Real-World Outcomes of Patients with Monoclonal Gammopathy of Renal Significance.

Introduction

Monoclonal gammopathy of renal significance (MGRS) comprises a group of renal disorders caused by monoclonal immunoglobulins produced by non-malignant B-cell or plasma cell clones. The monoclonal proteins generated by these clones deposit in the kidneys and give rise to a spectrum of histopathological lesions that include amyloidosis (MGRS-A) as well as non-amyloid forms (MGRS-NA) [ 1 , 2 ]. MGRS is rare, affecting approximately 0.32%–1.5% of patients with MGUS [ 3 ]. Yet, it poses significant clinical challenges due to its heterogeneous presentation and the consequent delays in diagnosis. Patients with MGRS have notably better overall survival (OS) compared with those with multiple myeloma, yet their renal outcomes remain comparatively poor [ 1 ]. A significant proportion of patients progress to end-stage kidney disease if left untreated, making early diagnosis and intervention critical.

The diagnostic pathway for MGRS typically involves collaboration between nephrologists and haematologists. Often the diagnosis of MGRS is made by nephrologists after a renal biopsy, prompted by unexplained proteinuria, haematuria, or declining renal function in the presence of a monoclonal gammopathy. However, once diagnosed, the treatment is generally managed by the haematology team, who focus on targeting the underlying clonal disorder with therapies such as chemotherapy, immunomodulatory drugs, or anti-CD38 monoclonal antibodies [ 4 ]. While haematologists are well-versed in assessing haematologic responses, renal responses, which are critical for preserving kidney function, may be less frequently discussed with patients or integrated into treatment decision-making. This discrepancy highlights a gap in the management of MGRS, where the renal outcomes, which directly impact patient quality of life and survival, may not receive equal attention compared to haematologic outcomes [ 5 ]. Overall, outcomes in this cohort remain poorly understood. Real-world evidence on renal, haematologic, and survival outcomes is thus essential to better understand the natural history of MGRS, inform treatment decisions, and guide shared decision-making with patients.

Methodology

Study Design and Patient Selection

Patients were identified from a single tertiary centre on follow-up between January 2022 and October 2024. Inclusion criteria required a confirmed diagnosis of MGRS based on renal biopsy and the absence of criteria for multiple myeloma or other B-cell malignancies. This study was conducted as a service evaluation, registered under the institutional clinical audit framework, and did not require formal ethical approval.

Data Collection

Clinical data were extracted from electronic health records and included demographic information, renal parameters, haematologic markers, treatment details, and survival outcomes. Renal parameters consisted of estimated glomerular filtration rate (eGFR) and urine protein-to-creatinine ratio (PCR). eGFR was calculated using the Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI) equation based on serum creatinine levels. Haematologic markers included serum paraprotein levels, free light chains (kappa and lambda), and kappa/lambda ratio, recorded at the same time points as renal parameters.

Definition of Outcomes

Renal response was defined in the study as an eGFR increase ≥25% [ 6 ]. Haematologic response was categorised as per the IMWG criteria [ 7 ]. Both renal and haematologic responses were assessed at the end of the last treatment cycle.

Statistical Analysis

OS was compared between MGRS-A and MGRS-NA using Kaplan-Meier curves and the log-rank test. Survival time was calculated from the first treatment cycle to death or last follow-up (censored).

Renal response was compared between subgroups using Fisher’s exact test. Renal outcomes were analysed longitudinally using a linear mixed-effects model to assess eGFR trajectories across time points.

A univariate analysis was conducted to evaluate the association between baseline characteristics (included age, paraprotein, albumin, urine PCR, creatinine, calcium, kappa/lambda ratio, and eGFR at presentation) and clinical outcomes. The outcomes assessed were death, relapse (defined as a 25% increase in serum paraprotein from the nadir after the last cycle of treatment), renal response (eGFR increase ≥25%), and haematological response (≥VGPR). For continuous variables and binary outcomes, the Mann-Whitney U test was used to compare the distributions of each variable between outcome groups. Statistical analyses were performed using R (version 4.3.1). All tests were two-sided, and p values <0.05 were considered statistically significant.

Results

Baseline Characteristics

The study cohort included 17 patients, of whom 10 were classified as MGRS-A and 7 MGRS-NA (online suppl. Table S1; for all online suppl. material, see https://doi.org/10.1159/000553058 ). The median age at diagnosis was 65.0 years in MGRS-A (95% CI: 53.0–73.0) and 62.0 years in MGRS-NA (95% CI: 52.0–83.0) ( Table 1 ).

Treatment Regimens and Tolerability

Our current treatment framework effectively delivers standard-of-care therapies for patients with MGRS (online suppl. Table S1). A majority (94.1%, 16/17) received bortezomib, cyclophosphamide, and dexamethasone (VCD) chemotherapy, completing a median of 4 cycles (IQR: 3.0–5.0). Autologous stem cell transplantation was offered to 5 (29.4%) patients. One declined due to concerns around toxicity and quality of life.

Chemotherapy-related toxicities were frequent, affecting 94.1% (16/17) of patients. These included fatigue (23.5%), renal function decline (17.6%), and neuropathy (17.6%), among others (online suppl. Table S2). A dose reduction of Velcade (from 1.3 mg/m 2 to 1 mg/m 2 ) was undertaken in 1 individual after a slight deterioration in renal function, resulting in hyperkalaemia. Treatment was discontinued in 4 individuals due to toxicities, three of which were due to a significant deterioration in renal function.

Timing of Key Clinical Interventions

The median time from the first presentation with renal impairment to a confirmed MGRS diagnosis was 5.0 months (IQR: 3.6–13.0). Initial renal review occurred within a median of 1.1 months (IQR: 0.0–2.5). The median wait for a renal biopsy was 1.6 months (IQR: 0.4–3.5), and the interval from renal review to haematology consultation was 4.1 months (IQR: 1.5–6.4). Once patients were under haematology care, the initiation of treatment was a median of 1.0 month (IQR: 0.5–1.3).

Renal Outcomes over Time

Baseline renal function at the time of first renal decline showed notable differences ( Fig. 1 ). The median baseline eGFR was 49.0 mL/min/1.73 m 2 (95% CI: 15.0–77.0) in MGRS-A compared to 18.0 mL/min/1.73 m 2 (95% CI: 6.0–45.0, p < 0.05) in MGRS-NA. The proportion of patients with eGFR <30 mL/min/1.73 m 2 (CKD stage >3b) at baseline was 30% in MGRS-A (3/10) compared to 85.7% in MGRS-NA (6/7, p < 0.05).

A linear mixed-effects model, adjusted for age, showed a significant time × subgroup interaction ( p < 0.01), indicating that MGRS-NA patients had a lower starting eGFR and a steeper decline over time compared to MGRS-A patients. Specifically, MGRS-NA patients started with a median eGFR of 18.0 mL/min/1.73 m 2 (95% CI: 6.0–45.0) at first renal presentation, declining to 9.0 mL/min/1.73 m 2 by last follow-up (95% CI: 5.0–43.0), while MGRS-A patients started at 49.0 mL/min/1.73 m 2 (95% CI: 15.0–77.0) and declined to 42.0 mL/min/1.73 m 2 (95% CI: 9.0–77.0, p < 0.05).

The overall median time to haemodialysis in the cohort was not reached (95% CI: 53.77–NA). MGRS-A patients did not reach the median time to haemodialysis, while MGRS-NA patients had a median time to haemodialysis of 29.35 months (95% CI: 3.97–NA, p < 0.01) ( Fig. 2 a).

Haematologic and Renal Response Correlation

Renal response (eGFR increase ≥25%) was observed in 3 patients, all MGRS-A (3/10, p = 0.23). In terms of haematologic response, 57.1% of MGRS-NA patients (4/7) and 50% of MGRS-A patients (5/10) achieved ≥VGPR. Among these individuals, 22.2% (2/9) met the renal response criterion, compared to 14.3% (1/7) in the <VGPR group. However, this association was not statistically significant ( p = 0.57).

Abnormal κ/λ ratios were present pre-treatment in 70.0% (7/10) of MGRS-A and 85.7% (6/7) of MGRS-NA patients. Post-treatment, abnormal κ/λ ratios were seen in 30.0% (3/10) and 14.3% (1/7), respectively. Accordingly, κ/λ ratios were normal post-treatment in 70.0% (7/10) of MGRS-A and 85.7% (6/7) of MGRS-NA patients. Among those abnormal at baseline, this represents normalisation in 57.1% (4/7) of MGRS-A and 83.3% (5/6) of MGRS-NA patients. The median κ/λ ratio improved from 0.23 to 0.86 ( p < 0.05) in MGRS-A and from 3.35 to 1.98 ( p = 0.11) in MGRS-NA.

Paraprotein was quantifiable in 3/10 MGRS-A and 4/7 MGRS-NA patients at baseline. It was either detectable below quantification (<LOQ) or not detected in the remainder. Post-treatment, the proportion with paraprotein not detected was 3/10 in MGRS-A and 1/7 in MGRS-NA. Conversion from detectable paraprotein (quantifiable or <LOQ) to not detected occurred in 2 MGRS-A and 2 MGRS-NA patients, with no new post-treatment paraprotein detection. Among patients with quantifiable paraprotein at both time points ( n = 2 per subgroup), paraprotein decreased by a median of 68.9% in MGRS-A and 66.7% in MGRS-NA.

Overall Survival

OS was compared between MGRS-A and MGRS-NA using Kaplan-Meier curves and the log-rank test ( Fig. 2 b). During follow-up, deaths occurred in 28.6% of MGRS-NA patients (2/7) and 20% of MGRS-A patients (2/10). The median survival was not reached in the MGRS-A. The median survival for the MGRS-NA subgroup was 33 months (95% CI: 33–NA). The log-rank test showed no significant difference in survival between subgroups ( p = 0.33).

Time to Haematologic Relapse

Time to haematologic relapse was evaluated using Kaplan-Meier curves and the log-rank test ( Fig. 2 c). Overall, 47.1% of patients (8/17) relapsed, with 42.9% of MGRS-NA patients (3/7) and 50% of MGRS-A patients (5/10) experiencing relapse. The overall median time to relapse was 62 months (95% CI: 33–NA). For MGRS-NA, the median time to relapse was 51 months (95% CI: 33–NA), while for MGRS-A, it was 69 months (95% CI: 62-NA).

Univariate Analysis of Baseline Characteristics on Outcomes

Individual baseline characteristics at first renal decline were analysed to determine association with survival, relapse, renal, and haematological responses (online suppl. Table S3). In the overall cohort, creatinine was the only significant predictor of renal response ( p < 0.05), with higher creatinine levels associated with a reduced likelihood of renal response.

In the MGRS-NA subgroup, lower eGFR levels were associated with an increased likelihood of death and higher levels associated with haematological response ( p < 0.05, both). Urine PCR showed a trend toward significance where higher levels were associated with the risk of death ( p = 0.07). In the MGRS-A subgroup, creatinine was a significant predictor of renal response ( p < 0.05), with higher levels associated with a reduced likelihood of renal response. Creatinine also showed a trend with haematological response ( p = 0.05).

Discussion

The diagnosis of MGRS-NA has many difficulties primarily due to its smouldering nature and rarity [ 8 ]. MGRS-NA can progress insidiously and often without overt symptoms, leading to delayed diagnosis. In our cohort, the smouldering course of MGRS-NA and the challenges with making a firm diagnosis on renal histology likely contributed to the observed lower baseline eGFR and faster progression to haemodialysis compared to MGRS-A. This aligns with literature indicating that MGRS-NA lesions may present with subtle or atypical features, complicating early detection [ 8 , 9 ]. Additionally, the heterogeneity of renal presentations in our cohort (online suppl. Table S1) further complicates recognition of this condition. The rarity of MGRS-NA, accounting for a small fraction of renal biopsies, further exacerbates diagnostic delays as clinicians may not immediately consider it in the differential diagnosis of CKD.

Our study uniquely provides deep phenotypic data on renal responses, trends with treatment alongside survival, relapse, and time to dialysis, which are crucial for shared decision-making with patients when deciding to undertake treatment. eGFR at presentation is a predictor of death and response within this analysis. However, we were unable to further risk-stratify patients by providing cutoff values due to small sample size, a limitation stemming from the rarity of the disease. In comparison to the literature, elevated creatinine levels have been associated with poorer outcomes [ 8 ]. Other factors associated with prognosis in that study included age, beta-2-microglobulin, and dialysis at presentation.

Existing VCD-based treatment strategies, which largely mimic protocols established for myeloma, may not fully address the unique pathophysiology of renal injury in MGRS. As only a minority of patients achieved renal improvement, this raises the possibility that stabilisation of renal function rather than marked improvement might represent a more realistic and clinically meaningful goal in the management of MGRS. Emerging therapeutic agents, including clone-directed therapies such as daratumumab, show promise in this setting [ 10 ].

Our findings support the urgency of a joint renal-haematology service to prevent irreversible damage [ 11 ]. This is a finding also supported by the British Society for Haematology [ 4 ]. A joint service is needed to streamline referrals from nephrology for prompt haematology review, expedite renal biopsy, and initiating treatment with the aims of controlling the monoclonal protein and preserving renal function. Specialist renal histology service underpins the diagnosis, and we suggest that services have streamlined processes to refer kidney biopsy to specialist centres with high throughput and expertise. This is crucial given the rapid progression of renal injury in MGRS-NA.

Limitations in our study include the small sample size and mixed MGRS subtypes. This single-centre service evaluation included a cohort of 17 patients which limits statistical power and the ability to adjust for confounding. As a result, subgroup comparisons should be interpreted as exploratory and hypothesis-generating rather than definitive. Validation in larger multi-centre cohorts is therefore required. Haematologic monitoring was additionally constrained by the nature of monoclonal protein detection in MGRS. Specifically, paraprotein was frequently absent or below the limit of quantification which limited the utility of quantitative paraprotein kinetics and restricting numeric analyses to a small subset with measurable paraprotein at both time points. To mitigate this, we summarised paraprotein status categorically (quantifiable vs. <LOQ vs. not detected). We did not systematically capture formal patient-reported outcomes or quality-of-life measures related to treatment burden and symptomatic benefit; incorporation of these measures in future prospective studies will allow a more comprehensive assessment of patient-centred impact alongside biochemical and renal endpoints. Finally, MGRS-NA encompasses biologically and histologically diverse lesions and pooled comparisons against MGRS-A should be regarded as pragmatic “real-world” contrasts rather than lesion-specific inference. Our findings should therefore be analysed cautiously in this respect. However, the generalisability of the findings and trends may aid haematologists, nephrologists, and patients in appreciating the differences in renal presentation and outcomes in this rare cohort.

Conclusion

Our real-world analysis highlights the divergent renal trajectories and clinical outcomes observed in MGRS subtypes. By examining both renal and haematologic trajectories, we suggest that timely diagnosis and targeted treatment are critical, especially in patients presenting with more advanced renal impairment. These findings underscore the value of an integrated renal-haematology service to facilitate earlier referral, coordinated care, and potentially improved clinical outcomes. Continued efforts to refine diagnostic strategies, expedite intervention, and explore novel therapeutic options will be essential for optimising care in this challenging population.

Statement of Ethics

This study was conducted as a service evaluation, registered under the institutional clinical audit framework, and did not require formal ethical approval. Patients provide institutional consent for their anonymised data to be used for service evaluations and improvements.

Conflict of Interest Statement

The authors have no conflicts of interest to declare.

Funding Sources

The authors declare no funding was obtained or used for this study.

Author Contributions

G.G.: writing – original draft, data collection, and formal analysis. J.F. and D.K.: writing – conceptualisation and review and editing. P.C.: writing – review and editing.

Funding Statement

The authors declare no funding was obtained or used for this study.

Data Availability Statement

All data generated or analysed during this study are included in this published article and its supplementary information files.

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Associated Data

Supplementary Materials

Data Availability Statement

All data generated or analysed during this study are included in this published article and its supplementary information files.