Comparison of progression risk of monoclonal gammopathy of undetermined significance by method of detection
Bibliographic record
Abstract
ABSTRACT: Monoclonal gammopathy of undetermined significance (MGUS) is an asymptomatic premalignant disorder. The current standard of care is not to screen for MGUS, so it is often incidentally diagnosed in the clinic. It is unknown whether the outcomes of screened vs clinically detected MGUS differ. We compared the progression risk between screened vs clinical MGUS cohorts and assessed whether the MGUS detection method affected risk prediction of established clinical factors (score). We included 379 screened MGUS cases from the Olmsted County population-based study and 1384 patients with MGUS diagnosed during routine clinical evaluation at Mayo Clinic. Median follow-up time for the screened vs clinical cohort was 26.6 and 40.1 years, respectively. Accounting for death as a competing risk, the cumulative incidence of progression at 25 years was similar in the screened (11.1% [95% confidence interval [CI], 8.3-14.8]) vs clinical (10.1% [95% CI, 8.6-11.8]) MGUS cohorts, even when stratified by sex, age, or the baseline MGUS risk score. Overall, 0.9 (95% CI, 0.6-1.2) of patients with screened MGUS vs 1.0 (95% CI, 0.9-1.2) of those with clinically detected MGUS experienced disease progression for every 100 person-years of follow-up. MGUS detection method did not modify the association between MGUS risk score and progression risk (pinteraction = 0.217) and did not add to known risk factors for progression (likelihood ratio test; P = .839). Here, we show that progression risk among patients with screened vs clinically detected heavy-chain MGUS was similar. Future studies are needed to assess whether tailored follow-up of patients with screened MGUS affects clinical outcomes.
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.
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 | 0.008 | 0.020 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".