Leukemia Research 37 (2013) 1527–1531
Contents lists available at ScienceDirect
Leukemia Research journal homepage: www.elsevier.com/locate/leukres
Genetic variants in DNA repair pathways are not associated with disease progression among multiple myeloma patients Bharat Thyagarajan a,∗ , Mukta Arora b , Weihua Guan c , Helene Barcelo a , Scott Jackson d , Shaji Kumar e , Morie Gertz e a
Department of Laboratory Medicine and Pathology, University of Minnesota, Minneapolis, MN, USA Division of Hematology, Oncology and Transplantation, Department of Medicine, University of Minnesota, Minneapolis, MN, USA c Division of Biostatistics, School of Public Health, University of Minnesota, Minneapolis, MN, USA d Biostatistics and Informatics Core, Masonic Cancer Center, University of Minnesota, Minneapolis, MN, USA e Division of Hematology, Department of Medicine, Mayo Clinic, Rochester, MN, USA b
a r t i c l e
i n f o
Article history: Received 25 February 2013 Accepted 8 July 2013 Available online 12 October 2013 Keywords: Multiple myeloma Melphalan Autologous transplantation Nucleotide excision repair Base excision repair Single nucleotide polymorphisms Disease progression
a b s t r a c t DNA damage induced by high dose melphalan and autologous transplantation is repaired by the nucleotide excision repair (NER) and base excision repair (BER) pathways. We evaluated the association between single nucleotide polymorphisms (SNPs) (n = 311) in the NER and BER pathways and disease progression in 695 multiple myeloma patients who underwent autologous transplantation. None of the SNPs were associated with disease progression. Pathway based analyses showed that the NER pathway had a borderline association with disease progression (p = 0.09). These findings suggest that common variation in the NER and BER pathways do not substantially influence disease progression in multiple myeloma patients. © 2013 Elsevier Ltd. All rights reserved.
1. Introduction High dose chemotherapy using melphalan supported by autologous transplantation is currently the standard of care for treatment of multiple myeloma [1–8]. A variety of DNA repair pathways are involved in the repair of the melphalan-induced DNA damage that include DNA alkylation and DNA interstrand cross-links [9–11]. The considerable heterogeneity in clinical response to high dose melphalan and autologous transplantation among patients undergoing treatment for multiple myeloma [12,13] suggests that inter-individual variation in DNA repair may be an important determinant of treatment response. In vitro experiments have clearly shown that the nucleotide excision repair pathway (NER) plays a crucial role in the repair of monoadducts [14]. Another study has also shown the base excision repair (BER) pathway to be important in repair of melphalan induced monoadducts [15]. Previous studies have shown that
∗ Corresponding author at: University of Minnesota, Department of Laboratory Medicine and Pathology, 515 Delaware Street SE, 1-136 Moos Towers, Minneapolis, MN 55455, USA. Tel.: +1 612 624 1257; fax: +1 612 625 8950. E-mail address: [email protected] (B. Thyagarajan). 0145-2126/$ – see front matter © 2013 Elsevier Ltd. All rights reserved. http://dx.doi.org/10.1016/j.leukres.2013.07.012
genetic variations in both the NER and BER pathway that modify DNA repair capacity influence the outcome of cancer chemotherapy [16–18]. In NER, a multi-component repair complex incises a 24–32mer oligonucleotide containing the lesion and the gap created is filled by DNA polymerase and DNA ligases [19]. During BER the damaged base is removed by a glycosylase, the resulting apurinic deoxyribose is excised by a separate apurinic endonuclease or by an apurinic lyase and the resulting single nucleotide gap is usually filled in as a single nucleotide repair patch [19]. Consistent with important roles of NER and BER pathways in the repair of melphalan induced DNA damage, two studies have shown genetic variants in NER and BER genes to be associated with response to high dose melphalan based chemotherapy [20,21]. Though, these candidate gene studies provide preliminary evidence of the importance of genetic variation in the DNA repair pathway in determining treatment response, both the NER and BER pathways are complex biological processes consisting of several genes. Hence, a systematic evaluation of genetic variation in both these pathways is needed to comprehensively evaluate the role of genetic variation in these DNA repair pathways in determining treatment response after high dose melpahalan and autologous transplantation. We genotyped all common genetic variation (minor allele frequency (MAF) ≥5%) in 24 NER, 21 BER and 7 genes that are common
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B. Thyagarajan et al. / Leukemia Research 37 (2013) 1527–1531
to both DNA repair pathways and evaluated their association with disease progression among a cohort of 695 multiple myeloma patients treated with high dose melphalan and autologous transplantation at the Mayo Clinic or the University of Minnesota. 2. Materials and methods 2.1. Patient selection The patients were recruited from two centers; the Mayo Clinic and the University of Minnesota. We included 541 consecutive adult patients (age >18 years) from the Mayo Clinic and 154 consecutive adult patients from the University of Minnesota who underwent an autologous HCT for multiple myeloma between January 1998 and July 2009 and had blood samples available for DNA extraction. Patients who underwent tandem autologous followed by allogeneic transplants were excluded from this study. Patients who underwent a salvage allogeneic transplant after autologous transplant for disease relapse or progression were censored at the event (disease relapse or progression). 2.2. Clinical data and collection of DNA samples All clinical data from the Mayo Clinic were obtained using the Mayo Clinic Blood and Marrow Transplant database. All clinical data from the University of Minnesota was obtained using the University of Minnesota Blood and Marrow Transplant Database and supplemented by chart reviews when necessary. Demographic and transplant characteristics included age at transplant, gender, race, immunoglobulin subtype, Durie-Salmon stage, cytogenetic risk group, time from diagnosis to transplant, clinical center, conditioning regimen and year of autologous HCT. Patients were censored at death or for patients surviving in complete remission at last contact. Time from transplant to disease relapse or progression was taken as time to disease progression. The International Myeloma Working Group (IMWG) Uniform Response Criteria were used to assess post-transplant disease relapse [22]; however, free light chain assay were not uniformly available, especially from the earlier years of study [22]. DNA samples from patients were obtained from peripheral blood samples obtained at the time of stem cell collection prior to autologous HCT. DNA was extracted using the Qiagen Midi Blood kit (Qiagen Inc., San Jose, CA) as per manufacturer recommendations. All DNA samples were stored in −80 ◦ C freezers until further analyses.
status pre-transplant, number of relapses prior to transplant, conditioning pre-transplant (melphalan based versus other) and year of autologous HCT to adjust for differences in pre-transplant treatment based regimens. Significant covariates were selected by a backward stepwise regression procedure where covariates with p < 0.1 were included in the final model. Significant covariates selected in the final model included clinical site (Mayo clinic vs. University of Minnesota), number of relapses prior to transplant, time between initial diagnosis and first transplant, disease status prior to transplantation, year of autologous HCT (1998–2003 vs. 2004–2009) and self-reported race. We also restricted these analyses to patients of European-American descent. We used a modified Bonferroni correction after accounting for SNPs in linkage disequilibrium [27] to adjust for false positive findings and a p value of ≤2 × 10−4 was considered to be statistically significant. Among SNPs found to be nominally associated with disease progression (p ≤ 0.05), we evaluated pair-wise SNP-SNP and SNPclinical covariate interactions. Assuming an additive genetic model and adjustment for multiple comparisons using the modified Bonferroni correction, this study has 87% power to detect a SNP-disease progression association with a hazards ratio (HR) of 1.45 and MAF of 0.2, 77% power to detect HR of 1.4 and MAF of 0.3, or 85% power to detect HR of 1.35 and MAF of 0.4. We also performed a pathway analysis to globally evaluate whether genetic variation in the NER and BER pathways was associated with disease progression. For the pathway analysis, we selected the lowest p-value from each gene in a particular pathway (genes involved in both NER and BER were included in both pathways) and summed the −2 log(p) over all genes in a particular pathway (NER or BER) analogous to a Fisher’s combined probability test [26]. We then used permutation testing (n = 1000) to evaluate whether the summed −2 log(p) value for all the genes in a particular pathway is greater than expected by chance.
2.3. SNP selection and genotyping
4. Results We used data from Environmental Genome Project [23–25] to identify and select Linkage Disequilibrium (LD) tagging single nucleotide polymorphisms (tagSNPs) with r2 >0.8 that had MAF ≥5% in the Caucasian population in 24 NER, 21 BER and 7 genes that are common to both DNA repair pathways. If tagSNPs were not identified in the Environmental Genome Project, we used HapMap data for European American populations to identify tagSNPs that had ≥5% MAF in European American populations using the Genome Variation Server software (http://gvs.gs.washington.edu/GVS/). Single nucleotide polymorphisms with MAF ≥5% that did not fit into any of the LD bins were also included in this study. This tagSNPs approach allowed us to comprehensively evaluate all genetic variation with MAF ≥5% in the genes evaluated. Though some SNPs included in this study resulted in an amino acid change, individual SNPs that resulted in an amino acid change or that were predicted to affect protein function were not specifically included in this study. This approach allowed us to genoytpe 168 SNPs in 24 genes in the NER pathway, 104 SNPs in 21 genes in the BER pathway and 42 SNPs in 7 genes that participate in both DNA repair pathways (n = 314). All DNA samples were genotyped using the Sequenom iPLEX system at the Biomedical Genomics Center at the University of Minnesota using primers and probes designed by Sequenom primer design software. After excluding monomorphic SNPs (n = 3), 311 SNPs were included for further analyses.
The baseline characteristics of the study population are described in Table 1. All patients underwent an autologous HCT for treatment of multiple myeloma at the Mayo Clinic (N = 541) or the University of Minnesota (n = 154). The median age at diagnosis for this cohort was 56.5 years (range: 23.9–75.3 years). The median time from diagnosis of multiple myeloma to first transplant was 6.5 months (range: 3.2–110.6 months) with a majority (84.5%) of patients undergoing autologous transplantation within 1 year of diagnosis. The majority of the patients underwent a single autologous transplantation (83.5%) using a melphalan based conditioning (91%). The patients at both centers had similar age, gender, racial and immunoglobulin subtype distributions. The cumulative incidence of disease relapse at 2 years was 85% (95% CI: 81–87%) in this study. The median time between first transplant and relapse was 16.3 months (range: 0.6–177.8 months). The median follow-up time was 35.1 months (range: 0.6–177.8 months).
3. Statistical analysis All statistical analyses were performed using SAS software version 9.2 (SAS Institute, Inc., Cary, NC) and R Statistical software version 2.4.1 [26]. Minor allele frequencies and LD among SNPs genotyped within a particular gene were estimated. Assuming an additive model for the SNPs, the association between each of these SNPs and disease progression at 2 years was evaluated using a Cox proportional hazards model after adjustment for covariates. The following covariates were included in the initial model: clinical site (Mayo Clinic vs. University of Minnesota), age at transplant, gender, self-reported race, immunoglobulin subtype, Durie-Salmon stage at diagnosis, cytogenetic risk, time from diagnosis to transplant,
4.1. Association between DNA repair SNPs and disease progression After adjustment for clinical site, number of relapses prior to transplant, time between initial diagnosis and first transplant, year of autologous HCT and race, nine SNPs in the NER pathway (Table 2a) and three SNPs in the BER pathway (Table 2b) were nominally associated with disease progression (p ≤ 0.05). However, none of these SNPs remained significantly associated with disease progression after adjusting for multiple comparisons using the modified Bonferroni correction. The findings were similar when the analyses were restricted to the patients of European-American
B. Thyagarajan et al. / Leukemia Research 37 (2013) 1527–1531 Table 1 Demographic and transplant characteristics of patients who underwent hematopoietic stem cell transplant at the Mayo Clinic and the University of Minnesota for treatment of multiple myeloma: 1998–2007. Variable
N = 695 (%)
Clinical Center (Mayo) 541 (78%) 154 (22%) University of Minnesota Age at diagnosis 60 239 (34.4) Age at first transplant 60 259 (37.3) Race European American 663 (95.4) African American 14 (2.0) Hispanic 4 (0.6) Other 11 (1.6) Missing 3 (0.4) Gender Male 406 (58.4) Female 289 (41.6) Ig subtype (TYPE1) IgG 416 (59.9) IgA 142 (20.4) Light chain disease (lambda light chain + kappa light chain) 113 (16.3) Non secretory 15 (2.1) 6 (0.9) IgD 3 (0.4) IgM Durie Salmon stage at diagnosis ≤2 239 (34.4) 3 414 (59.6) 42 (6.0) Missing Cytogenetic riska Standard risk 524 (75.4) High risk 60 (8.6) Missing 111 (16.0) Time from diagnosis to transplant ≤1 year 587 (84.5) >1 year 108 (15.5) Second transplant Yes 115 (17.5) No 580 (83.5) Time between first and second transplant median/range 33.4 (2.3–130.6) Type of second transplant Autologous 101 (14.5) Allogeneic 14 (2.0) 580 (83.5) NA Status pre-transplant 466 (67.1) Plateau/response 229 (32.9) Relapse/refractory Number of relapses prior to transplant 520 (74.8) 0 145 (20.9) ≥1 30 (4.3) Missing Conditioning 42 (6.0) Melphalan
Contents lists available at ScienceDirect
Leukemia Research journal homepage: www.elsevier.com/locate/leukres
Genetic variants in DNA repair pathways are not associated with disease progression among multiple myeloma patients Bharat Thyagarajan a,∗ , Mukta Arora b , Weihua Guan c , Helene Barcelo a , Scott Jackson d , Shaji Kumar e , Morie Gertz e a
Department of Laboratory Medicine and Pathology, University of Minnesota, Minneapolis, MN, USA Division of Hematology, Oncology and Transplantation, Department of Medicine, University of Minnesota, Minneapolis, MN, USA c Division of Biostatistics, School of Public Health, University of Minnesota, Minneapolis, MN, USA d Biostatistics and Informatics Core, Masonic Cancer Center, University of Minnesota, Minneapolis, MN, USA e Division of Hematology, Department of Medicine, Mayo Clinic, Rochester, MN, USA b
a r t i c l e
i n f o
Article history: Received 25 February 2013 Accepted 8 July 2013 Available online 12 October 2013 Keywords: Multiple myeloma Melphalan Autologous transplantation Nucleotide excision repair Base excision repair Single nucleotide polymorphisms Disease progression
a b s t r a c t DNA damage induced by high dose melphalan and autologous transplantation is repaired by the nucleotide excision repair (NER) and base excision repair (BER) pathways. We evaluated the association between single nucleotide polymorphisms (SNPs) (n = 311) in the NER and BER pathways and disease progression in 695 multiple myeloma patients who underwent autologous transplantation. None of the SNPs were associated with disease progression. Pathway based analyses showed that the NER pathway had a borderline association with disease progression (p = 0.09). These findings suggest that common variation in the NER and BER pathways do not substantially influence disease progression in multiple myeloma patients. © 2013 Elsevier Ltd. All rights reserved.
1. Introduction High dose chemotherapy using melphalan supported by autologous transplantation is currently the standard of care for treatment of multiple myeloma [1–8]. A variety of DNA repair pathways are involved in the repair of the melphalan-induced DNA damage that include DNA alkylation and DNA interstrand cross-links [9–11]. The considerable heterogeneity in clinical response to high dose melphalan and autologous transplantation among patients undergoing treatment for multiple myeloma [12,13] suggests that inter-individual variation in DNA repair may be an important determinant of treatment response. In vitro experiments have clearly shown that the nucleotide excision repair pathway (NER) plays a crucial role in the repair of monoadducts [14]. Another study has also shown the base excision repair (BER) pathway to be important in repair of melphalan induced monoadducts [15]. Previous studies have shown that
∗ Corresponding author at: University of Minnesota, Department of Laboratory Medicine and Pathology, 515 Delaware Street SE, 1-136 Moos Towers, Minneapolis, MN 55455, USA. Tel.: +1 612 624 1257; fax: +1 612 625 8950. E-mail address: [email protected] (B. Thyagarajan). 0145-2126/$ – see front matter © 2013 Elsevier Ltd. All rights reserved. http://dx.doi.org/10.1016/j.leukres.2013.07.012
genetic variations in both the NER and BER pathway that modify DNA repair capacity influence the outcome of cancer chemotherapy [16–18]. In NER, a multi-component repair complex incises a 24–32mer oligonucleotide containing the lesion and the gap created is filled by DNA polymerase and DNA ligases [19]. During BER the damaged base is removed by a glycosylase, the resulting apurinic deoxyribose is excised by a separate apurinic endonuclease or by an apurinic lyase and the resulting single nucleotide gap is usually filled in as a single nucleotide repair patch [19]. Consistent with important roles of NER and BER pathways in the repair of melphalan induced DNA damage, two studies have shown genetic variants in NER and BER genes to be associated with response to high dose melphalan based chemotherapy [20,21]. Though, these candidate gene studies provide preliminary evidence of the importance of genetic variation in the DNA repair pathway in determining treatment response, both the NER and BER pathways are complex biological processes consisting of several genes. Hence, a systematic evaluation of genetic variation in both these pathways is needed to comprehensively evaluate the role of genetic variation in these DNA repair pathways in determining treatment response after high dose melpahalan and autologous transplantation. We genotyped all common genetic variation (minor allele frequency (MAF) ≥5%) in 24 NER, 21 BER and 7 genes that are common
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B. Thyagarajan et al. / Leukemia Research 37 (2013) 1527–1531
to both DNA repair pathways and evaluated their association with disease progression among a cohort of 695 multiple myeloma patients treated with high dose melphalan and autologous transplantation at the Mayo Clinic or the University of Minnesota. 2. Materials and methods 2.1. Patient selection The patients were recruited from two centers; the Mayo Clinic and the University of Minnesota. We included 541 consecutive adult patients (age >18 years) from the Mayo Clinic and 154 consecutive adult patients from the University of Minnesota who underwent an autologous HCT for multiple myeloma between January 1998 and July 2009 and had blood samples available for DNA extraction. Patients who underwent tandem autologous followed by allogeneic transplants were excluded from this study. Patients who underwent a salvage allogeneic transplant after autologous transplant for disease relapse or progression were censored at the event (disease relapse or progression). 2.2. Clinical data and collection of DNA samples All clinical data from the Mayo Clinic were obtained using the Mayo Clinic Blood and Marrow Transplant database. All clinical data from the University of Minnesota was obtained using the University of Minnesota Blood and Marrow Transplant Database and supplemented by chart reviews when necessary. Demographic and transplant characteristics included age at transplant, gender, race, immunoglobulin subtype, Durie-Salmon stage, cytogenetic risk group, time from diagnosis to transplant, clinical center, conditioning regimen and year of autologous HCT. Patients were censored at death or for patients surviving in complete remission at last contact. Time from transplant to disease relapse or progression was taken as time to disease progression. The International Myeloma Working Group (IMWG) Uniform Response Criteria were used to assess post-transplant disease relapse [22]; however, free light chain assay were not uniformly available, especially from the earlier years of study [22]. DNA samples from patients were obtained from peripheral blood samples obtained at the time of stem cell collection prior to autologous HCT. DNA was extracted using the Qiagen Midi Blood kit (Qiagen Inc., San Jose, CA) as per manufacturer recommendations. All DNA samples were stored in −80 ◦ C freezers until further analyses.
status pre-transplant, number of relapses prior to transplant, conditioning pre-transplant (melphalan based versus other) and year of autologous HCT to adjust for differences in pre-transplant treatment based regimens. Significant covariates were selected by a backward stepwise regression procedure where covariates with p < 0.1 were included in the final model. Significant covariates selected in the final model included clinical site (Mayo clinic vs. University of Minnesota), number of relapses prior to transplant, time between initial diagnosis and first transplant, disease status prior to transplantation, year of autologous HCT (1998–2003 vs. 2004–2009) and self-reported race. We also restricted these analyses to patients of European-American descent. We used a modified Bonferroni correction after accounting for SNPs in linkage disequilibrium [27] to adjust for false positive findings and a p value of ≤2 × 10−4 was considered to be statistically significant. Among SNPs found to be nominally associated with disease progression (p ≤ 0.05), we evaluated pair-wise SNP-SNP and SNPclinical covariate interactions. Assuming an additive genetic model and adjustment for multiple comparisons using the modified Bonferroni correction, this study has 87% power to detect a SNP-disease progression association with a hazards ratio (HR) of 1.45 and MAF of 0.2, 77% power to detect HR of 1.4 and MAF of 0.3, or 85% power to detect HR of 1.35 and MAF of 0.4. We also performed a pathway analysis to globally evaluate whether genetic variation in the NER and BER pathways was associated with disease progression. For the pathway analysis, we selected the lowest p-value from each gene in a particular pathway (genes involved in both NER and BER were included in both pathways) and summed the −2 log(p) over all genes in a particular pathway (NER or BER) analogous to a Fisher’s combined probability test [26]. We then used permutation testing (n = 1000) to evaluate whether the summed −2 log(p) value for all the genes in a particular pathway is greater than expected by chance.
2.3. SNP selection and genotyping
4. Results We used data from Environmental Genome Project [23–25] to identify and select Linkage Disequilibrium (LD) tagging single nucleotide polymorphisms (tagSNPs) with r2 >0.8 that had MAF ≥5% in the Caucasian population in 24 NER, 21 BER and 7 genes that are common to both DNA repair pathways. If tagSNPs were not identified in the Environmental Genome Project, we used HapMap data for European American populations to identify tagSNPs that had ≥5% MAF in European American populations using the Genome Variation Server software (http://gvs.gs.washington.edu/GVS/). Single nucleotide polymorphisms with MAF ≥5% that did not fit into any of the LD bins were also included in this study. This tagSNPs approach allowed us to comprehensively evaluate all genetic variation with MAF ≥5% in the genes evaluated. Though some SNPs included in this study resulted in an amino acid change, individual SNPs that resulted in an amino acid change or that were predicted to affect protein function were not specifically included in this study. This approach allowed us to genoytpe 168 SNPs in 24 genes in the NER pathway, 104 SNPs in 21 genes in the BER pathway and 42 SNPs in 7 genes that participate in both DNA repair pathways (n = 314). All DNA samples were genotyped using the Sequenom iPLEX system at the Biomedical Genomics Center at the University of Minnesota using primers and probes designed by Sequenom primer design software. After excluding monomorphic SNPs (n = 3), 311 SNPs were included for further analyses.
The baseline characteristics of the study population are described in Table 1. All patients underwent an autologous HCT for treatment of multiple myeloma at the Mayo Clinic (N = 541) or the University of Minnesota (n = 154). The median age at diagnosis for this cohort was 56.5 years (range: 23.9–75.3 years). The median time from diagnosis of multiple myeloma to first transplant was 6.5 months (range: 3.2–110.6 months) with a majority (84.5%) of patients undergoing autologous transplantation within 1 year of diagnosis. The majority of the patients underwent a single autologous transplantation (83.5%) using a melphalan based conditioning (91%). The patients at both centers had similar age, gender, racial and immunoglobulin subtype distributions. The cumulative incidence of disease relapse at 2 years was 85% (95% CI: 81–87%) in this study. The median time between first transplant and relapse was 16.3 months (range: 0.6–177.8 months). The median follow-up time was 35.1 months (range: 0.6–177.8 months).
3. Statistical analysis All statistical analyses were performed using SAS software version 9.2 (SAS Institute, Inc., Cary, NC) and R Statistical software version 2.4.1 [26]. Minor allele frequencies and LD among SNPs genotyped within a particular gene were estimated. Assuming an additive model for the SNPs, the association between each of these SNPs and disease progression at 2 years was evaluated using a Cox proportional hazards model after adjustment for covariates. The following covariates were included in the initial model: clinical site (Mayo Clinic vs. University of Minnesota), age at transplant, gender, self-reported race, immunoglobulin subtype, Durie-Salmon stage at diagnosis, cytogenetic risk, time from diagnosis to transplant,
4.1. Association between DNA repair SNPs and disease progression After adjustment for clinical site, number of relapses prior to transplant, time between initial diagnosis and first transplant, year of autologous HCT and race, nine SNPs in the NER pathway (Table 2a) and three SNPs in the BER pathway (Table 2b) were nominally associated with disease progression (p ≤ 0.05). However, none of these SNPs remained significantly associated with disease progression after adjusting for multiple comparisons using the modified Bonferroni correction. The findings were similar when the analyses were restricted to the patients of European-American
B. Thyagarajan et al. / Leukemia Research 37 (2013) 1527–1531 Table 1 Demographic and transplant characteristics of patients who underwent hematopoietic stem cell transplant at the Mayo Clinic and the University of Minnesota for treatment of multiple myeloma: 1998–2007. Variable
N = 695 (%)
Clinical Center (Mayo) 541 (78%) 154 (22%) University of Minnesota Age at diagnosis 60 239 (34.4) Age at first transplant 60 259 (37.3) Race European American 663 (95.4) African American 14 (2.0) Hispanic 4 (0.6) Other 11 (1.6) Missing 3 (0.4) Gender Male 406 (58.4) Female 289 (41.6) Ig subtype (TYPE1) IgG 416 (59.9) IgA 142 (20.4) Light chain disease (lambda light chain + kappa light chain) 113 (16.3) Non secretory 15 (2.1) 6 (0.9) IgD 3 (0.4) IgM Durie Salmon stage at diagnosis ≤2 239 (34.4) 3 414 (59.6) 42 (6.0) Missing Cytogenetic riska Standard risk 524 (75.4) High risk 60 (8.6) Missing 111 (16.0) Time from diagnosis to transplant ≤1 year 587 (84.5) >1 year 108 (15.5) Second transplant Yes 115 (17.5) No 580 (83.5) Time between first and second transplant median/range 33.4 (2.3–130.6) Type of second transplant Autologous 101 (14.5) Allogeneic 14 (2.0) 580 (83.5) NA Status pre-transplant 466 (67.1) Plateau/response 229 (32.9) Relapse/refractory Number of relapses prior to transplant 520 (74.8) 0 145 (20.9) ≥1 30 (4.3) Missing Conditioning 42 (6.0) Melphalan
