Smoldering multiple myeloma: evolving diagnostic criteria and treatment strategies
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The adage for smoldering myeloma (SMM) has been to observe without treatment, until criteria for active multiple myeloma were satisfied. Definitions and risk stratification models have become more sophisticated, with prognostication tailored to include high-risk cytogenetics as per the most recent International Myeloma Working Group 2020 risk model. Moreover, progress in defining genomic evolution and changes in the bone marrow microenvironment through the monoclonal continuum have given insight into the complexities underlying the different patterns of progression observed in SMM. Given recent data showing improved progression-free survival with early intervention in high-risk SMM, the current dilemma is focused on how these patients should be treated. This case-based article maps the significant advancements made in the diagnosis and risk stratification of SMM. Data from landmark clinical trials will also be discussed, and ongoing trials are summarized. Ultimately, we outline our approach to SMM and hope to impart to the reader a sound concept of the current clinical management of SMM.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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 | 0.000 |
| 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 it