Histopathologic Features of Prognostic Significance in High-Grade Osteosarcoma
Bibliographic record
Abstract
Context .- In osteosarcoma treated with neoadjuvant chemotherapy the extent of tumor necrosis on resection is considered an indicator of treatment response, and this has been shown to correlate with survival in most but not all studies. Objective .- To identify additional histologic variables of prognostic significance in high-grade osteosarcoma. Design .- Slides of pretreatment biopsy and primary postneoadjuvant chemotherapy resections from 165 patients with high-grade osteosarcoma were reviewed. Univariate (Kaplan-Meier) and multivariate (Cox regression) analyses were performed to identify clinical and histomorphologic attributes associated with overall survival. Results .- Univariate analyses confirmed the prognostic significance of metastatic status on presentation, primary tumor size, anatomic site, and histologic subtype. Additionally, the identification of lymphovascular invasion, 10% or more residual viable tumor, and 10 or more mitoses per 10 high-powered fields assessed in posttreatment resections were associated with poor survival, retaining significance in multivariate analyses. Based on results from multivariate analysis, we developed a prognostic index incorporating primary tumor size and site, and significant histologic features assessed on resection (ie, lymphovascular invasion status, mitotic rate, and extent of viable tumor). This scoring system segregates patients into 3 risk categories with significant differences in overall survival and retained significance in an independent validation set of 42 cases. Conclusions .- The integration of clinical and microscopic features improves prognostication of patients with osteosarcoma.
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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 | 0.001 |
| 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 | 0.002 |
| 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".