Comparative Analysis of Skip Metastasis in Pediatric Osteosarcoma: Clinical Features and Outcomes
Bibliographic record
Abstract
BACKGROUND: Skip metastasis (SM) is a synchronous regional bone metastasis. Using new imaging modalities, the detection of SM is easier and possibly more common. We reviewed patients with SM and compared their characteristics and outcomes to other patients with osteosarcoma treated at our center. METHODS: We reviewed retrospectively children (<18 years) with newly diagnosed osteosarcoma who presented from June 2006 to March 2022. Patients' characteristics, treatment modalities, and outcomes were analyzed. All cases were discussed in a multidisciplinary clinic that included 2 experienced radiologists. RESULTS: We identified 155 patients with osteosarcoma, among which 13 (8.3%) patients had SM detected by MRI. Patients with SM had a median age at diagnosis of 11.2 years (range 7 to 17). Three patients had lung metastasis at diagnosis. Bone scan was positive for the SM in 8 patients (62%). All patients underwent primary tumor resection after neoadjuvant chemotherapy (amputation in 5, limb salvage surgery in 8). Five had postchemotherapy necrosis ≥90% in primary tumor. Seven patients relapsed/progressed (1 local and 6 in the lung), all relapsed patients died of disease. Compared to the rest of the patients, those with SM had similar clinical features to patients without SM; outcomes were similar with no significant differences in event-free survival and overall survival ( P =0.7 and 0.3, respectively). CONCLUSION: In this study, we observed a percentage of patients with SM comparable to previous reports. Patients with SM exhibited clinical features akin to the rest of our patients. Thorough evaluation of imaging studies and multidisciplinary care, coupled with meticulous surgical planning, are crucial for achieving a cure, which remained unjeopardized in our patients with SM.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.001 | 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".