Costs and Impact of Disease in Adults with Sickle Cell Disease: A Pilot Study

doi:10.21203/rs.3.rs-2207406/v1

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Research Article

Costs and Impact of Disease in Adults with Sickle Cell Disease: A Pilot Study

https://doi.org/10.21203/rs.3.rs-2207406/v1

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published 22 May, 2024

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Background: The Consensus Study report from National Academy of Science, Engineering, Medicine on September 2020 found a lack of data to characterize sickle cell disease (SCD) related disease burden, outcomes, and the unmet needs. This study’s objectives were to 1) assess the feasibility of collecting data to estimate illness burden in adults with SCD; 2) investigate factors associated with health-related quality of life (HRQoL); and 3) estimate the societal burden.

Method: We recruited 32 adults aged ≥18 years with a diagnosis of SCD who obtained care at two adult SCD specialty centers in the US. We collected data on fatigue, HRQoL measured by the EQ-5D-3L and the Adult Sickle Cell Quality of Life Measurement Information System (ASCQ-Me), and the Work Productivity and Activity Impairment via patient survey. Healthcare utilization was abstracted for the 12 months prior to enrollment using medical chart review. Factors associated with HRQoL scores were assessed by Pearson correlations.

Results: Data collection was feasible, although prescription data could not be used to estimate medication costs. Mean age was 36.7±10.6 (standard deviation) years, 84.4% had hemoglobin (Hb)SS/Sb_thal⁰ disease, and 81.3% reported chronic pain (experiencing pain on ≥3 days per week in the past 6 months). Mean EQ-5D VAS was 63.4. The mean EQ-5D index score was 0.79. ASCQ-Me scores are comparable to the referent population of adults with SCD. The mean fatigue score was 57.9 (range 33.7-75.9) and was negatively correlated with the EQ-5D index score (correlation coefficient r=-0.35, p=0.049), and ASCQ-Me scores, including pain (r=-0.47, p=0.006), sleep (r=-0.38, p=0.03), and emotion (r=-0.79, p<0.0001). The number of hospitalizations was negatively correlated with HRQoL (all p<0.05). Patients who reported chronic pain had significantly lower mean ASCQ-Me sleep scores (48.3±10.1 vs. 57.1±9.1, p=0.04) and EQ-5D index scores (0.72±0.21 vs. 0.89±0.09, p=0.002) than those without chronic pain. Mean estimated annual per-person costs were $51,779 (median: $36,366) for total costs, $7,619 ($0) for indirect costs, and $44,160 ($31,873) for medical costs.

Conclusions: Fatigue, SCD complications, hospitalization and chronic pain negatively impact HRQoL in this small cohort of US adults with SCD. This sample experienced a high economic burden, largely from outpatient doctor visits.

Sickle cell disease

health related quality of life

societal burden

The Consensus Study report from the National Academies of Science, Engineering, Medicine on September 2020 reported that there is lack of data available characterizing SCD related disease burden, outcomes, and unmet needs.
This study demonstrates the feasibility of recruiting adults with SCD to collect data on fatigue, health-related quality of life (HRQoL), the Work Productivity and Activity Impairment via a survey, and healthcare utilization via medical chart review.
These data can be analyzed to explore the factors associated with HRQoL and estimate the SCD societal burden.

Sickle cell disease (SCD) is an inherited red blood cell disorder that inflicts millions of people throughout the world [1]. People with SCD typically suffer from periodic episodes of severe acute and chronic pain. There are many additional SCD complications such as infection, acute chest syndrome (ACS), stroke, renal disease, pulmonary hypertension, leg ulcers, and liver pathology, that have been shown to increase with age [1, 2]. Approximately 1 in 1,900 newborns are affected by SCD [3], resulting in a total of 90,000 to 100,000 affected individuals (~ 60% are adults) in the U.S. [4, 5], primarily Black/African Americans. Advances in the diagnosis and care of SCD have improved the life expectancy of persons with SCD from a US average lifespan of 14 years in 1973 to about 40–60 years at the present time [6, 7]. The mortality rate in the U.S. is low for children with SCD, but increases once they reach adulthood [8, 9].

Pain crisis is the most common debilitating manifestation of SCD, and frequently results in hospital admissions for both children and adults [10]. Increased frequency of pain associated with acute care use (emergency department and inpatient hospital visits) is associated with early death in adults with SCD [11]. Additionally, acute pain crises are associated with significantly impaired health-related quality of life (HRQoL) [12]. Along with the pain crises, other chronic medical complications of SCD, such as stroke and avascular necrosis, can affect social, emotional, cognitive and physical well-being [13, 14]. Avascular necrosis of the long bones (femur, humerus) caused by ischemic bone damage from vaso-occlusion due to SCD is a common co-morbidity, and negatively influences HRQoL, especially in the physical activity and psychosocial domains [15]. Quality of life in persons with SCD is influenced not only by the disease itself, but also by the impairment of intra- and interpersonal relationships due to the emotional and social impact of the disease [16]. To assess HRQoL, the Sickle Cell Epidemiology Study (PiSCES) enrolled 308 individuals with SCD, aged 16 years or older who resided in Virginia. The study found that enrolled persons had much lower HRQoL scores than individuals with asthma, cystic fibrosis, and those on hemodialysis. These lower HRQoL scores were reported on all sub-scales except mental health, including physical function, physical and emotional role function, bodily pain, vitality, social function, and general health [17]. A recent systematic review regarding patient-reported outcomes showed overall HRQoL for adults with SCD was poor and significantly worse in those who are prescribed opioids [19].

The economic burden associated with SCD treatment in the U.S. is high, estimated at greater than $1.1 billion per year in 2009, which corresponds to approximately $16,092 per patient-year [18]. The treatment of SCD, especially complications, result in a costly, lifetime commitment on the part of affected individuals, their providers, hospitals and insurers. Although these cost studies provide insight into the economic burden of SCD [18, 20], the research is now outdated.

HRQoL research is still new in the field of SCD. Prior to the development of the Adult Sickle Cell Quality of Life Measurement Information System (ASCQ-Me) in 2014, there were no disease-specific instruments to measure HRQoL in SCD[21, 22]. Thus, research using ASCQ-Me is still relatively limited. The National Academies of Science, Engineering and Medicine (NASEM)’s Consensus Study report on SCD released in September 2020 found a lack of data to characterize SCD related disease burden, outcomes, and the unmet needs [23]. These findings motivated the present pilot study, which is intended to implement standardized data collection tools from patient self-report and clinical chart review. The objectives of this article are 1) assess the feasibility of collecting data to estimate illness burden in adults with SCD, 2) to investigate the factors associated with HRQoL in SCD and 3) to estimate the societal burden of SCD, including direct and indirect costs.

Design

We used a cross-sectional study design. Patient surveys were developed using validated instruments and questionnaires related to SCD clinical characteristics and treatment. A clinical data collection tool was developed to obtain clinical and healthcare utilization data, based on the experience gained from studies conducted by a national hemophilia research consortium [24, 25]. Institutional review board approvals were obtained from the University of Southern California and Johns Hopkins University. Participants met the following inclusion criteria: 1) age 18 years or older; 2) persons with a diagnosis of SCD (any genotype); 3) persons who have received their SCD care at a specialty SCD treatment center at least one year prior to the enrollment; 4) persons who speak either English or Spanish; and, 5) persons who provide written informed consent. Individuals who were judged by the clinician to be cognitively impaired, or who had any additional blood disorder were excluded.

Recruitment and procedures

Two SCD specialty centers located in the eastern and western United States recruited participants. Eligible participants were identified by the study coordinator during clinic visits or through retrospective clinical chart review. After obtaining informed consent, the study coordinator administered the baseline participant survey and entered data into the web-based RedCap data management system. The survey collected data on sociodemographic and SCD clinical characteristics and treatment, HRQoL, fatigue, work productivity and activity impairment, access to care, physical activity, anxiety and depression. Participants received a $20 gift card for completing the survey. Recruitment began on July 31, 2019, and was completed on August 5, 2020.

The study coordinator abstracted information from the medical chart review using standardized chart abstraction forms developed specifically for this study. Data was abstracted for the period of one year prior to enrollment for clinical characteristics and healthcare utilization. We also abstracted prescription information focusing on antibiotics and opioid products for a six-month period prior to enrollment.

Measures

Demographics. The survey completed by study participants collected sociodemographic data including marital status, employment, education, ethnicity, race, health insurance status, and household income.

Health related quality of life. Adult Sickle Cell Quality of Life Measurement Information System (ASCQ-Me) is a validated disease-specific measure of HRQoL for patients with SCD [21, 22]. The overall measurement system assesses seven different health domains; six of which are assessed through 5-item questionnaires (Emotional Impact, Pain Impact, Sleep Impact, Social Functioning Impact, Stiffness Impact, Pain Episode). The seventh domain is assessed through a 9-item questionnaire (SCD Medical History Checklist). Except for the medical history checklist, each health domain was scored according to the ASCQ-Me user manual and transformed to T-scores [26]. T-scores are standardized to have a mean of 50 and a standard deviation (SD) of 10, where a score of 50 represents the average SCD patient’s HRQoL from a benchmark population of adults with SCD [26]. Higher domain scores represent a more favorable status for the Emotional, Pain, Sleep, Social Functioning, and Stiffness Impacts domains. Lower domain scores represent a more favorable status for the Pain Episode Frequency and Pain Episode Severity scores.

The EQ-5D-3L consists of the EQ-5D descriptive system and EQ visual analogue scale (VAS). The EQ-5D-3L descriptive system comprises the following five dimensions: mobility, self-care, usual activities, pain/discomfort, and anxiety/depression. Each dimension has 3 levels: no problems, some problems, and extreme problems. The US-based valuation algorithm was used to generate a time trade-off (TTO) index score [27].

Fatigue. Patient-Reported Outcomes Measurement Information System (PROMIS®) short form Fatigue 4a is a 4-item instrument measuring fatigue. The total raw score for each participant is translated into a T-score. The T-score rescales the raw score into a standardized score with a mean of 50 and a standard deviation (SD) of 10. Therefore, a person with a T-score of 40 is one SD below the population mean. For negatively-worded concepts like fatigue, a T-score of 60 is one SD worse than the population mean. By comparison, a fatigue T-score of 40 is one SD better than the population mean [28].

Anxiety and Depression. The 7-item Generalized Anxiety Disorder (GAD-7) was used to measure anxiety [29], and the 8-item Patient Health Questionnaire depression scale (PHQ-8) was used to measure depression [30]. If scores on either of these measures reach 10 or greater, it is considered as potentially diagnostic for the respective mental health condition in the general population [29, 30]. GAD-7 and PHQ had been used previously in adults SCD study to measure the symptoms of depression and anxiety [31].

Chronic Pain and Disease Severity. A question worded “Do you experience pain on 3 or more days a week in the past 6 months?” was used to measure chronic pain. The ASQ-Me medical history checklist (MHC) sums nine SCD complications and treatment history checked. Score cut-offs (low, medium and high) for the SCD MHC are based on tertiles of the distribution of scores. Cutoffs for low, medium, and high groups were SCD-MHC scores less than 2, equal to 2, and greater than 2, respectively [32]. Due to our small sample size, we combined the low and medium groups.

Opioid used. Medical chart review documented opioid medication prescriptions for 6 months prior to enrollment. Both short and long-acting opioid prescriptions were captured in these data.

Direct costs. Annual healthcare utilization data were obtained from medical charts. The number of hospital admissions, length of stay (LOS) and primary diagnosis recorded in the charts were used to calculate inpatient costs. Direct SCD-related healthcare costs were determined by multiplying measured units of healthcare utilization by the representative unit price associated with each service [33]. SCD treatments received outside the patients’ designated treatment center and non-medical direct costs (e.g. transportation to a healthcare provider) were not considered. Inpatient cost was estimated based on the mean costs associated with diagnosis of SCD with crisis from 2017 Agency for Healthcare Research and Quality’s (AHRQ’s) Healthcare Cost and Utilization Project National Inpatient Sample (HCUPNIS) since 68% of persons in the sample who were hospitalized had a diagnosis of acute pain crisis [34]. The cost of outpatient or doctor visits and emergency department (ED) visits were based on the Medical Expenditure Panel Survey (MEPS) reports latest available data for 2018 [35]. Outpatient or doctor visits include annual multidisciplinary comprehensive visits as well as acute provider (physician and nursing), physical therapy, social work/psychology, genetic counseling, outpatient procedure, transfusion, and other visits. Total direct medical costs were summed from outpatient doctor visits, ED visits, and hospitalizations. Since individuals with SCD were prescribed many medications during the 6-month period prior to enrollment, assessments of fill rate were not available. Since the medical chart records may not include inpatient prescriptions, we decided to exclude prescription cost data due to the likelihood of incomplete reporting.

Indirect costs. Indirect costs were imputed using the human capital approach [36], in which productivity loss is measured in terms of lost earnings of participants, using wages as a proxy measure for the output of work time. Indirect costs include lost wages from missed work for employed participants and lost wages due to working part-time or being unemployed because of SCD. Missed work-days due to SCD were calculated from the patient survey of Work Productivity and Activity Impairment: Specific Health Problem (WPAI:SHP) [37]. Average hourly earnings for 2018 were obtained from the US Department of Labor Statistics [38]. Total costs included both direct and indirect costs and were presented as 2018 costs.

Statistical Analysis

Descriptive analyses were performed, and results were compared to the general U.S. population where available. Descriptive statistics, such as frequencies and proportions (for categorical variables) and means, standard deviations, medians, and ranges (for continuous variables), were used to describe the sample in terms of patient characteristics, HRQoL, fatigue, WPAI scores, and healthcare utilization. Descriptive statistics were also used to describe participants’ clinical characteristics and treatments. The factors associated with HRQoL scores were assessed by Pearson correlation, or from Wilcoxon nonparametric tests for two group differences.

Participants’ Characteristics

We recruited and collected data from 32 adults aged ≥ 18 years. Mean age was 36.7 ± 10.6 (standard deviation) years, and 65.6% were female (Table 1). Half of the sample reported working at a job or business in the week prior to take the survey, 50% had completed a 4-year college degree or higher, and 31.3% earned $25,000 or less annual household income, 84.4% of the participants were Black or African American, and 6.2% of the overall sample reported that they were of Hispanic, Latino or Spanish origin. Of 31 participants who completed the insurance question, 6.5% reported that they did not have any health insurance, and 93.5% had some coverage through public and private sources, although 23.3% reported having difficulty in finding adequate health insurance. More than 10% of respondents reported that they or their spouse needed to make work-related adjustments to obtain or maintain health insurance due to SCD.

Table 1

Participants’ Sociodemographic Characteristics
Variable	Frequency	Percent
Gender
Male	11	34.38
Female	21	65.62
Marital Status
Single, divorced, separated	23	71.87
Married, with a partner	9	28.13
Employment
Working at a job or business	16	50.00
With a job or business but not at work	4	12.50
Looking for work	1	3.13
Not working at a job or business	9	28.13
Choose not to answer	2	6.25
Education level
Less than high school diploma	2	6.25
High school diploma/equivalency (e.g. GED)	7	21.88
Less than bachelor's degree (< 4-year college)	7	21.88
More than bachelor's (4-year college) degree	16	50.00
Household income in the last 12 months
Less than or equal to $25,000 per year	10	31.25
More than $25,000 per year	17	53.14
Don't know	1	3.13
Choose not to answer	4	12.50
Hispanic, Latino or Spanish origin
Yes	2	6.25
No	30	93.75
Race
Black or African American	27	84.38
Other, specify*	5	15.63
Health insurance type†
No insurance	2	6.45
Public	16	51.61
Private	11	35.48
Public & private	2	6.45
Difficulty in finding adequate health insurance*
Yes	7	23.3
No	21	70.0
Don’t know	2	6.7
Note: Data were obtained from participants’ survey.
*Other race included Afro-Latina, Middle Eastern, West Indian, and multiple race.
†Variables have missing data due to under-reporting. Total sample does not sum up to 32 due to missing data.

The chart review documented that 78.1% of the sample had been diagnosed with hemoglobin (Hb) SS disease, 15.6% had Hb SC disease, and 6.3% were Hb Sβ_thal⁰ (Table 2). Among the sample, 53.1% were on hydroxyurea, 31.3% have been prescribed prophylactic penicillin or other antibiotics to prevent infection, 9.4% participants have been prescribed a treatment for continuous positive airway pressure (CPAP) machine in the last 12 months. In addition, 31.3% participants received a red blood cell transfusion to treat an acute complication, while 12.5% were on chronic transfusion therapy. Chart review of prescriptions from the 6 months prior to enrollment showed that of all prescription scripts written of 483 records, the most commonly prescribed drugs were short-acting opioid products (62.9%), followed by long-acting opioid products (14.1%), antibiotics (12.0%), hydroxyurea (10.1%), and L-Glutamine (0.8%) (Table 2).

Table 2

Participants’ clinical characteristics from clinical chart review
Variable	Frequency	Percent
Sickle cell disease type
Hemoglobin SS disease	25	78.13
Hemoglobin SC disease	5	15.63
Hemoglobin SB 0 (Beta-zero) thalassemia	2	6.25
Received a red blood cell transfusion to treat an acute complication	10	31.25
Received chronic transfusion	4	12.50
Participant has been prescribed the following treatment
Folic acid	29	90.6
Hydroxyurea	17	53.1
Prophylactic penicillin or other antibiotics to prevent infection	10	31.30
Iron chelation medication	9	28.10
Continuous positive airway pressure (CPAP) machine	3	9.40
Most common prescribed drugs from 483 records†
Short-Acting opioid products	304	62.94
Long-Acting opioid products	68	14.08
Antibiotics	58	12.01
Hydroxyurea	49	10.14
L-Glutamine	4	0.83
Most common diagnosis for ED visits‡
Acute pain crisis	65	89.04
Acute chest syndrome	1	1.37
Pneumonia	1	1.37
Other	6	8.22
Most common diagnosis for hospitalization from 73 records‡
Acute pain crisis	50	68.49
Pneumonia	3	4.11
Acute chest syndrome	2	2.74
Heart disease (heart failure)	1	1.37
Other	17	23.29
Note: Data were obtained from clinical chart review for 12 months prior to enrollment.
†Analysis was performed based on chart review for 483 prescription records during 6-months prior to the enrollment period.
‡Analysis was performed based on chart review for 73 records for during 12 months prior to enrollment.

Health Related Quality of Life

In our sample, the mean (standard deviation (SD), range) reported EQ-5D VAS was 63.4 (22.6, 10.0–95.0), which is 18.4 points lower than the US population mean of 81.8 for the 35–44 age group [39]. The mean reported EQ-index was 0.79 (0.20, 0.26-1.0), which is lower than US 35–44 age group population norm of 0.853 [39]. The reported ASCQ-Me scores were comparable to the mean scores of SCD patients in the ASCQ-Me field test sample [26]. The mean fatigue T-score was 57.9 (SD = 11.5), which is worse than the US population average for this age group by 7.9 points [28].

Mean hemoglobin was 9.24 (1.87, 6.3–13.4). Hemoglobin was not correlated with fatigue score or HRQoL scores, all p > 0.06. Fatigue score was negatively correlated with EQ-5D index score (correlation coefficient r=-0.35, p = 0.049), ASCQ-Me scores, including pain (r=-0.47, p = 0.006), sleep (r=-0.38, p = 0.03), emotion (r=-0.79, p < 0.0001), and social (r=-0.61, p = 0.0002) (Table 3). The sum of the medical history checklist was negatively correlated with EQ-5D VAS (r=-0.53, p = 0.002) and index scores (r=-0.50, p = 0.004), ASCQ-Me pain (r=-0.41, p = 0.02), and stiffness (r=-0.63, p = 0.0001). There was no correlation between number of ED visits with HRQoL scores. The number of hospitalizations was negatively correlated with EQ-5D index score (r=-0.56, p < 0.001), ASCQ-Me sleep (r=-0.64, p < 0.0001), emotion scores (r=-0.38, p = 0.03), stiffness (r=-0.36, p = 0.04), and pain (r=-0.35, p = 0.048).

Table 3

Correlation of health-related quality of life scores with hemoglobin, medical history checklist, emergency room visits, and hospitalization
HRQoL	Hemoglobin	Fatigue	ASCQ-Me MHC	ED visits	Hospitalization
EQ-5D VAS Correlation Coefficients P value	0.03 0.89	-0.32 0.07	-0.53 0.002	0.21 0.25	-0.05 0.79
EQ-5D index score Correlation Coefficients P value	-0.06 0.73	-0.35 0.049	-0.50 0.004	-0.18 0.32	-0.56 0.0009
ASCQ-Me pain Correlation Coefficients P value	0.16 0.39	-0.47 0.006	-0.41 0.02	-0.12 0.50	-0.35 0.05
ASCQ-Me stiffness Correlation Coefficients P value	-0.002 0.99	-0.22 0.23	-0.63 0.0001	0.07 0.69	-0.36 0.04
ASCQ-Me sleep Correlation Coefficients P value	0.06 0.76	-0.39 0.03	-0.30 0.09	-0.17 0.36	-0.64 < .0001
ASCQ-Me emotion Correlation Coefficients P value	0.18 0.32	-0.79 < .0001	-0.29 0.11	-0.08 0.67	-0.38 0.03
ASCQ-Me social Correlation Coefficients P value	0.002 0.99	-0.61 0.0002	-0.31 0.0795	-0.07 0.72	-0.33 0.07
ASCQ-Me pain episode frequency Correlation Coefficients P value	0.25 0.18	0.45 0.01	0.31 0.09	0.24 0.18	0.32 0.08
ASCQ-Me pain episode severity Correlation Coefficients P value	-0.33 0.06	0.32 0.08	0.18 0.32	0.13 0.48	0.23 0.20
Abbreviations: N, number, represent sample size; ASCO-Me, Adult Sickle Cell Quality of Life Measurement Information System; MHC, medical history checklist; ED, emergency department; EQ-5D VAS, EuroQol visual analogue scale.

Table 4 showed the HRQoL scores stratified by status on medical history checklist, emergency department visits, hospitalization, opioid use, and chronic pain. Except for ASCQ-Me pain episode severity and fatigue score, the patients with MHC > 2 had significantly lower mean ASCQ-Me and EQ-5D VAS and index scores, than those with MHC ≤ 2, all p < 0.01. HRQoL scores were not significantly different between the patients who had ED visits and those without ED visits. However, for those with ED visits, mean pain episode severity scores were significantly higher than for without ED visits (51.61 ± 4.28 vs. 45.28 ± 9.64, p = 0.03). Compared to those without hospitalization, participants who were hospitalized had significantly lower HRQoL scores, higher pain episode frequency or severity scores, or higher fatigue scores (all p < 0.05). Individuals who were prescribed opioid medications for pain anytime over the course of the 6-month chart review had a significantly higher mean ASCQ-Me pain episode frequency score (53.19 ± 9.26 vs. 40.19 ± 13.24, p = 0.008) than those without prescriptions of opioid medications. Participants who reported chronic pain (81% of sample) had significantly lower mean ASCQ-Me pain and social scores (47.96 ± 7.00 vs. 62.47 ± 3.27, p < 0.0001 and 48.08 ± 8.09 vs 58.30 ± 6.73, p = 0.008, respectively). They also had higher pain episode frequency and pain severity scores (50.86 ± 6.45 vs. 39.04 ± 6.22, p < 0.05 and 50.86 ± 6.45 vs 39.04 ± 6.22, p = 0.0003, respectively) than those without chronic pain.

Table 4

HRQoL scores stratify by status on medical history checklist, emergency department visits, hospitalization, used opioid, and chronic pain
Variable		All (n = 32)	MHC		P value*	ED Visits		P value	Hospitalizations		P value*	Used opioid		P value*	Chronic pain		P value*
Variable		All (n = 32)	MHC ≤ 2 (N = 18))	MHC > 2 (N = 14)	P value*	No (N = 15)	Yes (N = 17)	P value	No (N = 16)	Yes (N = 16)	P value*	No (N = 6)	Yes (N = 26)	P value*	No (N = 6)	Yes (N = 26)	P value*
EQ VAS	Mean	63.41	73.61	50.29	0.005	61.33	65.24	0.63	66.56	60.25	0.43	63.33	63.42	0.99	72.50	61.31	0.28
EQ VAS	Std	22.58	14.55	24.68	0.005	22.44	23.22	0.63	18.82	26.03	0.43	17.22	23.93	0.99	12.94	23.96	0.28
EQ Index	Mean	0.75	0.87	0.60	0.0005	0.79	0.72	0.30	0.83	0.68	0.03	0.78	0.74	0.69	0.89	0.72	0.06
EQ Index	Std	0.20	0.10	0.21	0.0005	0.17	0.23	0.30	0.15	0.23	0.03	0.27	0.19	0.69	0.09	0.21	0.06
Emotion†	Mean	48.88	52.40	44.36	0.02	49.15	48.65	0.89	53.93	43.83	0.002	50.63	48.48	0.63	54.88	47.50	0.10
Emotion†	Std	9.90	8.02	10.52	0.02	10.88	9.29	0.89	8.71	8.52	0.002	11.73	9.66	0.63	8.96	9.74	0.10
Pain†	Mean	50.68	53.73	46.75	0.02	53.09	48.55	0.14	53.04	48.31	0.12	52.92	50.16	0.49	62.47	47.96	< 0.0001
Pain†	Std	8.63	7.43	8.70	0.02	7.99	8.83	0.14	8.57	8.27	0.12	9.86	8.44	0.49	3.27	7.00	< 0.0001
Sleep†	Mean	49.98	54.72	43.87	0.002	52.61	47.65	0.18	54.95	45.00	0.005	49.43	50.10	0.89	57.10	48.33	0.06
Sleep†	Std	10.37	8.61	9.41	0.002	7.88	11.91	0.18	7.91	10.34	0.005	17.33	8.56	0.89	9.14	10.09	0.06
Social†	Mean	49.99	52.52	46.74	0.06	50.04	49.95	0.98	53.41	46.58	0.02	56.02	48.60	0.06	58.30	48.08	0.008
Social†	Std	8.74	9.30	7.01	0.06	9.42	8.40	0.98	9.57	6.45	0.02	9.79	8.06	0.06	6.73	8.09	0.008
Stiffness†	Mean	50.35	55.56	43.65	0.0003	52.10	48.80	0.36	51.89	48.81	0.39	53.37	49.65	0.42	57.02	48.81	0.07
Stiffness†	Std	10.03	7.85	8.57	0.0003	9.17	10.76	0.36	10.18	9.95	0.39	11.69	9.73	0.42	5.79	10.24	0.07
PEF†	Mean	50.75	47.31	55.18	0.046	47.44	53.68	0.12	46.99	54.52	0.05	40.19	53.19	0.008	42.78	52.59	< 0.05
PEF†	Std	11.14	12.02	8.33	0.046	12.54	9.13	0.12	12.73	7.99	0.05	13.24	9.26	0.008	12.45	10.20	< 0.05
PES†	Mean	48.64	47.36	50.29	0.30	45.28	51.61	0.03	44.99	52.30	0.006	47.23	48.97	0.09	39.04	50.86	0.0003
PES†	Std	7.86	8.97	6.08	0.30	9.64	4.28	0.03	7.73	6.28	0.006	5.21	8.40	0.09	6.22	6.45	0.0003
Fatigue	Mean	57.89	54.94	61.69	0.10	58.86	57.04	0.66	54.58	61.21	0.10	49.95	59.73	0.06	49.78	59.77	0.05
Fatigue	Std	11.48	11.23	11.03	0.10	11.83	11.45	0.66	11.70	10.57	0.10	14.10	10.25	0.06	15.63	9.75	0.05
Abbreviations: MHC, medical history checklist; ED, emergency department; EQ VAS, EuroQol visual analogue scale; Std, standard deviation; PEF, pain episodes frequency; PES, pain episodes severity.
*P values were calculated from Student T-test. †Adult Sickle Cell Quality of Life Measurement Information System (ASCQ-Me) health domains includes emotional impact, pain impact, sleep impact, social functioning impact, stiffness impact, pain episodes.

Anxiety and Depression

In our sample, 81.3% met the anxiety threshold and 68.8% of participants met the depression threshold with a score ≥ 10 of measure of GAD 7 and PHQ 8, respectively.

Work Productivity and Activity Impairment (WPAI)

Nineteen participants (59.4%) reported that they were currently employed (working for pay). Among these, the mean work time missed due to SCD problems was 26.2%±34.5% of the time on average. Impairment while working due to SCD was 42.9%±29.3% and on average, overall work impairment was 46.8%±31.4%. Mean daily activity impairment due to SCD problems was 43.1%±27.9%.

Healthcare Utilization and Costs

The one-year chart review revealed a total of 73 ED visits and 73 hospitalizations for all 32 participants. The most common reason for ED visits or hospitalizations was acute pain crisis: 89% for ED visits and 68% for hospitalizations.

Table 5 showed the analytic results of healthcare utilization and costs. The mean annual number of visits included outpatient or doctor visits (14.3 ± 11.3), ED visits (2.3 ± 4.8) and hospitalizations (2.3 ± 3.7). Mean outpatient or doctor visit cost per person per year was $21,028±$16,530, while ER cost was $3,499±$7,323 and hospitalization cost was $19,633±$31,847. The mean total direct medical care cost was $44,160±$44,262 and the estimated mean annual indirect cost from lost work was $7,619±$16,214. The estimated mean total cost (the sum of direct and indirect costs) was $51,779±$50,278.

Table 5

Mean annual healthcare utilization and costs in persons with Sickle Cell Disease
Variable	Minimum	Maximum	Median	Mean	Std Dev
Number of outpatient/doctor visits Number of ED visits Number of hospitalizations Number of prescriptions*	0.0 0.0 0.0 0.0	46.0 21.0 16.0 72.0	11.5 1.0 0.5 7.5	14.3 2.3 2.3 15.1	11.3 4.8 3.7 18.5
Outpatient/doctor visit costs ($) ER visit costs ($) Hospitalization costs ($) Indirect costs/year ($) Total medical costs ($) Total costs ($)	0.0 0.0 0.0 0.0 0.0 0.0	67,436.0 32,214.0 137,701.9 563,68.0 208,205.9 208,205.9	16,859.0 1,534.0 4,303.2 0.0 31,872.7 36,365.6	21,027.9 3,499.4 19,633.3 7,618.5 44,160.7 51,779.1	16,529.8 7,323.0 31,846.5 16,213.6 44,262.2 50,277.9
Abbreviations: N, number, represent sample size; ER, emergency room; Std Dev, standard deviation.

Analyses of data collected for this project demonstrate the feasibility of collecting data to evaluate HRQoL and burden of illness in persons with SCD using validated, standardized data collection tools. The data collection from the current study provides important insights into the emotional and social disease burden associated with SCD, as measured in a pilot sample of patients treated at two comprehensive sickle cell centers.

Many individuals with SCD suffer from significant pain. As reported elsewhere [40, 41], the majority of SCD patients experience vaso-occlusive crises (VOC), otherwise known as sickle cell pain crises, and as many as 30% of patients experience chronic pain. In our sample, about 91% of participants reported that they used prescription pain medications to treat SCD, and 81% reported having chronic pain, both of which are higher than reported in other studies.[40, 41] Fifty percent of our sample had required emergency department visits or hospitalization due to their SCD (the majority of these visits due to acute pain crisis and not including infusion center treatment) in the last 12 months. The data analyses indicated that fatigue, SCD medical history, hospitalization and chronic pain negatively impact HRQoL. Thus, while pain is a major factor in HRQoL, fatigue is also important and should be considered in determining treatment. In this study fatigue was not correlated with hemoglobin levels, which may be due to sample size. Further investigation into the causes of fatigue in this population is needed. Based on these data, it is possible that treatment strategies to prevent SCD complications may reduce pain, fatigue, and hospitalization, thus improving HRQoL.

The strength of an association between two variables can be described using correlation coefficient. Absolute magnitude of the correlation coefficient of 0-0.39 indicate negligible to weak correlation; 0.40–0.69 indicate moderate correlation, and 0.70-1.0 indicate strong correlation [42]. Although our pilot study sample is small, the ASCQ-Me pain domain displayed statistically significant moderate correlations with the fatigue score, ASCQ-Me MHC, and number of hospitalizations. The stiffness impact score was moderately correlated with MHC, and was weakly correlated with the number of hospitalizations. The sleep score was weakly correlated with fatigue and moderately correlated with the number of hospitalizations. The emotion and social scores were moderately correlated with the fatigue score. These results provide some indication that ASCQ-Me domain measures were correlated with SCD severity and its associated healthcare utilization.

The EQ-5D-3L is a generic instrument widely used to measure HRQoL. The EQ-5D VAS and index score were both moderately correlated with the ASCQ-Me MHC. Like the ASCQ-Me, the EQ-5D index score was lower in persons who reported chronic pain than in those without chronic pain. In this study, the EQ-5D index score was associated with SCD-related conditions. Using a generic HRQoL measure like the EQ-5D allows a comparison of SCD patients’ wellbeing with the general U.S. population, and with populations affected by other disease conditions. Further research is needed to validate use of the EQ-5D in the SCD population.

The anxiety and depression rates in our sample were much higher than that among the general US population in 2019, who reported moderate/severe symptoms of anxiety (score GAD 7 ≥ 10) [43] at a rate of 7.1%, and depression (score PHQ 8 ≥ 10) at a rate of 7.0% [44]. It was also much higher than rates reported in a population of adults with SCD who participated in the National Survey of American Life survey which used structured diagnostic interviews and DSM-IV criteria and found that 24.7% of subjects had an anxiety disorder and 38.8% had a mood disorder [45]. Fatigue and pain can lead to anxiety and depressive disorders [46]. It is likely that the use of PHQ and GAD 78 screening tools led to an overreporting of both depression and anxiety in this study. As both somatic and psychological disturbances are considered to interfere with patients’ HRQoL [46], further investigation of the role of mental health disorders on outcomes is needed.

Persons with SCD experienced high annual medical costs and loss of work productivity. We should note that infusion procedures were included in outpatient visits. Outpatient and doctor visits comprised the largest portion of medical costs (approximately 50%). Based on our analyses, SCD patients used many prescription medications, including opioid products. The extensive use of prescription medications makes it difficult to abstract prescription information manually to estimate prescription costs. Therefore, we have not included prescription costs in estimating the total burden of illness. This pilot work illustrates the importance of using other sources, such as administrative data, to evaluate drug use costs in the SCD population.

This was a convenience sample. Thus, the patients who have the most clinic visits are those most likely to be enrolled. In addition, there is insufficient power for some group comparisons because this was a pilot study of a small sample. Furthermore, since the current data collection effort included only adults with SCD, additional studies should assess children with SCD in order to fully understand the disease burden for the entire SCD population.

The data collection tools developed from this pilot study illustrate the feasibility of evaluating HRQoL and economic burden for persons with SCD, laying the foundation for better characterization of important health and economic impacts in this understudied population. Further, these data continue to highlight the need for a national, longitudinal clinical registry to track outcomes. This should include patient-reported outcomes in order to enhance our understanding of the disease course, and the emotional/social implications of the disease and their relationship with biologic findings. These data provide some evidence that fatigue, SCD complications, hospitalization, and chronic pain negatively impact HRQoL. Similarly, our data demonstrates that SCD is associated with high economic burden, largely from direct medical costs incurred through outpatient and transfusion visits. While these data are derived from limited sample sizes, they suggest specific areas where SCD healthcare teams, SCD community-based organizations, affected individuals and caregivers can begin to create interventions to improve the health-related quality of life of affected individuals. These data add to emerging evidence that quantifies SCD’s economic burdens, vital to setting baselines for future policy interventions that could address innovations to reduce costs while retaining health care quality.

SCD, Sickle cell disease

HRQoL, Health-related quality of life

ASCQ-Me, Adult Sickle Cell Quality of Life Measurement Information System

NASEM, National Academies of Science, Engineering and Medicine

SD, standard deviation

VAS, visual analogue scale

TTO, time trade-off

GAD, generalized anxiety disorder

PHQ, patient health questionnaire

MHC, medical history checklist

LOS, length of stay

AHRQ, Agency for Healthcare Research and Quality

HCUPNIS, Healthcare Cost and utilization Project National Inpatient Sample

ED, emergency department

MEPS, Medical Expenditure Panel Survey

WPAI, Work Productivity and Activity Impairment

CPAP, continuous positive airway pressure

HUGS, Hematology Utilization Group Studies

Ethics approval and consent to participate

The study was approved by the institutional review board from the University of Southern California and Johns Hopkins University. Participating SCD treatment centers obtained informed consent from all study participants.

Consent for publication

This manuscript contains no individual person’s data in any form.

Availability of data and materials

The datasets generated and/or analyzed for the current study are available from the Principal Investigator, Dr. Michael B. Nichol ([email protected]) on reasonable request.

Competing interests

Sophie Lanzkron received research funds from Global Blood Therapeutics, Shire, Novartis, CSL-Behring. She also received consult fee from ICON, Bluebird Bio, Magenta, Novartis, Novo-Nordisk and Pfizer. Joanne Wu received financial support through the project funding provided by Pfizer Inc, and Global Blood Therapeutics. Randall Curtis received a consultant fee from USC through the project funding provided by Pfizer. He also received consultant fee from Bayer, and Novo Nordisk. Michael B. Nichol is the principal investigator for the HUGS research group and has received grant funding from multiple sources including Pfizer, Genentech Inc., Baxalta US Inc., Bannockburn, IL (a Takeda Company), Octapharma, CSL Behring, Global Blood Therapeutics, and Novo Nordisk. Nicole Crook, Sarah Hussain, Derek Robertson, Judith Baker, Diane Nugent, Amit Soni, Jonathan C. Roberts, Megan Ullman, and Julie Kanter have no significant conflicts of interest associated with this project to declare.

Funding

The study was supported by Investigator-Initiated Research agreements between USC and Pfizer Inc, and USC and Global Blood Therapeutics.

Authors’ contributions

MN was the lead principal investigator (PI), and SL, AS were Co-PIs on the study. MN, JW, SL, NC conceived the project and methodological approach and data collection tools development. SH and NC collected the data. JW, MN developed the key parameters and analysis approach, interpreted the data, and drafted the manuscript. JW analyzed the data. All authors edited and revised the manuscript. All authors approved the final manuscript.

Acknowledgements

The members of the study group: University of Southern California: Michael B. Nichol, PhD (Principal investigator (PI)), Joanne Wu, MS, Steven Carrasco, MPH. Johns Hopkins University: Sophie Lanzkron, MD (site PI), Sarah Hussain, MBBS, MS. Center for Inherited Blood Disorders (CIBD): Amit Soni, MD (site PI), Nicole Crook, RN, Rajalakshmi Ganapathy.

We thank Mary Brown from Sickle Cell Disease Foundation, who is the member of HUGS SCD Advisory Group for her advice and contributions.

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Costs and Impact of Disease in Adults with Sickle Cell Disease: A Pilot Study

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Abstract

Key Messages

Introduction

Methods

Design

Recruitment and procedures

Measures

Statistical Analysis

Results

Participants’ Characteristics

Health Related Quality of Life

Anxiety and Depression

Work Productivity and Activity Impairment (WPAI)

Healthcare Utilization and Costs

Discussion

Limitations

Conclusions

Abbreviations

Declarations

References

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