Burden of disease progression in patients with multiple myeloma in the US

Abstract

Effects of disease progression on healthcare resource utilization (HRU) and costs among multiple myeloma (MM) patients with ≥1 line of therapy (LOT) and without receipt of stem cell transplant were estimated using large US claims database. Disease progression was defined as advancement to the next LOT, bone metastasis, hypercalcemia, soft tissue plasmacytoma, skeletal related events, acute kidney failure, or death within 12 months of LOT initiation. Annual HRU and costs in the first four LOTs were compared for patients with versus without progression using inverse probability of treatment weighting to adjust for differences between groups in baseline characteristics. In all LOTs, mean annual hospitalizations and healthcare costs were greater for patients with versus without progression. Total incremental annual costs among patients with versus without progression in 1LOT to 4LOT were $25,920, $30,632, $47,320, and $19,769, respectively. For MM patients receiving drug therapy, the economic burden of disease progression is substantial.

Keywords:

• Multiple myeloma
• disease progression
• healthcare costs
• retrospective study

Introduction

MM is a plasma cell neoplasm that is associated with a variety of complications, including – but not limited to – anemia, neutropenia, thrombocytopenia, bone loss and fractures, and kidney disease. In the US, approximately 30,770 new cases of MM are diagnosed, and approximately 12,770 persons die from the disease each year. Five-year survival for patients diagnosed with MM is approximately 51% [1].

Current treatment guidelines by the National Comprehensive Cancer Network (NCCN) Clinical Practice recommend initiating therapy when patients become symptomatic [2]. Initial treatment is individualized according to patients’ risk factors and is typically stratified according to transplant eligibility [2]. Most patients receive an initial regimen that includes combination treatment with a corticosteroid (i.e. dexamethasone) and a proteasome inhibitor (PI: bortezomib, carfilzomib, and ixazomib), and an immunomodulatory drug (IMiD: lenalidomide, pomalidomide, and thalidomide), a monoclonal antibody (MAb: daratumumab, and elotuzumab), and/or a chemotherapy [2]. For patients who are refractory to or relapse following initial treatment, the NCCN Guidelines recommend numerous treatment options including PIs, IMiDs, MAbs, and/or histone deacetylase inhibitors (panobinostat) [2]. Despite the multitude of options, the likelihood and duration of response decrease with each line of therapy (LOT) and the disease is ultimately fatal [2].

Previous retrospective observational studies have documented substantial costs for MM patients receiving second or subsequent treatments [3–6]. Although studies by Hagiwara et al. [3], Teitelbaum et al. [4], and Arikian et al. [5] have suggested no clear relationship between LOT and total or monthly costs, a study by MacEwan et al. [6] suggested slightly increasing total costs but relatively constant monthly costs by LOT. Data on the effects of disease progression on healthcare resource utilization (HRU), costs, and outcomes such as mortality and time to next treatment are limited [6–9]. Pandya et al. [7] and Clancy et al. [8] studied newly diagnosed MM patients in the US Medicare population and defined LOTs using a 60-day therapy identification period and a 60-day gap period. Pandya et al. [7] compared 1LOT patients who progressed early, defined by advancement to 2LOT before the median time to 2LOT of 1028 days versus 1LOT patients who did not progress, and reported that the annual per patient total healthcare costs were $120,604 versus $96,684 among patients with versus without early progression.

The objective of this study was to compared HRU and healthcare costs between MM patients with versus without progression who have received at least one LOT in the US using inverse probability of treatment weights (IPTWs) [10] to adjust for differences between the two groups.

Methods

Study design and patient selection

A retrospective incident user cohort design [11] was employed. Data for the study were obtained from the Truven Analytics MedStat MarketScan^® Commercial Claims and Encounters (CCAEs) and Medicare and Coordination of Benefits (MDCR) databases. Study subjects included all adult patients in the databases with a confirmed diagnosis of MM during the study period (1 January 2006 and 31 December 2016), where a confirmed diagnosis of MM was defined as at least one inpatient claim with a diagnosis of MM (ICD-9-CM code 203.0x or ICD-10-CM C90.0), or at least two non-diagnostic outpatient claims within 30–365 days apart with a diagnosis of MM. The date of each patient’s first claim with a diagnosis of MM was designated the ‘diagnosis date’. To ensure that the first claim with a diagnosis of MM in the databases represented initial diagnosis of the disease, patients with less than six months of continuous enrollment prior to their diagnosis date were excluded. Patients were further required to have initiated during the study period a course of MM therapy including one or more of the following: lenalidomide, pomalidomide, thalidomide, bortezomib, carfilzomib, ixazomib, daratumumab, elotuzumab, panobinostat, or vorinostat. Although vorinostat is not indicated for MM, it was included in our study since its use among MM patients has been investigated in clinical studies [12]. Patients with receipt of MM therapy or unclassified antineoplastic medications (HCPCS Code J9999) before the diagnosis date were excluded. Patients with stem cell transplant (SCT) at any time during the study period also were excluded since patient characteristics and patterns of treatment for patients with SCT are substantially different from those who do not receive transplant. For each remaining patient, the first date with MM therapy (1LOT initiation date) was identified. Patients with gaps in enrollment between the diagnosis date and the day 30 after the 1LOT initiation date were excluded. Also excluded were patients with evidence of receipt of more than one type of PIs simultaneously, with missing information on supply amounts of MM therapy that could not be imputed, or with missing demographic information.

Data source

The CCAE and MDCR databases contain enrollment information and information on the health insurance claims of employees of large, self-insured corporations and their dependents, along with a few commercial health plans (CCAE) and for Medicare-eligible persons (mainly retirees) who are also covered by self-insured employers (MDCR), and they are fully de-identified and compliant with the Health Insurance Portability and Accountability Act of 1996 (‘HIPAA’) [13]. All claims include information on charges and paid amounts. For each person in the databases, claim-level data can be arrayed in chronologic order to provide a detailed, longitudinal profile of all medical and pharmacy services received. The databases have been used widely in health services research over the past decade.

Identification of LOTs

For each qualified patient, LOT was identified based on a published algorithm [14]. The ‘treatment identification period’ for a LOT was defined as the 90-day period beginning with LOT initiation date. The LOT advancement date or the start date for the subsequent LOT was identified based on the earliest of: (1) the date of the first claim for a ‘new MM therapy,’ defined as an MM therapy for which there was no claim during the treatment identification period; (2) the date of the first claim for any MM therapy with a gap period greater than 90 days after the end of cycle; or (3) for patients who received more than one type of PI during the treatment identification period as there is no recommended combination therapy involving two PI medications, the first date with a claim for the second type of PI. Patients receiving lenalidomide maintenance therapy for 1LOT were identified based on the following: (1) patient’s first claim for a new MM therapy after the 1LOT treatment identification period was lenalidomide; (2) the first claim for lenalidomide occurred ≤60 days after the most recent prior cycle for a different MM therapy; and (3) there were no claims for any other MM therapy in the 90 day period beginning with this lenalidomide claim (i.e. lenalidomide monotherapy). If these conditions were met, the date of the first claim for lenalidomide after the 1LOT treatment identification period was designated as the start of 1LOT maintenance therapy (rather than 2LOT).

Disease progression and matching patients

For each qualified patient and LOT up to 4LOT, progression status was assessed for each LOT based on claims observed during ‘event identification period’, defined as the first 12-month period after LOT initiation date (Figure 1). Progression was defined as: (1) advancement to the next LOT; (2) evidence of bone metastasis, hypercalcemia, soft tissue plasmacytoma, skeletal related events fractures, acute kidney failure, and renal failure while off-therapy; or (3) evidence of death (based on discharge status, diagnosis codes, receipt of hospice care, that are observed within 1 month of disenrollment, excluding the disenrollment date of 31 December 2016, the end of study period).

Figure 1. Study design schematic.

For patients with progression, the ‘index date’ was defined as the date 30 days prior to documented progression (in order to capture care during ‘prodromal’ period and terminal care for those who died). For patients without progression, index date was randomly assigned to ensure similar distribution of time from treatment initiation to index date as for patients with progression.

Patient baseline clinical characteristics were assessed during ‘pre-index period’, defined as 12 months prior to index date. Patients with less than 12 months of continuous enrollment pre-index were excluded. Outcomes of interest were examined over the ‘follow-up period’ defined as the period beginning with the index date and ending with the end of the study period (31 December 2016) or the end of post-index continuous enrollment, whichever occurred first. For patients with claims for unclassified antineoplastic medications, the follow-up period was truncated on the date of the claim. When patients on Commercial plan switched to Medicare plan, the follow-up period was truncated at the date of the switch. Analyses were conducted by LOT, thus each patient could contribute to multiple analyses.

Outcomes and analysis

Annual HRU and total healthcare costs, during follow-up period were calculated for each patient and each LOT. Costs included patient contributions and were adjusted to 2016 US dollars. HRU measures included number of outpatient hospital visits and number of inpatient admissions. Cost measures included costs of MM therapy medications and administrations, costs of inpatient hospitalization, costs of outpatient services excluding services for MM therapy medications and administrations, costs of outpatient pharmacy excluding MM therapy medications, and total costs.

Annual HRU and costs were compared between patients with versus without progression using stabilized inverse probability of treatment weights (sIPTW) to adjust for differences between the groups in baseline characteristics including year of index date, age, gender, region, plan type, Medicare status, comorbidities, and pre-index HRU and healthcare costs. For each LOT, IPTWs were estimated using logistic regression with the progression status as the dependent variable and baseline patient characteristics as independent variables. The resulting predicted probability of progression was used to calculate the weights. Average treatment effect (ATE) weights were used. sIPTW was used to ensure that weighted samples did not artificially inflate the sample size [10]. The stabilized weights were calculated using the marginal probabilities of progression and no progression. To adjust for difference in duration of follow-up period, individual patients were also weighted by duration of follow-up.

Alternative cost estimates that take into account censored follow-up time were also estimated. For each LOT, expected cumulative total plan costs for patients with versus without progression were calculated using Kaplan–Meier’s sampling average (KMSA) method [15], a robust method for estimating cumulative costs over time when patients are censored. Due to lack of information on death, patients were censored when their disenrollment occurred at the end of the study period, thus the estimates are expected cumulative total cost to health plans. Incremental total plan costs were defined as the difference in expected cumulative total plan costs between patients with versus without progression.

A subgroup analyses was conducted for LOTs with index date between 2013 and 2016 to assess impact of progression in current era of novel treatments for multiple myeloma (MM) (carfilzomib was approved in late 2012, pomalidomide was approved in 2013, and daratumumab, elotuzumab, ixazomib, and panobinostat were approved in 2015), and for the remaining LOTs with index date in 2006–2012.

Results

Study patients

Of the 28,184 adult MM patients who received one or more MM therapy during the study period, 11,179 qualified for the study, including 4781 patients with progression and 6398 without progression during 1LOT, respectively. The numbers of matched pairs of patients with and without progression were 4612, in 1LOT, 1676 in 2LOT, 675 in 3LOT, and 285 in 4LOT, respectively.

Baseline characteristics

Mean age at index date was 68 years and 57% were male (Table 1). In all LOTs patients with progression were more likely to have comorbidities and had higher Charlson’s comorbidity index than those without progression. Number of emergency department visits, physicians’ office and other outpatient visits, and hospitalizations during 12-month period before index date (date of progression) were all higher among patients with progression in all LOTs. Hospitalization costs and costs of outpatient services during the pre-index period were higher among patients with progression, but the cost of outpatient prescription during the same period was higher among patients without progression. With sIPTW adjustment, all baseline characteristics were well balanced in all LOTs with standardized mean differences <0.1 for all characteristics for all LOTs (Supplement 1).

Table 1. Patient characteristics at index date by progression and LOT (for matched patients).

Characteristic	1LOT		2LOT		3LOT		4LOT
	Without progression	With progression	Without progression	With progression	Without progression	With progression	Without progression	With progression
	(N = 4612)	(N = 4612)	(N = 1676)	(N = 1676)	(N = 675)	(N = 675)	(N = 285)	(N = 285)
Time to progression since LOT initiation, months, mean (SD)	NA	4.74 (2.87)	NA	4.60 (2.99)	NA	4.44 (2.97)	NA	4.06 (2.83)
Age, years, mean (SD)	69.2 (11.6)	67.3 (11.9)	70.0 (11.3)	68.3 (11.9)	69.6 (11.4)	69.0 (12.0)	69.5 (12.0)	70.0 (11.5)
Females, N (%)	2022 (43.8)	1929 (41.8)	748 (44.6)	731 (43.6)	308 (45.6)	292 (43.3)	129 (45.3)	119 (41.8)
On Medicare, N (%)	2865 (62.1)	2485 (53.9)	1058 (63.1)	951 (56.7)	406 (60.1)	409 (60.6)	175 (61.4)	181 (63.5)
Charlson index, mean (SD)^a	1.95 (1.92)	2.26 (2.07)	1.84 (1.80)	2.16 (2.00)	1.73 (1.76)	2.07 (1.88)	1.97 (1.82)	2.11 (1.85)
Healthcare utilization, mean (SD)^a
No. of emergency department visits	1.71 (3.30)	2.09 (3.59)	1.44 (2.19)	1.99 (3.26)	1.30 (2.38)	1.77 (3.03)	1.48 (2.45)	2.12 (8.81)
No. of physician office or outpatient visits	30.6 (18.3)	32.0 (19.0)	34.3 (22.1)	37.3 (22.8)	33.1 (22.5)	36.8 (24.8)	34.5 (25.4)	35.9 (24.9)
No. of outpatient prescriptions	45.0 (28.6)	42.3 (30.9)	55.1 (30.4)	51.6 (33.4)	53.1 (29.2)	53.1 (34.0)	50.0 (29.1)	52.8 (30.8)
No. of hospitalizations	1.02 (1.19)	1.35 (1.46)	0.89 (1.17)	1.32 (1.68)	0.74 (1.08)	1.14 (1.57)	0.82 (1.14)	1.19 (1.43)
No. of inpatient days	7.06 (12.1)	10.76 (17.4)	7.17 (15.0)	10.15 (17.8)	4.97 (10.5)	7.45 (14.4)	5.13 (10.6)	7.76 (12.9)
Healthcare costs, $ in 2016, mean (SD)^a
Outpatient services	60,441 (70,248)	73,941 (77,440)	77,458 (84,211)	96,758 (105,845)	79,790 (91,311)	95,335 (99,013)	83,565 (98,559)	99,219 (105,848)
Outpatient prescriptions	27,471 (30,673)	19,192 (24,841)	48,272 (39,898)	34,309 (36,281)	49,631 (42,038)	38,968 (38,691)	50,215 (42,113)	40,349 (39,199)
Inpatient services	31,843 (65,368)	47,102 (86,168)	32,241 (77,903)	41,567 (76,140)	23,721 (51,035)	33,134 (70,544)	22,074 (53,152)	36,048 (84,600)
Total healthcare costs	119,756 (109,011)	140,235 (129,245)	157,970 (132,502)	172,634 (150,173)	153,142 (127,000)	167,437 (148,690)	155,855 (137,459)	175,615 (167,281)

LOT: line of therapy; N: number; SD: standard deviation.

a Calculated over 12-month period prior to the index date.

Healthcare utilization and costs

The mean number of hospitalizations per year was greater for patients with progression in all LOTs, with differences ranging from 0.44 (95% CI 0.38, 0.49) for 1L to 0.76 (95% CI 0.55, 0.96) for 3L (Figure 2 and Table 2). The mean number of outpatient visits per year also was greater for patients with progression in 1LOT through 3LOT. Total annual healthcare costs were greater for patients with versus without progression for all LOTs, with the difference (p value) of $25,920 (<.0001) for 1LOT, $30,632 (<.0001) for 2LOT, $47,320 (<.0001) for 3LOT, and $19,769 (0.1859) for 4LOT (Figure 3 and Table 2). Expected cumulative total plan costs were greater among patients with versus without progression (Table 3). KMSA estimates of incremental total healthcare costs were $57,647 for 1LOT, $58,941 for 2LOT, $58,293 for 3LOT, and $41,370 for 4LOT at 1-year post-index.

Figure 2. sIPTW adjusted annual healthcare resource utilization among patients with versus without progression by LOT. (A) Outpatient visits. (B) Hospitalization among LOTs.

Figure 3. sIPTW adjusted mean annual healthcare costs among patients with versus without progression by LOT. (A) Among LOTs initiated in 2006–2016. (B) Among LOTs initiated in 2013–2016.

Table 2. Mean (SE) annual healthcare resource utilization and costs during the follow-up period, for IPTW matched sample of pts with versus without progression by LOT.

Outcome	1LOT		2LOT		3LOT		4LOT
Without versus with progression
N unweighted (weighted)	4612 (4612) vs. 4,612 (4614)		1676 (1648) vs. 1676 (1682)		675 (672) vs. 675 (678)		285 (282) vs. 285 (286)
Follow-up months, Mean (SE)	19.34 (0.31) vs. 17.06 (0.29)		16.13 (0.48) vs. 13.68 (0.41)		12.96 (0.66) vs. 11.27 (0.50)		10.85 (0.84) vs. 9.67 (0.68)
Difference (95% CI), p value
No. of outpatient visits	15.73 (13.43, 18.03)	<.0001	15.53 (11.55, 19.51)	<.0001	14.95 (8.20, 21.70)	<.0001	–0.19 (–11.43, 11.05)	.9735
No. of hospitalizations	0.44 (0.38, 0.49)	<.0001	0.54 (0.43, 0.65)	<.0001	0.76 (0.55, 0.96)	<.0001	0.69 (0.36, 1.03)	<.0001
No. of hospitalization days	4.14 (3.52, 4.77)	<.0001	4.12 (3.09, 5.15)	<.0001	5.31 (3.44, 7.17)	<.0001	5.95 (3.04, 8.85)	<.0001
Costs, 2016 $
MM therapy medications and administration	–270 (–2397, 1857)	0.8037	–3902 (–7890, 86)	0.0552	3081 (–3259, 9422)	0.3406	–9569 (–20,253, 1116)	0.0791
Hospitalization	17,136 (13,837, 20,436)	<.0001	20,158 (13,516, 26,799)	<.0001	26,927 (14,865, 38,988)	<.0001	23,822 (2661, 44,982)	0.0275
Other outpatient visits	8648 (5593, 11,702)	<.0001	14,028 (9294, 18,762)	<.0001	15,588 (7959, 23,218)	<.0001	8658 (–3896, 21,212)	0.1761
Other outpatient prescriptions	406 (–118, 930)	0.1285	348 (–202, 898)	0.2145	1723 (701, 2746)	0.0010	–3142 (–5266, –1018)	0.0038
Total	25,920 (20,385, 31,456)	<.0001	30,632 (20,626, 40,638)	<.0001	47,320 (30,030, 64,609)	<.0001	19,769 (–9557, 49,096)	0.1859

LOT: line of therapy; MM: multiple myeloma; SE: standard error; Y: year.

Table 3. Expected cumulative total healthcare costs by progression, LOT, and years since index date.

LOT	Years since index date	With progression		Without progression		Difference (95% CI)
		N at risk	Total cost	N at risk	Total cost
1	1	2034	119,939	2302	62,291	57,647 (52,399, 62,413)
	2	1126	167,248	1428	97,359	69,889 (62,440, 77,067)
	3	636	194,732	846	121,898	72,834 (63,493, 82,000)
	4	343	212,136	499	138,346	73,791 (62,537, 84,896)
	5	199	223,704	283	149,738	73,966 (61,693, 86,339)
	6	125	230,860	147	157,313	73,546 (60,146, 87,093)
	7	70	236,812	71	162,753	74,059 (59,810, 88,404)
	8	40	241,250	31	165,673	75,577 (61,031, 90,504)
	9	19	244,636	11	167,469	77,168 (61,788, 92,897)
2	1	588	115,500	696	56,559	58,941 (50,804, 67,700)
	2	286	156,277	413	91,656	64,621 (51,975, 77,311)
	3	155	181,664	233	114,043	67,621 (50,792, 84,198)
	4	92	196,923	131	129,595	67,328 (47,988, 85,911)
	5	49	206,074	81	139,903	66,171 (45,294, 86,938)
	6	30	212,331	32	148,240	64,091 (41,269, 86,364)
	7	18	217,388	21	156,848	60,540 (36,051, 84,269)
3	1	211	119,243	232	60,950	58,293 (44,753, 71,145)
	2	76	159,610	138	103,277	56,334 (35,670, 75,812)
	3	40	179,629	73	131,510	48,119 (22,898, 73,028)
	4	16	195,460	38	148,789	46,671 (14,569, 77,769)
4	1	76	121,483	89	80,113	41,370 (19,505, 62,422)
	2	19	144,477	44	130,129	14,348 (–16,858, 43,215)

CI: confidence interval; LOT: line of therapy; N: number.

95% CI (confidence interval) was calculated based on the bootstrap method with 2000 replicated samples. For each LOT, results are not reported for years with less than 10 patients at risk in both progressed and not progressed groups.

LOTs with index date between 2013 and 2016

For LOTs with index date during period from 2013 to 2016, the mean number of hospitalizations per year and the number of outpatient visits per year were greater for patients with versus without progression in all LOTs (Supplement 2). Total annual healthcare costs also were greater for patients with versus without progression for all LOTs initiated during this period, with annual cost difference (p value) of $43,848 (<.0001) for 1LOT, $43,825 (<.0001) for 2LOT, $40,544 (0.0064) for 3LOT, and $75,391 (0.0017) for 4LOT. KMSA estimates of cumulative total healthcare costs were greater among patients with versus without progression, with the incremental costs of $69,109 for 1LOT, $63,568 for 2LOT, $61,764 for 3LOT, and $55,749 for 4LOT at 1-year post-index (Supplement 3). For 1LOT, 2LOT, and 4LOT, differences in total annual cost were larger during years 2013–2016 than years 2006 through 2016. For all LOTs, the incremental costs based on KMSA estimates at 1-year post-index were larger during years 2013–2016 than years 2006 through 2016.

Discussion

In this study using data from a larger health insurance claims database, we found that among patients with MM initiating medical therapy, those who experienced progression within one-year of initiating treatment had higher mean annual numbers of hospitalization and outpatient visits and higher mean annual costs and expected cumulative costs at one-year after progression than among those who did not experience progression. Similar results were observed when the analysis was restricted to patients progressed between 2013 and 2016; although, differences in costs between patients with versus without progression were generally greater in patients who progressed in the 2013–2016 period.

Pandya et al. [7] studied MM patients who were on Medicare and on MM medication therapy between 2011 and 2015, compared 1LOT patients who progressed, defined by advancement to 2LOT before the median time to next LOT (1028 days), versus the remaining 1LOT patients without progression, and reported that the annual per patient total healthcare costs were $120,604 versus $96,684 (p value <.0001) among patients with versus without early progression. In our study, mean annual healthcare costs for patients initiating 1LOT were $134,616 versus $108,696 (p value <.0001) for patient who did versus did not experience progression within one year of initiating treatment.

There are differences in methods employed by Pandya et al. and our study. Pandya et al. used a 60-day therapy identification period and a 180-day gap period, and compared patients with early-progression (defined as patients started 2LOT within 1028 days) versus patients without progression. On the other hand, our study used a 90-day therapy identification period and a 90-day gap period based on previously published studies [3,14], compared patients with versus without progression within 365 days, progression being defined as LOT advancement, evidence of conditions associated with progression, or death, and the cost figures were adjusted for difference in baseline characteristics. Despite these differences in the methods, both studies found that the progression is costly among MM patients on MM medication therapy.

This study was subjected to limitations inherent in the use of administrative claims data and identification of study subjects, assessment of their baseline characteristics, and measurement of study outcomes were subject to possible errors in the databases. That being the case, we do not anticipate any particular reasons for any errors to differ across treatment groups, or to bias the comparisons. Although patients in the MarketScan^® commercial and Medicare databases are geographically diverse, they may not be representative of all patients in the US. The commercial database includes claims information for employees of large, self-insured corporations and their dependents as well as a few commercial plans. Individuals employed by small to medium sized employers are therefore underrepresented. The Medicare database captures healthcare records for retirees enrolled in employer-sponsored Medicare supplemental (Part B) plans, as well as a small proportion of retirees enrolled in Medicare Advantage (Part C) plans. It does not include patients who enrolled in Medicare Part A but not in Part B (though over 90% who enroll in Part A also enroll in Part B) and may underrepresent patients in Medicare Part C Plans. Mues et al. reported that, as of 2016, 31% of Medicare beneficiaries were enrolled in Part C [16].

Although we attempted to control for baseline characteristics using sIPTW weights, data on some clinical characteristics (e.g. bone biopsy and serum test results) were unavailable and the possibility that comparisons between cohorts were confounded by unmeasured characteristics must be recognized.

While the algorithm used to identify lines of therapy in this study was based on previously conducted studies [3,14], the method approximates actual clinical decision and based on a 90-day gap or an introduction of new medications, and lines of therapy might have been misclassified in some instances.

Data on clinical parameters used to identify progression in patients with MM are largely unavailable in the MarketScan^® database. Progression therefore was identified based on advancement to the next LOT, evidence of events indicative of progression, or evidence of death. While it was expected that these proxies captured the majority of progression events, their sensitivity and specificity are unknown. The comparison of patients with versus without progression may be biased if there are unobserved confounding factors that are associated with disease progression and study outcomes.

As patient characteristics and patterns of treatment for patients with SCT are substantially different from those who do not receive transplant, patients with SCT at any time during the study period were excluded in this analysis. Further research is needed to address differences in HRU and healthcare costs between MM patients with versus without progression who have received SCT.

Lastly, strength and limitations of the employed method, incident user cohort designs, should be mentioned. While the method allows us to identify and evaluate all disease progressions since MM therapy initiation and to produce less biased estimates of outcomes, the method tends to yield a smaller sample size due to restrictions imposed to ensure patients were in an incident cohort.

Conclusions

For MM patients receiving drug therapy, the economic burden of disease progression is substantial across all LOTs and this burden is generally greater in the era of novel treatments for relapse and refractory MM. Incremental costs of progression are largely attributable to hospitalizations and outpatient visits. Treatments that delay progression may yield important reductions in downstream disease management costs. These savings should be considered in frameworks assessing the value of innovative treatments for MM.

Disclosure statement

Sumeet Panjabi and Emre Yucel are employees of Amgen, Inc. Rafael Fonseca is a consultant for Amgen, AbbVie, Bayer, BMS, Celgene, Jansen, Juno, Kite, Pharmacyclics, Sanofi, and Takeda, and is on the Scientific Advisory Board of Adaptive Biotechnologies. May Hagiwara and Thomas Delea received research funding from Amgen, Celgene, EMD Serono, Jazz, Merck, Novartis, Pfizer, Sanofi, Seattle Genetics, and Takeda.

Additional information

Funding

Funding for this study was provided to Policy Analysis Inc. by Amgen Inc.