Nilotinib versus dasatinib as second-line therapy in patients with Philadelphia chromosome-positive chronic myeloid leukemia in chronic phase who are resistant or intolerant to imatinib: a cost-effectiveness analysis based on real-world data

Abstract

Objective: To evaluate the cost-effectiveness of second-line nilotinib vs dasatinib among patients with Philadelphia chromosome-positive chronic myeloid leukemia in chronic phase (Ph+ CML-CP) who are resistant or intolerant to imatinib, from a US third-party perspective.

Methods: A lifetime partitioned survival model was developed to compare the costs and effectiveness of nilotinib vs dasatinib, which included four health states: CP on treatment, CP post-discontinuation, progressive disease (accelerated phase [AP] or blast crisis [BC]), and death. Time on treatment, progression-free survival, and overall survival of nilotinib and dasatinib were estimated using real-world comparative effectiveness data. Parametric survival models were used to extrapolate outcomes beyond the study period. Drug treatment costs, medical costs, and adverse event costs were obtained from the literature and publicly available databases. Utilities of health states were derived from the literature. Incremental cost-effectiveness ratios, including incremental cost per life-year (LY) gained and incremental cost per quality-adjusted life-year (QALY) gained, were estimated comparing nilotinib and dasatinib. Deterministic sensitivity analyses were performed by varying patient characteristics, cost, and utility inputs.

Results: Over a lifetime horizon, nilotinib-treated patients were associated with 11.7 LYs, 9.1 QALYs, and a total cost of $1,409,466, while dasatinib-treated patients were associated with 9.5 LYs, 7.3 QALYs, and a total cost of $1,422,122. In comparison with dasatinib, nilotinib was associated with better health outcomes (by 2.2 LYs and 1.9 QALYs) and lower total costs (by $12,655). Deterministic sensitivity analysis results showed consistent findings in most scenarios.

Limitations: In the absence of long-term real-world data, the lifetime projection could not be validated.

Conclusions: Compared with dasatinib, second-line nilotinib was associated with better life expectancy, better quality-of-life, and lower costs among patients with Ph+ CML-CP who were resistant or intolerant to imatinib.

Keywords:

• Cost-effectiveness
• chronic myeloid leukemia
• Philadelphia chromosome-positive
• nilotinib
• dasatinib
• second-line

Introduction

Chronic myeloid leukemia (CML) is a cancer initiating in hematopoietic stem cells and constitutes ∼15% of all adult leukemia cases in the US¹. Approximately 95% of patients with CML display a reciprocal translocation between chromosomes 9 and 22, known as the Philadelphia chromosome (Ph)^2–4. Currently, inhibition of BCR-ABL kinase activity with tyrosine kinase inhibitors (TKIs) is the mainstay of treatment for Ph positive (Ph+) CML⁵. Specifically, the first-generation TKI imatinib has long been a standard-of-care first-line therapy for patients with CML in chronic phase (CP)^6–9. When patients develop resistance or intolerance to imatinib, they are then switched to second-generation TKIs such as nilotinib or dasatinib⁸.

Since their US Food and Drug Administration approvals in 2006, second-line treatments of nilotinib and dasatinib have been compared in several cost-effectiveness analyses (CEAs)^10–13. However, these studies included notable data limitations that could be overcome by real-world evidence. First, there was a lack of comparative effectiveness evidence for nilotinib and dasatinib, and these drugs’ respective trials recruited patients based on different criteria^14,15, making indirect comparisons difficult. Second, at the time when these models were constructed, comparative survival data were not yet available. Thus, varying surrogate markers have been used across studies to impute survival endpoints^10–13. Because there is no well-defined conversion algorithm mapping these surrogate markets to survival outcomes that can be used across these trials, the imputed survival outcomes may not represent the real survival endpoints.

Newly available real-world evidence on the direct comparative effectiveness between second-line treatment with nilotinib and dasatinib¹⁶ can now help overcome the limitations of prior CEAs^10–13. Specifically, an online medical chart review by Griffin et al.¹⁶ retrospectively collected time on treatment (TOT), progression-free survival (PFS), and overall survival (OS) information on CML-CP patients who switched from imatinib to nilotinib or dasatinib as second-line therapy from 122 US hematologists and oncologists. TKI treatment has established CML as a chronic disease with a high survival rate⁸. Thus, it is important to re-evaluate the cost-effectiveness of second-line nilotinib vs dasatinib over a lifetime horizon based on this new direct comparative TOT, PFS, and OS data¹⁶. Leveraging the partitioned survival model structure and adopting similar health states as those used in the National Institute for Health and Care Excellence (NICE) health technology assessments published by Rogers et al.¹⁰ and Loveman et al.¹¹, this CEA uses direct comparative effectiveness on TOT, PFS, and OS from Griffin et al.¹⁶ to assess the economic value of nilotinib vs dasatinib as a second-line therapy over the lifetime of CML-CP patients, and may assist US third-party payers to better evaluate these therapies.

Methods

Model overview

A partitioned survival model^17,18 was developed in Excel (Microsoft, v. 2010) to compare the cost-effectiveness of nilotinib vs dasatinib in Ph+ CML-CP patients who were resistant or intolerant to imatinib, with a starting age of 60 years, and comprised of 35% females. These parameters were selected to be consistent with the effectiveness input source¹⁶. The model was constructed from a US third-party payer perspective with a lifetime time horizon. Thus, only direct costs, including drug costs, medical costs, and adverse events (AE) costs, were considered. The partitioned survival model consisted of four mutually exclusive heath states (Figure 1): CP on treatment, CP post-discontinuation, progressive disease (accelerated phase [AP] or blast crisis [BC]), and death. To better estimate the cost and effectiveness of treatments, a half-cycle correction was applied to the model^17,19. Both costs and effectiveness were discounted at 3% annually.

Figure 1. Partitioned survival model structure. CP: chronic phase; AP: accelerated phase; BC: blast crisis.

Model assumptions

The model incorporated several key assumptions. First, a hypothetical cohort of Ph+ CML-CP patients who were resistant or intolerant to imatinib (per the drug labels of nilotinib or dasatinib) and received second-line nilotinib or dasatinib started with the CP on treatment state at the time of model entry. Patients with CML who were resistant or intolerant to imatinib were included in order to be consistent with the US FDA-approved indications of nilotinib and dasatinib^20,21. Second, all transitions were unidirectional, i.e. patients could only transition into a subsequent health state (e.g. CP on treatment to CP post-discontinuation) but not in the other direction. Patients in CP on treatment, CP post-discontinuation, or progressive disease could all transition directly to death. Third, after the discontinuation of second-line treatment (i.e. CP post-discontinuation), or when entering the progressive disease state, patients were assumed to have received a mixture of commonly-used treatments monthly. Fourth, in addition to monthly treatment costs, the model assumed that, when transitioning to the progressive disease state, a proportion of patients would also incur one-time costs for chemotherapy and bone marrow transplantation. Fifth, medical costs incurred by patients were assumed to be dependent only on health states and independent of treatments, i.e. nilotinib- and dasatinib-treated patients would incur the same medical costs in CP on treatment, CP post-discontinuation, and progressive disease, respectively. Sixth, grade 3/4 AE costs were considered in the model, and costs were added as monthly costs in CP on treatment during the first 24 months, which was consistent with the timeframe of AE inputs from the respective clinical trials (see “Model Inputs” section below). Finally, health utilities were assumed to be dependent only on health states and independent of treatments. No disutilities (decrease in health utility values) due to AEs were considered in the model in order to avoid double-counting in health state utilities (see “Model Inputs” section below).

Model inputs

Effectiveness inputs

Effectiveness inputs, including TOT, PFS, and OS, were derived from the patient-level data of Griffin et al.¹⁶, a US chart review study comparing nilotinib (n = 301) and dasatinib (n = 296) as second-line therapies (initiating treatment after October 28, 2007, when both drugs were approved) in Ph+ CML-CP patients who were resistant or intolerant to imatinib. Patients were included in that study if they met the following criteria: a diagnosis of Ph+ CML, at least 18 years of age at CML diagnosis, received imatinib as first-line therapy, switched to either dasatinib or nilotinib therapy after October 28, 2007 and at least 180 days prior to the data collection date, in CML-CP at the time of the switch, not diagnosed with other concurrent malignancies prior to the switch, and followed by the responding physician for at least 30 days after the switch¹⁶. Among the Griffin et al.¹⁶ patient cohort, the reasons for switching from imatinib to second-line therapy included primary or secondary imatinib resistance, AEs or intolerance of imatinib, and non-adherence to imatinib; more nilotinib patients experienced secondary resistance (p = .05) and more dasatinib patients experienced AEs or intolerance (p = .02)¹⁶ (Supplemental Table 1). The median time from CML diagnosis at the index date was 15 months for nilotinib patients and 13 months for dasatinib patients, with a median follow-up time of 11 months and 10 months for nilotinib and dasatinib patients, respectively.

Although Griffin et al.¹⁶ reported time to progression (TTP) data, PFS was used instead of TTP because the partitioned survival model intended to estimate the time on progression-free survival and post-progression survival. TTP, not accounting for pre-progression death, was not suitable for this model. The parameter estimates for TOT, PFS, and OS were obtained from the corresponding data using various parametric survival functions, i.e. exponential, log-logistic, log-normal, and Weibull distribution. The goodness-of-fit criteria including the Akaike information criterion (AIC)^22–24 and Bayesian information criterion (BIC)^23,25,26 were analyzed for each parametric function. The exponential function was selected as the base-case, because it was associated with the best AIC for TOT and OS, and the best BIC for TOT, PFS, and OS. Furthermore, the model incorporated the natural mortality rates from US life tables within the 2010 National Vital Statistics Report²⁷ into the calculation of OS. The TOT, PFS, and OS projection for both nilotinib and dasatinib, factoring in natural mortality rates, is shown in Figure 2, where all patients will be deceased at the end of the 480 months following second-line treatment initiation (i.e. when they are 100 years old).

Figure 2. Projected time on treatment, progression-free survival, and overall survival (including natural mortality). (A) Nilotinib (exponential parametric function). (B) Dasatinib (exponential parametric function). OS: overall survival; PFS: progression-free survival; TOT: time on treatment.

Utility inputs

Utility (a measurement of preferences for specific health-related outcomes) inputs for CP on treatment and progressive disease, were obtained from Szabo et al.²⁸, which was a time trade-off preference survey conducted among patients with CML in the US, UK, Canada, and Australia, and US-specific inputs were adopted in the model. Since Szabo et al.²⁸ incorporated incremental disutilities (decrease in utility values) due to treatment-related toxicities into the estimation of utility, no disutilities due to AEs were further considered in the model. In the absence of information on utility specific to CP post-discontinuation, utility for CP post-discontinuation was assumed to be the same as that in CP on treatment, because patients in CP post-discontinuation were still in CP (i.e. not experiencing disease progression) and had switched to a third-line treatment (Table 1).

Table 1. Base-case model inputs.

Input	Value	Notes/References
CML-related drug costs
CP on treatment (per month)	Nilotinib: $8,818.19	Unit costs based on the 2015 Red Book^30, with an average starting dose from Griffin et al.^16, assuming 100% adherence rate^10^,^11.
	Dasatinib: $12,041.58
CP post-discontinuation (per month)	For nilotinib-treated patients: $10,195.69	Treatments included: dasatinib, bosutinib, ponatinib, interferon alpha, and omacetaxine^8; unit costs based on the 2015 Red Book^30; proportions were estimated based on a physician survey^31.
	For dasatinib-treated patients: $10,196.87	Treatments included: nilotinib, bosutinib, ponatinib, interferon alpha, and omacetaxine^8; unit costs based on the 2015 Red Book^30; proportions were estimated based on a physician survey^31.
Progressive disease	Monthly cost: $7,233.73	Treatments included: bosutinib, ponatinib, interferon alpha, and omacetaxine^8; unit costs based on the 2015 Red Book^30; proportions were estimated based on a physician survey^31.
	One-time cost: $47,254.41	Treatments included chemotherapy and bone marrow transplant^8; unit cost of chemotherapy was based on a claims database analysis^31, while unit cost of bone marrow transplant was based on Maziarz et al.^35; proportions were estimated based on a physician survey^31.
Medical costs
Monitoring and resource utilization costs (per month)	CP on treatment: $552.72 CP post-discontinuation: $552.72Progressive disease: $2,230.73	Monitoring costs The types of monitoring tests were based on NCCN guidelines^8; the unit costs of monitoring tests were obtained from the CMS Physician Fee Schedule^36; the frequencies of monitoring tests for CP on treatment were obtained from Goldberg et al.^37, and frequencies of monitoring tests specific to CP post-discontinuation or progressive disease were assumed to be the same as those for CP on treatment.
		Resource utilization costs The types of resources used were based on Reed et al.^38; the unit costs of resources used were based on the CMS Physician Fee Schedule^36 and Reed et al.^38; the frequencies of resources used for CP on treatment and progressive disease were based on Reed et al.^38, and frequencies of resources used specific to CP post-discontinuation was assumed to be the same as those for CP on treatment.
Terminal care costs for the last month before death	$82,014.77	Based on Yabroff et al.^39.
AE costs (per month up to 24 months in CP on treatment)	Nilotinib: $396.13Dasatinib: $305.13	Grade 3/4 AEs included those occurring in ≥5% patients treated with either second-line nilotinib or dasatinib over a 24-month timeframe; the proportion of patients experiencing AEs for nilotinib and dasatinib were obtained from Kantarjian et al.^40 and Shah et al.^15, respectively; AE unit costs were obtained from Liou et al.^41 or HCUPnet^42.
Utility	CP on treatment: 0.82CP post-discontinuation: 0.82Progressive disease: 0.53	Utility inputs for CP on treatment and progressive disease were obtained from Szabo et al.^28; utility for CP post-discontinuation was assumed to be the same as that for CP on treatment.

CML: chronic myeloid leukemia; CP: chronic phase; LY: life years; QALY: quality-adjusted life years; AE: adverse event; NCCN: National Comprehensive Care Network; CMS: Center for Medicare and Medicaid Services.

Cost inputs

The model included the following types of direct healthcare cost inputs: CML-related drug costs, medical costs (including monitoring, resource utilization, and terminal care costs), and AE-related costs. All cost inputs were obtained from the literature or publicly available data (detailed below) and inflation-adjusted to 2015 USD using the medical component of the Consumer Price Index²⁹ (Table 1).

CML-related drug costs

When estimating CML-related drug costs for CP on treatment, the model considered unit drug cost, dosing schedule, average starting dose, and adherence level. The unit cost of nilotinib and dasatinib was obtained from the 2015 Red Book Online³⁰ using the wholesale acquisition cost. The dosing schedules for nilotinib (400 mg twice daily) and dasatinib (100 mg/day) for CML-CP were obtained from their corresponding drug labels^20,21. The starting doses were based on Griffin et al.¹⁶: of the dasatinib patients, 70.9% were prescribed 100 mg daily, and, of the nilotinib patients, 45.9% received 300 mg twice daily and 44.9% received 400 mg twice daily. Adherence was used as a proxy for relative dose intensity. The adherence levels for both nilotinib and dasatinib were assumed to be 100% in the base-case to be consistent with those in the previous CEAs of second-line nilotinib vs dasatinib^10,11. In the absence of strong real-word evidence comparing the adherence to second-line nilotinib vs dasatinib, adherence levels were tested in the sensitivity analysis.

When estimating CML-related drug costs for CP post-discontinuation, the model assumed that patients who initiated nilotinib as second-line treatment could switch to dasatinib in CP post-discontinuation and vice versa, as well as to other therapies including bosutinib, ponatinib, interferon alpha, and omacetaxine, based on the National Comprehensive Cancer Network (NCCN) guidelines⁸. Treatment costs were calculated for each monthly cycle (hereinafter referred to as “monthly treatment”). A survey of 100 hematologists and oncologists in the US who had treated Ph+ CML patients with second-line nilotinib or dasatinib after first-line imatinib was conducted to estimate the proportion of patients receiving each treatment for the CP post-discontinuation state³¹. For these monthly treatments, the unit cost was obtained from the 2015 Red Book Online³⁰ and the dosing schedule was obtained from drug labels and previous CEAs^{10,11,32–34}.

When estimating CML-related drug costs for progressive disease, the model considered both monthly treatment costs and one-time treatment costs, where treatments were selected based on the NCCN guidelines⁸. However, the model assumed that patients would not receive nilotinib or dasatinib in the progressive disease state. Monthly treatments included bosutinib, ponatinib, interferon alpha, and omacetaxine. One-time treatments included chemotherapy and bone marrow transplant. The proportion of patients receiving each treatment for progressive disease was also obtained from the aforementioned physician survey¹⁶. For monthly treatments, the unit costs were obtained as described above. For one-time treatments, the unit cost of chemotherapy was obtained from a retrospective claims database analysis using the PharMetrics Plus and MarketScan databases³¹; the unit cost of bone marrow transplantation was obtained from Maziarz et al.^35,36.

Medical costs

Medical costs consisted of monitoring costs, resource utilization costs, and terminal care costs. For monitoring costs, the types of monitoring tests used were based on the NCCN guidelines⁸. The unit costs of monitoring tests were obtained from the Centers for Medicare and Medicaid Services (CMS) Physician Fee Schedule (unit costs: polymerase chain reaction [PCR] test, $223; cytogenetic test, $543)³⁶. The frequencies of monitoring tests for CP on treatment were obtained from Goldberg et al.³⁷. In the absence of information on frequencies of monitoring tests specific to CP post-discontinuation or progressive disease, they were assumed to be the same as those for CP on treatment. For costs related to resource utilization, the types of resources used were based on Reed et al.³⁸. The unit costs of generalist and specialist visits were also obtained from the CMS Physician Fee Schedule³⁶. Because the unit costs of nurse and inpatient visits were not available from the CMS Physician Fee Schedule, they were obtained from Reed et al.³⁸. The frequencies of resource utilization for CP on treatment and progressive disease were also based on Reed et al.³⁸. In the absence of information on frequencies of resource utilization specific to CP post-discontinuation, they were assumed to be the same as those for CP on treatment. Last, all patients who transitioned to death were assumed to incur terminal care costs in the last cycle before death. Terminal care cost information was obtained from Yabroff et al.³⁹.

AE costs

Grades 3/4 AEs were included in the model if they had a rate of ≥5% over a 24-month timeframe in either of the pivotal trials of second-line nilotinib⁴⁰ or dasatinib¹⁵. The model first converted the 24-month rates to 1-month probabilities, and then applied the monthly AE costs up to 24 months in CP on treatment. Unit costs for neutropenia, thrombocytopenia, and anemia were obtained from Liou et al.⁴¹, a systematic review on costs of these hematological AEs in cancer patients, while unit costs for leukopenia, lipase elevation, hyperglycemia, hypophosphatemia, and elevated bilirubin (total) were obtained from the Agency for Healthcare Research and Quality’s HCUPnet⁴².

Model outputs

Model outputs included total costs and total effectiveness associated with nilotinib and dasatinib, measured by life years (LYs) and quality-adjusted life years (QALYs). LYs were estimated as the time spent in each state, while QALYs were estimated as the time spent in each state weighted by the utility for each state. Incremental cost-effectiveness ratios (ICERs), measured as the incremental costs per LY gained and the incremental costs per QALY gained, were estimated by comparing nilotinib with dasatinib:

Sensitivity analysis

A deterministic sensitivity analysis was conducted to test the model’s robustness by examining the impact of change in one key model input or assumption, while holding others at the base-case value. The model inputs varied were starting age, proportion of females, adherence/dose intensity for both drugs, CP post-discontinuation drug treatment costs, progressive disease drug treatment costs, medical costs, AE costs, and utility for CP post-discontinuation.

Results

Over a lifetime horizon, patients in the nilotinib group were found to have 11.7 LYs and 9.1 QALYs, and to incur a total cost of $1,409,466. Of this total direct healthcare cost, 87.9% was attributed to CML-related drug costs, 11.5% to medical costs, and 0.6% to AE-related costs. Patients in the dasatinib group were found to have 9.5 LYs and 7.3 QALYs, and to incur a total cost of $1,422,122. Of this total direct healthcare cost, 88.5% was attributed to CML-related drug costs, 11.0% to medical costs, and 0.5% to AE costs (Table 2). Thus, in comparison with dasatinib, second-line treatment with nilotinib was associated with better health outcomes (with differences of 2.2 LYs and 1.9 QALYs) as well as lower total costs (a difference of $12,655) over a lifetime horizon.

Table 2. Base-case results.

	Nilotinib	Dasatinib	Nilotinib vs Dasatinib
Costs (in 2015 USD)
Treatment costs	$1,238,256	$1,258,947	−$20,691
CP on treatment	$917,086	$999,406	−$82,320
CP post-discontinuation	$181,380	$104,278	$77,102
Progressive disease	$139,790	$155,264	−$15,474
Medical costs	$162,623	$156,762	$5,861
CP on treatment	$57,483	$45,948	$11,535
CP post-discontinuation	$9,833	$5,653	$4,180
Progressive disease	$41,746	$46,270	−$4,524
Death (terminal care cost)	$53,562	$58,891	−$5,329
AE costs	$8,587	$6,413	$2,174
Total costs	$1,409,466	$1,422,122	−$12,655
Effectiveness
Total LYs	11.7	9.5	2.2
CP on treatment	8.7	6.9	1.7
CP post-discontinuation	1.5	0.9	0.6
Progressive disease	1.6	1.7	−0.2
Total QALYs	9.1	7.3	1.9
CP on treatment	7.1	5.7	1.4
CP post-discontinuation	1.2	0.7	0.5
Progressive disease	0.8	0.9	−0.1
Incremental cost-effectiveness ratio (ICER)	Nilotinib was associated with a higher number of LY (difference: 2.2) and QALY (difference: 1.9), and lower costs (difference: $12,655) vs dasatinib

CP: chronic phase; LY: life years; QALY: quality-adjusted life years; USD: United States dollars.

The deterministic sensitivity analysis results showed a consistent finding of better QALY and lower costs for nilotinib vs dasatinib in most of the scenarios (Table 3), including variation in sex-ratio, progressive disease treatment costs, medical costs for all health states, AE costs, adherence/dose intensity, and utility for CP post-discontinuation. Out of 18 scenarios tested, the only three scenarios in which the sensitivity analysis resulted in better QALY but higher costs for nilotinib vs dasatinib were after decreasing the starting age of 60 years by 5 years to 55 years, decreasing the adherence of both nilotinib and dasatinib to 80%, and increasing CP post-discontinuation monthly treatment costs by 20%. In these cases, the ICERs were $10,095, $2,055, and $1,492 per QALY, respectively, suggesting that nilotinib was slightly more costly relative to dasatinib per QALY gained.

Table 3. Deterministic sensitivity analysis results.

Model input	Variation	Parameter	Base-case input	DSA input	DSA ICER per QALY (Nilotinib vs Dasatinib)
Starting age	+5 years	Starting age	60	65	Dominant*
	−5 years	Starting age	60	55	$10,095
% female	+10% absolute points	% female	35%	45%	Dominant
	−10% absolute points	% female	35%	25%	Dominant
Adherence for both drugs	Assume 80% adherence for both drugs	Nilotinib adherence	100%	80%	$2,055
		Dasatinib adherence	100%	80%
CP post-discontinuationdrug treatment costs	20%	Nilotinib monthly costDasatinib monthly cost	$10,196$10,197	$12,235$12,236	$1,492
	−20%	Nilotinib monthly cost	$10,196	$8,157	Dominant
		Dasatinib monthly cost	$10,197	$8,157
Progressive disease drug treatment costs	20%	Recurrent monthly costOne-time cost	$7,234$47,254	$8,680$56,705	Dominant
	−20%	Recurrent monthly cost	$7,234	$5,787	Dominant
		One-time cost	$47,254	$37,804
Medical costs	20%	CP on treatment	$553	$663	Dominant
		CP post-discontinuation	$553	$663	Dominant
		Progressive disease	$2,231	$2,677	Dominant
	−20%	CP on treatment	$553	$442	Dominant
		CP post-discontinuation	$553	$442	Dominant
		Progressive disease	$2,231	$1,785	Dominant
AE costs	20%	Nilotinib AE cost	$396	$475	Dominant
		Dasatinib AE cost	$305	$366
	−20%	Nilotinib AE cost	$396	$317	Dominant
		Dasatinib AE cost	$305	$244
Utility for CP post-discontinuation	−0.1 absolute points	CP post-discontinuation utility	0.82	0.72	Dominant

DSA: deterministic sensitivity analysis; ICER: incremental cost-effectiveness ratios; QALY: quality-adjusted life years; AE: adverse events; CP: chronic phase.

* “Dominant” indicates nilotinib was associated with better QALY and lower costs vs dasatinib.

Discussion

This study re-assessed the cost-effectiveness of second-line nilotinib vs dasatinib among patients with Ph+ CML-CP who were resistant or intolerant to imatinib, based on real-world comparative effectiveness data (TOT, PFS, and OS) from Griffin et al.¹⁶. The base-case results showed that, over a lifetime horizon, second-line nilotinib was associated with better life expectancy (LY difference =2.2 years) and better quality-of-life (QALY difference =1.9 years). Because the monthly treatment cost of nilotinib was lower than that of dasatinib, nilotinib was associated with a total lifetime treatment cost savings of $20,691, which exceeded the total medical cost difference ($5,861) and total AE cost difference ($2,174) compared to dasatinib. Therefore, over a lifetime horizon, nilotinib was associated with lower total healthcare cost (by $12,655) relative to dasatinib. In addition, these results remained robust across the various deterministic sensitivity analyses, with the majority of scenarios showing consistent dominance of nilotinib over dasatinib.

The current CEA presents improvements relative to previous CEAs comparing second-line nilotinib vs dasatinib^10–13. First, prior CEAs did not use comparative effectiveness evidence between nilotinib and dasatinib due to a lack of data. For example, in the dasatinib manufacturer’s UK NICE submission model¹³, effectiveness data for nilotinib and dasatinib were derived based on their respective trials, which recruited patients based on different criteria. Conversely, the current effectiveness data for nilotinib and dasatinib were based on direct comparative evidence from a real-world chart review study¹⁶, which retrospectively collected medical chart information from US hematologists and oncologists on Ph+ CML-CP patients who switched from imatinib to nilotinib (n = 301) or dasatinib (n = 296) as second-line therapy, and compared TOT, PFS, and OS between these two groups of patients. Second, prior CEAs used surrogate markers to impute survival endpoints. Specifically, the dasatinib manufacturer’s model submitted to the UK NICE¹³ used hematologic and cytogenetic response as surrogate markers to impute survival endpoints, Rogers et al.¹⁰, Loveman et al.¹¹, and Hoyle et al.⁴³ used major cytogenetic response (MCyR), and Whalen et al.¹² used complete cytogenetic response (CCyR) and major molecular response (MMR). In comparison, the current CEA used survival endpoints directly collected from the aforementioned chart-review study¹⁶. A 2014 study by Kulpeng et al.⁴⁴ found that, among a population of Thai patients with CML-CP resistant or intolerant to imatinib, dasatinib was more cost-effective that nilotinib⁴⁴. However, treatment with nilotinib resulted in the highest number of QALYs in comparison with dasatinib or high-dose imatinib. While this study came to a different conclusion per comparative cost-effectiveness, drug costs, healthcare access/costs, and patient characteristics vary widely by country and by population, as noted by Kulpeng et al.⁴⁴. Major differences in healthcare infrastructure and economic parameters exist between Europe/US and Thailand, and the mean age of CML onset in Thailand was 45 years vs ∼69 years in Western populations (the median age in Griffin et al.¹⁶ was 60 years). In addition, Kulpeng et al.⁴⁴ used CCyR as an efficacy indicator, which contrasts with prior studies which used MCyR^10,11,43, and came to conclusions that were similar to those of the current study. Finally, Kulpeng et al.’s⁴⁴ efficacy inputs were derived from three clinical trials, while the current study used real-world data—a major difference which may also account for our differing conclusions.

A 2015 study by Rochau et al.⁴⁵ assessed the balance of cost-effectiveness and effectiveness of 18 treatment strategies for patients with CML-CP, taking into consideration survival, quality-adjusted survival, and costs. The study assumed patients would transition from first-line TKI (imatinib, bosutinib, nilotinib, and dasatinib) to (1) chemotherapy/SCT, or (2) a second-line TKI followed by chemotherapy/SCT. In this context, the authors found that the most cost-effective treatment strategies involving second-line TKI were imatinib → nilotinib → chemotherapy/SCT ($253,500/QALY), and nilotinib → dasatinib → chemotherapy/SCT ($445,100/QALY). Rochau et al.’s⁴⁵ study may not be directly comparable to the current analysis, because they considered three lines of therapy while we considered two lines, although they similarly found that second-line nilotinib was the most cost-effective choice in the sequence. The sequencing of therapies is an important topic for healthcare decision-makers, particularly now that imatinib is now generic and can be assumed to be widely used as a cost-effective first-line therapy⁴⁶.

The results of this study provide economic evidence, in addition to the clinical literature, associated with the second-line treatment of Ph+ CML-CP patients to assist US third-party payers in making reimbursement decisions. US healthcare spending has been rapidly increasing over recent years⁴⁷, and the upward trend in cancer treatment costs is particularly striking⁴⁸. Various frameworks, such as the American Society of Clinical Oncology (ASCO) conceptual framework⁴⁹, have been developed to aid healthcare decision-makers such as payers in evaluating the comparative value of cancer treatment options. In the framework, CEA is considered an important method to determine the value of new technologies compared with the current standard of care. Although there is no standard process across third-party US payers to evaluate whether a drug is cost-effective, they have increasingly adopted CEA as an important reference for reimbursement decision-making⁵⁰. Therefore, the findings of this real-world data-based CEA, showing that second-line nilotinib was associated with better effectiveness and lower costs relative to dasatinib for Ph+ CML-CP patients, are of particular interest to US payers given their strong need to curb cancer drug spending.

This study is subject to several limitations, some of which are inherent to economic modeling studies. First, the model inputs were obtained from various data sources that were not necessarily based on the study population. However, best efforts were made to select the most fit model inputs based on the existing literature and de novo data collection (i.e. physician survey). Extensive sensitivity analyses were also conducted to test the robustness of the model and showed that, in the majority of scenarios, the results were consistent with the base-case analysis. Second, effectiveness inputs were estimated based on a chart review study¹⁶ with a 24-month follow-up time period, and the estimated effectiveness data fit well against the observed data. However, because long-term real-world data was not available, the lifetime projection could not be validated. Third, the proportion of patients receiving each CP post-discontinuation and progressive disease treatment was estimated based on a physician survey with a relatively small sample size (100 hematologists/oncologists in the US). Thus, the generalizability of the results may be limited. Fourth, due to lack of data, certain assumptions were made in cost and utility inputs, e.g. frequencies of monitoring tests specific to CP post-discontinuation or progressive disease were assumed to be the same as those for CP on treatment. Last, because this analysis used effectiveness inputs from Griffin et al.¹⁶, the limitations of that study carry forward to the present study. Namely, these include that no mutation test results were included and that median follow-up was a little less than a year. In addition, a greater proportion of Griffin et al.’s¹⁶ patients receiving second-line nilotinib had secondary resistance to imatinib (p = .047), and a greater proportion of those receiving second-line dasatinib had AEs with and intolerance to imatinib (p = .024). Thus, because nilotinib patients were more likely to be resistant to imatinib, our approach is likely biased against nilotinib because these patients are expected to have worse clinical outcomes, and thus is a conservative approach.

Conclusion

The current CEA, based on real-world comparative effectiveness evidence, suggested that, compared with dasatinib, second-line nilotinib was associated with better life expectancy and quality-of-life, and lower total healthcare costs among patients with Ph+ CML-CP who are resistant or intolerant to imatinib. Deterministic sensitivity analysis results were robust, and nilotinib had better outcomes and lower costs relative to dasatinib in all scenarios except when starting age, adherence for both drugs, and CP post-discontinuation costs were changed.

Transparency

Declaration of funding

Funding for this research was provided by Novartis Pharmaceuticals Corporation. The study sponsor was involved in all stages of the study research and manuscript preparation, but all authors participated in the design of the study and contributed to the manuscript development.

Declaration of financial/other relationships

NL, XY, LF, TT, and AG are employees of Analysis Group Inc., which has received consultancy fees from Novartis Pharmaceuticals Corporation. GJ, SB, and LC are employees of Novartis Pharmaceuticals Corporation and own stocks/options. JME peer reviewers on this manuscript have no relevant financial or other relationships to disclose.

Previous presentation

A synopsis of the current research was presented in poster format at the American Society of Hematology annual meeting, which took place in San Diego, CA during December 3–6, 2015, and at the Academy of Managed Care Pharmacy annual meeting in San Francisco, CA on April 19–22, 2016.

Acknowledgments

Medical writing assistance was provided by Shelley Batts, PhD, an employee of Analysis Group, Inc., ultimately paid by the sponsor. The authors thank Ankur Khare and Benjamin Cohen for technical review of the CEA model.