Growth of Pituitary Macroadenomas Postpartial Resection: Implications for Adjuvant Radiotherapy
Bibliographic record
Abstract
Objective To determine the volumetric growth in macroadenomas (MAs) patients with residual postoperative disease and to identify subpopulations with rapid postoperative growth rate that may benefit from early salvage radiotherapy (RT). Methods Patients who had undergone a partial resection for MAs and did not receive immediate postoperative RT were eligible. Residual tissue was contoured on serial magnetic resonance imaging and planimetric and volumetric changes in size were measured. Growth rates were established by a single observer using serial volumetric measurements. Data were analyzed to find a relationship among growth rate, adjuvant treatment, and patient and tumor characteristics. Results Thirty-one patients met the eligibility criteria. Nine patients (29%) required adjuvant treatment because of tumor growth. Volumetric growth was identified 95% of the time compared with 64% planimetrically. Planimetric growth could not be established in 10% of patients showing volumetric changes. Median growth rate was 0.4464 mL/y. Growth rate positively correlated with size of residual postoperative volume (p < 0.001). Receiving salvage treatment positively correlated with growth rate (p = 0.001), particularly at a rate above 2.19 mL/y (p = 0.0064). Five patients (16%) had a growth rate above this level, all of which required salvage treatment. Patients with postoperative residual volume > 3.95 mL were most likely to experience rapid growth rate and require salvage treatment (p = 0.007). Conclusion Volumetric measurement was found to be superior to planimetric measurement in detecting changes in patients with residual tumors. Patients with postoperative residual volume > 3.95 mL should be considered for early treatment with RT.
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How this classification was reachedexpand
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 | 0.000 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".