Indeterminate Pulmonary Nodules in Osteosarcoma Are Associated With Increased Risk of Pulmonary Metastasis
Bibliographic record
Abstract
Osteosarcoma is the most common primary malignant bone tumor in children. In addition to pulmonary metastasis, computed tomography frequently detects indeterminate pulmonary nodules (IPN). We conducted this study to determine the clinical significance of IPN in terms of progression to pulmonary metastasis and its impact on survival. It was a retrospective cohort study of pediatric nonmetastatic osteosarcoma patients treated from January 2005 to December 2018. Baseline computed tomography scans were reviewed for the presence of IPN (defined as a single nodule of <10 mm or ≥3 nodules of <5 mm). Subsequent scans were reviewed for the development of pulmonary metastasis. Of 155 patients, 31.6% (n=49) had IPN at baseline. A total of 43% (n=21) of those with IPN subsequently progressed to pulmonary metastasis compared with only 26% (n=28) of those without IPN (P<0.001) with a relative risk of 1.6 (1.03 to 2.5) in the IPN group. Patients with ≥3 IPN at baseline were at significantly greater risk of pulmonary metastasis as compared with <3 IPN (P=0.013). Overall and event-free survival in patients with and without IPN was 58% and 35%, and 72% and 46%, respectively. Our results suggest that patients with IPN may be at greater risk for progressing to pulmonary metastasis.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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 source (direct Gemma or distilled Codex), 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".