Abstract
There is limited research in adolescents at risk for psychosis. The new Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition attenuated psychosis syndrome (DSM-5 APS) criteria have not been validated in this group. We conducted a RECORD-compliant, real-world, prospective, 5-year cohort study addressing clinical profile, transition to psychosis, and prognostic accuracy of DSM-5 APS in help-seeking inpatient/outpatient adolescents accessing Children and Adolescent Neuropsychiatric services at IRCCS Mondino Foundation (Pavia, Lombardy, Italy) between 2012 and 2019. About 243 adolescents (31 early-onset psychosis [EOP]; 110 meeting DSM-5 APS criteria, DSM-5 APS; 102 not meeting psychotic or DSM-5 APS criteria, non-APS) were included. At baseline, DSM-5 APS adolescents (aged 15.4 ± 1.6) had on average 2.3 comorbid disorders (higher than EOP/non-APS, P < .001). DSM-5 APS adolescents had an intermediate psychopathological profile between non-APS/EOP (P < .001) and worsen Clinical Global Impression-Severity than non-APS (P < .001). DSM-5 APS functioning was intermediate between non-APS and EOP. 39.1% of DSM-5 APS were treated with psychotropic drugs (average = 64 days); 53.6% received psychotherapy. Follow-up of DSM-5 APS and non-APS groups lasted 33 and 26 months, respectively (median). The cumulative risk of transition at 1–5 years was 13%, 17%, 24.2%, 26.8%, and 26.8% in the DSM-5 APS group, 0%, 0%, 3.2%, 3.2%, and 3.2% in the non-APS group. The 5-year prognostic accuracy of the DSM-5 APS in adolescent was adequate (area under the curve = 0.77; Harrell’s C = 0.736, 95%CI 0.697–0.775), with high sensitivity (91.3%) and suboptimal specificity (63.2%). The DSM-5 APS diagnosis can be used to detect help-seeking adolescents at risk of psychosis and predict their long-term outcomes. Future research should consolidate these findings.
Keywords: psychosis, schizophrenia, CHR-P, risk, attenuated psychotic symptoms, prevention, adolescence
Introduction
One of the most promising strategies to improve outcomes for psychotic disorders is represented by preventive approaches in individuals at clinical high risk for psychosis (CHR-P) (termed “primary indicated prevention”).1,2 The first-rate limiting step for effective prevention of psychosis is the detection of individuals at risk3 through psychometric criteria validated internationally4: attenuated psychotic syndrome (APS), brief intermittent psychotic symptoms (BLIPS), and genetic risk and deterioration syndrome (GRD).5 These three CHR-P subgroups are characterized by different clinical outcomes.6 Given that the attenuated psychosis symptoms subgroup represents most (85%) CHR-P cases, a new clinically based (ie, non-psychometric) attenuated psychosis syndrome diagnosis has been introduced in the Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition (DSM-5) to further facilitate large scale detection7(DSM-5 APS hereby).8 Despite these progresses, there is only limited knowledge in underage CHR-P populations, with inconclusive and contrasting findings.9,10 Converging evidence indicates that risk factors for psychosis accumulate in these individuals, during the early neurodevelopmental phases, thus increasing the chances of transitioning to psychosis and of associated multiple comorbidities, impaired quality of life, suicidal behaviors, poor functioning, and healthcare burden.11–14 Conducting research in CHR-P adolescents is particularly challenging. For example, clinical utility of the new DSM-5 APS in children and adolescents has been explicitly tested only in small-scale baseline studies (n = 21).15 While the DSM-5 APS prognostic accuracy was acceptable (area under the curve [AUC] 0.76 at 24 months) and similar to CHR-P psychometric instruments in adult help-seeking samples,15 its prognostic accuracy in underage samples is currently unknown.
The present real-world prospective cohort study addresses these gaps by including a large and long-term follow-up cohort of adolescents ever ascertained clinically on the DSM-5 (and psychometrically on the CHR-P) criteria. The aims of this study were to (1) characterize the profile of DSM-5 APS adolescents, at presentation, compared with adolescents suffering from early-onset psychosis (EOP) and with other psychiatric disorders and (2) to estimate their long-term risk of transition to psychosis and prognostic accuracy of DSM-5 APS.
Methods
Design
This clinical register-based prospective cohort study was conducted according to the REporting of studies Conducted using Observational Routinely collected health Data (RECORD) statement (see supplementary table S1). The study has received ethical approval from the local ethics committee and was carried out in accordance with the Declaration of Helsinki.
Study Population
All help-seeking adolescents aged 12–17 years, consecutively admitted to the Child and Adolescent Neuropsychiatric inpatient and outpatient units of IRCCS Mondino Foundation (Pavia, Lombardy, Italy) between October 2012 and July 2019, were eligible to be recruited in this study. These are tertiary-level healthcare facilities that assess only adolescents referred by secondary mental healthcare services located in the local community or primary care. We then applied the following exclusion criteria: (i) previous history of any DSM-5 psychotic disorder, (ii) head injuries or any other underlying medical/neurological condition, (iii) current DSM-5 illicit substance dependence or illicit substance-induced mental disorders, (iv) the presence of BLIPS (the Comprehensive Assessment of At-Risk Mental States [CAARMS] was administered to identify this exclusion criterion16–19). Once participants and their legal guardians provided written consent, study enrollment was confirmed.
Participants were then divided into three groups: (i) adolescents with established EOP, (ii) adolescents meeting DSM-5 APS criteria (fully detailed in the supplementary methods S1),7 ascertained clinically by the child and adolescent psychiatrists who were consenting participants, (iii) adolescents with other DSM-5 psychiatric disorders who did not meet APS/EOP criteria (non-APS hereby). The CAARMS was not used to define the three groups.
Study Measures
Baseline Variables
Upon study entry, all participants underwent a comprehensive assessment (which is fully detailed in the supplementary methods S1) evaluating:
(i) sociodemographic characteristics;
(ii) family history of any DSM-5 psychiatric disorders;
(iii) personal history of any DSM-5 psychiatric disorders;
(iv) psychopathological assessment;
(v) level of functioning.
Follow-Up
Follow-up of non-APS and DSM-5 APS adolescents started at the time of the baseline assessment and lasted up to 7 years. Due to the naturalistic nature of the study, the follow-up assessments were scheduled depending on the clinical needs of the participants and included a clinical interview to investigate DSM-5 criteria for transition to psychosis. The assessments were preferably conducted face-to-face; however, when this was not possible, remote assessments were performed.
Clinical Outcome
The primary outcome was transition to psychosis according to the DSM-5 criteria; transition status was discussed and supervised in consensus conferences with a senior clinician.
Statistical Analysis
Descriptive analyses included median, first and third quartiles, mean values, and standard deviation (SD), as appropriate for continuous variables, absolute and relative frequencies for categorical variables. Descriptive analyses were complemented by statistical comparisons between the three groups. Kruskal-Wallis was used for numerical variables and Chi-square test for categorical variables, complemented by post hoc analyses (Dunn test and Fisher test, respectively, appended as supplementary material). To reduce the chance of type I error due to multiple testing, Bonferroni correction was applied to all post hoc analyses. Transition to psychosis was described through Kaplan-Meier failure function (1-survival), complemented by 95%CIs, calculated through log transformation of survival function as suggested in Link (1984), truncated at 1825 days when at least 10 adolescents were still at risk. Censoring was defined when adolescents did not transition to psychosis at the last clinical observation at follow-up. Prognostic accuracy for predicting psychosis onset was defined as time-dependent AUC, and timepoint sensitivity (SE), specificity (SP), positive predictive value (PPV), negative predictive value (NPV) were reported at each time point. We also reported the Harrell’s C with 95%CIs; values, which indexes the overall prognostic accuracy (discrimination). In interpreting Harrell’s C statistic, guidance suggests values of 0.9–1.0 are considered outstanding, 0.8–0.9 excellent, and 0.7–0.8 acceptable.20
Data were analyzed using R21; all tests were two-sided, with alpha set at 0.05. All authors have complete access to our database, in which data were collected only after pseudonymization.
Results
Study Population
The flow chart of the study population is shown in figure 1. 243 adolescents were included, 110 in the DSM-5 APS group, 102 in the non-APS, and 31 in the EOP group (see also supplementary results S1). Across study participants, all DSM-5 APS met the APS subgroup of the CHR-P. Furthermore, 3 individuals of the DSM-5 APS (2.7%) and 1 of the EOP (1%) groups additionally met GRD criteria.
Fig. 1.
Flow chart of the study population.
Cross-Sectional Between-Group Analysis
Sociodemographics
The average age of the DSM-5 APS group was 14.44 (±1.42), 62.7% of them were females, 80% of Italian ethnicity, 6% adopted, 38.2% from separated-divorced families and the median socioeconomic status was 31 (21 and 41 IQR 25 and 75, respectively); There were no between-group differences (table 1).
Table 1.
Sociodemographic Characteristics and Family History of Psychiatric Disorders in the Total Adolescent Sample and in the DSM-5 APS, non-APS, and EOP Subgroups
| Characteristic | Total (N = 243) | Non-APS (N = 102) | DSM-5 APS (N = 110) | EOP (N = 31) | P |
|---|---|---|---|---|---|
| Sociodemographics | |||||
| Age, median (min, max), y | 15.4 (12.0, 17.9) | 15.3 (12.1, 17.9) | 15.5 (12.0, 17.9) | 14.5 (12.0, 17.8) | .28 |
| Sex, female, n (%) | 152 (62.6) | 67 (65.7) | 69 (62.7) | 16 (51.6) | .37 |
| Ethnicity, n (%) | |||||
| Italian | 198 (81.5) | 82 (80.4) | 88 (80.0) | 28 (90.3) | |
| Northern African | 7 (2.9) | 3 (2.9) | 3 (2.7) | 1 (3.2) | |
| Hispanic | 7 (2.9) | 2 (1.9) | 5 (4.5) | 0 (0) | |
| Albanian | 8 (3.3) | 4 (3.9) | 4 (3.6) | 0 (0) | |
| Eastern European | 11 (4.5) | 3 (2.9) | 7 (7.4) | 1 (3.2) | |
| Other | 12 (4.9) | 8 (7.8) | 3 (2.7) | 1 (2.3) | |
| Socioeconomic status, median (IQR 25 and 75) | 29.25 (20.0, 39.0) | 27 (18.5, 37.5) | 31.0 (21.0, 41.0) | 27.0 (18.5, 37.0) | .57 |
| Adopted, n (%) | 15 (6.17) | 6 (5.8) | 7 (6.3) | 2 (6.5) | .98 |
| Separated-divorced family, n (%) | 91 (37.5) | 35 (34.3) | 42 (38.2) | 14 (45.2) | .54 |
| Family history of any DSM-5 psychiatric disorders, n (%) | |||||
| None | 94 (38.7) | 34 (33.3) | 45 (40.9) | 15 (48.4) | .26 |
| Psychosis | 19 (7.8) | 6 (5.9) | 7 (6.1) | 6 (19.3) | .08 |
| First degree | 5 (2.0) | 1 (1) | 3 (2.7) | 1 (3.2) | |
| Second degree | 14 (5.8) | 5 (4.9) | 4 (3.7) | 5 (16.1) | |
| Depression | 73 (30.1) | 32 (31.4) | 32 (29.1) | 9 (29.0) | .94 |
| First degree | 40 (16.5) | 17 (16.7) | 19 (17.3) | 4 (12.9) | |
| Second degree | 33 (13.6) | 15 (14.7) | 13 (11.8) | 5 (16.1) | |
| Anxiety | 47 (19.4) | 21 (20.6) | 18 (16.4) | 8 (25.8) | .55 |
| First degree | 24 (9.9) | 10 (9.8) | 11 (10.0) | 3 (9.7) | |
| Second degree | 23 (9.5) | 11 (10.8) | 7 (6.4) | 5 (16.1) | |
| Substance abuse | 21 (9.0) | 11 (10.8) | 10 (9.1) | 1 (3.2) | .68 |
| First degree | 19 (7.8) | 10 (9.8) | 8 (7.3) | 1 (3.2) | |
| Second degree | 3 (1.2) | 1 (1.0) | 2 (1.8) | 0 (0) | |
| Disruptive disorder | 11 (4.6) | 4 (3.9) | 5 (4.5) | 2 (6.5) | .19 |
| First degree | 7 (2.9) | 3 (2.9) | 4 (3.6) | 0 (0.0) | |
| Second degree | 4 (1.7) | 1 (1) | 1 (0.9) | 2 (6.5) | |
| Eating disorder | 11 (4.6) | 6 (5.8) | 4 (3.6) | 2 (3.2) | .84 |
| First degree | 6 (2.5) | 3 (2.9) | 2 (1.8) | 1 (3.2) | |
| Second degree | 5 (2.1) | 3 (2.9) | 2 (1.8) | 0 (2.3) | |
| Other | 40 (16.4) | 12 (11.7) | 23 (20.9) | 5 (16.1) | .12 |
| First degree | 21 (8.6) | 9 (8.8) | 11 (10.0) | 1 (3.2) | |
| Second degree | 19 (7.8) | 3 (2.9) | 12 (10.9) | 4 (12.9) |
Note: DSM-5 APS, Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition attenuated psychosis syndrome; EOP, early-onset psychosis; IQR, interquartile range.
Family History of Psychiatric Disorders
Lack of positive family history of any mental disorder was present in 40.9% of DSM-5 APS patients; family history of psychosis was traceable in 6.1% of participants, and the most frequent DSM-5 diagnosis was of depression disorders (29.1%); there were no between-groups differences (table 1).
Personality History of Psychiatric Disorders
In the DSM-5 APS group (table 2), the average number of comorbid DSM-5 diagnoses was 2.3, with 30.9% of individuals reporting more than 2 diagnoses. The average onset time of psychiatric symptoms before the initial assessment was of 14 months, and 74.3% of DSM-5 APS individuals reported negative symptoms. The number of comorbid DSM-5 diagnoses was significantly higher (P < .001) in the DSM-5 APS compared with EOP (P = .001) and non-APS (P = .001). Both DSM-5 APS/EOP adolescents showed greater negative symptoms than non-APS (P = .001, P < .001, respectively). DSM-5 APS showed a higher prevalence of depressive disorder (P = .003; P < .001, respectively) and personality disorders (P = .003; P < .001) than non-APS and EOP, higher prevalence of anxiety disorders than EOP adolescents (P = .004) and higher prevalence of bipolar disorders (P = .006) and obsessive disorders (P = .008) than non-APS adolescents (full post hoc analysis are reported in supplementary table S2).
Table 2.
Personal History of Psychiatric Disorders, Psychopathology, Functioning, Baseline Exposure to Psychiatric Treatments in the Whole Adolescent Sample and in the DSM-5 APS, non-APS, and EOP Subgroups
| Characteristic | Total (N = 243) | Non-APS (N = 102) | DSM-5 APS (N = 110) | EOP (N = 31) | P |
|---|---|---|---|---|---|
| Personal history of any DSM-5 psychiatric disorder | |||||
| Number of DSM-5 diagnoses, mean ± SD | 1.38 ± 0.8 | 1.5 ± 0.7 | 2.3 ± 0.8 | 1.0 ± 0.0 | <.001 |
| Number of diagnoses ≥3, n (%) | 40 (16.5) | 6 (5.9) | 34 (30.9) | 0 (0) | <.001 |
| Onset of psychiatric symptoms, months, median (IQR 25 and 75) | 14.0 (9.0, 24.0) | 14.0 (9.0, 24.0) | 14 (10.0, 24.0) | 18.0 (12.0, 26.5) | .53 |
| Type of DSM-5 diagnoses, n (%) | |||||
| Depressive disorders | 102 (42) | 42 (41.2) | 60 (54.5) | 0 (0) | <.001 |
| Anxiety disorders | 74 (30.5) | 30 (29.4) | 44 (40) | 0 (0) | .028 |
| Personality disorders | 74 (30.5) | 21 (20.6) | 53 (48.2) | 0 (0) | <.001 |
| Disruptive, impulse-control, and conduct disorders | 30 (12.4) | 15 (14.7) | 15 (13.6) | 0 (0) | .080 |
| Eating disorders | 40 (16.5) | 21 (20.6) | 19 (17.3) | 0 (0) | .075 |
| Bipolar disorders | 28 (11.5) | 8 (7.5) | 20 (18.2) | 0 (0) | .002 |
| Conversion disorder | 17 (7) | 8 (7.8) | 9 (8.2) | 0 (0) | .26 |
| Obsessive-compulsive and related disorders | 14 (5.8) | 2 (2.0) | 12 (11) | 0 (0) | .009 |
| Othersa | 20 (8.2) | 6 (5.9) | 14 (12.7) | 0 (0) | .41 |
| Presence of negative symptoms, n (%) | 161 (66.3) | 51 (50) | 81 (74.3) | 29 (93.5) | <.001 |
| Psychopathology | |||||
| CAARMS median (IQR 25 and 75) | |||||
| P1. Unusual thought content | |||||
| Severity | 2.0 (0.0, 3.0) | 0.0 (0.0, 1.0) | 2.0 (1.0, 4.0) | 5.0 (4.0, 6.0) | <.001 |
| Frequency | 2.0 (0.0, 4.0) | 0.0 (0.0, 1.0) | 3.0 (2.0, 4.0) | 5.0 (4.0, 5.0) | <.001 |
| P2. Non-bizarre ideas | |||||
| Severity | 2.0 (0.0, 3.0) | 0.5 (0.0, 2.0) | 3.0 (2.0, 4.0) | 5.0 (4.0, 6.0) | <.001 |
| Frequency | 3.0 (0.0, 4.0) | 0.0 (0.0, 3.0) | 3.0 (2.0, 4.75) | 5.0 (4.0, 5.5) | <.001 |
| P3. Perceptual abnormalities | |||||
| Severity | 3.0 (1.0, 4.0) | 0.5 (0.0, 2.0) | 3.0 (3.0, 4.0) | 5.0 (4.0, 5.0) | <.001 |
| Frequency | 2.0 (0.25, 4.0) | 0.5 (0.0, 2.0) | 3.0 (2.0, 4.0) | 4.0 (3.0, 4.0) | <.001 |
| P4. Disorganized speech | |||||
| Severity | 2.0 (0.0, 3.0) | 0.0 (0.0, 2.0) | 2.0 (0.0, 3.0) | 3.0 (2.5, 4.5) | <.001 |
| Frequency | 2.0 (0.0, 4.0) | 0.0 (0.0, 2.0) | 3.0 (1.0, 4.0) | 4.0 (3.0, 6.0) | <.001 |
| Clinical Global Impression-Severity (CGI-S) median (IQR 25 and 75) | 4.0 (3.0, 5.0) | 3.0 (3.0, 4.0) | 5.0 (4.0, 5.0) | 6.0 (5.0, 6.0) | <0.001 |
| Functioning | |||||
| Current SOFAS, median (IQR 25 and 75) | 51.0 (44.5, 60.0) | 60.5 (55.0, 70.0) | 50.0 (41.0, 55.0) | 40.0 (31.0, 50.0) | <.001 |
| Current role functioning (GF:R), median (IQR 25 and 75) | 6.0 (4.0, 7.0) | 7.0 (6.0, 8.0) | 5.0 (4.0, 6.0) | 4.0 (2.5, 5.0) | <.001 |
| Current social functioning (GF:S), median (IQR 25 and 75) | 5.0 (4.0, 6.0) | 7.0 (6.0, 7.0) | 4.0 (4.0, 5.0) | 3.0 (3.0, 5.0) | <.001 |
| Global assessment functioning (CGAS) | 51.0 (420, 60.0) | 60.0 (55.0, 70.0) | 50 (41.0, 51.0) | 35.0(30.0, 47.50) | <.001 |
| Baseline exposure to psychiatric treatments | |||||
| Psychotropic drugs, yes, n (%) | 84 (34.6) | 26 (25.5) | 43 (39.1) | 15 (48.4) | .075 |
| Number of psychotropic drugs, min, max | 0.0, 4.0 | 0.0, 4.0 | 0.0, 4.0 | 0.0, 3.0 | .11 |
| Type of psychotropic drugs, n (%)b | |||||
| Antipsychotics | 17 (20.3) | 3 (11.5) | 7 (16.3) | 7 (46.6) | .001 |
| Antidepressants | 48 (57.1) | 17 (65.4) | 26 (60.5) | 5 (33.3) | .38 |
| Benzodiazepines | 40 (47.6) | 12 (46.1) | 21 (48.8) | 7 (46.6) | .22 |
| Mood stabilizers | 8 (9.5) | 2 (7.7) | 4 (9.3) | 2 (13.3) | .45 |
| Duration psychotropic treatment, days, IQR 25 and 75 | 0.0, 30.0 | 0.0, 0.0 | 0.0, 30.0 | 0.0, 60.0 | .009 |
| Psychotherapy, yes, n (%) | 115 (47.3) | 40 (39.2) | 59 (53.6) | 16 (51.6) | .096 |
| Psychotherapy duration, days, IQR 25 and 75 | 0.0, 330.0 | 0.0, 240.0 | 0.0, 360.0 | 0.0, 330.0 | .11 |
Note: CAARMS, Comprehensive Assessment of At-Risk Mental States; CGAS, Children’s Global Assessment Scale; DSM-5 APS, Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition attenuated psychosis syndrome; EOP, early-onset psychosis; IQR, interquartile range; SOFAS, Social and Occupational Functioning Assessment Scale.
aIncludes attention deficit hyperactivity disorders, tics, post-traumatic disorders; bAs some participants were exposed to more than one medication, the total exceeds 100%.
P values with statistically relevance are evidence in bold.
Psychopathology
The DSM-5 APS group (table 2) had a median of CAARMS severity and frequency of respectively 2.0/3.0 in unusual thought content, 3.0/3.0 in non-bizarre ideas, 3.0/3.0 in perceptual abnormalities, 2.0/3.0 in disorganized speech, respectively. As expected, CAARMS scores were higher in the EOP, intermediate in the DSM-5 APS and lower in the non-APS (P < .001, table 2 and supplementary table S2). With respect to Global Impression-Severity scale (CGI-S), there are no significant differences between EOP and DSM-5 APS; conversely, the DSM-5 APS subgroup has higher scores than non-APS (median = 5) (P < .001, supplementary table S2 and table 2).
Functioning
The DSM-5 APS group (table 2) have a median level of Social and Occupational Functioning Assessment Scale (SOFAS) of 50, Global functioning role scale (GF:R) 5.0, Global functioning social scale (GF:S) 4.0, and Children’s Global Assessment Scale (CGAS) 50. The level of functioning was lower in the EOP, intermediate in the DSM-5 APS, and higher in the non-APS subgroups (P < .001; table 2 and supplementary table S2).
Baseline Treatments
At baseline, 39.1% of DSM-5 APS (table 2) were treated with psychotropic drugs (average 64 days): of these, 16.3% with antipsychotics, 60.5% with antidepressants, 48.9% benzodiazepines, 9.3% mood stabilizer, and 18% with more than one drug. The proportion of baseline antipsychotics was higher in the EOP than in non-APS e DSM-5 APS (P = .004, P = .043, respectively). Duration of psychotropic treatment was greater in both EOP and DSM-5 APS group compared with non-APS (P = .033; P = .036, respectively) (table 2 and supplementary table S2). At baseline, 53.6% of DSM-5 APS participants had received psychotherapy, with no significant differences compared with the other two groups (P > .11, table 2 and supplementary table S2).
Longitudinal Analysis
The median follow-up time for the DSM-5 APS group was 33 months; range 4–81 months. The median follow-up time for the non-APS group was 26 months; range 2–81 months. Because the vast majority of participants (92.9%) completed the follow-up, it was not possible to test differences among those who followed and not followed up.
Transition to Psychosis
Over follow-up time, 21 out of 103 DSM-5 APS adolescents transitioned to psychosis: 12 transitioned during the first year, 4 during the second, 5 during the third, 1 during the fourth, and 0 during the fifth year of follow-up. DSM-5 APS adolescents that converted to psychosis had an average time to conversion of 423.7 days (SD = 343.5); the mean age at transition was 16.9 years (SD = 1.8). The cumulative proportion of psychosis transition was 0.130 (95%CI 0.061–0.193) at 1 year, 0.170 (95%CI 0.089–0.243) at 2 years, 0.242 (95%CI 0.334–0.138) at 3 years, and 0.268 (95%CI 0.153–0.368) at 4 and 5 years.
Conversely, only 1 of 94 non-APS adolescents transitioned to psychosis (time to conversion = 991 days, age = 15 years). The cumulative proportion of psychosis transition was 0 (95%CI 0–0) at 1 year, 0 (95%CI 0–0) at 2 years, and 0.0032 (95%CI 0–0.093) at 3- to 5-year follow-up. For details, see figure 2.
Fig. 2.
Failure function (1-survival) of transition to psychosis in DSM-5 APS (n = 103) and non-APS (n = 94) adolescents. Note: DSM-5 APS, Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition attenuated psychosis syndrome.
Prognostic Accuracy for Prediction of Psychosis Onset
The prognostic accuracy of DSM-5 APS for predicting psychosis onset, measured as time-dependent AUC, was respectively 0.75 at 1 year, 0.75 at 2 years, 0.69 at 3 years, 0.71 at 4 years, and 0.77 at last observation (1825 days of follow-up). For details, see figure 3.
Fig. 3.
Prognostic accuracy (time-dependent area under the curve and 95% confident interval) of the DSM-5 APS for the prediction of psychosis onset in adolescents APS and non-APS. Note: DSM-5 APS, Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition attenuated psychosis syndrome.
The point-estimates of SE, SP, PPV, and NPV were as follows: SE 100%, SP 49%, PPV 11.6%, NPV 100% at 1 year; SE 100%, SP 50%, PPV 16.6%, NPV 100% at 2 years; SE 90.4%, SP 48.3%, PPV 22.9%, NPV 96.7% at 3 years; SE 91.3%, SP 51.4%, PPV 26.4%, NPV 97.4% at 4-year follow-up; SE 91.3%, SP 63.2%, PPV 32.1%, NPV 97.4% at the last observation (1825 days of follow-up). The Harrell’s C index was 0.736 (95%CI 0.697–0.775).
Discussion
A recent systematic review and meta-analysis22 revealed that the largest study in adolescents meeting DSM-5 APS criteria enrolled only 21 adolescents (compared with 68 non-APS patients).15 Furthermore, there are no longitudinal studies in underage DSM-5 APS patients and no studies evaluating non-APS transition risk to psychosis. Therefore, to our best knowledge, this is the largest real-world prospective cohort study and with the most comprehensive clinical assessment and longest follow-up addressing the presentation and outcomes of adolescents meeting DSM-5 APS criteria and with other nonpsychotic psychiatric disorders, and the first one to report the prognostic accuracy of DSM-5 APS in this population. Given that recruiting and following up children and adolescents at risk for psychosis is challenging, the results of the current study provide substantial advancement of knowledge in the field.
The key innovation of the current study is that the sampling frame for our adolescent cohorts consisted of all clinical entrants (filtered by our exclusion criteria) rather than referrals solicited via a research selection. We found a relatively high proportion (110/243 = 45%) of adolescents meeting DSM-5 APS criteria, likely reflecting the tertiary-level nature of our healthcare facility, where only adolescents with pronounced symptoms and disability are typically assessed. The first finding is that at presentation most DSM-5 APS adolescents presented with a family history of mental disorders (only 40.9% were lacking a positive familial history), with depressive disorders being more frequent than psychotic disorders. This aligns with evidence indicating that psychotic disorders can emerge from subtle mood dysregulation.23 Previous studies indicated that depressive symptoms are present in one-third of caregivers of CHR-P individuals, triggering criticism, and distress.24 About one-third of our DSM-5 APS adolescents are from separated-divorced families that may be associated with high levels of emotional distress. Screening for emotional distress in families of help-seeking adolescents accessing mental health care seems relevant to inform psychoeducation approaches. In line with the recent review,22 adolescents meeting APS criteria of the DSM-5 or CHR-P are more frequently females, in contrast with the predominant male composition of the adult CHR-P population.25 This difference may be due to specific neurodevelopmental effects such as the high proportion of affective or personality comorbidities, that are typically more frequent in females.
The second core finding is that at baseline DSM-5 APS adolescents showed higher clinical impairment than non-APS adolescents on most domains and comparable clinical impairments to EOP. This result confirms the syndromic nature of DSM-5 APS, which deserves clinical attention at presentation, independent of clinical outcomes and subsequent risk of transitioning to psychosis. In particular, DSM-5 APS adolescents had on average 2.3 comorbid disorders (higher than EOP/non-APS), confirming the association between DSM-5 APS status and other nonpsychotic mental disorders26,27 and the potential transdiagnostic nature of this syndrome.28 This is interesting because although the DSM-5 APS diagnosis requires excluding symptoms that may be better explained by other mental disorders, clinicians may rarely attribute psychotic-like symptoms in adolescents to other nonpsychotic mental disorders. In detail, we found a higher prevalence of depressive (54%), anxiety (40%), and personality disorders (48%), that in the adolescent general population.22 The association of depressive as well as anxiety disorders and psychosis risk has been widely reported in the CHR-P literature.29 Prevalence of nonpsychotic comorbidities is similar to that reported in other adolescents CHR-P15 and in a recent meta-analysis of the general population.30
Interestingly, in our sample, bipolar disorders were significantly more prevalent in DSM-5 APS adolescents than non-APS. The overlap between psychosis risk and bipolar risk in CHR-P cohort has been confirmed and lead to the development of specific assessment instruments.31 Furthermore, the onset of symptoms predated the DSM-5 APS designation of more than 1 year (14 months), opening to the possibility of earlier detection and assessment in this population.1 The high comorbid load of DSM-5 APS adolescents was related to high levels of negative symptoms (anhedonia and abulia) compared with the non-APS, and similar levels to the EOP group, in line with a previous study.32 The presence of negative symptoms is often endorsed in the CHR-P stage.33 Our group has already demonstrated that the inclusion of a fourth CHR-P subgroup based on the presence of negative symptoms can maximize the impact of preventive approaches for psychosis in underage populations.34 Because negative symptoms are typically refractory to treatments,35 their early identification in children and adolescents may be pivotal to improve outcomes.
As noted above, the DSM-5 APS group had an intermediate baseline CAARMS/CGI-S and functioning profile between the non-APS and the EOP groups. While the CAARMS/CGI-S results were expected, the functional impairments bring new clinically relevant information. First, they were consistently observed across complementary scales; since the SOFAS does not well distinguish between social and role functioning, we additionally employed the GF:R/GF-S36 as well as the CGAS (which has been specifically developed to rate of functioning in 6- to 17-year-old individuals). Second, functional impairments corroborate the syndromic nature of the DSM-5 APS in adolescents, alleviating concerns of stigmatization and of unnecessary treatments (see below). Third, functional impairments in CHR-P individuals represent also one of the most robust predictors of transition to psychosis.14,37
The third core finding of the current study is that 39.1% of DSM-5 APS adolescents were already treated with psychotropic drugs at baseline, for an average of 2 months. This demonstrated that antipsychotic prescription in young people at risk for psychosis occurs before they seek help from specialized CHR-P clinics. Antidepressants were prescribed more frequently (60.5%) than antipsychotics (16.3%) presumably in the light of the frequent comorbid affective disorders observed in DSM-5 APS adolescents. There is some evidence from naturalistic studies that antidepressants may have a protective role in CHR-P cohorts,38 but this has not been confirmed in children and adolescents or by randomized studies. Notably, 53.6% of DSM-5 APS adolescents had received psychotherapy for a median duration of 2 months. The efficacy of psychotherapy to prevent the onset of psychosis is unclear, as evidenced by recent meta-analyses.25,39 We did not perform inferential analyses to test the impact of treatment exposure on the risk of developing psychosis because this would require a specific statistical approach that will be part of a subsequent study.
The fourth core finding is that we reported the longest ever follow-up in adolescents meeting DSM-5 APS, indexing the cumulative proportion of psychosis risk: 13% at 1 year, 17% at 2 years, 24.2% at 3 years, and 26.8% at 4- to 5-year follow-up. These findings are clinically relevant 3-fold. First, the 2.3- and 4-year risks fall within the recent meta-analytical confidence intervals of risk for psychosis that have been estimated for children and adolescents under the age of 18 years: 0.20 (95%CI 0.15–0.26) at 1 year, 0.23 (95%CI 0.12–0.39) at 2 years, 0.27 (95%CI 0.21–0.35) (from table S12 in Ref. 22).40,41 This confirms that the sample recruited in our site aligns with international CHR-P cohorts recruited worldwide. This observation is relevant given the relevant sampling biases that impact risk enrichment in the CHR-P field.42 Second, the level of risk for psychosis observed in our DSM-5 APS adolescents is also comparable with that observed meta-analytically in adult samples (20% at 1 year and 22% at 2 years).9 Therefore, in line with the previous meta-analyses, this study does not indicate a reduced level of risk for psychosis in underage populations. Third, in line with previous meta-analytical literature in adults,43 the risk of transitioning was maximal in the first 24 months but still increased in the long term. Previous studies confirm that the risk of psychosis onset can increase for up than one decade.44,45 Thus, especially in adolescents, it seems essential to provide clinical monitoring for at least 3 years, as recently recommended.46 It is also important to underline that risk of transition in DSM-5 APS adolescents is higher compared with non-APS adolescents (3.2% at 3-year follow-up): this finding supports DSM-5 APS criteria in adolescents.
The additional relevant finding of this study is to have demonstrated for the first time that DSM-5 APS holds statistically significant prognostic accuracy in adolescent populations. This is a relevant discovery which is confirming the potential clinical usefulness of this designation to predict outcomes in the youngsters. Importantly, prognostic accuracy at 5 years was acceptable (AUC = 0.77; Harrell’s C = 0.736) and comparable to that observed in adult samples. The observed prognostic accuracy is comparable if not superior to that of structural neuroimaging methods (ie, gray matter volume) to detect an emerging psychosis at the individual level, with accuracies ranging from 0.5 to 0.63.47 A recent machine-learning prediction modeling study reported a 1-year prognostic accuracy of 0.59 but concluded that, if implemented at scale, performance even only significantly above chance can be considered to be clinically useful.48 Therefore, our finding of an adequate prognostic accuracy of DSM-5 APS diagnosis in adolescents should be interpreted along with the demonstration of feasibility of administration in complex clinical settings such as inpatient neuropsychiatric units. Furthermore, as previously noted, the DSM-5 APS indexes a syndromic condition that requires support and interventions at presentation, independent from clinical outcomes.7 These findings suggest that a stepped use of DSM-5 APS assessment may be preferable in adolescents, with those testing positive subjected to further psychopathological assessments to refine the predictions. These assessments are not yet available but should become a core area of research aiming at improving prognostic validity and ultimately clinical utility of DSM-5 APS in young populations.49
The main limitation of the current study is represented by the heterogeneous nature of the convenience sample. For example, we did not exclude adolescents that had been treated with antipsychotics prior study entry. However, these adolescents may have received antipsychotics mostly because for nonpsychotic symptoms (eg, aggressive behavior or mood instability). Another limitation is that because we included adolescents recruited at a third-level center, our adolescents were more severe and clinically impaired than those recruited from the general population50 and community mental health services, thus, representing a more severe spectrum of the DSM-5 APS status. However, our transition risk and thus level of risk enrichment are comparable with that of other sites worldwide. Finally, these findings were not externally validated, and therefore, their international generalizability should be addressed by future research.
Conclusions
Our findings support the clinical utility of DSM-5 APS diagnosis for the identification of APS in help-seeking adolescents and children, for predicting their clinical outcomes and informing preventive interventions.
Funding
This project was supported by a grant funded by the Italian Ministry of Education, University and Research (MIUR) between 2012 and 2017. This research was supported by the Italian Ministry of Health (current research 2017–2020).
Supplementary Material
Acknowledgments
The authors would like to thank the Colleagues, Capone Luca, Carpani Adriana, Chiappedi Matteo Alessio, Ferro Federica, Morabito Chiara, Spada Giulia, Tantardini Michela, Zandrini Chiara for the clinical management and evaluations of many of the patients reported in this study during these years. P.F.P. has received grant fees from Lundbeck and honoraria fees from Lundbeck, Menarini, and Angelini outside the current study. All other authors declare no conflict of interest.
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