Phenotypic Heterogeneity in Multiple Myeloma Families
Bibliographic record
Abstract
PURPOSE: To describe a series of families with familial multiple myeloma (MM). Observations were used to generate hypotheses about the role of genetic factors, the mode of inheritance of these factors, and the association of other cancers with familial MM. PATIENTS AND METHODS: This observational study consisted of 39 families with multiple cases of MM or related disorders from four collaborating research centers. Each center followed its usual family study method. Probands were interviewed, and, when possible, cancers were verified by medical records and pathology review. A working pedigree was compiled on each family. RESULTS: Seventeen families had affected members in two or more generations, and eight families had two or more affected members in a single generation. Four families had two or more members with plasma cell dyscrasias, with or without a single case of MM. In the remaining 10 families, a single MM case occurred with a family history of other cancers. Other cancers observed in family members included hematologic malignancies and solid tumors. In families with MM in multiple generations, there was a decrease in the age at MM diagnosis in successive generations. CONCLUSION: The study of familial MM may provide insights into the pathogenesis and, ultimately, the control and prevention of MM and related disorders. Population-based epidemiologic studies are crucial, but because of the rarity of familial MM, a concerted case-finding approach may also be fruitful. Therefore, we propose an international consortium to study familial MM, and we invite all interested colleagues to participate.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".