Literature DB >> 32024337

Global prevalence of classic phenylketonuria based on Neonatal Screening Program Data: systematic review and meta-analysis.

Hamid Reza Shoraka1, Ali Akbar Haghdoost2, Mohammad Reza Baneshi3, Zohre Bagherinezhad4, Farzaneh Zolala5.   

Abstract

Phenylketonuria is a disease caused by congenital defects in phenylalanine metabolism that leads to irreversible nerve cell damage. However, its detection in the early days of life can reduce its severity. Thus, many countries have started disease screening programs for neonates. The present study aimed to determine the worldwide prevalence of classic phenylketonuria using the data of neonatal screening studies. The PubMed, Web of Sciences, Sciences Direct, ProQuest, and Scopus databases were searched for related articles. Article quality was evaluated using the Joanna Briggs Institute Critical Appraisal Evaluation Checklist. A random effect was used to calculate the pooled prevalence, and a phenylketonuria prevalence per 100,000 neonates was reported. A total of 53 studies with 119,152,905 participants conducted in 1964-2017 were included in this systematic review. The highest prevalence (38.13) was reported in Turkey, while the lowest (0.3) in Thailand. A total of 46 studies were entered into the meta-analysis for pooled prevalence estimation. The overall worldwide prevalence of the disease is 6.002 per 100,000 neonates (95% confidence interval, 5.07-6.93). The metaregression test showed high heterogeneity in the worldwide disease prevalence (I2=99%). Heterogeneity in the worldwide prevalence of phenylketonuria is high, possibly due to differences in factors affecting the disease, such as consanguineous marriages and genetic reserves in different countries, study performance, diagnostic tests, cutoff points, and sample size.

Entities:  

Keywords:  Meta-analysis; Neonates; Phenylketonuria; Prevalence; Screening

Year:  2020        PMID: 32024337      PMCID: PMC7029670          DOI: 10.3345/kjp.2019.00465

Source DB:  PubMed          Journal:  Clin Exp Pediatr        ISSN: 2713-4148


Graphical Abstract

Introduction

Genetic and congenital abnormalities are the most important causes of death and malformation in the first month of life [1]. Phenylketonuria (PKU) is an inborn error of amino acid metabolism caused by phenylalanine hydroxylase gene mutations [2,3]. PKU patients experience an irreversible decrease in intelligence quotient scores, suppressed verbal function, impaired attention, and underdeveloped motor control skills [4,5]. The early diagnosis of PKU before the end of the first month of life is critical to controlling hyperphenylalaninemia [4,6]. Children with PKU seem normal during the first days of life; however, nervous system damage progresses gradually and becomes apparent over several months [7]. The early detection of PKU in the asymptomatic period and treatment with a phenylalanine restricted diet is warranted to ensure normal development [8-12]. Therefore, neonatal screening as a fundamental public health intervention started in the mid-20th century [4,12,13]. Since PKU has autosomal recessive inheritance, consanguineous marriage is an important risk factor [1,4]; thus, countries with a high prevalence of consanguineous marriages have high disease prevalence [6,14]. PKU varies among ethnic groups, races, and geographic regions. For example, In Japan, the incidence is reportedly 1:108,822 [15]. Turkey, with an incidence of 1:6,000, and Iran, with an incidence of 1:4,698, are among the countries with the highest PKU incidences [16,17]. Despite numerous studies conducted in various countries on PKU prevalence using screening programs, no study has systematically compared the prevalence of PKU across regions and countries or sources of heterogeneity. To address this gap, this systematic review and meta-analysis aimed to investigate the worldwide prevalence of PKU. Moreover, many countries have acknowledged the benefits of newborn screening programs for PKU. Moreover, newborn screening programs have enabled the rapid and large-scale testing of many children with good quality control.

Methods

This systematic review adhered to the guidelines of the Joanna Briggs Institute Reviewers’ Manual 2014, Systematic Review of Prevalence Data [18]. The PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) 2009 flow diagram was used to guide the study identification and selection process [19].

1. Search method

The PubMed, Web of Sciences, Sciences Direct, ProQuest, and Scopus databases were searched on Oct 28, 2018, without publication date restrictions. The search strategy carefully captured all potentially eligible records of PKU prevalence. A combination of medical subject headings (MeSH) and similar text words in English was used. Google Scholar was searched, as were the reference lists of the reviewed articles to identify additional relevant articles. The key MeSH terms were as follows: (Infants OR Newborns OR Neonate) AND (Phenylketonuria OR Hyperphenylalaninemia, Non-Phenylketonuric OR BH4 Deficiency OR Tetrahydrobiopterin Deficiency OR Phenylketonuria II OR DHPR Deficiency OR Dihydropteridine Reductase Deficiency OR Atypical PKU) AND (Incidence OR Prevalence) and Screening. No time limitation was considered for the database search.

2. Inclusion criteria

All original articles that directly reported PKU prevalence based on newborn screening of populations were included. A newborn, infant, or neonate is a child younger than 28 days of age; in this review, the sampling period was limited to the first 28 days of life. All studies were included if they used a laboratory screening test for disease detection. Reviews, comments, and letters were excluded. Moreover, studies that reported the prevalence in a selective neonatal population (congenital diseases, intellectual disability), those that included children older than 28 days, and those that indirectly estimated prevalence according to consanguinity or the incidence of another genetic disease were excluded. In some cases, studies were conducted of the same PKU prevalence in one country using different dates; in such cases, the more recent study (which also included the data from the older study) was included and the older study was omitted. Moreover, studies that detected PKU based on clinical manifestations in neonates or neural tube defects in fetuses were excluded.

3. Data collection

The title, abstract, and keywords of every identified article were carefully scanned and relevant articles were selected by title or abstract review.

4. Data extraction and management

Two reviewers (HSH. and FZ) independently extracted the patient characteristics, study characteristics, screening test used, and incidence from the reviewed studies using a data extraction form. Any disagreements between the 2 researchers were solved by consultation of another reviewer or a clinical adviser. Abstracts not published as full texts were not included in the study. To avoid data entry errors, all results were double-entered into a data extraction form. The included studies used different units such as mmol/L, μmol/dL, and mg/dL to report phenylalanine level. However, in this study, to increase comparability, all units were converted to mg/dL. In addition, to ensure more accurate comparisons, PKU prevalence was calculated as percentage and rate per 100,000 screened neonates.

5. Assessment of methodological quality

Article quality was assessed using the Joanna Briggs Institute Critical Appraisal Checklist for studies that reported prevalence data. Each article was evaluated according to the following methodological criteria: appropriate sample, adequate sample size, valid methodology, valid measure to detect the disease, and an appropriate statistical analysis.

6. Risk of bias

Risk of bias was assessed using the risk of bias tool for studies measuring disease prevalence designed and developed by Hoy et al. [20] Based on this 10-point checklist, studies were assessed for internal and external validity and grouped as having high, moderate, or low bias risk. Studies with a score of 9–10 were considered at having low risk of bias; 6–8, as having moderate risk; and less than 6, as having high risk. Those studies with a high risk of bias were excluded from the meta-analysis.

7. Data analysis

The data were analyzed using Stata ver. 12 (StataCorp LP., College Station, TX, USA). In a meta-analysis, pooled prevalence was estimated based on World Health Organization (WHO) regions and reported as per 100,000 neonates/population with 95% confidence interval (CI). The degrees of heterogeneity among the included studies are expressed by the I2 heterogeneity statistic, and the random effects model was used to estimate the pooled prevalence in subgroups. A forest plot was used to display the meta-analysis results. The mixed model test considered WHO regions as a random intercept. In this test, phenylalanine levels were modeled as independent variables, while prevalence was considered a dependent variable. Furthermore, a meta-regression analysis was performed to investigate the impact of variables such as WHO region, phenylalanine cutoff point, study period, national or governmental screening program, and participant age on the I2 and pooled prevalence.

Results

1. Study selection

After a comprehensive search, 1,228 relevant articles were identified, 608 duplicates were removed. The relevance of the remaining 1,346 studies was evaluated based on the titles/abstracts alone; of them, 99 studies were subjected to fulltext review, which eliminated another 46 studies according to the inclusion and exclusion criteria. Finally, 53 studies with 119,152,905 participants were included in the present systematic review; of them, 46 were included in the meta-analysis (Fig. 1).
Fig. 1.

Flow diagram of the literature search and study selection process. PKU, phenylketonuria.

2. Risk of bias

In the bias assessment, 7 studies scored below 6 (high risk) and were excluded from the meta-analysis; thus, the pooled global prevalence was estimated without them [11-13,21-24]. Moreover, 33 of the studies scored 6–8 (moderate risk) [1,9,16,17,25-53], while the other 13 studies had low risk [2,10,54-64].

3. Study characteristics

In this section, the systematic review results are presented based on different characteristics, including region, test, and participant characteristics.

4. Region characteristics

The included studies (1964–2017) are presented in Table 1. The longest study, conducted in France, examined 35 years of screening data from 1966 to 2001 [56]. The largest screening population was in China (35,795,550 newborns for 30 years from the start of the screening project); the largest number of cases was detected (3,082 patients) in this study [60]. However, the smallest population belonged to a study conducted in Iraq in 2015, and only 8,255 newborns were screened [13].
Table 1.

Description of studies included in the study

IDStudyStudy locationPopuiation sizeStudy periodAge taking a biood sampieScreening test/cutoff level (mg/dL)No. of cases in screening test (incidence per 100,000)Diagnostic test/cutoff level for classic PKU (mg/dL)No. of classic PKU cases (incidence per 100,000)ConsanguinityNeonatal participation rateRist of bias ScoreRemarksWHO regions
1MacCready, [25] 1964USA/Massachusetts134,5801962–196428 DaysGuthrie/≥4NAGuthrie/≥414 (10.4)NANA7Pan American
2Peterson, [26] 1968USA/Caiifornia311,953196630 DaysGuthrie and Fluorometric/20NAGuthrie and Fluorometric/≥2016 (5.12)NANA6Pan American
3Fox, [27] 1971Canada/Manitoba85,8681966–19704-5 DaysGuthrie test/20NAGuthrie test/≥205 (5.82)NA95.7%8Pan American
4Alm, [54] 1981Sweden1,362,4971965–19794-6 DaysIon exchange chromatography/4.12312 (22.89)Ion exchange chromatography/≥4.1243 (3.15)NA86%9The phenylalanine cut point reported 0.25 mmol/L, this is equal to 4.12 mg/dLEurope
5Antonozzi, [28] 1982Itaiy/3 regions220,0001974–1981Median of 7.6 daysIon exchange chromatography/1.65211 (95.9)Ion exchange chromatography/≥1.6523 (10.45)NA42%6The phenyl alanine cut point reported 100 μmol/dL, this is equal to 1.65 mg/dLEurope
6Farhud, [22] 1982Iran/Tehran8,63319824-8 DaysGuthrie/20NAGuthrie/≥ 201 (11.58)NANA5Eastern Mediterranean
7Liu, [29] 1986china/11 province198,3201982–19851-3 DaysGuthrie/4225 (113.4)Guthrie/≥159 (4.53)NANA8Reports overall incidence 1:16500 but the incidence is 1:22035Western Pacific
8Mathias, [30] 1986West Germany940,3691969–19845-7 DaysGuthrie/15170 (18.07)Ion exchange chromatography/≥1594 (10)NANA8Europe
9Özalp, [31] 1986Turkey/Ankara20,9791983–1985>24 HrGuthrie/4NAFluorometric/≥208 (38.13)NANA8Europe
10Aoki, [55] 1988Japan12,168,6451977–19855-7 DaysGuthrie/20NAGuthrie/≥20102 (0.83)NA87%10Western Pacific
11Missiou-Tsagaraki, [32] 1988Greece1,042,0001974–1986>24 HrThin-layer chromatography/4776 (74.47)Thin-layer chromatography/≥2043 (4.12)NANA8Europe
12Chen, [33] 1989China/Shanghai358,7671981–1989>3 DaysGuthrie/472 (20.06)Fluorometric/≥ 2021 (5.85)NA33%6Western Pacific
13Smith, [34] 1991United Kingdom3,796,6451984–19886-7 Days9 Laboratories Guthrie, 6 used fluorometric and 11 used thin layer or paper chromatography/4NA9 Laboratories Guthrie, 6 used fluorometric and 11 used layer or paper chromatography/≥20273 (7.19)100%8The phenylalanine cut point reported 240 μmol/dL, this is equal to 4 mg/dLEurope
14Gerasimova, [35] 1992Russia, Moscow139,6641990–19914-5 DaysFluorometric/3529 (378)Fluorometric/≥2021 (15.03)NANA7The phenylalanine cut point reported 180 μmol/dL, this is equal to 3 mg/dLEurope
15Cabalska, [36] 1993Poland2,861,5041965–1990NAGuthrie/4NAGuthrie/≥20368 (12.86)NA40%–100%8They just presented data from the National Research Institute for Mother and ChildEurope
16Fernandez-Iglesias, [37] 1995Spain/Principado75,4881982–19935-8 DaysThin-layer chromatography/4NAHigh performance liquid chromatography/≥45 (6.62)NANA7The phenylalanine cut point reported 240 pmol/dL, this is equal to 4 mg/dLEurope
17Hitzeroth, [23] 1995South Africa/Pretoria59,6001979–19863-5 DaysThin-layer chromatography/4NAThin-layer chromatography/NA1 (1.67)NANA5Africa
18Özalp, [16] 1995Turkey576,1221987–1994>24 HrFluorometric/20NAFluorometric/≥ 2096 (16.66)45%NA7The phenylalanine cut point reported 1,200 μmol/dL, this is equal to 20 mg/dL)Europe
19Kucinskas, [38] 1996Uthuania907,1681975–199321 DaysFluorometric/2.5NAFluorometric/≥ 2.585 (9.36)NANA8The phenylalanine cut point reported 150 pmol/dL, this is equal to 2.5 mg/dLEurope
20Ounap, [66] 1998Estonia36,0741993–19953-5 DaysFluorometric/3NAFluorometric /≥36 (16.63)NA85%7The phenyl alanine cut point reported 180 pmol/dL, this is equal to 3 mg/dLEurope
21Abadie, [56] 2001France21,500,0001966–20013-5 DaysUntil 1990 (Guthrie) 1991–2001 (Fluorometric)/101,426 (6.63)Until 1990 (Guthrie), 1991–2001 (Fluorometric)/≥101,164 (5.41)NA3%–65%9The phenylalanine cut point reported 600 pmol/dL, this is equal to 10 mg/dLEurope
22Zytkovicz, [39] 2001England257,0001999–20011-3 DaysMS/MS/2.2992 (35.79)MS/MS/≥2.297 (2.72)NANA8The phenylalanine cut point reported 139 pmol/dL, this is equal to 2.29 mg/dLEurope
23Schulze, [40] 2002Germany423,7731994–19995 Days (1–10 days)MS/MS/2.5NAMS/MS/≥1041 (9.67)NANA8The phenylalanine cut point reported 150 pmol/dL, this is equal to 2.5 mg/dlEurope
24Zaffanello, [57] 2002Northeastern Italy1,142,3381978–19973-5 DaysGuthrie/2NAHigh performance liquid chromatography/≥2025 (2.18)NA97%9Europe
25Capistrano-Estrada, [41] 2003Philippines189,7201996–2001>24 HrGuthrie/3.375 (39.53)Guthrie/≥3.33 (1.58)NANA6The phenylalanine cut point reported 200 pmol/dL, this is equal to 3.3 mg/dLWestern Pacific
26Charoensiriwatana, [42] 2003Thailand1,425,0251992–20012-7 DaysGuthrie/4321 (22.52)Fluorometric/≥45 (0.35)NANA7South-East Asia
27Jiang, [43] 2003China/Guangdong461,805NA3 DaysGuthrie and Fluorometric/2NAGuthrie and Fluorometric/≥206 (1.29)NANA7The phenylalanine cut point reported 120 pmol/dL, this is equal to 2 mg/dLWestern Pacific
28Yoon, [44] 2005South Korea5,243,8411996–2006NAGuthrie and Fluorometric/4NAHigh performance liquid chromatography/≥2016 (0.3)NANA8Western Pacific
29Pangkanon, [67] 2009Thailand79,1792001–20042-3 DaysMS/MS/2.29NAMS/MS/≥205 (6.31)NA5.40%9The phenylalanine cut point reported 139 pmol/dL, this is equal to 2.29 mg/dLSouth-East Asia
30Senemar, [17] 2009Iran/Fars70,4772000–20053 DaysFluorometric/4NAFluorometric/≥415 (21.28)86.60%NA7Eastern Mediterranean
31Cornejo, [58] 2010Chile2,478,1231992–20083.6 MeanFluorometric/20NA1998–2002 Fluorometric-2002–2008 MS/MS/≥20131 (5.28)NA48-98%9Pan American
32Habib, [45] 2010Iran/Fars175,2352004–20073-5 DaysEnzymatic colorimetric method/430 (17.11)High performance liquid chromatography/≥1028 (15.97)NANA8Eastern Mediterranean
33Karamifar, [9] 2010Iran/Fars76,9662007–20083-5 DaysEnzymatic colorimetric method/29 (11.69)High performance liquid chromatography/≥208 (10.39)NANA8Eastern Mediterranean
34Niu, [46] 2010Taiwan1,495,1322000–20092-3 DaysMS/MS/4NAMS/MS/≥205 (0.33)NA>99%8The phenylalanine cut point reported 240 pmol/dL, this is equal to 4 mg/dLWestern Pacific
35Vilarinho, [59] 2010Portugal316,2432004–20083-6 DaysMS/MS/2.5NAMS/MS/≥626 (8.22)NA99.80%9The phenylalanine cut point reported 150 pmol/dL, this is equal to 2.5 mg/dLEurope
36Sutivijit, [47] 2011Thailand/Southern Region1,118,6762000–2009>2 DaysGuthrie/4120 (10.72)Fluorometric/≥45 (0.44)NAnear 100%8South-East Asia
37Botler, [10] 2012Brazil541,2482005–20072-5 DaysFluorometric/464 (11.82)Thin layer amino acid chromatography≥1026 (4.8)NA71-80%9Pan American
38Shi, [60] 2012China35,795,5501981–20112-3 DaysGuthrie/2NAFluorometric: ≥2 Guthrie: ≥43,082 (8.6)NA3.86% in 2003 and 59.01% in 20099The phenylalanine cut point reported 120 pmol/dL, this is equal to 2 mg/dLWestern Pacific
39Yang, [61] 2012China/Zhejiang3,791,5381999–20103-5 DaysFluorescent ninhydrine method/2NAFluorescent ninhydrine method/≥2143 (3.77)NANA9The phenylalanine cut point reported 120 pmol/dL, this is equal to 2 mg/dLWestern Pacific
40Dluholucký, [11] 2013Slovakia927,5241995–2012NAGuthrie/NANAFluorometric (NA)157 (16.92)NA98%5Europe
41Al Hosani, [62] 2014United Arab Emirates750,3651995–2011>2 DaysTime-resolved fluorescence/457 (7.59)1995-2001 time-resolved fluorescence application 2011 MS/MS/≥2051 (6.79)NA1995-50%, 2010-95%10Eastern Mediterranean
42Dluholucký, [12] 2014Slovakia82,8922013–2014NAMS/MS/NANAMS/MS (NA)5 (6.03)NANA5Europe
43Ramalho, [63] 2014Brazil/Sergipe43,4492007–20082-6 DaysEnzymatic colorimetric method/ 5NAEnzymatic colorimetric method/≥204 (9.2)NA78.93%9Pan American
44Hamawandi, [13] 2015Iraq/Sulaimani8,2552013–20143-10 DaysELISA/411 (133.25)High performance liquid chromatography/≥41 (12.11)100%NA5Eastern Mediterranean
45Šmon, [2] 2015Slovenia385,8311993–20123-5 DaysFluorometric/3.3NAFluorometric/≥2038 (9.84)NANA9The phenylalanine cut point reported 0.2 mmol/l, this is equal to 3.3 mg/dLEurope
46Hassan, [49] 2016Egypt25,27620083-7 DaysMS/MS/2.5NAMS/MS/≥1.695 (19.78)NANA6The phenylalanine cut point reported 150 μmol/dL, this is equal to 2.5 mg/dLEastern Mediterranean
47Zhong, [24] 2016China13,187,1962013NANA/NANANA1,123 (8.51)NA10%-85%4Western Pacific
48Al-Jasmi, [21] 2016United Arab Emirates136,0492011–20143-5 DaysMS/MS/NANAMS/MS (NA)11 (8.08)81%NA5Eastern Mediterranean
49Alkhazrajy, [48] 2016Iraq/Baghdad80,40920143-5 DaysMS/MS/2.5NAMS/MS/≥1.696 (7.46)NA66%6Self-calculated Prevalence. Article did not report prevalence of PKU.Eastern Mediterranean
50Saadatpour, [50] 2016Iran/Hormogan71,6772014–20163-5 DaysELISA/215 20.92)High performance liquid chromatography≥4 mg/dL3 (4.18)66%88%8Consanguinity Reported 53 % but from 3 positive case 2 had Consanguinity marriage and should correct 66%Eastern Mediterranean
51Alfadhel, [52] 2017Saudi Arabia775,0002005–2012After 24 hr of birthMS/MS/3NAMS/MS≥2.0353 (6.83)NANA7Eastern Mediterranean
52Abbaskhanian, [51] 2017Iran/Mazandaran407,2442007–20153-5 DaysELISA/4465 (114.18)High performance liquid chromatography>206 (1.47)NANA8Eastern Mediterranean
53Motamedi, [1] 2017Iran/Lorestan384,9932006–20163-5 DaysHigh performance liquid chromatography/4NAHigh performance liquid chromatography≥474 (19.22)82%53.60%7Eastern Mediterranean

PKU, phenylketonuria; WHO, World Health Organization; MS/MS, tandem mass spectrometry; ELISA, enzyme-linked immunosorbent assay; NA, not announced.

5. Participants’ characteristics

Sampling age at screening was below 5 days in 30 studies [1,2,9,10,16,17,21,23,27,29,31-33,35,39,41,43-46,48,50-53,56-58,60,61], 5–10 days in 15 studies [13,22,28,30,34,37,42,47,49,54,55,59,62,63,65], and over 10 days in 3 studies [25,26,38]. Five studies did not report newborn age at screening [11,12,24,36,64]. The neonatal participation rate was reported in 23 studies [1,10,11,24,27,28,33,34,44,46-48,50,53-60,62,63]; of them, it was above 90% in 7 studies [11,27,34,46,47,57,59]. The participation rate increased with the progression of the screening process in 8 studies [1,24,27,36,56,58,60,62]. Moreover, 6 studies reported the percentage of consanguineous marriages among the parents of newborns with PKU [1,13,16,17,21,50]. The percentage of consanguineous marriages varied from 45% in Turkey [16] to 100% in Iraq [13].

6. Test characteristics

In the included studies, 2 stages were used to diagnose infants with classical PKU.

7. Screening tests

A total of 19 studies reported the number of positive cases in the first stage of screening. The phenylalanine cutoff point for separating positive cases and referrals for diagnostic testing ranged from 1.65 mg/dL to 20 mg/dL. The highest recall rate in the first stage of screening was 378 per 100,000 neonates in a study conducted in Russia [35].

8. Diagnostic tests

In the diagnostic stage, the phenylalanine cutoff point for diagnosing classic PKU patients ranged from 1.65 mg/dL to 20 mg/dL. Moreover, 22 studies selected 20 mg/dL as the positive cutoff point and 5 studies did not report a cutoff point [2,9,16,22,25,26,31-36,43,44,46,51,55,57,58,62-64].

9. Pooled global prevalence of classic PKU

Among the included studies, the highest prevalence was found in Turkey (38.13), followed by Iran, with a prevalence of 21.28 per 100,000 neonates [17,31], while the lowest prevalence was reported in studies conducted in Thailand (0.3) and Taiwan (0.44) [42,46 47,64]. A subgroup estimation of the polled prevalence showed that the pooled prevalence of classic PKU in the included studies was 6.002 (95% CI, 5.07–6.93). The highest prevalence was seen in Eastern Mediterranean (9.83; 95% CI, 6.18–13.48), Europe (8.11; 95% CI, 6.54–9.69), Pan America (5.32; 95% CI, 4.47–6.07), Western Pacific (2.94; 95% CI, 0.91–4.97), and Southeast Asia (0.32; 95% CI, 0.19–0.45) per 100,000 neonates (Fig. 2).
Fig. 2.

Forest plot of pooled global prevalence of phenylketonuria. ES, estimated; CI, confidence interval.

10. Statistical analysis

According to the results of mixed model, cutoff point selection had no effect on prevalence. The p value obtained from the likelihood ratio test in the mixed model test suggested that the random intercept model was appropriate. Moreover, based on the intraclass coefficient, 29% of the PKU prevalence changes in different countries were justified by consideration of the WHO regions (Table 2).
Table 2.

Result of mixed model test

VariableCoefficientSEP valueEstimate95% CI
Cut-point level-0.030.110.792
Random-effect parameter
WHO regions (var constant)12.0715.613.43–71.08
Var (residual)8.0936.2723.43–56.16

SE, standard error; CI, confidence interval; WHO, World Health Organization.

Intraclass correlation coefficient=0.29. Likelihood-ratio test=0.0019.

A meta-regression test was used to assess the effect of year, phenylalanine cutoff point, region, neonate age at screening, and screening level (national or regional) on heterogeneity. In the naïve model without any variables, I2 was 99%. Several models with different variables were created in which I2 ranged was 97%–99%, and the input of different variables did not decrease the heterogeneity. Among the variables included in the model, only some WHO regions were significant. In the meta-regression model, the European region was selected as a reference. In the Eastern Mediterranean region, the prevalence was 1.01 greater than that in the European region, but the difference was not significant. The pooled prevalence of the different regions is reported in Table 3.
Table 3.

Result of meta-regression test

WHO regionCoefficientSEP valueI2
EuropeReference98.69%
Eastern Mediterranean1.011.890.593
Pan American-2.032.150.350
Western Pacific-5.371.720.003
Southeast Asia-7.972.540.003

WHO, World Health Organization; SE, standard error.

According to I2 by region and overall, the studies had high heterogeneity (Table 4).
Table 4.

Prevalence rate and heterogeneity in regions

WHO regionP valueI2Prevalence in 100 000 neonates (range)Pooled prevalence in 100,000 neonates
Pan American0.4904.8–10.45.32
Europe<0.000195.1%2.18–38.138.12
Western Pacific<0.000199.7%0.3–8.62.94
Southeast Asia0.7900.3–0.440.32
Eastern Mediterranean<0.000191.8%1.47–21.289.84
Overall<0.000199%1.47–38.136.002

WHO, World Health Organization.

Discussion

This systematic review aimed to investigate the worldwide prevalence of PKU and provided a general picture of its status. The results of this study demonstrate that the worldwide prevalence of the disease is 0.3–38.13 per 100,000 newborns. However, the meta-analysis revealed that the I2 index, which indicates heterogeneity, was reported for all regions except Southeast Asia (91.8%) and Pan America (99.7%), indicating high heterogeneity among countries and regions. The uni- and multivariate models in the meta-regression showed that phenylalanine level, geographical area, neonate age at screening, screening level (national or regional), after the control for year of study, did not change heterogeneity. However, the differences in prevalence can be attributed to 2 factors: (1) variability of the factors affecting disease worldwide; and (2) differences in the methods used in the studies. PKU is a c0ngenital genetic disease; thus, factors such as culture, customs, consanguineous marriage, and genetics are expected to affect its incidence but among included studies only 6 studies in Iran, Iraq, Turkey, and the United Arab Emirates [1,13, 16,17,21,50] reported consanguineous marriages among parents of children with PKU. Therefore, a lack of information about the prevalence of PKU in many countries in which consanguineous marriage is prevalent and a lack of reporting consanguineous marriage status in parents of children with PKU in many studies prevented us from controlling the effect of this variable on prevalence. The next important determinant of prevalence is study performance; factors such as diagnostic tests, cutoff point, and sample size can affect the pooled prevalence in prevalence studies. However, in the mixed model test, there was no significant relationship between cutoff point and disease prevalence, which might have been due to the effect of the confounding variables. However, the difference was noticeable when the cutoff point differed in the same population and within the same country. For example, in 3 studies conducted during 2000–2008 in Fars province (Iran), a different cutoff point was found. Moreover, Senemar chose a phenylalanine level of ≤4 mg/dL to define classical PKU and reported a prevalence of 21.28 [17]. Habib et al. [45] considered a phenylalanine ≤10 mg/dL cutoff value and reported a prevalence of 15.97. Furthermore, in the study of Karamifar et al. [9], phenylalanine levels above 20 mg/dL were considered positive and a prevalence of 10.39 was reported. Sample size is the other factor involved in the difference in prevalence among studies. In a meta-analysis, the pooled prevalence is estimated according to the sample size, and larger studies have greater impact on prevalence. Thus, although studies conducted in the Eastern Mediterranean region reported higher prevalence than those in the Western Pacific region, since most studies in the latter had a larger sample size and the weighted sample size in that region was 24.83%, higher than that in the Eastern Mediterranean region (16.2%), the pooled prevalence in studies conducted in the Eastern Mediterranean region was close to that of the Western Pacific region. Although this study addressed an important concern in genetic diseases, its findings may not be highly accurate, as there were many sources of heterogeneity in the reviewed studies that could have affected their pooled prevalence. Moreover, some heterogeneous sources might not have been identified. However, the standardization of study methods can partly solve this problem. One of the limitations of this study was the failure to report consanguineous marriage in parents of newborns with PKU. Thus, it was not possible to answer the following question: Is the difference in PKU prevalence among different countries due to differences in the number of consanguineous marriages? Thus, we suggest that consanguineous marriages be recorded and reported in screening programs designed to identify patients with PKU and other congenital metabolic diseases. In conclusion, all relevant studies conducted in 1964–2017 were included in this review. The highest PKU prevalence was observed in Turkey (38.13), while the lowest was seen in Thailand (0.3). Among the WHO regions, the highest prevalence belonged to Eastern Mediterranean Regional Office, while the lowest was in Southeast Asia. This difference in the prevalence may be due to differences in the number of consanguineous marriages among the different regions, phenylalanine cutoff points, and sample sizes.
  46 in total

1.  Four years of expanded newborn screening in Portugal with tandem mass spectrometry.

Authors:  Laura Vilarinho; Hugo Rocha; Carmen Sousa; Ana Marcão; Helena Fonseca; Mário Bogas; Rui Vaz Osório
Journal:  J Inherit Metab Dis       Date:  2010-02-23       Impact factor: 4.982

Review 2.  Phenylketonuria.

Authors:  Nenad Blau; Francjan J van Spronsen; Harvey L Levy
Journal:  Lancet       Date:  2010-10-23       Impact factor: 79.321

3.  Evaluation of 6-year application of the enzymatic colorimetric phenylalanine assay in the setting of neonatal screening for phenylketonuria.

Authors:  Andreas Schulze; Ertan Mayatepek; Georg F Hoffmann
Journal:  Clin Chim Acta       Date:  2002-03       Impact factor: 3.786

4.  Expanded Newborn Screening Program in Saudi Arabia: Incidence of screened disorders.

Authors:  Majid Alfadhel; Ali Al Othaim; Saif Al Saif; Fuad Al Mutairi; Moeenaldeen Alsayed; Zuhair Rahbeeni; Hamad Alzaidan; Mohammed Alowain; Zuhair Al-Hassnan; Mohamad Saeedi; Saeed Aljohery; Ali Alasmari; Eissa Faqeih; Mansour Alwakeel; Maher AlMashary; Sulaiman Almohameed; Mohammed Alzahrani; Abeer Migdad; Osama Y Al-Dirbashi; Mohamed Rashed; Mohamed Alamoudi; Minnie Jacob; Lujane Alahaidib; Fahd El-Badaoui; Amal Saadallah; Ayman Alsulaiman; Wafaa Eyaid; Ali Al-Odaib
Journal:  J Paediatr Child Health       Date:  2017-03-24       Impact factor: 1.954

5.  Tandem mass spectrometric analysis for amino, organic, and fatty acid disorders in newborn dried blood spots: a two-year summary from the New England Newborn Screening Program.

Authors:  T H Zytkovicz; E F Fitzgerald; D Marsden; C A Larson; V E Shih; D M Johnson; A W Strauss; A M Comeau; R B Eaton; G F Grady
Journal:  Clin Chem       Date:  2001-11       Impact factor: 8.327

6.  Phenylketonuria, congenital hypothyroidism and haemoglobinopathies: public health issues for a Brazilian newborn screening program.

Authors:  Judy Botler; Luiz Antonio Bastos Camacho; Marly Marques da Cruz
Journal:  Cad Saude Publica       Date:  2012-09       Impact factor: 1.632

7.  Detection of phenylketonuria by the newborn screening program in Thailand.

Authors:  S Pangkanon; W Charoensiriwatana; N Janejai; W Boonwanich; S Chaisomchit
Journal:  Southeast Asian J Trop Med Public Health       Date:  2009-05       Impact factor: 0.267

8.  Evaluation of effectiveness and outcome of PKU screening and management in the State of Sergipe, Brazil.

Authors:  Antônio R O Ramalho; Roberto J R Ramalho; Carla R P Oliveira; Marta M G S Magalhães; Elenilde G Santos; Polyana M P Sarmento; Diana O Matos; Mario C P Oliveira; André L P Oliveira; Manuel H Aguiar-Oliveira
Journal:  Arq Bras Endocrinol Metabol       Date:  2014-02

9.  Inborn Errors of Metabolism in the United Arab Emirates: Disorders Detected by Newborn Screening (2011-2014).

Authors:  Fatma A Al-Jasmi; Aisha Al-Shamsi; Jozef L Hertecant; Sania M Al-Hamad; Abdul-Kader Souid
Journal:  JIMD Rep       Date:  2015-11-21

10.  Incidence of Neonatal Hyperphenylalaninemia Based on High-performance Liquid Chromatography Confirmatory Technique in Mazandaran Province, Northern Iran (2007-2015).

Authors:  Ali Abbaskhanian; Daniel Zamanfar; Parvaneh Afshar; Einollah Asadpoor; Hamed Rouhanizadeh; Ali Jafarnia; Mohammad Shokzadeh
Journal:  Int J Prev Med       Date:  2017-11-07
View more
  5 in total

1.  The Genetic Landscape and Epidemiology of Phenylketonuria.

Authors:  Alicia Hillert; Yair Anikster; Amaya Belanger-Quintana; Alberto Burlina; Barbara K Burton; Carla Carducci; Ana E Chiesa; John Christodoulou; Maja Đorđević; Lourdes R Desviat; Aviva Eliyahu; Roeland A F Evers; Lena Fajkusova; François Feillet; Pedro E Bonfim-Freitas; Maria Giżewska; Polina Gundorova; Daniela Karall; Katya Kneller; Sergey I Kutsev; Vincenzo Leuzzi; Harvey L Levy; Uta Lichter-Konecki; Ania C Muntau; Fares Namour; Mariusz Oltarzewski; Andrea Paras; Belen Perez; Emil Polak; Alexander V Polyakov; Francesco Porta; Marianne Rohrbach; Sabine Scholl-Bürgi; Norma Spécola; Maja Stojiljković; Nan Shen; Luiz C Santana-da Silva; Anastasia Skouma; Francjan van Spronsen; Vera Stoppioni; Beat Thöny; Friedrich K Trefz; Jerry Vockley; Youngguo Yu; Johannes Zschocke; Georg F Hoffmann; Sven F Garbade; Nenad Blau
Journal:  Am J Hum Genet       Date:  2020-07-14       Impact factor: 11.025

2.  Spectrum of PAH gene mutations in 1547 phenylketonuria patients from Iran: a comprehensive systematic review.

Authors:  Reza Alibakhshi; Aboozar Mohammadi; Nader Salari; Sahand Khamooshian; Mohsen Kazeminia; Keivan Moradi
Journal:  Metab Brain Dis       Date:  2021-02-24       Impact factor: 3.584

3.  Birth prevalence of phenylalanine hydroxylase deficiency: a systematic literature review and meta-analysis.

Authors:  Pamela K Foreman; Andrea V Margulis; Kimberly Alexander; Renee Shediac; Brian Calingaert; Abenah Harding; Manel Pladevall-Vila; Sarah Landis
Journal:  Orphanet J Rare Dis       Date:  2021-06-03       Impact factor: 4.123

Review 4.  Food Regime for Phenylketonuria: Presenting Complications and Possible Solutions.

Authors:  Sudipt Kumar Dalei; Nidhi Adlakha
Journal:  J Multidiscip Healthc       Date:  2022-01-18

5.  Optimizing the Phenylalanine Cut-Off Value in a Newborn Screening Program.

Authors:  Dasa Perko; Barbka Repic Lampret; Ziga Iztok Remec; Mojca Zerjav Tansek; Ana Drole Torkar; Blaz Krhin; Ajda Bicek; Adrijana Oblak; Tadej Battelino; Urh Groselj
Journal:  Genes (Basel)       Date:  2022-03-15       Impact factor: 4.096

  5 in total

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