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Enregistrement W2971830193 · doi:10.1182/blood-2018-99-117930

Monoclonal Gammopathy of Undetermined Significance - Patient Characteristics and Referral Patterns

2018· article· en· W2971830193 sur OpenAlexaffabout
Holly Lee, Lesley Street, Jason Tay, Jennifer Grossman, John F. Thaell, Dawn Goodyear, Sylvia McCulloch, Peter Duggan, Paola Neri, Víctor H. Jiménez‐Zepeda

Notice bibliographique

RevueBlood · 2018
Typearticle
Langueen
DomaineMedicine
ThématiqueMultiple Myeloma Research and Treatments
Établissements canadiensInstitute of Cancer ResearchUniversity of Calgary
Organismes subventionnairesnon disponible
Mots-clésMonoclonal gammopathy of undetermined significanceMedicineMultiple myelomaPopulationInternal medicineParaproteinemiaHematologyReferralIncidence (geometry)CohortPediatricsMonoclonalImmunologyFamily medicineMonoclonal antibody

Résumé

récupéré en direct d'OpenAlex

Abstract Introduction Monoclonal gammopathy of undetermined significance (MGUS) is a prevalent hematological condition among elderly population with incidence rates of 3% and 5% over the age of 50 and 70 years, respectively (Kyle et al., 2018). It is considered a premalignant state of multiple myeloma with a risk of progression of 1% per year. It has also been shown that MGUS patients have a shorter survival compared to the age- and sex-matched cohort (Kyle et al., 2018). Recent reports have highlighted the clinical significance of monoclonal gammopathy and the organ injury that may result from the effects of paraproteinemia (Fermand et al., 2018). With new insights into the significance of monoclonal gammopathy, the purpose of our study was to characterize the MGUS patient population referred at our hematology clinics by observing the reason for monoclonal protein testing and assessing patient comorbidities at the time of MGUS diagnosis. Methods We collaborated with three different clinicians who see the majority of MGUS patients at the University of Calgary Medical Group (UCMG) clinics. Patients who were referred and diagnosed with MGUS at the hematology clinic at UCMG since 2014 were assessed. Retrospective chart reviews were performed and reasons for monoclonal testing were recorded as indicated in referral request notes or initial consult notes. Data on patient comorbidities was collected as indicated in the initial consult notes. MGUS risk stratification was calculated per previous reports (Katzmann et al., 2013; Kyle et al., 2018) Results A total of 606 MGUS patients were seen at our clinic from February 2014 to June 2018. There were 565 patient charts available for complete review. 56% of the patients were male. Median age was 72 and median follow up was 2 years. MGUS risk stratification showed that 33.2% had low, 47.9% intermediate-low, 17.8% intermediate-high, and 1.2% high-risk MGUS. There were 55.5% IgG-MGUS, 20.5% IgM-MGUS, 12.3% IgA-MGUS, and 8.4% light chain-MGUS patients. 3% had biclonal gammopathy. Patient comorbidities at time of diagnosis are reported in table 1. The most common conditions were hypertension (50.4%), dyslipidemia (33.1%), chronic kidney disease (22.4%), diabetes (21.6%), coronary artery disease (18.6%), and solid tumors (14.6%). The most common solid tumors were prostate cancer (22/ 83, 25%), colon cancer (12/83, 14.4%), and breast cancer (10/83, 12.0%). Of the 565 patient charts, 140 had either missing referral sheets or had no record of the reasons for paraproteinemia investigations in the notes. In the rest of the 425 patients, the most common reason for monoclonal protein testing by referring physician was for renal dysfunction, which included work up for acute kidney injury, chronic kidney injury, proteinuria and hematuria. The next most common reason was work up of neuropathy, followed by anemia, and constitutional symptoms (figure 1). The patients in the 'Others' group had various reasons for testing including work up for seizure, forgetfulness, stroke, headache, chronic pancreatitis, multiple sclerosis, myasthenia gravis, family history of myeloma, history of venous thromboembolism, splenomegaly, bronchiectasis, chest pain, and as part of routine physical and blood donor testing. Discussion and Conclusion MGUS is often incidentally detected as part of a work up for other medical conditions, and our results reveal that there is a variety of reasons for which monoclonal testing is performed. With recent developments in our understanding of the significance of monoclonal gammopathy and its association with certain renal and organ damage (Fermand et al., 2018; Leung et al., 2012), there may be a change in how the paraproteinemia investigations are utilized by clinicians in different disciplines. It will be important to recognize and establish appropriate indications for testing. Furthermore, MGUS patients present with a wide range of comorbidities at the time of diagnosis. Interdisciplinary care will play a key role in discerning how much of the organ dysfunction and patients' symptoms are secondary to their underlying medical conditions versus the effect of monoclonal gammopathy. Disclosures McCulloch: Celgene: Honoraria; Takeda: Other: Travel expenses. Neri:Celgene: Consultancy, Honoraria; Janssen: Consultancy, Honoraria.

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 machine sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.

score de la tête « metaresearch » (Codex)0,001
score de la tête « metaresearch » (Gemma)0,003
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Observationnel · Signal consensuel: Observationnel
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,009
Score d'incertitude au seuil0,018

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0010,003
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0020,003
Études des sciences et des technologies0,0010,000
Communication savante0,0010,001
Science ouverte0,0000,001
Intégrité de la recherche0,0010,000
Charge utile insuffisante (le modèle a refusé de juger)0,0040,001

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.

Tête enseignante Opus0,032
Tête enseignante GPT0,292
Écart entre enseignants0,260 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_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 découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeObservationnel
Domainenon disponible
GenreEmpirique

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations0
Publié2018
Routes d'admission2
Résumé présentoui

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