Somatostatin analogs in neuroendocrine tumors with <scp>Ki‐67</scp> index of ≥10%
Bibliographic record
Abstract
Somatostatin analogs (SSAs) are an established first-line therapy in intestinal and pancreatic neuroendocrine tumors (NETs). Based on Phase III studies, their use is recommended in NET with a Ki-67 index of up to 10%. The effect of first-line SSA therapy on differentiated NET with a Ki-67 index ≥10% is poorly understood. This study aimed to investigate the outcomes of SSA therapy in differentiated NETs with a Ki-67 index of ≥10%. A retrospective analysis of a prospectively created dataset of consecutive patients with NETs was performed. Patients with first-line SSA monotherapy in advanced NET with a Ki-67 index ≥10% were included. The study endpoints were progression-free survival (PFS), overall survival (OS), and clinical benefit rate, defined as partial remission (PR) or stable disease (SD). Of 362 consecutive patients with a Ki-67 index ≥10%, 67 received first-line SSA therapy. The Ki-67 index was 10-20% (G2) in 57 (85%) patients and >20% (G3) in 10 (15%). SD as the best response was reached in 40 (59.7%) patients and PR in 3 (4.5%), irrespective of the NET origin, time from the diagnosis, or somatostatin receptor-based tracer uptake. The median PFS was 18 (95% confidence interval [CI], 5.7-30.3) months, and the median OS was 60 (95% CI, 38.2-81.8) months after the initiation of SSA therapy. Median PFS was significantly longer in patients with a Ki-67 index of 10-20% (19 months; 95% CI, 6.2-31.8) compared to those with G3 NETs (6 months; 95% CI, 2.9-9.1; p = .015, log-rank test), and in patients with a liver tumor burden of ≤10% (24 months; 95% CI, 12.7-35.3) versus >10% (4 months; 95% CI, 2.3-5.7; p = .007). First-line SSA therapy can provide meaningful disease control in patients with G2 NETs and low tumor burden, despite a Ki-67 index ≥10%. It may be a reasonable alternative to more intensive therapies in selected patients.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| 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".