Visual Abstract
Keywords: chronic renal disease, glomerulonephritis, mortality, Mpgn (membranoproliferative glomerulonephritis), renal progression
Abstract
Background
Little is known about the prognostic significance of monoclonal gammopathy of undetermined and renal significance (MGUS and MGRS) in patients with CKD. The objective of this study was to determine the clinical and kidney outcomes of patients with CKD with either MGUS or MGRS compared with those with CKD without MGUS or MGRS.
Methods
We conducted a retrospective cohort study from 2013 to 2018. Patients who had both CKD diagnosis and monoclonal testing were identified. Patients were divided into MGRS, MGUS, and no monoclonal gammopathy groups. Cumulative incidence functions and Cox proportional hazards regression were used to model time to event data and to evaluate the association between monoclonal gammopathy status and risk of kidney failure, with death treated as a competing risk.
Results
Among 1535 patients, 59 (4%) had MGRS, 648 (42%) had MGUS, and 828 (54%) had no monoclonal gammopathy. Unadjusted analysis showed that compared with no monoclonal gammopathy patients, patients with MGRS were at higher risk of kidney failure (hazard ratio [HR] [95% confidence interval]: 2.5 [1.5 to 4.2] but not patients with MGUS (HR [95% confidence interval]: 1.3 [0.97 to 1.6]), after taking death into account as a competing risk. However, in the multivariable analysis, after adjusting for age, sex, eGFR, proteinuria, and Charlson Comorbidity Index, the risk of progression to kidney failure (with death as competing risk) in the MGRS group was no longer statistically significant (HR: 0.9 [0.5 to 1.8]). The same was also true for the MGUS group compared with the group with no monoclonal gammopathy (HR: 1.3 [0.95 to 1.6]). When evaluating the association between MGUS/MGRS status and overall survival, MGRS was significantly associated with mortality in fully adjusted models compared with the group with no monoclonal gammopathy, while MGUS was not.
Conclusions
After adjusting for traditional risk factors, MGUS/MGRS status was not associated with a greater risk of kidney failure, but MGRS was associated with a higher risk of mortality compared with patients with no monoclonal gammopathy.
Introduction
Monoclonal gammopathy is characterized by the excessive production of a monoclonal protein and results from the abnormal clonal proliferation of cells from the B-cell lineage, including plasma cells and B lymphocytes. These clonal cells are typically associated with an underlying hematologic malignancy, such as multiple myeloma.1–3 When their population size is small, however, they can remain quiescent for a long time without evidence of organ damage. In this instance, the condition is called monoclonal gammopathy of undetermined significance (MGUS), which does not require treatment. Monoclonal proteins, however, can affect various organs—most commonly the kidneys, depending on their chemical characteristics.3,4 In this instance, the condition is called monoclonal gammopathy of renal significance (MGRS) provided that the kidney injury caused by the monoclonal protein does not meet the traditional criteria for an overt hematologic malignancy.2
The incidences of both MGUS and CKD increase with advancing age, and MGUS is associated with shorter overall survival compared with the general population.5–8 MGUS is found in 3% of people age 50 years or older, and its rate increases up to 8% in those age 85 years or older.5 Similarly, data from the Centers for Disease Control and Prevention indicate that CKD is more common in the elderly population. Close to 40% of people age 65 years or older have CKD compared with 6% of those age 18–44 years.6 As a result, it is not surprising that MGUS has been found to be more prevalent in patients with CKD compared with the general population (10%–12%).9,10 Monoclonal testing is commonly performed as part of the workup for patients who present with CKD to identify those whose CKD may be related to an underlying monoclonal gammopathy.11,12 In clinical practice, the significance of a positive monoclonal test in the setting of CKD remains uncertain. To the best of our knowledge, there have been only two published studies thus far that assessed the prognostic significance of MGUS on risk of kidney failure or mortality in patients with CKD, both of which did not find any association between MGUS and kidney failure or death.9,10 However, neither of these studies included patients with MGRS when evaluating the role of monoclonal protein on kidney disease progression and mortality. In addition, the patients did not undergo a comprehensive monoclonal study evaluation. The objective of this study was to evaluate kidney and mortality outcomes of patients with monoclonal gammopathy (including both MGUS and MGRS) compared with those without either condition in a cohort of patients with CKD who have undergone comprehensive monoclonal testing.
Methods
Patient Selection
This study was approved by the Mayo Clinic Institutional Review Board (ID: 20-001583). We identified our cohort by searching for all diagnostic indices of CKD in adult patients seen at Mayo Clinic in Rochester, Minnesota, from January 1, 2013, to December 31, 2018. We further confirmed CKD diagnosis via manual chart review. We defined CKD as having either an eGFR of <60 ml/min per 1.73 m2 on the basis of the Chronic Kidney Disease Epidemiology Collaboration equation or, among patients with an eGFR of ≥60 ml/min per 1.73 m2, having evidence of proteinuria, which was defined as an estimated 24-hour urine protein of >300 mg. Monoclonal testing was considered completed if it included serum protein electrophoresis (SPEP), serum immunofixation, urine protein electrophoresis (UPEP), urine immunofixation, and/or immunoglobulin kappa and lambda free light chains.
Inclusion/Exclusion Criteria
Inclusion criteria included age older than 18 years, presence of CKD, and monoclonal testing completed within 6 months of their CKD diagnosis. Exclusion criteria included absence of research authorization, concurrent active hematologic malignancies at the time of CKD diagnosis (including MM, Waldenstrom macroglobulinemia, leukemia, and lymphoma), those who were already on maintenance dialysis, were kidney transplant recipients, or had no follow-up available after their CKD diagnosis (Figure 1).
Figure 1.
Flow chart of inclusion and exclusion criteria for the cohort. MGRS, monoclonal gammopathy of renal significance; MGUS, monoclonal gammopathy of undetermined significance.
Data Collection and Measurements
Data including patient demographics, clinical characteristics, and comorbidities were obtained via manual chart review at baseline. The Charlson Comorbidity Index (CCI) (see Supplemental Material) was calculated as reported previously.13 eGFR values were also collected at baseline and during the patient's first year of follow-up. Hematologic parameters were also collected at baseline among patients with monoclonal gammopathy. For this study, baseline was defined as the date of CKD diagnosis. Kidney failure was defined as the initiation of KRT, including in-center hemodialysis, peritoneal dialysis, and home hemodialysis, or receipt of a kidney transplant, whichever came first. eGFR was calculated using the Chronic Kidney Disease Epidemiology Collaboration equation.
Patients were categorized as having MGUS when they had a positive monoclonal testing defined by either a detectable monoclonal protein in the blood on SPEP and/or immunofixation or in the urine detected by UPEP and/or immunofixation or an abnormal kappa to lambda free light chain ratio without meeting criteria for a hematological malignancy (Supplemental Material). For those with an eGFR <60 ml/min per 1.73 m2, a free light chain ratio outside the range of 0.37 and 3.10 was considered abnormal.14 Patients were then categorized as having MGRS when they had a positive monoclonal testing as defined above in addition to a kidney lesion(s) related to monoclonal protein as defined by the consensus report of the International Kidney and Monoclonal Gammopathy Research Group.15
Statistical Methods
Continuous variables were summarized as mean±SD for normally distributed and median (Q1, Q3) for non-normally distributed data, and categorical variables were summarized as No. (%). Comparisons of baseline characteristics across monoclonal gammopathy groups were evaluated using Kruskal–Wallis tests for continuous variables and chi-squared tests or Fisher exact test, as appropriate, for categorical variables.
Cumulative incidence plots were estimated using cumulative incidence functions, and models evaluating the association between monoclonal gammopathy status and risk of kidney failure were fit using Cox proportional hazards regression, with death treated as a competing risk. Additional Cox regression models were also fit to assess risk of overall survival. The patient group without monoclonal gammopathy was considered as the reference level for all models, and corresponding hazard ratios (HRs) and 95% confidence intervals were reported. Models were fit both unadjusted and adjusted for age, sex, eGFR, proteinuria, and the weighted CCI. Functional forms of all covariates were assessed for nonlinearity by modeling natural cubic spline functions using three knots placed at the fifth, 50th, and 95th distribution percentiles. Covariates without evidence of nonlinear associations were fit as linear terms in the final models, while covariates with evidence of nonlinear associations were fit as natural cubic spline functions in the models (eGFR).
Changes in eGFR over 1 year post-CKD diagnosis were evaluated using linear mixed models with random intercepts to account for repeated measurements within patients and fixed effects for all other covariates. eGFR changes were assessed within each monoclonal gammopathy group using group×time interactions to evaluate whether changes in eGFR over time differed across monoclonal gammopathy groups.
Results
Patients' Baseline Demographic and Clinical Characteristics
After applying inclusion and exclusion criteria, a total of 1535 patients were included in the final cohort for analysis with a mean (±SD) follow-up time of 5 (±0.1) years (Figure 1). Among them, 59 (4%) had MGRS, 648 (42%) had MGUS, and 828 (54%) did not have evidence of monoclonal gammopathy (no monoclonal gammopathy group). Baseline characteristics by monoclonal status are reported in Table 1. The mean (±SD) age of the cohort was 72 (±12) years, with patients with MGRS tending to be younger than patients with MGUS or no monoclonal gammopathy patients. Most patients were male (58%) and White (97%). Patients with MGRS had lower eGFR levels and higher serum creatinine levels compared with patients with MGUS or no monoclonal gammopathy patients. In addition, patients in the MGRS group had higher proteinuria at baseline, with 41% having nephrotic range proteinuria and a median proteinuria of 2.5 (1.4–5.5) g/24 hours among those who had proteinuria. The most common medical comorbidities in the cohort were hypertension (77%), diabetes mellitus (34%), and coronary artery disease (30%). Patients in the MGRS group had an overall lower weighted CCI score compared with the other groups (CCI=0 for 34% of MGRS group, 17% of MGUS group, and 13% of no monoclonal gammopathy group, P < 0.001).
Table 1.
Baseline characteristics of patients with CKD, overall and by monoclonal gammopathy status
| Baseline Characteristic | All (N=1535) | No Monoclonal Gammopathy (n=828) | MGUS (n=648) | MGRS (n=59) |
|---|---|---|---|---|
| Age, yr | 72 ± 12 | 73 ± 13 | 72 ± 11 | 66 ± 11 |
| Male sex, No. (%) | 888 (58) | 446 (54) | 398 (61) | 44 (75) |
| White race, No. (%) | 1481 (97) | 812 (98) | 618 (95) | 51 (86) |
| Serum creatinine, mg/dl | 1.4 (1.2, 1.7) | 1.4 (1.2, 1.7) | 1.4 (1.2, 1.7) | 1.7 (1.3, 2.8) |
| eGFR, ml/min per 1.73 m2 | 44 ± 16 | 43 ± 15 | 45 ± 16 | 44 ± 25 |
| Proteinuria level, mg/24 h, No. (%) | — | — | — | — |
| <300 | 671/1387 (48) | 396/786 (50) | 273/542 (50) | 2 (3) |
| 300–1500 | 464/1387 (34) | 260/786 (33) | 187/542 (35) | 17 (29) |
| 1500–3500 | 139/1387 (10) | 78/786 (10) | 45/542 (8) | 16 (27) |
| ≥3500 | 113/1387 (8) | 52/786 (7) | 37/542 (7) | 24 (41) |
| Proteinuriaa | 806 (437, 2086) | 830 (482, 2064) | 619 (358, 1537) | 2499 (1373, 5526) |
| Hypertension, No. (%) | 1176/1534 (77) | 669 (81) | 479/647 (74) | 28 (48) |
| Congestive heart failure, No. (%) | 366/1533 (24) | 204 (25) | 157/646 (24) | 5 (9) |
| Liver disease, No. (%) | 138 (9) | 56 (7) | 81 (13) | 1 (2) |
| Stroke, No. (%) | 129/1534 (8) | 62 (8) | 65/647 (10) | 2 (3) |
| Diabetes, No. (%) | 521/1533 (34) | 317 (38) | 199/646 (31) | 5 (9) |
| Cancer, No. (%) | 312 (20) | 154 (19) | 146 (23) | 12 (20) |
| Coronary artery disease, No. (%) | 463/1530 (30) | 270 (33) | 185/645 (29) | 8 (14) |
| Peripheral vascular disease, No. (%) | 98/1533 (6) | 45 (5) | 52/646 (8) | 1 (2) |
| Dementia, No. (%) | 38/1534 (2) | 23 (3) | 15/647 (2) | 0 (0) |
| COPD, No. (%) | 169/1534 (11) | 90 (11) | 77/647 (12) | 2 (3) |
| Autoimmune or connective tissue disease, No. (%) | 237 (15) | 120 (15) | 111 (17) | 6 (10) |
| CCI (weighted), No. (%) | — | — | — | — |
| 0 | 240 (16) | 111 (13) | 109 (17) | 20 (34) |
| 1 | 239 (16) | 131 (16) | 101 (16) | 7 (12) |
| 2 | 363 (24) | 197 (24) | 148 (23) | 18 (31) |
| 3+ | 693 (45) | 389 (47) | 290 (45) | 14 (24) |
Continuous variables are reported as mean±SD or median (Q1, Q3), and categorical variables are reported as number (%). CCI, Charlson Comorbidity Index; COPD, chronic obstructive pulmonary disease; MGRS, monoclonal gammopathy of renal significance; MGUS, monoclonal gammopathy of undetermined significance.
Proteinuria was calculated among patients who had nonmissing proteinuria values ≥300 units (390 patients in the no MGUS group, 269 patients in the MGUS group, and 57 patients in the MGRS group).
Patients' Baseline Hematologic Characteristics
Among patients with monoclonal gammopathy, baseline hemoglobin was similar between groups (12.6 [10.9, 14.0] g/dl versus 12.4 [10.6, 13.8] g/dl for MGUS and MGRS, respectively, P = 0.57). The most common monoclonal protein identified on SPEP with serum immunofixation was IgG (64%) followed by IgM (21%) for heavy chain and kappa (57%) followed by lambda (43%) for light chain. The median serum M-spike was 0.0 (0.0–0.7) in the MGRS group and 0.0 (0.0–0.0) in the MGUS group. Most of these patients did not undergo bone marrow biopsy. Among those who did (175 [25%]), 50% of them were found to have 1%–5% plasma cells on biopsy.
Etiology of CKD
A total of 213 kidney biopsies were performed. All biopsies included immunofluorescence and electron microscopy studies in addition to light microscopy. As expected, all 59 patients with MGRS underwent a kidney biopsy to establish the diagnosis. The different MGRS lesions are presented in Supplemental Table 1. Of those patients, 54 (92%) had a glomerular disease and five (9%) had tubulointerstitial disease as their CKD etiology type. Comparisons of CKD etiology type among the remaining 154 patients with MGUS and no monoclonal gammopathy, overall and stratified by kidney biopsy status, are presented in Supplemental Table 2. There were no differences in the etiology of CKD between the MGUS and no monoclonal gammopathy groups among patients who underwent a kidney biopsy; however, among those who did not undergo a kidney biopsy, more patients had their CKD etiology type attributed to diabetes mellitus in the no monoclonal gammopathy group than the MGUS group, and there were more patients with unclear etiology in the MGUS group than the no monoclonal gammopathy groups (P < 0.001). Among those who did not undergo a kidney biopsy in the MGUS group (n=583), 225 patients had unclear etiology, and of them, 153 patients (68%) had either proteinuria >1500 mg/d, hematuria, or a free light chain ratio >4, all of which are considered risk factors for finding an MGRS lesion.16
Monoclonal Gammopathy Status and Incidence of Kidney Failure
Among the 1535 patients in the cohort, 249 (16%) developed kidney failure, and 389 (25%) patients died without developing kidney failure during the follow-up period. In the unadjusted model, the risk of progression to kidney failure with death as competing risk was higher in the MGRS group compared with the group with no monoclonal gammopathy (HR: 2.5 [95% confidence interval, 1.5 to 4.2]; P < 0.001) but not in the MGUS group compared with no monoclonal gammopathy group (HR: 1.3 [0.97 to 1.6]; P = 0.088) (Table 2). Risk of kidney failure was also higher in the MGRS group compared with the MGUS group (HR: 2.0 [1.2 to 3.4]). The cumulative incidence of kidney failure with death as a competing risk among the three groups is shown in Figure 2. Cumulative incidence estimates by year, both overall and by group status, are also provided in Supplemental Table 3. In the multivariable analysis, after adjusting for age, sex, eGFR, proteinuria, and weighted CCI, the risk of progression to kidney failure (with death as competing risk) in the MGRS group was no longer statistically significant (HR: 0.9 [0.5 to 1.8]; P = 0.78). The same was also true for the MGUS group compared with the group with no monoclonal gammopathy (HR: 1.3 [0.95 to 1.6], P = 0.11), both overall and after stratifying by type of monoclonal protein in the MGUS group (n=400 IgG, n=112 IgM, n=66 IgA) (data not shown).
Table 2.
Unadjusted and adjusted associations between monoclonal gammopathy status and risk of kidney failure, with death as a competing risk
| Model | MGUS | MGRS | ||
|---|---|---|---|---|
| Adjusting Variable | No. | Events | HR (95% CI) | HR (95% CI) |
| Unadjusted | 1535 | 249 | 1.25 (0.97 to 1.62) | 2.53 (1.52 to 4.24) |
| Age | 1535 | 249 | 1.24 (0.96 to 1.61) | 2.02 (1.18 to 3.44) |
| Sex | 1535 | 249 | 1.26 (0.97 to 1.63) | 2.57 (1.53 to 4.31) |
| eGFR | 1535 | 249 | 1.38 (1.06 to 1.79) | 1.76 (0.94 to 3.31) |
| Proteinuriaa | 1387 | 232 | 1.31 (1.00 to 1.72) | 0.73 (0.41 to 1.32) |
| Weighted CCI | 1535 | 249 | 1.20 (0.93 to 1.55) | 2.92 (1.67 to 5.11) |
| Age, sex, eGFR, proteinuriaa | 1387 | 232 | 1.37 (1.04 to 1.80) | 0.82 (0.42 to 1.64) |
| Age, sex, eGFR, proteinuriaa, CCI | 1387 | 232 | 1.25 (0.95 to 1.64) | 0.91 (0.45 to 1.83) |
Models were fit using Cox proportional hazards regression with kidney failure as the event of interest and death treated as a competing risk. CCI, Charlson Comorbidity Index; CI, confidence interval; HR, hazard ratio; MGRS, monoclonal gammopathy of renal significance; MGUS, monoclonal gammopathy of undetermined significance.
148 patients were missing their proteinuria values and so were removed from analysis.
Figure 2.
Cumulative incidence of kidney failure with death as a competing risk, by monoclonal gammopathy status.
Given the concern that some patients in the MGUS group may have had an undiagnosed MGRS (as 68% of patients with MGUS without a kidney biopsy and unclear CKD etiology had at least one risk factor for having an MGRS lesion), a sensitivity analysis was also performed restricting to the 213 patients who had undergone a kidney biopsy to diagnose the cause of their CKD (see Figure 3 and Table 3). Of them, there were 89 patients in the no monoclonal gammopathy group, 65 in the MGUS group, and 59 in the MGRS group. In both unadjusted and multivariable analyses, no significant differences in the risk of progression to kidney failure with death as competing risk were observed among the three groups.
Figure 3.
Cumulative incidence of kidney failure with death as a competing risk, by monoclonal gammopathy status, among the N=213 patients who underwent a kidney biopsy.
Table 3.
Unadjusted and adjusted associations between monoclonal gammopathy status and risk of kidney failure, with death as a competing risk, among the N=213 patients who underwent a kidney biopsy
| Model | MGUS | MGRS | ||
|---|---|---|---|---|
| Adjusting Variable | No. | Events | HR (95% CI) | HR (95% CI) |
| Unadjusted | 213 | 81 | 1.11 (0.67 to 1.83) | 0.79 (0.45 to 1.39) |
| Age | 213 | 81 | 1.14 (0.70 to 1.86) | 0.78 (0.44 to 1.38) |
| Sex | 213 | 81 | 1.07 (0.62 to 1.82) | 0.75 (0.41 to 1.38) |
| eGFR | 213 | 81 | 1.26 (0.74 to 2.15) | 0.85 (0.43 to 1.66) |
| Proteinuriaa | 212 | 80 | 1.14 (0.70 to 1.86) | 0.65 (0.36 to 1.17) |
| CCI | 213 | 81 | 1.19 (0.72 to 1.96) | 0.81 (0.44 to 1.48) |
| Age, sex, eGFR, proteinuriaa | 212 | 80 | 1.29 (0.78 to 2.15) | 0.79 (0.39 to 1.57) |
| Age, sex, eGFR, proteinuriaa, CCI | 212 | 80 | 1.38 (0.84 to 2.26) | 0.81 (0.40 to 1.65) |
Models were fit using Cox proportional hazards regression with kidney failure as the event of interest and death treated as a competing risk. CCI, Charlson Comorbidity Index; CI, confidence interval; HR, hazard ratio; MGRS, monoclonal gammopathy of renal significance; MGUS, monoclonal gammopathy of undetermined significance.
1 patient was missing their proteinuria values and so was removed from analysis.
Monoclonal Gammopathy Status and Mortality
When evaluating the association between monoclonal gammopathy status and overall survival, MGRS was significantly associated with mortality in the fully adjusted model compared with the group with no monoclonal gammopathy, while MGUS was not associated with higher mortality (Figure 4 and Table 4). Causes of death by monoclonal gammopathy status are reported in Supplemental Table 4. Among the 389 patients who died during follow-up, the cause of death could not be determined in 65 (17%) of these individuals. In the remaining 324 patients, death due to cardiovascular disease was the most common (n=115, 35%), followed by malignancy (n=49, 15%) and infection (n=46, 14%). In the MGRS group, the most common cause of death was complication from AL amyloidosis (n=10, 63%), followed by infection (n=3, 19%).
Figure 4.
Cumulative incidence of death by monoclonal gammopathy status.
Table 4.
Unadjusted and adjusted associations between monoclonal gammopathy status and risk of death
| Model | MGUS | MGRS | ||
|---|---|---|---|---|
| Adjusting Variable | No. | Events | HR (95% CI) | HR (95% CI) |
| Unadjusted | 1535 | 389 | 1.01 (0.82 to 1.23) | 1.45 (0.83 to 2.56) |
| Age | 1535 | 389 | 1.05 (0.85 to 1.29) | 2.00 (1.11 to 3.61) |
| Sex | 1535 | 389 | 0.99 (0.81 to 1.22) | 1.39 (0.79 to 2.46) |
| eGFR | 1535 | 389 | 1.02 (0.83 to 1.25) | 1.41 (0.80 to 2.49) |
| Proteinuriaa | 1387 | 351 | 0.95 (0.76 to 1.19) | 1.44 (0.80 to 2.61) |
| CCI | 1535 | 389 | 1.01 (0.816 to 1.238) | 2.04 (1.13 to 3.67) |
| Age, sex, eGFR, proteinuriaa | 1387 | 351 | 0.99 (0.79 to 1.24) | 1.75 (0.94 to 3.26) |
| Age, sex, eGFR, proteinuriaa, CCI | 1387 | 351 | 0.95 (0.76 to 1.19) | 2.49 (1.35 to 4.59) |
Models were fit using Cox proportional hazards regression with death as the event of interest. CCI, Charlson Comorbidity Index; CI, confidence interval; HR, hazard ratio; MGRS, monoclonal gammopathy of renal significance; MGUS, monoclonal gammopathy of undetermined significance.
148 patients were missing their proteinuria value.
Monoclonal Gammopathy Status and Change in eGFR in First Year
Change in eGFR over the first year was also evaluated among the three groups. Overall, patients had a median of two follow-up eGFR measurements within 1 year of baseline. Change in eGFR over time was not found to be significantly different among the three groups (Supplemental Figure 1).
Discussion
This study is the first to evaluate the association between monoclonal gammopathy and kidney disease progression and mortality in patients with CKD on the basis of kidney involvement related to monoclonal gammopathy (MGUS and MGRS). Of the 101,047 adult patients with CKD diagnosis and no active hematologic malignancy and with research authorization, only 2777 of them (3%) underwent monoclonal testing. This finding indicates that in most patients with CKD, monoclonal testing is still not routinely performed. This contrasts with the findings published by Mendu et al., which showed a notably higher rate of monoclonal testing (34%) being conducted in their CKD population.17 This discrepancy might be because their study only included patients with CKD who were seen in their nephrology clinic, and nephrologists generally are more inclined to perform monoclonal testing as part of the diagnostic workup for CKD compared with other practitioners. Our data, on the other hand, included patients with CKD from the entire Mayo Clinic enterprise and were not limited to those seen in the nephrology clinic. Indeed, the rate of monoclonal testing in our study is closer to the rate of testing at the Department of Veteran Affairs, wherein only 1% of their patients underwent testing.12 On the basis of the final cohort of 1535 patients with CKD who were included in this study, 42% had evidence of MGUS. This rate is markedly higher compared with that reported in a previous study where the rate of abnormal monoclonal testing in CKD population was about 11%.10 The exact reason for this discrepancy is not clear; however, it may be partially explained by the fact that the median age of the patients in our study was 74 years, which is higher than the average age of the previous study of 65 years,10 because the rate of monoclonal gammopathy is higher with older age.5 It is also possible that the other studies relied only on SPEP evaluation while patients in our cohort had a more complete monoclonal gammopathy evaluation (serum immunofixation, free light chain ratio, UPEP, and urine immunofixation in addition to SPEP), and by performing more sensitive screening tests, there was a higher detection rate. Other possibilities include referral bias because there is a high rate of referral of patients with CKD and MGUS to the Mayo Nephrology Clinic for evaluation of MGRS. Finally, it is also possible that we may have missed patients with CKD and negative monoclonal testing because our initial identification strategy relied on International Classification of Diseases 10 codes to identify the patients.
We found that MGUS by itself was not associated with a higher risk of progression to kidney failure among patients with CKD—both in unadjusted and fully adjusted models. Similarly, the rate of eGFR change in the first year after CKD diagnosis was similar between the monoclonal gammopathy groups. Our data are consistent with those of previous studies that did not find any association between MGUS and kidney failure among patients with CKD.9,10 The presence of MGRS in the unadjusted model was significantly associated with progression to kidney failure, compared with no monoclonal gammopathy. This higher risk of progression could be partly explained by the fact that these patients had lower eGFR and higher proteinuria at the time of presentation, and when these covariates were adjusted for in the final model, MGRS was no longer significantly associated with progression to kidney failure. It is also important to note that this was a cohort of patients with MGRS who underwent treatment, which likely had a positive impact on preventing adverse kidney outcomes because it is well known that in the absence of treatment, patients with MGRS are at elevated risk of kidney failure.18–20 As such, it is likely that an untreated cohort of patients with MGRS would have had a higher rate of progression to kidney failure—even after adjusting for their baseline clinical characteristics.
We did observe a higher cumulative incidence of kidney failure in the MGUS group compared with the no monoclonal gammopathy group at year 1 (5 [2–4.0]% versus 3 [4–8]%) and year 2 (9 [7–11]% versus 6 [5–8]%), which was less apparent at year 3 and beyond. This finding could suggest the possibility that some patients who were labeled as having MGUS did, in fact, have MGRS because not all patients with MGUS and CKD underwent a kidney biopsy to confirm their diagnosis; therefore, sensitivity analyses in the subgroup of patients undergoing a kidney biopsy was performed and did not reveal significant differences in the incidence of kidney failure in the monoclonal gammopathy group.
Our study also showed that MGUS was not significantly associated with a greater risk of death among patients with CKD. This finding contrasts with the study by Kyle et al. who showed that MGUS was associated with a higher risk of mortality in the general population7 but is similar to the findings of other studies that showed MGUS was not associated with a higher risk of mortality in the CKD population.9,10 One possible reason for the difference in findings between our study and the study by Kyle et al. may be because they included patients with MGRS in the MGUS group because at that time (1960–1994), the diagnosis of MGRS was not yet established. As such, it was not possible to parse out this subgroup of patients, and as we have shown, patients with MGRS do have a higher risk of mortality compared with those without monoclonal gammopathy. Another reason for this difference could be because our study focused specifically on patients with CKD, and CKD alone is associated with higher mortality compared with the general population driven by cardiovascular diseases.21–24 As a result, from a survival standpoint, having MGUS as a medical comorbidity in the setting of CKD may not have an effect on mortality. The leading cause of death in our cohort was indeed cardiovascular disease—which further supports this notion. Our results are also similar to other studies that evaluated the effect of MGUS in the CKD population and did not find a greater risk of mortality.9,10 A novel finding of our study was that in contrast to patients with MGUS, patients with MGRS were at significantly higher risk of mortality compared with no monoclonal gammopathy patients after adjustment for clinical risk factors. The higher rate of mortality was primarily noted in those patients who carried a diagnosis of AL amyloidosis and who eventually died from complications of their disease. This finding is similar to that of a recent study showing that among patients with MGRS, those with a diagnosis of amyloidosis have a higher rate of mortality compared with those with nonamyloid MGRS.25
Our study has several strengths. It is one of the largest studies to evaluate the effect of monoclonal gammopathy on kidney and survival outcomes. We separated MGUS and MGRS groups to investigate each group's separate contribution to the risk of kidney failure and death. We included complete monoclonal gammopathy data, which is necessary to accurately determine the prognostic significance of MGUS in terms of kidney failure progression and mortality. Finally, CKD diagnosis was confirmed in all our patients by manual chart review rather than relying on International Classification of Diseases codes.
Our study also has several limitations. Only 3% of the overall CKD population underwent monoclonal testing, and given the retrospective nature of this study, we were unable to identify the reason for which monoclonal testing was performed. In addition, our CKD population was enriched in patients who tested positive for monoclonal gammopathy partly due to referral bias and may not be a true representation of the general CKD population. Because not all patients in the MGUS group underwent a kidney biopsy, it is possible that a small fraction of patients in the MGUS group might have truly had MGRS and were misclassified. Finally, the full impact of MGUS on progression to kidney failure may have been missed given the shorter duration of follow-up in this study.
In summary, MGUS is not associated with a higher risk of kidney failure progression or mortality in patients with CKD. MGRS, when treated, was not associated with a higher risk of kidney failure progression after adjusting for baseline characteristics and comorbidities; however, it is associated with a higher risk of mortality after adjusting for clinical risk factors.
Supplementary Material
Footnotes
See related editorial, “Monoclonal Gammopathies and CKD Progression: An Unfinished Story,” on pages 280–282.
Disclosures
F.C. Fervenza reports employment with Mayo Clinic; consultancy for Alexion Pharmaceuticals, Amgen, ByoCryst Pharmaceuticals, Galapagos, GSK, Morphosys AG, Novartis, Otsuka, Takeda, Travere, and Zyversa Therapeutics; research funding from Chemocentryx, Genentech, Hoffman La Roche, Janssen Pharmaceutical, Morphosys, Retrophin, and Travere; unrestricted research grants from Genetech and Janssen pharmaceutical paid to Mayo Clinic; honoraria from UpToDate; and advisory or leadership roles for JASN, Kidney International, Nephrology, Nephrology Dialysis and Transplantation, and UpToDate. S. Moubarak and L. Vaughan report employment with Mayo Clinic. J.P.T. Sy-Go reports employment with Mayo Clinic Rochester (fellowship training) and Renal Physicians Hawaii, LLC (current employer). J.P.T. Sy-Go's spouse reports employment with Hawaii Infectious Disease Associates (current employer). J.K. Viehman reports employment with Mayo Clinic and NAMSA. L. Zand reports employment with Mayo Clinic, Rochester, MN; unrestricted research grants from Genetech and Janssen pharmaceutical paid to Mayo Clinic; and advisory or leadership roles for Calliditas Therapeutics and Travere Pharmaceuticals. The remaining author has nothing to disclose.
Funding
This work is supported by Mayo Foundation for Medical Education and Research (F.C. Fervenza).
Author Contributions
Conceptualization: Janina Paula T. Sy-Go, Lisa E. Vaughan, Ladan Zand.
Data curation: Nattawat Klomjit, Simon Moubarak, Janina Paula T. Sy-Go, Jason K. Viehman, Ladan Zand.
Formal analysis: F.C. Fervenza, Janina Paula T. Sy-Go, Lisa E. Vaughan, Jason K. Viehman, Ladan Zand.
Funding acquisition: F.C. Fervenza.
Methodology: F.C. Fervenza, Janina Paula T. Sy-Go, Lisa E. Vaughan, Ladan Zand.
Supervision: Ladan Zand.
Writing – original draft: Janina Paula T. Sy-Go, Lisa E. Vaughan, Ladan Zand.
Writing – review & editing: F.C. Fervenza, Nattawat Klomjit, Simon Moubarak, Janina Paula T. Sy-Go, Lisa E. Vaughan, Ladan Zand.
Data Sharing Statement
All data are included in the manuscript and/or supporting information.
Supplemental Material
This article contains the following supplemental material online at http://links.lww.com/CJN/B831.
Supplemental Figure 1. Transparent lines represent eGFR trajectories over 1-year follow-up by monoclonal gammopathy group (A–C). The last panel (D) shows all patients. Black lines represent fitted average eGFR trajectories from linear mixed models. Solid line=no monoclonal gammopathy; dashed line=MGUS; dotted line=MGRS.
Supplemental Table 1. Type of MGRS lesions on the basis of kidney biopsy.
Supplemental Table 2. CKD etiology type by monoclonal gammopathy status (no monoclonal gammopathy versus MGUS), overall and stratified by kidney biopsy status.
Supplemental Table 3. Cumulative incidence estimates by year by monoclonal gammopathy status.
Supplemental Table 4. Causes of death by monoclonal gammopathy status.
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Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Supplementary Materials
Data Availability Statement
All data are included in the manuscript and/or supporting information.
Supplemental Material
This article contains the following supplemental material online at http://links.lww.com/CJN/B831.
Supplemental Figure 1. Transparent lines represent eGFR trajectories over 1-year follow-up by monoclonal gammopathy group (A–C). The last panel (D) shows all patients. Black lines represent fitted average eGFR trajectories from linear mixed models. Solid line=no monoclonal gammopathy; dashed line=MGUS; dotted line=MGRS.
Supplemental Table 1. Type of MGRS lesions on the basis of kidney biopsy.
Supplemental Table 2. CKD etiology type by monoclonal gammopathy status (no monoclonal gammopathy versus MGUS), overall and stratified by kidney biopsy status.
Supplemental Table 3. Cumulative incidence estimates by year by monoclonal gammopathy status.
Supplemental Table 4. Causes of death by monoclonal gammopathy status.
