BACKGROUND:

Although extended newborn screening (NBS) programs have been introduced more than 20 years ago, their impact on the long-term clinical outcome of individuals with inherited metabolic diseases (IMDs) is still rarely investigated.

METHODS:

We studied the clinical outcomes of individuals with IMDs identified by NBS between 1999 and 2016 in a prospective multicenter observational study.

RESULTS:

In total, 306 screened individuals with IMDs (115 with phenylketonuria and 191 with other IMDs with a lifelong risk for metabolic decompensation) were followed for a median time of 6.2 years. Although the risk for metabolic decompensation was disease-specific and NBS could not prevent decompensations in every individual at risk (n = 49), the majority did not develop permanent disease-specific signs (75.9%), showed normal development (95.6%) and normal cognitive outcome (87.7%; mean IQ: 100.4), and mostly attended regular kindergarten (95.2%) and primary school (95.2%). This demonstrates that not only individuals with phenylketonuria, serving as a benchmark, but also those with lifelong risk for metabolic decompensation had a favorable long-term outcome. High NBS process quality is the prerequisite of this favorable outcome. This is supported by 28 individuals presenting with first symptoms at a median age of 3.5 days before NBS results were available, by the absence of neonatal decompensations after the report of NBS results, and by the challenge of keeping relevant process parameters at a constantly high level.

CONCLUSIONS:

NBS for IMDs, although not completely preventing clinical presentations in all individuals, can be considered a highly successful program of secondary prevention.

What’s Known on This Subject:

After the introduction of tandem mass spectrometry, newborn screening programs for inherited metabolic diseases have been significantly extended since the 1990s. The long-term health benefit for neonatally screened individuals, however, has not yet been studied in a large cohort.

What This Study Adds:

This long-term observational study confirms that extended newborn screening for inherited metabolic diseases is the prerequisite for favorable long-term health outcomes of affected individuals, thus proving the success of this program of secondary prevention.

Since the late 1990s, tandem mass spectrometry (MS/MS) has been increasingly introduced into newborn screening (NBS) programs,1,2  technically enabling identification of >30 inherited metabolic diseases (IMDs) by using a single method.3  Although all existing NBS programs refer to the same set of principles,4  national NBS disease panels still lack harmonization.5,6  Longitudinal outcome studies have remained the neglected part of NBS programs, and formal evidence of the clinical effectiveness of NBS is still scarce. Exceptions are medium-sized NBS cohort studies (that include various IMDs) from Australia (New South Wales; 70 individuals, 23 different IMDs, until age of 6 years),7  the United States (Boston; 178 individuals, 24 different IMDs, average follow-up of 3.9 years),8  Spain (Galicia; 137 individuals, 26 different IMDs, average observation period of 4.5 years),9  and Germany (Southwest Germany; 125 individuals, 19 different IMDs, median age of 3.3 years),10  all demonstrating promising results.

To investigate whether MS/MS-based NBS is beneficial, in the current study, we evaluate the long-term clinical outcomes of 306 screened individuals with IMDs from the German national NBS panel.

Since 1999, the NBS laboratory of the University Hospital Heidelberg (UKHD) has used MS/MS-based NBS,2  initially in a pilot study (1999–2004) that included IMDs similar to the previously proposed core panel of 29 diseases.3  From 2005 to 2016, after a decision of the German regulatory authorities, the panel was reduced to 14 diseases (hereafter termed the national NBS panel), which included 2 endocrine diseases and 12 IMDs (Table 1).11  In this longitudinal outcome study, we focus on individuals identified by NBS between 1999 and 2016 with a confirmed diagnosis of an IMD included in the national NBS panel. Individuals with mild hyperphenylalaninemia, not requiring continuous therapy, are excluded.

TABLE 1

Birth Prevalences of Screened Individuals With IMDs: Comparison of the UKHD NBS Sample (1999–2016), the German NBS Sample (2004–2016), and a German Prescreening Cohort (1999–2000)

UKHD NBS SampleGerman NBS SampleGerman Prescreening SampleBirth Prevalence, P
Patients, No. Individuals (Deaths)Patients (Individuals With ≥1 Study Visit), No. Individuals (%)Birth Prevalence, Mean (95% Confidence Interval)Patients,a No. IndividualsBirth Prevalence,a Mean (95% Confidence Interval)Patients,b No. Individuals (Deaths)Birth Prevalence,b Mean (95% Confidence Interval)UKHD Versus German NBS SampleaUKHD NBS Sample Versus German Prescreening Sampleb
Screened individuals, birth cohort 1 881 481 (N/a) 1 881 481 (N/a) N/a 9 097 938 N/a 844 575 (N/a) N/a N/a N/a 
PKUc 152 (0) 115 (75.7) 1: 12 378 (1: 12 360–12 396) 853 1: 10 666 (1: 10 659–10 673) N/a N/a .10 N/a 
MSUD 13 (0) 9 (69.2) 1: 144 729 (1: 144 523–144 936) 52 1: 174 960 (1: 174 847–175 074) 3 (0) 1: 281 525 (1: 280 925–282 126) .65 .43 
IVA 30 (0) 29 (96.7) 1: 62 716 (1: 62 626–62 806) 100 1: 90 979 (1: 90 920–91 039) 3 (1) 1: 281 525 (1: 280 925–282 126) .09 .01 
GA1 14 (1) 13 (92.8) 1: 134 392 (1: 134 200–134 584) 68 1: 133 793 (1: 133 706–133 880) 1 (0) 1: 844 575 (1: 842 775–846 378) .99 .08 
MCADD 173 (0) 91 (52.6) 1: 10 876 (1: 10 860–10 891) 886 1: 10 269 (1: 10 261–10 275) 20 (2) 1: 42 229 (1: 42 139–42 319) .51 <.0001 
VLCADD 14 (0) 10 (71.4) 1: 134 392 (1: 134 200–13 584) 103 1: 88 330 (1: 88 272–88 387) 2 (0) 1: 422 288 (1: 421 387–423 189) .17 .18 
LCHADD/mTFPD 15 (2) 9 (60) 1: 125 432 (1: 125 253–125 611) 57 1: 159 613 (1: 159 509–159 717) 2 (2) 1: 422 288 (1: 421 387–423 189) .50 .15 
CPT1D 1 (0) 1 (100) 1: 1 881 481 (1: 1 878 795–1 884 170) 1: 1 137 242 (1: 1 136 504–1 137 981) 0 (0) N/a .97 N/a 
CPT2D 2 (2) 0 (0) 1: 940 741 (1: 939 397–942 085) 1: 1 516 323 (1: 1 515 338–1 517 308) 1 (1) 1: 844 575 (1: 842 775–846 378) .90 .99 
CACTD 0 (0) N/a <1: 1 881 481 (N/a) 1: 4 548 969 (1: 4 546 014–4 551 925) 0 (0) N/a .99 N/a 
Gal 27 (0) 19/27 (70.4) 1: 69 684 (1: 69 585–69 784) 127 1: 71 637 (1:71 591–71 684) N/a N/a .98 N/a 
BioD 20 (0) 10/20 (50) 1: 94 074 (1: 93 940–94 209) 354 1: 25 700 (1: 25 684–25 717) N/a N/a <.0001 N/a 
UKHD NBS SampleGerman NBS SampleGerman Prescreening SampleBirth Prevalence, P
Patients, No. Individuals (Deaths)Patients (Individuals With ≥1 Study Visit), No. Individuals (%)Birth Prevalence, Mean (95% Confidence Interval)Patients,a No. IndividualsBirth Prevalence,a Mean (95% Confidence Interval)Patients,b No. Individuals (Deaths)Birth Prevalence,b Mean (95% Confidence Interval)UKHD Versus German NBS SampleaUKHD NBS Sample Versus German Prescreening Sampleb
Screened individuals, birth cohort 1 881 481 (N/a) 1 881 481 (N/a) N/a 9 097 938 N/a 844 575 (N/a) N/a N/a N/a 
PKUc 152 (0) 115 (75.7) 1: 12 378 (1: 12 360–12 396) 853 1: 10 666 (1: 10 659–10 673) N/a N/a .10 N/a 
MSUD 13 (0) 9 (69.2) 1: 144 729 (1: 144 523–144 936) 52 1: 174 960 (1: 174 847–175 074) 3 (0) 1: 281 525 (1: 280 925–282 126) .65 .43 
IVA 30 (0) 29 (96.7) 1: 62 716 (1: 62 626–62 806) 100 1: 90 979 (1: 90 920–91 039) 3 (1) 1: 281 525 (1: 280 925–282 126) .09 .01 
GA1 14 (1) 13 (92.8) 1: 134 392 (1: 134 200–134 584) 68 1: 133 793 (1: 133 706–133 880) 1 (0) 1: 844 575 (1: 842 775–846 378) .99 .08 
MCADD 173 (0) 91 (52.6) 1: 10 876 (1: 10 860–10 891) 886 1: 10 269 (1: 10 261–10 275) 20 (2) 1: 42 229 (1: 42 139–42 319) .51 <.0001 
VLCADD 14 (0) 10 (71.4) 1: 134 392 (1: 134 200–13 584) 103 1: 88 330 (1: 88 272–88 387) 2 (0) 1: 422 288 (1: 421 387–423 189) .17 .18 
LCHADD/mTFPD 15 (2) 9 (60) 1: 125 432 (1: 125 253–125 611) 57 1: 159 613 (1: 159 509–159 717) 2 (2) 1: 422 288 (1: 421 387–423 189) .50 .15 
CPT1D 1 (0) 1 (100) 1: 1 881 481 (1: 1 878 795–1 884 170) 1: 1 137 242 (1: 1 136 504–1 137 981) 0 (0) N/a .97 N/a 
CPT2D 2 (2) 0 (0) 1: 940 741 (1: 939 397–942 085) 1: 1 516 323 (1: 1 515 338–1 517 308) 1 (1) 1: 844 575 (1: 842 775–846 378) .90 .99 
CACTD 0 (0) N/a <1: 1 881 481 (N/a) 1: 4 548 969 (1: 4 546 014–4 551 925) 0 (0) N/a .99 N/a 
Gal 27 (0) 19/27 (70.4) 1: 69 684 (1: 69 585–69 784) 127 1: 71 637 (1:71 591–71 684) N/a N/a .98 N/a 
BioD 20 (0) 10/20 (50) 1: 94 074 (1: 93 940–94 209) 354 1: 25 700 (1: 25 684–25 717) N/a N/a <.0001 N/a 

Adapted from Klose DA, Kölker S, Heinrich B, et al. Incidence and short-term outcome of children with symptomatic presentation of organic acid and fatty acid oxidation disorders in Germany. Pediatrics. 2002;110(6):1204–1211. N/a, not applicable.

a

According to the annual reports of the German Society for Newborn Screening.12 

b

According to Klose et al.13 

c

Without mild hyperphenylalaninemia.

The recommended time frame for sampling of dried blood spots (DBS) is age 36 to 72 hours.11  To evaluate the diagnostic process quality of all screened individuals born at ≥32 weeks’ gestation who were ≥36 hours of age at sampling, we determined the times of DBS sampling (time 1), DBS sample receipt in the NBS laboratory (time 2), and reporting of the NBS result (time 3) and, subsequently, calculated 3 intervals: Δ1 = time 3 − time 1 (total NBS interval), Δ2 = time 3 − time 2 (analysis interval), and Δ3 = time 2 − time 1 (shipping interval). Because time 1, time 2, and time 3 were not systematically recorded between 1999 and 2002, this analysis is restricted to NBS data collected between 2003 and 2016. Data sets with missing values and those considered as implausible (time 1 > 28 days, time 2 > 42 days, time 3 > 56 days, Δ1 > 54.5 days, and Δ2 and Δ3 > 14 days each) were excluded.

To evaluate the clinical benefit of NBS, a prospective multicenter observational study was implemented in 2005 (NGS2020, German Clinical Trials Register identifier: DRKS00013329). The study was approved by the local ethics committee of the coordinating site (Medical Faculty of Heidelberg, application S-104/2005) and consecutively by all study sites (in Düsseldorf, Freiburg, Mainz, Reutlingen, and Ulm, Germany). Inclusion criteria are (1) date of birth on or after January 1, 1999; (2) positive NBS result; (3) confirmation of diagnosis according to the national guideline14  by using additional metabolite, enzyme and/or genetic tests; and (4) written informed consent before enrollment. Comprehensive regular follow-up information by structured clinical examination and medical history taking, analysis of medical records, and neuropsychological testing was obtained at defined ages (Table 2). The cutoff date for database readout was February 1, 2018.

TABLE 2

Clinical and Cognitive Outcome

DiagnosisIndividuals, nIndividuals With Permanent Disease-Specific Clinical Signs, nIndividuals With Metabolic Decompensation, n (EO/LO)Result of Last DDST, n Appropriate for Age (n Tested)Result of Last IQ Test, Median ± SD (n Tested)
PKU 115 0 (0/0) 75 (76) 100.5 ± 13.9 (75) 
MSUD 8 (4/4) 5 (5) 89.9 ± 13 (8) 
IVA 29 6 (5/1) 13 (14) 98 ± 12.2 (10) 
GA1 13 3 (0/3) 4 (7) 95.4 ± 9.6 (7) 
MCADD 91 11 (6/5) 48 (49) 102.4 ± 13.8 (48) 
VLCADD 10 4 (2/2) 4 (5) 103.1 ± 4.9 (7) 
LCHADD/mTFPD 7 (2/5) 7 (8) 101.8 ± 6.0 (6) 
CPT1D 1 (0/1) Not tested Not tested 
Gal 19 9 (9/0) 11 (11) 95.2 ± 14.3 (12) 
BioD 10 0 (0/0) 8 (8) 113.3 ± 11.0 (6) 
Total 306 26 49 (28/21) 175 (183) 100.4 ± 13.4 (179) 
DiagnosisIndividuals, nIndividuals With Permanent Disease-Specific Clinical Signs, nIndividuals With Metabolic Decompensation, n (EO/LO)Result of Last DDST, n Appropriate for Age (n Tested)Result of Last IQ Test, Median ± SD (n Tested)
PKU 115 0 (0/0) 75 (76) 100.5 ± 13.9 (75) 
MSUD 8 (4/4) 5 (5) 89.9 ± 13 (8) 
IVA 29 6 (5/1) 13 (14) 98 ± 12.2 (10) 
GA1 13 3 (0/3) 4 (7) 95.4 ± 9.6 (7) 
MCADD 91 11 (6/5) 48 (49) 102.4 ± 13.8 (48) 
VLCADD 10 4 (2/2) 4 (5) 103.1 ± 4.9 (7) 
LCHADD/mTFPD 7 (2/5) 7 (8) 101.8 ± 6.0 (6) 
CPT1D 1 (0/1) Not tested Not tested 
Gal 19 9 (9/0) 11 (11) 95.2 ± 14.3 (12) 
BioD 10 0 (0/0) 8 (8) 113.3 ± 11.0 (6) 
Total 306 26 49 (28/21) 175 (183) 100.4 ± 13.4 (179) 

Comprehensive regular follow-up information by structured clinical examination and medical history taking, analysis of medical records, and neuropsychological testing or record of previous tests (ie, DDST, revised edition and age-adapted IQ-based psychological tests, such as Wechsler Preschool and Primary Scale of Intelligence, Third Edition; Wechsler Intelligence Scale for Children, Fourth Edition; and Wechsler Adult Intelligence Scale, Fourth Edition) was obtained at defined ages (ie, 1.5, 3.5, 5.5, 9, 14, and 18 y), with permitted deviation of 6 (1.5–5.5 y) or 12 mo (9–18 y). Permanent disease-specific clinical signs are according to Supplemental Fig 9.

Metabolic decompensation is defined as any event requiring hospitalization (at least 1 night) because of subclinical biochemical derangement or any clinical presentation indicating metabolic decompensation. Onset of first metabolic decompensation in the neonatal period (<29 days of life) was classified as early onset (EO), and onset at a later age was classified as late onset (LO).

All statistical analyses were performed by using R, a language for statistical computing and graphics (https://www.r-project.org). Missing data that could not be retrieved and implausible data that could not be verified were treated as case-wise missing for the respective analysis. IQ values between groups were compared by using analysis of variance with post hoc Tukey contrasts based on marginal means from R package “emmeans.” First clinical manifestations were calculated by using Kaplan-Meier estimates for right-censored data, and groups were compared by using the log-rank test. Differences in onset of first metabolic crisis between diseases were analyzed by using Kaplan-Meier estimates in conjunction with model-based recursive partitioning.15  IMD birth prevalences with confidence intervals were computed by using the R package “epiR.” Differences between birth prevalences as well as count data from frequency tables were analyzed by using χ2 tests. Disease-specific hospitalization rates were computed as the ratio of the total number of all hospitalizations at ≤6 years of age by the total number of participants per diagnosis. Poisson regression was used to model hospitalization risk rates across diseases. Dunnett contrasts with reference to hospitalization rates of individuals with biotinidase deficiency (BioD) were computed to test differences in hospitalization rates between BioD and all other diseases. Contrasts were estimated by using estimated marginal means from R package “emmeans.” To control for family-wise error rates (type I error), Dunnett corrections were used in Dunnett contrasts; the Tukey procedure was applied otherwise. For statistical analysis of all outcome parameters, sex and migrant background were considered besides diagnosis.

From 1999 to 2016, 1 881 481 newborns were screened at UKHD, representing 14.77% of the live births during this time interval in Germany.16  In 521 individuals (245 girls and 276 boys), the suspected IMD was confirmed,14  and 461 of them (212 girls and 249 boys) had an IMD from the national NBS panel (Fig 1). Two patients were missed: 1 with phenylketonuria (PKU) because of a technical error and another with biochemically mild medium-chain acyl-coenzyme A dehydrogenase deficiency (MCADD) who had an NBS result below the cutoff. IMD birth prevalences of the UKHD sample and the complete German NBS sample12 2 test) were similar, except for BioD. The birth prevalences of MCADD (P < .0001) and isovaleric aciduria (IVA) (P = .011) in the NBS sample were higher than those in a prescreening cohort reported by a former study13  (Table 1).

FIGURE 1

Description of the study sample. a The national NBS panel included PKU, MSUD, IVA, GA1, MCADD, VLCADD, long-chain 3-hydroxyacyl-coenzyme A dehydrogenase deficiency, CPT1D, CPT2D, CACTD, Gal, and BioD. b 6-Pyruvoyl-tetrahydropterin synthase deficiency (n = 2), identified by PKU screening (elevated phenylalanine concentration), and IMDs of the pilot panel (ie, argininosuccinate synthetase 1 deficiency [n = 10], short-chain acyl-coenzyme A dehydrogenase deficiency [n = 9], 3-methylcrotonyl-coenzyme A carboxylase deficiency [n = 8], carnitine transporter deficiency [n = 7], multiple acyl-coenzyme A dehydrogenase deficiency [n = 7], propionic aciduria [n = 6], methylmalonic acidurias [n = 4: 1 with mut0-type methylmalonic aciduria (due to inherited loss of methylmalonyl-CoA mutase activity), 2 with cobalamin C deficiency, and 1 with unclassified methylmalonic aciduria], tyrosinemia type 1 [n = 4], and argininosuccinate lyase deficiency [n = 2]). c Individuals with PKU. d Individuals with MSUD, IVA, GA1, MCADD, VLCADD, LCHADD, CPT1D, Gal, and BioD.

FIGURE 1

Description of the study sample. a The national NBS panel included PKU, MSUD, IVA, GA1, MCADD, VLCADD, long-chain 3-hydroxyacyl-coenzyme A dehydrogenase deficiency, CPT1D, CPT2D, CACTD, Gal, and BioD. b 6-Pyruvoyl-tetrahydropterin synthase deficiency (n = 2), identified by PKU screening (elevated phenylalanine concentration), and IMDs of the pilot panel (ie, argininosuccinate synthetase 1 deficiency [n = 10], short-chain acyl-coenzyme A dehydrogenase deficiency [n = 9], 3-methylcrotonyl-coenzyme A carboxylase deficiency [n = 8], carnitine transporter deficiency [n = 7], multiple acyl-coenzyme A dehydrogenase deficiency [n = 7], propionic aciduria [n = 6], methylmalonic acidurias [n = 4: 1 with mut0-type methylmalonic aciduria (due to inherited loss of methylmalonyl-CoA mutase activity), 2 with cobalamin C deficiency, and 1 with unclassified methylmalonic aciduria], tyrosinemia type 1 [n = 4], and argininosuccinate lyase deficiency [n = 2]). c Individuals with PKU. d Individuals with MSUD, IVA, GA1, MCADD, VLCADD, LCHADD, CPT1D, Gal, and BioD.

Close modal

Clinical long-term outcome was analyzed in 306 (154 girls and 152 boys) individuals (ie, 66.4% of those identified by NBS) (Fig 1). Because no patient with carnitine-acylcarnitine translocase deficiency (CACTD) had been identified and 2 individuals with the neonatal form of carnitine palmitoyltransferase 2 deficiency (CPT2D) had died before enrollment, the cohort included 10 of the 12 IMDs from the national NBS panel. The median age at last visit was 6.2 years (interquartile range [IQR]: 3.4–10.8; range: 1.0–17.4), migrant background was more frequent (34.3%) than in the general population17  (23.6%), and 16% of individuals had consanguineous parents. None of the longitudinally followed individuals died during the observation period. However, 7 individuals (2 with neonatal CPT2D or neonatal mitochondrial trifunctional protein deficiency and 1 with glutaric aciduria type 1 [GA1], multiple acyl-coenzyme A dehydrogenase deficiency, or propionic aciduria) each died before the first study visit because of metabolic (all except GA1) or nonmetabolic causes (GA1). This reveals a mortality rate of 1.1% (5 of 461 patients) for the German national NBS panel and 3.3% (2 of 60 patients) for screened individuals with other IMDs (Fig 1, Table 1).

High NBS process quality is the prerequisite of favorable clinical outcomes of screened individuals. Therefore, NBS process quality was studied in 1 499 129 individuals screened between 2003 and 2016 (Supplemental Fig 6). Time of DBS sampling (time 1) decreased continuously. Similarly, the time of the first NBS report (time 3) decreased between 2003 and 2007 but has remained stable ever since. This is explained by the concomitantly increasing DBS shipping interval (Δ3) (Fig 2, Supplemental Fig 6F), highlighting that the sender and recipient of the NBS sample have improved their performance, whereas the carrier has not. As a consequence, the requirements of the national NBS directive were fulfilled in >75% of screened individuals for time 1 (36–72 hours) and in almost 100% of screened individuals for the analytical time interval (Δ2 ≤ 24 hours), whereas the recommended time interval from DBS sampling to first NBS report (Δ1 ≤ 72 hours) was achieved in <50% of screened individuals11  (Supplemental Fig 6 A, D, and E).

FIGURE 2

NBS process quality. NBS process quality was evaluated in 1 499 129 individuals screened from 2003 to 2016. Age at DBS sampling (time 1, red), age at first report of the NBS result to the sender (time 3, green), and time interval (∆3, blue) between DBS sampling (time 1) and receipt of the DBS sample in the NBS laboratory (time 2) are presented. Time 1, time 3, and ∆3 (hours) are depicted as medians (lines) and IQRs (color-shaded areas).

FIGURE 2

NBS process quality. NBS process quality was evaluated in 1 499 129 individuals screened from 2003 to 2016. Age at DBS sampling (time 1, red), age at first report of the NBS result to the sender (time 3, green), and time interval (∆3, blue) between DBS sampling (time 1) and receipt of the DBS sample in the NBS laboratory (time 2) are presented. Time 1, time 3, and ∆3 (hours) are depicted as medians (lines) and IQRs (color-shaded areas).

Close modal

Acute Metabolic Decompensation and Hospitalization Rate

Except for individuals with PKU (n = 115), all other participants (n = 191) had an IMD with a lifelong risk for metabolic decompensation (Table 2). The majority (n = 168) was at risk for neonatal decompensations, except for those with BioD and GA1. Overall, 49 of the 191 individuals (25.7%) at risk experienced at least 1 metabolic decompensation, 28 of them (14.7%) already before the NBS result was known (Fig 3). The overall median age at first decompensation was 7 days (IQR: 1–542; range: 0–2075), and the median age at first decompensation was 3.5 days (IQR: 0–5; range: 0–9) in the EO group and 587 days (IQR: 466–740; range: 37–2075) in the LO group (n = 21). Noteworthy, none of the neonatal decompensations occurred after the report of the positive NBS result. Highest frequencies of decompensations were found for maple syrup urine disease (MSUD) (89%) and long-chain 3-hydroxyacyl-coenzyme A dehydrogenase and mitochondrial trifunctional protein deficiency (LCHADD/mTFPD) (78%).

FIGURE 3

Age at first metabolic decompensation of screened individuals with IMDs. Kaplan-Meier analysis of age at first metabolic decompensation. Depicted groups are the results of the statistical analysis (model-based recursive partitioning) demonstrating that the age and risk of acute metabolic decompensation differs in IMDs: group 1 (PKU, BioD; n = 125): no risk of metabolic decompensation; group 2 (IVA, MCADD, GA1; n = 133): moderate risk of metabolic decompensation; group 3 (Gal, MSUD, VLCADD, LCHADD/mTFPD, CPT1D; n = 48): high risk of metabolic decompensation. Age at first decompensation differed between groups 2 and 3 (P < .001). Vertical lines indicate censored patients.

FIGURE 3

Age at first metabolic decompensation of screened individuals with IMDs. Kaplan-Meier analysis of age at first metabolic decompensation. Depicted groups are the results of the statistical analysis (model-based recursive partitioning) demonstrating that the age and risk of acute metabolic decompensation differs in IMDs: group 1 (PKU, BioD; n = 125): no risk of metabolic decompensation; group 2 (IVA, MCADD, GA1; n = 133): moderate risk of metabolic decompensation; group 3 (Gal, MSUD, VLCADD, LCHADD/mTFPD, CPT1D; n = 48): high risk of metabolic decompensation. Age at first decompensation differed between groups 2 and 3 (P < .001). Vertical lines indicate censored patients.

Close modal

Although the majority of individuals had a single reported decompensation (total: n = 30; EO: n = 17), 39% (n = 19) had recurrent decompensations for a total of 166 episodes. On average, single episodes were documented for GA1, classic galactosemia (galactose-1-phosphate uridyltransferase deficiency) (Gal), and carnitine palmitoyltransferase 1 deficiency (CPT1D); 1.3 episodes for MCADD; 3.2 for IVA; 4.1 for MSUD; 5.3 for LCHADD/mTFPD; and 12.5 for very long-chain acyl-coenzyme A dehydrogenase deficiency (VLCADD). In analogy, frequency of hospitalizations (total: N = 953) was disease-dependent (Supplemental Fig 7), being more frequent in patients at risk for decompensation (3.8 times per patient) than in those without (1.9 times; P < .001; Table 3). In 93% of them, however, the clinical status at discharge was unchanged compared with the predecompensation status (Supplemental Table 4).

TABLE 3

Hospitalizations of Screened Individuals With IMDs: Frequency and Causes

Total (n = 306)Individuals Without Risk for Decompensation (n = 115)Individuals at Risk for Decompensation (n = 191)Individuals Without Risk Versus at Risk, P
Total hospitalizations (average per patient) 953 (3.1) 223 (1.9) 730 (3.8) <.001 
Causes for hospitalization, n (%)a     
 Elective admissionb 344 (36.1) 161 (72.2) 183 (25.1) <.001 
 Infectious disease 420 (44.1) 38 (17.0) 382 (52.3) <.001 
 Feeding difficulty 145 (15.2) 11 (4.9) 134 (18.4) <.001 
 Neurologic presentation (new) 19 (2.0) 9 (4.0) 10 (1.4) .013 
 Metabolic decompensation 166 (17.4) 0 (0) 166 (22.7) N/a 
 Othersc 146 (15.3) 37 (16.6) 109 (14.9) .55 
Total (n = 306)Individuals Without Risk for Decompensation (n = 115)Individuals at Risk for Decompensation (n = 191)Individuals Without Risk Versus at Risk, P
Total hospitalizations (average per patient) 953 (3.1) 223 (1.9) 730 (3.8) <.001 
Causes for hospitalization, n (%)a     
 Elective admissionb 344 (36.1) 161 (72.2) 183 (25.1) <.001 
 Infectious disease 420 (44.1) 38 (17.0) 382 (52.3) <.001 
 Feeding difficulty 145 (15.2) 11 (4.9) 134 (18.4) <.001 
 Neurologic presentation (new) 19 (2.0) 9 (4.0) 10 (1.4) .013 
 Metabolic decompensation 166 (17.4) 0 (0) 166 (22.7) N/a 
 Othersc 146 (15.3) 37 (16.6) 109 (14.9) .55 

Individuals without risk for metabolic decompensation and individuals at risk for metabolic decompensation (χ2 test). All hospitalizations (at least 1 night) from birth to last study visit were counted for analysis. N/a: not applicable.

a

Multiple choice is possible. Therefore, the sum of documented causes may exceed the number of hospitalizations (eg, for 953 hospitalizations, a total of 1240 causes have been documented).

b

For example, confirmation diagnosis, elective surgery, optimization of metabolic therapy.

c

For example, perinatal problems, unintentional injuries, allergic reaction or anaphylaxis, cardiac symptoms.

Long-term Clinical Outcome

Assumingly irreversible, disease-specific clinical signs were defined for each IMD included in the national NBS panel (Supplemental Fig 9). Until the last available visit (up to age 17 years), 75.9% of individuals did not develop permanent disease-specific clinical signs (Supplemental Fig 8), with remarkable disease-dependent differences: Individuals with LCHADD/mTFPD, MSUD, and GA1 more often developed permanent clinical signs than those with the remaining IMDs (P < .001; Fig 4). Individuals who experienced a metabolic decompensation before the NBS result was known (n = 28) did not differ from individuals at risk who remained asymptomatic, until the NBS report, regarding disease-specific clinical signs (n = 140; P = .993; Fig 5) or IQ (n = 91; P = .073, Welch t test).

FIGURE 4

Onset of permanent disease-specific clinical signs is disease-dependent. Kaplan-Meier analysis of onset of assumingly irreversible disease-specific signs (Supplemental Fig 9) in screened individuals with IMDs. Depicted groups are the results of the statistical analysis (model-based recursive partitioning) demonstrating that age at first onset of permanent disease-specific signs differs in IMDs: group 1: PKU, BioD, IVA, MCADD, VLCADD, CPT1D, Gal (n = 275); group 2: MSUD, LCHADD/mTFPD, GA1 (n = 31; log-rank test, P < .001). Vertical lines indicate censored patients. Color-shaded areas indicate the 95% confidence interval.

FIGURE 4

Onset of permanent disease-specific clinical signs is disease-dependent. Kaplan-Meier analysis of onset of assumingly irreversible disease-specific signs (Supplemental Fig 9) in screened individuals with IMDs. Depicted groups are the results of the statistical analysis (model-based recursive partitioning) demonstrating that age at first onset of permanent disease-specific signs differs in IMDs: group 1: PKU, BioD, IVA, MCADD, VLCADD, CPT1D, Gal (n = 275); group 2: MSUD, LCHADD/mTFPD, GA1 (n = 31; log-rank test, P < .001). Vertical lines indicate censored patients. Color-shaded areas indicate the 95% confidence interval.

Close modal
FIGURE 5

Neonatal metabolic decompensation does not predict unfavorable disease course. Kaplan-Meier analysis of onset of assumingly permanent (ie irreversible disease-specific clinical signs) (Supplemental Fig 9) in individuals who experienced a neonatal metabolic decompensation before the NBS result was known (blue; n = 28) compared with individuals at risk who remained asymptomatic until the NBS report (green; n = 140). Both courses did not differ (log-rank test, P = .993). Vertical lines indicate censored patients.

FIGURE 5

Neonatal metabolic decompensation does not predict unfavorable disease course. Kaplan-Meier analysis of onset of assumingly permanent (ie irreversible disease-specific clinical signs) (Supplemental Fig 9) in individuals who experienced a neonatal metabolic decompensation before the NBS result was known (blue; n = 28) compared with individuals at risk who remained asymptomatic until the NBS report (green; n = 140). Both courses did not differ (log-rank test, P = .993). Vertical lines indicate censored patients.

Close modal

Latest results of the Denver Developmental Screening Test (DDST) (n = 183) at a median age of 18.9 (IQR: 18–21; range: 12.5–71.4) months revealed age-appropriate results in 95.6% of tested individuals. Last IQ-based tests (n = 179) at a median age of 8.4 (IQR: 5.1–9.9; range: 2.8–17.0) years revealed a mean IQ of 100.4 (SD 13.4), with 87.7% (n = 157) of individuals with an IQ ≥85 (Table 2). Regardless of the theoretical risk, children who actually experienced a metabolic decompensation differed from those who did not (P = .004, analysis of variance). The mean IQ, although still in the normal range, was lower in individuals with a decompensation (IQ of 96.3 [SD 11.6]) than in those without (n = 92; IQ of 102.9 [SD 13.7]; P = .04, Tukey contrast).

The majority of individuals (95.2%; 237 of 249) at least 3 years of age attended regular kindergarten. Similarly, the majority of individuals (95.2%; 139 of 146) who reached compulsory school age attended regular primary school.

Assistive Technology and Allied Health Professions

Data on use of assistive technology and allied health professions were available for 215 and 207 individuals, respectively. Three patients (1.4%) used assistive technology (orthopedic aids [3; 1.4%], wheelchairs [2; 0.9%], and communications aids [1; 0.5%]), whereas the great majority (n = 212; 98.6%) did not. Patients required speech and physical therapy more often than the cohort insured by Allgemeine Ortskrankenkasse (AOK), Germany’s largest health insurance company18  (Supplemental Table 5).

Previous NBS programs for IMDs such as PKU enormously improved health outcomes of affected individuals,19  fostering the extension of NBS disease panels. The inclusion of IMDs in worldwide MS/MS-based NBS programs followed systematic evaluations of IMDs regarding cost, yield, and outcome in the United Kingdom20  and United States.3  However, the long-term clinical benefit of extended NBS programs for individuals with IMDs has remained largely unknown. Here, we demonstrate that MS/MS-based NBS, as exemplified by the German national NBS panel, is a highly successful preventive care program and a major prerequisite of early diagnosis and timely start of therapy, resulting in favorable clinical outcomes of screened individuals.

Although most of the screened individuals with an IMD (total 90.8%; 85.3% of individuals at risk for metabolic decompensations) were asymptomatic at the time of the NBS report, some (total 9.2%; 14.7% of those at risk) had already developed a neonatal decompensation, the majority of them as a single episode. None of the neonatal decompensations occurred after the positive NBS result had been reported, underlining the importance of optimal diagnostic process quality and early NBS results. Seventy-five percent of neonatal decompensations occurred in the first 5 days of life. Although it seems unlikely to catch these individuals when they are asymptomatic (unless DBS sampling would be moved to an even earlier time), the remaining 25% of neonatal decompensations, occurring between days 6 and 9 of age, could be reduced by further optimization of the NBS process. However, optimization processes are complex. This is demonstrated by the continuous improvement of the age at sampling (sender) and the analysis interval (NBS laboratory) but the simultaneously decreasing performance of the carrier (national mail service), once one of the fastest in Europe,5  hampering an overall improvement of the process quality. Individuals with IMDs requiring immediate therapy are particularly affected because the risk of neonatal decompensation increases with every day of delay. This is also relevant for extensions of NBS programs toward urea cycle disorders, such as propionic or methylmalonic aciduria, IMDs with a high frequency of severe and potentially fatal neonatal decompensations often already during the first days of life.21,22 

In the majority of individuals with a risk of decompensation (74.3%), these potentially life-threatening episodes were prevented. The consequences of metabolic decompensations vary considerably between IMDs. In GA1, the first episode usually results in irreversible striatal injury with subsequent dystonia but can be prevented in the majority of screened individuals who adhere to treatment recommendations.23  In other IMDs, these episodes may remain without clinical long-term consequences if emergency therapy is started immediately, exemplified by the overall favorable outcomes in individuals with IVA and MCADD in comparison with those in the prescreening era.7,2426  Although NBS leads to reduced mortality and higher frequency of asymptomatic individuals with IVA and MCADD, this positive effect of NBS programs might be overestimated by identification of individuals with an attenuated or benign disease variant.27  The clinical benefit of NBS for individuals with long-chain fatty acid oxidation disorders (LCHADD/mTFPD, VLCADD) is less obvious, which is also reflected by their lower inclusion rate in European NBS panels.5  Similar to previous studies,28,29  the majority of these patients (78%) were asymptomatic at the NBS report, but recurrent decompensations, mostly rhabdomyolysis, could not be reliably prevented thereafter. More than 50% of all decompensations were reported for this IMD group, which accounts for only 10% of individuals at risk for decompensation. MSUD revealed high rates of metabolic decompensations, whereas the survival rate was 100% and cognitive outcome remained in the normal range. This is in line with previous studies showing reduced mortality30  (n = 24) and improved cognitive outcome31,32  (n = 8 each) in screened individuals.

Despite metabolic decompensations, the overall health outcome remained favorable in screened individuals. This is confirmed by the high survival rate (99%), the moderate frequency of persisting clinical signs until the maximal evaluated age of 17 years (24.1%), the age-appropriate neurologic development (95.6%; DDST) and favorable cognitive functions (mean IQ of 100.4; 87% having an IQ ≥85), the scarce use of assistive technology (1.4%), and the high attendance rates (95.2%) at regular kindergarten and primary school. This highlights that in comparison with screened individuals with PKU and BioD, who did not suffer a single metabolic decompensation during the study interval and hence serve as a benchmark, screened individuals with IMDs with a moderate (IVA, MCADD, and GA1) or high risk of metabolic decompensation and hospitalization (Gal, LCHADD/mTFPD, MSUD, VLCADD, and CPT1D; Fig 3, Table 3) also had a favorable clinical and cognitive long-term outcome (Table 2).

Although NBS leads to a favorable outcome, living with a child with an IMD is often stressful for parents and families.33  This is underlined by the high hospitalization rate, including numerous preemptive admissions. As a consequence of coping efforts, quality of life of these parents is often lower than that of their children,34  the lifelong risk of morbidity and mortality hanging over them like a “Sword of Damocles.” This emphasizes the importance of support by a multiprofessional expert team. To secure the success of NBS programs, development of evidence- and consensus-based recommendations by scientific consortia involving patient representatives and the establishment of European References Networks, such as MetabERN (https://metab.ern-net.eu), seem instrumental.35 

This study is limited by the following aspects: First, implementation of NBS programs increased birth prevalences of some IMDs compared to the prescreening era. This might be explained not only by underdiagnosis of symptomatic individuals before the start of MS/MS-based NBS programs but also by an NBS-induced increase in the identification of individuals with attenuated disease variants. Because individuals with attenuated disease variants of IVA, VLCADD, and MCADD could not be discriminated with certainty from those with a severe phenotype and, hence, were treated in a similar way to avoid potentially life-threatening metabolic decompensations, the effect size of NBS for these diseases is likely to be overestimated. Second, the cohort of the long-term outcome study differed slightly regarding the case mix of IMDs compared with the total cohort identified by NBS. Individuals with MCADD and BioD, usually showing excellent clinical outcomes if diagnosed by NBS, are underrepresented. This might result in underestimation of the positive NBS effect. Third, the study cohort, although including schoolchildren and adolescents, does not yet reliably inform about the sustainability of the positive NBS effect until adulthood.

The German MS/MS-based NBS program for IMDs, allowing an early, mostly (>90%) asymptomatic, diagnosis and immediate access to specialized metabolic therapy, is a highly successful program of secondary prevention. It serves as a major prerequisite of early diagnosis and timely start of therapy, resulting in a favorable clinical outcome. This notion is supported by low frequencies of cognitive disability, irreversible organ dysfunction, and premature death in screened individuals. However, NBS cannot prevent disease manifestations in all screened individuals, highlighting the need for safer and more effective therapies. Observational longitudinal studies, an often-neglected part of NBS programs, are indispensable to precisely evaluate the long-term health benefit and life-changing impact of NBS for individuals with rare diseases, answering the ultimate and most important question of NBS programs.

We thank all patients and their parents who participated in this study by sharing their experiences of daily practice and family life as a child or parent of a child with an IMD for their motivation and trust. We thank Michèle Dressel and Elena Boyd for critically proofreading the manuscript. The Strengthening the Reporting of Observational Studies in Epidemiology statement was used when preparing this article.

Deidentified individual participant data will not be made available.

Dr Mütze conceptualized and designed the study and the data collection instruments, coordinated and supervised data collection, evaluated and interpreted data, drafted the initial manuscript, reviewed and revised the final manuscript, had full access to all the data in the study, and had final responsibility for the decision to submit for publication; Dr Kölker conceptualized and designed the study and the data collection instruments, coordinated and supervised data collection, evaluated and interpreted data, drafted the initial manuscript, and reviewed and revised the final manuscript; Dr Garbade conducted the statistical analyses and critically reviewed and revised the manuscript for important intellectual content; Drs Lindner and Gramer designed the study, collected newborn screening and clinical data, and critically reviewed and revised the manuscript for important intellectual content; Mr Gleich conducted data collection and management and critically reviewed and revised the manuscript for important intellectual content; Drs Freisinger, Hennermann, Ensenauer, Leichsenring, Grünert, Thimm, and Zirnbauer collected the data at their study site and reviewed and critically revised the manuscript for important intellectual content; Drs Hörster, Grohmann-Held, and Boy collected data at the study center and reviewed and revised the manuscript critically for important intellectual content; Dr Fang-Hoffmann collected newborn screening data and reviewed and critically revised the manuscript for important intellectual content; Dr Burgard designed the study, collected clinical data, conducted psychological tests, and critically reviewed and revised the manuscript for important intellectual content; Dr Walter collected clinical data, conducted psychological tests, and critically reviewed and revised the manuscript for important intellectual content; Dr Hoffmann conceptualized and designed the study and critically reviewed and revised the manuscript for important intellectual content; and all authors approved the final manuscript as submitted and agree to be accountable for all aspects of the work.

This trial has been registered with the German Clinical Trials Register (https://www.drks.de/drks_web/) (identifier DRKS00013329).

FUNDING: This long-term outcome study (titled “Long-term Outcome of Patients With Inherited Metabolic Diseases After Diagnosis by Expanded Newborn Screening,” NGS2020) is generously supported by the Dietmar Hopp Foundation, Sankt Leon-Rot, Germany (grants 23011220 and 2311221). The authors confirm independence from the sponsor; the content of the article has not been influenced by the sponsor. Dr Mütze is supported by an Olympia Morata research fellowship of the Medical Faculty of the Ruprecht Karl University of Heidelberg (grant F.206852).

Δ1

time 3 − time 1

Δ2

time 3 − time 2

Δ3

time 2 − time 1

BioD

biotinidase deficiency

CACTD

carnitine-acylcarnitine translocase deficiency

CPT1D

carnitine palmitoyltransferase 1 deficiency

CPT2D

carnitine palmitoyltransferase 2 deficiency

DBS

dried blood spots

DDST

Denver Developmental Screening Test

EO

early onset

GA1

glutaric aciduria type 1

Gal

classic galactosemia (galactose-1-phosphate uridyltransferase deficiency)

IMD

inherited metabolic disease

IQR

interquartile range

IVA

isovaleric aciduria

LCHADD/mTFPD

long-chain 3-hydroxyacyl-coenzyme A dehydrogenase and mitochondrial trifunctional protein deficiency

LO

late onset

MCADD

medium-chain acyl-coenzyme A dehydrogenase deficiency

MS/MS

tandem mass spectrometry

MSUD

maple syrup urine disease

NBS

newborn screening

PKU

phenylketonuria

UKHD

University Hospital Heidelberg

VLCADD

very long-chain acyl- coenzyme A dehydrogenase deficiency

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Competing Interests

POTENTIAL CONFLICT OF INTEREST: The authors have indicated they have no potential conflicts of interest to disclose.

FINANCIAL DISCLOSURE: The authors have indicated they have no financial relationships relevant to this article to disclose.

Supplementary data