Solitary Plasmacytoma of Bone of the Spine
Bibliographic record
Abstract
STUDY DESIGN: Retrospective analysis. OBJECTIVE: To determine the prognostic indicators in patients with solitary plasmacytoma of bone (SPB) of the spine. SUMMARY OF BACKGROUND DATA: Population-level estimates for prognosis among patients with SPB of the spine are still lacking. Sociodemographic and clinical predictors of outcome have not been well characterized. METHODS: The Surveillance, Epidemiology, and End Results Registry was used to identify all patients with SPB of the spine from 1995 through 2014. Associated population data were used to determine annual incidence and limited-duration prevalence. Overall survival (OS) estimates were obtained using the Kaplan-Meier method and compared across groups using log-rank test. A Cox regression model was used for multivariate analysis of survival. Logistic regression was performed to identify predictors of the progression to multiple myeloma (MM). RESULTS: The incidence and prevalence of the disease increased during the study period. Spinal SPB most commonly affected older people (>50) with a male preponderance. The median OS were 74.0 months. The 5 and 10-year survival rates for these patients were 56.1% and 36.7%, respectively. On multivariable analyses, older age, and surgery without radiotherapy were correlated with poor survival of patients with spinal SPB. The 3-year probability of progression to MM was 10.1%. Patients aged >70 years were associated with progression to MM. There was no significant association between the methods of surgical resection (radical or local/partial) and OS or progression to MM. CONCLUSION: The findings of this study provide population-based estimates of the incidence, prevalence and prognosis for patients with SPB of the spine. This analysis indicated that the only identifiable prognostic indicators were older age and surgery without radiotherapy. Moreover, the methods of surgical resection did not influence the OS or progression to MM. LEVEL OF EVIDENCE: 4.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| 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".