Clinical trial · Observational
Screening for AL Amyloidosis in Smoldering Multiple Myeloma
NCT06365060CI-TRIAL-00093202recruitingClinicalTrials.gov clinicaltrialsProvenance
- Source
- ClinicalTrials.gov
- Retrieved
- Sep 8, 2026
- Layer
- normalized (units and labels harmonized; values unchanged)
- Run
- ING-CLINICALTRIALS-20260908-000001
Summary
Brief summary (as posted)
In this multicenter study, we will recruit 400 patients 40 years of age or older at 15 centers with a diagnosis of smoldering multiple myeloma (SMM), a group of patients for whom standard of care is observation not treatment. The main goal of this study is to screen for the diagnosis of light-chain amyloidosis (AL) before the onset of symptomatic disease and to develop a training set for a likelihood algorithm.
Conditions
Conditions (1)
Free-text conditions as registered, with the CancerIndex entity they were reconciled to and the match type.
| Condition (as posted) | Mapped entity | Match | Confidence |
|---|---|---|---|
| Smoldering Multiple Myeloma | Smoldering Multiple Myeloma | ONTOLOGY_EXACT | 0.98 |
Interventions
Interventions (0)
Data not yet available
No intervention recorded.
Design
Arms and outcomes
Arms (0)
[]Primary outcomes (2)
- measure
- Creating a network to enroll patients on a collaborative study requiring marrow and blood specimens, to collect data for a training set of likelihood statistics and to plan a future validation study.
- timeFrame
- 5 years
- description
- With a 15-center network covering 12 states and almost 45% of the US population, we will evaluate 400 SMM patients \> 40 years old who pass FLC criteria using standard of care tests including NT-proBNP and clinical marrow specimens evaluated for the presence of t(11;14) and gain1q. Marrow cells will be processed by NGS for clonal IGLV gene identification. With the training data obtained, we will use existing statistical modeling techniques to generate a statistical algorithm for identifying undiagnosed cases of AL and assessment of risk of AL, and to plan a validation study testing the training model. We will also investigate a role for the novel biomarker clusterin (Clu) as an indicator of risk of AL in SMM patients; preliminary work indicates that Clu is significantly lower in AL than in SMM patients.
- measure
- Validating an NGS assay that identifies IGLV genes in clonal plasma cells
- timeFrame
- 5 years
- description
- All subjects will have their clonal IGLV genes identified by NGS enabling the creation and validation of a laboratory developed test in a precision medicine laboratory that is certified under regulations of the Clinical Laboratory Improvement Amendments of 1988 (CLIA). Approval for this laboratory developed test for both κ and λ IGVL genes will permit providers, patients and researchers to use the test in decision-making to care for monoclonal gammopathy patients. We will also investigate the exploratory objective of defining the alterations in sequence in AL and non-AL FLC derived from the same IGLV germline gene.
Eligibility
Eligibility (as posted)
- Sex
- All
- Minimum age
- 40 Years
Show eligibility criteria text
Inclusion Criteria: * Patients 40 years of age and older * diagnosed with either Smoldering Multiple Myeloma or a Monoclonal Gammopathy * dFLC greater than 23 mg/L * abnormal FLC ratio * If the patient has an eGFR less than 50 mL/min/1.73m2, the FLC ratio is inconsequential. The patient only needs to meet the age and dFLC criterion. Exclusion Criteria: * Patients younger than 40 years of age are not eligible * Patients with a previous finding of amyloid in other biopsies will not be included * Adults unable to consent are not eligible, including the cognitively impaired Pregnant women, pregnant minors, minors (i.e., individuals who are not yet adults), wards of the state, non-viable neonates, neonates of uncertain viability, and prisoners are not eligible
References
Publications (22)
- BACKGROUNDAvalos M, Pouyes H, Grandvalet Y, Orriols L, Lagarde E. Sparse conditional logistic regression for analyzing large-scale matched data from epidemiological studies: a simple algorithm. BMC Bioinformatics. 2015;16 Suppl 6(Suppl 6):S1. doi: 10.1186/1471-2105-16-S6-S1. Epub 2015 Apr 17. PMID 25916593
- BACKGROUNDBodi K, Prokaeva T, Spencer B, Eberhard M, Connors LH, Seldin DC. AL-Base: a visual platform analysis tool for the study of amyloidogenic immunoglobulin light chain sequences. Amyloid. 2009 Mar;16(1):1-8. doi: 10.1080/13506120802676781. PMID 19291508
- BACKGROUNDBujang MA, Adnan TH. Requirements for Minimum Sample Size for Sensitivity and Specificity Analysis. J Clin Diagn Res. 2016 Oct;10(10):YE01-YE06. doi: 10.7860/JCDR/2016/18129.8744. Epub 2016 Oct 1. PMID 27891446
- BACKGROUNDComenzo RL, Wally J, Kica G, Murray J, Ericsson T, Skinner M, Zhang Y. Clonal immunoglobulin light chain variable region germline gene use in AL amyloidosis: association with dominant amyloid-related organ involvement and survival after stem cell transplantation. Br J Haematol. 1999 Sep;106(3):744-51. doi: 10.1046/j.1365-2141.1999.01591.x. PMID 10468868
- BACKGROUNDComenzo RL, Zhang Y, Martinez C, Osman K, Herrera GA. The tropism of organ involvement in primary systemic amyloidosis: contributions of Ig V(L) germ line gene use and clonal plasma cell burden. Blood. 2001 Aug 1;98(3):714-20. doi: 10.1182/blood.v98.3.714. PMID 11468171
- BACKGROUNDChaulagain CP, Comenzo RL. How we treat systemic light-chain amyloidosis. Clin Adv Hematol Oncol. 2015 May;13(5):315-24. PMID 26352777
- BACKGROUNDDasari S, Theis JD, Vrana JA, Meureta OM, Quint PS, Muppa P, Zenka RM, Tschumper RC, Jelinek DF, Davila JI, Sarangi V, Kurtin PJ, Dogan A. Proteomic detection of immunoglobulin light chain variable region peptides from amyloidosis patient biopsies. J Proteome Res. 2015 Apr 3;14(4):1957-67. doi: 10.1021/acs.jproteome.5b00015. Epub 2015 Mar 20.