Abstract

Introduction of new myeloma therapies offers new options for patients refractory to immunomodulatory drugs (IMiDs) and proteasome inhibitors (PIs). In this multicenter study, patients with relapsed multiple myeloma, who have received at least three prior lines of therapy, are refractory to both an IMiD (lenalidomide or pomalidomide) and a PI (bortezomib or carfilzomib), and have been exposed to an alkylating agent were identified. The time patients met the above criteria was defined as time zero (T0). Five hundred and forty-three patients diagnosed between 2006 and 2014 were enrolled in this study. Median age at T0 was 62 years (range 31–87); 61% were males. The median duration between diagnosis and T0 was 3.1 years. The median number of lines of therapy before T0 was 4 (range 3–13). The median overall survival (OS) from T0 for the entire cohort was 13 (95% confidence interval (CI) 11, 15) months. At least one regimen recorded after T0 in 462 (85%) patients, with a median (95% CI) progression-free survival and OS from T0 of 5 (4, 6), and 15.2 (13, 17) months, respectively. The study provides the expected outcome of relapsed multiple myeloma that is refractory to a PI and an IMiD, a benchmark for comparison of new therapies being evaluated.

Introduction

Treatment options for multiple myeloma (MM) have expanded considerably in the last decade with the introduction of several new classes of drugs. The use of these drugs as part of highly effective combinations for treatment of newly diagnosed and relapsed myeloma have resulted in improved survival of patients with this disease.1, 2, 3 From a genetic standpoint, MM is a very heterogeneous disease at the time of diagnosis and undergoes further genomic evolution during the natural course of the disease.4, 5, 6, 7 Although the current treatments are highly effective in controlling the disease and producing deep remissions, including molecular remissions, the disease invariably relapses after a period of time, requiring continued therapeutic intervention to maintain disease control.8, 9, 10, 11, 12, 13, 14 The clinical course of the disease and accompanying genomic and phenotypic alterations in the myeloma cell have been studied extensively, especially in recent years.15 As the disease relapses, it becomes increasingly refractory to the currently available drugs resulting in ever shorter remissions, with the vast majority of patients eventually succumbing to complications of relapsed, refractory disease.15, 16 Hence, it is clear that new therapeutic approaches will have to be developed to further prolong disease control beyond what is afforded by the current drugs. Recently, monoclonal antibodies and immune approaches have shown significant promise in controlling myeloma, with two monoclonal antibodies already approved for use in relapsed disease and several others currently in clinical trials.11, 12, 13, 14 In order to better estimate the impact of the newer therapies, it is important to understand the outcomes of patients who become refractory to commonly used classes of drugs, such as the proteasome inhibitors (PIs) and immunomodulatory drugs (IMiDs). In a previous study, we examined the natural history of MM that had become refractory to bortezomib as well as refractory or ineligible to receive at least one of the IMiDs (thalidomide or lenalidomide).15 The outcome of these patients, from the time they became refractory to these drugs was rather poor, with a progression-free survival (PFS) of 5 months and an overall survival (OS) of 9 months. However, not only have newer drugs in these classes become available, but combinations of these drugs have increasingly become the treatments of choice for newly diagnosed as well as relapsed disease. Given the dramatic change in the treatment approaches in the past several years and the consequent improvements in the survival outcomes, it is important to define the natural history of myeloma among patients who have been exposed to the most common classes of drugs used currently such as the PIs, IMiDs and alkylators.1 We undertook the current multicenter, retrospective study, to obtain a real world assessment of the outcomes of patients who have received at least three prior lines of therapy, were refractory to both an IMiD (lenalidomide or pomalidomide) and a PI (bortezomib or carfilzomib), and had been exposed to an alkylating agent; a group representative of those who are most in need of newer therapies.

Patients and methods

Patients diagnosed with MM on or after 1 January 2006 were included in the current study based on data collected from existing medical records from multiple centers across North America, Europe and Asia-Pacific. Patients with relapsed MM, who have received at least three prior lines of therapy, were refractory to both IMiD (lenalidomide and/or pomalidomide) and a PI (bortezomib and/or carfilzomib), and had been exposed to an alkylating agent (melphalan including its use as conditioning for transplant, cyclophosphamide or bendamustine) were identified from review of medical records and included in the study. Refractoriness to a drug (administered either alone or in combination with other agents) was defined as no response (less than partial response) or progression on therapy or within 60 days of stopping the drug-containing regimen as per published consensus criteria.17 The date they met these criteria was defined as time zero (T0). Patients should have received both a PI and an IMiD in the at least one of the last two lines of therapy immediately prior to T0. Patients who were alive at the time of last contact, were required to have at least 6 months of follow up from T0. Patients were followed until either the end of study follow-up, death or loss to follow-up. Given the goal of using this data as a benchmark for assessing future clinical trial results, we only included patients who would typically be considered for participation in a clinical trial. Hence, patients had to have measurable disease at T0 (defined conventionally as at least one of the following: serum M protein 1.0 g/dl, 24 h urine M-protein excretion 200 mg or bone marrow plasma cells 30%). Patients with prior allogeneic stem cell transplantation were excluded from the study.

Clinical and laboratory data pertaining to the time of diagnosis and from the time of individual relapses were obtained from clinical records. The dates of initiation and discontinuation of each treatment regimen, as well as the reason for discontinuation were identified, with specific attention to confirm use and discontinuation of IMiDs and PIs due to emergence of resistance or toxicity. Detailed data collection sheets were developed, which were used at all the study sites for uniformity of data collection. The data were sent to a centralized area (Axiom) for analysis in a de-identified fashion. Institutional Review Boards from each site approved the study and the use of patient medical records and was conducted in accordance with the principles of the Declaration of Helsinki.

The primary objective of the current study was to determine OS and document current patterns of treatment among patients with relapsed MM, who met the inclusion criteria. The secondary objectives included determination of (i) the response rates to different regimens following development of refractory disease, (ii) the PFS, time to progression, time to next treatment and duration of responses to subsequent treatments following development of dual refractoriness and (iii) prognostic factors for survival in this patient group.

The response categories were defined according to the International Myeloma Working Group consensus criteria and the response rate was defined as the proportion of patients achieving at least a partial response, from among those patients with valid response data. Patients who did not receive a myeloma regimen following T0 were not included in the response rate analysis. The response rate and best response were calculated for each regimen used after T0.

OS was defined as the length of time between T0 and the date of death. Patients without a recorded death date were censored for OS at their last contact date. PFS was defined as the length of time between T0 until the earlier of the date at which criteria for progression were met or the date of death. Patients who did not have a documented progression after T0 and who did not have a recorded death date were censored for PFS at their last contact date. OS and PFS were estimated using the Kaplan–Meier method with the median survival durations summarized. Cox regression analysis was performed to determine which prognostic factors at T0 and/or at diagnosis correlated with improved OS or PFS from T0. Prognostic factors were dichotomized, where appropriate, using standard myeloma cutoffs.

Duration of response was defined as the length of time between the date a patient first achieved a partial response or greater response level and the earlier of the dates at which criteria for progression (defined by International Myeloma Working Group criteria) were met, or the date of death. Patients who did not have a documented progression after achieving at least a partial response and who were still alive at last contact were censored for duration of response at the date of last contact. Patients who did not achieve a partial response or better following T0 and patients for whom the date of such response was missing were excluded from the duration of response analysis. Duration of response was estimated using the Kaplan–Meier method with the median duration of response summarized.

All analyses were performed using SAS version 9.2 Software (SAS Institute, Cary, NC, USA).

Results

The study enrolled 543 patients from centers in North America (n=181), Europe (n=318) and the Asia Pacific (n=44). The median (range) age for the patient group was 59 years (27–85) at diagnosis and 62 years (31–87) at T0; 61% were males. The median (95% confidence interval (CI)) estimated follow-up from diagnosis and from T0 were 61 (57, 66) months and 13 (11, 15) months, respectively. The median (range) duration between diagnosis of myeloma and study entry (T0) was 3.1 years (0.6–8.7). The baseline characteristics from diagnosis and from T0 are shown in Table 1. The median number of lines of therapy before T0 was 4 (3–13); 48% had a prior stem cell transplant. Four hundred 62 (85%) patients received at least one treatment regimen after T0 and form the cohort for response and response-related outcome analyses. In terms of prior therapy, 435 (94%) and 45 (10%) patients had received bortezomib or carfilzomib, respectively, and 456 (99%) and 26 (6%) patients had received lenalidomide or pomalidomide, respectively. Baseline characteristics for these 462 patients are also shown in Table 1.

Table 1: Baseline characteristics from diagnosis and from T0

Initial therapy following time zero

We initially examined the types of therapy that were employed immediately following T0 among the 462 patients (85%) who had a treatment identified in the medical records following T0. The drugs utilized (alone or in combinations) for the initial treatment of the relapsed refractory disease are detailed in Table 2. For these 462 patients, the median (range) number of recorded regimens after T0 was 2 (1–9). As expected, majority of patients received a regimen that included dexamethasone (339, 73.4%). Similarly, nearly three quarters received a combination regimen rather than a single agent. Among the combinations, only a third of the combinations had two drugs other than steroids (triplets). Interestingly, in this group of patients who met the criteria for having PI refractory disease, 81 patients (17.5%) received a bortezomib-containing treatment regimen immediately following T0. Carfilzomib was used in another 38 (8.2%) patients, with nearly a quarter of the patients receiving a PI containing regimen. An IMiD was part of the initial regimen after T0 in 274 (60%) patients, including 11% with lenalidomide, 39% with pomalidomide and 9.5% with thalidomide. Alkylating agents (cyclophosphamide, melphalan or bendamustine) were commonly employed at this stage of the disease with 173 (37.5%) patients receiving a regimen that contained one of these drugs. Also of interest, 32 (7%) and 25 (5.4%) of patients received cisplatin and etoposide, respectively, likely to be a reflection of use of regimens such as DT-PACE.

Table 2: Distribution of drug types across post T0 treatment regimens

Nearly a third of patients achieved a partial response or better to the first regimen used after T0 (154/462, 33%) including a very good partial response or better in 50 (11.8%) of the patients. Nearly a third of the patients 162 (35.1%) had stable disease as their best response to the treatment and the remaining patients 146 (31.7%) had progressive disease to the first line of therapy following T0 or a response was not assessable. The response rates and categories of responses observed are as detailed in Table 3. We specifically looked at the response rates of regimens containing carfilzomib or pomalidomide, as most patients had not received these drugs prior to T0; these results are detailed in Supplementary Tables 1 And 2. The most common reason for discontinuation of a treatment regimen was lack of response or disease progression followed by adverse event or completion of planned course of treatment.

Table 3: Best response to regimen, by regimen number, for the regimens following T0

Survival outcomes

The median (95% CI) OS for the entire cohort was 13.0 months (11.1, 14.5) from T0 (Figure 1a). The median (95% CI) PFS for the 462 patients who received at least one regimen after T0 was 5.0 months (4.3, 5.7) and the median (95% CI) OS was 15.2 months (13.2, 17.0) (Figure 1b). For the 81 patients who did not receive any further therapy, median (95% CI) OS was 2.1 months (1.2, 3.0). Both PFS and OS were influenced by the response to the first regimen after T0 (Figures 2a and b). The patient disposition over time is detailed in Supplementary Table 3. The PFS and OS based on other clinical characteristics such as International Staging System, fluorescence in-situ hybridization (FISH) risk status at diagnosis and T0, serum creatinine and lines of therapy are shown in Supplementary Figures 1–6.

Figure 1
Figure 1

OS from T0 for all enrolled patients (N=543) (a); PFS and OS from T0 for patients receiving a therapy post T0 (b).

Figure 2
Figure 2

Figure shows the Kaplan–Meier curves for PFS (a) and OS (b) based on depth of response to first regimen given post T0.

Prognostic factors

We performed additional analyses to identify prognostic factors predicting PFS and OS following T0. Factors impacting the OS and PFS from T0 identified in a univariate analysis are shown in Table 4. In a multivariate model employing step-wise selection that included most of these variables, shorter duration from diagnosis to T0, higher number of lines of therapy and higher International Staging System at T0 were independently predictive for inferior PFS and OS, and in addition serum creatinine at diagnosis was prognostic for OS as well (Table 5). We also examined the differences between patients who had a survival <3 months from T0 and those surviving over 2 years from T0 (Supplementary Table 4).

Table 4: Univariate analysis of prognostic factors for PFS and OS from T0
Table 5: Multivariate analysis

Discussion

The current study provides an assessment of the current treatment landscape of MM, before the introduction of the monoclonal antibodies. Although a small proportion of patients in the current study may have received the monoclonal antibodies, the oral PI ixazomib and the histone deacetylase inhibitor panobinostat, most patients were treated through their course with the major drug classes including PI, IMIDs and alkylators. Interestingly, a significant number of patients received either a single active drug with or without steroids. However, the use of single-agent dexamethasone was substantially low compared with prior studies. It is important to highlight that the current study included patients from broad geographical regions, thus providing a true picture of the current state.

It is informative to contrast the findings of this study with a previous similar study that included patients from an earlier period.15 The previous study had included patients who were refractory to bortezomib and refractory or ineligible to one of the IMiDs including lenalidomide and thalidomide. The current study included patients who may have been exposed to more drugs (pomalidomide and carfilzomib) and had to be refractory to at least one drug from each class in addition to having received at least three prior lines of therapy and having been exposed to an alkylator, thus including a more advanced patient population. Finally, we limited the patients to those who were diagnosed after 2006, to better capture the effect of current upfront regimens and to limit any bias from the relatively small group of patients with favorable biology. Despite the more advanced disease status, the PFS in the current study was similar to that observed in the prior study. This probably reflects the increasing access to newer drugs from the same class, such as carfilzomib, which has been shown to be more effective compared with bortezomib in the ENDEAVOR study.8 Importantly, there has been a substantial improvement in the OS of the patients from 9 months in the prior study to over a year in the current study. This probably reflects increasing access to the newer drugs across the multiple lines of therapy and, to a limited extent, the access to newer drug classes in the context of clinical trials.8, 9, 10, 11, 12, 13, 14, 18, 19, 20

As seen in the prior studies and the recent phase 3 trials, both the number of prior lines of therapy and the duration from diagnosis to T0 are prognostic for PFS and OS, albeit in different directions. Longer time between diagnosis and T0 reflects better a more favorable disease biology and is associated with better survival outcomes. However, more lines of therapy reflect a more refractory myeloma clone with little residual drug sensitivity and portends a poorer outcome. The ability to examine the impact of conventional risk factors such as high-risk FISH abnormalities and International Staging System was limited in this data set due to missing data, a reflection of the unselected nature of patients in this study. However, the results do suggest an important role of these factors at relapse and should be routinely included in clinical trials of relapsed myeloma. The depth of response to the first regimen after T0 had a profound impact on the PFS as well as OS outcomes. There appeared to be a trend towards improved response rate, especially the depth of response among those receiving a carfilzomib or pomalidomide containing regimen, reflecting lack of prior exposure to these drugs.

This study once again highlights the poor outcome for patients with relapsed refractory MM, who have become refractory to the major classes of drugs currently used in the clinic across the globe. It is clear that these patients need access to newer classes of drugs. The current study results define a new benchmark for comparison of the results of the current clinical trials with the newer drug class. As has been shown in the context of daratumumab used as single agent in a patient group similar to that shown here, newer drugs with novel mechanisms of action can improve the outcomes of patients with relapsed, refractory MM.11

There is clearly some bias that is inevitable in a study such as this, which primarily includes referral centers. This is evident in the younger median age of the study population, reflecting both a referral bias and the fact that younger patients are more likely to continue to receive multiple therapies. However, for the purpose of this study, which is to form a realistic benchmark for assessing new drugs, the study population is representative of those that go one clinical trials involving new drugs.

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Acknowledgements

Janssen Pharmaceuticals provided funding for the study.

Author contributions

All authors (except BGMD) provided patient data and were involved in manuscript preparation. SKK was involved in the statistical analysis.

Author information

Affiliations

  1. Department of Hematology, Mayo Clinic Rochester, Rochester, MN, USA

    • S K Kumar
  2. School of Medicine, National and Kapodistrian University of Athens, Athens, Greece

    • M A Dimopoulos
    • , E Kastritis
    •  & E Terpos
  3. Division of Hematology, Karolinska Institutet, Karolinska University Hospital at Huddinge, Stockholm, Sweden

    • H Nahi
  4. National Center for Tumor Diseases Heidelberg, Heidelberg, Germany

    • H Goldschmidt
  5. Department Med. V, University Hospital Heidelberg, Heidelberg, Germany

    • H Goldschmidt
    •  & J Hillengass
  6. Oncologie hematologique et therapie cellulaire, chu de poitiers, Poitiers, France

    • X Leleu
  7. Department of Hematology, Ankara University School of Medicine, Ankara, Turkey

    • M Beksac
  8. Hematologic Malignancies Program, H. Lee Moffitt Cancer Center, Tampa, FL, USA

    • M Alsina
  9. Department of Hematology, Skane University Hospital, Malmö, Sweden

    • A Oriol
    •  & I Turesson
  10. Department of Experimental, Diagnostic and Specialty Medicine, University of Bologna, Bologna, Italy

    • M Cavo
  11. Department of Hematology, University Hospital of Salamanca (HUS/IBSAL), Salamanca, Spain

    • E M Ocio
  12. Department of Hematolgy, Hospital Universitario de Salamanca, Salamanca, Spain

    • M V Mateos
  13. Massachusetts General Hospital, Boston, MA

    • E K O'Donnell
  14. Division of Oncology, Department of Medicine, Washington University School of Medicine, Saint Louis, MO, USA

    • R Vij
  15. Department of Hematology, VU University Medical Center, Amsterdam, The Netherlands

    • H M Lokhorst
  16. VU University Medical Center, Amsterdam, The Netherlands

    • N W C J van de Donk
  17. Department of Hematology, Seoul St. Mary’s Hospital, College of Medicine, The Catholic University of Korea, Seoul, The Republic of Korea

    • C Min
  18. Weill Cornell Medical College, New York, NY, USA

    • T Mark
  19. Department of Hematology, Skåne University Hospital, Lund University, Lund, Sweden

    • M Hansson
  20. Department of Medicine, Center of Oncology, Hematology and Palliative Care, Wilhelminen Cancer Research Institute, Wilhelminenspital, Vienna, Austria

    • H Ludwig
  21. Department of Hematology and Medical Oncology, Icahn School of Medicine at Mount Sinai, New York, NY, USA

    • S Jagannath
  22. Myeloma Study Group, Belgian Hematological Society, Brussels, Belgium

    • M Delforge
  23. Department of Haematology, North West London NHS Trust, NPH Hospital, London, UK

    • C Kyriakou
  24. Division of Hematology/Oncology, Medical College of Wisconsin, Milwaukee, WI, USA

    • P Hari
  25. Section of Hematology and Coagulation, Department of Medicine, Sahlgrenska University Hospital, Gothenburg, Sweden

    • U Mellqvist
  26. Department of Hematologic Oncology and Blood Disorders, Levine Cancer Institute/Carolinas HealthCare System, Charlotte, NC, USA

    • S Z Usmani
  27. Department of Hematology and Bone Marrow Transplantation, University of Medical Sciences in Poznan, Poland, Poznan, Poland

    • D Dytfeld
  28. Greenebaum Cancer Center, University of Maryland School of Medicine, Baltimore, MD, USA

    • A Z Badros
  29. Department of Hematology, Nantes University Hospital, Nantes, France

    • P Moreau
  30. Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, The Republic of Korea

    • K Kim
  31. Clínica Universidad de Navarra, University of Navarra, Pamplona, Spain

    • P R Otero
  32. Department of Internal Medicine, Gachon University Gil Medical Center, Incheon, The Republic of Korea

    • J H Lee
  33. Division of Haematology, McGill University Health Center, Montreal, QC, Canada

    • C Shustik
  34. McGill University, Montreal, QC, Canada

    • D Waller
  35. Department of Haematology-Oncology, National University Health Systems, Singapore

    • W J Chng
  36. Department of Hematology, Tokushima Prefectural Central Hospital, Tokushima, Japan

    • S Ozaki
  37. Department of Hematology-Oncology, Chonnam National University Hwasun Hospital, Jeollanamdo, The Republic of Korea

    • J-J Lee
  38. Hospital Dr. Peset, Valencia, Spain

    • J de la Rubia
  39. HematologicOncology Clinic, Center for Specific Organs, National Cancer Center, Goyang, South Korea

    • H S Eom
  40. Department of Hematology, Hospital Clinic iProvincial, Barcelona, Spain

    • L Rosinol
  41. Hospital Universitario 12 de Octubre, Madrid, Spain

    • J J Lahuerta
  42. Institut Català d'Oncologia, Hospital Duran i Reynals, Barcelona, Spain

    • A Sureda
  43. Yonsei University College of Medicine, Severance Hospital, Seoul, The Republic of Korea

    • J S Kim
  44. Samuel Oschin Comprehensive Cancer Institute, CedarsSinai Outpatient Cancer Center, Los Angeles, CA, USA

    • B G M Durie

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Competing interests

SKK: research funding (Abbvie, Celgene, Janssen, Merck, Novartis, Roche, Sanofi and Takeda) and honoraria (Skyline Diagnostics); MAD: honoraria (Celgene, Janssen, Amgen and Takeda); ET: research funding and honoraria (Amgen, Celgene and Janssen), and honoraria (Novartis, GSK, Bristol Myers Squibb and Takeda); HG: research funding, advisory board and honoraria (Janssen, Celgene, Novartis and BMS), research funding and honoraria (Chugai), and advisory boards (Amgen and Takeda); JH: consultancy, honoraria and advisory board (Amgen), honoraria and advisory board (Janssen, Celgene and Novartis), honoraria (Bristol Myers Squibb) and research funding (Sanofi); MB: speakers bureau and advisory board (Celgene, Janssen-Cilag, Amgen, Novartis, Takeda and Bristol Myers Squibb); MA: speakers bureau (Janssen); AO: advisory board and consultancy (Amgen and Janssen), and consultancy (Takeda); MVM: honoraria and advisory board (Janssen, Celgene, Takeda and Amgen); RV: research support and consultancy/honoraria (Amgen, Celgene and Takeda), and consultancy/honoraria (Bristol Myers Squibb, Janssen, Karyopham and Abbvie); H Lokhorst: research funding and advisory board (Janssen), and research funding (Genmab); NvdD: research funding (Janssen, Celgene, Amgen and BMS) and advisory board (Janssen, Celgene, Amgen, BMS and Novartis); TM: research funding (Amgen and Celgene); MH: advisory board (Celgene, Janssen, Amgen and Takeda); H Ludwig: speakers bureau (Celgene, Takeda, Amgen and Janssen-Cilag), advisory board (Celgene, Amgen, Janssen-Cilag, AbbVie and Bristol Myers Squibb) and research funding (Takeda and Amgen); MD: consultancy (Amgen, Bristol Myers Squibb, Celgene, Janssen and Takeda) and research funding (Celgene and Janssen); U-HM: advisory board (Amgen and Takeda) and honoraria (Amgen, Celgene, Takeda, Mundipharma, Janssen and Novartis); SZU: advisory board (Amgen, Celgene and Skyline Diagnostics), speakers bureau (Amgen, Celgene and Takeda) and research funding (Amgen, Celgene, Janssen, Sanofi, Pharmacyclics, Array Biopharma and Takeda); PM: advisory board (Celgene, Takeda, Janssen, Novartis and Amgen); LR: honoraria (Janssen and Celgene); all the other authors declare no conflicts of interest.

Corresponding author

Correspondence to S K Kumar.

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Publication history

Received

Revised

Accepted

Published

DOI

https://doi.org/10.1038/leu.2017.138

Supplementary Information accompanies this paper on the Leukemia website (http://www.nature.com/leu)