Ascl1 and <scp>OTP</scp> tumour expressions are associated with disease‐free survival in lung atypical carcinoids
Bibliographic record
Abstract
and/or foci of necrosis (usually punctate). Besides morphological criteria, no further tools in predicting AC clinical outcomes are proposed. The aim of this work was to identify novel factors able to predict AC disease aggressiveness and progression. METHODS AND RESULTS: Three hundred-seventy lung carcinoids were collected and centrally reviewed by two expert pathologists. Morphology and immunohistochemical markers (Ki-67, TTF-1, CD44, OTP, SSTR2A, Ascl1, p53, and Rb1) were studied and correlated with disease-free survival (DFS) and overall survival (OS). Fifty-eight of 370 tumours were defined as AC. Survival analysis showed that patients with Ascl1 + ACs and those with OTP-ACs had a significantly worse DFS than patients with Ascl1-ACs and OTP + ACs, respectively. Combining Ascl1 and OTP expressions, groups were formed reflecting the aggressiveness of disease (P = 0.0005). Ki-67 ≥10% patients had a significantly worse DFS than patients with Ki-67 <10%. At multivariable analysis, Ascl1 (present versus absent, hazard ratio [HR] = 3.42, 95% confidence interval [CI] 1.35-8.65, P = 0.009) and OTP (present versus absent, HR = 0.26, 95% CI 0.10-0.68, P = 0.006) were independently associated with DFS. The prognosis of patients with Ki-67 ≥10% tended to be worse compared to that with Ki-67 <10%. On the contrary, OTP (present versus absent, HR = 0.28, 95% CI 0.09-0.89, P = 0.03), tumour stage (III-IV versus I-II, HR = 4.25, 95% CI 1.42-12.73, P = 0.01) and increasing age (10-year increase, HR = 1.67, 95% CI 1.04-2.68, P = 0.03) were independently associated with OS. CONCLUSION: This retrospective analysis of lung ACs showed that Ascl1 and OTP could be the main prognostic drivers of postoperative recurrence.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".