1. Introduction
Multiple myeloma (MM) is a plasma cell neoplasm, characterized by various and potentially severe complications, and is the second most common hematological cancer, accounting for about 13% of all cases. In 2020, 176,404 new MM cases were reported in Europe, with a 5-year prevalence of 138,083 and 32,495 deaths [ 1 ]. In Portugal, MM incidence is around 7.8/100,000 [ 2 ].
The median age at diagnosis is 70 years [ 3 ], slightly above the median age in Portuguese data (69 years) [ 2 ]. As life expectancy increases, so does the incidence of MM [ 4 ]. This presents a significant challenge in countries with marked inverted demographic pyramid such as Portugal, a trend that is anticipated to become more striking as the birthrate is well below the necessary population replacement rates.
The MM patient journey often contemplates alternating cycles of treatment, periods of remission, and relapse events. Due to its biological heterogeneity, relapses manifest throughout the natural history of the disease, each exhibiting specific characteristics and distinct implications [ 5 ]. Relapsed and/or refractory MM (rrMM) translates into significant physical and psychological burden on patients and families, especially in older and frailer populations. Data from Portugal show that burden to caregivers increases with successive treatment lines [ 6 ]. Physicians face a substantial burden navigating the complexity of addressing relapses. This challenge entails considering not only the characteristics of the relapse and the patient but also social and familiar backgrounds, despite the availability of the numerous current and innovative therapies [ 5 , 7 , 8 , 9 ].
The emergence of a wide array of novel MM treatments [ 10 ], including immunomodulators (IMiDS), monoclonal antibodies (mAbs), and proteasome inhibitors (PIs), broadened the therapeutic arsenal beyond the conventional options—chemotherapy, stem cell transplantation, and supportive care—translating into better survival outcomes and improved quality of life [ 11 , 12 ]. More recently, bispecific antibodies [ 13 , 14 ], CAR T cells [ 15 , 16 ] or even antibody–drug conjugates (ADCs), such as belantamab mafodotin [ 17 , 18 , 19 ] have proven the added potential benefits of novel therapeutics in improving the clinical outcomes in MM patients. Regardless of the outstanding therapeutic advances, the heterogeneity of MM implies high variability in both treatment response and survival outcomes [ 20 ]. Therefore, this patient population requires more effective, well-tolerated, and personalized therapeutic strategies to achieve high-quality responses and overcome this heterogeneous and challenging hematologic malignancy [ 21 ].
In Portugal, access to care in oncology centers is primarily organized within the National Health Service (SNS), which ensures universal coverage. However, specific criteria and structured systems help determine which patients are eligible for care in these centers. Patients typically access cancer centers through referrals from primary care physicians or specialists. The referral is based on confirmed diagnoses or suspicion of cancer. The National Oncology Referral Network outlines guidelines for referring patients to specialized cancer centers, focusing on the complexity and type of cancer, ensuring appropriate treatment in centers of excellence. On the other hand, access may depend on clinical factors, such as the stage of the disease, comorbidities, and the potential to benefit from specific innovative therapies or clinical trials. While the SNS strives for equitable access, the geographical location of the patient relative to a cancer center may influence access, although transport assistance may be available if required. Information in the country regarding the rrMM population and its clinical management in the real-world setting is scarce. The objective of the CharisMMa Portugal study was to characterize rrMM patients regarding socio-demographic and clinical features, as well as to describe treatment patterns.
2. Materials and Methods
2.1. Study Design and Population
This was an observational, cross-sectional, multicenter study using a consecutive sample of rrMM patients routinely managed at seven reference public hospitals in Portugal. For reasons of transparency, the CharisMMa Portugal study was registered on the ClinicalTrials.gov platform (ID– NCT04135963 ) on 21 October 2019.
The study population consisted of patients with an rrMM diagnosis established within the 5 years before study inclusion and who had received at least one previous line of treatment. This timeframe was selected to reduce variability due to evolving treatment protocols, ensuring a more up-to-date characterization. Additionally, patients must have started a new treatment line due to a relapsed/refractory disease in the 6 months prior to study inclusion. Data were collected from medical charts and through patient interviews during routine clinical appointments between July 2020 and September 2022. Symptomatic relapse was considered a recurrence of the signs and symptoms of MM, such as anemia, renal failure, and/or bone pain, as stated in the International Myeloma Working Group (IMWG) guidelines [ 22 ]. In this study, symptomatic recurrence in rrMM was defined as the reappearance or progression of disease-related clinical manifestations, which can include anemia, bone lesions, renal dysfunction, hypercalcemia, or other organ damage, as outlined by the IMWG criteria, occurring after a period of response or stability following prior therapy.
All patients provided written informed consent. Each local independent ethics committee approved the study protocol before the start of data collection.
2.2. Study Data
Patient socio-demographic information included sex, body mass index (BMI), area of residence, educational level, employment and cohabitation status, financial assistance need, degree of dependence [ 23 ], physical activity level, smoking status, and alcohol use, which were all recorded during the study appointment.
Clinical data for patients at the time of MM diagnosis included age, staging according to the International Staging System (ISS) and Revised ISS (R-ISS), and ECOG performance status. Regarding the latest rrMM episode, SLiM-CRAB criteria, cytogenetic analysis and risk-strata based on cytogenetic profile (mSMART v2 and mSMART v3), clinical presentation, comorbidities, and paraprotein characteristics were collected.
Furthermore, treatments previously prescribed and those ongoing during study appointments were recorded.
2.3. Statistical Analysis
Sample size was calculated to allow for a robust characterization of rrMM patients in the Portuguese setting. From the available data for Portugal, assuming a confidence level of 95% and a margin of error of 7.5%, the calculated sample size was 151 rrMM patients. However, due to recruitment constraints, 74 patients were screened and only 62 patients were analyzed.
All eligible patients were included in the full-analysis set (FAS). Data were summarized using descriptive statistics. Statistical analyses were carried out with SAS ® software (version 9.4; SAS Institute Inc., Cary, NC, USA) [ 24 ].
3. Results
3.1. Patient Disposition and Sociodemographic Characterization
Of the 74 patients who were screened, 62 patients (83.8%) were included in the FAS. The reasons for screening failure are detailed in Figure 1 .
Most patients were male (54.8%) ( Table 1 ). The mean BMI was 25.48 kg/m2 (±3.86) with overweight/obesity found in nearly 55% of patients. Most patients (67.7%) resided in urban areas, had a primary education level (65.5%), and were retired (62.3%). Almost all patients (90.3%) lived with relatives, 49.2% were independent, and 18.3% were in need of financial assistance. Regarding lifestyle factors, over half of the patients (56.7%) practiced low to moderate physical activity, 11.3% were current smokers, and 8.1% reported alcohol consumption.
3.2. Clinical Characterization
The mean age at MM diagnosis was 65.76 (±9.24) years old, and the mean time from the last relapse to the study visit date was 2.57 months (±1.76). Regarding MM staging, 69.6% of patients were classified as R-ISS Stage II at diagnosis and 37.1% were categorized as stage II using the ISS staging system ( Table 2 ). At the time of MM diagnosis, 5.1% of patients had an ECOG-PS 3 performance status, with most patients (74.6%) reporting ECOG-PS 0–1. At diagnosis, 80% of patients presented with a Heavy Chain type. Among these, 56.7% had an IgG Heavy Chain, while 21.7% had an IgA Heavy Chain.
The most common SLiM-CRAB signs at last relapse were bone lesions (59.0% of patients), followed by anemia (45.9%).
Among the 24 patients who underwent cytogenetic analysis at the last relapse, 11 (45.8%) reported at least one cytogenetic abnormality. Of these eleven patients, eight (72.7%) were classified as high-risk.
Bone fractures were identified in 22.6% of the patients at last relapse. Medullary/extramedullary plasmacytomas were present in 64.9% of patients, with 52.6% reporting two or more plasmacytomas.
At last disease relapse, the average LDH level was 233 (±169) IU/L, with 26.6% of patients presenting with elevated LDH levels (>250 IU/L). The mean serum paraprotein level was 53.19 (±105.42) g/L. The mean serum kappa free light chain (FLC) level was 42.08 (±123.02) g/L. The mean serum lambda FLC level was 16.08 (±31.81) g/L.
In the last rrMM episode, 62.9% had at least one concomitant disease, with the most prevalent being diabetes (22.6%, n = 14), cardiovascular disease (17.7%), and peripheral neuropathy (16.1%). Around 42% (41.9%) had another secondary disorder.
3.3. Treatment Patterns
3.3.1. Before Last Relapse
The median treatment duration before the last relapse was 165.50 days (IQR: 112.5–279.0). In total, 19 patients (30.6%) received second-line treatment before their last relapse preceding the study visit, while four patients (6.5%) received third-line or above treatment. PIs were the agents most used in first-line treatment (46.8% of patients), while a combination of PI and IMiDs was used in 38.7% of patients. mAbs became more common during second-line treatment, accounting for 31.6% of patients. In third-line and above treatments, PIs re-emerged as the most frequently used option (50.0% of patients), either retreatment with the same PI or a different PI ( Figure 2 a). The rate of transplants was 24.2% in first-line treatment (15 out of 62 patients), decreasing to 15.8% in second-line treatment (3 out of 19 patients).
Triplet regimens were predominant across all treatment lines, accounting for 69.4%, 57.9% and 75% of cases in first-, second- and third/subsequent-line treatments, respectively ( Figure 2 b).
Oral plus subcutaneous were the main routes of administration during first-line treatment (78.9% of patients). In third-line and subsequent treatments, combined oral and intravenous administration became the predominant approach (50%). Additionally, the oral route was used exclusively for 12.3% during first-line treatment and for 26.3% of patients during second-line treatment ( Figure 3 ).
Figure 4 provides an overall summary diagram of the distributions observed throughout the treatment lines for therapeutic classes, number of therapeutic groups, and routes of administration before the last relapse.
The tables (left panels) represent percentages of patients and are color-coded such that green indicates an increase from the previous line, red indicates a decrease, and white indicates no change. The charts (right panels) are 100% stacked area graphs representing the relative proportion of each category in lines 1, 2, and 3+.
3.3.2. At Study Appointment–After Last Relapse
At the study appointment, all patients, except for one, were undergoing treatment (n = 61). For 91.8% of patients, the ongoing treatment regimen coincided with the one used to treat the last relapse. The median duration of treatment ongoing at study appointment was 43 days (IQR: 21–106), while median disease duration was 1.59 years (IQR: 0.96–2.82). In addition, most patients (70.5%) were receiving second-line treatment while 26.2% were undergoing third-line treatment. mAbs emerged as the leading agent during second- (46.5%) and third-line (43.8%) treatments, followed by a PIs plus IMiDs combination (18.6% and 18.8%, respectively), as shown in Figure 5 .
Triplet regimens were the most common in all treatment lines (65.1%, 68.8%, and 50% in first, second, and third and subsequent treatment lines, respectively), followed by duplet regimens (20.9%, 18.8%, and 50%, respectively) ( Figure 6 ).
Oral alone and oral plus subcutaneous routes of administration were the most common in second-line and fourth-line and subsequent treatments (45.2% and 100%, respectively), while oral plus intravenous (36.4%) was the most common route in third-line treatments ( Figure 7 ).
Figure 8 provides an overall summary diagram of the distributions observed throughout the treatment lines for therapeutic classes, number of therapeutic groups, and routes of administration at the last relapse (ongoing at study appointment).
The tables (left panels) represent percentages of patients and are color-coded, with green indicating an increase from the previous line, red indicating a decrease, and white indicating no change. The charts (right panels) are 100% stacked area graphs representing the relative proportion of each category in treatment lines 2, 3, and 4+.
4. Discussion
This analysis of rrMM patients in Portugal has provided valuable information regarding the clinical presentation of the disease, the sociodemographic characteristics of patients and treatment patterns over time.
The patient population was heterogeneous, reflecting the diverse sociodemographic profile of individuals living with rrMM. There was a predominance of the elderly, male patients, and a retired population, which was in alignment with previous research [ 23 ]. Regardless, this sample was slightly younger, with a better educational profile and with a higher rate of active employment [ 23 ].
Patient dependence negatively affects daily activities of MM patients and caregivers and access to healthcare, potentially contributing to a lack of follow-up that could ultimately contribute to the development of clinical relapses. It is of note that despite being an old and at higher risk of clinical complications population, and that around 90% of patients lived with their families, half of the patients reported being autonomous. This is aligned with previous research in Portugal that suggested a low burden of rrMM for caregivers [ 6 ]. Not surprisingly, most patients had comorbidities, such as diabetes, cardiovascular disease, and peripheral neuropathy. This highlights the multifaceted nature of the health challenges faced by these patients, adding to the complexity of managing these often poly-medicated populations. These insights underscore the importance of a broad and personalized approach to treatment that should consider not only the specific characteristics of the diseases but also individual circumstances and social backgrounds [ 8 ]. Lastly, the importance of financial constraints should not be underestimated. Although only roughly 12% of our sample needed financial assistance, research has shown that reducing costs can improve treatment compliance [ 25 ], particularly as the economic burden increases in later lines of treatment [ 26 ]. It should also be considered that the sample collected in this study was identified in the public healthcare setting, which provides unrestricted and mostly free medical care to MM patients, which may have reduced the impact of financial constraints.
Most patients enrolled in the study exhibited ISS stage II or ISS stage III at the time of diagnosis, indicating a population with an unfavorable prognosis. The cytogenetic risk assessment is an essential surrogate for understating patient prognosis and for optimizing the clinical management of the rrMM patients [ 10 ]. We found a high proportion of patients with high-risk cytogenetics. This high proportion was to be expected given that the SMART V3.0 risk classification considers d (17p), t (4;14), t (14;16), t (14;20), g (1q), and p53 mutations to all be high-risk, and a combination of these proportions of cytogenetic abnormalities in MM patients have been shown to have very high g (1q)/Amp1q counts of between 30 and 40% alone, which is expected to be even higher in rrMM patients [ 27 , 28 , 29 ]. However, it is noteworthy that cytogenetic assay data were only available for approximately one-third of the sample, a limitation that can be justified by the retrospective nature of the study [ 30 ].
The study’s description of treatment patterns revealed the changing landscape of therapeutic strategies over the last few years, as well as demonstrating the diverse array of therapeutic options in this clinical setting in Portugal, which is corroborated by previous research [ 2 ]. Commonly, therapeutic protocols include the adoption of treatment combinations, especially triplet regimens. This study showed that triplet regimens were predominant across all treatment lines. Tailoring treatments to patient profiles is essential to improve outcomes. Given the expanding arsenal of therapeutics [ 5 , 11 , 12 , 21 , 31 , 32 ], treatment guidelines should reflect patient-related factors as well as the biological heterogeneity of MM. Notably, this study showed that monoclonal antibodies were increasingly adopted as the number of treatment lines progressed, reflecting the integration of novel agents into the MM treatment paradigm. Conversely, PIs and IMIDs are widely adopted throughout the disease course, with a higher rate of adoption in first-line treatment. The pattern of treatment regimens used on the onset of disease relapse reveals the complexity of the therapeutic decisions in this context, which seem to be influenced by the combinations used and number of previous lines of treatment.
Despite the substantial advances in the management of rrMM, including the integration of immunotherapy, there remains a critical need for the development of novel effective and better tolerated approaches with sustained high-quality responses that delay the resurgence of relapses. This necessity is especially pronounced among high-risk patients, who face a very poor prognosis [ 21 ].
Furthermore, the analysis of treatment administration routes also revealed a notable trend. Oral alone and the combined oral + subcutaneous administrations were most common in the second, fourth, and subsequent lines of treatment, while the more classical combination of oral + intravenous administration was more common in third-line treatment. These findings highlight the adaptability towards patient-centric approaches, enabling a tailored response to the specific needs and preferences of patients, many of them residing far from the hospital, some with mobility restrictions and some depending on relatives to go to the hospital, as previously highlighted [ 33 ].
The results also support previous research, showing a trend in the increase in advanced treatment lines [ 34 ].
4.1. Study Limitations
The pandemic restrictions negatively impacted recruitment leading to a significant reduction in sample size and resulting in the potential introduction of selection bias. This factor makes the generalization of results to the overall MM population challenging. However, the consecutive sampling approach was devised to control for such bias, as all the patients that fulfilled the study criteria were invited to participate in the study at a routine medical appointment. Another notable limitation was the presence of missing data, especially regarding cytogenetic analysis, as already discussed. It is important to highlight that these data reflect the standard of care (SoC) at study inclusion for patients diagnosed within the previous 5 years and, therefore, may not accurately represent recent changes in SoC, namely in the context of first-line treatments.
4.2. Final Remarks
Given the increasing importance of patient-centric approaches in the clinical management of blood malignancies [ 35 ], the patient-reported outcomes (quality of life) collected in the CharisMMa study must be explored in future publications and research, along with a patient’s preferences and needs.
In conclusion, the findings from this study provide an overview of the MM landscape in Portugal, encompassing demographic characteristics, treatment patterns, and administration routes. Around 80% of the patients are retired or temporarily/permanently disabled and most have a low education level, which is expected in an elderly population in Portugal. Although the majority of patients enrolled in the study present with an unfavorable prognosis and comorbidities, most of them are independent or present grade I dependence, which is in line with previous research in Portugal that suggested a low burden of rrMM patients for caregivers [ 6 ]. This is an essential topic for the National Health System, when planning healthcare in a geriatric population with an oncological disease. The insights of this study may contribute to the expanding knowledge in the field of rrMM and are expected to provide enriching information about the clinical burden of this disease and serve as a valuable resource for ongoing efforts at improving the quality of care to MM patients.
As for clinical implications, as rrMM patients progress through multiple lines of therapy, the increased frailty, comorbidities, and treatment-related toxicities make less invasive and more convenient administration routes preferable. Oral therapies reduce the need for frequent hospital visits, which is beneficial for patients with mobility issues, economic limitations, or those living far from treatment centers. Also, newer-generation oral agents are becoming more widely available, expanding the treatment arsenal beyond intravenous or subcutaneous regimens. Lastly, patient preference and quality-of-life should be considered, as oral therapies offer greater flexibility and may improve adherence compared to other more invasive routes of administration, as well as healthcare resource utilization, in which outpatient treatment models and resource optimization may contribute to increasing the options for oral agents in later treatment lines.
Future research should focus on key areas to address the evolving landscape of rrMM treatment. Given that data collection occurred in Portugal between July 2020 and September 2022, new studies should explore how newer therapies—bispecific antibodies, CAR T cell therapies, and next-generation targeted agents—impact treatment patterns and patient outcomes in real-world settings. Additionally, cost-effectiveness analyses comparing different therapeutic regimens should contribute to identifying the financial burden of treatment and offer recommendations on improving the Portuguese NHS sustainability. Further exploration on how route of administration influences patient quality of life, treatment adherence, and healthcare resource utilization would also be relevant, particularly regarding the role of oral versus more invasive therapeutics. Moreover, assessing the long-term impact of treatment sequencing, including how earlier exposure to novel agents affects subsequent therapeutic options and survival outcomes, would also be pertinent. Finally, patient-reported outcomes should be included and considered to better understand treatment tolerability, symptom burden, and the psychosocial aspects of disease management, especially in rrMM patients.
Acknowledgments
The authors would like to thank the patients involved in the current study for providing consent and dedicating time to this study, as well as the teams involved in conducting the study and data collection. Diogo Morais from Clinical Trial and Consulting Services (CTI) provided medical writing assistance and editorial support with this manuscript, funded by Takeda.
Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content.
Supplementary Materials
The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/hematolrep18030034/s1 . Table S1: Local IEC/IRB for each participating site.
Author Contributions
R.B.: Writing—original draft preparation, conceptualization, methodology, validation, data curation, investigation, and writing—reviewing and editing; J.G.F.: writing—original draft preparation, conceptualization, methodology, validation, data curation, investigation, and writing—reviewing and editing; C.G. (Cristina Gonçalves): conceptualization, methodology, validation, data curation, investigation, and writing—reviewing and editing; H.M. (Helena Martins): conceptualization, methodology, validation, data curation, investigation, and writing—reviewing and editing; H.M. (Herlander Marques): conceptualization, methodology, validation, data curation, investigation, and writing—reviewing and editing; H.C.: conceptualization, methodology, validation, data curation, investigation, and writing—reviewing and editing; P.S.: conceptualization, methodology, validation, data curation, investigation, and writing—reviewing and editing; A.R.: conceptualization, methodology, validation, data curation, investigation, and writing—reviewing and editing; M.T.: conceptualization, methodology, validation, data curation, investigation, and writing—reviewing and editing; P.P.: conceptualization, methodology, validation, data curation, investigation, and writing—reviewing and editing; A.R.F.: conceptualization, methodology, validation, data curation, investigation, and writing—reviewing and editing; J.T.: conceptualization, methodology, validation, data curation, investigation, and writing—reviewing and editing; C.G. (Catarina Geraldes): conceptualization, methodology, validation, data curation, investigation, and writing—reviewing and editing, supervision and writing—original draft preparation. All the authors contributed equally to the conceptualization, methodology, validation, data curation, investigation, and writing—reviewing and editing. All the authors were involved in writing the manuscript and reviewing drafts, as well as approval of the final manuscript version. Author order was decided based on active contribution to the study. All authors have read and agreed to the published version of the manuscript.
Institutional Review Board Statement
The study was conducted in accordance with the Declaration of Helsinki and approved by each site’s Institutional Review Board (or Ethics Committee) as follows: Comissão de Ética para a Saúde do Centro Hospitalar Universitário de São João/Faculdade de Medicina da Universidade do Porto; Comissão de Ética do CAML; Comissão de Ética para a Saúde do IPOLFG; Comissão de Ética CHUP/ICBAS; Comissão de Ética para a Saúde do CHUC; E.P.E; Comissão de Ética para a Saúde do CHVNG-E; Comissão de Ética para a Saúde do IPO Porto EPE; Comissão de Ética do Hospital de Braga (CEHB). For more information, see Table S1 .
Informed Consent Statement
Informed consent was obtained from all subjects involved in the study.
Data Availability Statement
Supporting raw data and derived variables were submitted to MDPI to assist in the peer review process and provide full transparency on the results reported. The raw data supporting the conclusions of this article will be made available by the authors on request.
Conflicts of Interest
R.B.—Amgen: Consultancy, Research Funding, Speaker; Janssen: Consultancy, Speakers; B.M.S: Consultancy, Research Funding, Speakers; Takeda: Consultancy, Speakers; Sanofi: Consultancy, Speaker; Pfizer: Consultancy. A.R.—Received honoraria from Janssen, Takeda, Roche, Sanofi, Abbvie and AstraZeneca for invited speaker activities, and from Takeda, Roche and Prothena for advisory board activities. C.G.—Honoraria (consultancy, scientific lectures and participation in ad-visory boards) from Celgene/BMS, Janssen, Amgen, Takeda, Sanofi, Pfizer, Gilead, Abbvie; J.T., A.R.F.—Employees at Takeda Farmacêuticos Portugal. J.G.M., C.G., H.M., H.M., H.C., M.T., P.S., and P.P.—Nothing to disclose. The funder was involved in discussions regarding submission, but all decisions related to study selection and the decision to submit, including timing, were made solely by the authors. All authors had full access to the complete de-identified dataset and to all statistical programs/outputs used for the analyses and take responsibility for the integrity of the data and the accuracy of the data analysis.
References
1. WHO Multiple Myeloma Source: Globocan 2020 WHO Geneva, Switzerland 2020
2. Bergantim R. João C. Geraldes C. Neves M. Trigo F. Neves M. Mendes J. Pedrosa H. Lúcio P. Multiple Myeloma in Portugal: Incidence, Prevalence, Mortality and Treatment Pattern. EHA Library 2020 Available online: https://library.ehaweb.org/eha/2020/eha25th/297938/rui.bergantim.multiple.myeloma.in.portugal.incidence.prevalence.mortality.and.html?f=listing=0*browseby=8*sortby=1*search=MULTIPLE+MYELOMA+IN+PORTUGAL:+INCIDENCE,+PREVALENCE,+MORTALITY+AND+TREATMENT+PATTERN (accessed on 21 December 2023)
3. Urban V.S. Cegledi A. Mikala G. Multiple myeloma, a quintessential malignant disease of aging: A geroscience perspective on pathogenesis and treatment Geroscience 2023 45 727 746 10.1007/s11357-022-00698-x 36508077 PMC9742673
4. Huang J. Chan S.C. Lok V. Zhang L. Lucero-Prisno D.E. 3rd Xu W. Zheng Z.J. Elcarte E. Withers M. Wong M.C.S. The epidemiological landscape of multiple myeloma: A global cancer registry estimate of disease burden, risk factors, and temporal trends Lancet Haematol. 2022 9 e670 e677 10.1016/S2352-3026(22)00165-X 35843248
5. Bhatt P. Kloock C. Comenzo R. Relapsed/Refractory Multiple Myeloma: A Review of Available Therapies and Clinical Scenarios Encountered in Myeloma Relapse Curr. Oncol. 2023 30 2322 2347 10.3390/curroncol30020179 36826140 PMC9954856
6. Costa C. Neves M. Roque A.I. Sarmento-Ribeiro A.B. Gerivaz R. Tomé A. Afonso S. Santos J.S. Afonso C. Afonso A. 3335 Assessment of Multiple Myeloma-Related Burden on Caregivers—A Portuguese National Study Proceedings of the 65th ASH Annual Meeting and Exposition San Diego, CA, USA 2 November 2023
7. Hulin C. Hansen T. Heron L. Pughe R. Streetly M. Plate A. Perkins S. Morgan K. Tinel A. Rodrigues F. Living with the burden of relapse in multiple myeloma from the patient and physician perspective Leuk. Res. 2017 59 75 84 10.1016/j.leukres.2017.05.019 28582636
8. Dombeck C. Swezey T. Gonzalez Sepulveda J.M. Reeve B.B. LeBlanc T.W. Chandler D. Corneli A. Patient perspectives on considerations, tradeoffs, and experiences with multiple myeloma treatment selection: A qualitative descriptive study BMC Cancer 2023 23 65 10.1186/s12885-022-10458-x 36658490 PMC9850680
9. Oros J.F.F.G. Prieto M.L.R. Borda A. Quintero G. Lopez C.A. Melo A. Lacouture M.C.F. Tijaro-Ovalle N.M. Duarte M. Bernal P. Improving Quality of Life and Treatment Adherence in Multiple Myeloma Patients Using Education Strategies Based on Digital and Spaced Learning Blood 2022 140 13085 13087 10.1182/blood-2022-166879
10. Steinmetz H.T. Singh M. Milce J. Haidar M. Rieth A. Lebioda A. Kohnke J. Management of Patients with Relapsed and/or Refractory Multiple Myeloma Treated with Novel Combination Therapies in Routine Clinical Practice in Germany Adv. Ther. 2022 39 1247 1266 10.1007/s12325-021-02022-z 35034310 PMC8918129
11. Gay F. Engelhardt M. Terpos E. Wäsch R. Giaccone L. Auner H.W. Caers J. Gramatzki M. van de Donk N. Oliva S. From transplant to novel cellular therapies in multiple myeloma: European myeloma network guidelines and future perspectives Haematologica 2018 103 197 211 10.3324/haematol.2017.174573 29217780 PMC5792264
12. Dima D. Jiang D. Singh D.J. Hasipek M. Shah H.S. Ullah F. Khouri J. Maciejewski J.P. Jha B.K. Multiple Myeloma Therapy: Emerging Trends and Challenges Cancers 2022 14 4082 10.3390/cancers14174082 36077618 PMC9454959
13. Swan D. Murphy P. Glavey S. Quinn J. Bispecific Antibodies in Multiple Myeloma: Opportunities to Enhance Efficacy and Improve Safety Cancers 2023 15 1819 10.3390/cancers15061819 36980705 PMC10046900
14. Caraccio C. Krishna S. Phillips D.J. Schürch C.M. Bispecific Antibodies for Multiple Myeloma: A Review of Targets, Drugs, Clinical Trials, and Future Directions Front. Immunol. 2020 11 501 10.3389/fimmu.2020.00501 32391000 PMC7193016
15. Sheykhhasan M. Ahmadieh-Yazdi A. Vicidomini R. Poondla N. Tanzadehpanah H. Dirbaziyan A. Mahaki H. Manoochehri H. Kalhor N. Dama P. CAR T therapies in multiple myeloma: Unleashing the future Cancer Gene Ther. 2024 31 667 686 10.1038/s41417-024-00750-2 38438559 PMC11101341
16. Zhang X. Zhang H. Lan H. Wu J. Xiao Y. CAR-T cell therapy in multiple myeloma: Current limitations and potential strategies Front. Immunol. 2023 14 1101495 10.3389/fimmu.2023.1101495 36891310 PMC9986336
17. Martino E.A. Bruzzese A. Iaccino E. Labanca C. Mendicino F. Mimmi S. Lucia E. Olivito V. Neri A. Morabito F. Belantamab mafodotin in multiple myeloma Expert. Opin. Biol. Ther. 2023 23 1043 1047 10.1080/14712598.2023.2218543 37227998
18. Lonial S. Lee H.C. Badros A. Trudel S. Nooka A.K. Chari A. Abdallah A.-O. Callander N. Lendvai N. Sborov D. Belantamab mafodotin for relapsed or refractory multiple myeloma (DREAMM-2): A two-arm, randomised, open-label, phase 2 study Lancet Oncol. 2020 21 207 221 10.1016/S1470-2045(19)30788-0 31859245
19. Hungria V. Robak P. Hus M. Zherebtsova V. Ward C. Ho P.J. Ribas de Almeida A.C. Hajek R. Kim K. Grosicki S. Belantamab Mafodotin, Bortezomib, and Dexamethasone for Multiple Myeloma N. Engl. J. Med. 2024 391 393 407 10.1056/NEJMoa2405090 38828933
20. De Mel S. Lim S.H. Tung M.L. Chng W.J. Implications of Heterogeneity in Multiple Myeloma Biomed. Res. Int. 2014 2014 232546 10.1155/2014/232546 25101266 PMC4102035
21. Kumar S. Baizer L. Callander N.S. Giralt S.A. Hillengass J. Freidlin B. Hoering A. Richardson P.G. Schwartz E.I. Reiman A. Gaps and opportunities in the treatment of relapsed-refractory multiple myeloma: Consensus recommendations of the NCI Multiple Myeloma Steering Committee Blood Cancer J. 2022 12 98 10.1038/s41408-022-00695-5 35768410 PMC9243011
22. Moreau P. Kumar S.K. San Miguel J. Davies F. Zamagni E. Bahlis N. Ludwig H. Mikhael J. Terpos E. Schjesvold F. Treatment of relapsed and refractory multiple myeloma: Recommendations from the International Myeloma Working Group Lancet Oncol. 2021 22 e105 e118 10.1016/S1470-2045(20)30756-7 33662288
23. Ocio E.M. Montes-Gaisán C. Bustamante G. Garzón S. González E. Pérez E. Sirvent M. Arguiñano J.M. González Y. Ríos R. Clinical and Sociodemographic Characteristics of Patients With Relapsed and/or Refractory Multiple Myeloma and Their influence on Treatment in the Real-World Setting in Spain: The CharisMMa Study Clin. Lymphoma Myeloma Leuk. 2022 22 e241 e249 10.1016/j.clml.2021.10.001 34774462
24. SAS Institute Inc SAS Software 9.4 (SAS/STAT 15.2) SAS Institute Inc. Cary, NC, USA 2016
25. Mathew A. Hasan Farooqui H. Kumar L. Quality of life assessment & out-of-pocket expenditure in multiple myeloma: An observational study Indian. J. Med. Res. 2022 154 823 832 10.4103/ijmr.IJMR_4028_20 PMC9347259 35662087
26. Kocaata Z. Wilke T. Fischer F. Welte R. Einsele H. Healthcare Resource Utilization and Cost of Patients with Multiple Myeloma in Germany: A Retrospective Claims Data Analysis Pharmacoecon Open 2022 6 619 628 10.1007/s41669-022-00344-4 35750956 PMC9283612
27. Hanamura I. Multiple myeloma with high-risk cytogenetics and its treatment approach Int. J. Hematol. 2022 115 762 777 10.1007/s12185-022-03353-5 35534749 PMC9160142
28. Kumar S.K. Mikhael J.R. Buadi F.K. Dingli D. Dispenzieri A. Fonseca R. Gertz M.A. Greipp P.R. Hayman S.R. Kyle R.A. Management of newly diagnosed symptomatic multiple myeloma: Updated Mayo Stratification of Myeloma and Risk-Adapted Therapy (mSMART) consensus guidelines Mayo Clin. Proc. 2009 84 1095 1110 10.4065/mcp.2009.0603 19955246 PMC2787395
29. Rajkumar S.V. Multiple myeloma: 2024 update on diagnosis, risk-stratification, and management Am. J. Hematol. 2024 99 1802 1824 10.1002/ajh.27422 38943315 PMC11404783
30. Gengenbach L. Graziani G. Reinhardt H. Rösner A. Braun M. Möller M.-D. Greil C. Wäsch R. Engelhardt M. Choosing the Right Therapy for Patients with Relapsed/Refractory Multiple Myeloma (RRMM) in Consideration of Patient-, Disease- and Treatment-Related Factors Cancers 2021 13 4320 10.3390/cancers13174320 34503130 PMC8430818
31. Dimopoulos M.A. Moreau P. Terpos E. Mateos M.V. Zweegman S. Cook G. Delforge M. Hájek R. Schjesvold F. Cavo M. Multiple myeloma: EHA-ESMO Clinical Practice Guidelines for diagnosis, treatment and follow-up† Ann. Oncol. 2021 32 309 322 10.1016/j.annonc.2020.11.014 33549387
32. Sonneveld P. Broijl A. Treatment of relapsed and refractory multiple myeloma Haematologica 2016 101 396 406 10.3324/haematol.2015.129189 27033237 PMC5004403
33. Rifkin R.M. Bell J.A. DasMahapatra P. Hoole M. Lowe M. Curran C. Campbell S. Hou P. Romanus D. Treatment Satisfaction and Burden of Illness in Patients with Newly Diagnosed Multiple Myeloma Pharmacoecon Open 2020 4 473 483 10.1007/s41669-019-00184-9 31605300 PMC7426337
34. Bergatim R. Geraldes C. João C. Lúcio P. Neves M. Trigo F. Ventura M.P. Ramos D. P-178 Evolution of the multiple myeloma treatment landscape in Portugal: A 5-year longitudinal analysis of treatment patterns in nationwide clinical practice Clin. Lymphoma Myeloma Leuk. 2023 23 S133 S134 10.1016/S2152-2650(23)01796-2
35. Bylund C.L. Eggly S. LeBlanc T.W. Kurtin S. Gandee M. Medhekar R. Fu A. Khurana M. Delaney K. Divita A. Survey of patients and physicians on shared decision-making in treatment selection in relapsed/refractory multiple myeloma Transl. Behav. Med. 2023 13 255 267 10.1093/tbm/ibac099 36688466