MétaCan
Menu
← Back to cohort

Testing Mayo Clinic’s new 20/20/20 risk stratification model in another cohort of smoldering myeloma patients: A retrospective study.

2021· article· en· W3172419753 on OpenAlexaff
Camille Tessier, Jean‐Samuel Boudreault, Rayan Kaedbey, Fléchère Fortin, Vincent Éthier, Michel Pavic

Bibliographic record

VenueJournal of Clinical Oncology · 2021
Typearticle
Languageen
FieldMedicine
TopicMultiple Myeloma Research and Treatments
Canadian institutionsMcGill University Health CentreHôpital Notre-DameUniversité de SherbrookeCentre Hospitalier Universitaire de Sherbrooke
Fundersnot available
KeywordsMedicineMultiple myelomaHazard ratioInternal medicineRetrospective cohort studyAsymptomaticCohortPopulationClinical endpointProportional hazards modelOncologyGastroenterologyConfidence intervalClinical trial

Abstract

fetched live from OpenAlex

e20005 Background: Smoldering multiple myeloma (SMM) is an asymptomatic plasma cell disorder associated with a high risk of transformation to symptomatic multiple myeloma (MM). SMM risk of progression to MM is highly heterogeneous and several models have been suggested to predict this risk, but none have yet been adopted internationally. Lakshman et al. recently proposed a risk stratification model based on three markers: bone marrow plasma cell (BMPC) percentage > 20%, free light chain ratio (FLCr) > 20 and serum M protein > 20 g/L. In this “20/20/20” model, patients with 0, 1 or ≥ 2 risk factors are respectively considered at low, intermediate and high-risk of progression. The goal of our study was to test this risk model in our population and to determine if similar results could be obtained in another cohort of SMM patients. Methods: We conducted a retrospective, single center study with 89 patients diagnosed with SMM between January 2008 and December 2019. Patients were identified by query of the electronic medical records and the 2014 International Myeloma Working Group (IMWG) diagnostic criteria for SMM were used to determine eligibility. The main endpoint was progression to symptomatic multiple myeloma or amyloidosis. Results: All three markers proposed by Lakshman et al. were associated with an increased risk of progression: BMPC percentage ≥ 20% (hazard ratio [HR]: 4.28 [95% C.I., 1.90 – 9.61]; p < 0.001), serum M protein ≥ 20g/L (HR: 4.20 [95% C.I., 1.90 – 15.53]; p = 0.032) and FLCr ≥ 20 (HR: 3.25 [95% C.I., 1.09 – 9.71]; p = 0.035). Immunoparesis (HR: 2.61 [95% C.I., 1.07 – 6.41]; p = 0.036) was also an independent risk factor in our population. The estimated median time to progression (TTP) was not reached for the low and intermediate risk groups and was 29.1 months (95% C.I., 3.9 – 54.4) in the high-risk group (p = 0.006). The estimated mean TTP for the low-risk group, the intermediate-risk group and the high-risk group were respectively 78.4 months (95% C.I., 68.3 – 88.5), 48.3 months (95% C.I., 31.9 – 64.8) and 35.2 months (95% C.I., 19.1 – 51.2). Sex, IgA isotype, positive Bence-Jones, abnormal β2-microglobulin and MGUS prior to SMM did not result in an increased risk of progression. The estimated proportion of progression-free patients at 1, 2 and 5 years were 96.8%, 93.4% and 77.5% for the low-risk group, 80.0%, 80.0% and 62.2% for the intermediate risk group and 70.0%, 58.3% and 29.2% for the high-risk group. Conclusions: When Mayo Clinic’s new 20/20/20 risk model was applied to our population, it adequately predicted the risk of progression to symptomatic disease at 2 years. As it relies on readily available biological parameters, this model is easy to use and can be applied in most clinical settings. We believe this model could be used to further study therapeutic approaches in higher risk 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.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.005
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.009
Threshold uncertainty score0.018

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.005
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.170
GPT teacher head0.466
Teacher spread0.297 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2021
Admission routes1
Has abstractyes

Explore more

Same venueJournal of Clinical Oncology→Same topicMultiple Myeloma Research and Treatments→French-language works237,207→