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Table 3 Prognostic models combining liquid biopsy with other conventional parameters

From: Liquid biopsy by analysis of circulating myeloma cells and cell-free nucleic acids: a novel noninvasive approach of disease evaluation in multiple myeloma

Sample

Method

Model

Reference

MGUS

Slide-based immunofluorescence

Prognostic score for PFS: 0–3

1. Presence of CMMCs

2. M protein ≥ 2 g/L in the PB

3. Disease type: non-IgG heavy chain

[15]

SMM

Slide-based immunofluorescence

Prognostic score for TTP: 0–2

1. CMMCs > 5,000 × 106/L and/or > 5% cytoplasmic Ig-positive PCs

2. M protein spike ≥ 3 g/dL in the PB

[16]

NDMM

Slide-based immunofluorescence

Prognostic score for OS:

1. CMMC ≥ 4%

2. the BMPC labeling index (LI) ≥ 1%

[17]

NDMM

MFC (2-color)

Prognostic score (CMMC + ISS stage) for OS: 0–3

1. > 10 CMMCs/50,000 events at diagnosis

2. β2-microglobulin > 3.5 mg/L

3. Albumin < 3.5 g/dL

[19]

NDMM

MFC (2-color)

For PFS and OS:

 ≥ 41 CMMCs/50,000 events at diagnosis increased the stratification of NDMM with standard-risk cytogenetics but not of NDMM with high-risk cytogenetics

[21]

NDMM

MFC (2-color)

Prognostic score for PFS and OS:

1. Presence of CMMCs

2. R-ISS stage (R-ISSII)

[22]

MM with ASCT

MFC (2-color)

Prognostic score for PFS and OS: 0–2

1. Presence of CMMCs before ASCT

2. High-risk cytogenetics

[20]

MM with ASCT

MFC (6-color)

Prognostic score for OS:

1. Presence of CMMCs before ASCT

2. High-risk cytogenetics

[27]

NDMM

MFC (6-color)

Prognostic score for TTNT and OS:

1. ≥ 400 CMMCs/150,000 events (≥ 5 CMMCs/μL) at diagnosis

2. R-ISS stage (R-ISSII)

[28]

MM

MACS (CD138) combined with MFC (6-color)

Prognostic score for OS:

1. Presence of CMMCs

2. Presence of EM lesions

[35]

NDMM

MFC (7-color)

The PET-CMMC staging system for PFS and OS:

1. CMMCs ≥ 0.10% of the total mononuclear cells at diagnosis

2. Presence of > 3 focal lesions with or without EM disease in PET-CT

The PET-CMMC system combined with the R-ISS stage

The PET-CMMC system combined with high-risk cytogenetics

[32]

NDMM

MFC (7-color)

Nomogram for PFS and OS:

1. ≥ 0.038% CMMCs at diagnosis

2. Creatine and LDH levels

[33]

NDMM

MFC (7-color)

Prognostic score (CMMC + R-ISS) for PFS and OS:

1. ≥ 0.07% CMMCs (≥ 5 cells/μL) at diagnosis

2. R-ISS stage (R-ISSII)

Prognostic score (CMMC + MRD) for PFS and OS:

1. ≥ 0.07% CMMCs (≥ 5 cells/μL) at diagnosis

2. Premaintenance MRD status

[34, 71]

NDMM

MFC (8-color)

Prognostic score (CMMC + R-ISS) for PFS and OS:

1. ≥ 0.105% CMMCs at diagnosis

2. R-ISS stage (R-ISSIII)

[72]

MGUS, SMM, MM

MFC (10-color)

Risk stratification for PFS and OS:

1. ≥ 0.0035% CMMCs of total leukocytes at diagnosis

2. High LDH and/or β2-microglobulin > 5.5 mg/L

1. High CMMCs combined with Mayo risk stratification in MGUS

2. High CMMCs combined with IMWG risk stratification in SMM

3. High CMMCs combined with R-ISS in MM

[68]

NDMM

NGF

Prognostic score for PFS:

1. ≥ 0.1 CMMCs/μL of blood at diagnosis

2. sIF status (≥ VGPR or not)

Prognostic score for PFS:

1. ≥ 0.1 CMMCs/μL of blood at diagnosis

2. MRD status in the BM evaluated by NGF

[7]

NDMM

NGF

Prognostic score for PFS in all MM cohorts: 0–2

1. Presence of CMMCs after therapy

2. sIF status

Prognostic score for PFS in MM achieved CR/sCR: 0–2

1. Presence of CMMCs after therapy

2. MRD status in the BM evaluated by NGF

Prognostic score for PFS in longitudinal monitoring:

1. Changes of sIF status (− / − , − / + , + / + , + / −)

2. Changes of CMMC status (− / − , − / + , + / + , + / −)

[38]

NDMM

NGF

Prognostic score (CMMC + R-ISS) for PFS and OS: 0–4

1. ≥ 0.01% CMMCs (0.6 CMMCs/mL) at diagnosis

2. R-ISS stage (three factors)

[6]

RRMM

ULP-WGS

Stratification (cfDNA + IMWG response criteria) for PFS:

1. ≥ 10% TF in cfDNA after two cycles of treatment

2. IMWG response status (SD or PR)

[47]

SMM

/

Stratification (cfDNA + GEP70) for PFS and OS:

1. cfDNA > 25.2 ng/mL of plasma

2. GEP70 (high-risk or low-risk)

[9]

NDMM

NGS

Nomogram for PFS:

1. Age ≥ 65 years

2. DNA repair pathway mutation in ctDNA

3. Transcriptional regulation pathway mutation in ctDNA

[73]

MGUS, MM

RNA-seq

Ten-gene model in cf-mRNA: distinguish MM from MGUS and MGUS from non-cancer cases

AIDA, CA1, EPB42, HBG1, HBG2, CENPE, CPOX, and NUSAP1, NEK2, ELL2

[81]