asd in the dsm5 sensibilidade e especificidade diagnostica na infancia

8/19/2019 ASD in the DSM5 Sensibilidade e Especificidade Diagnostica Na Infancia

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O R I G I N A L P A P E R

Autism Spectrum Disorder in the DSM-5: Diagnostic Sensitivityand Specificity in Early Childhood

Jessica A. Christiansz1 • Kylie M. Gray1,2 • John Taffe1 • Bruce J. Tonge1

Springer Science+Business Media New York 2016

Abstract Changes to the DSM-5 Autism Spectrum

Disorder (ASD) criteria raised concerns among parents andpractitioners that the criteria may exclude some children

with Pervasive Developmental Disorder (PDD). Few

studies have examined DSM-5 sensitivity and specificity in

children less than 5 years of age. This study evaluated 185

children aged 20–55 months with DSM-IV PDD or

developmental delay. Autism Diagnostic Interview—Re-

vised (ADI-R) and Autism Diagnostic Observation

Schedule (ADOS) data was assigned to DSM-5 subdo-

mains. Children displaying the required symptomatology

were classified with DSM-5 ASD. DSM-IV clinical diag-

noses were compared to DSM-5 classifications. Using

combined ADI-R/ADOS information, sensitivity was .84

and specificity was .54. Comorbid behaviour and emotional

problems were significantly lower in children with PDD

that did not meet DSM-5 criteria.

Keywords Autism Spectrum Disorder ADI-R ADOS

Diagnosis DSM-5

Introduction

The revisions to the American Psychiatric Association’s

(APA) diagnostic criteria for Autism Spectrum Disorder in

the DSM-5 (APA 2013) raised concerns that some indi-

viduals, particularly those more cognitively able or those

with Pervasive Developmental Disorder Not Otherwise

Specified (PDD-NOS), may be less likely to receive a

DSM-5 (APA 2013) diagnosis of ASD (e.g. McPartland

et al. 2012; Tanguay 2011). A systematic review and meta-

analysis of 14 studies reported that ASD diagnoses sig-

nificantly decreased by 31 % (7.3–68.4 %) under the

DSM-5 criteria (Kulage et al. 2014). Sample characteristics

such as age and comorbid intellectual disability, varied

widely across studies. Individuals initially diagnosed with

PDD-NOS appeared to be the most affected, with a 70 %

decrease in diagnosis under the DSM-5 compared to 22 %

for Autistic Disorder.

A comprehensive study comparing DSM-IV and DSM-5

concluded that most children aged 2–17 years who received

a DSM-IV PDD diagnosis met the DSM-5 ASD criteria,

including more cognitively able individuals (Huerta et al.

2012). Three large archival data sets contained a total of

4453 children with DSM-IV PDD diagnoses (Autistic

Disorder, PDD-NOS or Asperger’s Disorder) and 690 chil-

dren with non-PDD DSM-IV diagnoses (e.g. language dis-

order, Attention Deficit Hyperactivity Disorder). Autism

Diagnostic Observation Schedule (ADOS; Lord et al. 2001)

and Autism Diagnostic Interview—Revised (ADI-R; Lord

et al. 1994) items were mapped onto both DSM-IV and

DSM-5 criteria. That is, individual ADI-R and ADOS

symptoms were assigned to the criterion that best matched

the symptoms described in the diagnostic criteria. Good

overall sensitivity (.91–.99) was reported, however speci-

ficity was low (.33–.53). Similarly, sensitivity was typically

Electronic supplementary material The online version of this

article (doi:10.1007/s10803-016-2734-4 ) contains supplementarymaterial, which is available to authorized users.

& Kylie M. Gray

[email protected]

1 Centre for Developmental Psychiatry and Psychology,

Department of Psychiatry, School of Clinical Sciences,

Monash University, Notting Hill, VIC, Australia

2 Centre for Developmental Psychiatry and Psychology, Early

in Life Mental Health Services, Monash Medical Centre, 246

Clayton Rd, Clayton, VIC 31768, Australia

1 3

J Autism Dev Disord

DOI 10.1007/s10803-016-2734-4

http://dx.doi.org/10.1007/s10803-016-2734-4http://crossmark.crossref.org/dialog/?doi=10.1007/s10803-016-2734-4&domain=pdfhttp://crossmark.crossref.org/dialog/?doi=10.1007/s10803-016-2734-4&domain=pdfhttp://dx.doi.org/10.1007/s10803-016-2734-4


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high in females (.88–.93) and children under age 4 (.90–98),

although specificity in both groups remained low (.51–.76

and .40–.53). Most children did not meet the DSM-5 criteria

based on insufficient Social communication and social

interaction (Social-Communication) symptoms. As such, the

authors argued that their findings support the DSM-5

Restricted, repetitive patterns of behaviour, interests, or

activities (RRB) domain requirements.Although the findings mitigated concerns regarding

DSM-5 sensitivity, the results may partially reflect the

subdomain cut-offs selected. An ADI-R/ADOS coding of 1

may not always indicate a clinically significant impair-

ment. When only a code of 1 on any ADOS or ADI-R item

is required as evidence for a DSM-5 subdomain, more

children without ASD may be incorrectly classified,

resulting in reduced specificity. As such, more stringent

subdomain cut-offs may need to be considered to capture

clinically significant impairments best differentiating those

with and without ASD.

Using a similar methodology, Kent et al. (2013) exploredthe impact of various subdomain cut-offs to develop a DSM-

5 ASD algorithm for the Diagnostic Interview for Social and

Communication Disorders (DISCO; Leekam et al. 2002).

An 85-item algorithm that mapped onto DSM-5 criteria was

developed and tested on two separate samples of children

aged 2–12 years with or without PDD. Optimal sensitivity

(.85–1.0) and specificity (.74–.89) was obtained using a

Social-Communication subdomain cut-off of 3 for subdo-

main A1 (deficits in social-emotional reciprocity), 1 for

subdomain A2 (deficits in nonverbal communicative beha-

viours used for social interaction) and 3 for subdomain A3

(deficits in developing, maintaining and understanding

relationships), together with RRB subdomain cut-offs of 1

for two of the four RRB subdomains. Good sensitivity and

specificity was reported across ability levels.

More recent work identified DISCO items that best dif-

ferentiated children (aged 2.8–11.7) with and without ASD

(e.g. intellectual disability, language impairment) according

to the DSM-5 (Carrington et al. 2014). The most discrimi-

nating items were largely within the Social-Communication

domain, particularly socio-emotional reciprocity items.

Within the RRB domain, sensory behaviour items best dis-

criminated between groups. The 54-item algorithm produced

sensitivity and specificity comparable to the 85-item algo-

rithm. The larger number of DISCO items available may

have enabled better discrimination between those with and

without ASD when compared previous studies (Huerta et al.

2012), however replication is necessary.

DSM-5 Diagnoses in Early Childhood

The majority of studies include broad age ranges, which

may miss important differences in symptom presentation

between age groups. The importance of early identification

and intervention highlights the need for research specifi-

cally applying the DSM-5 criteria to young children.

A study of 180 children under age 5 reported that most

children with a DSM-IV PDD diagnosis (96.88 %) would

meet criteria for ASD according to the published DSM-5

diagnostic criteria (Sumi et al. 2014). Diagnoses were

based on reviewing assessment records of intellectualfunctioning, child observations, an initial parent interview

and semi-structured parent interview (Pervasive Develop-

mental Disorders Autism Society Japan Rating Scale).

However, the Social-Communication domain was consid-

ered as a whole, rather than symptoms in all three subdo-

mains, as specified in the DSM-5.

In contrast, a larger study reviewing the case files of

2721 children aged 1–3 years suggested that diagnostic

changes may significantly impact toddlers (Matson et al.

2012). DSM-IV and DSM-5 diagnoses were based on

judgement by an experienced psychologist reviewing

M-CHAT scores (Robins 2001) and the Battelle Develop-mental Inventory developmental profiles (BDI-2; Newborg

2005). Of the 795 toddlers diagnosed with DSM-IV

Autistic Disorder or PDD-NOS, 52.20 % (n = 415) also

met DSM-5 criteria for ASD. Symptom severity was then

assessed based on a parent-completed measure of ASD

symptoms (BISCUIT-Part 1; Matson et al. 2009). Based on

the BISCUIT-Part 1 scores, parent-reported ASD symptom

severity was significantly higher in children who met the

DSM-5 ASD diagnostic criteria compared to children who

met DSM-IV but not DSM-5 diagnostic criteria. However,

both groups displayed significant impairments when com-

pared to those with no PDD/ASD diagnosis. As such, the

authors argued that children with PDD may still require

intervention even though they may not meet DSM-5 ASD

criteria. However, as diagnoses were only based on infor-

mation obtained from a brief screening tool and develop-

mental profiles, it is unlikely there was sufficient

information to reliably diagnose children according to

either DSM-IV or DSM-5.

Another study evaluated the sensitivity and specificity of

DSM-5 ASD classifications in 422 children under age

4 years (Barton et al. 2013). Using a similar methodology

to Huerta et al. (2012), ADI-R and ADOS items were

mapped onto the proposed DSM-5 criteria. As item map-

pings differed between the two research groups, analyses

were also completed using mapping by Huerta et al.

(2012). Sensitivity and specificity differed based on the

mappings used, the subdomain cut-offs summing ADI-R/

ADOS codes and the domain requirements that either

matched or modified the proposed DSM-5 criteria. Using

the proposed DSM-5 criteria and the subdomain cut-off of

1 on any ADI-R/ADOS item as defined by Huerta et al.

(2012), sensitivity ranged from .84 to .86 while specificity

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ranged from .41 to .55. Altering subdomain-level cut-offs

based on Receiver Operating Characteristic (ROC) curves

increased specificity (.94), but reduced sensitivity (.72–

.77). Optimal sensitivity (.93) and specificity (.74) was

obtained by reducing the DSM-5 Social-Communication

requirements to two subdomains and the RRB requirements

to one subdomain. The study did not examine variables that

differentiated children who did and did not meet the DSM-5 diagnostic criteria for ASD. As such, it is not known

whether they differed according to features such as

chronological age, gender, adaptive functioning or devel-

opmental level.

The Role of Chronological Age, Gender, Cognitive

Ability and Adaptive Behaviour Skills

A variety of studies examining the role of chronological

age and gender have typically found that children with

PDD, who did not meet DSM-5 criteria, did not signifi-

cantly differ from those who did meet DSM-5 criteria onchronological age or gender (Gibbs et al. 2012; Matson

et al. 2012; McPartland et al. 2012; Taheri and Perry 2012;

Turygin et al. 2013; Mayes et al. 2014).

However, cognitive ability may impact whether children

with DSM-IV PDD meet the DSM-5 diagnostic criteria for

ASD. In samples with broad age ranges, children with PDD

who did not meet DSM-5 criteria had, on average, higher

cognitive abilities compared to those who met the DSM-5

criteria (Mayes et al. 2014; Taheri and Perry 2012; Taheri

et al. 2014). Similarly, both Mattila et al. (2011) and

McPartland et al. (2012) reported that fewer children with

an IQ above 70 received a DSM-5 diagnosis of ASD

compared to children with lower cognitive abilities

(IQ\ 70).

Adaptive behaviour skills may also differ between

children with and without DSM-5 ASD. Taheri et al.

(2014) reported that 45 % of children did not meet DSM-

5 ASD criteria, displaying significantly higher adaptive

and cognitive abilities compared to children who did

meet DSM-5 criteria. However, the small sample

(n = 22), broad age range (5–19 years) and diagnostic

process based file reviews of clinical notes and ratings

from the Childhood Autism Rating Scale (CARS;

Schopler et al. 1988) limit the applicability of the find-

ings. Nevertheless, this pattern of results has also been

reported in toddlers (Turygin et al. 2013). Toddlers aged

17–36 months (n = 2054) with DSM-IV PDD who did

not meet DSM-5 diagnostic criteria displayed greater

adaptive, personal-social, motor abilities than those who

met DSM-5 criteria. This sample was a subset of toddlers

from an earlier study (Matson et al. 2012), and as pre-

viously noted, the measures used to inform diagnosis

were limited.

Although young children with a DSM-5 diagnosis may

represent a more functionally impaired group (Turygin

et al. 2013), limitations of current research indicate the

need for further research to examine the role of age, gen-

der, cognitive ability, and adaptive behaviour skills in

diagnosing young children with ASD according to DSM-5

criteria.

Summary and Current Study

Overall, studies to date provide some evidence supporting

concerns that some young children may be vulnerable to no

longer meeting the ASD diagnostic criteria, with some

suggesting modification of the DSM-5 criteria to improve

sensitivity. However, results across studies are mixed and

should be interpreted with caution. Subtle differences

between the draft and final DSM-5 criteria for ASD

regarding the phrasing of symptoms may have impacted

findings. Differences across studies may also reflect the

varying sample characteristics and range of methodologiesused, along with processes and methods for making diag-

noses, particularly in the application of the DSM-5 criteria

and diagnostic classification. Furthermore, studies have

typically included broad age ranges; however, particular

attention needs to be given to the application of the DSM-5

to young children. Studies specifically assessing young

children have been limited and further investigation of the

characteristics of children who do not meet DSM-5 criteria

is required.

This study therefore aimed to investigate the impact of

the published DSM-5 criteria on diagnostic classifications

of ASD in young children. The role of gender, chrono-

logical age, developmental level, language delay, adaptive

behaviour skills and co-morbid behaviour and emotional

problems were also examined in relation to agreement

across the two sets of DSM criteria.

Methods

Participants

This study was granted approval from the Monash

University Human Research Ethics Committee. Partici-

pants were recruited between 2003–2005 through regions

of Melbourne, Australia which consisted of a variety of

social classes and ethnic groups (Gray et al. 2008b). Par-

ticipants were referred through governmental/non-govern-

mental early childhood services and paediatricians in the

southern, western and northern regions of Melbourne, and a

public regional autism assessment programme in the

southern region of Melbourne. Families were invited to

participate if their child was 18–48 months of age and had,

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or was suspected to have developmental delay (suspected

autism was not a requirement).

Participants were aged 18–48 months when recruited

and aged 20–55 months of age at the time of assessment.

Informed consent was obtained from the participant’s

parent/caregiver prior to the assessment. The sample con-

sisted of 185 young children. The DSM-IV PDD (APA

2000) group (n = 126) included those with either AutisticDisorder (n = 103) or PDD-NOS (n = 23). Developmen-

tal delay was present in 91.74 % (n = 111) of children in

the PDD group. Comorbid diagnoses were given for four

children in the PDD group (Mixed Receptive-Expressive

Language Disorder, n = 1; Expressive Language Disorder,

n = 1; Attention Deficit Hyperactivity Disorder, n = 2.).

The non-PDD group (n = 59) was a heterogeneous group

that consisted of children with Mixed Receptive-Expres-

sive Language Disorder (n = 17), Expressive Language

Disorder (n = 4) or no DSM-IV clinical diagnosis

(n = 38; Axis 1 or 2). Developmental delay was present in

66.10 % (n = 39) of the non-PDD group. Sample charac-teristics are described in Table 1. The PDD and non-PDD

groups significantly differed in terms of gender, v2(1,

N = 185) = 7.8, p\ .01, adaptive behaviour skills,

t (182) = 5.30, p\ .001 and developmental level,

t (183) = 6.49, p\ .001.

Measures

Autism symptoms were assessed using the ADI-R (Rutter

et al. 2003) and ADOS (Lord et al. 2000, 2001). ADOS

modules were administered according to expressive lan-

guage ability (Module 1 n = 171; Module 2 n = 14).

Developmental level was assessed using either the Wech-

sler Preschool or Primary Scale of Intelligence (WPPSI-III;

Wechsler 2002) or the Psychoeducational Profile-Revised

(PEP-R; Schopler et al. 1990). The PEP-R has good

internal consistency (a = .85–.98) and is correlated with

another measure of nonverbal intelligence (Steerneman

et al. 1997). Inter–rater reliability of the PEP-R has been

established (Schopler et al. 1990). Developmental level

was calculated using the WPPSI-III Full Scale IQ (n = 6)

or PEP-R developmental quotient (n = 179), a ratio of

developmental age to chronological age. Children were

identified as having a developmental delay if their devel-

opmental age was 6 months or more below their chrono-

logical age. Adaptive behaviour skills were assessed usingthe Vineland Adaptive Behavior Scales (VABS) survey

form (Sparrow et al. 1984). The Adaptive Behavior Com-

posite (ABC) provides a standardised score of overall

adaptive skills. The Reynell Developmental Language

Scales (RDLS-III) were used to assess expressive and

receptive language abilities (Edwards et al. 1997). Children

were identified as having a language delay if their

expressive or receptive abilities were 6 months or more

below their chronological age.

The Developmental Behaviour Checklist Primary Carer

version (DBC-P) was used to assess child behavioural and

emotional problems (Einfeld and Tonge 2002). Par-ents/caregivers rate items on a scale of 0–2, with higher

scores indicating greater behaviour and emotional prob-

lems. Items are summed, providing a Total Behaviour

Problems Score (TPBS). For the purposes of this study,

items from the DBC-Early Screen (DBC-ES), an autism

screening tool (Gray and Tonge 2005), were removed from

the TPBS prior to analyses to assess behaviour problems

independent of autism symptomatology. Scores were then

divided by the number of contributing items to calculate

Mean Item Scores (MIS; Taffe et al. 2008).

Procedure

Consensus DSM-IV diagnoses (APA 2000) were given by

psychologists experienced in the assessment and diagnosis

of autism and developmental disorders (Gray et al. 2008a,

b). DSM-5 classifications were based on item assignments

from the ADOS and ADI-R, a method utilised in other

Table 1 Sample characteristics

according to DSM-IV

classification

PDD

Mean (SD) (n = 126)

Non-PDD

Mean (SD) (n = 59)

Total

Mean (SD) ( N = 185)

Males [n (%)] 112 (88.89 %)* 42 (71.19 %) 154 (83.24 %)

Age in months 37.90 (6.96) 39.33 (7.77) 38.36 (7.24)

Age range in months 22.24–55.36 20.53–55.82 20.53–55.82

Developmental level 56.81 (20.20) 76.09 (15.45)^ 62.96 (20.82)

Developmental level range 14.49–139.45 45.77–106.29 14.49–139.45

Language delay [n (%)] 121 (96.03 %) 56 (94.92 %) 177 (95.68 %)

Vineland ABC 62.00 (12.05) 71.88 (11.27)^ 65.12 (12.65)

DBC-P total problem behaviour 0.47 (0.26) 0.42 (0.27) 0.45 (0.26)

* p\ .01

^ p\ .001

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studies (Barton et al. 2013; Huerta et al. 2012; Mazefsky

et al. 2013). Individual ADOS and ADI-R items were

assigned to each of the DSM-5 ASD subdomains, guided

by the procedures of two other studies (Barton et al. 2013;

Huerta et al. 2012), in conjunction with the published

DSM-5 diagnostic criteria (APA 2013). The ADOS and

ADI-R item assignments were completed independently

and then compared to the item assignments completed byBarton et al. and Huerta et al. With the exception of one

ADI-R item (item 51 relating to social smiling); all item

assignments used in the present study were consistent with

those used by Huerta et al.

Where the rationale for assignments was unclear, further

information was sought from the study authors. Item

assignments for the present study are available in the

Appendices of ESM. Each item only contributed to one

DSM-5 subdomain and not all items were assigned. ADI-R

and ADOS item codes ranged from 0 to 2, following

standard conversions of 3’s to 2’s and 8’s to 0’s (Lord et al.

2001; Rutter et al. 2003). Codes of 0 indicated the absenceof a subdomain symptom while codes of 1 or 2 indicated

the presence of a subdomain symptom. Codes contributing

to each DSM-5 subdomain were summed based on infor-

mation from the ADI-R alone, followed by combining the

ADI-R and ADOS. Classifications based on the ADOS

alone were not possible due to the lack of items relevant to

three subdomains.

The total points required as evidence for each DSM-5

subdomain impact sensitivity and specificity. As such, cut-

offs of 1 and 2 for each subdomain were evaluated, with a

cut-off of 2 consisting of at least two scores of 1 or one

score of 2. Consistent with final DSM-5 criteria, an ASD

diagnosis required all three Social-Communication subdo-

mains and two of the four RRB subdomains. The present

study did not have sufficient information to classify chil-

dren with DSM-5 Social Communication Disorder.

Statistical Analyses

Sensitivity and specificity calculations were completed

using DAG-Stat (Mackinnon 2000). Further analyses were

completed using Stata Version 13. Regression analyses

assessed whether children with PDD who did not meet

DSM-5 criteria (false negatives) differed from those with

PDD who met DSM-5 criteria (true positives) according to

chronological age, developmental level, adaptive beha-

viour skills, and behaviour and emotional problems. For

categorical variables (gender, language delay), Fisher’s

exact tests were used due to the small sample sizes in each

group. Comparisons were made based on DSM-5 classifi-

cations using a cut-off of 2 points from the ADI-R or the

ADOS as evidence for each subdomain. This cut-off was

selected as a code of 2 may indicate a clinically significant

impairment and ASD assessments ideally utilise informa-

tion from both parent report and child observations.

Results

DSM-5 classifications were based on ADI-R information

alone followed by combining the ADI-R and ADOS. Asshown in Table 2, sensitivity ranged from .95 to .96 and

specificity ranged from .31 to .36 when a code of 1 on any

assigned item was required to meet each subdomain.

Increasing the cut-off to 2 points to meet each subdomain

decreased sensitivity (.76–.84) and improved specificity

(.54–.61). Modifying the DSM-5 criteria produced partic-

ularly high sensitivity (.97) when the required RRB domain

criteria were reduced from two to one, but specificity was

still problematic (.41).

When using information from both the ADI-R and

ADOS and a cut-off of 2 for each subdomain, 20 children

(15.87 %) with PDD did not meet the DSM-5 criteria.Seven of the 23 children (30.43 %) with PDD-NOS did not

meet DSM-5 criteria compared to 13 of the 103 children

(12.62 %) with Autistic Disorder. One child did not meet

either domain criteria while 16 (80 %) did not meet the

RRB domain criteria. Fifteen of the 16 who had insufficient

RRB symptoms only had RRB symptoms on subdomain

B1 (stereotyped or repetitive motor movements, use of

objects, or speech).

Table 3 shows the true positive, false positive, true

negative, and false negative rates. Children with PDD who

did not meet the DSM-5 diagnostic criteria for ASD (false

negatives) had significantly lower DBC-P scores than

children correctly classified with ASD under the DSM-5

(true positives). However, false negatives and true positives

did not significantly differ in chronological age, develop-

mental level, adaptive behaviour skills (see Table 4) or

according to gender ( p = .24, Fisher’s exact test) or lan-

guage delay ( p = 1.00, Fisher’s exact test).

Discussion

This study assessed the sensitivity and specificity of the

DSM-5 in young children with PDD or developmental

delay. Overall, the number of children with PDD who did

not meet DSM-5 (APA 2013) ASD criteria ranged from

4.76 to 23.81 %. The results generally indicated good

sensitivity (.76–.96); however, this was at the expense of

specificity. As expected, sensitivity was high (.95–.96) and

specificity poor (.31–.36) when using a liberal cut-off for

subdomains. Barton et al. (2013) reported slightly lower

sensitivity and improved specificity, which may be a result

of differing item assignments and significantly younger

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participants than in the current study (t = 26.24, df = 605,

p\ .0001). Nevertheless, the lower specificity was broadly

consistent with other studies using this method (Huerta

et al. 2012; Barton et al. 2013). As Barton et al. (2013)

observed, an ADOS/ADI-R code of 1 does not necessarily

indicate a clinically significant impairment. Childrenwithout ASD may display symptomology and receive

codes of 1 on some items. As such, a more stringent cut-off

of 2 was also evaluated, improving specificity (.54–.61).

The inevitable trade-off between sensitivity and speci-

ficity presents an ongoing challenge in the ASD diagnostic

process. Some researchers have argued for the DSM-5

criteria to be modified due to sensitivity concerns (e.g.

Barton et al. 2013; Gibbs et al. 2012; Mayes et al. 2013)

whilst others have indicated support for the more stringent

criteria (Kent et al. 2013; Huerta et al. 2012). In the present

study, optimal sensitivity (.97) was obtained by modifying

the RRB domain criteria, reducing the required subdomains

from two to one. This result is unsurprising given that the

majority with PDD who did not meet DSM-5 criteria

(66.7–80.0 %) had insufficient symptoms on the RRBdomain, typically displaying only subdomain B1 symp-

tomatology (stereotyped or repetitive motor movements,

use of objects or speech).

These findings may reflect the presentation of RRBs in

young children with autism. Repetitive use of objects,

hand/finger mannerisms and unusual sensory interests are

common in younger children with autism or developmental

delay (Richler et al. 2007; Mooney et al. 2006). RRBs such

as compulsions and rituals, difficulties with changes in

Table 2 Sensitivity and Specificity of the published and modified DSM-5 Autism Spectrum Disorder criteria

Measure Domain

criteria

Symptom

cut-off

Sensitivity

(95 % CI)

Specificity

(95 % CI)

Efficiency

(95 % CI)

Positive predictive

value

Negative predictive

value

DSM-5

ADI-R 3 SC, 2 RRB 1 .95 (.90–.98) .36 (.24–.49) .76 (.69–.82) .76 (.69–.82) .78 (.58–.91)

ADI-R 3 SC, 2 RRB 2 .76 (.68–.83) .61 (.47–.73) .71 (.64–.78) .81 (.72–.87) .55 (.42–.67)

ADI-R/ADOS 3 SC, 2 RRB 1 .96 (.91–.99) .31 (.19–.44) .75 (.68–.81) .75 (.67–.81) .78 (.56–.93)ADI-R/ADOS 3 SC, 2 RRB 2 .84 (.77–.90) .54 (.41–.67) .75 (.68–.81) .80 (.72–.86) .62 (.47–.75)

Modified RRB

ADI-R/ADOS 3 SC, 1RRB 2 .97 (.92 –.99) .41 (.28–.54) .79 (.72–.85) .78 (.70–.84) .86 (.67–.96)

Modified SC

ADI-R/ADOS 2 SC, 2 RRB 2 .87 (.79–.92) .41 (.28–.54) .72 (.65–.78) .76 (.68–.82) .59 (.42–.74)

Modified both

ADI-R/ADOS 2 SC, 1 RRB 2 1.00 .15 (.07–.27) .73 (.66–.79) .72 (.64–.78) 1.00

RRB = restricted, repetitive patterns of behaviour, interests, or activities domain; SC = social communication and social interaction domain

Table 3 DSM-5 Autism Spectrum Disorder classifications: False positive, false negative, and true positive rates

Measure Domain criteria Symptom cut-off PDD [n (%)] Non-PDD [n (%)]

True positives False negatives True negatives False positives

DSM-5

ADI-R 3 SC, 2 RRB 1 120 (95.24 %) 6 (4.76 %) 21 (35.59 %) 38 (64.41 %)

ADI-R 3 SC, 2 RRB 2 96 (76.19 %) 30 (23.81 %) 36 (61.02 %) 23 (38.98 %)

ADI-R/ADOS 3 SC, 2 RRB 1 121 (96.03 %) 5 (3.97 %) 18 (30.51 %) 41 (69.49)

ADI-R/ADOS 3 SC, 2 RRB 2 106 (84.12 %) 20 (15.87 %) 32 (54.24 %) 27 (45.76 %)

Modified RRB

ADI-R/ADOS 3 SC, 1RRB 2 122 (96.83) 4 (3.17) 24 (40.68 %) 35 (59.32 %)

Modified SC

ADI-R/ADOS 2 SC, 2 RRB 2 109 (86.51 %) 17 (13.50 %) 24 (40.68 %) 35 (59.32)Modified Both

ADI-R/ADOS 2 SC, 1 RRB 2 126 (100 %) 0 (0 %) 9 (15.25 %) 50 (84.75 %)

RRB = restricted, repetitive patterns of behaviour, interests, or activities domain; SC = social communication and social interaction domain

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routine, and resistance to trivial changes in the environ-

ment are less commonly endorsed in young children

whether they have autism or not (Richler et al. 2007),

however, they increase with age (Richler et al. 2010). As

such, young children with autism may not yet display

significant symptomatology across more than one RRB

subdomain.

The current study also examined the characteristics of

children with PDD who did not meet the DSM-5 diagnostic

criteria for ASD. Children without DSM-5 ASD had sig-nificantly lower rates of parent reported behavioural and

emotional problems than children correctly classified with

DSM-5 ASD. Consistent with previous studies, the current

findings suggest that gender and chronological age do not

appear to differentiate children with PDD who did not meet

the DSM-5 ASD criteria (Gibbs et al. 2012; McPartland

et al. 2012; Matson et al. 2012; Taheri and Perry 2012;

Mayes et al. 2014; Turygin et al. 2013). However, given

the smaller number of females in these studies, gender

differences may be more difficult to detect. Contrary to

research in older samples (Mattila et al. 2011; Mayes et al.

2014; McPartland et al. 2012; Taheri and Perry 2012;Taheri et al. 2014), the developmental level of children

with PDD who did not meet the DSM-5 criteria was not

significantly different from that of children who met the

criteria. In addition, children were not differentiated by

language delay or adaptive behaviour skills.

Overall, it is concerning that a proportion of children

with PDD less than 5 years of age may not meet the DSM-

5 diagnostic criteria for ASD. Without a DSM-5 ASD

diagnosis, children may not have access to early inter-

vention services. Although they may have lower rates of

comorbid behavioural and emotional problems and have

fewer core symptoms according to the DSM-5 configura-tion of ASD, the clinically significant autism symptoms

warranted a PDD diagnosis according to the DSM-IV, thus

indicating the need for intervention services. Furthermore,

the majority of children with PDD that did not meet DSM-

5 ASD criteria had symptoms on all but one of the required

ASD subdomains, indicating deficits across a number of

areas that would warrant intervention.

The low specificity identified in the current study is of

concern as the use of diagnostic criteria with adequate

sensitivity at the expense of specificity may result in a high

number of false positives. However, the low specificity may

reflect the methodology used to classify children with ASD.

Prospective research using best-estimate clinical diagnoses

across the two sets of diagnostic criteria may result in higher

specificity compared to the current study. Furthermore, the

study is limited by the psychometric properties of the

measures used to inform DSM-IV best estimate diagnoses

and classify children according to the DSM-5 ASD criteria

(the ADI-R and ADOS). For example, less than optimalrates of ADI-R sensitivity (.53–.83) and specificity (.67–.72)

in children aged 55 months and under may have contributed

to some loss of sensitivity and specificity in the current study

(e.g. Ventola et al. 2006; Risi et al. 2006; Gray et al. 2008a).

As such, the content of ADI-R may need to be revised to

improve diagnostic sensitivity and specificity in young

children with autism. Overall, the DSM-5 ASD criteria

require further prospective evaluation using best-estimate

diagnoses before the criteria may be endorsed for young

children less than 5 years of age.

The findings nevertheless raise the question of whether the

DSM-IV diagnostic criteria were over-inclusive and whetherthe DSM-5 diagnostic criteria may more accurately diagnose

children with autism. Given that diagnoses are currently

based on behaviour, it is difficult to obtain a consensus among

clinicians regarding the number and severity of symptoms

that should be required to warrant a diagnosis of ASD.

Prospective research is necessary to explore the whether the

DSM-5 ASD criteria best distinguishes between those with

and without ASD in early childhood or whether further

revisions to the criteria are required.

It is important to note that the majority of the current

sample consisted of young children with Autistic Disorder

and other PDD subtypes (e.g. PDD-NOS). As the focus of the study was on young children, the findings cannot be

generalised to older children and adolescents. A further

limitation was that child developmental delay was defined

as a delay in ability (general development and language

abilities) that was 6 months or more below their chrono-

logical age. As such, percentage delay will differ based on

chronological age.

The authors recognise that the psychometric evaluation

of the DSM-5 using the DSM-IV criteria as the baseline is

Table 4 Means and regression coefficients for false negatives and true positives

False negatives (SD) (n = 20) True positives (SD) (n = 106) Regression coefficients (unstandardized)

Age in months 36.33 (7.24) 38.20 (6.90) 1.87

Developmental level 53.68 (16.63) 57.40 (20.83) 3.72

Vineland ABC 64.58 (11.29) 61.54 (12.18) -3.04

DBC-P total problem behaviour 0.36 (0.19) 0.49 (0.27) 0.14*

* p\ .05

J Autism Dev Disord

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inherently problematic. Although the DSM-IV diagnostic

criteria are imperfect, the absence of an alternative gold

standard baseline diagnosis necessitated the use of the

DSM-IV criteria in the current study. The study did not

classify children according to the DSM-IV and DSM-5 in

an equivalent manner. The aim of this study was to

examine retrospective DSM-5 classifications against best

estimate DSM-IV diagnosis and the methodology wasequivalent to that of Barton et al. (2013) and Huerta et al.

(2012), enabling results to be compared across studies.

Participants were retrospectively classified based on ADOS

and ADI-R scores given prior to the development of the

DSM-5. These classifications may not necessarily reflect

DSM-5 diagnoses given by an experienced clinician at the

time of assessment. For example, the ADI-R does assess a

child’s apparent indifference to pain or temperature, listed

as an example symptom under subdomain B4 in the DSM-

5 (American Psychiatric Association 2013). Taken toge-

ther, replication of the findings is required using best-es-

timate diagnoses across the two sets of diagnostic criteria.Assigning items to DSM-5 diagnostic criteria is a dif-

ficult process and assignments may differ between studies

(Huerta et al. 2012; Barton et al. 2013). Furthermore, the

number of ADI-R and ADOS items suitable for each DSM-

5 subdomain was highly variable and fewer items applied

to nonverbal children and children of particular ages. The

greater number of items mapped to the Social-Communi-

cation compared to the RRB domain may have also

impacted the results. Although the study would have ide-

ally had a comparable number of items per subdomain; this

was not possible given the items currently contained in the

ADOS and ADI-R. Although not unique to the DSM-5, the

current method highlights the complexities of opera-

tionalising diagnostic criteria in standardised measures of

symptoms. Given that ASD diagnoses are currently based

on behaviour, improving assessment tools and diagnostic

processes is critical in future research.

Conclusion

The present study is one of the very few DSM-5 studies

focusing specifically on young children less than 5 years of

age. The research addresses a significant gap in the DSM-5

ASD literature and provides new insights into the charac-

teristics of young children with PDD who may not meet the

DSM-5 diagnostic criteria for ASD. The results indicated

good sensitivity and problematic specificity for the DSM-5

ASD criteria in a sample of 185 young children. Children

with PDD who did not meet DSM-5 criteria, on average

had lower comorbid behaviour and emotional problems

and the majority had insufficient symptoms on the RRB

domain. Gender, developmental level, language delay and

adaptive behaviour skills did not significantly impact

DSM-5 classification.

Future studies could examine the impact of comorbid

behaviour and emotional problems on DSM-5 sensitivity

and specificity in older children and adolescents with aut-

ism. The impact of modifying the DSM-5 criteria on sen-

sitivity and specificity also needs to be investigated in

children across a range of developmental levels. Overall,prospective field trials comparing best-estimate DSM-IV

and DSM-5 diagnoses following diagnostic evaluations for

autism are necessary to advance research in this area.

Examining the possible reasons for any discrepancies may

guide future revisions to the DSM and revisions to diag-

nostic instruments such as the ADOS and ADI-R to enable

better differentiation between those with and without ASD.

Acknowledgments This study utilised data collected as part of a

project funded by the National Health and Medical Research Council

of Australia, awarded to A/Prof Kylie Gray and Prof Bruce Tonge.

The authors thank the families who participated in the project and the

research team who assisted with data collection—Deborah Sweeney,Dr Helen Jeges, Caroline Keating, Dr Erin Mooney, and Dr Sally

Herring. A preliminary version of the paper was orally presented at

the Australasian Society for Autism Research (ASfAR) Conference,

Bundoora, Australia in December 2014.

Author Contributions JAC contributed to the coordination of the

study, completed statistical analyses with JT and drafted the manu-

script; KMG designed and coordinated the study, acquired the orig-

inal data, and participated in the writing of the manuscript; JT

performed the statistical analyses; BJT participated in the data col-

lection and design of the study, and reviewed the manuscript. All

authors read and approved the final manuscript.

Funding The collection of the data used in this study was funded by

the National Health and Medical Research Council of Australia

(Project Number 236834), awarded to Kylie M. Gray and Bruce J.

Tonge.

Compliance with Ethical Standards

Conflict of interest The authors declare that they have no conflict

of interest.

Ethical Approval This study was granted approval from the

Monash University Human Research Ethics Committee. All proce-

dures performed in studies involving human participants were in

accordance with the ethical standards of the institutional and/or

national research committee and with the 1964 Helsinki declaration

and its later amendments or comparable ethical standards. This articledoes not contain any studies with animals performed by any of the

authors.

Informed Consent Informed consent was obtained at the time of

assessment from all parents of participants included in the study.

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asd in the dsm5 sensibilidade e especificidade diagnostica na infancia

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