Metastatic Bone Marrow Tumors Manifested by Hematologic Disorders: Study of Thirty-Four Cases and Review of Literature
Bibliographic record
Abstract
Purpose: Bone marrow metastasis of cancer is a sign of extensively hematogenous spreading of cancer and may be a terminal event of those patients. With the improvement of systemic chemotherapy for malignant disease, some patients may have longer survival. We plan to find out the clinical hematologic presentation and prognostic factors in cancer patients with bone marrow metastasis. Materials & Methods: In this retrospective study, we reviewed the results of 162 bone marrow examination carried out in adult malignancy patients (colon, lung, gastric, breast and prostate cancers) between January 2002 and December 2012 in Changhua Christian Hospital. The indication for bone marrow study for those patients with hematologic disorders included: leukoerythroblastosis, microangiopathic hemolytic anemia, unknown etiology of anemia, thrombocytopenia, bicytopenia and pancytopenia. Statistics analysis used SPSS 18.0 and overall survival was analyzed with the use of Kaplan-Meier curves and the log-rank test. Results: Thirty-four patients (20.9%) had evidence of involvement of the bone marrow by a solid tumor, most common cancers were prostate and lung. At the time of diagnosis, the most common hematologic disorders were leukoerythroblastosis and microangiopathic hemolytic anemia. Median survival after the diagnosis of bone marrow metastasis with supportive care only compared with definite treatments was 0.3 months and 20.6 months (p<0.0001). Patients with visceral organ metastasis (0.4 months vs 6.4 months, respectively; p <0.002) and anemia (2.1 months vs 6.4 months, p=0.031) had inferior survival. Patents without any cytopenia had better survival (12.5 months vs 4.1 months, p=0.029). Initial level of thrombocyte and neutrophil, bone marrow infiltration type (focal or diffuse) and disease status were not significant prognostic factor. Conclusions: Visceral metastasis and anemia are most poor prognostic factors in solid cancers with bone marrow metastasis. Since the improvement of the diagnosis and treatment for cancers during the recent decades, a portion of patients can be had better disease control after definite treatment especially in breast and prostate cancers with bone marrow 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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.007 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| 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".