Real-world total cost of care by line of therapy in relapsed/refractory diffuse large B-cell lymphoma.

AIMS: There are multiple recently approved treatments and a lack of clear standard-of-care therapies for relapsed/refractory (R/R) diffuse large B-cell lymphoma (DLBCL). While total cost of care (TCC) by the number of lines of therapy (LoTs) has been evaluated, more recent cost estimates using real-world data are needed. This analysis assessed real-world TCC of R/R DLBCL therapies by LoT using the IQVIA PharMetrics Plus database (1 January 2015-31 December 2021), in US patients aged ≥18 years treated with rituximab plus cyclophosphamide, doxorubicin, vincristine, and prednisone (R-CHOP) or an R-CHOP-like regimen as first-line therapy. METHODS: Treatment costs and resources in the R/R setting were assessed by LoT. A sensitivity analysis identified any potential confounding of the results caused by the impact of the COVID-19 pandemic on healthcare utilization and costs. Overall, 310 patients receiving a second- or later-line treatment were included; baseline characteristics were similar across LoTs. Inpatient costs represented the highest percentage of total costs, followed by outpatient and pharmacy costs. RESULTS: Mean TCC per-patient-per-month generally increased by LoT ($40,604, $48,630, and $59,499 for second-, third- and fourth-line treatments, respectively). Costs were highest for fourth-line treatment for all healthcare resource utilization categories. Sensitivity analysis findings were consistent with the overall analysis, indicating results were not confounded by the COVID-19 pandemic. LIMITATIONS: There was potential misclassification of LoT; claims data were processed through an algorithm, possibly introducing errors. A low number of patients met the inclusion criteria. Patients who switched insurance plans, had insurance terminated, or whose enrollment period met the end of data availability may have had truncated follow-up, potentially resulting in underestimated costs. CONCLUSION: Total healthcare costs increased with each additional LoT in the R/R DLBCL setting. Further improvements of first-line treatments that reduce the need for subsequent LoTs would potentially lessen the economic burden of DLBCL.

Validation of an Updated Algorithm to Identify Patients With Incident Non-Small Cell Lung Cancer in Administrative Claims Databases.

PURPOSE: Real-world lung cancer data in administrative claims databases often lack staging information and specific diagnostic codes for lung cancer histology subtypes. This study updates and validates Turner's 2017 treatment-based algorithm using more recent claims and electronic health record (EHR) data. METHODS: This study used Optum's deidentified Market Clarity Data of linked medical and pharmacy claims with EHR data. Eligible patients had an incident lung cancer diagnosis (January 2014-December 2020) and ≥one valid histology code for lung cancer 30 days before to 60 days after diagnosis. Histology and stage information from the EHR were used to evaluate the sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV). We evaluated the Turner algorithm using cohort 1 patients diagnosed between June 2014 and October 2015 (step 1) and between November 2015 and December 2020 after approval of immunotherapies (step 2). Next, we evaluated cohort 2 patients diagnosed between November 2015 and December 2020 using an updated algorithm incorporating the latest US treatment guidelines (step 3), and compared the results for cohort 2 (Turner algorithm, step 2 patients). Furthermore, an algorithm to determine early NSCLC (eNSCLC; stage I-III) versus metastatic or advanced/metastatic non-small cell lung cancer (stage IV) was evaluated among patients with available histology and stage information. RESULTS: A total of 5,012 patients were included (cohort 1, step 1: n = 406; cohort 1, step 2: n = 2,573; cohort 2, step 3: n = 2,744). The updated algorithm showed improved performance relative to the previous Turner algorithm for sensitivity (0.920-0.932), specificity (0.865-0.923), PPV (0.976-0.988), and NPV (0.640-0.673). The eNSCLC algorithm showed high specificity (0.874) and relatively low sensitivity (0.539). CONCLUSION: An updated treatment-based algorithm identifying patients with incident NSCLC was validated using EHR data and distinguished lung cancer subtypes in claims databases when EHR data were not available.

Racial and Ethnic Inequities at the Practice and Physician Levels in Timely Next-Generation Sequencing for Patients With Advanced Non-Small-Cell Lung Cancer Treated in the US Community Setting.

PURPOSE: Racial/ethnic inequities in next-generation sequencing (NGS) were examined for patients with advanced non-small-cell lung cancer (aNSCLC) at the practice and physician levels to inform policies to improve equitable quality of care. METHODS: This retrospective study used a nationwide electronic health record-derived deidentified database for patients with aNSCLC diagnosed between April 2018 and March 2022 in the community setting. Timely NGS was an NGS result between initial diagnosis and ≤60 days after advanced diagnosis. We studied how inequities were driven by (1) non-Latinx Black (Black) and Latinx patient under-representation at high testing practices versus (2) Black and Latinx patients being tested at lower rates than non-Latinx White (White) patients, even at the same practice. We defined these two concepts as across inequity and within inequity, respectively, with total inequity as their summation. Mean percentage point inequities were estimated using a Bayesian approach. RESULTS: A total of 12,045 patients (9,981 White; 1,528 Black; 536 Latinx) met study criteria. At the practice level, versus White patients, the mean percentage point difference in NGS testing total inequity was 7.49 for Black and 8.26 for Latinx. Within- and across-practice inequities contributed to total inequity in NGS testing for Black (48% v 52%) and Latinx patients (60% v 40%). At the physician level, versus White patients, the mean percentage point difference in total inequity was 7.73 for Black and 8.81 for Latinx patients. Within- versus across-physician inequities contributed to total inequity for Black and Latinx patients (77% v 23% and 67% v 33%). CONCLUSION: Within-practice, across-practice, and across-physician inequities were main contributors to total inequity in NGS testing, requiring a suite of interventions to effectively address inequities.

Treatment Patterns by Race and Ethnicity in Newly Diagnosed Persons with Multiple Sclerosis.

BACKGROUND: Non-Hispanic Black and Hispanic persons with MS (pwMS) are more likely to experience rapid disease progression and severe disability than non-Hispanic White pwMS; however, it is unknown how the initiation of high-efficacy disease-modifying therapies (DMTs) differs by race/ethnicity. This real-world study describes DMT treatment patterns in newly diagnosed pwMS in the United States (US) overall and by race/ethnicity. METHODS: This retrospective analysis used the US Optum Market Clarity claims/electronic health records database (January 2015-September 2020). pwMS who were first diagnosed in 2016 or later and initiated any DMT in the two years following diagnosis were included. Continuous enrollment in the claims data for ≥ 12 months before and ≥ 24 months after diagnosis was required. Treatment patterns 2 years after diagnosis were analyzed descriptively overall and by race/ethnicity. RESULTS: The sample included 682 newly diagnosed and treated pwMS (non-Hispanic Black, n = 99; non-Hispanic White, n = 479; Hispanic, n = 35; other/unknown race/ethnicity, n = 69). The mean time from diagnosis to DMT initiation was 4.9 months in all pwMS. Glatiramer acetate and dimethyl fumarate were the most common first-line DMTs in non-Hispanic Black (28% and 20% respectively) and Hispanic pwMS (31%, 29%); however, glatiramer acetate and ocrelizumab were the most common in non-Hispanic White pwMS (33%, 18%). Use of first-line high-efficacy DMTs was limited across all race/ethnicity subgroups (11-29%), but uptake increased in non-Hispanic Black and White pwMS over the study period. CONCLUSION: Use of high-efficacy DMTs was low across all race/ethnicity subgroups of newly diagnosed pwMS in the US, including populations at a greater risk of experiencing rapid disease progression and severe disability.

Estimating the US Baseline Distribution of Health Inequalities Across Race, Ethnicity, and Geography for Equity-Informative Cost-Effectiveness Analysis.

OBJECTIVES: Information on how life expectancy, disability-free life expectancy, and quality-adjusted life expectancy varies across equity-relevant subgroups is required to conduct distributional cost-effectiveness analysis. These summary measures are not comprehensively available in the United States, given limitations in nationally representative data across racial and ethnic groups. METHODS: Through linkage of US national survey data sets and use of Bayesian models to address missing and suppressed mortality data, we estimate health outcomes across 5 racial and ethnic subgroups (non-Hispanic American Indian or Alaska Native, non-Hispanic Asian and Pacific Islander, non-Hispanic black, non-Hispanic white, and Hispanic). Mortality, disability, and social determinant of health data were combined to estimate sex- and age-based outcomes for equity-relevant subgroups based on race and ethnicity, as well as county-level social vulnerability. RESULTS: Life expectancy, disability-free life expectancy, and quality-adjusted life expectancy at birth declined from 79.5, 69.4, and 64.3 years, respectively, among the 20% least socially vulnerable (best-off) counties to 76.8, 63.6, and 61.1 years, respectively, among the 20% most socially vulnerable (worst-off) counties. Considering differences across racial and ethnic subgroups, as well as geography, gaps between the best-off (Asian and Pacific Islander; 20% least socially vulnerable counties) and worst-off (American Indian/Alaska Native; 20% most socially vulnerable counties) subgroups were large (17.6 life-years, 20.9 disability-free life-years, and 18.0 quality-adjusted life-years) and increased with age. CONCLUSIONS: Existing disparities in health across geographies and racial and ethnic subgroups may lead to distributional differences in the impact of health interventions. Data from this study support routine estimation of equity effects in healthcare decision making, including distributional cost-effectiveness analysis.

The Impact of Funding Inpatient Treatments for COVID-19 on Health Equity in the United States: A Distributional Cost-Effectiveness Analysis.

OBJECTIVES: We conducted a distributional cost-effectiveness analysis (DCEA) to evaluate how Medicare funding of inpatient COVID-19 treatments affected health equity in the United States. METHODS: A DCEA, based on an existing cost-effectiveness analysis model, was conducted from the perspective of a single US payer, Medicare. The US population was divided based on race and ethnicity (Hispanic, non-Hispanic black, and non-Hispanic white) and county-level social vulnerability index (5 quintile groups) into 15 equity-relevant subgroups. The baseline distribution of quality-adjusted life expectancy was estimated across the equity subgroups. Opportunity costs were estimated by converting total spend on COVID-19 inpatient treatments into health losses, expressed as quality-adjusted life-years (QALYs), using base-case assumptions of an opportunity cost threshold of $150 000 per QALY gained and an equal distribution of opportunity costs across equity-relevant subgroups. RESULTS: More socially vulnerable populations received larger per capita health benefits due to higher COVID-19 incidence and baseline in-hospital mortality. The total direct medical cost of inpatient COVID-19 interventions in the United States in 2020 was estimated at $25.83 billion with an estimated net benefit of 735 569 QALYs after adjusting for opportunity costs. Funding inpatient COVID-19 treatment reduced the population-level burden of health inequality by 0.234%. Conclusions remained robust across scenario and sensitivity analyses. CONCLUSIONS: To the best of our knowledge, this is the first DCEA to quantify the equity implications of funding COVID-19 treatments in the United States. Medicare funding of COVID-19 treatments in the United States could improve overall health while reducing existing health inequalities.

The Association Between Persistence and Adherence to Disease-Modifying Therapies and Healthcare Resource Utilization and Costs in Patients With Multiple Sclerosis.

Background: Persistence and adherence to disease-modifying therapies (DMTs) affects treatment efficacy and economic outcomes, both of which contribute to overall patient disease burden. Current literature suggests that patients with multiple sclerosis (MS) who adhere to DMT for 12 months have fewer relapses and reduced MS-related healthcare resource utilization (HCRU) and medical costs than nonadherent patients. Objective: To expand on previous research by estimating the association of persistence and adherence with all-cause and MS-related HCRU and non-DMT costs of patients with MS across 12 and 24 months of therapy use. Methods: This study was a retrospective analysis of adult patients with MS in the IBM MarketScan Commercial and Medicare Supplemental databases using claims data between April 2016 and December 2019. The index date was defined as the initiation of the DMT. Patients were required to have ≥12 months' continuous enrollment pre-index and ≥12 or ≥24 months' continuous enrollment post-index. Persistence was defined as no gap in DMT supply for ≥60 days within the post-index period or switch to another DMT. Adherence was calculated using the proportion of days covered (for this study, number of days covered by the DMT was 365 or 730 days), with ≥80% proportion of days covered considered adherent. Multivariable analyses were conducted to estimate total and individual components of non-DMT costs by persistence and adherence while controlling for baseline differences. Results: Patients who were persistent with medication for 12 months showed a reduction in mean total non-DMT medical costs of $10 022 compared with nonpersistent patients; these savings nearly doubled ($19 230) after 24 months of persistence. A similar pattern was observed for adherent vs nonadherent patients (reduction in costs at 12 months, $8543; at 24 months, $16 091). The largest reduction in all-cause HCRU costs was observed in the inpatient setting, while the largest reduction in MS-related costs was observed in the outpatient setting. Discussion: Patients with MS who were persistent and adherent to medication had substantially lower all-cause and MS-related non-DMT medical costs compared with those who were nonpersistent or nonadherent. Conclusions: These findings further support the importance of persistence and adherence to DMTs in patients with MS.

Impact of Immune Checkpoint Inhibitors on COVID-19 Severity in Patients with Cancer.

BACKGROUND: Amid continued uncertainty about the management of cancer patients during the pandemic, this study sought to obtain real-world data on the use of immune checkpoint inhibitors (ICIs) before COVID-19 diagnosis and its association with severity and survival outcomes in cancer patients who contracted COVID-19. METHODS: Cancer patients diagnosed with COVID-19 were identified from a large electronic health record database; those treated with ICIs before COVID-19+ diagnosis were matched in a 1:2 ratio to those not treated with ICIs, using a 2-step matching procedure. A descriptive analysis examined the difference in COVID-19 mortality (30-day and overall) and severity outcomes between the 2 cohorts, and overall survival was compared. RESULTS: Among 17 545 adults ≥18 years with cancer who tested positive for COVID-19 between February 20, 2020, and January 28, 2021, in the US, 228 ICI-treated patients were matched to 456 non-ICI-treated patients, comprising the 2 study cohorts. Clinical characteristics differed significantly between the 2 cohorts before matching, with metastatic disease, lung cancer, a history of smoking, and the presence of pulmonary comorbidities being more common in the ICI-treated cohort; after matching, the 2 cohorts were similar. There were no significant differences between the ICI-treated and non-ICI-treated cohorts for 30-day mortality (12.7% vs. 14.9%, P = .235), overall mortality (22.4% vs. 22.4%, P = 1.000), hospitalization (38.6% vs. 39.0%, P = .912), or emergency department visits (16.7% vs. 14.7%, P = .500). Overall survival was similar between the 2 cohorts. CONCLUSION: This analysis adds to the clinical evidence base that use of ICIs before SARS-CoV-2 infection does not affect COVID-19 severity or survival outcomes, supporting the continued use of ICIs in cancer patients during the pandemic.

Adherence to and Persistence with Disease-Modifying Therapies for Multiple Sclerosis Over 24 Months: A Retrospective Claims Analysis.

INTRODUCTION: We sought to assess adherence to and persistence with ocrelizumab (OCR) compared with other disease-modifying treatments (DMTs), by route of administration (RoA), for multiple sclerosis (MS) after 24 months in the United States. METHODS: This retrospective claims analysis of MS patients initiating a new DMT was conducted using the IBM MarketScan Commercial and Medicare Supplemental databases between April 2016 and December 2019. Continuous enrollment of ≥ 12 months before and up to 24 months after initiating the index DMT was required. Adherence was assessed based on proportion of days covered (PDC) in the follow-up period with values ≥ 80% considered adherent. Persistence was defined as no evidence of switching to another DMT or no gap ≥ 60 days in DMT coverage. RESULTS: A total of 1710 patients with ≥ 24 months of follow-up (OCR, n = 524; oral, n = 701; injectable, n = 365; other intravenous [IV], n = 120) were included. Patients initiating OCR had higher adherence (80% vs. 55%, 35%, and 54% for oral, injectable, and other IV, respectively) and persistence (75% vs. 54%, 33%, and 55%, respectively) at 24 months. Relative risks (RRs) of 24-month non-adherence for those initiating orals, injectables, and other IVs were 2.2 (95% CI, 1.7-2.9), 3.0 (95% CI, 2.2-4.0), and 2.2 (95% CI, 1.5-3.3), respectively, compared to those initiating OCR. Similarly, patients receiving orals, injectables, and other IVs had RR of 1.9 (95% CI, 1.4-2.4), 2.5 (95% CI, 1.9-3.4), and 1.8 (95% CI, 1.2-2.6) for 24-month discontinuation, respectively. Similar patterns were observed at 12 and 18 months. CONCLUSIONS: Patients initiating OCR in a real-world setting achieved higher rates of adherence and persistence at 24 months compared with those initiating other DMTs, consistent with published literature showing similar results at 12 and 18 months. Optimizing medication adherence and persistence is fundamental to MS care, so clinicians should consider all elements of DMTs that may improve compliance.

Trends in Use of Next-Generation Sequencing in Patients With Solid Tumors by Race and Ethnicity After Implementation of the Medicare National Coverage Determination.

Importance: In March 2018, Medicare issued a national coverage determination (NCD) for next-generation sequencing (NGS) to facilitate access to NGS testing among Medicare beneficiaries. It is unknown whether the NCD affected health equity issues for Medicare beneficiaries and the overall population. Objective: To examine the association between the Medicare NCD and NGS use by insurance types and race and ethnicity. Design, Setting, and Participants: A retrospective cohort analysis was conducted using electronic health record data derived from a real-world database. Data originated from approximately 280 cancer clinics (approximately 800 sites of care) in the US. Patients with advanced non-small cell lung cancer (aNSCLC), metastatic colorectal cancer (mCRC), metastatic breast cancer (mBC), or advanced melanoma diagnosed from January 1, 2011, through March 31, 2020, were included. Exposure: Pre- vs post-NCD period. Main Outcomes and Measures: Patients were classified by insurance type and race and ethnicity to examine patterns in NGS testing less than or equal to 60 days after diagnosis. Difference-in-differences models examined changes in average NGS testing in the pre- and post-NCD periods by race and ethnicity, and interrupted time-series analysis examined whether trends over time varied by insurance type and race and ethnicity. Results: Among 92 687 patients with aNSCLC, mCRC, mBC, or advanced melanoma, mean (SD) age was 66.6 (11.2) years, 51 582 (55.7%) were women, and 63 864 (68.9%) were Medicare beneficiaries. The largest racial and ethnic categories according to the database used and further classification were Black or African American (8605 [9.3%]) and non-Hispanic White (59 806 [64.5%]). Compared with Medicare beneficiaries, changes in pre- to post-NCD NGS testing trends were similar in commercially insured patients (odds ratio [OR], 1.03; 95% CI, 0.98-1.08; P = .25). Pre- to post-NCD NGS testing trends increased at a slower rate among patients in assistance programs (OR, 0.93; 95% CI, 0.87-0.99; P = .03) compared with Medicare beneficiaries. The rate of increase for patients receiving Medicaid was not statistically significantly different compared with those receiving Medicare (OR, 0.92; 95% CI, 0.84-1.01; P = .07). The NCD was not associated with statistically significant changes in NGS use trends by racial and ethnic groups within Medicare beneficiaries alone or across all insurance types. Compared with non-Hispanic White individuals, increases in average NGS use from the pre-NCD to post-NCD period were 14% lower (OR, 0.86; 95% CI, 0.74-0.99; P = .04) among African American and 23% lower (OR, 0.77; 95% CI, 0.62-0.96; P = .02) among Hispanic/Latino individuals; increases among Asian individuals and those with other races and ethnicities were similar. Conclusions and Relevance: The findings of this study suggest that expansion of Medicare-covered benefits may not occur equally across insurance types, thereby further widening or maintaining disparities in NGS testing. Additional efforts beyond coverage policies are needed to ensure equitable access to the benefits of precision medicine.

The costs of care from a US claims database in patients with neuromyelitis optica spectrum disorder.

BACKGROUND: Neuromyelitis optica spectrum disorder (NMOSD) is a rare autoimmune disease of the central nervous system that often leads to severe disability. Patients with highly active NMOSD have approximately a 10-times higher hospital inpatient admission rate compared with patients without NMOSD. Accurate assessments of the impact of NMOSD treatments on the burdens of illness require quantitative metrics of these burdens, including costs of care. METHODS: This study evaluated claims data from the IBM MarketScan Commercial and Medicare Supplemental Databases between 2014 and 2018. Patients were included based on inpatient or outpatient claims meeting criteria defined for NMOSD. Non-NMOSD controls were matched 5:1 to patients with NMOSD. Total costs of healthcare services in consumer price index-adjusted 2019 US dollars during the 1-year postindex follow-up period were calculated for patients and controls. RESULTS: Patients with NMOSD required more healthcare services and incurred significantly greater costs for inpatient hospitalizations (annual mean [SD] cost: $29,054 [$144,872] vs controls $1521 [$10,759]), outpatient services ($24,881 [$35,463] vs $4761 [$26,447]), and emergency department (ED) visits ($2400 [$7771] vs $408 [$2579]). Almost 12% of patients with NMOSD were further burdened with plasma exchange or intravenous immunoglobulin G treatments, costing an annual median (interquartile range) of $1684 ($566-$3817) and $24,353 ($5425-$42,975), respectively. CONCLUSIONS: Compared with controls, patients with NMOSD had significantly higher costs associated with hospitalizations, ED visits, and prescriptions. These results highlight the considerable economic burden of NMOSD, which may be favorably impacted by disease-modifying therapies that are regulatory-approved to be safe and effective.

Burden and cost of comorbidities in patients with neuromyelitis optica spectrum disorder.

BACKGROUND: Neuromyelitis optica spectrum disorder (NMOSD) is associated with various comorbidities, including non-autoimmune and autoimmune conditions. The burden and cost of illness for NMOSD are unclear, particularly in the context of comorbidities. METHODS: Claims data from IBM MarketScan Commercial and Medicare Supplemental Databases between 2014 and 2018 were analyzed. Patients with NMOSD were specified as having inpatient or outpatient claims for NMOSD diagnosis or specific NMOSD symptoms claims and no subsequent claims for multiple sclerosis (MS) or use of MS disease-modifying therapy (DMT). Continuous enrollment ≥ 6 months before and ≥ 1 year after the first claim (index date) was required for study inclusion. Total costs stratified by comorbidities within 12 months post-index date were calculated per patient and compared 1:5 with matched non-NMOSD controls. RESULTS: A total of 162 patients with NMOSD and 810 non-NMOSD controls were evaluated. A significantly higher proportion of NMOSD patients had comorbidities than non-NMOSD controls (66.7% vs 41.5%; P < 0.001). Concomitant autoimmune disease occurred in 19.1% vs 4.9% (P < 0.001) of patients with NMOSD vs non-NMOSD controls. NMOSD patients incurred significantly higher total median (interquartile range) healthcare costs per patient ($68,386.48 [$23,373.54-$160,862.70]) than matched non-NMOSD controls with autoimmune disease ($17,215.13 [$6715.48-$31,441.93]; P < 0.001) or patients with NMOSD without autoimmune comorbidity ($23,905.42 [$8632.82-$67,251.54]; P = 0.022). Similarly, patients with NMOSD and non-autoimmune comorbidities incurred higher median healthcare costs than matched controls. CONCLUSIONS: Patients with NMOSD experience significant disease burden and cost that are amplified by comorbidities. Effective therapies are needed, particularly for patients with concomitant autoimmune disease.

Healthcare Resource Use and Burden Associated with Influenza Transmission Among Household Members with a Primary Infection: Commercial Claims Data Analysis.

PURPOSE: To assess the burden of influenza transmission and care-seeking patterns over 3 influenza seasons among commercially insured households with a primary influenza infection. PATIENTS AND METHODS: This retrospective cohort study used commercial claims data from the US MarketScan® Commercial and Medicare Supplemental databases for the 2014, 2015, and 2016 influenza seasons. Patients with a billed diagnosis of influenza and with coverage for at least 1 household member under the same health plan policy were included. A secondary diagnosed case was defined as a diagnosis of influenza in a second household member occurring within 14 days of the index case in a household. RESULTS: Among 1,224,808 households with ≥2 members and a primary case of influenza, a secondary case of influenza was reported in 119,883 households (9.8%). A secondary diagnosed case of influenza occurred within 4 days of the primary diagnosis in 93,883 (78.3%) of those households. Both primary and secondary diagnosed influenza cases occurred most often among children (~60%). Household size was positively correlated to both the risk of a second case (6.4% of households with 2 or 3 members versus 12.6% of households with ≥4 members, P < 0.001) and the time to diagnosis of a second case (Spearman rank correlation coefficient = 0.09; P < 0.001). CONCLUSION: Claims data for 3 influenza seasons (2014, 2015, 2016) showed that intrahousehold transmission of influenza occurs in approximately 10% of households with a primary case and poses a higher burden on larger households. Intrahousehold transmission of influenza represents a large healthcare resource use burden, with an unmet need for interventions that limit transmission.

Association Between Medicare's National Coverage Determination and Utilization of Next-Generation Sequencing.

PURPOSE: In 2018, Medicare issued a national coverage determination (NCD) providing reimbursement for next-generation sequencing (NGS) tests for beneficiaries with advanced or metastatic cancer and no previous NGS testing. We examined the association between NCD implementation and NGS utilization trends in Medicare beneficiaries versus commercially insured patients. METHODS: This was a retrospective study of patients with advanced non-small-cell lung cancer (aNSCLC), metastatic colorectal cancer (mCRC), metastatic breast cancer (mBC), or advanced melanoma with a de novo or recurrent advanced diagnosis from January 1, 2011, through December 30, 2019, using a nationwide US electronic health record-derived deidentified database. Patients were classified by insurance and by advanced diagnosis date. NGS testing was assessed by receipt of first NGS test result ≤ 60 days of advanced diagnosis. Interrupted time series analysis assessed NGS utilization pre- and post-NCD effective date by insurance type. RESULTS: The utilization and repeat NGS testing analysis included 70,290 and 4,295 patients, respectively. Use of NGS rose from < 1% in 2011 to > 45% in Q4 2019 in aNSCLC while remaining < 20% in mBC and advanced melanoma. Among patients with aNSCLC, mCRC, or mBC, NGS testing increased post-NCD versus pre-NCD (P < .05). There was no significant difference in trends pre- and post-NCD between Medicare beneficiaries and commercially insured patients in any tumor. Repeat NGS testing was similar before the NCD (Medicare v commercial: 24.8% v 28.5%). Post-NCD, fewer Medicare beneficiaries had repeat NGS testing (27.7% v 36.0%; P < .01). CONCLUSION: Trends in NGS utilization significantly changed post-NCD, although the magnitude of change was not significantly different by insurance type, indicating private insurers may also be incorporating NCD guidance. Implementation of the NCD may have limited use of repeat NGS testing in Medicare beneficiaries.

Identification and temporal trends of patients with neuromyelitis optica spectrum disorder in a US insurance claims database.

BACKGROUND: This US claims-based study aimed to identify and characterize temporal trends in diagnostic pathways for patients likely to have neuromyelitis optica spectrum disorder (NMOSD). METHODS: Patients were identified from IBM MarketScan Commercial Databases if, within 1 year, they had two NMOSD claims separated by ≥ 60 days; two transverse myelitis (TM) or optic neuritis (ON) claims separated by ≥ 60 days, and one additional symptom (TM, ON, or area postrema syndrome); or one NMOSD claim and one additional symptom. The first NMOSD or TM/ON claim was the index date, and the second claim was the diagnosis date. Similar methodology was used in temporal trend and incidence and prevalence analyses. RESULTS: Among 1,901 patients with NMOSD, 34.2% were identified by two NMO claims, 53.2% by ON or TM +1 symptom, and 12.6% by one NMOSD claim +1 symptom. Anti-aquaporin-4 immunoglobin G (AQP4-IgG) autoantibody tests and magnetic resonance imaging was used for 23.0% and 71.9% of cases, respectively. Across cohorts, 21.4-49.1% had multiple sclerosis (MS) diagnosis claims prior to index date, and 37.3-60.6% had an MS diagnosis, 14.9-31.0% had MS disease-modifying therapy (DMT) claims and 6.3-44.8% had immunosuppressive therapy (IST) claims <1 year after diagnosis. Over time, there were slight changes in MS diagnosis claims, AQP4-IgG autoantibody testing, and DMT and IST use before and after NMOSD diagnosis. LIMITATIONS: This study is limited by the information available in US claims databases, which included the potential for misclassification of NMOSD based solely on claims codes and lack of reimbursement for AQP4-IgG testing by insurance companies. CONCLUSIONS: Among patients likely to have NMOSD, low AQP4-IgG testing rates, IST use, frequent MS diagnosis claims, and DMT use highlight the need for a diagnostic algorithm and timely treatment of NMOSD.

A Cost-Effectiveness Framework for COVID-19 Treatments for Hospitalized Patients in the United States.

INTRODUCTION: The COVID-19 pandemic is a global crisis impacting population health and the economy. We describe a cost-effectiveness framework for evaluating acute treatments for hospitalized patients with COVID-19, considering a broad spectrum of potential treatment profiles and perspectives within the US healthcare system to ensure incorporation of the most relevant clinical parameters, given evidence currently available. METHODS: A lifetime model, with a short-term acute care decision tree followed by a post-discharge three-state Markov cohort model, was developed to estimate the impact of a potential treatment relative to best supportive care (BSC) for patients hospitalized with COVID-19. The model included information on costs and resources across inpatient levels of care, use of mechanical ventilation, post-discharge morbidity from ventilation, and lifetime healthcare and societal costs. Published literature informed clinical and treatment inputs, healthcare resource use, unit costs, and utilities. The potential health impacts and cost-effectiveness outcomes were assessed from US health payer, societal, and fee-for-service (FFS) payment model perspectives. RESULTS: Viewing results in aggregate, treatments that conferred at least a mortality benefit were likely to be cost-effective, as all deterministic and sensitivity analyses results fell far below willingness-to-pay thresholds using both a US health payer and FFS payment perspective, with and without societal costs included. In the base case, incremental cost-effectiveness ratios (ICER) ranged from $22,933 from a health payer perspective using bundled payments to $8028 from a societal perspective using a FFS payment model. Even with conservative assumptions on societal impact, inclusion of societal costs consistently produced ICERs 40-60% lower than ICERs for the payer perspective. CONCLUSION: Effective COVID-19 treatments for hospitalized patients may not only reduce disease burden but also represent good value for the health system and society. Though data limitations remain, this cost-effectiveness framework expands beyond current models to include societal costs and post-discharge ventilation morbidity effects of potential COVID-19 treatments.

Estimated Impact of Public and Private Sector COVID-19 Diagnostics and Treatments on US Healthcare Resource Utilization.

INTRODUCTION: Coronavirus disease 2019 (COVID-19) has imposed a considerable burden on the United States (US) health system, with particular concern over healthcare capacity constraints. METHODS: We modeled the impact of public and private sector contributions to developing diagnostic testing and treatments on COVID-19-related healthcare resource use. RESULTS: We estimated that public sector contributions led to at least 30% reductions in COVID-19-related healthcare resource utilization. Private sector contributions to expanded diagnostic testing and treatments led to further reductions in mortality (- 44%), intensive care unit (ICU) and non-ICU hospital beds (- 30% and - 28%, respectively), and ventilator use (- 29%). The combination of lower diagnostic test sensitivity and proportions of patients self-isolating may exacerbate case numbers, and policies that encourage self-isolating should be considered. CONCLUSION: While mechanisms exist to facilitate research, development, and patient access to diagnostic testing, future policies should focus on ensuring equitable patient access to both diagnostic testing and treatments that, in turn, will alleviate COVID-19-related resource constraints.

Five-Year Patterns of Diabetic Retinopathy Progression in US Clinical Practice.

PURPOSE: To characterize the natural course of diabetic retinopathy (DR) in contemporary clinical practice. PATIENTS AND METHODS: This was a retrospective analysis of US claims data collected between January 1, 2006, and April 30, 2017. Patients aged ≥18 years with continuous medical and prescription insurance coverage for 18 months before DR diagnosis (index date) and for a follow-up period of 5 years were included (N=14,490). The time and risk of progressing to severe nonproliferative DR (NPDR) or proliferative DR (PDR) and of developing diabetic macular edema (DME) were evaluated over 5 years in patients stratified by DR severity at initial diagnosis. RESULTS: The estimated probability of progressing to severe NPDR or PDR within 5 years of diagnosis was 17.6% for patients with moderate NPDR versus 5.8% for mild NPDR. The probability of developing DME within 5 years was 62.6%, 44.6%, and 28.4% for patients diagnosed with severe NPDR, moderate NPDR, and PDR, respectively, versus 15.6% for mild NPDR. Among those observed to progress, median time to severe NPDR or PDR was approximately 2.0 years in patients with moderate NPDR, whereas median time to DME was approximately 0.5 years in patients with severe NPDR, 1.3 years in moderate NPDR, and 1.6 years in PDR. Relative to mild NPDR, adjusted hazard ratios (95% confidence interval) for progression to severe NPDR or PDR within 5 years were 3.12 (2.61-3.72) in patients with moderate NPDR, and for incident DME were 5.92 (5.13-6.82), 3.54 (3.22-3.91), and 1.96 (1.80-2.14) in patients with severe NPDR, moderate NPDR, and PDR, respectively. CONCLUSION: The risk of DR progression and DME over 5 years was highest among patients diagnosed with moderate and severe NPDR, respectively. Our findings reinforce the importance of close monitoring for these patients to avoid unobserved disease progression toward PDR and/or DME.

Impact of delaying initiation of anaplastic lymphoma kinase inhibitor treatment on survival in patients with advanced non-small-cell lung cancer.

INTRODUCTION: Several obstacles may delay receipt of targeted treatment in patients with anaplastic lymphoma kinase positive (ALK+) non-small-cell lung cancer (NSCLC). This study examined the factors associated with delayed initiation of ALK inhibitor (ALKi) treatment and its impact on overall survival (OS) as well as the impact of initiating chemotherapy before biomarker test results. MATERIALS AND METHODS: Advanced NSCLC (aNSCLC) patients selected from the deidentified Flatiron Health electronic health record-derived database were stratified into early- and delayed-use cohorts based on initiation of ALKi treatment relative to time since receiving ALK+ biomarker test results; cohorts were further stratified by timing of chemotherapy initiation relative to availability of ALK+ test results. Prescription-time matching (PTM) was used to examine the effect of delayed ALKi treatment and chemotherapy on survival; Cox proportional hazards models adjusting for baseline characteristics before and after PTM were used to examine factors associated with delayed ALKi treatment and the effects of delayed ALKi treatment and chemotherapy on OS, respectively. RESULTS: Comparison of OS between early- and delayed-use cohorts (N = 442 ALK + aNSCLC patients) demonstrated that a >3-week delay in the initiation of ALKi treatment was associated with a >2-fold higher risk of death (adjusted hazard ratio [HR] [95 % CI] 2.05 [1.13, 3.71]. The number of office visits, age factors, and use of chemotherapy were associated with an increased risk of being untreated >3 weeks after ALK+ test results. There were no significant differences in survival outcomes regardless of whether patients received chemotherapy before the ALK+ test result or ALKi treatment (adjusted HR [95 % CI] 1.02 [0.64, 1.63]). Completing the chemotherapy regimen after receiving ALK+ test results did not appear to improve survival (adjusted HR [95 % CI] 0.84 [0.38, 1.9]). CONCLUSION: Initiating ALKi treatment for aNSCLC patients in a timely manner may have a positive impact on survival outcomes.

HER2-Positive Metastatic Breast Cancer: A Retrospective Cohort Study of Healthcare Costs in the Targeted-Therapy Age.

INTRODUCTION: Claims data (IBM MarketScan Commercial and MarketScan Medicare Supplemental databases) from June 30, 2011 to September 30, 2017 were used to evaluate the cost impact of human epidermal growth factor receptor 2 (HER2)-positive metastatic breast cancer (MBC) in this retrospective cohort study. METHODS: The primary analysis compared short-term costs for patients diagnosed with HER2+ MBC at least 180 days after the end of first HER2-targeted treatment (MBC+ cohort) versus a propensity score matched cohort of patients with breast cancer who did not develop MBC (MBC- cohort). A pseudo-post period for patients in the HER2+ MBC- cohort was defined by indexing to the HER2+ treatment completion-MBC diagnosis time interval of the matched pair in the HER2+ MBC+ cohort; we then compared average monthly cost differences between these groups for the year preceding and following MBC diagnosis. In secondary analyses, we estimated medium-term aggregate and categorical healthcare costs for patients with HER2+ MBC up to 3 years post-diagnosis. RESULTS: In the short-term primary analysis, costs for the HER2+ MBC+ and HER2+ MBC- cohorts were largely comparable in the year preceding MBC diagnosis. Monthly direct costs were significantly higher for the HER2+ MBC+ cohort in the months immediately preceding MBC diagnosis, with differences in the range of $500-5000. Following diagnosis, total monthly costs were $13,000-34,000 higher for patients in the HER2+ MBC+ cohort vs. the HER2+ MBC- cohort. In the medium-term secondary analysis, mean per patient total costs were $218,171 [standard error (SE) $5450] in the first year following MBC diagnosis and $412,903 (SE $13,034) cumulatively over 3 years following diagnosis (among patients with complete follow-up). Primary cost contributors were outpatient visits ($195,162; SE $8043) and HER2-targeted therapy drug costs ($177,489; SE $8120). CONCLUSIONS: HER2+ MBC is associated with high short-term and medium-term direct healthcare costs. These could be alleviated with early diagnosis and optimal standard-of-care treatment for early breast cancer, which can significantly reduce the risk of recurrence.