Serum-free light chains combined with the Revised International Staging System could further distinguish the superior and inferior clinical outcome of multiple myeloma patients

The prognostic utility of dynamic risk stratification at disease progression in patients with multiple myeloma

OBJECTIVES

There may be a shift in risk stratification at progression compared to that at diagnosis in patients with multiple myeloma (MM). We aimed to evaluate whether re-staging and stage migration is of prognostic impact.

METHODS

Real-world data from the National Longitudinal Cohort of Hematologic Diseases-multiple myeloma were collected; 263 consecutive patients demonstrating disease progression were finally included. Staging at diagnosis and re-staging at progression were performed using the International Staging System (ISS) and Revised International Staging System (RISS).

RESULTS

Based on ISS re-staging, the median post-progression survival (mPPS) of patients with stage I, II, and III was 44.2, 21.7, and 11.6 months, respectively (P < 0.0001). Based on RISS re-staging, the mPPS of patients with stage I, II, and III was 50.3, 22.2, and 11.4 months, respectively (P < 0.0001). The mPPS in patients with improved, maintained, and deteriorated ISS stage migration from diagnosis was 33.6, 20.9, and 16 months, respectively (P = 0.0051) and that with improved, maintained, and deteriorated RISS stage migration was 48.4, 23.1, and 13.9 months, respectively (P < 0.001). Compared to patients with maintained or improved disease stage, those with deteriorated ISS/RISS migration showed significantly higher incidence of Del(17P) at progression and worse PPS. Multivariate analyses indicated both re-staging and stage migration by ISS/RISS at progression were independent predictors for PPS.

CONCLUSIONS

We demonstrated that ISS/RISS re-staging showed superior prognostic utility over ISS/RISS staging in predicting PPS. Patients with deteriorated stage migration or maintained advanced stage at progression may need more individualized treatment.

Retrospective Analysis of Serum Free Light Chain Reference Intervals and Risk for Monoclonal Gammopathy Suggests Different Limits Than Those in International Guidelines

OBJECTIVES

Recent reference interval studies of the serum free light chain (FLC) test using contemporary instruments display divergence with the diagnostic range generally adopted as the international standard. In this study, we perform a retrospective reference interval analysis with risk predictions for monoclonal gammopathy.

METHODS

Retrospective laboratory and clinical data for 8,986 patients were included in the study. Reference intervals were generated against a set of inclusion/exclusion criteria for two time periods representing the use of different instruments. The presence of monoclonal gammopathy was established from diagnostic test interpretations and EHR diagnosis codes in the patient problem lists and medical history.

RESULTS

The 95% FLC ratio reference intervals were 0.76-2.38 for SPAPLUS®, and 0.68-1.82 for Optilite® instruments. These intervals varied considerably from the current diagnostic range of 0.26-1.65 and mapped approximately to the FLC ratios beyond which risk of monoclonal gammopathy substantially increased.

CONCLUSIONS

These findings corroborate recent reference interval studies and support recommendations for independent re-evaluation of intervals by institutions as well as an update of international guidelines.

A prognostication system based on clinical parameters and [18F]-FDG PET/CT in patients with newly diagnosed multiple myeloma

PURPOSE

This study aimed to assess prognosis of patients with newly diagnosed multiple myeloma (NDMM) by combining [¹⁸F]-FDG positron emission tomography (PET)/CT parameters and clinical indices.

METHODS

Clinical data and PET/CT parameters of 133 NDMM patients were retrospectively analyzed for associations between clinical indices and PET/CT parameters. Independent predictors of progression-free survival (PFS) and overall survival (OS) were determined. A new prognostic prediction system (NPPS) was constructed based on our findings. Prediction effectiveness was compared among the NPPS, International Staging System (ISS), Revised ISS (R-ISS), and R2-ISS.

RESULTS

Prevalence of elevated β2-microglobulin, serum creatinine (sCr), serum calcium (sCa), and C-reactive protein concentrations was higher in patients with higher SUVmax (≥ 5.3). Prevalence of elevated sCa, sCr, and extramedullary disease (EMD) was higher in patients with a higher number of focal lesions (≥ 10). SUVmax, serum free-light chain (sFLC) ratio, and EMD were independent predictors of PFS and OS. The NPPS used SUVmax, sFLC ratio, and EMD could effectively predict OS and was more effective at prognostication than the ISS, R-ISS, and R2-ISS.

CONCLUSIONS

[¹⁸F]-FDG PET/CT parameters play a significant role in predicting prognosis in NDMM patients. The NPPS based on SUVmax, sFLC ratio, and EMD outperformed the ISS, R-ISS, and R2-ISS in prognostication.

The role of serum-free light chain ratios in the prediction of poor prognosis in multiple myeloma patients: a systematic review and meta-analysis

BACKGROUND

The association between the serum free light chain (sFLC) ratio and the prognosis of multiple myeloma (MM) patients is controversial.

AIM

The purpose of this study is to explore the relationship between the sFLC ratio and the prognosis of MM patients through meta-analysis.

METHODS

Online public databases were searched to find relevant studies. The retrieval time is limited from the establishment of the database to July 2021. The overall survival (OS) and progression-free survival (PFS) rates were compared. The results were described using hazard ratio (HR) and a 95% confidence interval (CI). Qualitative studies were also included.

RESULTS

A total of 9 studies involving 2864 participants were included. A pooled analysis based on four studies including newly-diagnosed MM patients, demonstrated that an abnormal sFLC ratio was associated with poor outcomes of OS (HR = 1.82, 95% CI: 1.15-2.90) and PFS (HR = 1.87, 95% CI: 1.20-2.90). Three qualitative studies showed that an abnormal sFLC ratio was related with poor outcomes of OS (studies all included newly diagnosed MM patients) and PFS (two studies included newly-diagnosed MM patients and one study included non-newly-diagnosed MM patients). Two studies stated that the sFLC ratio is not associated with OS (both studies included non-newly-diagnosed MM patients) and one study reported that the sFLC ratio is not associated with PFS (study included non-newly-diagnosed MM patients).

CONCLUSION

sFLC ratio could be used to predict adverse outcomes in newly-diagnosed MM patients, but is not suitable for non-newly-diagnosed MM patients.

Role of serum-free light chain assay for defining response and progression in immunoglobulin secretory multiple myeloma

The International Myeloma Working Group (IMWG) guidelines recommend using electrophoresis and immunofixation to define response and progressive disease (PD) in immunoglobulin (Ig) secretory multiple myeloma (Ig-MM), whereas the role of serum-free light chain (sFLC) is controversial. We retrospectively analyzed the value of adding sFLC assays in the definition of response and PD according to IMWG criteria in 339 Ig-MM patients treated with a first-line novel agent-based therapy (median follow-up 54 months). sFLC PD was defined according to conventional criteria plus increased sFLC levels, or sFLC escape (sFLCe); progression/sFLCe-free survival (ePFS) was the time from the start of treatment to the date of first PD or sFLCe, or death; overall survival after PD/sFLCe (OS after Pe) was the time from first PD or sFLCe to the date of death. 148 (44%) patients achieved a complete response and 198 (60%) a normal sFLC ratio (sFLCR). sFLCR normalization was an independent prognostic factor for extended PFS (HR = 0.46, p = 0.001) and OS (HR = 0.47, p = 0.006) by multivariable analysis. 175 (52%) patients experienced PD according to the IMWG criteria, whereas 180 (53%) experienced PD or sFLCe. Overall, a sFLCe was observed in 31 (9%) patients. Median PFS and ePFS were both equal to 36 (95% CI = 32-42, and 32-40, respectively) months. sFLC PD adversely affected the OS after Pe compared to PD with increasing monoclonal Ig only (HR = 0.52, p = 0.012). Our results support the inclusion of the sFLC assay for defining response and PD in Ig-MM.

Patient-Derived Extracellular Vesicles Proteins as New Biomarkers in Multiple Myeloma - A Real-World Study

Multiple myeloma (MM) is a hematological malignancy of clonal antibody–secreting plasma cells (PCs). MM diagnosis and risk stratification rely on bone marrow (BM) biopsy, an invasive procedure prone to sample bias. Liquid biopsies, such as extracellular vesicles (EV) in peripheral blood (PB), hold promise as new minimally invasive tools. Real-world studies analyzing patient-derived EV proteome are rare. Here, we characterized a small EV protein content from PB and BM samples in a cohort of 102 monoclonal gammopathies patients routinely followed in the clinic and 223 PB and 111 BM samples were included. We investigated whether EV protein and particle concentration could predict an MM patient prognosis. We found that a high EV protein/particle ratio, or EV cargo &gt;0.6 µg/108 particles, is related to poorer survival and immune dysfunction. These results were supported at the protein level by mass spectrometry. We report a set of PB EV-proteins (PDIA3, C4BPA, BTN1A1, and TNFSF13) with a new biomarker potential for myeloma patient outcomes. The high proteomic similarity between PB and BM matched pairs supports the use of circulating EV as a counterpart of the BM EV proteome. Overall, we found that the EV protein content is related to patient outcomes, such as survival, immune dysfunction, and possibly treatment response.

Employment of Artificial Intelligence Based on Routine Laboratory Results for the Early Diagnosis of Multiple Myeloma

Objective

In order to enhance the detection rate of multiple myeloma and execute an early and more precise disease management, an artificial intelligence assistant diagnosis system is developed.

Methods

4,187 routine blood and biochemical examination records were collected from Shengjing Hospital affiliated to China Medical University from January 2010 to January 2020, which include 1,741 records of multiple myeloma (MM) and 2,446 records of non-myeloma (infectious diseases, rheumatic immune system diseases, hepatic diseases and renal diseases). The data set was split into training and test subsets with the ratio of 4:1 while connecting hemoglobin, serum creatinine, serum calcium, immunoglobulin (A, G and M), albumin, total protein, and the ratio of albumin to globulin data. An early assistant diagnostic model of MM was established by Gradient Boosting Decision Tree (GBDT), Support Vector Machine (SVM), Deep Neural Networks (DNN), and Random Forest (RF). Out team calculated the precision and recall of the system. The performance of the diagnostic model was evaluated by using the receiver operating characteristic (ROC) curve.

Results

By designing the features properly, the typical machine learning algorithms SVM, DNN, RF and GBDT all performed well. GBDT had the highest precision (92.9%), recall (90.0%) and F1 score (0.915) for the myeloma group. The maximized area under the ROC (AUROC) was calculated, and the results of GBDT (AUC: 0.975; 95% confidence interval (CI): 0.963–0.986) outperformed that of SVM, DNN and RF.

Conclusion

The model established by artificial intelligence derived from routine laboratory results can accurately diagnose MM, which can boost the rate of early diagnosis.