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Out-of-Pocket Costs for Tyrosine Kinase Inhibitors and Patient Outcomes in EGFR- and ALK-Positive Advanced Non–Small-Cell Lung Cancer
Abstract
We investigated the association of out-of-pocket (OOP) costs for tyrosine kinase inhibitors (TKIs) with overall survival (OS) in epidermal growth factor receptor (EGFR)- and anaplastic lymphoma kinase (ALK)-positive advanced non–small-cell lung cancer (NSCLC). We secondarily investigated associations of TKI OOP costs with TKI adherence, duration of therapy (DOT), and TKI discontinuation.
We used the Hutchinson Institute for Cancer Outcomes Research registry-claims database to identify patients with stage IV EGFR- or ALK-positive NSCLC; ≥ 1 claims for EGFR or ALK TKIs; and ≥ 3-month survival from TKI initiation. We estimated the average monthly TKI OOP costs per patient up to 3 months from TKI initiation, categorizing patients into quartiles of TKI OOP costs (Q1 < Q2 < Q3 < Q4). We conducted landmark analysis at 3 months from TKI initiation to compare Q1-3 v Q4 TKI OOP costs with respect to OS, TKI DOT, TKI adherence, and TKI discontinuation.
Seventy-eight and twenty-seven patients comprised the Q1-3 and Q4 groups, respectively. Median monthly TKI OOP costs were $1,431 (Q1-3) v $2,888 (Q4). Compared with Q1-3, Q4 patients had inferior OS (adjusted hazard ratio [HR], 1.85; [95% CI, 1.11 to 3.10], similar TKI DOT (adjusted HR, 1.06; 95% CI, 0.53 to 2.15), decreased TKI adherence (adjusted odds ratio [OR], 0.28; 95% CI, 0.10 to 0.76), and higher TKI discontinuation rate (adjusted OR, 8.75; 95% CI, 2.59 to 29.52).
Oral tyrosine kinase inhibitors (TKIs) improve clinical outcomes for patients with advanced non–small-cell lung cancer (NSCLC) whose tumors harbor epidermal growth factor receptor (EGFR) or anaplastic lymphoma kinase (ALK) mutations.1 From the payers' perspective, EGFR and ALK TKIs may be considered cost-effective.2 However, the high prices of TKIs can result in elevated out-of-pocket (OOP) costs to patients whose insurance plans impose high cost-sharing policies for oral drugs.3,4 In 2019, Medicare part D beneficiaries were responsible for $7,800 in annual OOP costs for erlotinib.5 In 2011, commercially insured patients paid $198 per month OOP for oral targeted therapies.6 When TKI OOP costs become a financial burden to patients, the likelihood of drug nonadherence increases.7,8 Patient financial burden is associated with poor survival and quality of life outcomes, a phenomenon known as financial toxicity.9-12 Accordingly, we hypothesized that higher patient OOP costs for TKIs (TKI OOP costs) are associated with reduced overall survival (OS) because of lower TKI adherence and a higher likelihood of TKI discontinuation for Medicare and/or commercially insured patients with advanced EGFR- and ALK-positive NSCLC.
We conducted a retrospective cohort study leveraging the Hutchinson Institute for Cancer Outcomes Research database, which provides patient-level data from the Cancer Surveillance System (CSS) registry linked to claims from Medicare and commercial (Regence Blue Shield and Premera Blue Cross) insurance plans.13 The CSS registry represents the SEER program in Washington State, providing data on tumor and sociodemographic characteristics, and vital status derived from the Washington State Department of Health.14 Insurance claims provide longitudinal information on resource utilization, including reimbursements for intravenous and oral antineoplastic drugs. The Fred Hutchinson Institutional Review Board has reviewed and approved the study protocol.
After identifying patients with a diagnosis of nonsquamous NSCLC between January 1, 2010, and December 31, 2015, we selected those whose tumors tested positive for sensitizing EGFR or ALK mutations by applying natural language processing algorithms on CSS pathology reports followed by manual confirmation of positive genetic test results.15 Among patients identified with EGFR- or ALK-positive NSCLC, eligibility criteria were as follows (Data Supplement, online only): stage IV at diagnosis; 12 months of continuous insurance enrollment prediagnosis and postdiagnosis; ≥ 1 pharmacy claims for EGFR or ALK TKIs that were or became commercially available during the observation period (EGFR: erlotinib, gefitinib, afatinib, and osimertinib; ALK: crizotinib, ceritinib, alectinib, and brigatinib); and survival ≥ 3 months from the first TKI claim date (TKI initiation). All Medicare patients had part D and included those with fee for service, additional insurance from Premera or Regence (but no other commercial plans or health maintenance organizations), Medicare-Medicaid dual eligibles, and Medicare patients meeting other criteria for federal low-income subsidy (LIS).4 Patients with Medicaid insurance alone were ineligible.
We assessed all EGFR and ALK TKI pharmacy claims incurred in the observation period. We also extracted age at diagnosis, sex, National Cancer Institute comorbidity index, year of diagnosis, urban status, Census-tract household income, Area Deprivation Index, eligibility for federal LIS, insurance type, and receipt of any cytotoxic chemotherapy or programmed cell death 1 (PD-1) or programmed cell death ligand 1 (PD-L1) checkpoint inhibitors that were or became approved by the US Food and Drug Administration during the study observation period.16-19 We followed patients from diagnosis to death, censoring those who were alive at the last follow-up date on December 31, 2017.
We estimated patients' TKI OOP costs by calculating patients' financial share for the first prescribed TKI, including drug deductibles, co-payments, and co-sharing costs. To calculate patients' financial share for TKIs, we subtracted the amount reimbursed from the maximum amount allowed by the insurance for TKI drug supplies, following published methodology.7 We then normalized TKI OOP costs to 30-day drug supplies to estimate the average monthly TKI OOP costs. For example, if a pharmacy claim covered 60 days of a TKI, we calculated patients' OOP costs and divided the result by two to estimate the average 30-day (or monthly) TKI cost. We estimated average monthly TKI OOP costs over the first 3 months of therapy. For patients who discontinued the TKI before 3 months, we calculated the average monthly TKI OOP costs up to the last TKI claim assuming a minimum of 1-month TKI supply. We categorized patients in quartiles of monthly TKI OOP costs, defining those in the lower three quartiles as controls (Q1-3) and those in the fourth highest quartile (Q4) as exposed. We adjusted costs to 2017 US dollars using the Consumer Price Index.
Our primary outcome was OS. Secondary outcomes included TKI adherence, TKI duration of therapy (DOT), and TKI discontinuation rates at 3 months. To allow the inference of causality between average monthly TKI OOP costs up to 3 months from TKI initiation with the outcome measures, we performed landmark analyses starting after 3 months from the date of TKI initiation. We measured OS from the 3-month landmark to death or censoring.
We calculated medication possession ratios (MPRs) after the 3-month landmark as a proxy of TKI adherence.20 The MPR measures consisted of the total number of days supplied by all prescriptions for the first TKI divided by the total number of days between the date of the first TKI fill and date of the last refill of the same TKI plus the number of days included in that last refill.8 We defined patients as adherent if they had an MPR of ≥ 0.8 for their first TKI according to the published literature.7,8,21,22 We assumed that patients were nonadherent if they had an MPR of <0.8 after the 3-month landmark or if they discontinued the first TKI before 3 months from TKI initiation.
We defined the date of TKI discontinuation as the last day of the last refill period that was followed by a minimum of a 60-day gap without further prescriptions for that TKI.7,8 We measured TKI DOT from the 3-month landmark to TKI discontinuation, death, or censoring, whichever occurred first. For patients who discontinued their first TKI prior to the 3-month landmark, we assigned a TKI DOT of 0 months.
We defined TKI discontinuation rates at 3 months as the proportion of patients who discontinued their first TKI within the first 3 months from TKI initiation.
We used multivariate Cox proportional hazard models to test associations of the average monthly TKI OOP costs (Q1-3 v Q4) with (1) OS and (2) TKI DOT starting after the 3-month landmark. To reduce the confounding effects of patient characteristics that could be associated with TKI OOP costs and OS, we adjusted the survival models for age, sex, insurance type (Medicare v commercial), mutation type (EGFR v ALK), number of weeks from the diagnosis of stage IV NSCLC to TKI initiation, and receipt of chemotherapy or PD-1/PD-L1 checkpoint inhibitors at any time. For TKI DOT, we adjusted the models for age, sex, insurance type, and mutation type.
We used multivariate logistic regression models to test associations of TKI OOP costs with (1) TKI adherence after the 3-month landmark and (2) TKI discontinuation within the first 3 months from initiation. The dependent variables were the probability of being TKI adherent after the 3-month landmark and the probability of discontinuing the TKI within the first 3 months from initiation, respectively. The independent variable of interest was TKI OOP costs (Q1-3 v Q4) in both models. We adjusted the models for age, sex, insurance, and mutation type.
Given the differences in patient characteristics and TKI OOP costs between Medicare and commercially insured individuals, we repeated all analyses stratifying patients by insurance type (Medicare v commercial) after recalculating insurance-specific quartiles of TKI OOP costs. Because of small patient samples, subgroup analyses were unadjusted.
We applied an unadjusted Cox regression model to assess the effect of TKI OOP costs on OS in the subset of patients who did not qualify for federal LIS. We used unadjusted logistic and Cox models to test the associations of TKI OOP costs with TKI adherence and DOT after the 3-month landmark in a subset of patients who remained on TKI therapy at the 3-month landmark. We recalculated the quartiles of TKI OOP costs for each respective patient subsample used for sensitivity analyses.
We defined P values < .05 as statistically significant.
Of 105 eligible patients, 78 and 27 comprised Q1-3 and Q4 of average monthly TKI OOP costs, respectively (Table 1). Compared with Q1-3, Q4 patients were older, resided in areas of lower median household income, were more likely to have Medicare insurance and to be eligible for federal LIS, and less likely to receive chemotherapy or immunotherapy. Median monthly TKI OOP costs over the first 3 months from TKI initiation were $1,431 and $2,888 for Q1-3 v Q4 groups, respectively. Among 67 Medicare beneficiaries, patient characteristics were more similarly distributed between Q1-3 (n = 50) and Q4 (n = 17) subgroups, although the time interval from diagnosis to TKI initiation was shorter for Medicare Q1-3 v Q4 patients (median of 7.7 v 13.1 weeks). Median TKI OOP costs were $1,618 v $4,084 for Medicare Q1-3 v Q4, respectively. Among 38 commercially insured patients, those in Q4 (n = 10) were older, more likely to be female, and more likely to reside in areas of greater material deprivation and lower household income, compared with Q1-3 (n = 28) patients. Median TKI OOP costs were $0 v $1,618 for commercially insured Q1-3 v Q4 patients.
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With a median follow-up time of 23.8 months, 92 (87.6%) patients died. After the 3-month landmark, the median OS was 22.4 months (95% CI, 16.6 to 26.0) v 9.1 months (95% CI, 3.0 to 19.2) for the Q1-3 v Q4 groups, respectively. In multivariate analysis using Q1-3 as reference, Q4 patients had an adjusted hazard ratio (HR) for death of 1.85 (95% CI, 1.11 to 3.10; P = .019; Fig 1A; Data Supplement). Using Q1 as reference, we did not observe a statistically significant increase in mortality for each incremental quartile of TKI OOP costs (adjusted HR, 1.16; 95% CI, 0.90 to 1.49; P = .241).
Fig 1. Landmark OS analysis starting at 3 months from TKI initiation, by quartiles of TKI OOP costs. Overall survival after the 3-month landmark (ie, starting at 3 months from TKI initiation). Quartiles 1-3 v quartile 4 refer to the lower 3 quartiles v fourth highest quartile of monthly TKI OOP costs calculated over the first 3 months from TKI initiation. (A) All patients: Cox model adjusted for age at diagnosis, sex, insurance type at the month of TKI initiation (Medicare v commercial), mutation type (EGFR v ALK), receipt of intravenous chemotherapy or immune checkpoint inhibitors at any time, and time interval from diagnosis date to date of the first TKI claim. (B) Medicare patients: Cox model is unadjusted because of smaller sample size. (C) Commercially insured patients: Cox model is unadjusted because of smaller sample size. Quartile group rows refer to the number of patients at risk for death at each time interval. Numbers in parentheses correspond to patients who died in each time interval. Ticks in the Kaplan-Meier curves refer to censored patients. ALK, anaplastic lymphoma kinase; EGFR, epidermal growth factor receptor; HR, hazard ratio; OOP, out-of-pocket; OS, overall survival; TKI, tyrosine kinase inhibitor.
Among Medicare beneficiaries, 60 (89.6%) died. The median OS after the 3-month landmark was 23.8 months (95% CI, 15.2 to 29.2) v 6.2 months (2.0 to 16.0) for Medicare-specific Q1-3 v Q4 patients, respectively. Q4 patients had an unadjusted HR for death of 1.71 (95% CI, 0.94 to 3.11; P = .078; Fig 1B).
Among commercially insured patients, 32 (84.2%) died. The median OS after the 3-month landmark was 19.1 months (95% CI, 13.7 to 25.7) v 24.8 months (95% CI, 4.8 to not reached) for Q1-3 v Q4, respectively. The Q4 subgroup had an unadjusted HR for death of 0.64 (95% CI, 0.29 to 1.45; P = .289; Fig 1C).
Ninety-four (89.5%) patients discontinued the first TKI in the observation period. Compared with Q1-3, Q4 patients had similar TKI DOT after the 3-month landmark (median DOT of 6.0 v 7.0 months for Q1-3 v Q4; adjusted HR for TKI discontinuation = 1.06; 95% CI, 0.53 to 2.15; P = .862). Among Medicare beneficiaries and commercially insured subgroups, TKI DOT was not statistically different between Q1-3 and Q4 patients (Medicare: median DOT of 6.0 v 7.0 months for Q1-3 v Q4; unadjusted HR, 1.60; 95% CI, 0.70 to 3.67; P = .270; commercial: median DOT of 9.0 v 5.0 months for Q1-3 v Q4; unadjusted HR, 0.87; 95% CI, 0.35 to 2.16; P = .768), respectively (Table 2).
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After the 3-month landmark, 60 (57.1%) patients remained TKI adherent. The probability of being TKI adherent was 65.4% v 33.3% for the Q1-3 v Q4 patients, respectively (adjusted odds ratio [OR] for adherence, 0.28; 95% CI, 0.10 to 0.76; P = .012). Among Medicare beneficiaries, Q4 patients were less likely to be adherent to TKIs compared with Q1-3 patients (probability of being TKI adherent of 60.0% v 29.4% for Q1-3 v Q4; unadjusted OR, 0.28; 95% CI, 0.08 to 0.91; P = .034). Among commercially insured patients, TKI adherence was similar between the Q1-3 v Q4 subgroups (64.3% v 70% for Q1-3 v Q4; unadjusted OR, 1.30; 95% CI, 0.27 to 6.16; P = .744; Table 2).
Twenty-one (20.0%) patients discontinued TKIs within 3 months from TKI initiation: eight (10.3%) in the Q1-3 group v 13 (48.2%) in the Q4 group (adjusted OR for TKI discontinuation, 8.75; 95% CI, 2.59 to 29.52; P < .001). Among Medicare beneficiaries, 8 (16.0%) and 8 (47.1%) patients in the Q1-3 and Q4 subgroups discontinued TKIs, respectively (unadjusted OR, 4.67; 95% CI, 1.38 to 15.74; P = .013). Among the commercially insured, 3 (10.7%) and 2 (20.0%) patients discontinued TKIs in the Q1-3 and Q4 subgroups, respectively (unadjusted OR, 2.08; 95% CI, 0.29 to 14.77; P = .463).
Among the 87 patients who were not eligible for federal LIS, 65 and 22 comprised the Q1-3 and Q4 subgroups, respectively. The median (IQR) monthly TKI OOP costs were $1,402 ($1,506) and $2,857 ($1,641) for Q1-3 and Q4 patients, respectively. After the 3-month landmark, the median OS was 21.5 v 10.7 months for Q1-3 v Q4, respectively (unadjusted HR death, 1.88; 95% CI, 1.09 to 3.23; P = .023).
Among the 91 patients who remained on the first TKI after 3 months from TKI initiation, 68 and 23 comprised the Q1-3 and Q4 groups. The median (IQR) monthly TKI OOP costs were $1,420 ($1,484) and $2,585 ($1,864) for Q1-3 and Q4 patients, respectively. After the 3-month landmark, the median TKI DOT was 6.0 v 7.0 months for Q1-3 v Q4 subgroups, respectively (unadjusted HR for TKI discontinuation = 1.22; 95% CI, 0.68 to 2.17; P = .501). The probability of being TKI adherent after the 3-month landmark was 72.1% and 52.2% for Q1-3 v Q4 patients, respectively (unadjusted OR, 0.42; 95% CI, 0.16 to 1.12; P = .084).
In this retrospective cohort study, we observed statistically and clinically significative associations between the highest quartile of average monthly TKI OOP costs with increased mortality, decreased TKI adherence, and a higher likelihood of TKI discontinuation within the first 3 months. The associations remained statistically significant after risk adjustment for patient confounding characteristics. DOT was not statistically different between Q1-3 and Q4 groups. The association of TKI OOP costs with survival was significant only for the highest OOP cost quartile compared with the lower three quartiles; we did not observe a significant trend of shorter OS with each increasing quartile of TKI OOP costs. Overall, our results suggest that patients incurring very high TKI OOP costs possibly are at higher risk of death, and that lower TKI adherence and early TKI discontinuation at least in part mediate the associations of higher TKI OOP costs with inferior survival.
The Medicare subgroup drove all the observed associations of higher TKI OOP costs with decreased survival, lower TKI adherence, and an increased likelihood of early TKI discontinuation. We did not observe these associations in the small subgroup of commercially insured patients. Compared with Medicare, commercially insured patients incurred lower TKI OOP costs and probably had access to financial assistance programs from drug manufacturers, whereas federal legislation prohibits Medicare beneficiaries from applying for such assistance. Further studies are necessary to elucidate the impact of insurance type on the association of TKI OOP costs with patient outcomes.
We defined patients as TKI nonadherent if they had an MPR of < 0.8 after the 3-month landmark or discontinued the TKI within 3 months from initiation. Since a higher proportion of Q4 patients discontinued their TKIs within 3 months from initiation compared with Q1-3 patients, the association of the higher quartile TKI OOP costs with TKI nonadherence after the 3-month landmark could have been inflated by a higher proportion of early TKI discontinuation in the Q4 group. In sensitivity analysis, we observed a statistical trend toward lower TKI adherence after the 3-month landmark in the Q4 group among patients who were still on the same TKI 3 months after initiation (P = .084). Although not statistically significant, the trend suggests that patients in the highest quartile of TKI OOP costs remain at an increased risk of TKI nonadherence even if they manage to continue on TKI therapy after initial exposure to high TKI OOP costs.
Our findings confirm previous observations that high cost-sharing for TKIs is associated with decreased TKI adherence in lung and other cancers.7,8,21 In addition, our study raises the potential concern that patients' inability to afford expensive medicines ultimately undermines the clinical benefits conferred by TKIs. As mounting evidence links expensive targeted therapies to financial toxicity, health policy makers face increasing demands to revise drug pricing policies and reduce patients' financial burden of cancer care.9,23-29
Several limitations apply to the study. Given the observational design, the analysis is subject to selection bias. Imbalances in age, insurance, and measures of socioeconomic status were evident between the Q4 and Q1-3 groups. Although we adjusted comparisons for those differences through multivariate analyses, imbalances in nonmeasured patient characteristics could still have introduced selection bias in our analysis. The study sample is small and restricted to the Washington State, limiting the generalizability of results. We estimated OOP costs from pharmacy claims and could not account for the receipt of copay assistance programs, limiting accurate measurement of TKI OOP costs at the time of drug purchase. Pharmacy claims do not provide the reasons for TKI discontinuation; some patients could have discontinued TKIs because of early tumor progression or drug intolerance as opposed to the financial burden from TKIs. Future studies should link electronic medical records to claims data to evaluate the association of higher TKI OOP costs with lower TKI adherence, and whether lower TKI adherence mediates the effect of TKI OOP costs on progression-free survival and OS.
In summary, this preliminary observational study showed associations of higher TKI OOP costs with decreased TKI adherence, early TKI discontinuation, and inferior survival in patients with stage IV EGFR- and ALK-positive NSCLC. If confirmed in larger studies using nationally representative databases, our findings may support reforms in drug coverage policies for oral TKIs.
Bernardo H.L. Goulart received funding support from the National Cancer Institute research grant P30 CA015704 to conduct this study.
Conception and design: Bernardo H.L. Goulart, Joseph M. Unger, Scott D. Ramsey
Collection and assembly of data: Bernardo H.L. Goulart, Shasank Chennupati, Catherine R. Fedorenko, Scott D. Ramsey
Data analysis and interpretation: All authors
Manuscript writing: All authors
Final approval of manuscript: All authors
Accountable for all aspects of the work: All authors
The following represents disclosure information provided by authors of this manuscript. All relationships are considered compensated unless otherwise noted. Relationships are self-held unless noted. I =Immediate Family Member, Inst = My Institution. Relationships may not relate to the subject matter of this manuscript. For more information about ASCO’s conflict of interest policy, please refer to www.asco.org/rwc or ascopubs.org/op/authors/author-center.
Open Payments is a public database containing information reported by companies about payments made to US-licensed physicians (Open Payments).
Scott D. Ramsey
Employment: Flatiron Health
Consulting or Advisory Role: Kite Pharma, Bayer Corporation, Genentech, Bristol-Myers Squibb, AstraZeneca, Merck & Company, Inc., Epigenomics, GRAIL
Research Funding: Bayer Corporation, Bristol-Myers Squibb, Microsoft Corporation
Travel, Accommodations, Expenses: Bayer Schering Pharma, Bristol-Myers Squibb, Flatiron Health, Bayer, GRAIL
No potential conflicts of interest were reported.
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