Abstract
Aim
Describe the clinical and economic burden of hospitalizations for amyloid light chain (AL) amyloidosis.
Materials & methods
This retrospective analysis used nationally representative hospital discharge data (2017–2020) to report discharge status, resource use and costs for hospitalizations among patients with AL amyloidosis.
Results
Of 1341 patients identified, 92% were discharged alive and 8% experienced in-hospital death. Compared with the average US hospital stay during 2017–2019 (4.7 days, mean costs of $13,046 and mean charges of $54,496), hospital stays for AL amyloidosis were longer and costlier (9.7 days, $27,098.61, $111,233.91), especially in patients with in-hospital death (12.2 days, $44,966, $182,338.18).
Conclusion
AL amyloidosis is associated with significant clinical and economic burden.
Keywords: AL amyloidosis, hospitalization, mortality
Plain language summary
What is this article about?
Delayed amyloid light chain (AL) amyloidosis diagnosis is common and associated with poor prognosis and increased healthcare utilization and costs due to disease progression. The study objective was to examine mortality, hospitalization and associated costs.
What were the results?
About 8% of patients hospitalized with amyloid light chain (AL) amyloidosis died in the hospital, of these, 80% had both cardiac and renal involvement versus 54% of patients discharged alive. Compared with the average US hospital stay, the average AL amyloidosis hospitalization is twice as costly and for individuals who died in hospital it is three-times as much.
What do the results of the study mean?
Results suggest that there is still a need for increased awareness of the disease, which may lead to earlier treatment and reduced costs.
Systemic amyloid light chain (AL) amyloidosis is a rare, progressive and fatal disease where clonal plasma cells overproduce light chain proteins that misfold, aggregate and deposit as amyloid in vital organs [1–4]. It is the most common and severe form of systemic amyloidosis [1]. Diagnosis of this condition is complicated since there is no solitary diagnostic test value [5]. Furthermore, as multiple organs (e.g., kidney, heart and liver) can be impacted by amyloid accumulation, diagnosis is often delayed due to overlapping symptoms that mimic common conditions [1–3,5–9].
Survival is poor with disease progression, as most organ damage is irreversible, and mortality is primarily driven by cardiac failure [1–3,5–8,10]. The goal of treatment is to recover organ function by targeting the abnormal plasma cell clone as quickly as possible, with most regimens derived from those used to treat multiple myeloma [6,11]. Untreated, survival is less than 1 year [1,2,5,6,8]. And while overall survival has improved with increasing disease awareness and number of treatment options and clinical advents [6,10,12], mortality is still high among patients with AL amyloidosis, especially among subpopulations such as older adults and patients with Mayo stage 4 disease [10,12].
Poor prognosis further hindered by delayed diagnosis makes AL amyloidosis especially burdensome both clinically and economically. Previous studies have examined healthcare utilization and costs among patients with AL amyloidosis, but available information is still limited [13]. Past studies are based on data from individual treatment centers (rather than nationally representative data) or utilize older real-world data and had to rely on algorithms to identify patients with AL amyloidosis rather than the more recently introduced (2017) AL amyloidosis-specific International Classification of Diseases, 10th Revision, Clinical Modification (ICD-10-CM) diagnosis code (E85.81) [13–16]. To add to the limited research on disease and economic burden among patients with AL amyloidosis, we used a nationally, representative claims database and specific AL amyloidosis coding to examine mortality, hospitalization and associated costs.
Materials & methods
This was a retrospective claims analysis of the Premier® Healthcare Database (PHD) (Premier, Inc., NC, USA). Premier contains complete clinical coding, hospital cost and patient billing data from more than 1041 hospitals throughout the USA. The database covers 25% of US hospital discharges. Data are at the admission level, and patients admitted more than once are considered separate admissions. In this study, the terms admission and patient are used interchangeably for simplicity. Both charge and cost data are available for each hospitalization. Charges are amounts billed to the payer. In contrast, costs represent payment for services and include variable expenses (those related directly to the activity of the relevant department such as supplies and direct patient care) and fixed expenses (including depreciation, management, repair and maintenance and overhead). Costs are reported by Premier based on a combination of information from individual hospital cost-accounting systems and calculations using Medicare costs to charges ratios. Reported costs do not include professional fees for services by physicians and other independent practitioners [17]. Premier data are deidentified, compliant with the Health Insurance Portability and Accountability Act (HIPAA) and consistent with 45 CFR 46.101(b)(4) making it exempt from Institutional Review Board oversight.
Adult patients with AL amyloidosis were identified by the presence of at least one inpatient claim for AL amyloidosis (ICD-10-CM diagnosis code: E85.81) in any diagnosis field during the study period (1 October 2017–31 December 2020). This period was selected because the specific code for AL amyloidosis (ICD-10-CM: E85.81) was not available until 1 October 2017. If patients had multiple qualified inpatients claims during the study period, only the first hospitalization was included.
Of the above identified patients, those having any of the following diseases during the same hospitalization(s) were excluded if they had a diagnosis for other types of amyloidosis (ICD-10-CM codes: E85.0x-E85.3x), chronic inflammatory disease (e.g., rheumatoid arthritis [ICD-10-CM: M05.40-M06.9]), inflammatory bowel diseases (Crohn’s disease [ICD-10-CM: K50.xx], ulcerative colitis [ICD-10-CM: K51.xx]), bronchiectasis (ICD-10-CM: J47.xx, Q33.4) or chronic osteomyelitis (ICD-10-CM: A02.24, H05.02x; M86.xx).
Demographic characteristics, comorbidities (e.g., Charlson Comorbidity Index [CCI]) and admission characteristics, including admission type, most frequent admitting or primary diagnoses, severity of disease (all patient refined diagnosis related groups [APR-DRG] severity of illness: minor, moderate, major, extreme), cardiac or renal involvement (calculated based on presence of relevant diagnostic codes) and discharge status, were measured. Healthcare utilization (e.g., length of stay [LOS], emergency department visits, in-patient services) and costs were also measured. All costs were inflated to 2020 USD using the medical care component of the Consumer Price Index [18]. Utilization measures were identified based on diagnosis and procedure codes while cost measures were based on hospital billing records. Total hospital associated costs included the total cost to treat the patient during the hospital encounter (e.g., supplies, labor, depreciation of equipment), as well as variable and fixed expenses. Variable expenses included expenses that relate directly to or vary with the activity (volume) of the department (e.g., supplies and hands on patient care); fixed expenses included those that do not relate directly to or vary with the activity (volume) of the department (e.g., depreciation, management, repair and maintenance and overhead). The total costs did not include professional fees for the services received in hospitals by physicians and other skilled healthcare professionals licensed for independent practice.
Patients were stratified between those with an in-hospital death and those discharged alive. Descriptive statistics including mean, standard deviations (SD) and relative frequencies and percentages for continuous and categorical data, respectively, were reported. To compare between diagnostic versus other hospitalizations, t-test and χ2 (or exact χ2) test were performed for continuous and categorical variables, respectively. The exact χ2 test was used when one of the cell counts was less than 5. All data transformations and statistical analyses were performed using SAS© version 9.4 (SAS Institute Inc., NC, USA).
Results
Among the 1419 adult patients with a diagnosis of AL amyloidosis between 1 October 2017 and 31 December 2020, 60 were excluded for having a diagnosis code for another type of amyloidosis and 18 for having a diagnosis code for a chronic inflammatory disease, which left a final sample of 1341. Table 1 provides demographic characteristics for the study cohort. The mean (SD) age of the overall sample was 67.2 (11.2) years, with the majority of patients being 65 years or older in age (61%), 44.1% were female, 64.3% were White and Medicare was the primary payer type (62.4%). Patients were quite ill with a mean CCI score of 3.9 and APR-DRG severity of illness classification of major (56.9%) or extreme (27.5%) (Table 2). Hospitalizations were primarily urgent/emergent (87.6%) and occurred in the South (42.1%) and in teaching hospitals (62.4%) (Table 3). The main source of admission was nonhealthcare facilities (74.6%). Most patients were discharged home or home with nursing care (66.4%) (Table 3) and had an overall LOS of 9.7 days (Table 4).
Table 1. . Demographics of hospitalized amyloid light chain amyloidosis patients, stratified by discharge status.
| Discharge status | Adult AL amyloidosis patients n (%) = 1341 (100%) |
p-value | ||
|---|---|---|---|---|
| In-hospital death n (%) = 107 (8.0%) |
Discharged alive n (%) = 1234 (92.0%) |
|||
| Age, years, mean (SD) [median] | 66.4 (10.1) [67] | 67.3 (11.3) [68] | 67.2 (11.2) [68] | 0.441 |
| Age group, years, n (%) | 0.511 | |||
| 18–34 | 0 (0) | 7 (0.6) | 7 (0.5) | |
| 35–54 | 12 (11.2) | 151 (12.2) | 163 (12.2) | |
| 55–64 | 34 (31.8) | 319 (25.9) | 353 (26.3) | |
| 65 or older | 61 (57.0) | 757 (61.3) | 818 (61.0) | |
| Female, n (%) | 45 (42.1) | 547 (44.3) | 592 (44.1) | 0.650 |
| Race, n (%) | 0.965 | |||
| White | 67 (62.6) | 795 (64.4) | 862 (64.3) | |
| African–American | 26 (24.3) | 280 (22.7) | 306 (22.8) | |
| Other | 9 (8.4) | 115 (9.3) | 124 (9.2) | |
| Asian | 2 (1.9) | 17 (1.4) | 19 (1.4) | |
| Unable to determine | 3 (2.8) | 27 (2.2) | 30 (2.2) | |
| Primary payer type, n (%) | 0.051 | |||
| Medicare | 60 (56.1) | 777 (63.0) | 837 (62.4) | |
| Medicaid | 12 (11.2) | 116 (9.4) | 128 (9.5) | |
| Commercial | 12 (11.2) | 88 (7.1) | 100 (7.5) | |
| Self-pay | 4 (3.7) | 11 (0.9) | 15 (1.1) | |
| Managed care | 17 (15.9) | 202 (16.4) | 219 (16.3) | |
| Other | 2 (1.9) | 40 (3.2) | 42 (3.1) | |
| Year of hospitalization, n (%) | 0.860 | |||
| 2017† | 5 (4.7) | 75 (6.1) | 80 (6.0) | |
| 2018 | 33 (30.8) | 352 (28.5) | 385 (28.7) | |
| 2019 | 35 (32.7) | 434 (35.2) | 469 (35.0) | |
| 2020 | 34 (31.8) | 373 (30.2) | 407 (30.4) | |
ICD-10-CM code E85.81 for light chain (AL) amyloidosis was not available until 1 October 2017.
AL: Systemic amyloid light chain; SD: Standard deviation.
Table 2. . Charlson Comorbidity Index, stratified by discharge status.
| Discharge status | Adult AL amyloidosis patients n (%) = 1341 (100%) |
p-value | ||
|---|---|---|---|---|
| In-hospital death n (%) = 107 (8.0%) |
Discharged alive n (%) = 1234 (92.0%) |
|||
| Charlson Comorbidity Index, mean (SD) [median] | 4.5 (2.2) [4] | 3.9 (2.3) [4] | 3.9 (2.3) [4] | 0.008 |
AL: Systemic amyloid light chain; SD: Standard deviation.
Table 3. . Hospital characteristics, stratified by discharge status.
| Discharge status | Adult AL amyloidosis patients n (%) = 1341 (100%) |
p-value | ||
|---|---|---|---|---|
| In-hospital death n (%) = 107 (8.0%) |
Discharged alive n (%) = 1234 (92.0%) |
|||
| Admission type, n (%) | <0.001 | |||
| Elective | 1 (0.9) | 165 (13.4) | 166 (12.4) | |
| Urgent/emergent | 106 (99.1) | 1069 (86.6) | 1175 (87.6) | |
| Hospital region, n (%) | 0.379 | |||
| Northeast | 29 (27.1) | 272 (22.0) | 301 (22.4) | |
| Midwest | 20 (18.7) | 305 (24.7) | 325 (24.2) | |
| West | 14 (13.1) | 137 (11.1) | 151 (11.3) | |
| South | 44 (41.1) | 520 (42.1) | 564 (42.1) | |
| Hospital type, n (%) | 0.504 | |||
| Teaching | 70 (65.4) | 767 (62.2) | 837 (62.4) | |
| Non teaching | 37 (34.6) | 467 (37.8) | 504 (37.6) | |
| Hospital location, n (%) | 0.883 | |||
| Rural | 9 (8.4) | 109 (8.8) | 118 (8.8) | |
| Urban | 98 (91.6) | 1125 (91.2) | 1223 (91.2) | |
| Hospital bed size, n (%) | 0.022 | |||
| 0–199 | 11 (10.3) | 142 (11.5) | 153 (11.4) | |
| 200–499 | 30 (28.0) | 498 (40.4) | 528 (39.4) | |
| 500+ | 66 (61.7) | 594 (48.1) | 660 (49.2) | |
| Admission source, n (%) | <0.001 | |||
| Clinic | 7 (6.5) | 158 (12.8) | 165 (12.3) | |
| Nonhealthcare facility | 71 (66.4) | 929 (75.3) | 1000 (74.6) | |
| Transfer from hospital, SNF or other facility | 29 (27.1) | 139 (11.3) | 168 (12.5) | |
| Other | 0 (0) | 8 (0.6) | 8 (0.6) | |
AL: Systemic amyloid light chain; SD: Standard deviation; SNF: Skilled nursing facility.
Table 4. . Discharge status and healthcare utilization, stratified by discharge status.
| Discharge status | Adult AL amyloidosis patients n (%) = 1341 (100%) |
p-value | ||
|---|---|---|---|---|
| In-hospital death n (%) = 107 (8.0%) |
Discharged alive n (%) = 1234 (92.0%) |
|||
| Discharge status, n (%) | n/a | |||
| Home or home with nursing care | 0 (0) | 891 (72.2) | 891 (66.4) | |
| Transferred to hospice, rehabilitation center or nursing home | 0 (0) | 269 (21.8) | 269 (20.1) | |
| Death during hospitalization | 107 (100.0) | 0 (0) | 107 (8.0) | |
| Other/unknown | 0 (0) | 74 (6.0) | 74 (5.5) | |
| Overall length of stay (days), mean (SD) (median) | 12.2 (13.0) [9.0] | 9.2 (9.4) [6.0] | 9.5 (9.7) [6.0] | 0.024 |
| Intensive care unit (ICU),† n (%) | 53 (49.5) | 216 (17.5) | 269 (20.1) | <0.001 |
| Length of ICU stay among utilizers, mean (SD) (median) | 7.2 (7.1) [5.0] | 6.3 (7.8) [3.0] | 6.5 (7.6) [3.0] | 0.479 |
| ED,† n (%) | 74 (69.2) | 841 (68.2) | 915 (68.2) | 0.830 |
| Length of ED stay among utilizers, mean (SD) (median) | 1.2 (0.9) [1.0] | 1.3 (3.1) [1.0] | 1.3 (3.0) [1.0] | 0.581 |
| Coronary care unit,† n (%) | 15 (14.0) | 43 (3.5) | 58 (4.3) | <0.001 |
| Length of coronary care unit stay among utilizers, mean (SD) (median) | 7.5 (6.4) [6.0] | 5.7 (4.6) [4.0] | 6.1 (5.1) [4.5] | 0.241 |
| Oncology ward,† n (%) | 3 (2.8) | 72 (5.8) | 75 (5.6) | 0.191 |
| Length of oncology ward stay among utilizers, mean (SD) (median) | 2.3 (0.6) [2.0] | 9.5 (9.4) [7.0] | 9.3 (9.3) [7.0] | <0.001 |
| Hospice,† n (%) | 0 (0.0) | 0 (0.0) | 0 (0.0) | n/a |
Care units identified through hospital billing records, based on any charge for room and board.
AL: Systemic amyloid light chain; ED: Emergency department; ICU: Intensive care unit; SD: Standard deviation.
Of the 1341 patients, 8% had an in-hospital death (defined as discharge status of death) (Table 4). Demographic characteristics (age, gender, race, primary payer type) for this subgroup were similar to the overall cohort. Patients who died at the hospital had a higher comorbidity burden compared with those discharged alive (CCI: 4.5 vs 3.9; p = 0.008), as well as more severe disease on the APR-DRG scale (extreme: 77.6 vs 23.2%). Nearly 80% of patients who died in the hospital had an admission with cardiac or renal involvement compared with 50% of those discharged alive (Table 5). The most frequent admitting and primary diagnoses were similar between groups; however, sepsis was a frequent diagnosis only among those who died in the hospital (Table 5). Hematopoietic stem cell transplant was more frequent in patients discharged alive than in those who died in the hospital (6.4 vs 0.9%; p = 0.017).
Table 5. . Cardiac or renal involvement and most frequent diagnosis (admitting and primary), stratified by discharge status.
| Discharge status | Adult AL amyloidosis patients n (%) = 1341 (100%) |
p-value | ||
|---|---|---|---|---|
| In-hospital death n (%) = 107 (8.0%) |
Discharged alive n (%) = 1234 (92.0%) |
|||
| Cardiac or renal involvement, n (Col%) (Row%) | <0.001 | |||
| Cardiac and renal | 85 (79.4) [11.6] | 649 (52.6) [88.4] | 734 (54.7) [100.0] | |
| Cardiac only | 7 (6.5) [4.0] | 169 (13.7) [96.0] | 176 (13.1) [100.0] | |
| Renal only | 13 (12.1) [4.2] | 296 (24.0) [95.8] | 309 (23.0) [100.0] | |
| No cardiac or renal involvement | 2 (1.9) [1.6] | 120 (9.7) [98.4] | 122 (9.1) [100.0] | |
| Most frequent admitting diagnosis, by cohort, n (%) | ||||
| Unknown | 8 (7.5) | 125 (10.1) | – | – |
| Shortness of breath | 10 (9.4) | 98 (7.9) | – | – |
| Sepsis, unspecified organisms | 9 (8.4) | – | – | – |
| Light chain (AL) amyloidosis | – | 72 (5.8) | – | – |
| Acute kidney failure, unspecified | – | 65 (5.3) | – | – |
| Most frequent primary diagnosis, by cohort, n (%) | – | |||
| Light chain (AL) amyloidosis | 18 (16.8) | 222 (18.0) | – | – |
| Sepsis, unspecified organisms | 12 (11.2) | – | – | – |
| Hypertensive heart and CKD w/HF and stage 1–4 CKD or unspecified CKD | 11 (10.3) | 73 (5.9) | – | – |
| Acute kidney failure, unspecified | 6 (5.6) | 70 (5.7) | – | – |
| Organ-limited amyloidosis | 6 (5.6) | – | – | – |
| MM not having achieved remission | – | 67 (5.4) | – | – |
AL: Systemic amyloid light chain; CKD: Chronic kidney disease; HF: Heart failure; MM: Multiple myeloma; SD: Standard deviation.
For the overall cohort, mean (SD) total costs were $27,098.61 ($34,849.13) and total charges were $111,233.91 ($144,852.70) (Figure 1). In terms of resource use and costs, a significant difference was found between patients who died in the hospital and those discharged alive. The mean LOS was 12.2 days for patients who died in the hospital compared with 9.2 days for patients who were discharged alive (p = 0.024). Total costs and charges were also significantly higher among the first group when compared with the second ($44,965.97 [$60,813.82] vs $25,549.33 [$31,173.79]; p < 0.001) and $182,338.18 [$230,288.49] vs $105,068.46 [$133,293.58]; p = 0.001).
Figure 1. . Hospital-associated costs† of in-hospital deaths, adjusted to 2020 USD.
†Total costs and charges do not include professional fees for the services received in hospitals by physicians and other skilled healthcare professionals licensed for independent practice.
‡Determined by the hospital billing records, not by procedure codes.
*p < 0.001.
**p = 0.001.
Discussion
While AL amyloidosis is the most common form of systemic amyloidosis, little is known about the economic burden associated with AL amyloidosis hospitalizations. The present study adds to the limited real-world data on hospital utilization and cost in AL amyloidosis, while also comparing these characteristics between patients with different outcomes post-hospitalization – those with an in-hospital death versus those discharged alive.
This retrospective analysis of hospital records found a mean cost of $27,099 for AL amyloidosis hospitalizations. In-hospital mortality among patients hospitalized with AL amyloidosis was 8%. Examining resource use and costs associated with AL amyloidosis hospitalizations by discharge status showed that patients who died in the hospital had higher costs and longer stays than those discharged alive ($44,966 vs $25,549; p < 0.001 and 12.2 vs 9.4 days; p = 0.024).
For additional context, the average US hospital stays during 2017–2019 had a mean cost of $13,046 and mean charge of $54,496, while its LOS was 4.7 days. Thus, the average AL amyloidosis hospitalization is twice as costly as the average US hospital stay. Furthermore, costs associated with stays for individuals who died during a hospitalization are three-times as much as the costs of the average US stay.
Past research has shown that cardiac and renal involvement is common in AL amyloidosis, with cardiac involvement being a primary driver of mortality in patients with AL amyloidosis [9,13,14,19,20]. We found that among the patients with AL amyloidosis who died in hospital, 80% had both cardiac and renal involvement compared with 53% of patients who were discharged alive. Costs related to end of life heart failure and renal disease are high in the general population [13], but have not been directly examined in AL amyloidosis. We did not stratify costs by cardiac and renal involvement, but this involvement is likely to have impacted the cost difference among patients with AL amyloidosis with an in-hospital death compared with those discharged alive.
As the specific diagnosis code for AL amyloidosis was not introduced until 2017, our results may not be directly comparable to prior research. A 2018 study using commercial insurance claims data from 2007–2015 estimated the LOS at 10.2 days and inpatient cost at just under $37,909 per year, but patients were identified through an algorithm that relied on a more general code plus the use of specific medications [15]. A 2019 study using the same database as the current study but focusing on cardiac amyloidosis from all subtypes found an average LOS of 8.3 days and a cost of $20,584 [14]. Similarly to our findings, a 2019 study of patients with amyloidosis in the 2005–2014 National Inpatient Sample found that hospitalized patients with amyloidosis had a longer LOS, lower likelihood of being discharged home, and higher likelihood of dying in the hospital compared with a matched cohort without amyloidosis [20]. Additionally, a concomitant diagnosis of heart failure was associated with more comorbidity and mortality [20].
Rates of hospital admissions in patients with amyloidosis are increasing [20], thus, characterizing hospitalizations and possibly identifying areas for cost savings and unmet need among this population is key for future research, as well as clinical management of AL amyloidosis. Diagnostic delay is still common for a number of reasons, including the overlapping and non specific nature of symptoms and lack of familiarity of the disease among patients and physicians, which leads to poorer outcomes and greater disease burden [7,9,21]. This was evident in our study as the majority of patients had emergency department visits (69.2% of patients with an in-hospital death and 68.2% of patients discharged alive). Patients who died in the hospital were also more likely to be seen in the ICU than those discharged alive (49.5 vs 17.5%; p < 0.001). Untreated patients with AL amyloidosis and cardiac involvement have a median survival of less than 1 year [4,8,22]. In an analysis of survival trends and primary causes of death among a population of patients with AL amyloidosis, Staron et al. found that while survival rates among those with cardiac involvement had generally improved, in older patients (>70 years), this was not the case [12]. The mean age in our study was 67.2 years. Older patients had the highest rate of mortality due to factors such as poor tolerance to treatment and comorbidity burden along with multiorgan involvement, highlighting the need for earlier diagnosis in this population [7,12].
This study has several limitations. While the Premier database covers 25% of US hospital discharges, it does not include federally funded (e.g., US Department of Veterans Affairs) or closed panel health maintenance organization facilities. In addition, because it primarily includes information relevant to payment for services, miscoding is possible. Relying on diagnosis codes, rather than clinical information (e.g., lab values), did not allow us to use Mayo staging for disease severity or examine the impact on outcomes. This lack of lab values also hindered us from examining whether patients with in-hospital death had any lab markers that may have predicted cardiac involvement earlier or later in their clinical journey, timing of which could have impacted prognosis [4,10,23]. Additionally, all data pertained to only the hospital admission of interest. This, coupled with the fact that results were only descriptive, meant that we also did not examine any long-term factors, such as early or late diagnosis or healthcare journey prior to index, or control for differences between the stratified groups (patients with in-hospital death and patients discharged alive) that could have impacted outcomes.
Conclusion
This is the first real-world study to use an AL amyloidosis-specific ICD diagnostic code to characterize in-hospital mortality among patients with the disease. While all AL amyloidosis hospitalizations are associated with greater resource use and higher costs than the average US hospitalization, the clinical and economic burden is especially severe corresponding to AL amyloidosis patients who died during a hospitalization. Cardiac and renal involvement is found in a higher proportion of patients with AL amyloidosis who died in the hospital compared with those discharged alive. Adding to what little is known about the clinical and hospitalization characteristics among this population may increase awareness and knowledge of the disease, leading to earlier treatment and possibly reduced costs.
Summary points.
Diagnosing systematic amyloid light chain (AL) amyloidosis is challenging as there is no solitary diagnostic test to detect this disease and the condition is associated with symptoms that mimic common conditions.
Delayed diagnosis impacts survival, as disease progression is associated with irreversible organ damage.
This retrospective cohort study used 2017–2020 hospital discharge data from the Premier® Healthcare Database.
Between 2017 and 2020, 1419 hospitalizations included at least one inpatient claim with a diagnosis for AL amyloidosis. After applying additional study criteria, the final sample included 1341 patients.
Of the 1341 patients, 8% died in-hospital.
Among those who died in the hospital, nearly 80% had an admission with cardiac or renal involvement compared with 50% of those discharged alive.
Patients with an in-hospital death had longer hospital stays and higher total costs and charges compared with those discharged alive.
Characterizing the hospitalizations and clinical outcomes of these patients may increase awareness of the disease and improve early diagnosis.
Footnotes
Financial & competing interests disclosure
This analysis was supported by Prothena Biosciences Ltd (Dublin, Ireland), a member of the Prothena Corporation plc group. TP Quock is an employee of Prothena Biosciences Inc. and holds stock in Prothena Corporation plc group. A D'Souza is an employee of the Medical College of Wisconsin and was paid by Prothena Biosciences Inc. to consult as a subject matter expert. E Chang, K Bognar, MS Broder and MH Tarbox are employees of PHAR, LLC, which received funding from Prothena to conduct the research described in this manuscript. The authors have no other relevant affiliations or financial involvement with any organization or entity with a financial interest in or financial conflict with the subject matter or materials discussed in the manuscript apart from those disclosed.
Partnership for Health Analytic Research provided analysis, writing and editorial support, funded by Prothena Biosciences Ltd.
Ethical conduct of research
The authors state that they have obtained appropriate institutional review board approval or have followed the principles outlined in the Declaration of Helsinki for all human or animal experimental investigations. In addition, for investigations involving human subjects, informed consent has been obtained from the participants involved.
Open access
This work is licensed under the Attribution-NonCommercial-NoDerivatives 4.0 Unported License. To view a copy of this license, visit http://creativecommons.org/licenses/by-nc-nd/4.0/
References
Papers of special note have been highlighted as: • of interest; •• of considerable interest
- 1.Al Hamed R, Bazarbachi AH, Bazarbachi A, Malard F, Harousseau J-L, Mohty M. Comprehensive review of AL amyloidosis: some practical recommendations. Blood Cancer J. 11(5), 97 (2021). [DOI] [PMC free article] [PubMed] [Google Scholar]
- 2.Hasib Sidiqi M, Gertz MA. Immunoglobulin light chain amyloidosis diagnosis and treatment algorithm 2021. Blood Cancer J. 11(5), 90 (2021). [DOI] [PMC free article] [PubMed] [Google Scholar]
- 3.Dittrich T, Kimmich C, Hegenbart U, Schönland SO. Prognosis and staging of AL amyloidosis. Acta Haematol. 143(4), 388–400 (2020). [DOI] [PubMed] [Google Scholar]
- 4.Tahir UA, Doros G, Kim JS, Connors LH, Seldin DC, Sam F. Predictors of mortality in light chain cardiac amyloidosis with heart failure. Sci. Rep. 9(1), 8552 (2019). [DOI] [PMC free article] [PubMed] [Google Scholar]
- 5.Gertz MA. Immunoglobulin light chain amyloidosis: 2020 update on diagnosis, prognosis, and treatment. Am. J. Hematol. 95(7), 848–860 (2020). [DOI] [PubMed] [Google Scholar]
- 6.Elsayed M, Usher S, Habib MH et al. Curent updates on the management of AL amyloidosis. J. Hematol. 10(4), 147–161 (2021). [DOI] [PMC free article] [PubMed] [Google Scholar]
- 7.McCausland KL, White MK, Guthrie SD et al. Light chain (AL) amyloidosis: the journey to diagnosis. Patient 11(2), 207–216 (2018). [DOI] [PMC free article] [PubMed] [Google Scholar]; •• Provides a background on the challenges of diagnosing amyloid light chain (AL) amyloidosis, including the clinical and emotional impact of delayed diagnosis, as well as highlights available treatments.
- 8.Grogan M, Dispenzieri A, Gertz MA. Light-chain cardiac amyloidosis: strategies to promote early diagnosis and cardiac response. Heart 103(14), 1065–1072 (2017). [DOI] [PMC free article] [PubMed] [Google Scholar]
- 9.D'Souza A, Myers J, Cusatis R et al. Development of a conceptual model of patient-reported outcomes in light chain amyloidosis: a qualitative study. Qual. Life Res. 31(4), 1083–1092 (2022). [DOI] [PMC free article] [PubMed] [Google Scholar]
- 10.Barrett CD, Dobos K, Liedtke M et al. A changing landscape of mortality for systemic light chain amyloidosis. JACC Heart Fail. 7(11), 958–966 (2019). [DOI] [PubMed] [Google Scholar]
- 11.Kumar S, Callender N, Adekola K, Anderson L, Baljevic M, Campagnaro E. NCCN Clinical Practice Guidelines in Oncology (NCCN Guidelines®): Systemic Light Chain Amyloidosis Version 2. National Comprehensive Cancer Network. 2021, (2021). https://www.nccn.org/guidelines/category_1 [DOI] [PubMed]
- 12.Staron A, Zheng L, Doros G et al. Marked progress in AL amyloidosis survival: a 40-year longitudinal natural history study. Blood Cancer J. 11(8), 139 (2021). [DOI] [PMC free article] [PubMed] [Google Scholar]; •• Results indicate improvement in survival and decreased early mortality among patients with AL amyloidosis; however, the study found that certain subpopulations (e.g., older adults) have higher mortality rates highlighting the need for earlier diagnosis in these populations.
- 13.Lin HM, Gao X, Cooke CE et al. Disease burden of systemic light-chain amyloidosis: a systematic literature review. Curr. Med. Res. Opin. 33(6), 1017–1031 (2017). [DOI] [PubMed] [Google Scholar]; • This systematic literature review highlights the continued need for more research on the clinical and economic burden among patients with AL amyloidosis, including the use of more recent data.
- 14.Quock TP, Yan T, Tieu R, D'Souza A, Broder MS. Untangling the clinical and economic burden of hospitalization for cardiac amyloidosis in the United States. Clin. Outcomes Res. 11, 431–439 (2019). [DOI] [PMC free article] [PubMed] [Google Scholar]; • Provides one of the few estimates of healthcare resource utilization and cost among patients with cardiac amyloidosis.
- 15.Quock TP, Yan T, Chang E, Guthrie S, Broder MS. Healthcare resource utilization and costs in amyloid light-chain amyloidosis: a real-world study using US claims data. J. Comp. Eff. Res. 7(6), 549–559 (2018). [DOI] [PubMed] [Google Scholar]; • Provides one of the few estimates of healthcare resource utilization and costs among patients with AL amyloidosis; however, patients were identified by a general amyloidosis code plus the use of specific medications.
- 16.Hari P, Lin HM, Asche CV et al. Treatment patterns and health care resource utilization among patients with relapsed/refractory systemic light chain amyloidosis. Amyloid 25(1), 1–7 (2018). [DOI] [PubMed] [Google Scholar]
- 17.Premier Applied Sciences®. Premier Healthcare Database White Paper: data that informs and performs [internet]. Premier Inc. (2020). https://learn.premierinc.com/white-papers/premier-healthcare- database-whitepaper [Google Scholar]
- 18.U.S. Bureau of Labor Statistics. Division of Consumer Prices and Price Indexes. “Consumer Price Index” (2021). https://www.bls.gov/cpi/ [Google Scholar]
- 19.Gertz MA. Immunoglobulin light chain amyloidosis: 2016 update on diagnosis, prognosis, and treatment. Am. J. Hematol. 91(9), 947–956 (2016). [DOI] [PubMed] [Google Scholar]
- 20.Sperry BW, Saeed IM, Raza S, Kennedy KF, Hanna M, Spertus JA. Increasing rate of hospital admissions in patients with amyloidosis (from the National Inpatient Sample). Am. J. Cardiol. 124(11), 1765–1769 (2019). [DOI] [PubMed] [Google Scholar]; • Utilizes the National Impatient Sample and found that patients with amyloidosis had longer hospital stays and higher likelihood of dying in the hospital compared with a matched cohort of patients without amyloidosis.
- 21.Hester LL, Gifkins DM, Bellew K et al. Diagnostic delay and characterization of the clinical prodrome in AL amyloidosis among 1523 US adults diagnosed between 2001 and 2019. Eur. J. Haematol. 107(4), 428–435 (2021). [DOI] [PubMed] [Google Scholar]
- 22.Falk RH, Alexander KM, Liao R, Dorbala S. AL (Light-Chain) cardiac amyloidosis. J. Am. Coll. Cardiol. 68(12), 1323–1341 (2016). [DOI] [PubMed] [Google Scholar]
- 23.Kumar S, Dispenzieri A, Lacy MQ et al. Revised prognostic staging system for light chain amyloidosis incorporating cardiac biomarkers and serum free light chain measurements. J. Clin. Oncol. 30(9), 989–995 (2012). [DOI] [PMC free article] [PubMed] [Google Scholar]