Next Article in Journal
Discriminative Evaluation of Sarcopenic Dysphagia Using Handgrip Strength or Calf Circumference in Patients with Dysphagia Using the Area under the Receiver Operating Characteristic Curve
Next Article in Special Issue
Early Strokes Are Associated with More Global Cognitive Deficits in Adults with Sickle Cell Disease
Previous Article in Journal
Differential Effects of Patient Navigation across Latent Profiles of Barriers to Care among People Living with HIV and Comorbid Conditions
Previous Article in Special Issue
Echocardiographic Evaluation in Paediatric Sickle Cell Disease Patients: A Pilot Study
 
 
Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 
Journals
JCM
Volume 12
Issue 1
10.3390/jcm12010117
jcm-logo
Submit to this Journal Review for this Journal Propose a Special Issue
► Article Menu

Article Menu

share Share announcement Help format_quote Cite question_answer Discuss in SciProfiles thumb_up
...
Endorse textsms
...
Comment
first_page
settings
Order Article Reprints
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Article

Real-World Evidence on Disease Burden and Economic Impact of Sickle Cell Disease in Italy

by
Lucia De Franceschi
1,*,
Chiara Castiglioni
2,
Claudia Condorelli
2,
Diletta Valsecchi
2,
Eleonora Premoli
2,
Carina Fiocchi
2,
Valentina Perrone
3,
Luca Degli Esposti
3,
Gian Luca Forni
4 and
on behalf of the GREATalyS Study Group
†
1
Department of Medicine, University of Verona, 37129 Verona, Italy
2
Novartis Farma S.p.A., 20154 Milan, Italy
3
CliCon S.r.l. Società Benefit Health, Economics & Outcomes Research, 40137 Bologna, Italy
4
Centro della Microcitemia e Anemie Congenite, Ospedale Galliera, 16128 Genoa, Italy
*
Author to whom correspondence should be addressed.
†
GREATalyS Study Group member are listed in Acknowledgments.
J. Clin. Med. 2023, 12(1), 117; https://doi.org/10.3390/jcm12010117
Submission received: 14 November 2022 / Revised: 5 December 2022 / Accepted: 21 December 2022 / Published: 23 December 2022
(This article belongs to the Special Issue Acute and Chronic Sickle Cell Disease: Causes, Consequences, and Treatment)
Browse Figures
Review Reports Versions Notes

Abstract

:
A real-world analysis was conducted in Italy among sickle cell disease (SCD) patients to evaluate the epidemiology of SCD, describe patients’ characteristics and the therapeutic and economic burden. A retrospective analysis of administrative databases of various Italian entities was carried out. All patients with ≥1 hospitalization with SCD diagnosis were included from 01/2010-12/2017 (up to 12/2018 for epidemiologic analysis). The index date corresponded to the first SCD diagnosis. In 2018, SCD incidence rate was 0.93/100,000, the prevalence was estimated at 13.1/100,000. Overall, 1816 patients were included. During the 1st year of follow-up, 50.7% of patients had one all-cause hospitalization, 27.8% had 2, 10.4% had 3, and 11.1% had ≥4. Over follow-up, 6.1–7.2% of patients were treated with SCD-specific, 58.4–69.4% with SCD-related, 60.7–71.3% with SCD-complications-related drugs. Mean annual number per patient of overall treatments was 14.9 ± 13.9, hospitalizations 1.1 ± 1.1, and out-patient services 5.3 ± 7.6. The total mean direct cost per patient was EUR 7918/year (EUR 2201 drugs, EUR 3320 hospitalizations, and EUR 2397 out-patient services). The results from this real-world analysis showed a high disease burden for SCD patients with multiple hospitalizations during the follow-up. High healthcare resource utilization and costs were associated with patient’ management and were most likely underestimated since indirect costs and Emergency Room admissions were not included.

1. Introduction

Sickle Cell Disease (SCD) is a worldwide distributed hereditary red cell disorder recognized by WHO as an emerging global health problem. SCD is caused by a point mutation occurring in the β-globin gene, resulting in the synthesis of pathological hemoglobin S (HbS) [1]. This protein polymerizes upon deoxygenation, causing red blood cell sickling and dehydration [2,3]. The vaso-occlusion process and the pathophysiological aspects of the disease is the result of more complex interactions between the pro-adhesive sickle cells, neutrophils, and endothelium that trigger a pro-inflammatory environment [3,4,5,6]. The main clinical manifestations of SCD are chronic hemolytic anemia and acute vaso-occlusive crisis (VOCs), which are associated with severe pain and amplified inflammatory response, resulting in end organ damage [7]. This still impacts morbidity and mortality of patients with SCD [8], as well as patients’ quality of life [7].
The therapeutic management of SCD span in the following main areas [9]: supportive care as newborn screening; the prevention of infection (penicillin prophylaxis, vaccination); the management of acute and chronic complications; and disease-modifying therapies specific for SCD, such as hydroxyurea and more recently Crizanlizumab, Voxelotor and L-Glutamine [9,10,11]. Although the therapeutic portfolio of SCD is increasing, the benefits of novel therapeutic options on disease natural history still needs to be established. This highlights the importance of real-life studies on SCD clinical management and outcomes. In addition, the generation of knowledge on disease burden in different care settings might help (i) to prevent undertreatment of adult SCD patients with increased risk of severe organ dysfunction and (ii) to reduce costs linked to SCD patients’ frequent emergency department visits [12,13,14].
In Europe, SCD is now regarded as the paradigm of immigration hematology [15]. Indeed, SCD was originally limited to sub-Saharan African areas; however, migration fluxes have significantly impacted SCD distribution and increased its prevalence in areas where it was previously uncommon [16]. In this scenario, recent immigration from Africa, South America, and the Balkans has changed the geographic profile of SCD, thus also becoming an emerging public health burden in Italy, enlarging the endemic SCD population and with an estimate of 3–5-fold increased prevalence over the last years [9].
A national register of hemoglobinopathies was approved in 2017 in Italy, but it has not yet been fully populated with clinical data of all patients with hemoglobinopathies cared for by the national territory [17]. Therefore, we designed a retrospective observational study, the GREATALYS (Generating Real world Evidence Across Italy In SCD, study code CSEG101AIT01), on Italian health claims data to estimate the epidemiologic burden and the economic impact of SCD in Italy. The main purpose was to evaluate the epidemiology of SCD in Italy in terms of prevalence and incidence rate and to provide an estimation on the number of patients currently living with SCD. The secondary aims were to describe the demographic characteristics of patients affected by SCD and to analyze the patients’ journey in terms of therapeutic pathways, disease features, and economic insights in clinical practice setting by using real-world data.

2. Materials and Methods

2.1. Data Source

In Italy, healthcare is provided by a public system, known as the National Health System (NHS), which is based on the principle of universal coverage for all citizens and residents, namely health-assisted subjects. This study is based on existing data linked and extracted from administrative databases used by the Italian NHS for the reimbursement of healthcare services of two Regional and fifteen Local Health Units geographically distributed throughout the Italian territory, covering approximately 15.3 million health-assisted subjects (about 25% of the whole Italian population). According to the objectives of the analysis, the following databases and related items were used: beneficiaries’ database, which contains all demographic data for patients in analysis; pharmaceutical databases that collect data on all drugs supplied through Anatomical Therapeutic Chemical code (ATC), marketing authorization holder code, the number of packages and number of units per package, unit cost per package, and prescription date; hospitalization database that includes all hospitalization data with discharge diagnosis codes classified according to the International Classification of Diseases, Ninth Revision, Clinical Modification (ICD-9-CM), diagnosis Related Group (DRG) and DRG-related charge (provided by Health System); outpatient specialist services database, which contains date of prescription, type, and description activity of diagnostic tests and visits for patients in analysis and laboratory test or specialist visit charge. Emergency Room, “Temporarily Present Foreigner” codes, and refugees were not recorded in this study. In order to guarantee patient privacy, each beneficiary was assigned an anonymous univocal numeric code (patient ID) by the Region/Local Health Units that allowed electronic linkage between databases. The anonymous code of the patient ensures the anonymity of the extracted data in full compliance with EU Data Privacy Regulation 2016/679 (“GDPR”) and Italian D.lgs. n. 196/2003, as amended by D.lgs. n. 101/2018. All the results of the analyses were produced as aggregated summaries, which could not be connected, either directly or indirectly, to individual patients. Informed consent was not required since obtaining it would be impossible for organizational reasons (pronouncement of the Data Privacy Guarantor Authority, General Authorization for personal data treatment for scientific research purposes—n. 9/2014). The study was approved by the Ethics Committee of the Regions and Local Health Units involved.

2.2. Study Design

All patients with main or secondary discharge diagnosis for SCD were included between 1 January 2010 to 31 December 2017 (up to December 2018 for epidemiologic analysis). SCD diagnosis was extrapolated from the hospitalization database through ICD-9-CM codes (provided in Supplementary Table S1) previously reported in the literature [18,19,20]. Regarding the epidemiologic analysis, prevalence, and incidence rates were stratified by age, sex, and the presence/absence of VOCs at inclusion (defined by ICD-9-CM code for SCD with crisis, as explained in the next section). Incidence was defined as the number of new SCD hospitalization discharge diagnoses with codes listed above within each year of inclusion (considering all data availability period). Data were also re-proportioned to fit the overall Italian population for the year 2018: the projections were obtained by reproportioning the epidemiological data of the sample population in the analysis to the national scale, as previously described [21,22]. For longitudinal analyses, the index date corresponded to the first diagnosis detected in the database between 1 January 2010 to 31 December 2017 (inclusion period). Patients were followed up from the index date to death or end of data availability (at least one year). A one-year period before the index date was used to characterize patients. Patients without data available in the one-year period prior the index date or who moved away from the Region/Local Health Units after the index date were excluded from the analysis.

2.3. Study Variables

At index date, all included patients were described according to demographic characteristics, such as age and gender, expressed by proportion of female subjects. Clinical characteristics at baseline were recoded using the Charlson comorbidity index, which assigns a score to each concomitant disease assessed in the previous 12 months on drug treatment and hospitalizations; therefore, patients who were untreated and not hospitalized with comorbidities were not captured [23]. The patient’s distribution by type of SCD diagnosis at index date was also reported. During follow-up, therapeutic pathways were evaluated as all treatments prescribed (by third level ATC code) and all SCD treatments classified as follows: SCD-specific treatment, SCD-related drugs, and SCD complication-related drugs; detail on the type of drugs within each category is provided in Supplementary Table S2. Blood transfusions were identified by presence of ICD-9-CM code V58.2 (blood transfusion, without reported diagnosis) or ICD-9-CM procedure code 99.0 (transfusion of blood). To obtain insights into patients’ journey, all-cause hospitalizations were grouped by Major Diagnostic Category (MDC) and SCD-related hospitalization were analyzed (both ordinary admissions and day hospitals were considered; Emergency Room access not requiring hospitalizations were not included). VOCs and SCD complications were also considered by applying the same methodology reported in the literature [7]. These were identified by ICD-9-CM codes for SCD with crisis and VOC claims without a three-day gap were combined and considered as one single VOC episode. Therefore, only VOC requiring hospitalization were captured in this study. SCD complication codes are reported in Supplementary Table S3.
Mean annual healthcare resource consumption and related direct costs sustained by the NHS were analyzed during follow-up in terms of overall treatments, all-cause hospitalizations, and out-patients services. The costs are reported in Euros (EUR). Drug costs were evaluated using the Italian NHS purchase price. Hospitalization costs were determined using the DRG tariffs, which represent the reimbursement levels of the NHS to healthcare providers. The cost of instrumental and laboratory tests was defined according to the regional tariffs. The transfusion costs refer to costs for the procedure and did not include all other costs regarding the overall transfusion processes, for instance those related to transformation activity (blood collection, validation, and donor services).

2.4. Statistical Analysis

Descriptive analyses are presented in this report. Categorical data were summarized in terms of the number and percentages of patients providing data. The frequency counts and percentages of patients in each category are provided. Percentages were calculated using the number of observations with non-missing values as the denominator. Continuous data were summarized in terms of mean, with standard deviation (SD). All analysis was performed using STATA SE version 12.0.

3. Results

3.1. Epidemiology Estimates a High Prevalence of SCD in Italy

An epidemiological analysis was first carried out to evaluate the incidence and prevalence of SCD diagnosis within the sample population. Incidence rates slightly fluctuated over the years, ranging from 2.89 per 100,000 health-assisted subjects in 2010 to 0.93 per 100,000 in 2018. Since the data were available starting from 2009, the higher incidence observed for the year 2010 could be due to prevalent patients for whom only one year was available to distinguish between prevalent and incident patients. In the last year of inclusion, the incidence rate of SCD was 1.09 per 100,000 among females and 0.76 per 100,000 among males (Figure 1A). The prevalence of SCD for 2018 was of 13.1 cases per 100,000 health-assisted subjects, 10.9 cases per 100,000 males, and 15.3 per 100,000 females. SCD prevalence in younger (<18 years old) and adult (≥18 years old) individuals was 17.2 and 12.4 cases per 100,000, respectively (Figure 1B). The prevalence of adult SCD patients without VOCs at diagnosis in 2018 ranged from 6.99 (age group 25–29) to 11.63 (age group 75–84) per 100,000 health-assisted subjects without a clear pattern, while the prevalence of adult SCD patients with VOCs at diagnosis tended to be higher among young adults (2.81 and 3.04 in age ranges 18–24 and 25–29, respectively to a prevalence below 1 for age group from 55 to 84 years old) (Figure 1C). According to geographic distribution, the prevalence of SCD with crisis was 2.96 in the north, 1.77 in the central, and 2.06 in the south regions of Italy per 100,000 health-assisted subjects (Figure 1D).
The number of SCD patients were then projected on the Italian population of year 2018, estimated as 59,816,673 inhabitants, according to the yearly ISTAT (Italian National Institute of Statistics) report (available online: https://www.tuttitalia.it/statistiche/popolazione-andamento-demografico/ (accessed on 20 October 2022). A total of 7977 patients with SCD was estimated for year 2018, specifically 1690 young and 6287 adult patients. Stratification by gender estimated a total of 3235 male (919 young and 2316 adult) and 4742 female (771 young and 3971 adult) SCD patients among the Italian population (Figure 1E). Among adult patients with SCD, the age-group more represented were 35–44 years (N = 1273) and 45–54 years (N = 1149) (Figure 1F). Distribution by type of diagnosis revealed 1279 patients out of 7977 are estimated to have a diagnosis of SCD with concomitant VOC and 5894 to have SCD without concomitant VOC (Figure 1G). Taken together, these data suggest an increasing prevalence and incidence of SCD in Italy and underline a sub-population of SCD patients with a milder clinical phenotype not being referred to comprehensive centers for hemoglobinopathies.

3.2. High Healthcare Utilization and Significant Direct Medical Costs Contribute to High Burden of Sickle Cell Disease in Italian Adult Population

A total of 2347 patients matched at least one inclusion criterium during all study periods (Figure 2). Of these, 1816 (77.4%) presented the 12-month period minimum before the index date needed for characterization and a 12-month period minimum after the index date to allow follow-up analysis and were therefore included.
Table 1 details the demographic and clinical characteristics of SCD patients included in the analysis. The average age was 43.8 years and 58.4% were female. Adults with SCD had a Charlson comorbidity index value that was higher than younger patients, defined as subjects under 18 years of age (1.2 and 0.4, respectively). Regarding the diagnosis at index date, 74.3% were SCD without concomitant VOCs, 16.1% with concomitant VOCs, and 9.6% were unspecified.
The distribution of SCD genotypes among patients was 70.9% Sβ genotype without crisis; 9.7% unspecified SCD genotype with crisis; 6.9% of Sβ genotype with crisis; 4.6% and 2.0% Hb-SS with and without crisis, respectively; 3.9% other SCD with crisis (0.6% other SCD without crisis); and 0.8% and 0.5% SCD genotype without and with crisis, respectively. In patients without crisis, SCD was mainly included through secondary diagnosis (83.7% of patients without crisis), while patients with crisis were mainly identified by primary diagnosis (59.4% of patients with crisis). In SCD patients without crisis and included by secondary SCD diagnosis, a wide heterogeneity of primary diagnoses was collected. Considering the most frequent ones, 2.1% of SCD patients had a primary diagnosis for obstructive chronic bronchitis with (acute) exacerbation, 1.7% for iron deficiency anemias secondary to blood loss (chronic), while atrial fibrillation or unspecified chest pain accounted for 1.4% and 1.2% of primary diagnoses (Figure 3A). To address the question as to whether knowledge on SCD might affect the use of ICD-9 codes for SCD at hospital discharge, we looked for departments where the most frequent admission/discharge hospital areas were reported. Hematology and general medicine were found to be the main hospital areas involved (evaluated in a sub-cohort of 927 patients for whom these data were available). Physicians from both areas are the specialists commonly more experienced in SCD management with its clinical manifestations. During first year of follow-up (index date included), 50.7% of patients had one all-cause hospitalization, 27.8% had two, 10.4% had three and 11.1% had ≥four. In the second year of follow-up, 44% had at least one hospitalization, and in the third and fourth year that number dropped to 38.2% and 35.8%, respectively (Figure 3B).
The length of hospitalization stay was of 8.0 ± 7.2 days for ordinary hospitalizations, with those related to musculoskeletal system having a mean length from a minimum of 9.1 days and up to 20.1 days. VOCs and SCD-related complications were evaluated during follow-up (SCD index hospitalization was excluded). Since the Emergency Room database was not among the databases in analysis, there might be an underestimation of acute events requiring intensive medical treatment (e.g., infusion for the hydration of pain treatment) [24]. Here, we focused on the hospitalization of patients with sickle cell-related acute events and SCD complications, reported as discharge diagnosis. Considering all available follow-up (mean 4.9 ± 2.2 years), the proportion of those with one VOC/SCD complication was 3.7% and 15.2%, with two VOC/SCD complications was 2.3% and 6.2%, and with ≥3 VOC/SCD complications was 7.7% and 12.8%, respectively (Figure 3C).
As expected, the most frequent ordinary hospitalization regarded the Major Diagnostic Category (MDC) blood and blood-forming organs and immunological disorders, which include SCD diagnosis, followed by those related to circulatory system (range between 12% during first year to 2.6% during fourth year of follow-up) and respiratory system (range between 10.8% during the first year to 2.4% during third year of follow-up) (Table 2).
SCD related treatment patterns are reported in Figure 4A,B. The proportion of patients with SCD-specific treatment, i.e., with hydroxyurea, a gold standard treatment for SCD, ranged between 6.1% and 7.2% during follow-up (Figure 4A). SCD-related drugs were prescribed to 58.4–69.4% of patients and those SCD-related complications rose from 60.7% to 71.3% (Figure 4A). Antithrombotic agents were prescribed in around 24.5–33.6% of patients each year of follow-up. Focusing on patients with VOC at index date, SCD disease-modifying drugs prescribed during follow-up were in the range 17.2–21.8%, SCD-related drugs were in the range 39.4–53.6% while SCD complication-related drugs were around 43.3–58% (Figure 4B). Mean total all-cause health care costs per patient during all available follow-up was EUR 7918, of which EUR 2201 was for overall drugs, EUR 3320 was for all-cause hospitalizations, and EUR 2397 was for outpatient specialist services (Figure 4C). It is noteworthy that around 15 treatment prescriptions per year were reported, a mean number of 1.1 hospitalizations and 5.3 outpatient services (Figure 4C).
During the 4 years of follow-up, among SCD-related drugs, anti-bacterial molecules were the most frequently prescribed (62.8–52.8%), followed by anti-inflammatory drugs (23.5–28.9%), and lastly analgesics (9–11%) with opioids prescribed only in around 8.0–10.5% of patients (Table 3).
Considering all available follow-up, the average yearly number of transfusions was 0.8 in the total population included, 1.4 in patients with crisis, 0.5 in young patients (<18 years), and 0.9 in adults. The mean annual cost for transfusions during all available follow-up was EUR 1291.

4. Discussion

Our study on real-world-data shows that the prevalence of SCD in Italy is higher than has been previously described [9]. This agrees with a previous report on prevalence of SCD in France [25], which examined the database that explores hospital access for sickle cell-related acute events [25]. Based on hospitalization discharge diagnosis, we found an incidence rate of 0.93 SCD cases per 100,000 and a prevalence of 13 SCD cases per 100,000 health-assisted individuals for year 2018, corresponding to 567 new SCD patients for year 2018. This highlights an increasing trend, which is similar to that reported by Hansen, D.L., et al. in the Danish population between 2000–2015 [26]. In addition, growing evidence generated by isolated studies on newborn screening in different Italian areas supports the increase trend of patients with SCD [27,28,29]. A world-wide estimation of inherited red cell disorders using global health data exchange database shows a significant increase in the global incidence of SCD associated with decreased mortality [30]. This characterizes Africa, which is continent more largely affected by voluntary migration or displacement towards Europe and North America due to violent conflicts. Our analysis provides an interesting focus on Italy, the gateway to Europe, reflecting the new world migratory influences and anticipating the impact of SCD on health systems. To better understand the phenomenon, the number of SCD patients were projected on the Italian population: a total of 7977 patients was estimated for year 2018 (1690 young and 6287 adult patients) [9]. Prevalence by geographic areas was in agreement with the presence of SCD patients in urban areas (northern regions) and historic SCD patients (southern regions) [15,31]. Approximately two thirds (74%) of the patients had at least one hospitalization without a concomitant diagnosis of crisis, thus suggestive of a high disease burden beyond severe VOC. In this direction, the International Sickle Cell World Assessment Survey reported a high prevalence of other symptoms, such as notable fatigue or depression/anxiety, that are perceived as high severe as VOCs by SCD patients [32].
Since the study population was identified by diagnosis codes of SCD, patients with milder forms not yet referred to specialist centers might have been included. Therefore, the sample analyzed might represent the pathology as a whole in terms of clinical variability and disease presentation. This might also explain the different estimates between our findings and the epidemiology reported: given the clinical variability of SCD, characterized by severe acute events as well as silent, progressive, and chronic course, real-world settings might capture those patients not taken over by specialist centers and therefore underreported in epidemiology studies.
The main cause of hospitalization agrees with other reports in similar European setting, confirming anemia, cardiopulmonary disease, and infections as the top three causes of hospitalization of patients with SCD [25]. Indeed, antibacterial drugs were among the most frequent drugs administered during characterization and follow-up periods, in line with the literature reporting that infections are a main complication of young adult and adults with SCD (from low urinary infection, tooth infection, pneumonia) [33,34,35,36,37,38]. This is also supported by the observation that the average number of 15.5 prescriptions/year is suggestive for a complicated and chronic clinical course. The relative low prescription of opioids might be most likely related to the lower use of major opioids alone according to the Italian guidelines on the management of pain [39,40,41,42]. This is based on multimodal analgesic therapy, which consists of the simultaneous use of molecules with different mechanisms of action, targeting pain of different origins. Multimodal analgesic therapy allows an optimal pain control, reducing the pharmacologic adverse events and attempting to avoid the development of chronic pain.
It is noteworthy that the use of drugs and the frequency of use decreases as we move away from the index hospitalization but the percentages of use generally remain high, especially with regard to anti-bacterials, anti-acids, anti-thrombotics, and anti-inflammatory. Concerning the gold-standard treatment for SCD, such as hydroxyurea or transfusion, we found a time-dependent reduction in hydroxyurea prescription in our population after hospital discharge. This might be related to the low compliance of the SCD population to hydroxyurea as chronic treatment as well as possible social barriers affecting the accessibility of migrants to public health services, such as outpatient clinics or family doctors [43,44]. In our study, the mean annual number of transfusions tend also to be higher among patients with crisis; in this regard, a recent Italian study pinpoints transfusion regimens to still be crucial as intensive treatments for both acute and chronic SCD-related complications [45].
Our study has some limitations, such as (i) the lack of detailed clinical information (e.g., genotypes, comorbidity, lifestyle habits) [46]; (ii) the full traceability of drugs (e.g.,: dosage prescribed, the actual use by the patients, and the therapeutic indication); and (iii) the exclusion of the Emergency Room database that might contribute to underestimating the phenomenon, as well as immigrants not coved by public health system.
Our estimates in the number of SCD patients could have considered patients not referred to specialist centers who are generally underreported, providing up-to-date insights into SCD profile and contributing to the determining of the extent, distribution, and burden of SCD in Italy. In this way, our data could be representative of the different presentation of the disease showing a high disease burden beyond VOCs that suggests a severe chronic clinical course of SCD, as also supported by the proportion of patients with anti-thrombotic agents as indicators of the underlying inflammatory vasculopathy and thrombotic risk that shed light on the management of patients not generally described in the literature. Last but not least, our data describe a population of SCD patients with high resource absorption, both in terms of drugs (for SCD and related diseases) but also for hospitalizations and specialist services. In comparison with other disorders the economic burden of which has been well investigated, such as myocardial infarction or cystic fibrosis, characterized by annual direct total healthcare costs/patients averaging EUR 3044–3668 [47] or ranging EUR 4000–30,000 (based on cystic fibrosis severity) [48], respectively, the cost of care for SCD remains constrained, with approximately EUR 8000 per year per patients. Moreover, the economic burden of SCD patients reported in the present analysis could be underestimated, since the healthcare resource consumption related to the access to emergency units in acute phase patients was not retrievable from the database in question. Ultimately, during the period considered, the only SCD-specific drug available was hydroxyurea, characterized by its low cost. The introduction of innovative therapies with different costs could modify the economic scenario of the overall direct healthcare expenditure for SCD, although it should be noted the increase in the drug costs could potentially correspond to a reduction in disease management costs.

5. Conclusions

Although population projections might present some limitations related to the time frame analyzed, the “starting” population for the projection, and the assumption about future trends, population projections represent a powerful tool for the development of strategies to intersect missing patients with SCD and define plans and policies for care of patients with SCD. This might help to ensure the timely management of patients with milder forms to prevent and treat clinical manifestations that could lead to more severe complications and/or more severe and potentially fatal clinical forms [49]. Finally, our data further reinforce the importance of a holistic approach to patients with SCD [32], who display a severe disease burden, which deeply affects their quality of life and require personalized illness education.

Supplementary Materials

The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/jcm12010117/s1; Table S1: International Classification of Diseases, Ninth Revision, Clinical Modification (ICD-9-CM) diagnosis codes of sickle cell disease forms. Table S2: List of SCD treatments in analysis. Table S3: International Classification of Diseases, Ninth Revision, Clinical Modification (ICD-9-CM) diagnosis codes of sickle cell-related complications.

Author Contributions

Conceptualization, C.C. (Chiara Castiglioni), D.V., C.F., V.P., L.D.E., G.L.F. and GREATalyS Study Group; Data curation, C.C. (Chiara Castiglioni) and V.P.; Formal analysis, V.P. and L.D.E.; Investigation, C.C. (Chiara Castiglioni), C.C. (Claudia Condorelli), C.F., L.D.E. and G.L.F.; Methodology, C.C. (Chiara Castiglioni), C.C. (Claudia Condorelli), D.V. and V.P.; Supervision, L.D.F., E.P., L.D.E. and G.L.F.; Validation, L.D.F., E.P., L.D.E. and G.L.F.; Visualization, L.D.F.; Writing—original draft, L.D.F. and V.P.; Writing—review and editing, C.C. (Chiara Castiglioni), C.C. (Claudia Condorelli), D.V., E.P., L.D.E. and G.L.F. All authors have read and agreed to the published version of the manuscript.

Funding

The GREATalyS study and this manuscript were sponsored by Novartis Farma S.p.A., Italy. Clicon S.r.l. Società Benefit is an independent company. The agreement signed by Clicon S.r.l. Società Benefit and Novartis Farma S.p.A does not create any ownership, joint venture or any similar relationship between parties. Neither CliCon S.r.l. Società Benefit nor any of their representatives are employees of Novartis Farma S.p.A for any purpose.

Institutional Review Board Statement

The study was conducted in accordance with the Declaration of Helsinki. This study has been notified and approved by the local Ethics Committee of the Local Health Units involved in the study: Comitato Etico Regionale delle Marche (protocol number 2019 327, approval date 31 October 2019); Comitato Etico Indipendente (protocol number 0077216, approval date 11 September 2019)); Comitato Etico di Bergamo (protocol number 225/19, approval date 14 November 2019); Comitato Etico Regionale (protocol number 267/2019, approval date 16 March 2020); Comitato Etico ASL Lecce (protocol number 37, approval date 08 October 2019); Comitato Etico Campania Centro (protocol number 28/C.E. 33/19 Os, approval date 22 January 2020); Comitato Etico Palermo 1 (protocol number 10/2019, approval date 13 November 2019); Comitato Etico Lazio 1 (protocol number 1994/CE Lazio 1, approval date 30 October 2019 and protocol number1997/CE Lazio 1, approval date 30 October 2019); Comitato Etico Interaziendale Campania Sud (protocol number 122678, approval date 29 August 2019); Comitato Etico di Area Vasta Sud Est (protocol number 1518, approval date 23 July 2020); Comitato Etico Interaziendale (protocol number AslVC.FarmT.20.02, approval date 23 January 2020); Regione Calabria Comitato Etico Sezione Area Centro (protocol number 285, approval date 26 November 2018); Servizio Coordinamento Comitato Etico Campania Sud (protocol number 43, approval date 12 June 2019); Comitato Etico Interprovinciale Area 1 (protocol number 28/CE/2019, approval date 02 April 2019 and protocol number 70/CE/2019, approval date 18 September 2019); Comitato Etico Lazio 2 (protocol number 0087354, approval date 15 May 2019).

Informed Consent Statement

Informed consent was not required since obtaining it would be impossible for organizational reasons (pronouncement of the Data Privacy Guarantor Authority, General Authorisation for personal data treatment for scientific research purposes—n.9/2014).

Data Availability Statement

All data used for the current study are available upon reasonable request next to CliCon s.r.l. which is the body entitled to allow data treatment and analysis by Local Health Units.

Acknowledgments

The authors thank all the investigators of the «GREATalyS study group» for their contribution to the project: Resta A.M., Regione Marche, Timossi R., ASL Genova, Pastorello M., ASP Palermo, Barbieri A., ASL Vercelli, Lena F., Azienda USL Toscana sud-est, Cillo M.R., ASL Salerno, Quarta F., ASL Lecce, Antonacci S., ASL Bari, Pagliaro R., ASL Roma 5, Paciello A., ASL Bergamo, Svanera G., ASL Napoli 2 Nord, Dell’Orco S., ASL Roma 6, Ubertazzo L., ASL Roma 4, Vercellone A., ASL Napoli 3 SUD, Citraro R., Regione Calabria, Lombardi R., ASL Foggia, Rizzi F., ASL Barletta—Andria—Trani. We thank Elisa Giacomini from CliCon S.r.l. Società Benefit for providing medical writing assistance in preparation of this manuscript, in accordance with Good Publication Practice (GPP3) guidelines, funded by Novartis Farma S.p.A., as well as Paola Amore from Novartis Farma S.p.A., Milan, Italy for project management and medical writing assistance. All authors contributed to the design, the interpretation of the data and the writing and critical revision of the manuscript.

Conflicts of Interest

De Franceschi L. is a medical consultant for Novartis, Roche, and received a research grant from Agios. Forni G.L. is a medical consultant for Novartis, Celgene, BlueBirdBio. Castiglioni C., Condorelli C., Valsecchi D. and Premoli E. are employees of Novartis Farma S.p.A., Italy. Perrone V. and Degli Esposti L. are employees of CliCon S.r.l. Società Benefit. Fiocchi C. was an employee of Novartis Farma S.p.A., Italy, and of Blueprint Medicines Italy from 30 September 2021.

Abbreviations

ATC: Anatomical Therapeutic Chemical code; DRG: Diagnosis-Related Group; Hb: hemoglobin; ICD-9-CM: International Classification of Diseases, Ninth Revision, Clinical Modification; MDC: Major Diagnostic Category; NHS: National Health System; OSS: outpatient services; SCD: sickle cell disease; SD: standard deviation; VOC: vaso-occlusive crisis; WHO: World Health Organization.

References

  1. Cordovil, K. Sickle Cell Disease: A Genetic Disorder of Beta-Globin. In Thalassemia and Other Hemolytic Anemias; AL-Zwaini, I., Ed.; InTech: London, UK, 2018; ISBN 978-1-78923-366-7. [Google Scholar]
  2. Brugnara, C.; Armsby, C.C.; De Franceschi, L.; Crest, M.; Martin Euclaire, M.-F.; Alper, S.L. Ca2+-Activated K+ Channels of Human and Rabbit Erythrocytes Display Distinctive Patterns of Inhibition by Venom Peptide Toxins. J. Membarin Biol. 1995, 147, 71–82. [Google Scholar] [CrossRef] [PubMed]
  3. De Franceschi, L.; Brugnara, C.; Rouyer-Fessard, P.; Jouault, H.; Beuzard, Y. Formation of Dense Erythrocytes in SAD Mice Exposed to Chronic Hypoxia: Evaluation of Different Therapeutic Regimens and of a Combination of Oral Clotrimazole and Magnesium Therapies. Blood 1999, 94, 4307–4313. [Google Scholar] [CrossRef] [PubMed]
  4. McNaughton-Smith, G.A.; Burns, J.F.; Stocker, J.W.; Rigdon, G.C.; Creech, C.; Arrington, S.; Shelton, T.; de Franceschi, L. Novel Inhibitors of the Gardos Channel for the Treatment of Sickle Cell Disease. J. Med. Chem. 2008, 51, 976–982. [Google Scholar] [CrossRef] [PubMed]
  5. Kalish, B.T.; Matte, A.; Andolfo, I.; Iolascon, A.; Weinberg, O.; Ghigo, A.; Cimino, J.; Siciliano, A.; Hirsch, E.; Federti, E.; et al. Dietary ω-3 Fatty Acids Protect against Vasculopathy in a Transgenic Mouse Model of Sickle Cell Disease. Haematologica 2015, 100, 870–880. [Google Scholar] [CrossRef] [Green Version]
  6. De Franceschi, L.; Bertoldi, M.; Matte, A.; Santos Franco, S.; Pantaleo, A.; Ferru, E.; Turrini, F. Oxidative Stress and 𝛽-Thalassemic Erythroid Cells behind the Molecular Defect. Oxidative Med. Cell. Longev. 2013, 2013, e985210. [Google Scholar] [CrossRef] [Green Version]
  7. Shah, N.; Bhor, M.; Xie, L.; Paulose, J.; Yuce, H. Sickle Cell Disease Complications: Prevalence and Resource Utilization. PLoS ONE 2019, 14, e0214355. [Google Scholar] [CrossRef] [Green Version]
  8. Telen, M.J.; Malik, P.; Vercellotti, G.M. Therapeutic Strategies for Sickle Cell Disease: Towards a Multi-Agent Approach. Nat. Rev. Drug. Discov. 2019, 18, 139–158. [Google Scholar] [CrossRef]
  9. Russo, G.; De Franceschi, L.; Colombatti, R.; Rigano, P.; Perrotta, S.; Voi, V.; Palazzi, G.; Fidone, C.; Quota, A.; Graziadei, G.; et al. Current Challenges in the Management of Patients with Sickle Cell Disease–A Report of the Italian Experience. Orphanet J. Rare Dis. 2019, 14, 120. [Google Scholar] [CrossRef] [Green Version]
  10. Matte, A.; Cappellini, M.D.; Iolascon, A.; Enrica, F.; De Franceschi, L. Emerging Drugs in Randomized Controlled Trials for Sickle Cell Disease: Are We on the Brink of a New Era in Research and Treatment? Expert. Opin. Investig. Drugs 2020, 29, 23–31. [Google Scholar] [CrossRef]
  11. Matte, A.; Zorzi, F.; Mazzi, F.; Federti, E.; Olivieri, O.; De Franceschi, L. New Therapeutic Options for the Treatment of Sickle Cell Disease. Mediterr. J. Hematol. Infect Dis. 2019, 11, e2019002. [Google Scholar] [CrossRef]
  12. Peterson, E.E.; Salemi, J.L.; Dongarwar, D.; Salihu, H.M. Acute Care Utilization in Pediatric Sickle Cell Disease and Sickle Cell Trait in the USA: Prevalence, Temporal Trends, and Cost. Eur. J. Pediatr. 2020, 179, 1701–1710. [Google Scholar] [CrossRef] [PubMed]
  13. Kanter, J.; Meier, E.R.; Hankins, J.S.; Paulukonis, S.T.; Snyder, A.B. Improving Outcomes for Patients With Sickle Cell Disease in the United States: Making the Case for More Resources, Surveillance, and Longitudinal Data. JAMA Health Forum. 2021, 2, e213467. [Google Scholar] [CrossRef] [PubMed]
  14. Shah, N.; Bhor, M.; Xie, L.; Halloway, R.; Arcona, S.; Paulose, J.; Yuce, H. Treatment Patterns and Economic Burden of Sickle-Cell Disease Patients Prescribed Hydroxyurea: A Retrospective Claims-Based Study. Health Qual. Life Outcomes 2019, 17, 155. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  15. De Franceschi, L.; Lux, C.; Piel, F.B.; Gianesin, B.; Bonetti, F.; Casale, M.; Graziadei, G.; Lisi, R.; Pinto, V.; Putti, M.C.; et al. Access to Emergency Departments for Acute Events and Identification of Sickle Cell Disease in Refugees. Blood 2019, 133, 2100–2103. [Google Scholar] [CrossRef] [PubMed]
  16. Colombatti, R.; Sainati, L. Management of Children With Sickle Cell Disease in Europe: Current Situation and Future Perspectives. Available online: https://emj.emg-health.com/hematology/article/management-of-children-with-sickle-cell-disease-in-europe-current-situation-and-future-perspectives/ (accessed on 23 November 2021).
  17. Italian Republic. Official Journal of the Italian Republic. Rome-Friday, 12 May 2017 (Gazzetta Ufficiale Della Repubblica Italiana Roma-Venerdì, 12 Maggio 2017). Available online: https://www.gazzettaufficiale.it/eli/gu/2017/05/12/109/sg/pdf (accessed on 24 April 2022).
  18. Reeves, S.; Garcia, E.; Kleyn, M.; Housey, M.; Stottlemyer, R.; Lyon-Callo, S.; Dombkowski, K.J. Identifying Sickle Cell Disease Cases Using Administrative Claims. Acad. Pediatr. 2014, 14, S61–S67. [Google Scholar] [CrossRef]
  19. Michalik, D.E.; Taylor, B.W.; Panepinto, J.A. Identification and Validation of a Sickle Cell Disease Cohort Within Electronic Health Records. Acad. Pediatr. 2017, 17, 283–287. [Google Scholar] [CrossRef]
  20. Singh, A.; Mora, J.; Panepinto, J.A. Identification of Patients with Hemoglobin SS/Sβ0 Thalassemia Disease and Pain Crises within Electronic Health Records. Blood. Adv. 2018, 2, 1172–1179. [Google Scholar] [CrossRef] [Green Version]
  21. Perrone, V.; Sangiorgi, D.; Andretta, M.; Ducci, G.; Forti, B.; Francesa Morel, P.; Gambera, M.; Maina, G.; Mencacci, C.; Mennini, F.; et al. Assessment of Patients Affected by Treatment-Resistant Depression: Findings from a Real-World Study in Italy. J. Psychiatry Psychiatr. Disord. 2020, 4, 104–117. [Google Scholar] [CrossRef]
  22. Degli Esposti, L.; Perrone, V.; Sangiorgi, D.; Sinigaglia, L. Assessment of Patients Affected by Rheumatoid Arthritis Eligible for Biotechnological Agents and Evaluation of Their Healthcare Resource Utilization and Related Costs. Reumatismo 2021, 73, 5–14. [Google Scholar] [CrossRef]
  23. Charlson, M.E.; Pompei, P.; Ales, K.L.; MacKenzie, C.R. A New Method of Classifying Prognostic Comorbidity in Longitudinal Studies: Development and Validation. J. Chronic. Dis 1987, 40, 373–383. [Google Scholar] [CrossRef]
  24. Lanzkron, S.; Carroll, C.P.; Haywood, C. The Burden of Emergency Department Use for Sickle-Cell Disease: An Analysis of the National Emergency Department Sample Database. Am. J. Hematol. 2010, 85, 797–799. [Google Scholar] [CrossRef] [PubMed]
  25. Leleu, H.; Arlet, J.B.; Habibi, A.; Etienne-Julan, M.; Khellaf, M.; Adjibi, Y.; Pirenne, F.; Pitel, M.; Granghaud, A.; Sinniah, C.; et al. Epidemiology and Disease Burden of Sickle Cell Disease in France: A Descriptive Study Based on a French Nationwide Claim Database. PLoS ONE 2021, 16, e0253986. [Google Scholar] [CrossRef] [PubMed]
  26. Hansen, D.L.; Glenthøj, A.; Möller, S.; Biemond, B.J.; Andersen, K.; Gaist, D.; Petersen, J.; Frederiksen, H. Prevalence of Congenital Hemolytic Disorders in Denmark, 2000-2016. Clin. Epidemiol. 2020, 12, 485–495. [Google Scholar] [CrossRef]
  27. Lodi, M.; Bigi, E.; Palazzi, G.; Vecchi, L.; Morandi, R.; Setti, M.; Borsari, S.; Bergonzini, G.; Iughetti, L.; Venturelli, D. Universal Screening Program in Pregnant Women and Newborns At-Risk for Sickle Cell Disease: First Report from Northern Italy. Hemoglobin 2017, 41, 230–233. [Google Scholar] [CrossRef] [PubMed]
  28. Martella, M.; Viola, G.; Azzena, S.; Schiavon, S.; Biondi, A.; Basso, G.; Corti, P.; Colombatti, R.; Masera, N.; Sainati, L. Evaluation of Technical Issues in a Pilot Multicenter Newborn Screening Program for Sickle Cell Disease. Int. J. Neonatal. Screen. 2018, 5, 2. [Google Scholar] [CrossRef] [Green Version]
  29. Colombatti, R.; Martella, M.; Cattaneo, L.; Viola, G.; Cappellari, A.; Bergamo, C.; Azzena, S.; Schiavon, S.; Baraldi, E.; Barba, B.D.; et al. Results of a Multicenter Universal Newborn Screening Program for Sickle Cell Disease in Italy: A Call to Action. Pediatr. Blood Cancer 2019, 66, e27657. [Google Scholar] [CrossRef]
  30. Lippi, G.; Mattiuzzi, C. Updated Worldwide Epidemiology of Inherited Erythrocyte Disorders. Acta. Haematol. 2020, 143, 196–203. [Google Scholar] [CrossRef]
  31. Rigano, P.; De Franceschi, L.; Sainati, L.; Piga, A.; Piel, F.B.; Cappellini, M.D.; Fidone, C.; Masera, N.; Palazzi, G.; Gianesin, B.; et al. Real-Life Experience with Hydroxyurea in Sickle Cell Disease: A Multicenter Study in a Cohort of Patients with Heterogeneous Descent. Blood Cells Mol. Dis. 2018, 69, 82–89. [Google Scholar] [CrossRef] [Green Version]
  32. Osunkwo, I.; Andemariam, B.; Minniti, C.P.; Inusa, B.P.D.; El Rassi, F.; Francis-Gibson, B.; Nero, A.; Trimnell, C.; Abboud, M.R.; Arlet, J.-B.; et al. Impact of Sickle Cell Disease on Patients’ Daily Lives, Symptoms Reported, and Disease Management Strategies: Results from the International Sickle Cell World Assessment Survey (SWAY). Am. J. Hematol. 2021, 96, 404–417. [Google Scholar] [CrossRef]
  33. Brousseau, D.C.; Owens, P.L.; Mosso, A.L.; Panepinto, J.A.; Steiner, C.A. Acute Care Utilization and Rehospitalizations for Sickle Cell Disease. JAMA 2010, 303, 1288–1294. [Google Scholar] [CrossRef]
  34. Kato, G.J.; Piel, F.B.; Reid, C.D.; Gaston, M.H.; Ohene-Frempong, K.; Krishnamurti, L.; Smith, W.R.; Panepinto, J.A.; Weatherall, D.J.; Costa, F.F.; et al. Sickle Cell Disease. Nat. Rev. Dis. Prim. 2018, 4, 18010. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  35. Cannas, G. Sickle cell disease and infections in high- and low-income countries. Mediterr. J. Hematol. Infect Dis. 2019, 11, 02019042. [Google Scholar] [CrossRef] [PubMed]
  36. Claudio, A.M.; Foltanski, L.; Delay, T.; Britell, A.; Duckett, A.; Weeda, E.R.; Bohm, N. Antibiotic Use and Respiratory Pathogens in Adults With Sickle Cell Disease and Acute Chest Syndrome. Ann. Pharm. 2019, 53, 991–996. [Google Scholar] [CrossRef] [PubMed]
  37. Vichinsky, E.P.; Neumayr, L.D.; Earles, A.N.; Williams, R.; Lennette, E.T.; Dean, D.; Nickerson, B.; Orringer, E.; McKie, V.; Bellevue, R.; et al. Causes and Outcomes of the Acute Chest Syndrome in Sickle Cell Disease. New. Engl. J. Med. 2000, 342, 1855–1865. [Google Scholar] [CrossRef] [Green Version]
  38. William, B.M.; Thawani, N.; Sae-Tia, S.; Corazza, G.R. Hyposplenism: A Comprehensive Review. Part II: Clinical Manifestations, Diagnosis, and Management. Hematology 2007, 12, 89–98. [Google Scholar] [CrossRef]
  39. Ferrari, R.; Duse, G.; Capraro, M.; Visentin, M. Risk Assessment of Opioid Misuse in Italian Patients with Chronic Noncancer Pain. Pain Res. Treat. 2014, 2014, 1–9. [Google Scholar] [CrossRef]
  40. De Franceschi, L.; Finco, G.; Vassanelli, A.; Zaia, B.; Ischia, S.; Corrocher, R. A Pilot Study on the Efficacy of Ketorolac plus Tramadol Infusion Combined with Erythrocytapheresis in the Management of Acute Severe Vaso-Occlusive Crises and Sickle Cell Pain. Haematologica 2004, 89, 1389–1391. [Google Scholar]
  41. De Franceschi, L.; Mura, P.; Schweiger, V.; Vencato, E.; Quaglia, F.M.; Delmonte, L.; Evangelista, M.; Polati, E.; Olivieri, O.; Finco, G. Fentanyl Buccal Tablet: A New Breakthrough Pain Medication in Early Management of Severe Vaso-Occlusive Crisis in Sickle Cell Disease. Pain. Pr. 2016, 16, 680–687. [Google Scholar] [CrossRef]
  42. Forni, G.L.; Finco, G.; Graziadei, G.; Balocco, M.; Rigano, P.; Perrotta, S.; Olivieri, O.; Cappellini, M.D.; De Franceschi, L. Development of Interactive Algorithm for Clinical Management of Acute Events Related to Sickle Cell Disease in Emergency Department. Orphanet. J. Rare Dis. 2014, 9, 91. [Google Scholar] [CrossRef] [Green Version]
  43. Honsel, V.; Khimoud, D.; Ranque, B.; Offredo, L.; Joseph, L.; Pouchot, J.; Arlet, J.-B. Comparison between Adult Patients with Sickle Cell Disease of Sub-Saharan African Origin Born in Metropolitan France and in Sub-Saharan Africa. J. Clin. Med. 2019, 8, 2173. [Google Scholar] [CrossRef] [Green Version]
  44. Lesage, N.; Deneux Tharaux, C.; Saucedo, M.; Habibi, A.; Galacteros, F.; Girot, R.; Bouvier Colle, M.H.; Kayem, G. Maternal Mortality among Women with Sickle-Cell Disease in France, 1996-2009. Eur. J. Obs. Gynecol. Reprod. Biol. 2015, 194, 183–188. [Google Scholar] [CrossRef]
  45. Graziadei, G.; De Franceschi, L.; Sainati, L.; Venturelli, D.; Masera, N.; Bonomo, P.; Vassanelli, A.; Casale, M.; Lodi, G.; Voi, V.; et al. Transfusional Approach in Multi-Ethnic Sickle Cell Patients: Real-World Practice Data From a Multicenter Survey in Italy. Front. Med. 2022, 9, 832154. [Google Scholar] [CrossRef]
  46. Snyder, A.B.; Lane, P.A.; Zhou, M.; Paulukonis, S.T.; Hulihan, M.M. The Accuracy of Hospital ICD-9-CM Codes for Determining Sickle Cell Disease Genotype. J. Rare Dis. Res. Treat. 2017, 2, 39–45. [Google Scholar] [CrossRef]
  47. Angelucci, E.; Antmen, A.; Losi, S.; Burrows, N.; Bartiromo, C.; Hu, X.H. Direct Medical Care Costs Associated with β-Thalassemia Care in Italy. Blood 2017, 130, 3368. [Google Scholar] [CrossRef]
  48. Colombo, C.; Daccò, V.; Alicandro, G.; Loi, S.; Mazzi, S.; Lucioni, C.; Ravasio, R. Cost of Cystic Fibrosis: Analysis of Treatment Costs in a Specialized Center in Northern Italy. Adv. Ther. 2013, 30, 165–175. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  49. Piel, F.B.; Steinberg, M.H.; Rees, D.C. Sickle Cell Disease. New Engl. J. Med. 2017, 376, 1561–1573. [Google Scholar] [CrossRef] [PubMed]
Jcm 12 00117 g001 550
Figure 1. (Upper plots A–D) Epidemiology of SCD in the sample population (N = 15,300,00). (A) Incidence rate overall and by gender per year included in the study (2010–2018). (B) Prevalence by gender and age (<18 years and ≥18 years) for year 2018. (C) Prevalence by age classes in adult SCD patients with and without VOC at diagnosis for year 2018. (D) Prevalence by geographic area and presence of crisis for year 2018. (Lower plots E–G) Projections to Italian population for year 2018. (E) Number of SCD patients estimated in Italy by age and gender. (F) Number of SCD patients estimated in Italy by age ranges. (G) Number of SCD patients estimated in Italy by presence of VOCs at diagnosis.
Figure 1. (Upper plots A–D) Epidemiology of SCD in the sample population (N = 15,300,00). (A) Incidence rate overall and by gender per year included in the study (2010–2018). (B) Prevalence by gender and age (<18 years and ≥18 years) for year 2018. (C) Prevalence by age classes in adult SCD patients with and without VOC at diagnosis for year 2018. (D) Prevalence by geographic area and presence of crisis for year 2018. (Lower plots E–G) Projections to Italian population for year 2018. (E) Number of SCD patients estimated in Italy by age and gender. (F) Number of SCD patients estimated in Italy by age ranges. (G) Number of SCD patients estimated in Italy by presence of VOCs at diagnosis.
Jcm 12 00117 g001
Jcm 12 00117 g002 550
Figure 2. Study flow-chart of patients in analysis. The inclusion period was from 1st January 2010 to 31st December 2017. Patients were identified by SCD diagnosis retrieved from the hospitalization database (ICD-9-CM codes 282.41, 282.42, 282.60, 282.61, 282.62, 282.63, 282.64, 282.68, and 282.69; code 282.50 related to the Sickle cell trait was not considered for inclusion).
Figure 2. Study flow-chart of patients in analysis. The inclusion period was from 1st January 2010 to 31st December 2017. Patients were identified by SCD diagnosis retrieved from the hospitalization database (ICD-9-CM codes 282.41, 282.42, 282.60, 282.61, 282.62, 282.63, 282.64, 282.68, and 282.69; code 282.50 related to the Sickle cell trait was not considered for inclusion).
Jcm 12 00117 g002
Jcm 12 00117 g003 550
Figure 3. Hospitalization of patients with SCD. (A) More frequent primary diagnosis in SCD patients without crisis with secondary SCD diagnosis at inclusion (n = 1129). (B) Percentages of patients with all-cause hospitalizations during follow-up period. Hospitalizations comprised ordinary admissions and day hospitals; Emergency Room access not requiring hospitalization was not included. Hospitalization corresponding to the index date was counted in the number of hospitalizations. (C) Percentages of SCD patients with VOC episodes or complications during follow-up.
Figure 3. Hospitalization of patients with SCD. (A) More frequent primary diagnosis in SCD patients without crisis with secondary SCD diagnosis at inclusion (n = 1129). (B) Percentages of patients with all-cause hospitalizations during follow-up period. Hospitalizations comprised ordinary admissions and day hospitals; Emergency Room access not requiring hospitalization was not included. Hospitalization corresponding to the index date was counted in the number of hospitalizations. (C) Percentages of SCD patients with VOC episodes or complications during follow-up.
Jcm 12 00117 g003
Jcm 12 00117 g004 550
Figure 4. Therapeutic pathways and healthcare resource costs. (A) Patients treated with at least one SCD-specific drug, SCD-related drug, and SCD complication-related drug during the follow-up period (1–4 years). (B) Patients with crisis treated with at least one SCD-specific drug, SCD-related drug, and SCD complication-related drug during the follow-up period (1–4 years). (C) Mean annual healthcare resource consumption and related costs considering all available follow-up. List of SCD treatments in analysis and the related ATC code is reported in Supplementary Table S2. Abbreviation: OSS, outpatient services.
Figure 4. Therapeutic pathways and healthcare resource costs. (A) Patients treated with at least one SCD-specific drug, SCD-related drug, and SCD complication-related drug during the follow-up period (1–4 years). (B) Patients with crisis treated with at least one SCD-specific drug, SCD-related drug, and SCD complication-related drug during the follow-up period (1–4 years). (C) Mean annual healthcare resource consumption and related costs considering all available follow-up. List of SCD treatments in analysis and the related ATC code is reported in Supplementary Table S2. Abbreviation: OSS, outpatient services.
Jcm 12 00117 g004
Table
Table 1. Demographic and clinical characteristics of SCD patients included.
Table 1. Demographic and clinical characteristics of SCD patients included.
<18 years (N = 335)≥18 years (N = 1481)Total (N = 1816)
Age at index date, mean ± SD6.9 ± 5.252.1 ± 19.943.8 ± 25.2
Female, n (%)158 (47.2)902 (60.9)1060 (58.4)
Charlson comorbidity index, mean ± SD0.4 ± 0.51.4 ± 1.51.2 ± 1.4
Diagnosis with crisis, n (%)88 (26.3)205 (13.8)293 (16.1)
Diagnosis without crisis, n (%)181 (54.0)1168 (78.9)1349 (74.3)
Diagnosis with unspecified crisis, n (%)66 (19.7)108 (7.3)174 (9.6)
Table
Table 2. Most frequent ordinary hospitalizations and average length of stays during follow-up period.
Table 2. Most frequent ordinary hospitalizations and average length of stays during follow-up period.
MDCFirst Year Follow-Up (n = 1816)Second Year Follow-Up
(n = 1670)		Third Year Follow-Up (n = 1432)Fourth Year Follow-Up
(n = 1194)
Blood and blood-forming organs and immunological disorders, n (%)290 (16.0)81 (4.9)71 (5.0)45 (3.8)
Average length (in days), mean ± SD6.9 ± 6.45.3 ± 4.35.9 ± 5.411.6 ± 45.3
Circulatory system, n (%)218 (12.0)71 (4.3)52 (3.6)31 (2.6)
Average length (in days), mean ± SD7.9 ± 8.58.1 ± 7.28.8 ± 6.610.4 ± 8.0
Respiratory system, n (%)197 (10.8)46 (2.8)35 (2.4)41 (3.4)
Average length (in days), mean ± SD10.2 ± 7.310.6 ± 7.49.7 ± 5.311.1 ± 7.5
Digestive system, n (%)165 (9.1)32 (1.9)27 (1.9)19 (1.6)
Average length (in days), mean ± SD7.0 ± 8.813.7 ± 19.38.0 ± 7.66.5 ± 5.2
Hepatobiliary system and pancreas, n (%)154 (8.5)36 (2.2)25 (1.7)23 (1.9)
Average length (in days), mean ± SD8.5 ± 7.38.3 ± 5.98.2 ± 4.69.6 ± 6.0
Musculoskeletal system and connective tissue, n (%)117 (6.4)42 (2.5)28 (2.0)23 (1.9)
Average length (in days), mean ± SD12.7 ± 13.39.1 ± 8.08.8 ± 8.820.1 ± 56.7
Nervous system, n (%)91 (5.0)31 (1.9)22 (1.511 (0.9)
Average length (in days), mean ± SD13.0 ± 22.910.5 ± 11.017.6 ± 9.113.8 ± 10.8
Kidney and urinary tract *, n (%)76 (4.2)25 (1.5)-10 (0.8)
Average length (in days), mean ± SD8.3 ± 6.88.9 ± 10.2-14.5 ± 11.5
Pregnancy, childbirth, and puerperium **, n (%)60 (3.3)--9 (0.8)
Average length (in days), mean ± SD6.4 ± 8.2--4.9 ± 3.3
Infectious and parasitic DDs, n (%)56 (3.1)20 (1.2)15 (1.0)9 (0.8)
Average length (in days), mean ± SD8.6 ± 12.114.3 ± 14.59.8 ± 7.55.0 ± 3.1
* Not among the top ten more frequent hospitalization during third year of follow-up; ** not among the top ten more frequent hospitalization during second and third year of follow-up. Note: The MDC Blood and Blood-Forming Organs and Immunological Disorders includes SCD diagnosis. List of ICD-9-CM diagnosis codes of sickle cell-related complications is reported in Supplementary Table S3.
Table
Table 3. Most frequently prescribed drugs during each year of follow-up.
Table 3. Most frequently prescribed drugs during each year of follow-up.
1st Year
Follow-Up
(n = 1816)		2nd Year
Follow-Up
(n = 1670)		3rd year
Follow-Up
(n = 1432)		4th Year
Follow-Up
(n = 1194)
Descriptionn%n%n%n%
Antibacterials for systemic use114062.899559.680556.263052.8
Drugs for acid related disorders86847.869441.654738.241434.7
Antithrombotic agents61033.647928.738426.829224.5
Anti-inflammatory and antirheumatic products52528.946527.839327.428123.5
Antianemic preparations44224.335321.128519.922318.7
Drugs for obstructive airway diseases44024.239023.428820.124220.3
Agents acting on RAAS43624.038322.930621.426121.9
Corticosteroids for systemic use41923.133119.829220.421518.0
Diuretics33018.226615.920414.215312.8
Beta-blocking agents *28115.525515.3----
Vitamins **----24116.820016.8
Analgesics20911.518811.31349.41048.7
Opioids19110.517610.01218.4958.0
* Among the top ten more frequent drugs during first and second year of follow-up; ** among the top ten more frequent drugs during third and fourth year of follow-up. Note: List of SCD treatments in analysis and related ATC code is reported in Supplementary Table S2.
Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content.

Share and Cite

MDPI and ACS Style

De Franceschi, L.; Castiglioni, C.; Condorelli, C.; Valsecchi, D.; Premoli, E.; Fiocchi, C.; Perrone, V.; Esposti, L.D.; Forni, G.L.; on behalf of the GREATalyS Study Group. Real-World Evidence on Disease Burden and Economic Impact of Sickle Cell Disease in Italy. J. Clin. Med. 2023, 12, 117. https://doi.org/10.3390/jcm12010117

AMA Style

De Franceschi L, Castiglioni C, Condorelli C, Valsecchi D, Premoli E, Fiocchi C, Perrone V, Esposti LD, Forni GL, on behalf of the GREATalyS Study Group. Real-World Evidence on Disease Burden and Economic Impact of Sickle Cell Disease in Italy. Journal of Clinical Medicine. 2023; 12(1):117. https://doi.org/10.3390/jcm12010117

Chicago/Turabian Style

De Franceschi, Lucia, Chiara Castiglioni, Claudia Condorelli, Diletta Valsecchi, Eleonora Premoli, Carina Fiocchi, Valentina Perrone, Luca Degli Esposti, Gian Luca Forni, and on behalf of the GREATalyS Study Group. 2023. "Real-World Evidence on Disease Burden and Economic Impact of Sickle Cell Disease in Italy" Journal of Clinical Medicine 12, no. 1: 117. https://doi.org/10.3390/jcm12010117

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

Article Metrics

Back to TopTop