Frontline treatment patterns and attrition rates by subsequent lines of therapy in patients with newly diagnosed multiple myeloma

Multiple myeloma (MM) treatment options have improved in recent years, but MM remains an incurable disease with an estimated 5-year survival rate of 52% in the United States [1]. Frontline and subsequent treatment options are selected based on a patient’s age, frailty, comorbidity status, intolerance, resistance, and/or exposure to previous therapy, and disease biology [2, 3]. If a patient is eligible, autologous stem cell transplant (ASCT) is recommended [2, 3]. Although patients who receive a stem cell transplant and maintenance therapy have superior outcomes compared with those who are transplant ineligible [4, 5], both groups of patients frequently experience disease relapse and require subsequent lines of therapy (LOTs).

Clinical trials evaluate the efficacy and safety of a therapy at a given disease stage and can be highly selective for a patient population (ie, by restricting enrollment to patients with good performance status). Although clinical trials provide valuable information for specific therapeutic regimens, there is limited information on the factors guiding treatment patterns and patient outcomes in a real-world setting.

Available real-world data suggest that most patients diagnosed with MM receive frontline therapy (64–95%); however, attrition rates increase with each successive LOT, with an estimated 32–61% and 14–38% of diagnosed patients receiving second- and third-line therapy, respectively [6‐8]. The depth of response, time to progression, and duration of treatment decrease with each successive LOT, while the incidences of toxicity increase [6]. Moreover, patient-reported health-related quality of life significantly decreases with each LOT [9]. Together, these data strongly support the use of the most effective therapy upfront.

The impact of newer agents on observed attrition rates has not yet been evaluated. This study utilized the most recent patient-level data available from three databases in the United States, capturing the years 2000 to 2018. Additionally, it characterized and compared newly diagnosed MM (NDMM) patients who did receive ASCT with those who did not by the number of subsequent LOTs received.

This retrospective analysis of real-world data from the United States demonstrates that attrition rates were high (up to 50% per LOT) and remained steady from the first through the fifth LOT among non-transplant patients. For transplant patients, attrition rates were generally lower, but increased with each successive LOT, ranging from 21–37%. The difference in attrition for non-transplant and transplant patients is not unexpected, given the different baseline characteristics and comorbidities of these two patient populations. For non-transplant patients, older age at diagnosis, cardiovascular disorders, pulmonary circulation disorders, and renal impairment were associated with higher attrition rates beyond the first LOT. For transplant patients, liver disease was associated with higher attrition rates. With longer follow-up, younger transplant patients were more likely to receive a second LOT, and pulmonary circulation disorders and renal impairment were associated with higher attrition rates.

Among non-transplant patients who received frontline therapy, approximately half received a second LOT and as few as 8% received a fifth LOT. For transplant patients, the proportions in subsequent therapies at each LOT were higher; 79% received a second LOT and 22% received a fifth LOT. In similar analyses of European patients with NDMM, 32–61%, 14–38%, 15%, and 1% received a second, third, fourth, and fifth LOT [6‐8, 11]. These estimates included patients with NDMM from multiple countries and, in some instances, did not differentiate between transplant and non-transplant patients. This analysis of the most recent patient-level data (up to 2018) available from three databases in the United States demonstrates a clear difference in attrition rates among transplant-ineligible and transplant-eligible patients. There was a slight increase in patients receiving subsequent LOTs, although it should be noted that the study included only those patients with NDMM who had received at least one LOT rather than all patients diagnosed with MM. Nevertheless, our analysis is consistent with previous real-world studies [6‐8, 11] and demonstrates the occurrence of high attrition rates in early lines of MM therapy. Treatment durations in our study were also generally consistent with other real-world analyses [6, 7, 12].

Vd and Rd were the most common standard-of-care (SoC) frontline treatments for patients who did not receive ASCT; the use of Rd as frontline therapy in this setting is consistent with current guidelines [13], although the use of triplets is increasing, and use of Vd is consistent with another real-world analysis reporting that non-transplant patients received Vd as frontline therapy (13.5%) [14]. However, these therapies are no longer optimal. For patients who received ASCT, the most common induction therapies were VRd and other bortezomib-containing regimens. These treatment patterns reflect current guidelines recommending that induction therapy include a minimum of bortezomib and dexamethasone [13]. For patients who received frontline induction therapy plus ASCT, the use of consolidation therapy was limited, seen in only 11% of patients. In our analysis, patients who received consolidation therapy were younger at diagnosis, had lower CCI scores, and had lower rates of cardiac arrhythmia, simple hypertension, pulmonary circulation disorders, and renal impairment. Although this estimate appears low, it is within range of previous real-world analyses (range, 2–22%) [11, 15].

Several limitations should be considered for this retrospective analysis of claims data. Claims data in real-world analyses inherently reflect the individual decisions of physicians as they evaluate and treat patients, which differ from the controlled and standardized methods used in clinical studies. In this real-world dataset, the incidence of pre-existing renal insufficiency was higher in non-transplant than transplant patients, which may or may not be attributable to MM. Furthermore, algorithms were used to establish LOTs, the details of which are included in Additional file 1. This may have led to the overestimation of attrition, as it included patients who were lost to follow-up due to a switch in insurance plans, loss of insurance coverage, or end of the study period. Attrition rates may also have been overstated because the database did not include information on patients’ disease progression; it was therefore not possible to distinguish between patients who did not experience disease progression and did not receive subsequent treatment and those who had disease progression but did not receive subsequent treatment during the study period. It is possible that some of the MM patients who received frontline therapy may have had smoldering MM. Moreover, this study excluded patients with NDMM who opted to forgo therapy. As such, the data herein should be interpreted in the context of patients who received at least one LOT, rather than the entire MM population. Lastly, comparisons within the same LOT between non-transplant and transplant patients, and comparisons of different LOTs within the transplant group, were not adjusted for exposure, and hence should be interpreted with caution.

High attrition rates for frontline and subsequent LOTs for MM, coupled with known decreases in overall survival, progression-free survival, and response to treatment with each LOT [6, 8, 14, 16] suggest that the most effective treatment is needed early to provide each patient the best opportunity for durable disease control and improved survival. As newer regimens evolve and are adopted into clinical practice as frontline therapies, further analyses of real-world data should be conducted to confirm whether improved outcomes and decreased attrition rates are associated with the earlier use of these superior therapies in the treatment paradigm.