Incidence and prevalence of clinically detected smoldering multiple myeloma within the general population: a retrospective observational cohort study
Notice bibliographique
Résumé
Smoldering multiple myeloma (SMM) is a precursor plasma cell disorder characterized by clonal proliferation without end-organ damage. Although asymptomatic, SMM remains clinically relevant due to its potential progression to multiple myeloma (MM) or AL amyloidosis. Recent studies suggest that early therapeutic intervention may delay progression in high-risk cases [ 1 , 2 , 3 , 4 ]. However, the real-world epidemiology of SMM—particularly cases diagnosed through routine clinical evaluation rather than screening—remains poorly characterized. Population-based screening, such as the iStopMM study, identified a 0.53% prevalence of SMM in individuals aged ≥40 years [ 5 ]. But these estimates may differ in clinical practice, where SMM is typically diagnosed incidentally during evaluation for other conditions. Prior studies using administrative databases have been limited by the absence of an ICD code to differentiate SMM from untreated or “SLiM” MM [ 6 , 7 , 8 ], making it difficult to assess true population-level trends. We aimed to address this gap by describing the incidence and prevalence of clinically detected SMM between 2010 and 2022 using real-world data from a defined Canadian health region. We conducted a retrospective cohort study using laboratory and clinical data from The Ottawa Hospital, the sole tertiary hematology center for Ontario’s Champlain Local Health Integration Network (LHIN). Due to the regionally centralized healthcare delivery and universal healthcare model in Ontario, all patients within the Champlain LHIN suspected to have a malignant hematologic disorder requiring a bone marrow biopsy—such as SMM—must be referred to our institution. In contrast, MGUS may be diagnosed and monitored by community hematologists or internists and would not necessarily be captured in our dataset. We identified all adults tested for monoclonal proteins (serum protein electrophoresis [SPEP], urine protein electrophoresis [UPEP], serum free light chains [FLC], and immunofixation) between January 1, 2010, and December 31, 2022. We flagged patients with detectable monoclonal proteins (MCP) or abnormal FLC ratios and cross-referenced pathology records for bone marrow biopsies. We also retrieved treatment data from the Ontario Cancer Registry to identify patients who received therapies indicative of plasma cell or lymphoproliferative disorders (see supplementary data for further details). Electronic medical records were reviewed in detail to discern the workup and diagnosis of patients. We defined SMM as either: (i) ≥10% bone marrow plasma cells (BMPCs) without CRAB or SLiM criteria, or (ii) MCP ≥ 30 g/L without MM-defining events [ 9 ]. We applied the Mayo 20/20/20 risk model to classify patients as high-risk if they had ≥2 of the following: BMPCs >20%, MCP > 20 g/L, or FLC ratio >20 [ 10 ]. As SMM is asymptomatic the true incidence of SMM cannot be determined, as this would require screening for MGUS and monitoring for progression to SMM. Therefore, incident SMM was defined as the date that a patient was first diagnosed with SMM during clinical evaluation. We defined incidence as the number of new SMM diagnoses per year and prevalence as the number of alive, non-progressed, and actively followed SMM patients in a given year (even if diagnosed previously). Publicly reported Champlain LHIN census data from 2011, 2016, and 2021 were used to calculate incidence and prevalence rates of SMM within the general population [ 11 , 12 , 13 ]. We evaluated 51,798 patients for monoclonal gammopathies over the study period, of whom 7,431 (14.3%) had a detectable MCP. Among these, 344 patients had confirmed SMM. Figure S1 outlines the full cohort selection. Of the 344 patients, 260 were diagnosed during the study period (incident cases), while the rest were diagnosed before 2010 but remained under follow-up. The median age at diagnosis was 70.9 years (IQR 61.8–79.4), and 53% were male. Median MCP was 12.4 g/L (IQR 6.4–22.2), and the median FLC ratio was 9.5 (IQR 3.1–28.1). Only 3 patients were diagnosed before age 40. Table 1 summarizes baseline characteristics stratified by diagnostic period. We observed improved diagnostic completeness over time: by 2020–2022, 99% of patients had both a bone marrow biopsy and FLC evaluation, compared to 0% having a FLC and only 77% undergoing a baseline bone marrow biopsy in 2010–2014. The number of new SMM diagnoses in patients above 40 years rose from 14 in 2011 to 28 in 2022. Incidence rates per 100,000 Champlain LHIN residents increased from 0.7 in 2011 (0.0007% of the population) to 1.9 (0.0019% of the population) in 2021. Among individuals aged ≥40, incidence increased from 1.5 to 3.6 per 100,000 people over the same period. We performed age-specific standardization using the 2016 population as reference; the standardized incidence ratio (SIR) in 2021 was 1.9 (95% CI 1.2–2.6), indicating that observed cases were nearly double the expected (compared to the 2016 incidence rates). Tables S1 , S2 summarizes these age-specific SIRs and incidence stratified by age and sex over time, respectively. Importantly, the increase in SMM incidence appeared driven by low- and intermediate-risk patients. Figure 1B shows that while overall incidence increased, the proportion of high-risk SMM remained stable. Table 1 supports this trend, showing a significant decline in median MCP over time (2010–2014: 15.0 g/L vs. 2020–2022: 9.2 g/L, p < 0.001). Table 1 Baseline characteristics of clinically detected smoldering multiple myeloma patients diagnosed between 2010 and 2022. Full size table Fig. 1: Incidence and prevalence of SMM over time. A Incidence of annual SMM cases in general over time, as well as among patients evaluated for a plasma cell disorder (PCD). B SMM incidence stratified by the baseline Mayo 20/20/20 risk score (patients with missing BM biopsy, FLC ratio, or serum MCP data were deemed non-evaluable for risk stratification) . C Prevalence of SMM over time. Total prevalent SMM is presented, stratified by annual incident and prevalent cases. Full size image
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,002 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».