<i>TP53</i> Mutations and Outcome in Osteosarcoma: A Prospective, Multicenter Study
Why this work is in the frame
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Bibliographic record
Abstract
PURPOSE: Mutations of the TP53 gene have been associated with resistance to chemotherapy as well as poor prognosis in many different malignancies. This is the first prospective study of the prognostic value of somatic TP53 mutations in patients with newly diagnosed extremity osteosarcoma. PATIENTS AND METHODS: One hundred ninety-six patients with high-grade, nonmetastatic osteosarcoma of the extremities were enrolled from seven tertiary care institutions and observed prospectively for tumor recurrence (median follow-up duration, 44 months). All patients received neoadjuvant or adjuvant chemotherapy and surgery. Tumors were analyzed for the presence of TP53 mutations by polymerase chain reaction single-strand conformation polymorphism analysis and direct DNA sequencing. The association of the status of the TP53 gene with the risk of systemic recurrence was examined using survival analyses with traditional and histologic markers as prognostic factors. RESULTS: Patient age was the only factor that varied with TP53 gene status (P = .05). No relationship was identified between TP53 status and systemic relapse (relative risk, 1.24; P = .41). Analyses based on missense or nonsense mutations gave similar results (P > .10). In multivariate analysis, large (> 9 cm) tumor size (relative risk, 1.9; P = .006) and poor histologic response (< or = 90% necrosis) to chemotherapy (relative risk, 2.14; P = .02) were the only significant independent predictors of systemic outcome. CONCLUSION: We found no evidence that TP53 mutations predict for development of metastases in patients with high-grade osteosarcoma. Identification of other genes that influence chemotherapy response and clinical outcome in osteosarcoma is needed to facilitate further improvements in patient outcomes.
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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 | 0.001 |
| 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 | 0.001 |
| 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 it