Abstract
Introduction
Alopecia areata (AA) is an autoimmune disease characterized by patchy or complete nonscarring scalp hair loss (SHL) and is associated with significant psychosocial impacts. Current epidemiologic data on AA in Brazil are sparse, and advanced therapies may be difficult for patients to access. The objective of this study was to assess the real-world burden of disease and unmet need for patients with AA in Brazil.
Methods
This study used data from the Adelphi Real World AA II Brazil Disease Specific Programme™ (DSP), a cross-sectional survey conducted in Brazil (March–June 2024) incorporating retrospective data collection. Participating dermatologists completed patient record forms for their adult patients with AA. Variables assessed included patient demographics, clinical characteristics, treatment goals, prior and current treatments, and issues with current treatments, presented for the overall population, and stratified by extent of SHL and modality of health care access (public vs private health setting).
Results
Of the 341 patients included, 22 had 0% SHL, while 84, 95, 46, and 17 had 1–20%, 21–49%, 50–94%, and 95–100% SHL, respectively. More patients with 50–94% SHL had chronic AA versus other SHL groups, and patients with ≥ 50% SHL displayed more severe disease symptoms than those with < 50% SHL. The most common physician-reported goal is to improve current treatment to reduce SHL. Patients with < 50% SHL usually used non-systemic therapies (e.g., topical and intralesional treatments), whereas patients with ≥ 50% SHL reported using non-advanced systemic therapies. Significantly more patients in public settings received topical corticosteroids as their current treatment than in private settings (p = 0.0413).
Conclusion
The burden of disease associated with AA is underrecognized in Brazil. To achieve the stated treatment goals, there is a need to expand access to advanced therapies that overcome the limitations of traditional therapies.
Supplementary Information
The online version contains supplementary material available at https://doi.org/10.1007/s13555-026-01848-1.
Keywords: Alopecia areata, Brazil, Burden of disease, Real-world data
Introduction
Alopecia areata (AA) is an autoimmune disease characterized by patchy or complete nonscarring hair loss on the scalp, with or without additional loss of facial and/or body hair [1]. AA can manifest in various patterns, ranging from small patches on the scalp to complete loss of scalp hair (alopecia totalis [AT]) or complete loss of all body hair (alopecia universalis [AU]) [1, 2]. The disease course of AA is unpredictable, and patients often experience periods of relapse and remission [2]. AA affects approximately 0.58% to 2% of the global population [3–6]. AA is associated with significant psychosocial impacts, including anxiety and depression, which can all profoundly affect patients’ health-related quality of life (QoL) [7–10].
Data examining how AA impacts patients are needed to better understand the burden of AA and the unmet treatment need, but the availability of such data is limited, especially in certain regions, such as Latin America. In Brazil, AA accounts for a notable proportion of dermatologic consultations and is among the top primary dermatologic diagnoses for many patient groups [11, 12]. However, current epidemiologic data on AA in Brazil are sparse, highlighting a critical gap in understanding the disease burden and its impact on patients [11, 13, 14]. In addition, the region’s unique geographic, ethnic, cultural, and economic conditions exacerbate the challenges in managing AA, including limited access to specialized dermatologic care and therapies [13].
The Brazilian consensus statement on the treatment of AA (2025) recommends various treatments based on disease severity [15]. For mild and moderate disease, the guidelines recommend traditional AA therapies, including intralesional corticosteroids (CS), topical CS, systemic CS, systemic immunomodulators, topical minoxidil, oral minoxidil, and topical immunotherapy. For severe AA, the Brazilian consensus statement recommends Janus kinase (JAK) inhibitors as having the strongest evidence for treating these patients, while systemic CS and immunomodulators offer additional treatment options in cases of rapid progression or when JAK inhibitors are unavailable. A number of advanced therapies have been approved for treating AA in Brazil, including various JAK 1/2 inhibitors and ritlecitinib, an orally administered, irreversible kinase inhibitor that selectively inhibits Janus kinase 3 (JAK3) and members of the TEC family of kinases. However, patient access to these modern approved drugs is limited in Brazil [13]. This underscores the need for more data on the epidemiology of AA and current treatment patterns in Brazil to inform effective management strategies and improve patient outcomes including the psychosocial and economic impacts of AA in the region.
The objective of this study was to examine patient demographics, clinical characteristics, the patient journey, AA treatment patterns, and physician perceptions of AA disease management among adult patients with AA in Brazil. Results were stratified by the extent of scalp hair loss (SHL) and by health care access (public vs private settings).
Methods
Study Design and Data Source
This study used data from the Adelphi Real World AA II Brazil Disease Specific Programme™ (DSP), a cross-sectional survey that incorporated retrospective data collection from dermatologists and their patients. DSPs serve as independent and impartial data sources and are not tailored to address specific research questions. They adhere to the European Pharmaceutical Market Research Association (EphMRA) Code of Conduct and undergo review by the Pearl Institutional Review Board (IRB).
The AA II Brazil DSP was conducted in Brazil from March to June 2024. Dermatologists eligible for the DSP included those actively managing ≥ 8 adult patients with AA monthly, with a minimum of two mild, four moderate, and two severe or very severe cases. Eligible patients had a diagnosis of AA, were aged ≥ 18 years, and were not currently participating in a clinical trial. Participating dermatologists were required to complete patient record forms (PRFs) for their next eight consecutive consulting patients. The PRF included details on patient demographics, clinical characteristics, and treatment history. Each PRF was completed at a single time point, although physicians included historical data from patients’ medical records. Patients with completed PRFs were invited to take a voluntary patient self-completion survey (PSC) independently. The PRFs and PSCs were interconnected through unique, pseudo-anonymized codes assigned to both physicians and patients. While minimal selection criteria were imposed, participation was influenced by willingness to complete the record forms.
Study Variables and Analysis
Variables assessed included patient demographics, clinical characteristics, physician-reported treatment goals, physician-reported areas for improvement of current treatments, patients’ prior and current treatments, and physician-reported issues with current treatments. Results were presented for the patient population overall and stratified by extent of SHL, type of health care access (public health setting and private health setting), and therapy type (traditional vs advanced). Traditional therapies were defined as systemic CS, topical CS, topical minoxidil, oral minoxidil, topical calcineurin inhibitor, systemic immunomodulators, and phototherapy; advanced therapies were defined as oral and topical JAK inhibitors, topical immunomodulators, and biologic therapy. Chronic AA was defined as the reversal of the terminal-vellus ratio and many more miniaturized hairs becoming visible at the expense of terminal hairs.
Data analysis was conducted using Stata 19 software, version 19.0 (StataCorp, College Station, TX). Descriptive statistics were reported overall and for each subgroup including count, mean, and standard deviation for continuous variables and count and percentage of patients for categorical variables. Bivariate analysis was used to compare patients stratified by extent of SHL (0%, 1–20%, 21–49%, 50–94%, and 95–100%). Analysis of variance (ANOVA) was used for continuous variables, Fisher’s exact test for categorical variables (or chi-squared when Fisher’s exact test could not be calculated), and Kruskal-Wallis tests were used for ordered categorical variables. Nominal P-values were provided. Patients with missing values for a particular variable were removed from analyses involving that variable but remained eligible for other analyses. Missing data were not imputed, and no adjustments were made for multiplicity.
Ethical approval
A complete description of the survey methods has been previously published and validated [16–19]. Using a checkbox, patients provided informed consent for use of their anonymized and aggregated data for research and publication in scientific journals. Data were collected in such a way that patients and physicians could not be identified directly; all data were aggregated and de-identified before receipt.
Data collection was undertaken in line with European Pharmaceutical Marketing Research Association [20] guidelines, and as such it does not require ethics committee approval. Each survey was conducted in full accordance with the relevant legislation in effect at the time of data collection, including the Health Information Technology for Economic and Clinical Health Act [21].
Results
Patient Demographics and Clinical Characteristics
Overall, 44 dermatologists provided information on 341 patients with a mean (SD) age of 34.8 (12.2) years; 174/341 patients (51.2%) were female and 229/341 (67.2%) were White. When stratified by extent of SHL (0%, 1–20%, 21–49%, 50–94%, and 95–100%), demographic characteristics were comparable across groups. As the extent of hair loss increased, the proportion of patients working full-time decreased (64.5%, 74.4%, 61.0%, 50.0%, and 48.0%, respectively; p = 0.0101, Table 1).
Table 1.
Patient demographics by extent of SHL
| Overall | 0% SHL | 1–20% SHL | 21–49% SHL | 50–94% SHL | 95–100% SHL | p-value | |
|---|---|---|---|---|---|---|---|
| Patient age, years | |||||||
| All patients | 341 | 32 | 95 | 128 | 61 | 25 | 0.6485 |
| Mean (SD) | 34.8 (12.2) | 35.2 (13.0) | 33.7 (11.3) | 35.3 (11.7) | 34.0 (12.7) | 37.4 (14.9) | |
| Patient sex, n (%) | |||||||
| Patients with known data | 340 | 32 | 94 | 128 | 61 | 25 | 0.5014 |
| Male | 166 (48.8) | 19 (59.4) | 45 (47.9) | 58 (45.3) | 29 (47.5) | 15 (60.0) | |
| Female | 174 (51.2) | 13 (40.6) | 49 (52.1) | 70 (54.7) | 32 (52.5) | 10 (40.0) | |
| Ethnic origin, n (%) | |||||||
| All patients | 341 | 32 | 95 | 128 | 61 | 25 | |
| White | 229 (67.2) | 21 (65.6) | 64 (67.4) | 86 (67.2) | 42 (68.9) | 16 (64.0) | 0.9922 |
| Black | 54 (15.8) | 6 (18.8) | 12 (12.6) | 20 (15.6) | 12 (19.7) | 4 (16.0) | 0.7677 |
| South or Central American Native | 65 (19.1) | 8 (25.0) | 22 (23.2) | 23 (18.0) | 7 (11.5) | 5 (20.0) | 0.3578 |
| Other* | 6 (1.8) | 0 (0.0) | 0 (0.0) | 2 (1.6) | 4 (6.6) | 0 (0.0) | - |
| Patient employment status, n (%) | |||||||
| Patients with known data | 327 | 31 | 90 | 123 | 58 | 25 | 0.0101 |
| Working full time | 203 (62.1) | 20 (64.5) | 67 (74.4) | 75 (61.0) | 29 (50.0) | 12 (48.0) | |
| Student | 58 (17.7) | 5 (16.1) | 14 (15.6) | 20 (16.3) | 13 (22.4) | 6 (24.0) | |
| Working part time | 22 (6.7) | 4 (12.9) | 5 (5.6) | 7 (5.7) | 5 (8.6) | 1 (4.0) | |
| Unemployed | 21 (6.4) | 0 (0.0) | 2 (2.2) | 11 (8.9) | 5 (8.6) | 3 (12.0) | |
| Homemaker | 10 (3.1) | 1 (3.2) | 1 (1.1) | 7 (5.7) | 1 (1.7) | 0 (0.0) | |
| Retired | 10 (3.1) | 1 (3.2) | 1 (1.1) | 3 (2.4) | 2 (3.5) | 3 (12.0) | |
| On long term-sick leave | 3 (0.9) | 0 (0.0) | 0 (0.0) | 0 (0.0) | 3 (5.2) | 0 (0.0) | |
| Modalities of health care access, n (%) | |||||||
| Patients with known data | 332 | 31 | 93 | 124 | 60 | 24 | < 0.0001 |
| Public health system |
77 (23.2) |
2 (6.5) |
15 (16.1) |
34 (27.4) |
19 (31.7) |
7 (29.2) |
|
| Self-financed (out-of-pocket expenses) | 116 (34.9) | 9 (29.0) | 24 (25.8) | 48 (38.7) | 22 (36.7) | 13 (54.2) | |
| Private health insurance |
110 (33.1) |
17 (54.8) |
38 (40.9) |
36 (29.0) |
16 (26.7) |
3 (12.5) |
|
| Other | 29 (8.7) | 3 (9.7) | 16 (17.2) | 6 (4.8) | 3 (5.0) | 1 (4.2) | |
SHL scalp hair loss
*East or Southeast Asian, Middle Eastern or North African, and Other
Modalities of health care access also significantly differed across SHL groups (p < 0.0001; Table 1); patients with a greater extent of SHL were more likely to receive care in the public health system (29.2%), while patients with a lesser extent of SHL tended to require private health insurance (54.8%). The 50–94% and 95–100% SHL groups displayed more severe disease symptoms, including more patients in these groups than in those with < 50% SHL experiencing eyebrow (55.7% and 68.0%), eyelash (37.7% and 64.0%), body (27.9% and 44.0%), and pubic hair loss (18.0% and 28.0%; p < 0.0001 for all; Table 2). A greater proportion of patients in the 50–94% (41.0%) and 95–100% (40.0%) SHL groups was reported to have chronic AA vs the other groups (0% SHL, 6.3%; 1–20% SHL, 14.7%; 21–49% SHL, 21.1%; p < 0.0001; Table 2), and more patients in the 95–100% SHL group had AA that was worsening rapidly (20%) than in the other SHL groups (0%, 0.0%; 1–20%, 0.0%; 21–49%, 7.0%; 50–94%, 8.2%; p < 0.0001; Table 2). As the extent of SHL increased, the proportion of patients with current hair regrowth decreased, with the fewest patients experiencing current hair regrowth in the 95–100% SHL group (28%, p < 0.0001). The mean (SD) number of estimated health care provider (HCP) visits over the next 12 months also increased as the extent of SHL increased, from 4.5 (4.1) in the 0% SHL group to 6.7 (2.8) in the 95–100% SHL group (p = 0.0137).
Table 2.
Clinical characteristics by extent of SHL
| Overall | 0% SHL | 1–20% SHL | 21–49% SHL | 50–94% SHL | 95–100% SHL | p-value | |
|---|---|---|---|---|---|---|---|
| Current disease progression, n (%) | |||||||
| All patients | 341 | 32 | 95 | 128 | 61 | 25 | < 0.0001 |
| Improving | 139 (40.8) | 16 (50.0) | 57 (60.0) | 40 (31.3) | 20 (32.8) |
6 (24.0) |
|
| Stable | 132 (38.7) | 11 (34.4) | 34 (35.8) | 53 (41.4) | 24 (39.3) | 10 (40.0) | |
| Worsening slowly | 51 (15.0) |
5 (15.6) |
4 (4.2) |
26 (20.3) | 12 (19.7) |
4 (16.0) |
|
| Worsening rapidly |
19 (5.6) |
0 (0.0) |
0 (0.0) |
9 (7.0) |
5 (8.2) |
5 (20.0) |
|
| Current AA type, n (%) | |||||||
| All patients | 341 | 32 | 95 | 128 | 61 | 25 | < 0.0001 |
| Acute | 97 (28.5) |
7 (21.9) |
27 (28.4) | 34 (26.6) | 22 (36.1) |
7 (28.0) |
|
| Subacute | 74 (21.7) |
5 (15.6) |
17 (17.9) | 41 (32.0) |
7 (11.5) |
4 (16.0) |
|
| Chronic | 78 (22.9) |
2 (6.3) |
14 (14.7) | 27 (21.1) | 25 (41.0) | 10 (40.0) | |
| Recovery | 92 (27.0) | 18 (56.3) | 37 (39.0) | 26 (20.3) |
7 (11.5) |
4 (16.0) |
|
| Current symptoms, n (%) | |||||||
| All patients | 341 | 32 | 95 | 128 | 61 | 25 | |
| Scalp hair loss |
309 (90.6) |
0 (0.0) |
95 (100.0) |
128 (100.0) |
61 (100.0) |
25 (100.0) |
< 0.0001 |
| Eyebrow hair loss | 101 (29.6) |
6 (18.8) |
5 (5.3) |
39 (30.5) | 34 (55.7) | 17 (68.0) | < 0.0001 |
| Eyelash hair loss | 59 (17.3) |
1 (3.1) |
1 (1.1) |
18 (14.1) | 23 (37.7) | 16 (64.0) | < 0.0001 |
| Body hair loss (arms, legs, chest) | 38 (11.1) |
4 (12.5) |
1 (1.05) |
5 (3.9) |
17 (27.9) | 11 (44.0) | < 0.0001 |
| Pubic hair loss |
20 (5.9) |
0 (0.0) |
0 (0.0) |
2 (1.6) |
11 (18.0) |
7 (28.0) |
< 0.0001 |
| Facial hair loss (moustache or beard) | 39 (11.4) |
9 (28.1) |
6 (6.3) |
12 (9.4) |
9 (14.8) |
3 (12.0) |
0.0205 |
| Hair regrowth currently, n (%) | |||||||
| Patients with known data | 308 | 29 | 86 | 110 | 58 | 25 | < 0.0001 |
| No | 108 (35.1) |
4 (13.8) |
10 (11.6) | 48 (43.6) | 28 (48.3) | 18 (72.0) | |
| Yes | 200 (64.9) | 25 (86.2) | 76 (88.4) | 62 (56.4) | 30 (51.7) |
7 (28.0) |
|
| Estimated number of consultations over next 12 months | |||||||
| Patients with known data | 241 | 21 | 76 | 81 | 44 | 19 | 0.0137 |
| Mean (SD) |
5.1 (3.3) |
4.5 (4.1) |
4.2 (2.5) |
5.2 (3.4) |
5.7 (3.7) |
6.7 (2.8) |
|
AA alopecia areata, SHL scalp hair loss
Patient Journey to Diagnosis
The mean (SD) time since patients first experienced AA symptoms was 3.1 (4.8) years, and time since diagnosis was 2.4 (4.4) years, with no significant differences across SHL groups (Table 3) and no significant differences between patients being treated in public vs private health systems (Supplementary Table S1). The time since the current HCP started managing the patient was a mean (SD) of 13.9 (18.5) months, and there were significant differences across the groups (p = 0.0030), with patients in the 0% SHL group managed for the longest time (mean, 23.8; SD, 25.8 months) compared with other SHL groups (Table 3), but there were no significant differences between public vs private health systems (Supplementary Table S1). Physician assessment of disease severity at referral, diagnosis, and currently differed significantly across SHL groups, with increasing extent of SHL correlating with increasing disease severity (p < 0.0001 for all; Table 3); there were no significant differences between patients receiving care in public vs private settings (Supplementary Table S1).
Table 3.
Patient journey to diagnosis by extent of SHL
| Overall | 0% SHL | 1–20% SHL | 21–49% SHL | 50–94% SHL | 95–100% SHL | p-value | |
|---|---|---|---|---|---|---|---|
| Time since patient first experienced AA symptoms (days) | |||||||
| Patients with known data | 240 | 22 | 74 | 83 | 45 | 16 | 0.1157 |
| Mean (SD) | 1124.1 (1755.6) | 916.1 (920.0) | 1204.5 (2356.6) | 797.9 (1104.7) | 1644.7 (1821.8) | 1265.3 (1723.4) | |
| Time since diagnosis (days) | |||||||
| Patients with known data | 264 | 22 | 84 | 95 | 46 | 17 | 0.4847 |
| Mean (SD) | 889.2 (1600.2) | 846.7 (940.8) | 899.1 (2081.7) | 699.4 (1188.0) | 1210.8 (1531.4) | 1086.7 (1733.6) | |
| Time since the physician started managing the patient (days) | |||||||
| Patients with known data | 321 | 29 | 92 | 115 | 61 | 24 | 0.0030 |
| Mean (SD) | 418.2 (561.2) | 723.7 (783.4) | 443.6 (522.6) | 290.1 (451.3) | 487.2 (618.6) | 390.3 (575.5) | |
| Physician’s assessment of patient’s severity at referral, n (%) | |||||||
| Patients with known data | 218 | 16 | 52 | 87 | 48 | 15 | < 0.0001 |
| Mild | 47 (21.6) | 6 (37.5) | 39 (75.0) | 2 (2.3) | 0 (0.0) | 0 (0.0) | |
| Moderate | 96 (44.0) | 7 (43.8) | 9 (17.3) | 73 (83.9) | 6 (12.5) | 1 (6.7) | |
| Severe | 51 (23.4) | 1 (6.3) | 3 (5.8) | 12 (13.8) | 32 (66.7) | 3 (20.0) | |
| Very severe | 24 (11.0) | 2 (12.5) | 1 (1.9) | 0 (0.0) | 10 (20.8) | 11 (73.3) | |
| Physician’s assessment of patient’s severity at diagnosis, n (%) | |||||||
| Patients with known data | 276 | 27 | 86 | 90 | 51 | 22 | < 0.0001 |
| Mild | 97 (35.1) | 17 (63.0) | 61 (70.9) | 12 (13.3) | 5 (9.8) | 2 (9.1) | |
| Moderate | 113 (40.9) | 7 (25.9) | 21 (24.4) | 69 (76.7) | 12 (23.5) | 4 (18.2) | |
| Severe | 44 (15.9) | 2 (7.4) | 4 (4.7) | 8 (8.9) | 27 (52.9) | 3 (13.6) | |
| Very severe | 22 (8.0) | 1 (3.7) | 0 (0.0) | 1 (1.1) | 7 (13.7) | 13 (59.1) | |
| Physician’s assessment of patient’s severity currently, n (%) | |||||||
| Patients with known data | 341 | 32 | 95 | 128 | 61 | 25 | < 0.0001 |
| Mild | 88 (25.8) | 16 (50.0) | 69 (72.6) | 3 (2.3) | 0 (0.0) | 0 (0.0) | |
| Moderate | 168 (49.3) | 13 (40.6) | 23 (24.2) | 119 (93.0) | 10 (16.4) | 3 (12.0) | |
| Severe | 59 (17.3) | 2 (6.3) | 2 (2.1) | 6 (4.69) | 46 (75.4) | 3 (12.0) | |
| Very severe | 26 (7.6) | 1 (3.2) | 1 (1.1) | 0 (0.0) | 5 (8.2) | 19 (76.0) | |
SHL scalp hair loss
Most patients (90.3%) had their AA diagnosed by a dermatologist, and this proportion was consistently high across SHL groups (Table 4). There was no significant difference in the diagnosing physician specialty between patients in public vs private health systems (Supplementary Table S2). Most patients had either always been a patient of the physician completing the patient record form (29.7%) or self-referred from another HCP (40.0%), with no significant differences across SHL groups (Table 4). In private vs public health systems, a larger proportion of patients had always been a patient of the current dermatologist (34.3% vs 15.2%) and had self-referred from another HCP (41.5% vs 35.4%), while more patients in public settings were referred by a primary care physician (35.4% vs 6.1%; p < 0.0001; Supplementary Table S2). Common reasons for referral to their current dermatologist across SHL groups included that the physician to whom the patient was referred specializes in AA (19.0%) or the referring HCP is not specialized in dermatologic conditions (47.4%; Table 4). Significantly more patients in public vs private settings were referred because the referring HCP was not specialized in dermatologic conditions (60.5% vs 37.5%; p = 0.0359; Supplementary Table S2).
Table 4.
Referral and diagnosis history by extent of SHL
| Overall | 0% SHL | 1–20% SHL | 21–49% SHL | 50–94% SHL | 95–100% SHL | p-value | |
|---|---|---|---|---|---|---|---|
| Patient referral history, n (%) | |||||||
| Patients with known data | 330 | 32 | 94 | 123 | 59 | 22 | 0.1372 |
| Nobody, I have always been this patient’s physician* | 98 (29.7) | 14 (43.8) | 41 (43.6) | 28 (22.8) | 10 (17.0) | 5 (22.7) | |
| Patient self-referred from another HCP | 132 (40.0) | 13 (40.6) | 33 (35.1) | 56 (45.5) | 21 (35.6) | 9 (40.9) | |
| Another dermatologist | 29 (8.8) | 1 (3.1) | 5 (5.3) | 7 (5.7) | 13 (22.0) | 3 (13.6) | |
| Primary care physician | 43 (13.0) | 2 (6.3) | 10 (10.6) | 19 (15.5) | 9 (15.3) | 3 (13.6) | |
| Endocrinologist | 3 (0.9) | 0 (0.0) | 1 (1.1) | 2 (1.6) | 0 (0.0) | 0 (0.0) | |
| Psychiatrist | 7 (2.1) | 1 (3.1) | 0 (0.0) | 3 (2.4) | 2 (3.4) | 1 (4.6) | |
| Rheumatologist | 2 (0.6) | 0 (0.0) | 0 (0.0) | 1 (0.8) | 1 (1.7) | 0 (0.0) | |
| Internist | 1 (0.3) | 0 (0.0) | 0 (0.0) | 1 (0.8) | 0 (0.0) | 0 (0.0) | |
| Physician assistant | 1 (0.3) | 0 (0.0) | 0 (0.0) | 0 (0.0) | 1 (1.7) | 0 (0.0) | |
| Other | 9 (2.7) | 1 (3.1) | 3 (3.2) | 3 (2.4) | 1 (1.7) | 1 (4.6) | |
| I am seeing this patient because their usual physician is unavailable | 5 (1.5) | 0 (0.0) | 1 (1.1) | 3 (2.4) | 1 (1.7) | 0 (0.0) | |
| Reason for referral, n (%) | |||||||
| Patients with known data | 95 | 5 | 19 | 36 | 27 | 8 | |
| I specialize in AA | 18 (19.0) | 1 (20.0) | 5 (26.3) | 5 (13.9) | 4 (14.8) | 3 (37.5) | 0.4245 |
| Referring HCP is not specialized in dermatologic conditions | 45 (47.4) | 1 (20.0) | 5 (26.3) | 22 (61.1) | 13 (48.2) | 4 (50.0) | 0.1061 |
| Referring HCP had exhausted all therapy options available to them | 6 (6.3) | 1 (20.0) | 1 (5.3) | 2 (5.6) | 2 (7.4) | 0 (0.0) | 0.6896 |
| Patients condition got worse | 10 (10.5) | 0 (0.0) | 0 (0.0) | 3 (8.3) | 6 (22.2) | 1 (12.5) | 0.1440 |
| Patient has complications which I am best placed to manage | 3 (3.16) | 0 (0.0) | 1 (5.3) | 2 (5.6) | 0 (0.0) | 0 (0.0) | 0.6524 |
| Patient has other conditions which I am best placed to manage | 4 (4.2) | 0 (0.0) | 0 (0.0) | 2 (5.6) | 2 (7.4) | 0 (0.0) | 0.8231 |
| To try and identify triggers of AA | 6 (6.3) | 0 (0.0) | 4 (21.1) | 2 (5.6) | 0 (0.0) | 0 (0.0) | 0.0862 |
| Patient requires a treatment that the referring HCP is not permitted/comfortable prescribing | 11 (11.6) | 1 (20.0) | 4 (21.1) | 3 (8.3) | 3 (11.1) | 0 (0.0) | 0.4528 |
| Patient requested | 11 (11.6) | 1 (20.0) | 4 (21.6) | 1 (2.8) | 4 (14.8) | 1 (12.5) | 0.1340 |
| Other reason | 8 (8.4) | 3 (60.0) | 1 (5.3) | 2 (5.6) | 2 (7.4) | 0 (0.0) | 0.0169 |
| Diagnosing HCP, n (%) | |||||||
| Patients with known data | 331 | 30 | 94 | 123 | 60 | 24 | 0.0257 |
| Yourself* | 178 (53.8) | 23 (76.7) | 61 (64.9) | 64 (52.0) | 20 (33.3) | 10 (41.7) | |
| Another dermatologist | 121 (36.6) | 7 (23.3) | 28 (29.8) | 43 (35.0) | 32 (53.3) | 11 (45.8) | |
| Primary care physician | 21 (6.3) | 0 (0.0) | 3 (3.2) | 11 (8.9) | 5 (8.3) | 2 (8.3) | |
| Psychiatrist | 3 (0.9) | 0 (0.0) | 0 (0.0) | 1 (0.8) | 1 (1.7) | 1 (4.2) | |
| Rheumatologist | 2 (0.6) | 0 (0.0) | 1 (1.1) | 0 (0.0) | 1 (1.7) | 0 (0.0) | |
| Endocrinologist | 1 (0.3) | 0 (0.0) | 0 (0.0) | 0 (0.0) | 1 (1.7) | 0 (0.0) | |
| Other | 5 (1.5) | 0 (0.0) | 1 (1.1) | 4 (3.3) | 0 (0.0) | 0 (0.0) | |
AA alopecia areata, HCP health care provider, SHL scalp hair loss
*The physicians completing the patient record form, who were dermatologists
Treatment Goals
Among physician-reported treatment goals, reducing scalp hair loss was reported for > 90% of patients across all groups with SHL (Table 5). Many common treatment goals were observed in more patients in the 50–94% and 95–100% SHL groups vs other groups, including to reduce eyebrow hair loss (49.2% and 64.0%; p < 0.0001), reduce psychologic impact (70.5% and 64.0%; p = 0.0002), improve QoL (75.4% and 72.0%; p = 0.0002), reduce impact on patients’ ability to do what they enjoy (41.0% and 36.0%; p = 0.0054), and achieve long-term/chronic control of the condition (41.0% and 48.0%; p = 0.0400). The most common physician-reported area for improvement with the current treatment was in reducing scalp hair loss (reported for 51.7% of patients); this was followed by improvements in safety, scalp hair regrowth, and patient QoL (Fig. 1).
Table 5.
Physician-reported treatment goals by extent of SHL
| N (%) | Overall N = 341 |
0% SHL N = 32 |
1–20% SHL N = 95 |
21–49% SHL N = 128 |
50–94% SHL N = 61 |
95–100% SHL N = 25 |
p-value |
|---|---|---|---|---|---|---|---|
| Reduce scalp hair loss | 314 (92.1) |
16 (50.0) |
91 (95.8) |
126 (98.4) |
58 (95.1) |
23 (92.0) |
< 0.0001 |
| Reduce eyebrow hair loss |
94 (27.6) |
5 (15.6) |
8 (8.4) |
35 (27.3) |
30 (49.2) |
16 (64.0) |
< 0.0001 |
| Reduce psychologic impact | 201 (59.0) |
9 (28.1) |
48 (50.5) |
85 (66.4) |
43 (70.5) |
16 (64.0) |
0.0002 |
| Improve quality of life | 199 (58.4) |
10 (31.3) |
48 (50.5) |
77 (60.2) |
46 (75.4) |
18 (72.0) |
0.0002 |
| Reduce impact on patients’ ability to do what they enjoy |
93 (27.3) |
5 (15.6) |
16 (16.8) |
38 (29.7) |
25 (41.0) |
9 (36.0) |
0.0054 |
| Achieve long-term/chronic control of the condition | 121 (35.5) |
12 (37.5) |
22 (23.2) |
50 (39.1) |
25 (41.0) |
12 (48.0) |
0.0400 |
SHL scalp hair loss
Fig. 1.
Physician-reported areas for improvement in current treatments (N = 269)
Treatment Patterns
For current AA treatments, there were significant differences among the SHL groups (Fig. 2). Topical or intralesional injected CS were more commonly used in patients in the lower %SHL groups, while systemic CS, for example, oral CS, were more frequently used in patients with higher %SHL (Fig. 2). The proportion of patients prescribed systemic immunomodulators differed across all groups (p < 0.0001), with the highest in the 50–94% SHL group (50.0%), while more patients in the 50–94% (25.0%) and 95–100% (33.3%) SHL groups received oral or topical JAK inhibitors than the other SHL groups (p < 0.0001; Fig. 2).
Fig. 2.
Current physician-reported treatment classes by extent of SHL. CS corticosteroid, IM immunomodulator, IV intravenous, JAKi Janus kinase inhibitor, QoL quality of life, SHL scalp hair loss. *p<0.05, **p<0.01, ****p<0.0001
Significantly more patients in public settings received topical CS as their current treatment than in private settings (57.3% vs 44.0%; p = 0.0413; Supplementary Table S3). Significantly more patients in public vs private settings received oral CS (42.7% vs 29.0%; p = 0.0291), and fewer received oral or topical JAK inhibitors (7.3% vs 11.3%; p = 0.403), which was not significant. The mean (SD) duration of current treatment differed between groups; the 0% (15.3 [17.6] months) and 1–20% (10.6 [12.5] months) SHL groups received their current treatment for longer than the 21–49% (6.2 [6.4] months), 50–94% (8.8 [10.0] months), and 95–100% (9.4 [16.0] months) SHL groups (p = 0.0063). There were no differences in current treatment duration between public vs private settings (Supplementary Table S3).
For the first treatment patients received immediately prior to their current treatment, the only significant difference among the SHL groups was that more patients with 0% SHL received topical immunomodulators (21.4%) than in the other SHL groups (1–20%, 0.0%; 21–49%, 0.0%; 50–94%, 9.5%; 95–100%, 0.0%; p = 0.0126; Supplementary Table S4); however, the small sample size may have contributed to a lack of other significant differences. Overall mean (SD) duration of first prior treatment did not significantly differ across SHL groups (Supplementary Table S4). More patients in private health settings received topical IM as the first prior treatment than in public settings (5.3% vs 0%; p = 0.5710; Supplementary Table S3); however, the difference was not significant. There were also no significant differences in the duration of the first prior treatment (Supplementary Table S3).
Reasons for switching from the first previous treatment to the current treatment differed significantly across SHL groups (Supplementary Table S5). The reason was reported as “condition improved” for more patients in the 0.0% (42.9%), 1–20% (36.8%), and 21–49% (12.8%) SHL groups than in the 50–94% (0%) and 95–100% (0.0%) groups (p = 0.0004). The other reasons that differed across the 0%, 1–20%, 21–49%, 50–94%, and 95–100% SHL groups were “lack of initial efficacy” (35.7%, 5.3%, 31.9%, 58.3%, and 50.0%, respectively, p = 0.0034), “lack of tolerability” (7.1%, 0.0%, 2.1%, 0.0%, and 30.0%, respectively, p = 0.0055), and “safety concerns over long-term use” (28.6%, 5.3%, 4.3%, 16.7%, and 20.0%, respectively, p = 0.444).
Among patients receiving care in public vs private settings, there were a few significant differences in reasons for switching treatments (Supplementary Table S6). When switching from the first previous treatment to the current one, more patients in private settings switched because of patient concerns about long-term safety than in public settings (9.3% vs 0.0%; p = 0.1949); however, this was not significant. When switching from the second to the first previous treatment, more patients in public settings did so because of lack of tolerability than in private settings (11.1% vs 2.5%; p = 0.3367), although this was not significant. There were no significant differences among reasons for switching from previous 3 to previous 2 and from previous 4 to previous 3 (Supplementary Table S6).
Issues with Current Treatments
A few trends were observed in physician-reported issues with current treatments. As the extent of SHL increased, the proportion of patients who experienced issues with their current treatment increased (p = 0.0001; Fig. 3A). Among patients with 0%, 1–20%, 21–49%, 50–94%, and 95–100% SHL, no issues with their current treatment were reported for 89%, 94%, 79%, 69%, and 63% of patients, respectively. The following issues were reported across SHL groups and for a greater proportion of patients in the 95–100% SHL group vs the other groups: lack of improvement in QoL (26.3%; p = 0.0003), worsened condition (21.1%; p = 0.0014), lack of initial efficacy (21.1%; p = 0.0016), burdensome monitoring requirements (10.5%; p = 0.0065), lack of compliance (10.5%; p = 0.0164), and loss of response over time (15.8%; p = 0.0180).
Fig. 3.
Physician-reported select issues experienced with current treatment by (A) extent of SHL, (B) traditional therapya vs JAK inhibitorsb, and (C) traditional therapya vs advanced therapiesc. CS corticosteroid, IM immunomodulator, JAK Janus kinase, QoL quality of life, SHL scalp hair loss. aTraditional treatments include systemic CS, topical CS, minoxidil, topical calcineurin inhibitor, systemic IM, and phototherapy. bJAK inhibitors include oral and topical JAK inhibitors. cAdvanced therapy includes oral and topical JAK inhibitors, topical immunomodulators, and biologic therapy. *p<0.05, **p<0.01, ****p<0.0001
When stratified by patients who received traditional therapies (systemic CS, topical CS, minoxidil, topical calcineurin inhibitor, systemic CS, and phototherapy) vs JAK inhibitors, there were no significant differences in physician-reported issues with current treatment (Fig. 3B). However, when comparing traditional therapy vs advanced therapies (oral and topical JAK inhibitors, topical immunomodulators, and biologic therapy), physicians reported that a significantly higher proportion of patients had a lack of initial efficacy when receiving advanced therapy (14.3% vs 5.1%; p = 0.0354; Fig. 3C).
Discussion
In this survey of dermatologists and their patients with AA in Brazil, a substantial proportion of AA cases involved severe scalp hair loss, characterized by ≥ 50% SHL. Patients with ≥ 50% SHL were more likely to have chronic, worsening disease, lower full-time employment, and less current hair regrowth than patients with < 50% SHL. These findings are consistent with the results of a survey of dermatologists and patients with AA across several European countries [22]. They are also supported by studies of dermatologists and their patients in the United Arab Emirates and Saudi Arabia, which found that patients with ≥ 50% SHL have more severe disease and greater work impairment than patients with < 50% SHL [23]. These findings are also consistent with treatment guidelines and consensus statements, including those from the Brazilian Society of Dermatology, which often define severe AA as ≥ 50% SHL [15, 24].
Our study found that current treatments for AA in Brazil are deeply rooted in traditional therapies. For patients with < 50% SHL, the most common current treatments were traditional non-systemic therapies (e.g., topical CS and intralesional injected CS), while for patients with ≥ 50% SHL, traditional systemic therapies (e.g., systemic immunomodulators and oral CS) were more common. While this is in line with studies of AA treatment patterns in other regions [22, 25, 26], the AA treatment guidelines from the Brazilian Society of Dermatology include JAK inhibitors as having the strongest evidence for treating severe AA [15, 27], and the proportion of patients with ≥ 50% SHL receiving JAK inhibitors was lower than the proportion receiving traditional therapies. It is possible that these findings may change in the future as clinician awareness of these relatively new guidelines increases. It is also possible that awareness of newer advanced therapies may be low, as a survey of dermatologists in the Middle East found that awareness of JAK inhibitors for the treatment of AA ranged from 12% to 72% [28]. The modality of health care access could also impact the treatment patients receive. Reduced access to JAK inhibitors for patients with AA within the public health system has been observed previously [29], and studies in Brazil have demonstrated inequalities in health care services due to private vs public health coverage along with gaps between treatment guidelines and treatments patients are able to access [30, 31]. As our study found that a larger proportion of patients with ≥ 50% SHL was receiving care in public vs private health systems in Brazil, the reduced access to advanced therapies observed in public health care settings could greatly impact patient outcomes.
The AA of most patients in this survey was diagnosed by a dermatologist across all SHL and health care groups. Patients treated in a public setting were more likely to have been referred by a primary care physician because the referring HCP was not specialized in dermatologic conditions than patients treated in a private setting. Regardless of differences in referral history, there were no significant differences between patients with public vs private health care in AA disease severity at referral or diagnosis and in the time since the current physician started managing the patient. Together with our results on the differences in treatments received by patients with public vs private health care, these findings suggest that for patients with AA in Brazil, health care type may not affect their access to dermatologists for managing their condition but may impact their ability to access medications. This is supported by a study of health care services and medications in Brazil that found a 3.8% unmet need for health care services, while the unmet need for medications was 7.5% [30]. Further studies may be needed to assess geographical disparities. Additional investigations should evaluate the higher proportion of severe cases observed among those receiving care in the public health system, which may indicate barriers to access for milder cases, as well as a long time to diagnosis, which calls for disease awareness in the medical community. This study also found that use of the private health system contributed to inequalities in unmet needs for healthcare services and medicines (40% and 73% of overall inequality, respectively). The authors suggest that policy interventions to increase access to health care services that include coverage of advanced therapies for the treatment of AA are needed in Brazil [30].
In the present study, treatment goals for patients with AA included scalp hair regrowth, followed by reducing eyebrow hair loss and improving patients’ QoL. These treatment goals aligned with the physician-reported areas for improving current treatments, the most common of which were scalp hair loss/regrowth, safety, especially for long-term use, and improved QoL. Similar unmet needs in the treatment of AA were found in surveys of dermatologists in several European and Middle Eastern countries[22, 28]. A survey of dermatologists in Saudi Arabia and the United Arab Emirates found that treating severe AA is challenging, as traditional treatments can have limited efficacy, and physicians are concerned about the safety of current treatments [32]. Our findings also reflect the growing recognition of health-related QoL as an important component of AA diagnosis and severity [32–34]. Overall, these findings suggest that need remains for safe, effective, long-term treatment options that improve QoL for patients with AA.
Physicians in Brazil reported several issues with current AA treatments, which increased with the extent of SHL. This trend is not unexpected, as more severe AA has been found to be more refractory to treatment [35], and spontaneous remission is more commonly observed among patients with milder disease [36]. Physicians reported lack of initial efficacy as an issue among significantly more patients receiving advanced therapies, but lack of initial efficacy was not reported as a significant issue among patients receiving JAK inhibitors. Onset of efficacy among JAK inhibitors by 24 and 36 weeks is supported by clinical trial data. Both ritlecitinib, a dual JAK3/TEC family kinase inhibitor, and baricitinib, a JAK1/2 inhibitor, have shown efficacy and safety in patients with severe AA [37, 38]. However, access is currently a limiting factor for these treatments [13].
This study has several limitations inherent to survey studies. First, patients participating in the surveys may not reflect the general AA population, as they are visiting their physician and may be more severely affected than those who do not consult their physician as frequently. Second, the DSP is not based on a true random sample of physicians or patients. While minimal inclusion criteria governed the selection of the participating physicians, participation is influenced by willingness to complete the survey. Third, physicians are asked to provide data from a consecutive series of patients to avoid selection bias, but no formal procedures for verifying patient selection are in place. Fourth, identification of severity is based on the judgment of the respondent physician and not a formalized diagnostic checklist, but is representative of the physician’s real-world classification of the patient. Fifth, the point-in-time design of this study prevents any conclusions about causal relationships; however, identification of significant associations is possible. Sixth, recall bias might also have affected responses from both patients and physicians to the questionnaires, a common limitation of surveys. However, the data for these analyses were collected at the time of each patient’s appointment, and this is expected to reduce the likelihood of recall bias. Seventh, while our research design included methods to ensure that physicians and staff were unaware of patient responses on the patient-reported forms, it was not possible to confirm that no information exchange occurred between physicians and their patients. This has the potential to undermine the accuracy of estimated treatment adherence and patient responses to the standardized PRO questionnaires. Eighth, fully completed physician-reported forms and patient-reported forms were not obtained for all eligible patients. It is unclear whether this may have introduced a bias to our results. Missing data were not imputed; therefore, the base of patients for analysis could vary from variable to variable and is reported separately for each analysis. Finally, we were not able to evaluate differences in our results attributable to physician specialty. We recognize that the level of knowledge and management strategies for AA might differ between primary care physicians and specialists and that such differences might affect treatment satisfaction and clinical outcomes.
Conclusions
The burden of disease associated with AA is underrecognized in Latin American countries, including Brazil. To better understand the treatment landscape within this context, it is therefore important to disentangle disease burden, scalp hair loss, and access to care. The primary treatment goal for patients was regrowth of scalp hair, followed by reducing psychosocial burdens and improving QoL. Among patients with AA in Brazil, a substantial number of cases are characterized by severe scalp hair loss, with patients with ≥ 50% SHL exhibiting more severe disease manifestations.
At the time of this survey, treatments for AA in Brazil were predominantly based on traditional therapeutic approaches for patients with both < 50% and ≥ 50% SHL. The higher reported use of advanced therapies among private patients indicates that access to advanced AA therapies in Brazil may be impacted by whether patients are treated in public or private health care settings. To achieve the stated treatment goals, there is a need to expand access to advanced therapies that overcome the limitations of traditional therapies.
Supplementary Information
Below is the link to the electronic supplementary material.
Acknowledgements
The authors thank the study participants for their involvement in the study.
Medical Writing and Editorial Support
Editorial/medical writing support under the guidance of authors was provided by Nucleus Global, an Inizio Company, and was funded by Pfizer Inc. in accordance with Good Publication Practice (GPP 2022) guidelines (Ann Intern Med. 2022; 10.7326/M22-1460).
Author Contribution
Leonardo Spagnol Abraham, Ashley S. Cha-Silva, Camila Natal De Gaspari, Daniela V. Pachito, Peter Anderson, Emily Quinones, Alexa Russnak, Samantha K Kurosky, and Isabella Doche were involved in (1) conception and design, or analysis and interpretation of data; (2) drafting the article and revising it critically for important intellectual content; and (3) final approval of the version to be published, and therefore meet the ICMJE guidelines for authorship.
Funding
This study was sponsored by Pfizer Inc. The journal’s Rapid Service Fee was funded by Pfizer Inc. The Disease Specific Programme is a wholly owned Adelphi Real World product, of which Pfizer Inc. is one of multiple subscribers. Pfizer Inc. funded the data analysis of this study. Pfizer Inc. participated in interpretation of data, review, and approval of the abstract. All authors contributed to development of the abstract and maintained control over final content. No honoraria or payments were made for authorship.
Data Availability
All data, that is, methodology, materials, data, and data analysis, that support the findings of this survey are the intellectual property of Adelphi Real World. All requests for access should be addressed directly to Peter Anderson at peter.anderson@omc.com.
Declarations
Conflict of Interest
Leonardo Spagnol Abraham declares participation in clinical trials for Janssen; sponsored lectures for Vichy, GSK, Pfizer Inc., Achè, and FQM Melora; event support for Pfizer Inc. and Tricholab; and an advisory board for Pfizer Inc. and Vichy Laboratoires. Ashley S. Cha-Silva and Samantha K Kurosky are employees of Pfizer Inc. and own stock/stock options in Pfizer Inc. Camila Natal De Gaspari and Daniela V. Pachito are employees of Pfizer Brazil and own stock/stock options in Pfizer Inc. Peter Anderson, Emily Quinones, and Alexa Russnak are employees of Adelphi Real World, Bollington, UK. Isabella Doche declares participation in advisory boards for Veradermics and Pfizer Inc.; consultant honoraria from Veradermics, Achè, Pfizer Inc. and Loreal; speaker honoraria from Pierre-Fabre, Loreal, GSK and Loreal.
Ethical Approval
A complete description of the survey methods has been previously published and validated [16–19]. Using a checkbox, patients provided informed consent for use of their anonymized and aggregated data for research and publication in scientific journals. Data were collected in such a way that patients and physicians could not be identified directly; all data were aggregated and de-identified before receipt. Data collection was undertaken in line with European Pharmaceutical Marketing Research Association [20] guidelines, and as such it does not require ethics committee approval. Each survey was performed in full accordance with relevant legislation at the time of data collection, including the Health Information Technology for Economic and Clinical Health Act legislation [21].
Footnotes
Publisher's Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
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Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Supplementary Materials
Data Availability Statement
All data, that is, methodology, materials, data, and data analysis, that support the findings of this survey are the intellectual property of Adelphi Real World. All requests for access should be addressed directly to Peter Anderson at peter.anderson@omc.com.