonfunctioning adenomas (38.4%; 2.34), prolactinomas (34.3%; 2.22), Rathke's cyst (6.5%; 0.5), growth hormone-secreting adenomas (6.5%; 0.3), craniopharyngiomas (4.5%; 0.2), adrenocorticotropic hormone-secreting adenomas (3.8%; 0.2), meningiomas (1.9%), and others (3.9%; 0.21). At presentation, 526 (52.3%) had masses ≥1 cm, 318 (31.6%) at <1 cm, and 11 (1.1%) had functioning pituitary adenomas without discernible tumor, whereas tumor size data were unavailable in 150 (14.9%) patients. The specific pathologies and their most common presenting features were: nonfunctioning adenoma (incidental, headaches, and vision loss), prolactinomas (galactorrhea, menstrual irregularity, and headache), growth hormone-secreting adenomas (enlarging extremities and sweating), adrenocorticotropic hormone-secreting adenoma (easy bruising, muscle wasting, and weight gain) and nonpituitary lesions (incidental, headaches, and vision problems). Secondary hormonal deficiencies were common, ranging from 19.6% to 65.7%; secondary hypogonadism, hypothyroidism, and growth hormone deficiencies constituted the majority of these abnormalities. CONCLUSIONS: This is the largest North American study to date to assess the epidemiology of SM in a large stable population. Given their significant prevalence in the general population, more studies are needed to evaluate the natural history of these masses and to help allocate appropriate resources for their management.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".