Real-world treatment patterns, costs, and outcomes in patients with AL amyloidosis: analysis of the Optum EHR and commercial claims databases.

BACKGROUND: This study characterised real-world treatment patterns, clinical outcomes, and cost-of-illness in patients with light-chain (AL) amyloidosis. METHODS: Data were extracted from the US-based Optum® EHR and Clinformatics® Data Mart (claims) databases (2008-2019) for patients newly diagnosed with AL amyloidosis and who initiated anti-plasma cell therapies. Healthcare resource utilisation (HCRU) and related costs were compared across lines of therapy (LOT). Incidences of cardiac and renal failure were evaluated using the Kaplan-Meier method. RESULTS: About 1347 patients (EHR, n = 776; claims, n = 571) were included. Median age was 68 years; 56.8% were male. At initial diagnosis, 33.1% and 15.1% of patients had cardiac and renal failure, respectively. Most patients received bortezomib-containing treatment in LOT1 (69%); bortezomib-cyclophosphamide-dexamethasone was most common (26%). HCRU was similar across LOTs. Mean per-patient-per-month and per-patient-per-LOT costs were $19,343 and $105,944 for LOT1, $19,183 and $95,793 for LOT2, and $16,611 and $128,446 for LOT3, respectively. Costs were primarily driven by anti-plasma cell therapies, outpatient visits, and hospitalisations. The 5-year cardiac and renal failure rates following initial diagnosis were 64.5% and 39.0%, respectively. CONCLUSION: AL amyloidosis is associated with substantial costs and suboptimal outcomes, highlighting the need for new therapeutic approaches to prevent organ deterioration, and reduce disease burden.

Systematic literature review of evidence in amyloid light-chain amyloidosis.

Introduction: Treatment of amyloid light-chain (AL) amyloidosis, a rare disease with a <5-year lifespan, remains challenging. This systematic literature review (SLR) aimed to evaluate the current evidence base in AL amyloidosis. Methods: Literature searches on clinical, health-related quality of life, economic and resource use evidence were conducted using the Embase, MEDLINE and Cochrane databases as well as gray literature. Results: This SLR yielded 84 unique studies from: five randomized controlled trials; 54 observational studies; 12 health-related quality of life studies, none with utility values; no economic evaluation studies; and 16 resource use studies, none with indirect costs. Conclusion: This SLR highlights a paucity of published literature relating to randomized controlled trials, utility values, economic evaluations and indirect costs in AL amyloidosis.

Self-controlled assessment of thromboembolic event (TEE) risk following intravenous immune globulin (IGIV) in the U.S. (2006-2012).

Since 2013, the U.S. Food and Drug administration (FDA) has required that intravenous immune globulin (IGIV) products carry a boxed warning concerning the risk of thromboembolic events (TEEs). This study assessed the incidence of TEEs attributable to IGIV in a large population-based cohort. A self-controlled risk interval design was used to quantify the transient increase in TEE risk during the risk interval (days 0-2 and 0-13 following IGIV for arterial and venous TEEs, respectively) relative to a later control interval (days 14-27 following IGIV). Potential IGIV-exposed TEE cases from 2006 to 2012 were identified from the FDA-sponsored Sentinel Distributed Database and confirmed through medical record review. Inpatient IGIV exposures were not included in the venous TEE analysis due to concerns about time-varying confounding. 19,069 new users of IGIV who received 93,555 treatment episodes were included. Charts were retrieved for 62% and 70% of potential venous and arterial cases, respectively. There was a transient increase in the risk of arterial TEEs during days 0-2 following IGIV treatment (RR = 4.69; 95% CI 1.87, 11.90; absolute increase in risk = 8.86 events per 10,000 patients, 95% CI 3.25, 14.6), but no significant increase in venous TEE risk during days 0-13 following outpatient IGIV treatments (RR = 1.07, 95% CI 0.34, 3.48). Our results suggest there is a small increase in the absolute risk of arterial TEEs following IGIV. However, lower-than-expected chart retrieval rates and the possibility of time-varying confounding mean that our results should be interpreted cautiously. Continued pharmacovigilance efforts are warranted.

Treatment patterns, economic burden, and overall survival in US Medicare Advantage beneficiaries newly diagnosed with acute myeloid leukemia (AML) in 2015-2020.

The present study assessed changes in patient management, economic burden, and overall survival (OS) in a contemporary cohort of 2775 US Medicare Advantage beneficiaries aged ≥66 years newly diagnosed with acute myeloid leukemia (AML) between 01 January 2015 and 30 June 2020. Use of venetoclax-based therapy increased and replaced hypomethylating agent (HMA) monotherapy as the most common first-line treatment choice in 2019-2020. In newly diagnosed AML patients aged ≥75 and 66-74 years, mean per-patient 1-year healthcare expenditures were $81,818 and $156,033 (2020 USD) and median OS was 2.3 and 8.5 months, respectively. In addition, 40% of Medicare Advantage patients with newly diagnosed AML continue to receive supportive care alone. These findings indicate that at the population level clinical outcomes remain poor for older adults with AML, pointing to a continuing unmet medical need.

Association of body mass index and osteoarthritis with healthcare expenditures and utilization.

OBJECTIVE: Osteoarthritis is highly prevalent and, on aggregate, is one of the largest contributors to US spending on hospital-based health care. This study sought to examine body mass index (BMI)-related variation in the association of osteoarthritis with healthcare utilization and expenditures. METHODS: This is a retrospective study using administrative insurance claims linked to electronic health records. Study patients were aged ≥ 18 years with ≥1 BMI measurement recorded in 2014, with the first (index) BMI ≥ 25 kg m-2. Study outcomes and covariates were measured during a 1-year evaluation period spanning 6 months before and after index. Multivariable regression analyses examined the association of BMI with osteoarthritis prevalence, and the combined associations of osteoarthritis and BMI with osteoarthritis-related medication utilization, all-cause hospitalization, and healthcare expenditures. RESULTS: A total of 256 459 patients (median age = 56 y) met study eligibility criteria; 14.8% (38 050) had osteoarthritis. In multivariable analyses, the adjusted prevalence of osteoarthritis increased with increasing BMI (12.7% in patients who were overweight [25.0-29.9 kg m-2] to 21.9% in patients with class III obesity [BMI ≥ 40 kg m-2], P < .001). Among patients with osteoarthritis, increasing BMI (from overweight to class III obesity) was associated with increased (all P < .01): utilization rates for analgesic medications (41.5-53.5%); rates of all-cause hospitalization (26.3%-32.0%); and total healthcare expenditures ($18 204-$23 372). CONCLUSION: The prevalence and economic burden of osteoarthritis grow with increasing BMI; primary prevention of weight-related osteoarthritis and secondary weight management may help to alleviate this burden.

Assessment of obesity prevalence and validity of obesity diagnoses coded in claims data for selected surgical populations: A retrospective, observational study.

In many types of surgery, obesity may influence patient selection, prognosis, and/or management. Quantifying the accuracy of the coding of obesity and other prognostic factors is important for the design and interpretation of studies of surgical outcomes based on administrative healthcare data. This study assessed the validity of obesity diagnoses recorded in insurance claims data in selected surgical populations.This was a retrospective, observational study. Deidentified electronic health record (EHR) and linked administrative claims data were obtained for US patients age ≥20 years who underwent a qualifying surgical procedure (bariatric surgery, total knee arthroplasty [TKA], cardiac ablation, or hernia repair) in 2014Q1-2017Q1 (first = index). Patients' body mass index (BMI) as coded in the claims data (error-prone measure) during the index procedure or 180d pre-index was compared with their measured BMI as recorded in the EHR (criterion standard) to estimate the sensitivity and positive predictive value (PPV) of obesity diagnosis codes.Among patients who underwent bariatric surgery (N = 1422), TKA (N = 8670), cardiac ablation (N = 167), or hernia repair (N = 5450), obesity was present in 98%, 63%, 52%, and 54%, respectively, based on measured BMI. PPVs of obesity diagnosis codes were high: 99.3%, 96.0%, 92.8%, and 94.1% in bariatric surgery, TKA, cardiac ablation, and hernia repair, respectively. The sensitivity of obesity diagnoses was: 99.8%, 46.2%, 41.3%, and 42.3% in bariatric surgery, TKA, cardiac ablation, and hernia repair, respectively. Among false-positive patients diagnosed as obese but with measured BMI <30, the proportion with a BMI ≥28 was 40.0%, 67.6%, 60.7%, and 65.8% for bariatric surgery, TKA, cardiac ablation, and hernia repair, respectively.Our data indicate that obesity is highly prevalent in many surgical populations, obesity diagnosis codes have high PPVs, but also obesity is generally undercoded in claims data. Quantifying the validity of diagnosis codes for obesity and other important prognostic factors is important for the design and interpretation of studies of surgical outcomes based on administrative data. Further research is needed to determine the extent to which undercoding of BMI and obesity can be addressed through the use of proxies that may be better documented in claims data.

Using Machine Learning Applied to Real-World Healthcare Data for Predictive Analytics: An Applied Example in Bariatric Surgery.

OBJECTIVES: Laparoscopic metabolic surgery (MxS) can lead to remission of type 2 diabetes (T2D); however, treatment response to MxS can be heterogeneous. Here, we demonstrate an open-source predictive analytics platform that applies machine-learning techniques to a common data model; we develop and validate a predictive model of antihyperglycemic medication cessation (validated proxy for A1c control) in patients with treated T2D who underwent MxS. METHODS: We selected patients meeting the following criteria in 2 large US healthcare claims databases (Truven Health MarketScan Commercial [CCAE]; Optum Clinformatics [Optum]): underwent MxS between January 1, 2007, to October 1, 2013 (first = index); aged ≥18 years; continuous enrollment 180 days pre-index (baseline) to 730 days postindex; baseline T2D diagnosis and treatment. The outcome was no antihyperglycemic medication treatment from 365 to 730 days after MxS. A regularized logistic regression model was trained using the following candidate predictor categories measured at baseline: demographics, conditions, medications, measurements, and procedures. A 75% to 25% split of the CCAE group was used for model training and testing; the Optum group was used for external validation. RESULTS: 13 050 (CCAE) and 3477 (Optum) patients met the study inclusion criteria. Antihyperglycemic medication cessation rates were 72.9% (CCAE) and 70.8% (Optum). The model possessed good internal discriminative accuracy (area under the curve [AUC] = 0.778 [95% CI = 0.761-0.795] in CCAE test set N = 3527) and transportability (external AUC = 0.759 [95% CI = 0.741-0.777] in Optum N = 3477). CONCLUSION: The application of machine learning techniques to real-world healthcare data can yield useful predictive models to assist patient selection. In future practice, establishment of prerequisite technological infrastructure will be needed to implement such models for real-world decision support.

Body mass index and insulin use as identifiers of high-cost patients with type 2 diabetes: A retrospective analysis of electronic health records linked to insurance claims data.

AIMS: To study the association of body mass index (BMI) and insulin use with type 2 diabetes-related healthcare expenditures (T2D-HE). MATERIALS AND METHODS: Retrospective study using de-identified electronic health records linked to insurance claims data. Study included a prevalence-based sample of overweight or obese patients with antihyperglycaemic-treated T2D. Patients had ≥1 A1c measurement in 2014 (last observed = index A1c), ≥1 BMI measurement within ±90 days of index (average BMI = baseline BMI), and continuous enrolment for 180 days before (baseline) through 395 days after index (day 30-395 = follow-up). BMI was categorized as: 25 to 29.9 kg/m2 = overweight; 30 to 34.9 kg/m2 = obese class I (OCI); 35 to 39.9 kg/m2 = OCII; ≥40 kg/m2 = OCIII. Multivariable regressions were used to examine one-year follow-up T2D-HE as a function of BMI, insulin use, an interaction term between BMI and insulin use, and patient demographics. RESULTS: Study included 13 026 patients (mean age = 63.6 years; 48.1% female; 29.5% overweight, 31.6% OCI, 20.3% OCII, 18.6% OCIII; 25.3% insulin users). Baseline insulin use rates monotonically ranged from 19.7% in overweight patients to 33.0% in OCIII patients (P < 0.001). Together, BMI and insulin use were jointly associated with one-year follow-up T2D-HE, which monotonically ranged from $5842 in overweight patients with no insulin to $17 700 OCIII insulin users, P < 0.001. Within each BMI category, insulin users' one-year T2D-HE was at least double that of non-users. Additional analyses of all-cause healthcare expenditures yielded consistent results. CONCLUSIONS: BMI and insulin use represent simple stratifiers for identifying high-cost patients. OCIII insulin users incurred the greatest annual healthcare expenditures; these patients may be an ideal group for targeted interventions.

A dual-perspective analysis of the hospital and payer-borne burdens of selected in-hospital surgical complications in low anterior resection for colorectal cancer.

OBJECTIVES: The economic burden of surgical complications is borne in distinctly different ways by hospitals and payers. This study quantified the incidence and economic burden - from both the hospital and payer perspective - of selected major colorectal surgery complications in patients undergoing low anterior resection (LAR) for colorectal cancer. METHODS: Retrospective, observational study of patient undergoing LAR for colorectal cancer between 1/1/2010 and 7/1/2015. Analyses were replicated in two large healthcare administrative databases: Premier (hospital discharge and billing data; hospital perspective) and Optum (insurance claims data; payer perspective). Multivariable analyses evaluated the association between infection (surgical site or bloodstream), anastomotic leak, and bleeding complications and the following outcomes: hospital length of stay (LOS), non-home discharge, 90-day all-cause readmission, index admission costs to the hospital, index admission payer expenditures, and index admission +90-day post-discharge payer expenditures. RESULTS: 9,738 eligible LAR patients were included (7,479 in Premier; 2,259 in Optum). Overall, the incidences of infection, anastomotic leak, and bleeding complications were 6.4%, 10.6%, and 10.9%, respectively, during the index hospitalization. Each complication was associated with statistically significant longer LOS, higher risk of non-home discharge, higher risk of 90-day readmission, greater costs to the hospital, and higher payer expenditures. CONCLUSIONS: In-hospital infection, anastomotic leak, and bleeding were associated with a substantial economic burden, for both hospitals and payers, in patients undergoing LAR for colorectal cancer. This study provides information which may be used to quantify the potential economic value and impact of innovations in surgical care and delivery that reduce the incidence and burden of these complications.

Validation of body mass index (BMI)-related ICD-9-CM and ICD-10-CM administrative diagnosis codes recorded in US claims data.

PURPOSE: To quantify the sensitivity and positive predictive value (PPV) of body mass index (BMI)-related ICD-9-CM and ICD-10-CM diagnosis codes in claims data. METHODS: De-identified electronic health record (EHR) and claims data were obtained from the Optum Integrated Claims-Clinical Database for cross-sections of commercial and Medicare Advantage health plan members age ≥ 20 years in 2013, 2014, and 2016. In each calendar year, health plan members' BMI as coded in the insurance claims data (error-prone measure) was compared with their BMI as recorded in the EHR (gold standard) to estimate the sensitivity and PPV of BMI-related ICD-9-CM and ICD-10-CM diagnosis codes. The unit of analysis was the person-year. RESULTS: The study sample included 746 763 distinct health plan members who contributed 1 116 283 eligible person-years (median age 56 years; 57% female; 65% commercially insured and 35% with Medicare Advantage). BMI-related diagnoses were coded for 14.6%. The sensitivity of BMI-related diagnoses codes for the detection of underweight, normal weight, overweight, and obesity was 10.1%, 3.7%, 6.0%, and 25.2%, and the PPV was 49.0% for underweight, 89.6% for normal weight, 73.4% for overweight, and 92.4% for obesity, respectively. The sensitivity of BMI-related diagnosis codes was higher in the ICD-10-CM era relative to the ICD-9-CM era. CONCLUSIONS: The PPV of BMI-related diagnosis codes for normal weight, overweight, and obesity was high (>70%) but the sensitivity was low (<30%). BMI-related diagnoses were more likely to be coded in patients with class II or III obesity (BMI ≥35 kg/m2 ), and in 2016 relative to 2013 or 2014.

Time to Second-line Treatment and Subsequent Relative Survival in Older Patients With Relapsed Chronic Lymphocytic Leukemia/Small Lymphocytic Lymphoma.

BACKGROUND: Novel targeted therapies offer excellent short-term outcomes in patients with chronic lymphocytic leukemia and small lymphocytic lymphoma (CLL/SLL). However, there is disagreement over how widely these therapies should be used in place of standard chemo-immunotherapy (CIT). We investigated whether stratification on the length of the interval between first-line (T1) and second-line (T2) treatments could identify a subgroup of older patients with relapsed CLL/SLL with an expectation of normal overall survival, and for whom CIT could be an acceptable treatment choice. PATIENTS AND METHODS: Patients with relapsed CLL/SLL who received T2 were identified from the SEER-Medicare Linked Database. Five-year relative survival (RS5; ie, the ratio of observed survival to expected survival based on population life tables) was assessed after stratifying patients on the interval between T1 and T2. We then validated our findings in the Mayo Clinic CLL Database. RESULTS: Among 1974 SEER-Medicare patients (median age = 77 years) who received T2 for relapsed CLL/SLL, longer time-to-retreatment was associated with a modestly improved prognosis (P = .01). However, even among those retreated ≥ 3 years after T1, survival was poor compared with the general population (RS5 = 0.50 or lower in SEER-Medicare). Similar patterns were observed in the younger Mayo validation cohort, although prognosis was better overall among the Mayo patients, and patients with favorable fluorescence in situ hybridization retreated ≥ 3 years after T1 had close to normal expected survival (RS5 = 0.87). CONCLUSION: Further research is needed to quantify the degree to which targeted therapies provide meaningful improvements over CIT in long-term outcomes for older patients with relapsed CLL/SLL.