Abstract
Background
Vitiligo is an autoimmune disorder that causes patchy loss of skin pigmentation. Up to 2.16% of pediatric patients may have vitiligo. This study estimated vitiligo point prevalence in children and adolescents (ages: 4–11 and 12–17 years) in the United States (US).
Methods
An online, population-based survey of a nationally representative sample of individuals based on 2017 US Census Bureau estimates for age, race, Hispanic origin, income, and geographic region was conducted from December 2019 to March 2020. Parent/legal guardian proxies responded on behalf of their children or adolescents to vitiligo screening questions. Proxy-reported vitiligo status was adjudicated by expert dermatologists who reviewed photographs of vitiligo lesions uploaded by proxies using a teledermatology application. Estimated point prevalence (including diagnosed and undiagnosed vitiligo and its subtypes) was calculated for proxy-reported and clinician-adjudicated vitiligo.
Results
There were 9,118 eligible proxy responses (5,209 children, mean age 7.7 years; 3,909 adolescents, mean age 14.4 years). The proxy-reported vitiligo prevalence (95% confidence interval) for children and adolescents was 1.52% (1.11–1.93) and 2.16% (1.66–2.65), respectively. The clinician-adjudicated prevalence (sensitivity analysis bounds) was 0.84% (0.83–1.23) and 1.19% (1.18–1.74), respectively. Approximately 69% of children and 65% of adolescents had nonsegmental vitiligo (clinician adjudicated) and up to 50% may be undiagnosed.
Conclusion
Based on the clinician-adjudicated prevalence estimates, there were more than 591,000 cases of vitiligo in children and adolescents in the US in 2020. More than two-thirds had nonsegmental vitiligo and nearly half may be undiagnosed. Future studies should confirm these findings.
Keywords: Observational study, Study prevalence, Survey, United States, Vitiligo
Introduction
Vitiligo is characterized by a patchy loss of skin pigmentation due to the immune system targeting melanocytes in the epidermis. Vitiligo has been classified into two major clinical forms: nonsegmental vitiligo (NSV) and segmental vitiligo (SV) [1]. The most common form, NSV, results in bilateral symmetric distribution of lesions on the body, whereas SV is less common (5–16%) and usually presents as unilateral lesions. Furthermore, NSV has an unpredictable disease course with progressive onset and multiple flares, whereas SV usually stabilizes after a few months [1, 2].
The onset of vitiligo can occur at any age. However, the disease follows a bimodal pattern, with early onset at 7.3 years and late onset at 40.5 years of age [3]. The condition can be associated with considerable negative psychosocial impacts in children and their caregivers, and it has been shown that the impact of childhood vitiligo may persist in adult life with an impact on social development [3, 4, 5, 6, 7, 8, 9]. An analysis of 26 studies from around the world reported the prevalence of vitiligo in up to 2.16% of children [10].
There have been no recent studies conducted to estimate the point prevalence of vitiligo in the general population of children and adolescents in the United States (US). The prevalence of vitiligo among these two age groups will be useful to understand their disease burden and to inform the need for development of new therapies. In addition, as treatment modalities can vary for SV and NSV, prevalence estimates by vitiligo subtype will also be useful. The aim of this study was to estimate the point prevalence of overall vitiligo (diagnosed and undiagnosed combined), as well as diagnosed, undiagnosed, SV, and NSV among children and adolescents in the US.
Materials and Methods
Study Design
A cross-sectional, online, population-based survey was conducted between December 30, 2019, and March 11, 2020. Information for children (aged 4–11 years) and adolescents (aged 12–17 years) was obtained using parent/legal guardian proxy-participants in accordance with the Federal Trade Commission's Children's Online Privacy Protection Act. Proxy-participants who reported that their children or adolescents had vitiligo after screening positive for vitiligo in the survey (proxy-reported undiagnosed vitiligo) or after responding that a vitiligo diagnosis was made by a clinician (proxy-reported diagnosed vitiligo) were invited to submit photographs for evaluation by expert dermatologists. This evaluation was conducted between February 21 and March 30, 2020, using a teledermatology mobile health application (teledermatology app) designed and tested specifically for this study. The study was approved by the New England Institutional Review Board.
Study Population
A nationally representative sample of individuals – 2017 US Census Bureau estimates for age (4–85 years), gender, race, household income level, and geographic region – was recruited by email using a stratified, proportional sampling design from a US general population research panel (Schlesinger Group, Iselin, NJ, US) [11, 12]. In order to achieve a census-balanced sample of 50,000 individuals, subsequent invitations were sent to randomly selected individuals based on response rates within the various census quotas. Proxy-participants were required to have valid photo identification, provide key demographic information, and validate their email through a confirmation email link. Lastly, proxy-participants were required to provide electronic consent to be eligible for the study. The results of vitiligo prevalence in adults from this study were published previously [13]. Herein, we present the results for children and adolescents.
Proxy-Participant Survey
The proxy-participant survey included questions on demographics, clinical characteristics, comorbidities, and screening questions for vitiligo for all proxy-participants [13]. Vitiligo screening questions were adapted from published screening tools and the Vitiligo Screening Tool (VISTO), a validated, self-reported questionnaire [14]. The screening questions included items to discern from melanoma and depigmentation due to burns, which can be commonly mistaken as vitiligo, as well as an atlas of photographs developed by Phan et al. [15], along with input from expert dermatologists to determine identification of children and adolescents with undiagnosed vitiligo. Proxy-participants who reported diagnosed or undiagnosed vitiligo were asked to complete additional questions about the laterality (i.e., bilateral or unilateral) and other characteristics of their children's or adolescents' skin lesions (e.g., age of onset and extent of body surface area [BSA] involved). The Self Assessment Vitiligo Extent Score (SA-VES) [16] was used to determine BSA involvement for proxy-participants who reported bilateral vitiligo (as a proxy for NSV), and hand or index finger units were used to measure the extent of BSA involvement for proxy-participants who reported unilateral vitiligo (as a proxy for SV) [17, 18].
Proxy-participants who reported diagnosed or undiagnosed vitiligo were invited to upload up to 3 photographs of their children's or adolescents' skin lesions for clinical evaluation. Proxy-participants who consented to upload photographs were asked to download the study's teledermatology app to their personal device (e.g., smart phone).
Clinician Adjudication
Adjudication of the photographs uploaded by proxy-participants was conducted by 3 board-certified dermatologists with expertise in vitiligo (Khaled Ezzedine, MD, PhD; Amit G. Pandya, MD; and Mehdi Rashighi, MD). The dermatologists were also provided with the children's or adolescents' proxy-reported age, gender, race, age of vitiligo onset, laterality, Fitzpatrick skin type, and other skin conditions to assist in their evaluation. They were blinded to the proxy-participants' reports of diagnosed or undiagnosed vitiligo and independently classified the children or adolescents into 1 of 6 classifications: (1) definitely has vitiligo, (2) probably has vitiligo, (3) definitely does not have vitiligo, (4) probably does not have vitiligo, (5) unable to determine due to poor-quality photographs, and (6) unable to determine due to any other reason. These classifications were subsequently collapsed into 3 groups for analysis: (1) vitiligo (classifications #1 and #2), (2) nonvitiligo (classifications #3 and #4), and (3) indeterminate (classifications #5 and #6). Final vitiligo status was determined by clinician majority (i.e., at least 2 of the 3 dermatologists agreed on the vitiligo group assigned for analysis). If there was no majority, the case was included in the indeterminate group. The dermatologists also evaluated the reported laterality and provided their assessment of NSV or SV based on the photographs following the consensus classification from the 2011 Vitiligo Global Issues consensus conference for SV [19].
Statistical Analysis
All statistical analyses were performed with SAS version 9.4 (SAS Institute, Cary, NC). Proxy-reported vitiligo point prevalence estimates were calculated as the percentage of proxy-participants who reported vitiligo for their children or adolescents. Clinician-adjudicated vitiligo point prevalence estimates were calculated as the prevalence of proxy-reported vitiligo weighted by the proportion of children/adolescents with proxy-reported vitiligo in agreement with the clinician adjudication. Indeterminate cases were not included in either the numerator or denominator for the calculation of clinician-adjudicated point prevalence (base case scenario). Two sensitivity analyses that included the indeterminate group as either nonvitiligo or vitiligo were conducted in order to provide a lower and upper bound, respectively. Point prevalence estimates for proxy-reported and clinician-adjudicated NSV and SV were calculated separately.
To improve the representativeness of the estimates, all estimates of the vitiligo point prevalence were weighted using raking methods to adjust the census-based sample to projected 2020 US Census Bureau estimates and to mitigate differential representation across key characteristics such as age, gender, and race by using an iterative proportional fitting process [20, 21].
Results
Proxy-Participants
Of 1,294,401 invitations to participate in the survey sent to potential proxies, there were 70,977 (5.5%) who responded. Among these, 61,859 (87.2%) were not eligible, with the most common (51.1%) reason being that the US Census population quota was already met (Table 1). There were 9,118 eligible proxy responses, and therefore a sample of 9,118 proxy-participants were included in this analysis, which represented 5,209 children and 3,909 adolescents (Table 2). There were 10 proxy-participants who consented and uploaded photographs of their children's or adolescents' lesions.
Table 1.
Participant attrition
| Criteria | n (%) |
|---|---|
| Invited to participate | 1,294,401 |
| Responded to invitation to participate | 70,977 (5.5) |
| Eligible parent/guardian proxy-participants | 9,118 (12.8) |
| Not eligible | 61,859 (87.2) |
| Respondent US Census population quota already filled | 31,613 (51.1) |
| Ages <4 or >17 years | 14,079 (22.8) |
| Survey not completed | 10,913 (17.6) |
| Duplicate respondent or ineligible responsea | 5,254 (8.5) |
US, United States.
An ineligible response was defined as a respondent who selected having all of the listed comorbidities in a potential attempt to participate in the survey.
Table 2.
Characteristics of child and adolescent participants
| Characteristica | Children (4–11 years of age) |
Adolescents (12–17 years of age) |
||||
|---|---|---|---|---|---|---|
| all (n = 5,209) | diagnosed vitiligo (n = 29) | undiagnosed vitiligo (n = 39) | all (n = 3,909) | diagnosed vitiligo (n = 41) | undiagnosed vitiligo (n = 38) | |
| Age, mean (SD), years | 7.7 (2.2) | 8.6 (2.4) | 7.6 (2.1) | 14.4 (1.7) | 13.9 (1.4) | 14.5 (1.5) |
| Female | 1,439 (27.6) | 12 (41.4) | 13 (33.3) | 1,620 (41.4) | 16 (39.0) | 27 (71.1) |
| Race | ||||||
| American Indian or Alaska Native | 18 (0.3) | 0 (0) | 1 (2.6) | 15 (0.4) | 0 (0) | 0 (0) |
| Asian | 240 (4.6) | 3 (10.3) | 4 (10.3) | 234 (6.0) | 6 (14.6) | 6 (15.8) |
| Black or African American | 756 (14.5) | 3 (10.3) | 9 (23.1) | 349 (8.9) | 4 (9.8) | 3 (7.9) |
| Multiracialb | 248 (4.8) | 1 (3.4) | 1 (2.6) | 119 (3.0) | 2 (4.9) | 0 (0) |
| Native Hawaiian or other Pacific Islander | 9 (0.2) | 0 (0) | 0 (0) | 6 (0.2) | 0 (0) | 0 (0) |
| White | 3,721 (71.4) | 21 (72.4) | 21 (53.8) | 3,089 (79.0) | 28 (68.3) | 29 (76.3) |
| Other | 217 (4.2) | 1 (3.4) | 3 (7.7) | 97 (2.5) | 1 (2.4) | 0 (0) |
| Hispanic, Latino, or Spanish origin | 801 (15.4) | 4 (13.8) | 8 (20.5) | 440 (11.3) | 7 (17.1) | 14 (36.8) |
| Income levelc | ||||||
| $0–14,999 | 501 (9.6) | 3 (10.3) | 3 (7.7) | 208 (5.3) | 1 (2.4) | 1 (2.6) |
| $15,000–24,999 | 426 (8.2) | 1 (3.4) | 3 (7.7) | 246 (6.3) | 3 (7.3) | 1 (2.6) |
| $25,000–34,999 | 550 (10.6) | 6 (20.7) | 6 (15.4) | 276 (7.1) | 4 (9.8) | 1 (2.6) |
| $35,000–49,999 | 765 (14.7) | 5 (17.2) | 5 (12.8) | 428 (10.9) | 4 (9.8) | 3 (7.9) |
| $50,000–74,999 | 1,082 (20.8) | 3 (10.3) | 7 (17.9) | 608 (15.6) | 8 (19.5) | 5 (13.2) |
| $75,000–99,999 | 833 (16.0) | 4 (13.8) | 6 (15.4) | 507 (13.0) | 3 (7.3) | 4 (10.5) |
| $100,000–149,999 | 567 (10.9) | 2 (6.9) | 3 (7.7) | 654 (16.7) | 4 (9.8) | 1 (2.6) |
| $150,000–199,999 | 288 (5.5) | 4 (13.8) | 4 (10.3) | 578 (14.8) | 6 (14.6) | 20 (52.6) |
| $200,000+ | 197 (3.8) | 1 (3.4) | 2 (5.1) | 404 (10.3) | 8 (19.5) | 2 (5.3) |
| Region | ||||||
| South | 2,385 (45.8) | 10 (34.5) | 13 (33.3) | 1,745 (44.6) | 17 (41.5) | 11 (28.9) |
| West | 1,019 (19.6) | 8 (27.6) | 12 (30.8) | 756 (19.3) | 10 (24.4) | 17 (44.7) |
| Northeast | 933 (17.9) | 6 (20.7) | 8 (20.5) | 871 (22.3) | 9 (22.0) | 7 (18.4) |
| Midwest | 872 (16.7) | 5 (17.2) | 6 (15.4) | 537 (13.7) | 5 (12.2) | 3 (7.9) |
| FST | ||||||
| 1 (pale white skin) | – | 0 (0) | 1 (2.6) | – | 1 (2.4) | 0 (0) |
| 2 (white skin) | – | 7 (24.1) | 7 (17.9) | – | 13 (31.7) | 9 (23.7) |
| 3 (light 3rown skin) | – | 14 (48.3) | 20 (51.3) | – | 11 (26.8) | 10 (26.3) |
| 4 (moderate 3rown skin) | – | 8 (27.6) | 7 (17.9) | – | 10 (24.4) | 19 (50.0) |
| 5 (dark 3rown skin) | – | 0 (0) | 4 (10.3) | – | 6 (14.6) | 0 (0) |
| 6 (deeply pigmented dark brown to black skin) | – | 0 (0) | 0 (0) | – | 0 (0) | 0 (0) |
| Age of vitiligo onset, mean (SD), years | – | 4.8 (2.6) | 4.4 (2.7) | – | 8.7 (3.1) | 9.3 (3.8) |
| Presentationd | ||||||
| Bilateral (NSV proxy) | NA | 14 (48.3) | 16 (41.0) | 19 (46.3) | 11 (28.9) | |
| Unilateral (SV proxy) | NA | 14 (48.3) | 23 (59.0) | 21 (51.2) | 27 (71.1) | |
| BSA, mean (SD)d, % | ||||||
| Bilateral presentation | NA | 4.9 (3.8) | 5.9 (6.5) | 7.4 (10.9) | 6.5 (5.0) | |
| Unilateral presentation | NA | 0.9 (1.0) | 0.3 (0.4) | 0.8 (1.6) | 0.5 (0.4) | |
| Facial involvemente | NA | 10 (71.4) | 13 (81.3) | 11 (57.9) | 9 (81.8) | |
BSA, body surface area; FST, Fitzpatrick skin type; NA, not available; NSV, nonsegmental vitiligo; SA–VES, Self–Assessment Vitiligo Extent Score; SD, standard deviation; SV, segmental vitiligo; US, United States.
Data are n (%) unless otherwise stated.
Data represent participants who selected >1 category for race.
Currency is US dollars.
Unilateral presentation (SV) was measured using hands and fingers representing 0.81% and 0.081% of BSA in males, respectively, and 0.67% and 0.067% of BSA in females, respectively. Bilateral presentation (NSV) was measured using SA–VES. Includes only those participants with active lesions (i.e., BSA >0%). One child and one adolescent with proxy–reported diagnosed vitiligo had no reported active lesions.
In participants who reported bilateral presentation (NSV).
The mean (standard deviation) ages for children and adolescents were 7.7 [2.2] and 14.4 [1.7] years, respectively. The majority were male (72.4% for children, 58.6% for adolescents); white (71.4% for children, 79.0% for adolescents); and not of Hispanic, Latino, or Spanish origin (84.6% for children, 88.7% for adolescents).
Among those with proxy-reported diagnosed or undiagnosed vitiligo, almost all had Fitzpatrick skin type II–IV (92.6% of children and 91.1% of adolescents). The mean (standard deviation) age of vitiligo onset ranged from 4.4 (2.7) for undiagnosed to 4.8 (2.6) for diagnosed children and 8.7 (3.1) for diagnosed to 9.3 (3.8) years for undiagnosed adolescents. More than 40% of children (48.3%) and adolescents (46.3%) with proxy-reported diagnosed vitiligo had bilateral presentation. A lower percentage of children (41%) and adolescents (28.9%) with proxy-reported undiagnosed vitiligo had bilateral presentation. Among those with proxy-reported diagnosed vitiligo, BSA for bilateral presentation ranged from 4.9% for children to 7.4% for adolescents and was less than 1% for children and adolescents with unilateral presentation.
Prevalence of Vitiligo in Children
Proxy-reported vitiligo point prevalence (95% confidence interval [CI]) was 1.52% (1.11–1.93) overall, 0.69% (0.41–0.97) for diagnosed, and 0.83% (0.53–1.14) for undiagnosed (Table 3). The clinician-adjudicated vitiligo point prevalence (lower and upper sensitivity bounds) in the base case scenario was 0.84% (0.83–1.23) overall, 0.41% (0.41–0.55) for diagnosed, and 0.39% (0.39–0.68) for undiagnosed. The clinician-adjudicated point prevalence (lower and upper sensitivity bounds) of diagnosed NSV and diagnosed SV was 0.30% (0.30–0.40) and 0.11% (0.11–0.14), respectively (Table 4). The clinician-adjudicated point prevalence (lower and upper sensitivity bounds) of undiagnosed NSV and undiagnosed SV was 0.26% (0.26–0.45) and 0.13% (0.13–0.23), respectively.
Table 3.
Point prevalence estimates of vitiligo among children and adolescents in the US
| Age–group/vitiligo group | Point prevalence estimates |
|---|---|
| Children (age 4–11 years), n = 5,209 | |
| Proxy reported, % (95% CI) | |
| Diagnosed | 0.69 (0.41–0.97) |
| Undiagnosed | 0.83 (0.53–1.14) |
| Overall (diagnosed + undiagnosed)a | 1.52 (1.11–1.93) |
| Clinician adjudicated, % (95% CI)b,c | |
| Diagnosed | |
| Base case | 0.41 (0.24–0.59) |
| Lower bound | 0.41 (0.24–0.59) |
| Upper bound | 0.55 (0.35–0.75) |
| Undiagnosed | |
| Base case | 0.39 (0.22–0.56) |
| Lower bound | 0.39 (0.22–0.56) |
| Upper bound | 0.68 (0.46–0.91) |
| Overalla | |
| Base case | 0.84 (0.59–1.09) |
| Lower bound | 0.83 (0.59–1.08) |
| Upper bound | 1.23 (0.93–1.53) |
| Adolescents (age 12–17years), n = 3,909 | |
| Proxy reported, % (95% CI) | |
| Diagnosed | 1.03 (0.70–1.37) |
| Undiagnosed | 1.12 (0.75–1.50) |
| Overall (diagnosed + undiagnosed)a | 2.16 (1.66–2.65) |
| Clinician adjudicated, % (95% CI)b,c | |
| Diagnosed | |
| Base case | 0.62 (0.37–0.87) |
| Lower bound | 0.62 (0.37–0.86) |
| Upper bound | 0.82 (0.54–1.11) |
| Undiagnosed | |
| Base case | 0.53 (0.30–0.76) |
| Lower bound | 0.53 (0.30–0.76) |
| Upper bound | 0.92 (0.62–1.22) |
| Overalla | |
| Base case | 1.19 (0.85–1.53) |
| Lower bound | 1.18 (0.84–1.52) |
| Upper bound | 1.74 (1.33–2.15) |
CI, confidence interval.
Due to within–group weighting, the sum of the individual diagnosed and undiagnosed estimates may differ slightly from the overall estimates of diagnosed and undiagnosed combined.
Photographs were uploaded for clinician adjudication by 4 proxies for self–reported diagnosed vitiligo and 6 proxies for self–reported undiagnosed vitiligo.
Lower bound estimated by classifying indeterminate cases as nonvitiligo cases and upper bound estimated by classifying indeterminate cases as vitiligo cases.
Table 4.
Clinician–adjudicated prevalence estimates of vitiligo subtypes among children and adolescents in the US
| Age–group/vitiligo group | NSV | SV |
|---|---|---|
| Children (age 4–11 years), n = 5,209b,c | ||
| Diagnosed | ||
| Base case | 0.30 (0.13–0.48) | 0.11 (0.04–0.17) |
| Lower bound | 0.30 (0.13–0.48) | 0.11 (0.04–0.17) |
| Undiagnosed | ||
| Upper bound | 0.40 (0.20–0.61) | 0.14 (0.07–0.22) |
| Base case | 0.26 (0.09–0.43) | 0.13 (0.06–0.21) |
| Lower bound | 0.26 (0.09–0.43) | 0.13 (0.06–0.20) |
| Upper bound | 0.45 (0.23–0.68) | 0.23 (0.13–0.33) |
| Overalla | ||
| Base case | 0.58 (0.34–0.83) | 0.25 (0.15–0.35) |
| Lower bound | 0.58 (0.33–0.83) | 0.25 (0.15–0.35) |
| Upper bound | 0.85 (0.56–1.15) | 0.37 (0.25–0.49) |
| Adolescents (age 12–17years), n = 3,909b,c | ||
| Diagnosed | ||
| Base case | 0.45 (0.20–0.69) | 0.17 (0.08–0.27) |
| Lower bound | 0.45 (0.20–0.69) | 0.17 (0.08–0.27) |
| Upper bound | 0.59 (0.31–0.88) | 0.23 (0.12–0.34) |
| Undiagnosed | ||
| Base case | 0.30 (0.08–0.53) | 0.23 (0.12–0.34) |
| Lower bound | 0.30 (0.07–0.53) | 0.23 (0.12–0.34) |
| Upper bound | 0.53 (0.23–0.83) | 0.40 (0.25–0.54) |
| Overalla | ||
| Base case | 0.77 (0.43–1.11) | 0.43 (0.27–0.58) |
| Lower bound | 0.76 (0.42–1.10) | 0.42 (0.27–0.57) |
| Upper bound | 1.12 (0.71–1.53) | 0.62 (0.44–0.80) |
CI, confidence interval; NSV, nonsegmental vitiligo; SV, segmental vitiligo.
Due to within–group weighting, the sum of the individual diagnosed and undiagnosed estimates may differ slightly from the overall estimates of diagnosed and undiagnosed combined.
Photographs were uploaded for clinician adjudication by 4 proxies for self–reported diagnosed vitiligo and 6 proxies for self–reported undiagnosed vitiligo.
Lower bound estimated by classifying indeterminate cases as non–vitiligo cases and upper bound estimated by classifying indeterminate cases as vitiligo cases. NSV and SV clinician– adjudicated estimates were adjusted to account for 54.5% of self–reported SV cases being adjudicated as SV and 100% of self–reported NSV cases being adjudicated as NSV.
Prevalence of Vitiligo in Adolescents
Proxy-reported vitiligo point prevalence (95% CI) was 2.16% (1.66–2.65) overall, 1.03% (0.70–1.37) for diagnosed, and 1.12% (0.75–1.50) for undiagnosed (Table 3). The clinician-adjudicated vitiligo point prevalence (lower and upper sensitivity bounds) in the base case scenario was 1.19% (1.18–1.74) overall, 0.62% (0.62–0.82) for diagnosed, and 0.53% (0.53–0.92) for undiagnosed. The clinician-adjudicated point prevalence (lower and upper sensitivity bounds) of diagnosed NSV and diagnosed SV was 0.45% (0.45–0.59) and 0.17% (0.17–0.23), respectively (Table 4). The clinician-adjudicated point prevalence (lower and upper sensitivity bounds) of undiagnosed NSV and undiagnosed SV was 0.30 (0.30–0.53) and 0.23% (0.23–0.40), respectively.
Discussion
This study examined the prevalence of vitiligo in children and adolescents including diagnosed and undiagnosed vitiligo and vitiligo subtypes. Pediatric vitiligo is associated with greater disturbances in patients' quality of life with advancing age [22]. Childhood psychosocial distress can lead to a lifetime of psychiatric manifestations such as social disengagement, anxiety, depression, and body dysmorphic disorder [23]. In a study conducted in India, Parsad et al. [24] found that children with vitiligo avoided sports activities and missed more school days. Another study conducted in the Netherlands showed the impact of childhood vitiligo persisting into adult life [4]. Adolescence is a critical stage when one develops a sense of self identity and self-esteem: therefore, this population group with vitiligo experienced the most self-consciousness among all pediatric groups [25]. In light of significant impacts due to vitiligo among pediatric population and differences in impacts by age cohorts, it is important to evaluate vitiligo prevalence in pediatric patients both overall and by age cohort.
To our knowledge, this is one of the first population-based studies to estimate point prevalence of vitiligo through proxy report and clinician adjudication in children and adolescents in the US. In this large study of 9,118 children and adolescents, generalizability was supported by applying sample quotas based on the US Census Bureau and by using raking analytic methods to weight the sample to 2020 US population estimates separately for children and adolescents. In addition, this is also one of the first studies that reports on undiagnosed prevalence estimates.
In this study, the overall proxy-reported vitiligo point prevalence (95% CI) was 1.52% (1.11–1.93) in children and 2.16% (1.66–2.65) in adolescents. Clinician-adjudicated point prevalence of vitiligo was 0.84% in children and 1.19% in adolescents. This provides clinician-adjudicated estimates of approximately 284,000 and 307,000 cases of vitiligo (including both diagnosed and undiagnosed) in children and adolescents, respectively, in the US in 2020. The prevalence estimates from this study fall within the estimates reported by a previous analysis of 26 studies of vitiligo in children (up to 2.16%). The point prevalence estimates of diagnosed vitiligo in children and adolescents were 0.69% and 1.03% for proxy-reported, respectively, and 0.41% and 0.62% for clinician-adjudicated, respectively. The proxy-reported estimates are slightly higher than those prevalence estimates previously reported for the US (0.24%) and Europe (up to 0.67%) [10]. While heterogeneity across studies limits comparisons, it is also important to note that awareness and population diversity trends in the US have evolved over time, which may contribute to underlying genetic factors and population changes leading to higher estimates than previous reports.
The point prevalence estimates of undiagnosed vitiligo in children and adolescents were 0.83% and 1.12% for proxy-reported and 0.39% and 0.53% for clinician-adjudicated, respectively, suggesting that up to 50% of children and adolescents in the US may be undiagnosed. We observed that substantially more children of Hispanic, Latino, or Spanish origin were undiagnosed compared with the overall cohort. Future studies should investigate these findings and examine potential reasons for such differences.
In this study, we also evaluated the prevalence of vitiligo by its subtypes: SV and NSV. Consistent with previous studies and based on clinician-adjudicated estimates, NSV was more common with approximately 69% of children and 65% of adolescents reported with NSV [26]. Indeed, the distinction between NSV and SV is essential. The progressive course of vitiligo adds to the negative emotions experienced by these patients [27, 28], and, as such, the unpredictable nature of NSV is of importance in its therapeutic management.
One limitation of this study was that sample sizes were calculated to obtain a range of precise estimates for the prevalence of vitiligo among the overall sample and not within age-based subgroups. Similarly, stratified sampling based on demographics, such as race and ethnicity, was applied to the overall sample of adults, children, and adolescents to obtain a representative sample; it was not applied specifically within this cohort of adolescents and children only. Further, only 10 proxies uploaded photos for clinical adjudication, which is a small portion of vitiligo responses. There was also the potential for selection bias based on Internet access. Although it is possible that some of those invited to participate did not have access to the Internet, it has been estimated that almost 90% of US households had Internet access in 2016 [29]. Other limitations of the survey included the requirement for participants to be able to read English (comprehension was not assessed), and the reporting of vitiligo status was by a proxy without confirmation from an in-person clinical evaluation. Nevertheless, the study included vitiligo screening questions that were adapted from published screening tools following feedback from expert dermatologists. Clinician adjudication via a teledermatology app was also conducted to confirm proxy-reported vitiligo status and ensure accuracy of reporting. Given the proxy-reported nature of the survey, we relied on clinician adjudication of images in drawing the distinction between NSV and SV prevalence. It is assumed that a participant's photo-upload status was independent of their true vitiligo status. Finally, the use of telehealth solutions in epidemiologic research is a relatively novel method that does not allow for close control of the quality of submitted photos or possible user errors; therefore, clinician adjudication must be interpreted with caution.
In conclusion, this study provides current US population-based prevalence estimates for vitiligo in children (aged 4–11 years) and adolescents (aged 12–17 years), including those with undiagnosed vitiligo, along with estimates for SV and NSV subtypes. Based on the clinician-adjudicated estimates, there were more than 591,000 cases of vitiligo in those aged 4–17 years in the US in 2020, with over two-thirds being NSV and up to 50% of them undiagnosed. Future studies should confirm these findings and additionally evaluate prevalence estimates by race, ethnicity, and other demographics using stratified proportional sampling design to obtain a representative US sample of adolescents and children only.
Key Message
US vitiligo prevalence among children and adolescents is 0.84% and 1.19%, respectively; 50% are undiagnosed.
Statement of Ethics
The final protocol, any amendments, the data collection tool, and informed consent documentation were reviewed and approved by the New England Institutional Review Board (120190294). A copy of the IRB exemption was forwarded to the sponsor. The study was conducted in accordance with legal and regulatory requirements, as well as with scientific purpose, value, and rigor, and followed generally accepted research practices described in the Good Pharmacoepidemiology Practices issued by the International Society for Pharmacoepidemiology and the Declaration of Helsinki.
Conflict of Interest Statement
G.P. declares acting as a consultant for AbbVie, Arcutis, Avita, Chromaderm, Immune Tolerance Network, Incyte, Pfizer, Viela Bio, Villaris, and TWi and holds stock options with Zerigo Health and Tara Medical. K.G. and V.S. were employees of Pfizer and held stock and/or options with Pfizer at the time of study. Y.Y. and L.N. are employees of Pfizer and hold stock and/or stock options with Pfizer. R.P., K.P.A., S.R.D., and R.B. are employees of Labcorp Drug Development. K.E. declares acting as a consultant for Incyte, La Roche Posay, Pfizer, Pierre Fabre, Sanofi, and Viela Bio.
Funding Sources
This study was sponsored by Pfizer.
Author Contributions
Reema Patel, Yuji Yamaguchi, and Lynne Napatalung contributed to study concept and design; acquisition, analysis, or interpretation of data; drafting and critical revision of the manuscript for important intellectual content; and administrative, technical, or material support. Amit G. Pandya, Kathryn P. Anastassopoulos, and Khaled Ezzedine contributed to study concept and design; acquisition, analysis, or interpretation of data; drafting and critical revision of the manuscript for important intellectual content; administrative, technical, or material support; and supervision. Vanja Sikirica and Kavita Gandhi contributed to study concept and design; acquisition, analysis, or interpretation of data; drafting and critical revision of the manuscript for important intellectual content; administrative, technical, or material support; supervision; and obtaining funding. Shoshana R. Daniel and Rebecca Baik contributed to study concept and design; acquisition, analysis, or interpretation of data; drafting and critical revision of the manuscript for important intellectual content; administrative, technical, or material support; and statistical analysis. All authors had full access to all the data in the study and take responsibility for the integrity of the data and the accuracy of the data analysis.
Data Availability Statement
Upon request, and subject to review, Pfizer will provide the data that support the findings of this study. Subject to certain criteria, conditions, and exceptions, Pfizer may also provide access to the related individual de-identified participant data. See https://www.pfizer.com/science/clinical-trials/trial-data-and-results for more information.
Acknowledgments
The authors thank Dr. Mehdi Rashighi, MD (Department of Dermatology, University of Massachusetts Medical School, Worcester, MA, USA), for his contribution to the expert adjudication of photos provided by study participants via the teledermatology app. Medical writing support was provided by David Wateridge, PhD, and Rency Mathew, PhD, of Engage Scientific Solutions and was funded by Pfizer.
Vanja Sikirica and Kavita Gandhi: Affiliation at the time this study was conducted.
verified
Funding Statement
This study was sponsored by Pfizer.
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Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Data Availability Statement
Upon request, and subject to review, Pfizer will provide the data that support the findings of this study. Subject to certain criteria, conditions, and exceptions, Pfizer may also provide access to the related individual de-identified participant data. See https://www.pfizer.com/science/clinical-trials/trial-data-and-results for more information.