|Ahead of print publication
Multiple myeloma: Unveiling the survival data with different lines of treatments
Helan Kurian1, Suja Abraham2, Arpith Antony1, Jeeva Ann Jiju1, Timy Thomas1
1 Department of Pharmacy Practice, Nirmala College of Pharmacy, Muvattupuzha, Kerala, India
2 Department of Pharmacy Practice, MGM Silver Jubilee College of Polytechnic and Pharmaceutical Sciences, Ernakulam, Kerala, India
|Date of Submission||23-Aug-2021|
|Date of Acceptance||22-Sep-2021|
|Date of Web Publication||14-Jan-2022|
Kanjirapallil House, RECCAA Valley, Kakkanad, Ernakulam - 682 030, Kerala
Source of Support: None, Conflict of Interest: None
Purpose: The incidence of multiple myeloma (MM) is rising and there are fewer Indian studies; a comprehensive research of MM patients' survival data in a real-world population is needed. This study aims to analyze the survival status of MM patients with different treatment regimens along with its correlation to other parameters such as treatment-free interval (TFI) and time-to-next treatment (TTNT).
Materials and Methods: This was a retrospective observational study, done in the department of oncology, at a tertiary care hospital in Kerala, from August 2019 to July 2020, to analyze the survival data in patients diagnosed with MM from 2015 to 2019. The effectiveness endpoints include time-to-event analyses such as TTNT and TFI. After receiving various therapy regimens, the survival rates were analyzed; the Kaplan–Meier estimator was used to determine the cumulative survival. The correlations between overall survival (OS) and duration of therapy, TFI, TTNT, and other parameters were calculated using the Karl Pearson's correlation coefficient.
Results: 72 (82.80%) of the patients survived to the end of the study (OS), with a mean survival time of 4.02 ± 2.81 years. 52 (59.80%) patients had progression-free survival (PFS), while the remaining 35 (40.22%) had no significant disease prognosis. Both OS and PFS showed a significant positive correlation (P > 0.05) with TTNT and TFI.
Conclusions: Completely adherent chemotherapy for 1 year can promise a survival time not <2 years. Longer TFI resulted in better OS and PFS. Extending the duration of the second LOT correlated with the better OS and PFS.
Keywords: Lines of treatment, multiple myeloma, overall survival, progression-free survival, time-to-next treatment, treatment-free interval
| > Introduction|| |
Multiple myeloma (MM) is a cancer of the plasma cells' B cells that causes monoclonal gammopathy, polyclonal immunoglobulin suppression, skeletal degradation, renal dysfunction, anemia, and hypercalcemia,, with more than 150,000 new cases diagnosed each year. The incidence of MM is increasing worldwide, particularly in the United States. Between 1990 and 2016, the incidence increased by 126%, while death increased by 94%. According to the Surveillance, Epidemiology, and End Results data, there are approximately 71,000 MM cases in the United States, with a 5-year prevalence of 4.3/100,000 people worldwide. According to the Indian Council of Medical Research, yearly over 50,000 new MM cases are identified in India, with the incidence ranging from 1.2 to 1.8/100,000 people. The Regional Cancer Center, Trivandrum, Kerala, revealed over 258 MM cases (2% MM in India).
Various therapy regimens with different mechanisms of action, primarily an alkylating agent and a corticosteroid, are used for treatment. Induction therapy, which includes bortezomib/lenalidomide/dexamethasone, is the initial step in treating newly diagnosed MM patients. The choice of chemoregimens is subject-specific, based on the baseline data.
Introduction of novel targeted therapies with tolerable toxicity profile, as well as the use of high-dose chemotherapy and autologous stem cell transplant (ASCT) in the early 1990s, increased the median survival time; 47% of subjects survived longer than 5 years. MM remains a deadly disease, although the survival times have increased. The relapse rate is also higher and patients require numerous LOTs.,
The survival period of myeloma patients has improved drastically over the last two decades; before 2000, the median survival was 3–3.5 years and now it is 5.5–6 years. The survival rate depends on several factors, including the type and duration of therapy (DOT), the patients' initial reaction, adherence to the therapy, drug availability, and the likelihood of receiving ASCT. According to the International Staging System, the majority of the subjects were in advanced stages (III; 70%); presence of weight loss (P = 0.01), renal failure (P = 0.047), and anemia at diagnosis (P = 0.004) had a significant impact on survival. A complete response is associated with long-term progression-free survival (PFS) and overall survival (OS); with a median follow-up of 29 months, the 3-year PFS and OS rates were 29% and 65%, respectively.
Novel treatment options have become a part of clinical practice; however, the outcomes must be rigorously assessed when using them. Real-world data are crucial in evaluating ongoing practice, such as the use of novel drugs in different LOTs, creating criteria for treatment alterations. Recently, there has been a scarcity of acceptable real-world evidence describing current trends and outcomes in the survival data of MM people in India which physicians might use in making treatment decisions.
This study aims to analyze the real-world effects of survival rates in MM patients treated with various chemoregimens.
| > Materials And Methods|| |
This study was a retrospective observational study (August 2019–July 2020) conducted in the department of oncology, of a tertiary care hospital in Kerala, to provide real-world evidence of outcomes in subjects diagnosed with and managed for MM from 2015 to 2019 with at least 6 months of registered follow-up. The Institutional Human Ethics Committee gave consent for the research protocol before the start of the study.
For the current study, 150 MM participants were identified; 87 of them met the inclusion and exclusion criteria. The study included MM patients who had any of the following chemotherapies: cyclophosphamide/bortezomib/dexamethasone (CyBorD), thalidomide/dexamethasone (TD), bortezomib/lenalidomide/dexamethasone (VRD), lenalidomide/dexamethasone (RD), bortezomib/dexamethasone (VD), and a follow-up of at least 6 months. People with different types of cancer and myeloma, pregnant women, subjects on extra therapeutic regimens, and subjects in palliative care were all excluded.
From the individuals' medical and treatment reports, baseline demographics and clinical parameters (age, gender, duration of myeloma, and Durie–Salmon Staging) were documented.
From 2015 to 2019, data from MM subjects who met the inclusion criteria and received any of the chemoregimens were evaluated. LOTs corresponding with each regimen on different periods were analyzed. A new LOT was defined as an alteration in the intended course of therapy (to add other treatment agents, single or in combination) as a result of disease progression, relapse, or toxicity. LOTs were defined as one or more cycles of the proposed treatment (induction accompanied by ASCT would figure out as one LOT). The first LOT is the first systemic cancer therapy given after diagnosis. The second LOT can be a change in chemoregimen, the addition of a new drug after the first LOT, or the repetition of therapy after the treatment of >3 months. After the second LOT, the third LOT is a changeover to or addition of a new medication.
Regardless of whether the participants are eligible for ASCT or not, there are a variety of first LOT options available. The selection of additional LOTs and the sequencing of therapies should be done carefully. The second and third LOT may include novel medicines in various combinations and the therapy selection depends on subject-specific variables such as previous treatment class, efficacy and tolerance, number of prior LOTs, residual therapeutic choices, and time since the last therapy.
The time from the beginning of the first medicine to the discontinuation of the final drug in the prescribed regimens was recorded as the DOT. The DOT of all the LOTs was calculated from the first LOT's start date to the last LOT's end date, including mortality. For infused/injected medicines, the duration was 30 days from the date of administration, and for oral drugs, it was the prescribed date plus (days provided-1).
The MM individuals received the following chemotreatments:
- For subjects receiving RD, four 28-day cycles of oral lenalidomide 10–25 mg on days 1–21 and low-dose dexamethasone 40 mg weekly
- CyBorD therapy included four 28-day cycles of bortezomib 1.3 mg/m2 IV on days 1, 8, 15, and 22; oral cyclophosphamide 300 mg/m2 on days 1, 8, 15, and 22; and low-dose dexamethasone 40 mg weekly
- Patients on VRD had four 28-day cycles of bortezomib 1.3 mg/m2 IV on days 1, 8, 15, and 22; lenalidomide 10–25 mg on days 1–21; and low-dose dexamethasone 40 mg weekly
- Treatment consisted of four 28-day cycles of thalidomide 200 mg/day on days 1–28 and low-dose dexamethasone 40 mg weekly for TD patients
- Individuals on VD had four 28-day cycles of bortezomib 1.3 mg/m2 IV on days 1–21 and low-dose dexamethasone 40 mg weekly.
Time-to-event analyses, such as the time-to-next treatment (TTNT) and the treatment-free interval (TFI), are among the supplementary effectiveness endpoints. The interim between the start of the second LOT and the start of the third LOT, or death, whichever occurred first, is referred to as TTNT (a surrogate measure for PFS in real-world data interpretations). TFI is the time between the end of the first LOT and the start of the second LOT.,,
The clinical standards of PFS and OS were derived and utilized as surrogate endpoints to evaluate the survival data. The period from the start of the first LOT to disease progression or death without progression was defined as PFS, and the time from the start of the first LOT to the last follow-up, 30 days before the study end date, or death was defined as OS.,
Microsoft Excel 2010 and SPSS Version 16 were used to analyze data obtained from the subject records. Descriptive statistics were used to assess the study variables. Categorical variables were denoted by numbers and percentages, whereas quantitative variables were denoted by mean and standard deviation. The Karl Pearson's correlation coefficient was used to calculate the correlations between survival and DOT, TFI, TTNT, and other factors. The Kaplan–Meier method was used to express the cumulative survival curve. With a significance level of 0.05, all the P values obtained were two-tailed.
| > Results|| |
The study included 87 MM individuals, with a slight predominance of men with a mean age of 64.80 ± years. [Table 1] shows the demographics of the patients. Twelve (13.80%) of the 87 patients received the first LOT, 50 (57.50%) received the second LOT, and 25 (28.70%) received the third LOT. Twenty-eight (32.20%) patients received RD (9 ± 5.96 cycles), 22 (25.30%) received VD (7.5 ± 4.5 cycles), 17 (19.50%) received CyBorD (6.58 ± 2.15 cycles), 14 (16.10%) received TD (11.35 ± 4.78 cycles), and 6 (6.70%) received VRD (7.66 ± 3.14 cycles) as the first LOT.
|Table 1: Demographic details of multiple myeloma patients receiving different regimens|
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The TFI and TTNT were utilized for the survival time analysis. [Table 2] explains the mean TFI and TTNT of the patients who received different therapeutic regimens. The reasons for treatment modifications are listed in [Table 3]. OS and TFI were shown to have a positive Pearson's correlation of 0.222* (P = 0.039), whereas, between TFI and PFS, there was a slight positive association of 0.211* (P = 0.05). Between TTNT and OS, there was a positive correlation of 0.307** (P = 0.004), and between TTNT and PFS, there was a positive correlation of 0.310** (P = 0.003), which is depicted in [Table 4].
|Table 2: First line of treatment, treatment-free interval, and time-to-next treatment|
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|Table 3: Reasons for treatment modification from the first line of treatment|
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The patients' survival rates were analyzed in terms of OS and PFS. Seventy-two (82.80%) of the 87 patients were alive (OS) with a mean of 4.02 ± 2.81 years, while the rest of the 15 (17.24%) were deceased. Thirty-five patients (40.22%) showed disease progression and 52 (59.8%) had PFS with a mean of 2.60 ± 3.08 years. The ratio of DOT to OS was obtained as 1:2. The DOT and OS were found to have a substantial positive Pearson's correlation of 0.810** (P < 0.001).
The cumulative survival from the data was calculated using the Kaplan–Meier estimator. The curve [Figure 1] indicated that 16% of MM patients died within the first 2-year after initiating treatment, and 2% died in the years after that. The death rate was highest in the initial years of treatment, and it mostly affected patients who were diagnosed at the 3rd stage of MM. Thus, among the 87 MM patients in this study, the curve indicated a cumulative survival rate of 82% and a mortality rate of 18%.
|Figure 1: Kaplan–Meier curve for the survival analysis. Cum survival: Cumulative survival|
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| > Discussion|| |
The proper use of different chemoregimens in MM treatment has resulted in significantly better survival rates and improved patient outcomes. The survival status of 87 MM patients who were treated with five different therapeutic regimens was evaluated in this study.
There was a slight predominance of men, and majority of the subjects were >60 years. The men: women ratio in our analysis was similar to that in a study (2017) by the United Kingdom Cancer Research Statistics (57% men and 43% women).
Twelve of the 87 patients received the first LOT, 50 received the second LOT, and 25 received the third LOT. Treatment alterations or switching of therapy were made when the patient had poor prognosis, major adverse effects of the therapy, drug intolerance, unwilling to undergo certain high-cost chemoregimens, or nonadherent to the therapy.
Khan et al. in their study pointed out that the clinical development and successful application of novel agents have markedly led to improved PFS and OS in newly diagnosed MM as well as overall improvements in patient outcomes. The TFI had a positive correlation with the patients' OS and PFS in this study. This finding agrees with a cross-sectional assessment of 370 myeloma patients in the United Kingdom, which found that being in the first TFI and having a longer TFI were both related to a better health related quality of life. Linearity between TTNT and MM patients' OS and PFS was also found in the present study. Hari et al. concluded that each additional month of second LOT was associated with a reduced risk of death at 1 year. We observed that the highest percentage of mortality occurred in initial years, mainly subjects in stage 3 of MM.
This study must be seen in light of the limitations that all retrospective studies have. The doctor chose the treatment as well as the treatment doses, and durations varied across individuals. Furthermore, information about the disease's diagnosis and the rationale for choosing the first LOT and switching over between regimens was not always readily available from patient records.
| > Conclusions|| |
This study outlines the survival rate of MM patients who received various antimyeloma therapies. Seventy-two patients had OS and 52 had PFS with a mean survival time of 4 years. Completely adherent chemotherapy for 1 year can promise a survival time not <2 years. The DOT had a strong positive correlation with OS and a positive correlation existed between TFI and TTNT with both OS and PFS, respectively. In conclusion, despite the retrospective nature of our study, the limitation of a small geographical area, and the absence of clinical data such as supportive care, our study confirms that the survival of the MM patients and the quality of life cannot be attributed to a single therapeutic regimen alone. Future population-based studies are essential to confirm these observations.
We express our gratitude to the Kerala State Council for Science Technology and Environment (KSCSTE) who supported us for our needs.
Financial support and sponsorship
The Kerala State Council for Science Technology and Environment (KSCSTE) has technically supported us for our needs.
Conflicts of interest
There are no conflicts of interest.
| > References|| |
Agarwal A, Jacob L, Suresh Babu M, Lakshmaiah K, Babu K, Lokanatha D, et al
. Multiple myeloma: Experience of an institute in a limited-resource setting. Indian J Cancer 2017;54:340.
Khan ML, Reeder CB, Kumar SK, Lacy MQ, Reece DE, Dispenzieri A, et al
. A comparison of lenalidomide/dexamethasone versus cyclophosphamide/lenalidomide/dexamethasone versus cyclophosphamide/bortezomib/dexamethasone in newly diagnosed multiple myeloma. Br J Haematol 2012;156:326-33.
International Myeloma Foundation. International Myeloma Foundation; 2021. Available from: https://www.myeloma.org/
. [Last accessed on 2021 May 24].
Swerdlow SH, Campo E, Harris NL. WHO Classification of Tumours of Haematopoietic and Lymphoid Tissues. 4th
ed. Lyon, France: IARC; 2008. p. 200-13.
Regional Cancer Centre, RCC, Thiruvananthapuram, Kerala, India. Available from: https://www.rcctvm.gov.in/
. [Last accessed on 2021 May 24].
Garderet L, D'Souza A, Jacobs P, van Biezen A, Schönland S, Kroeger N, et al
. Response assessment in myeloma: Practical manual on consistent reporting in an era of dramatic therapeutic advances. Biol Blood Marrow Transplant 2017;23:1193-202.
Braunlin M, Belani R, Buchanan J, Wheeling T, Kim C. Trends in the multiple myeloma treatment landscape and survival: A U.S. analysis using 2011-2019 oncology clinic electronic health record data. Leuk Lymphoma 2021;62:377-86.
Mohty M, Terpos E, Mateos M, Cavo M, Lejniece S, Beksac M, et al
. Multiple myeloma treatment in real-world clinical practice: Results of a prospective, multinational, noninterventional study. Clin Lymphoma Myeloma Leuk 2018;18:e401-19.
Kumar L, Nair S, Vadlamani SP, Chaudhary P. Multiple myeloma: An update. J Curr Oncol 2020;3:72-80. [Full text]
Yanamandra U, Sharma R, Shankar S, Yadav S, Kapoor R, Pramanik S, et al
. Survival outcomes of newly diagnosed multiple myeloma at a tertiary care center in north India (IMAGe: 001A Study). JCO Glob Oncol 2021;7:704-15.
Gay F, Larocca A, Wijermans P, Cavallo F, Rossi D, Schaafsma R, et al
. Complete response correlates with long-term progression-free and overall survival in elderly myeloma treated with novel agents: analysis of 1175 patients. Blood 2011;117:3025-31.
Remes K, Anttila P, Silvennoinen R, Putkonen M, Ollikainen H, Terävä V, et al
. Real-world treatment outcomes in multiple myeloma: Multicenter registry results from Finland 2009-2013. PLoS One 2018;13:e0208507.
Hari P, Romanus D, Palumbo A, Luptakova K, Rifkin RM, Tran LM, et al
. Prolonged duration of therapy is associated with improved survival in patients treated for relapsed/refractory multiple myeloma in routine clinical care in the United States. Clin Lymphoma Myeloma Leuk 2018;18:152-60.
Chari A, Richardson PG, Romanus D, Dimopoulos MA, Sonneveld P, Terpos E, et al
. Real-world outcomes and factors impacting treatment choice in relapsed and/or refractory multiple myeloma (RRMM): A comparison of VRd, KRd, and IRd. Expert Rev Hematol 2020;13:421-33.
Usmani S, Ahmadi T, Ng Y, Lam A, Desai A, Potluri R, et al
. Analysis of real-world data on overall survival in multiple myeloma patients with≥3 prior lines of therapy including a proteasome inhibitor (PI) and an immunomodulatory drug (IMiD), or double refractory to a PI and an IMiD. Oncologist 2016;21:1355-61.
Acaster S, Gaugris S, Velikova G, Yong K. Lloyd A. Impact of the treatment-free interval on health-related quality of life in patients with multiple myeloma: a UK cross-sectional survey. Supportive Care in Cancer 2012;21:599-607.
[Table 1], [Table 2], [Table 3], [Table 4]