From hope to reality: the road to cure from multiple myeloma centers of excellence
Bibliographic record
Abstract
Multiple myeloma (MM) is a heterogeneous disease that until now has been considered incurable, even in the younger population (1,2). However, recent data show an increase in the number of MM patients who have achieved what is called an “operational cure” due to innovative treatments and diagnostic and follow-up alternatives, something that has become a hope in oncologic hematology (3,4). The strategies that have been determinant in the improvement of survival and quality of life in most patients are the use of combined and targeted treatment modalities from the onset of the disease, especially in patients at high biological risk (4-6), high-dose chemotherapy, and autologous stem cell transplantation (ASCT) (7,8), which helped obtain deeper responses by achieving the negativization of minimal residual disease (MRD), continuous therapy to control MRD when it persists (9), improved techniques for early detection of relapses (6), the use of novel therapies in relapse cases, especially immune effector cell therapy (8), and finally the possibility of access to novel drugs in the context of standard of care or clinical trials (10). The Instituto Nacional de Cancerología (INC) (Bogotá, Colombia) —an accredited health institution whose mission is to work for the integral control of cancer through patient attention and care, research, training of human talent, and the development of public health actions— has bet not only on the consolidation of functional cancer units but also on the attention of patients through centers of excellence (CE). In this regard, the Centro de Excelencia en Mieloma Múltiple del Instituto Nacional de Cancerología (CEMMINC) was a pioneer in the group of hematologic neoplasms (11). This CE is coordinated and run by professionals trained and dedicated exclusively to the care of MM and related diseases, a model that has been extraordinarily efficient in the best cancer centers in Canada, the United States, and Europe (12-15).
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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 | 0.022 | 0.045 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.008 | 0.011 |
| Scholarly communication | 0.020 | 0.020 |
| Open science | 0.005 | 0.028 |
| Research integrity | 0.018 | 0.037 |
| Insufficient payload (model declined to judge) | 0.039 | 0.011 |
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".