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Journal of Clinical Oncology logoLink to Journal of Clinical Oncology
. 2015 Sep 14;33(32):3741–3749. doi: 10.1200/JCO.2015.62.4015

Improved Outcomes After Autologous Hematopoietic Cell Transplantation for Light Chain Amyloidosis: A Center for International Blood and Marrow Transplant Research Study

Anita D'Souza 1,, Angela Dispenzieri 1, Baldeep Wirk 1, Mei-Jie Zhang 1, Jiaxing Huang 1, Morie A Gertz 1, Robert A Kyle 1, Shaji Kumar 1, Raymond L Comenzo 1, Robert Peter Gale 1, Hillard M Lazarus 1, Bipin N Savani 1, Robert F Cornell 1, Brendan M Weiss 1, Dan T Vogl 1, César O Freytes 1, Emma C Scott 1, Heather J Landau 1, Jan S Moreb 1, Luciano J Costa 1, Muthalagu Ramanathan 1, Natalie S Callander 1, Rammurti T Kamble 1, Richard F Olsson 1, Siddhartha Ganguly 1, Taiga Nishihori 1, Tamila L Kindwall-Keller 1, William A Wood 1, Tomer M Mark 1, Parameswaran Hari 1
PMCID: PMC4737858  PMID: 26371138

Abstract

Purpose

Autologous hematopoietic cell transplantation, or autotransplantation, is effective in light-chain amyloidosis (AL), but it is associated with a high risk of early mortality (EM). In a multicenter randomized comparison against oral chemotherapy, autotransplantation was associated with 24% EM. We analyzed trends in outcomes after autologous hematopoietic cell transplantation for AL in North America.

Patients and Methods

Between 1995 and 2012, 1,536 patients with AL who underwent autotransplantation at 134 centers were identified in the Center for International Blood and Marrow Transplant Research database. EM and overall survival (OS) were analyzed in three time cohorts: 1995 to 2000 (n = 140), 2001 to 2006 (n = 596), and 2007 to 2012 (n = 800). Hematologic and renal responses and factors associated with EM, relapse and/or progression, progression-free survival and OS were analyzed in more recent subgroups from 2001 to 2006 (n = 197) and from 2007 to 2012 (n = 157).

Results

Mortality at 30 and 100 days progressively declined over successive time periods from 11% and 20%, respectively, in 1995 to 2000 to 5% and 11%, respectively, in 2001 to 2006, and to 3% and 5%, respectively, in 2007 to 2012. Correspondingly, 5-year OS improved from 55% in 1995 to 2000 to 61% in 2001 to 2006 and to 77% in 2007 to 2012. Hematologic response to transplantation improved in the latest cohort. Renal response rate was 32%. Centers performing more than four AL transplantations per year had superior survival outcomes. In the multivariable analysis, cardiac AL was associated with high EM and inferior progression-free survival and OS. Autotransplantation in 2007 to 2012 and use of higher dosages of melphalan were associated with a lowered relapse risk. A Karnofsky score less than 80 and creatinine levels 2 mg/m2 or greater were associated with worsened OS.

Conclusion

Post-transplantation survival in AL has improved, with a dramatic reduction in early post-transplantation mortality and excellent 5-year survival. The risk-benefit ratio for autotransplantation has changed, and randomized comparison with nontransplantation approaches is again warranted.

INTRODUCTION

Light-chain amyloidosis (AL) is a multisystemic disease caused by a malignant plasma cell clone with resultant insoluble fibrillar deposition.1 Amyloid fibrils derived from misfolded immunoglobulin light chains cause direct organ toxicity leading to organ failure and death. Current AL therapies focus on eliminating the source of amyloid, that is, the plasma cell clone, by using chemotherapy. However, chemotherapy has minimal effect on preformed organ amyloid; consequently, organ improvements lag behind hematologic responses.2 After diagnosis, patients, particularly those with advanced cardiac AL, are at increased risk for early death from progressive heart failure and sudden death despite the use of effective chemotherapy.3

The role of autologous hematopoietic cell transplantation, or autotransplantation, in AL is controversial. Single-center studies revealed good outcomes in terms of hematologic responses and organ improvement.46 However, the prospective randomized clinical trial reported in 2007 in which autotransplantation was compared with oral melphalan and dexamethasone showed inferior survival with autotransplantation.7 Inferior outcomes were related to high early mortality (EM) of 24% in the transplantation arm and were partly attributed to the inclusion of patients with severe cardiac amyloidosis7 and possibly related to low-volume amyloid transplantation centers.8 Since that study,7 use of cardiac biomarkers—serum troponin T and N-terminal of brain natriuretic peptide —has helped improve detection and risk stratification in patients with cardiac AL.9 These refined selection criteria for autotransplantation, along with improvements in supportive care of patients in the peritransplantation period, have translated into a decrease in the post-transplantation EM to less than 5% at large amyloid centers in the United States.10,11 We hypothesized that outcomes of autotransplantation among patients with AL have improved over time. In addition, we wanted to test the utility of autotransplantation in AL in practice and to assess if center AL transplantation experience affects outcomes. We undertook a retrospective study using the Center for International Blood and Marrow Transplant Research (CIBMTR) database to address these issues.

PATIENTS AND METHODS

Data Source

The CIBMTR is a prospectively maintained registry that collects transplantation data from over 320 centers worldwide. Data are collected at two levels: registration and research. The registration data include disease type, age, sex, date of diagnosis, graft type, conditioning regimen, post-transplantation disease progression, survival, and cause of death, and it includes all transplantations reported to the CIBMTR. More-detailed clinical data are collected from a subgroup of registered patients selected for research data by using a weighted randomization scheme. Both the registration data and the research data are collected pretransplantation, at 100 days and 6 months post-transplantation, and annually thereafter until death or last follow-up.

Patients

Included in this study were patients registered with the CIBMTR in North America between 1995 and 2012 for an autotransplantation for AL within 24 months of diagnosis. Data from these patients were analyzed in three arbitrarily grouped cohorts based on the year of transplantation: 1995 to 2000, 2001 to 2006, and 2007 to 2012. Registration data set was used to assess survival outcomes. Robust research data were available for a subgroup of 354 patients who underwent transplantation between 2001 and 2012. This subgroup was analyzed for hematologic and organ responses and in multivariable analyses. Key characteristics and survival were compared between the registration set and this subset to confirm that the subgroup was a random representative of the data set (Appendix Table A1, online only, and Appendix Table A2, online only). Data accuracy was established by means of physician review (by A. D'Souza and P.H.) of discrepant data when present, and centers were contacted if needed for additional review.

Definitions of Early Mortality, Response, and Center Effect

EM was defined as mortality from any cause after transplantation within the defined time windows of 30 and 100 days. This differed from transplantation-related mortality (TRM), which excluded patients who died as a result of progressive AL or relapse. This avoided attribution bias wherein mortality from organ amyloid in the post-transplantation period could have been labeled as being caused by disease and, thus, causing an underestimation of TRM. Use of EM ensured that the risk of post-transplantation death was not underreported and that mortality in the post-transplantation period was accurately described irrespective of attribution to disease versus treatment-related causes.

The uniform system proposed at the 10th International Symposium on Amyloidosis was used to define hematologic and renal response and progressions.12 In 2012, new criteria were proposed to define hematologic response and progression on the basis of free light-chain (FLC) analysis.3 Because FLC and cardiac biomarkers were collected only after 2008, we were unable to apply the 2012 hematologic or cardiac response criteria to our data set retrospectively. Among organ responses, only renal response is reported in this analysis.

The association between amyloid transplantation volume and survival was analyzed as center experience.8 Owing to a wide variability in the numbers of transplantations performed by centers over the 18-year period of this study, center effect was calculated by using the mean number of amyloid transplantations performed per year over the 4 years13 between 2009 and 2012. Center experience in transplantation for AL was considered a dichotomous variable. After we preformed maximum likelihood testing using the various cut points of two, three, four, five, and 10 amyloid transplantations per year, we established that a minimum of four AL transplantations per year was an informative divider for this analysis.

Statistical Analysis

Patient-, disease- and treatment-related factors were compared by using the [CHI]2 test for categorical variables and the Kruskall-Wallis test for continuous variables. Outcomes analyzed included EM, relapse and/or progression, progression-free survival (PFS), and overall survival (OS). Estimates of outcomes were reported as probabilities with 95% CIs. The probability of OS was calculated with the Kaplan-Meier estimator, with the variance estimated by using the Greenwood formula. Survival curves were compared with the log-rank test. Multivariable analysis was performed by using the research data subset (n = 354) with a Cox proportional hazards model in which the transplantation period cohort of 2001 to 2006 versus 2007 to 2012 was the main effect. Other factors included age at transplantation, race, pretransplantation Karnofsky performance score (KPS), hematopoietic cell transplantation–comorbidity index (HCT-CI), serum creatinine level, serum albumin level, bone marrow plasma cell burden, amyloid organ pattern, number of involved organs, pretransplantation chemotherapy, time from diagnosis to transplantation, melphalan dose in mg/m2 and center effect. The assumption of proportional hazards was tested for each variable, and factors violating the proportionality assumption were adjusted by stratification. Potential interactions between the main effect and all other significant risk factors were tested. All P values were two-sided, and P < 0.05 was considered to indicate a significant difference.

RESULTS

Patient-, Disease-, and Transplantation-Related Variables

Table 1 displays available characteristics for the entire group from 1995 to 2012 (n = 1,536), and Table 2 shows data for the subset with detailed level data from 2001 to 2012 (n = 354). The median age at transplantation was 56 years, with evidence of increasing age at transplantation with successive time cohorts (Table 1). Most patients underwent transplantation within 6 months of diagnosis. The underlying plasma cell clone was λ in 72% of cases (Table 2). The M-spike was nonquantifiable in 42% of patients; when quantified, the median size was 0.6 g/dL. The distribution of cardiac and renal involvement was similar between the groups. Few patients had noncardiac, nonrenal organ involvement in this cohort, and renal involvement without cardiac involvement was the most frequently observed pattern. We found no difference in the 2001-to-2006 and 2007-to-2012 groups in terms of the number of organs involved, and four or more organ were involved in 12% and 11% patients, respectively. Most patients had no treatment before transplantation, but more patients received treatment in 2007 to 2012 than in 2001 to 2006 (33% v 13%, P < .001). Melphalan dosage was reduced most frequently in 2007 to 2012, with 64% of patients receiving less than 180 mg/m2 of melphalan conditioning, and 34% received less than 140 mg/m2.

Table 1.

Characteristics of Patients Who Underwent First AutoHCT for AL and Reported to CIBMTR

Characteristic No. (%)
Year of Transplantation
Overall (N = 1,536)
1995-2000 (n = 140) 2001-2006 (n = 596) 2007-2012 (n = 800)
No. of centers 50 93 104 134
Age at transplantation, years
    Median age (range) 54 (31-71) 57 (23-78) 59 (26-77) 56 (23-78)
    18-39 12 (9) 21 (4) 23 (3) 272 (18)
    40-49 30 (21) 123 (21) 119 (15) 604 (39)
    50-59 65 (46) 244 (41) 295 (37) 362 (24)
    60-65 30 (21) 118 (20) 214 (27) 242 (16)
    ≥ 66 3 (2) 90 (15) 149 (19) 56 (4)
Male sex 85 (61) 355 (60) 483 (60) 923 (60)
Karnofsky score < 80 21 (15) 82 (14) 110 (14) 213 (14)
Time from diagnosis to transplant, months
    < 6 80 (57) 399 (67) 483 (60) 962 (63)
    6-12 41 (29) 145 (24) 214 (27) 400 (26)
    12-24 19 (14) 52 (9) 103 (13) 174 (11)
Median follow-up of survivors from diagnosis (range), months 146 (7-209) 97 (5-152) 33 (6-94) 56 (5-209)
Median follow-up of survivors from transplantation (range), months 142 (4-194) 93 (3-145) 25 (3-76) 49 (3-194)

Abbreviations: AL, light-chain amyloidosis; autoHCT, autologous hematopoietic cell transplantation; CIBMTR, Center for International Blood and Marrow Transplant Research.

Table 2.

Baseline Characteristics of Patients From 2001-2012 Subgroup

Characteristic No. (%)
P
Year of Transplantation
2001-2006 (n = 197) 2007-2012 (n = 157)
No. of centers 51 41
Age at transplantation, years .05
    Median age (range) 57 (31-75) 58 (26-74) .28
    18-39 3 (2) 8 (5)
    40-49 43 (22) 19 (12)
    50-59 79 (40) 67 (43)
    60-65 36 (18) 36 (23)
    ≥ 66 36 (18) 27 (17)
Male sex 116 (59) 100 (64) .36
Race .12
    White 169 (86) 134 (85)
    African American 17 (9) 13 (8)
    Other/unknown 11 (6) 10 (6)
Karnofsky score < 80 31 (16) 20 (13) .38
HCT comorbidity score < .001
    0 36 (18) 33 (21)
    1-2 74 (38) 46 (29)
    ≥ 3 19 (10) 63 (40)
    Unknown* 68 (35) 15 (10)

Disease Related

Involved serum free light chain (after year 2008) NE
    No. evaluated NE 110
    λ 79 (72)
    κ 31 (28)
Serum monoclonal immunoglobulin at diagnosis, g/dL
    No. evaluated 74 98
    Nonquantifiable 25 (34) 48 (49)
    Median when measured (range) 0.7 (0.0002-5.0) 0.5 (0.0004-6.3) .28
Bone marrow plasma cells, % .53
    ≤ 10 136 (69) 114 (73)
    > 10 26 (13) 22 (14)
    Unknown 35 (18) 21 (13)
Serum creatinine at any time pretransplantation, mg/dL .06
    < 2 158 (80) 118 (75)
    ≥ 2 39 (2) 35 (22)
    Unknown 0 4 (3)
Serum albumin at any time before pretransplantation, g/dL .003
    < 2.5 74 (38) 49 (31)
    2.5-3 37 (19) 27 (17)
    ≥ 3 72 (37) 80 (51)
    Unknown 14 (7) 1 (< 1)

Organ Involvement

Organ or system
    Cardiac 75 (38) 59 (38) .47
    Renal 142 (72) 120 (76) .01
    Hepatic 20 (10) 9 (6) .56
    Autonomic nervous system 27 (14) 13 (8) .11
No. of organs involved .37
    1 55 (28) 52 (33)
    2 60 (30) 51 (32)
    3 48 (24) 33 (21)
    ≥ 4 23 (12) 18 (11)
    Unknown 11 (6) 3 (2)
Type of organ involvement .28
    Cardiac (cardiac ± renal ± others) 75 (38) 59 (38)
    Predominant renal (renal ± others) 85 (43) 77 (49)
    Other 26 (13) 18 (11)
    Unknown 11 (6) 3 (2)
CD34 cells infused, × 106/kg 160 113 .01
    Median (range) 4.8 (1.0-16.8) 4.0 (1.2-17.3)
Melphalan dose, mg/m2 .01
    Median (range) 175 (86-241) 143 (86-219) .15
    <140 65 (33) 69 (44)
     140-180 31 (16) 31 (20)
    ≥ 180 86 (44) 54 (34)
    Missing/outliers 15 (8) 3 (2)
Pretransplantation chemotherapy < .001
    Untreated 167 (85) 105 (67)
    Melphalan based 13 (7) 15 (10)
    IMID based 12 (6) 22 (14)
    Bortezomib based 0 15 (10)
    Missing 5 (3) 0
Time from diagnosis to transplantation, months .92
    < 6 131 (66) 103 (66)
    6-12 46 (23) 36 (23)
    12-24 20 (10) 18 (11)
Median follow-up of survivors from diagnosis (range), months 89 (5-51) 56 (12-82)
Median follow-up of survivors from transplant (range), months 77 (3-145) 49 (7-75)

Abbreviations: HCT, hematopoietic cell transplantation; IMID, immunomodulatory drug; NE, nonevaluable.

*

HCT comorbidity index was not collected before 2007.

EM and Causes of Death in 1,536 Patients

Figure 1A shows EM for the three groups. Mortality at 30 and 100 days declined from 11% (95% CI, 7% to 17%) and 20% (95% CI, 14% to 27%), respectively, for the 1995-to-2000 group to 5% (95% CI, 4% to 7%) and 11% (95% CI, 8% to 13%) for the 2001-to-2006 group to 3% (95% CI, 2% to 4%) and 5% (95% CI, 4% to 7%) for the 2007-to-2012 group (P < .001). No difference was seen in EM based on the time from diagnosis to transplantation. Rates were, at less than 6 months, 12% (95% CI, 8% to 17%); at 6 to 12 months, 5 (95% CI, 1% to 11%); and 12 to 24 months, 8% (95% CI, 2% to 18%). Causes of death reported within the first 100 days were attributed to amyloid and organ failure in most patients (83%), followed by infection (8%), nonengraftment (3%), and unknown causes (6%).

Fig 1.

Fig 1.

Probabilities of (A) early mortality and (B) overall survival (OS) in light-chain amyloidosis after transplantation for all three time cohorts.

OS in 1,536 Patients

Median follow-up was 56 months (5 to 209 months) from the time of diagnosis. One-, 3- and 5-year OS in successive cohorts improved from 75% (95% CI, 65% to 82%), 64% (95% CI, 56% to 72%), and 55% (95% CI, 46% to 63%), respectively, for 1995 to 2000 to 85% (95% CI, 81% to 87%), 72% (95% CI, 68% to 75%), and 61% (95% CI, 57% to 65%), respectively, for 2001 to 2006 and to 90% (95% CI, 88% to 92%), 83% (95% CI, 80% to 86%), and 77% (95% CI, 72 to 82%), respectively, for 2007 to 2012 (P < .001; Fig 1B).

We observed no difference in OS based on the time from diagnosis to transplantation. Rates were, at less than 6 months, 73% (95% CI, 67% to 79%); at 6 to 12 months, 81% (95% CI, 71% to 89%); and at 12 to 24 months, 81% (95% CI, 61% to 92%; P = 0.22).

For patients with cardiac amyloidosis, 3-year OS improved from 62% (95% CI, 48% to 75%) in 2001 to 2006 to 67% (95% CI, 52% to 80%) in 2007 to 2012 (P = .59; Fig 2A). For those with renal and without cardiac amyloidosis, 3-year OS improved from 78% (95% CI, 68% to 86%) in 2001 to 2006 to 89% (95% CI, 82% to 95%) in 2007 to 2012 (P = .03; Fig 2B).

Fig 2.

Fig 2.

Trends in (A) overall survival (OS) for cardiac light-chain amyloidosis (AL); (B) OS for renal, noncardiac AL; (C) early mortality (EM) based on center experience; and (D) time trends in improvement in EM among centers.

Response Rates in the Subset of 354 Patients

A best hematologic response to transplantation was available in 89% and 97% of patients in the 2001-to-2006 and 2007-to-2012 groups, respectively. A renal response at any point after autotransplantation was available in 70% and 78% of patients in 2001 to 2006 and 2007 to 2012, respectively. Table 3 shows a breakdown of hematologic and renal responses that were observed in this cohort. The hematologic response rate was higher in the 2007-to-2012 cohort than in the 2001-to-2006 cohort.

Table 3.

Hematologic and Renal Responses Observed With Transplantation

Response 2001-2006 (n = 197)
2007-2012 (n = 157)
P
No. % No. %
Best hematologic response .005
    Complete response 60 30 58 37
    Partial response 44 22 53 34
    Stable disease 42 21 25 16
    Progression 7 4 3 2
    Nonevaluable* 22 11 14 9
    Missing 22 11 4 3
Best renal response .30
    Response 61 31 51 32
    Stable disease 48 24 47 30
    Progression 7 4 10 6
    Nonevaluable* 22 11 14 9
    Missing 59 30 35 22
*

Nonevaluable was noted for patients who died in the first 100 days after transplantation.

Center Effects in the Subset of 354 Patients

EM was worse among 81 centers that performed fewer than four AL transplantations per year, that is, low volume, than in others. Their mortality rate of 5% (95% CI, 3% to 7%) at 30 days and 7% (95% CI, 5% to 10%) at 100 days compared with 1% (95% CI, 0.4% to 3%) at 30 days and 3% (95% CI 2% to 6%) at 100 days for centers that performed four or more AL transplantations a year, or high volume (n = 11; P = .01; Fig 2C). No statistically significant difference was found for age, KPS, HCT-CI, cardiac amyloidosis, number of organs involved with amyloidosis, melphalan conditioning dosage, or pretransplantation chemotherapy between the high-volume and low-volume centers (Appendix Table A3, online only). Both high- and low-volume centers showed an improvement in reported EM in the three time cohorts (P < .01; Fig 2D).

Multivariable Analysis in the Subset of 354 Patients

Table 4 shows results of the multivariable analysis. Adjusted analysis showed no difference between the 2001-to-2006 cohort and the 2007-to-2012 cohort for EM, PFS, or OS. The analysis for relapse and/or progression was nonproportional, and the optimal cut point identified was 9 months after transplantation. During the initial period, no difference occurred between the 2001-to-2006 and 2007-to-2012 cohorts for relapse and/or progression. After 9 months, the relapse and/or progression rate was lower in the 2007-to-2012 cohort. The presence of cardiac involvement was associated with increased EM (hazard ratio [HR], 3.5; 95% CI, 2 to 6.4; P < .001), worse PFS (HR, 2.0; 95% CI, 1.7 to 3.0; P < .001), and OS (HR, 2.5; 95% CI, 1.6 to 3.9; P < .001).

Table 4.

Multivariable Analysis of Outcomes

Effect No. Hazard Ratio 95% CI P
Early mortality 336
    2001-2006 183 1.0
    2007-2012 153 0.956 0.567 to 1.613 .87
    Type of organ involvement < .001
        Cardiac 128 1.000
        Renal, noncardiac 152 0.285 0.156 to 0.518 < .001
        Other 42 0.268 0.096 to 0.752 .01
        Missing 14 0.206 0.028 to 1.507 .12
Relapse and or progression 331*
    Early event, 0-9 months .02
        2001-2006 178 1.000
        2007-2012 153 1.440 0.561 to 3.700 .45
    Late event, > 9 months
        2001-2006 145 1.000
        2007-2012 119 0.321 0.137 to 0.753 .01
    Pretransplantation chemotherapy
        Untreated 259
        Treated 72 0.545 0.239 to 1.245 .15
    Melphalan dose, mg/m2 .001
        < 140 128 1.000
        140-180 58 0.511 0.235 to 1.114 .09
        ≥ 180 131 0.237 0.118 to 0.474 < .001
        Missing 14 0.487 0.116 to 2.049 .33
Progression-free survival 336
    2001-2006 183 1.000
    2007-2012 153 0.821 0.553 to 1.219 .33
    Karnofsky score .001
        ≥ 80 265 1.000
        < 80 49 2.41 1.556 to 3.749 < .001
        Missing 22 1.305 0.560 to 3.040 .54
    Type of organ involvement .003
        Cardiac 128 1.000
        Renal, noncardiac 152 0.504 0.331 to 0.766 .001
        Other 42 0.424 0.217 to 0.832 .013
        Missing 14 0.531 0.189 to 1.492 .23
Overall survival 350
    2001-2006 197 1.000
    2007-2012 153 0.703 0.460 to 1.075 .1
    Karnofsky score .001
        ≥ 80 278 1.000
        < 80 51 2.670 1.694 to 4.206 < .001
        Missing 21 1.644 0.696 to 3.882 .26
    Pretransplantation serum creatinine level, mg/dL
        < 2 276 1.000
        ≥ 2 74 1.7000 1.072 to 2.697 .02
    Type of organ involvement .001
        Cardiac 131 1.000
        Renal, noncardiac 161 0.402 0.255 to 0.632 < .001
        Other 44 0.444 0.218 to 0.905 .03
        Missing 41 0.425 0.129 to 1.401 .16
*

Five patients were excluded because pretransplantation chemotherapy data were not available.

Four patients excluded because pretransplantation serum creatinine levels were not available.

DISCUSSION

We describe outcomes after autotransplantation in the largest cohort of patients with AL reported to date. We make a number of clinically important observations. First, impressive reduction in EM has been achieved in recent years, and this is superior to the reported TRM of 24% from the only randomized clinical trial we know of in this setting.7 Second, cardiac amyloid involvement remains the critical variable associated with worse outcomes, with no improvement in outcomes of patients with cardiac amyloidosis over time. Third, center experience with AL transplantation is important in reducing EM. Centers that perform four or more AL transplantations per year report better results than those that do not. Fourth, 5-year survival in this real-world experience of autotransplantation has improved to 77% in the most recent cohort. This is comparable to data from specialized single centers and superior to the transplant arm of the randomized trial.7,14

Although established as an effective treatment modality in AL, autotransplantation has been controversial, owing to inferior outcomes reported in the prospective, randomized controlled, phase III trial described in 2007.7 Further, more recently, combination chemotherapy using novel agents such as bortezomib with alkylators has been shown to be associated with prompt and deep hematologic responses in the upfront setting.1518 Therefore, the role of autotransplantation in AL has been further questioned. This is reflected in our study; the number of transplantations performed in the US did not rise as rapidly after 2007 as they did in the preceding years.

Despite similar proportion of patients with cardiac involvement, transplantation after 2007 was associated with lower EM and superior OS than the earlier time periods. Therefore, EM improvements appeared to be multifactorial, representing improvements in supportive care and a higher level of experience overall in caring for these patients with complex conditions and not merely selection of fitter patients. Among patients with a renal, noncardiac pattern of AL involvement, outcomes improved significantly over time. However, for patients with cardiac AL, we were unable to demonstrate a statistically significant change in survival over time. A similar finding has been reported by others with novel chemotherapies17,19,20 and highlights the importance of earlier diagnosis of AL disease and an unmet need for safer and more effective therapies for patients with advanced cardiac amyloidosis, including antifibril therapies.

In our subset analyses of 354 patients, we were able to study response rates and prognostic factors. The response rate at day 100 was limited by missing data, particularly for the 2001-to-2006 group; therefore, it is not shown. However, when we assessed best hematologic response to transplantation, we noted more complete and partial hematologic responses in 2007 to 2012 than in 2001 to 2006. More patients received pretransplantation induction chemotherapy during 2007 to 2012, but melphalan conditioning doses were also lower in this period than in others. Of interest, renal response rates were equivalent in 2001 to 2006 and 2007 to 2012 at 31% and 32%, respectively; this result is similar to renal response of 33% reported after chemotherapy.21 However, fewer patients, less than 10%, in both groups had progression of renal AL. This was much lower compared with renal progression after chemotherapy, even among the 50% of patients who have complete and partial hematologic responses.21

A number of pretransplantation factors have been shown to be prognostic after autotransplantation for AL. Cardiac biomarkers using serum cardiac troponin T and N-terminal of brain natriuretic peptide provide a simple clinical prognostication system of staging AL amyloidosis,9 improving our ability to screen for patients with advanced cardiac amyloidosis who are at increased risk for post-transplantation complications and EM. Other known risk factors associated with transplantation mortality include performance status and multiorgan involvement with amyloidosis.22,23 In addition, lowered melphalan conditioning intensity to adjust for risk has been associated with a reduced response rate.24 In this study, we confirm that cardiac involvement, poor renal function, poor KPS less than 80, and use of melphalan conditioning less than 180 mg/m2 are associated with worse outcomes. The HCT-CI is a transplantation-specific prognostic variable that was described and validated in the mid-2000s. Although we were able to calculate it many patients using reported comorbidities, this variable was unavailable in the pre-2008 patient set. A bone marrow plasma cell clone greater than 10% has been found to be associated with worse outcomes,25,26 but this finding was not replicated in our study. Although pretransplantation chemotherapy was not associated with improved outcomes, most of the pretransplantation chemotherapy included nonbortezomib-based approaches.

In addition to the superior hematologic responses noted previously, patients in the 2007-to-2012 cohort also had a lower risk of relapse starting 9 months after transplantation. This was an interesting finding because lower doses of melphalan conditioning, which was more common in the 2007-to-2012 period that in others, was an independent predictor of relapse. Post-transplantation consolidation with bortezomib has been associated with deepening of response rates.27 In our analysis, only 38 patients received any post-transplantation consolidation, and further analyses could not be performed because of low numbers.

The best results for autotransplantation in AL have been reported from specialized, high-volume centers in contrast to the multicenter, randomized trial experience. It has been proposed that center experience in treating patients with AL is important, with low-volume centers having higher EM rates.8 Indeed, in our cohort, transplantation centers performing fewer than four AL transplantations per year had higher EM rates than those of centers performing four or more transplantations. Lack of differences in the patient, organ, or chemotherapy-related factors between high- and low-volume centers led us to believe that high-volume centers do not necessarily select fitter patients for transplantation. Rather, they may be more experienced in supporting and treating these patients in the early post-transplantation period. However, owing to the small numbers in the subset analysis, our analysis was not powered to show significant differences in outcomes on the basis of center volume in the multivariable analysis after other factors were adjusted.

Our study had a number of limitations inherent to its retrospective nature and the long interval under study. Amyloidosis management is a dynamic field, and, during study inclusion, criteria for response and organ involvement changed twice.12,28 Variability in reporting by centers and the introduction of markers such as FLC, cardiac biomarkers, and HCT-CI at various points during this period were other issues inherent to the interval under study. Data regarding FLC and cardiac biomarkers were not collected in our database after 2008, but serial FLC or cardiac biomarkers were reported for too few patients to adequately define amyloid stage29 or response by using the 2012 criteria described by Palladini et al.28 Another limitation of our study was our inability to stratify the severity of cardiac involvement because cardiac biomarker information was not uniformly reported. Therefore, although percentages of patients reported with cardiac involvement were similar between the 2001-to-2006 and 2007-to-2012 periods, we do not know if cardiac stage was similar between these cohorts. Finally, our data were limited to individuals undergoing transplantation, who are inherently a selected group of better-risk patients.30

Although our study does not replace a controlled, transplantation-versus-nontransplantation trial, it is reassuring to see that excellent outcomes of autotransplantation previously reported from large single centers were replicated in practice capturing most AL transplantations in the US. With the availability of novel plasma cell–directed agents such as bortezomib, we propose that it is time to reconsider a multi-institutional study to compare transplantation, perhaps limited to high-volume centers, versus novel nontransplantation therapy.

Appendix

Table A1.

Subgroup Versus Cohort Comparison for Key Variables and Overall Survival

Variable Research Data Set (n = 354) Entire Cohort (N = 1,356) P
Age at transplantation, years
    Median age (range) 57 (26-75) 58 (23-78) .40
    18-39 11 (3) 44 (3)
    40-49 62 (18) 242 (17)
    50-59 146 (41) 539 (39)
    60-65 72 (20) 332 (24)
    ≥ 66 63 (18) 239 (17)
Sex .73
    Male 216 (61) 838 (60)
    Female 138 (39) 558 (40)
Country .08
    United States 329 (93) 1,330 (95)
    Canada 25 (7) 66 (5)
Race .88
    White 303 (86) 1,188 (85)
    African American 30 (8) 112 (8)
    Others 12 (3) 49 (4)
    Missing 9 (3) 47 (3)
Karnofsky score* .02
    80-100 278 (79) 1,031 (74)
    < 80 51 (14) 192 (14)
    Missing 25 (7) 173 (12)
Time from diagnosis to transplantation, months .56
    < 6 234 (66) 882 (63)
    6-12 82 (23) 359 (26)
    12-24 38 (11) 155 (11)
Median follow-up of survivors (range), months 61 (3-145) 47 (3-145)
*

P for nonmissing groups = .93.

Table A2.

Subgroup Versus Cohort Comparison for Early Mortality and Overall Survival

Outcome Research Data Set (n = 354)
Entire Cohort (N = 1,396)
Probability (%) 95% CI Probability (%) 95% CI
Early mortality
    1 month 94 91 to 96 96 95 to 97
    100 day 90 86 to 93 93 91 to 94
Overall survival, years
    1 83 79 to 87 88 86 to 89
    3 76 71 to 80 77 75 to 80
    5 70 64 to 75 68 65 to 71

NOTE. Log rank test P = .94.

Table A3.

Comparison of Key Variables Between High- and Low-Volume Light-Chain Amyloidosis Transplantation Centers

Variable Center Experience, No. of Transplantations
P
< 4 (n = 91)
≥ 4 (n = 66)
No. % No. %
Age at transplantation, years .60
    18-39 3 3 5 8
    40-49 13 14 6 9
    50-59 40 44 27 41
    60-65 19 21 17 26
    ≥ 66 16 18 11 17
Karnofsky score .68
    80-100 71 78 52 79
    < 80 13 14 7 11
    Missing 7 8 7 11
Time from diagnosis to transplantation, months .49
    < 6 63 69 40 61
    6-12 18 20 18 27
    12-24 10 11 8 12
Cardiac involvement .24
    Yes 37 41 22 33
    No 32 35 32 48
    Missing 22 24 12 18
Renal involvement .65
    Yes 68 75 52 79
    No 11 12 5 8
    Missing 12 13 9 14
Organ involvement .13
    0 1 1 2 3
    1 29 32 23 35
    2 36 40 15 23
    3 18 20 15 23
    4 7 8 11 17
Hematopoietic cell transplantation–comorbidity index .15
    0 25 27 8 12
    1 10 11 9 14
    2 13 14 14 21
    3 13 14 7 11
    4 24 26 19 29
    Missing 6 7 9 14
Melphalan dose, mg/m2 .20
    < 140 35 38 34 52
    140-180 18 20 13 20
    > 180 37 41 17 26
    Missing 1 1 2 3
Chemotherapy .09
    No chemotherapy 65 71 40 61
    Melphalan based 6 7 9 14
    Thalidomide based 2 2 7 11
    Lenalidomide based 9 10 4 6
    Bortezomib based 9 10 6 9

NOTE. Center experience was measured by the mean number of light-chain transplantations performed at centers between 2009 and 2012. High volume was four or more transplantations per year, and low volume was four or fewer transplantations per year.

See accompanying editorial on page 3689

Support information appears at the end of this article.

Presented in part at the 56th Annual Meeting of the American Society of Hematology, San Diego, CA, December 6-9, 2014.

The views expressed in this article do not reflect the official policy or position of the National Institutes of Health, the Department of the Navy, the Department of Defense, the Health Resources and Services Administration, or any other agency of the US Government.

Authors' disclosures of potential conflicts of interest are found in the article online at www.jco.org. Author contributions are found at the end of this article.

Support

Supported by Public Health Service Grant/Cooperative Agreement No. U24-CA076518 from the National Cancer Institute (NCI), the National Heart, Lung and Blood Institute (NHLBI), and the National Institute of Allergy and Infectious Diseases (NIAID); Grant/Cooperative Agreement No. 5U10HL069294 from the NHLBI and the NCI; contract No. HHSH250201200016C with Health Resources and Services Administration (HRSA/DHHS); Grants No. N00014-13-1-0039 and No. N00014-14-1-0028 from the Office of Naval Research; and grants from Actinium Pharmaceuticals; Allos Therapeutics; Amgen; an anonymous donation to the Medical College of Wisconsin; Ariad; Be the Match Foundation; Blue Cross and Blue Shield Association; Celgene; Chimerix; Fred Hutchinson Cancer Research Center; Fresenius-Biotech North America; Gamida Cell Teva Joint Venture; Genentech; Gentium SpA; Genzyme Corporation; GlaxoSmithKline; Health Research Roswell Park Cancer Institute; HistoGenetics; Incyte Corporation; Jeff Gordon Children's Foundation; Kiadis Pharma; The Leukemia & Lymphoma Society; Medac; The Medical College of Wisconsin; Merck & Co; Millennium: The Takeda Oncology Co.; Milliman USA; Miltenyi Biotec; the National Marrow Donor Program; Onyx Pharmaceuticals; Optum Healthcare Solutions; Osiris Therapeutics; Otsuka America Pharmaceutical; Perkin Elmer; Remedy Informatics; Sanofi US; Seattle Genetics; Sigma-Tau Pharmaceuticals; Soligenix; St. Baldrick's Foundation; StemCyte, A Global Cord Blood Therapeutics Co.; Stemsoft Software; Swedish Orphan Biovitrum; Tarix Pharmaceuticals; TerumoBCT; Teva Neuroscience; THERAKOS; the University of Minnesota; the University of Utah; and Wellpoint (CIBMTR). Supported by the National Center for Research Resources and the National Center for Advancing Translational Sciences, National Institutes of Health, Grant No. 8UL1TR000055 (D'Souza).

AUTHORS' DISCLOSURES OF POTENTIAL CONFLICTS OF INTEREST

Disclosures provided by the authors are available with this article at www.jco.org.

AUTHOR CONTRIBUTIONS

Conception and design: Anita D'Souza, Angela Dispenzieri, Baldeep Wirk, Mei-Jie Zhang, Parameswaran Hari

Collection and assembly of data: Anita D'Souza, Angela Dispenzieri, Baldeep Wirk, Mei-Jie Zhang, Jiaxing Huang, Parameswaran Hari

Data analysis and interpretation: All authors

Manuscript writing: All authors

Final approval of manuscript: All authors

AUTHORS' DISCLOSURES OF POTENTIAL CONFLICTS OF INTEREST

Improved Outcomes After Autologous Hematopoietic Cell Transplantation for Light Chain Amyloidosis: A Center for International Blood and Marrow Transplant Research Study

The following represents disclosure information provided by authors of this manuscript. All relationships are considered compensated. Relationships are self-held unless noted. I = Immediate Family Member, Inst = My Institution. Relationships may not relate to the subject matter of this manuscript. For more information about ASCO's conflict of interest policy, please refer to www.asco.org/rwc or jco.ascopubs.org/site/ifc.

Anita D'Souza

No relationship to disclose

Angela Dispenzieri

Consulting or Advisory Role: Prothena (Inst), Pfizer (Inst)

Research Funding: Celgene (Inst), Millennium Pharmaceuticals (Inst), Janssen Oncology (Inst), Pfizer (Inst)

Travel, Accommodations, Expenses: Pfizer

Baldeep Wirk

No relationship to disclose

Mei-Jie Zhang

No relationship to disclose

Jiaxing Huang

No relationship to disclose

Morie A. Gertz

Honoraria: Celgene, Novartis, Millenium Pharmaceuticals, Med Learning Group, Research to Practice, Onyx Pharmaceuticals, ISIS, Sanofi, Prothena

Robert A. Kyle

No relationship to disclose

Shaji Kumar

Consulting or Advisory Role: Skyline Diagnostics

Research Funding: Celgene, Novartis, Onyx, Millennium, Sanofi Pasteur, Janssen Pharmaceuticals

Raymond L. Comenzo

Consulting or Advisory Role: Prothena, Takeda, Jannsen

Research Funding: Prothena, Takeda Pharmaceuticals, Jannsen Pharmaceuticals, Array BioPharma, Karyopharm

Robert Peter Gale

Employment: Celgene

Stock or Other Ownership: Celgene

Travel, Accommodations, Expenses: Celgene

Hillard M. Lazarus

Honoraria: Celgene

Speakers' Bureau: Celgene

Travel, Accommodations, Expenses: Celgene

Bipin N. Savani

No relationship to disclose

Robert F. Cornell

No relationship to disclose

Brendan M. Weiss

Research Funding: Prothena, Janssen Research & Development

Dan T. Vogl

Consulting or Advisory Role: Celgene, Amgen, Millennium Pharmaceuticals

Research Funding: Millennium Pharmaceuticals, Acetylon Pharmaceuticals, GlaxoSmithKline, Calithera Biosciences, Constellation Pharmaceuticals

César O. Freytes

Consulting or Advisory Role: Spectrum Pharmaceuticals, Clinipace

Speakers' Bureau: Sanofi

Research Funding: Merck

Emma C. Scott

Honoraria: Takeda, Onyx, Takeda (I), Onyx (I)

Consulting or Advisory Role: Millennium Pharmaceuticals, Onyx

Research Funding: Millennium Pharmaceuticals, Takeda

Heather J. Landau

Honoraria: Takeda, Prothena, Onyx, Spectrum Pharmaceuticals

Consulting or Advisory Role: Prothena

Research Funding: Onyx, Takeda

Jan S. Moreb

No relationship to disclose

Luciano J. Costa

No relationship to disclose

Muthalagu Ramanathan

Employment: Zoll (I)

Stock or Other Ownership: Smith & Nephew (I)

Consulting or Advisory Role: Med Learning Group

Research Funding: Celgene, Gilead Sciences, Millennium Pharmaceuticals, Pharmacyclics

Travel, Accommodations, Expenses: Gilead Sciences

Natalie S. Callander

No relationship to disclose

Rammurti T. Kamble

No relationship to disclose

Richard F. Olsson

No relationship to disclose

Siddhartha Ganguly

Honoraria: Seattle Genetics, Onyx

Consulting or Advisory Role: Takeda, Millennium, ARIAD

Speakers' Bureau: Onyx, Seattle Genetics

Research Funding: Janssen Pharmaceuticals, Sanofi, Celgene

Travel, Accommodations, Expenses: Onyx, Seattle Genetics

Taiga Nishihori

No relationship to disclose

Tamila L. Kindwall-Keller

Research Funding: Celldex, US Biotest

William A. Wood

No relationship to disclose

Tomer M. Mark

Stock or Other Ownership: Abbvie, Karyopharm Therapeutics, Portola Pharmaceuticals

Consulting or Advisory Role: Celgene, Janssen Pharmaceuticals, Takeda

Speakers' Bureau: Celgene, Takeda, Onyx

Research Funding: Celgene (Inst), Onyx (Inst)

Parameswaran Hari

Stock or Other Ownership: Pharmacyclics

Honoraria: Celgene, Millennium, Sanofi, Onyx

Consulting or Advisory Role: Celgene, Millennium Pharmaceuticals, Onyx, Sanofi

Research Funding: Millennium Pharmaceuticals (Inst), Celgene (Inst)

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