describes the sample of 78 children at their first assessment. As stated earlier, 48 were judged clinically to be ASD on one or more occasions, and 30 were not. “Never ASD” children were seen on average 5.4 times over 20.5 months and the “ever ASD” group 6.8 times over 20.5 months. As shown in , “ever ASD” and “never ASD” classes did not differ in proportion of males, number of observations or age at baseline, but “ever ASD” children were older at final assessments, t (76) = 2.83, p <0.01. “Ever ASD” participants had higher ADOS Social Affect scores, t (76) = 5.76, p <0.01; ADOS RRB scores, t (76) = 3.66, p <0.05; total ADOS algorithm scores, t (76) = 6.66, p <0.001; clinician diagnostic probability ratings, t (76) = 11.33, p <0.001; and all ADI-R domain scores, t (76) ≥ 4.86, p <0 .01, as well as lower Verbal IQs, t (76) = 2.05, p<.05. There were no significant class differences for nonverbal IQs or MSEL language age equivalents. displays ADOS total algorithm score histories.
ADOS Total Algorithm Score Trajectories for “Ever ASD” and “Never ASD” Children
Using the minimum BIC as the selection criterion, the best trajectory typology was a model with four classes that varied in intercepts and linear slopes, as shown in . displays the ADOS histories and fitted mean trends for these four classes. The average probabilities for being assigned to the most likely class were high, being 0.94 for class 1 (severe persistent ~ 21% of sample), 0.87 for class 2 (worsening ~ 21%), 0.84 for class 3 (improving ~ 19%), and 0.99 for class 4 (nonspectrum ~ 40%). Confirming the validity of this categorization, the last class included all children who had never received an ASD diagnosis at any point and one child who had received an ASD diagnosis only once.
Trajectory Model BIC scores for parsimonious fit
ADOS Total Algorithm Score Trajectories for Four Empirically Derived Classes
displays the ADOS SA and RRB histories and mean trends for the four classes. Marginal regression models confirmed our labeling of the severe persistent class, with there being no significant evidence of change over time in either SA or RRB. Among the worsening class, both SA (p=0.012) and RRB (p=0.001) increased (became more abnormal) over time. Among the improving class, while SA decreased (p<0.001), the RRB score showed little evidence of improvement (p=0.176). Within the nonspectrum class, there was a marginal decrease in SA (p=0.058) but not RRB (p=0.904).
ADOS Scores for Four Trajectory Classes: Social-Affect and Restricted, Repetitive Behaviors
Baseline ADOS domain scores discriminated among all four classes (SA χ2(3)=56.48, p<0.001; RRB χ2(3)=28.12, p<0.001) and among the three ASD classes alone (SA χ2(2)=15.15, p<0.001; RRB χ2(2)=12.25, p=0.002). Compared to the persistent class, those in the worsening class started significantly lower (less abnormal) on SA (p=0.002) and on RRB (p=0.003) and the improving class started marginally lower on SA (p=0.054), though similar on RRB (p=0.228).
In contrast, taking the final observation for each child, compared to those in the persistent class, those in the improving class scored 8.10 points lower (less abnormal) on SA (p<0.001) and 2.74 points lower on RRB (p=0.002). Those in the worsening class had scores that were still not yet as severe as the persistent class for either SA (3.18 points lower, p=0.006) or RRB (1.5 points lower, p=0.05).
We examined the association of class membership with a variety of factors and covariates. and show class demographics and means for a variety of measures. The classes did not differ by gender, χ2(3)=2.02, p=0.567, nor maternal education, χ2(3)=3.56, p=0.313, referral status, χ2(6)=5.24, p=0.513, (clinic non-sibling/sibling/control) nor with ADI-R report of any regression, χ2(3)=6.91, p=0.075. All three baseline ADI-R domain scores were strongly associated with ASD vs non-ASD class membership (social χ2(3)=33.26, p<0.001; nonverbal communication χ2(3)=13.40, p=0.004; repetitive χ2(3)=18.23, p<0.001), but did not discriminate among the three ASD trajectory classes when the nonspectrum class was excluded (social χ2(2)=3.24, p=0.198; nonverbal communication χ2(2)=2.44, p=0.295; repetitive χ2(3)=1.37, p=0.503).
Demographics by ADOS trajectories
Means and Standard Deviations for Trajectory Diagnoses
Similarly, ASD vs non-ASD children, irrespective of trajectory, differed in whether they had ever received any treatment after 24 months (ASD trajectory groups ranged from 77 –100% of participants; non-ASD 50%; χ2(3) = 7.25, p = .046), but not whether they had received ABA (ASD trajectory groups ranged from 14 – 27% vs no non-ASD; χ2(3) = 2.35, p = 0.67). All ASD trajectory groups, when combined, received more treatment hours than the non-ASD group, t (44) = −1.87, p = 0.07, but there were no differences among ASD trajectory groups.
Relatively large mean differences were accompanied by substantial variation. Half of the nonspectrum group did not receive any treatment; the three ASD groups, 77% (worsening), 80% (persistent) and 100% (improving), received at least some treatment, χ2(3)=7.25, p=0.046. There was no difference among the three ASD groups, χ2(2) = 3.55, p =.17. There were no significant differences in the proportion of children who received at least five hours a week of ABA beginning sometime before 30 months (27% persistent, 15% worsening, 14% improving, and 0% nonspectrum), exact p’s = 0.67). The large variability in the hours of treatment received after 24 months meant that the differences between groups remained non-significant, F (3.44) = 1.12 p = 0.35. Thus overall, there was no association between treatment and trajectory.
Though not significantly different, more of the children in the severe-pervasive group received ABA (27%) vs the other two ASD groups (15% and 14%), with little difference in absolute number of hours of treatment across the three ASD groups.
We examined the trajectories of the cognitive scores for which we had repeated measures over the same period. shows the histories for estimated verbal and nonverbal IQs. Differences by class in linear trend were found for verbal IQ, F(3.77)=5.26, p=0.002, but not nonverbal IQ, F(3.77)=2.03, p=0.116.
IQ Changes for Four Trajectory Classes: Nonverbal and Verbal
For nonverbal mental age, F(3.77)=3.36, p=0.023, the improving group showed increases in scores more quickly than the persistent group, while for verbal mental age, F(3.77)=8.28, p<0.001, the improving and the NS classes increased more quickly than the persistent class. More specifically, there were class differences in time trends in the MSEL expressive and receptive age-equivalents, F(3.77)=5.13, p=0.003; F(3.77)=7.21, p<0.001, with the improving class increasing more rapidly relative to the persistent class in both measures.
Clinicians’ probability-of-diagnosis estimates made after each assessment are depicted according to each trajectory group in . These estimates shared a common trend (trend × class interaction, F (3, 74) = 2.05, p = 0.11) but differed in mean level, F (3, 74) = 80.70, p < 0.001. The severe persistent and nonspectrum trajectory groups differed from each other and differed from the improving and worsening groups, which did not differ from each other.
Changes in Clinician Ratings of Probability of ASD Diagnosis for the Four Trajectory Classes.
For the prediction of final diagnosis we compared the performance of an ADOS algorithm total score from a single assessment with the sum from the two assessments for 57 children where a previous assessment had occurred within three months before the final diagnosis. The second assessment significantly improved prediction (Area-Under-Curve 0.85 vs 0.77, p=0.015).