Tenosynovial Giant Cell Tumor: Incidence, Prevalence, Patient Characteristics, and Recurrence. A Registry-based Cohort Study in Denmark
Why this work is in the frame
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Bibliographic record
Abstract
OBJECTIVE: Tenosynovial giant cell tumor (TGCT) is a rare benign proliferative and inflammatory disease arising from synovia of joints, bursae, or tendon sheaths. We aimed to estimate incidence rate and prevalence of TGCT in Denmark, to describe patient characteristics and treatment modalities among patients with TGCT, and to estimate risk of TGCT recurrence. METHODS: Using registry data on pathology examinations and inpatient and outpatient hospital diagnoses, we identified adult patients with diagnoses of diffuse TGCT (D-TGCT) or localized TGCT (L-TGCT) between 1997 and 2012, followed through 2012. We described patients' characteristics, treatment modalities, and recurrence. RESULTS: We identified 2087 patients with L-TGCT and 574 patients with D-TGCT. Their incidence rates per million person-years were 30.3 (95% CI 29.1-31.7) and 8.4 (95% CI 7.7-9.1), respectively. At the end of 2012, prevalence per 100,000 persons was 44.3 (95% CI 42.4-46.3) for L-TGCT and 11.5 (95% CI 10.6-12.6) for D-TGCT. Women made up 61% of the patients with L-TGCT and 51% of the patients with D-TGCT. Median age at diagnosis was 47 years. Ten-year risk of recurrence was 9.8% (95% CI 8.4-11.3%) after L-TGCT and 19.1% (95% CI 15.7-22.7%) after D-TGCT. CONCLUSION: This study contributes evidence about epidemiology of TGCT based on routinely collected population-based data gathered in a setting of universal equal access to healthcare and complete followup.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it