Validation of criteria for defining Pituitary Tumors Centers of Excellence (PTCOE)
Bibliographic record
Abstract
Abstract Purpose The Pituitary Society established the concept and mostly qualitative parameters for defining uniform criteria for pituitary tumor centers of excellence (PTCOEs) based on expert consensus. To validate those previously proposed criteria through collection and evaluation of self-reported activity of several internationally-recognized tertiary pituitary centers, thereby transforming the qualitative 2017 definition into a validated quantitative one, which could serve as the basis for future objective PTCOE accreditation. Methods An ad-hoc prepared database protocol was distributed to 9 Pituitary Centers chosen by the project scientific committee and comprising Centers of worldwide repute, which agreed to provide activity information derived from registries related to the years 2018-2020 and completing the database within 60 days. The database, composed of Excel® spreadsheets with requested specific information on leading and supporting teams provided by each Center, was reviewed by two blinded referees and all 9 of 9 candidate centers satisfied the overall PTCOE definition, according to referees’ evaluations. To obtain objective numerical criteria, median values for each activity/parameter were considered as the ideal PTCOE definition target, whereas the low limit of the range was selected as the acceptable target for each respective parameter. Results Three dedicated pituitary neurosurgeons were considered ideal, whereas one dedicated surgeon was acceptable. Moreover, 100 surgical procedures per year is ideal, while the results indicated that 50 surgeries per year is acceptable. Acute post-surgery complications, including mortality and readmission rates, should ideally be negligible or nonexistent, but acceptable criterion was a rate lower than 10% of patients with complications requiring readmission within 30 days after surgery. Four endocrinologists devoted to pituitary diseases are requested in a PTCOE and the total population of patients followed in a PTCOE should not be less than 850. It appears acceptable that at least one dedicated/expert in pituitary diseases is required in neuroradiology, pathology, and ophthalmology groups, whereas at least two expert radiation oncologists are needed. Conclusion This is, to our knowledge, the first study to survey and evaluate the activity of a relevant number of high-volume centers in the pituitary field. This effort, internally validated by ad-hocreviewers, allowed for transformation of previously formulated theoretical criteria for the definition of a PTCOE to precise numerical definitions based on real-life evidence. The application of a derived objective model can be used by external bodies for accreditation of pituitary centers as PTCOEs.
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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 | 0.147 | 0.285 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.012 | 0.007 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.007 | 0.004 |
| Open science | 0.004 | 0.010 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".