Developing an Evidence-based Followup Schedule for Bone Sarcomas Based on Local Recurrence and Metastatic Progression
Bibliographic record
Abstract
BACKGROUND: The potential for local recurrence and pulmonary metastasis after treatment of primary bone sarcomas necessitates careful patient followup; however, minimal data exist regarding the incidence and timing of these events, and therefore an evidence-based surveillance protocol has not been developed. QUESTIONS/PURPOSES: The purposes of this study were to (1) describe the frequency and timing of local recurrence by histologic grade over time; (2) describe the frequency and timing of metastasis by histologic grade and diagnosis over time; and (3) use these data to either justify current surveillance schedules and/or propose modifications that may improve the rate of new pulmonary metastatic events detected per examination. METHODS: A retrospective review was performed of all patients who underwent resection of a primary, nonmetastatic bone sarcoma (excluding chordoma) at a single tertiary oncology center from 1989 to 2010. Of the 680 patients identified, 15 were excluded for loss of followup in the first 2 years, leaving 665 eligible for study. Of these, 437 patients were alive with no evidence of disease at the conclusion of the study (mean followup, 136 months; range, 25-321 months). Cox regression analysis was performed to evaluate and control for patient age, tumor size, tumor location, and surgical margins. With patients stratified by sarcoma grade, Kaplan-Meier survival curves were constructed for the endpoints of local recurrence and metastasis, and log-rank tests were used to compare the rates of these events between grades and diagnoses. The number of new pulmonary metastatic events per patient-year was calculated for each sarcoma grade over the time intervals used in current surveillance protocols (0-2, 2-5, 5-10, and > 10 years) to facilitate development of a surveillance schedule that would maximize events detected per imaging study performed. In addition, to determine the effect of disease type, subset analysis was performed for osteosarcoma (OSA) and chondrosarcoma because these were the only diagnoses with sufficient numbers to support individual statistical analysis. RESULTS: With the numbers available for study, the overall local recurrence-free survival did not differ between sarcoma grades at any time points (p = 0.864). Metastasis-free survival curves differed between sarcoma grades (p < 0.001), and the pattern of Grade 2 OSA metastasis was more consistent with other Grade 3 sarcomas, so it was subsequently classified as high grade. No metastases of Grade 1 sarcomas occurred after 3 years, whereas Grade 2 and 3 sarcomas continued to metastasize until 10 years and rarely thereafter. According to the number of new pulmonary metastatic events per patient-year in each group, we propose that chest surveillance be performed according to the following schedule: annually only until 5 years for low-grade sarcomas; every 3 months for 2 years and annually from 2 to 10 years for intermediate-grade sarcomas; and every 3 months for 2 years, every 6 months from 2 to 5 years, and annually from 5 to 10 years for high-grade sarcomas. CONCLUSIONS: Pulmonary screening beyond 5 years may not be necessary for Grade 1 tumors but should be continued until 10 years for Grade 2 and 3 bone sarcomas. The surveillance frequency listed here, which is based on the number of new pulmonary metastatic events per patient-year in each grade, would increase the number of such events detected per examination performed. LEVEL OF EVIDENCE: Level III, therapeutic study.
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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 | 0.096 | 0.151 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.009 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.004 | 0.003 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".