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Psychosis Incident Cohort Outcome Study (PICOS). A multisite study of
clinical, social and biological characteristics, patterns of care and
predictors of outcome in firstepisode psychosis. Background,
methodology and overview of the patient sample
A. Lasalvia, S. Tosato, P. Brambilla, M. Bertani, C. Bonetto, D. Cristofalo, S. Bissoli, K. De Santi, L. Lazzarotto, G. Zanatta,
G. Marrella, R. Mazzoncini, M. Zanoni, N. Garzotto, C. Dolce, S. Nicolau, L. Ramon, C. Perlini, G. Rambaldelli, M. Bellani,
M. Tansella and M. Ruggeri
Epidemiology and Psychiatric Sciences / Volume 21 / Issue 03 / September 2012, pp 281 303
DOI: 10.1017/S2045796012000315, Published online: 15 June 2012
Link to this article: http://journals.cambridge.org/abstract_S2045796012000315
How to cite this article:
A. Lasalvia, S. Tosato, P. Brambilla, M. Bertani, C. Bonetto, D. Cristofalo, S. Bissoli, K. De Santi, L. Lazzarotto, G. Zanatta,
G. Marrella, R. Mazzoncini, M. Zanoni, N. Garzotto, C. Dolce, S. Nicolau, L. Ramon, C. Perlini, G. Rambaldelli, M. Bellani,
M. Tansella and M. Ruggeri (2012). Psychosis Incident Cohort Outcome Study (PICOS). A multisite study of clinical, social
and biological characteristics, patterns of care and predictors of outcome in firstepisode psychosis. Background,
methodology and overview of the patient sample. Epidemiology and Psychiatric Sciences, 21, pp 281303 doi:10.1017/
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Psychosis Incident Cohort Outcome Study (PICOS).
A multisite study of clinical, social and biological
characteristics, patterns of care and predictors of
outcome in first-episode psychosis. Background,
methodology and overview of the patient sample
A. Lasalvia1*, S. Tosato1, P. Brambilla2, M. Bertani1, C. Bonetto1, D. Cristofalo1, S. Bissoli1,
K. De Santi1, L. Lazzarotto1, G. Zanatta1, G. Marrella1, R. Mazzoncini1, M. Zanoni1, N. Garzotto3,
C. Dolce4, S. Nicolau5, L. Ramon6, C. Perlini7, G. Rambaldelli7, M. Bellani7, M. Tansella1, M. Ruggeri1
and the PICOS-Veneto Group
1Department of Public Health and Community Medicine, Section of Psychiatry, University of Verona, Verona, Italy
2DISM, Inter-University Centre for Behavioural Neurosciences, University of Udine, Udine, Italy and Scientific Institute IRCCS ‘E. Medea’,
3Department of Mental Health, 1st Psychiatric Service, ULSS 20, Verona, Italy
4Department of Mental Health, ULSS 6, Vicenza, Italy
5Department of Mental Health, ULSS 22, Isola d/S, VR, Italy
6Department of Mental Health, ULSS 10, Portogruaro, VE, Italy
7Department of Public Health and Community Medicine, Section of Psychiatry and Inter-University Centre for Behavioural Neurosciences
University of Verona, Verona, Italy
Aims. This paper aims at providing an overview of the background, design and initial findings of Psychosis Incident
Cohort Outcome Study (PICOS).
Methods. PICOS is a large multi-site population-based study on first-episode psychosis (FEP) patients attending public
mental health services in the Veneto region (Italy) over a 3-year period. PICOS has a naturalistic longitudinal design and
it includes three different modules addressing, respectively, clinical and social variables, genetics and brain imaging. Its
primary aims are to characterize FEP patients in terms of clinical, psychological and social presentation, and to inves-
tigate the relative weight of clinical, environmental and biological factors (i.e. genetics and brain structure/functioning)
in predicting the outcome of FEP.
Results. An in-depth description of the research methodology is given first. Details on recruitment phase and baseline
and follow-up evaluations are then provided. Initial findings relating to patients’ baseline assessments are also pre-
sented. Future planned analyses are outlined.
Conclusions. Both strengths and limitations of PICOS are discussed in the light of issues not addressed in the current
literature on FEP. This study aims at making a substantial contribution to research on FEP patients. It is hoped that the
Received 28 February 2012; Revised 4 April 2012; Accepted 4 April 2012; First published online 15 June 2012
Key words: First-episode psychosis, outcome, follow-up study, genetics, predictors, brain imaging.
The past two decades have seen the publication of a
growing number of studies on patients with first-
episode psychosis (FEP), which work on the assump-
tion that FEP is comparatively more treatment respon-
sive than multi-episode psychosis, and that intensive
phase-specific treatment may result in both short-
and medium-term improvements
(Edwards & McGorry, 2002). Understanding and
improving the outcome of psychosis remains, how-
ever, a major challenge for clinical research (Emsley
et al. 2008). Although focusing on FEP populations
has enabled researchers to provide useful information
*Address for correspondence: Dr Antonio Lasalvia, Department of
Public Health and Community Medicine, Section of Psychiatry,
University of Verona, Policlinico ‘G.B. Rossi’, Piazzale L. A. Scuro
10, 37134-Verona, Italy.
Epidemiology and Psychiatric Sciences (2012), 21, 281–303.
© Cambridge University Press 2012
regarding differential effects of treatment on outcome
(McGlashan et al. 1988; Ram et al. 1992), generalization
of the findings has been hampered by a number of
methodological problems, such as sample selection
bias (i.e. exclusion of patients with lower socio-
economic background or of patients who are difficult
to engage or who fail to collaborate), poor definition
of the catchment areas from which samples are
drawn, unsystematic attention to environmental and
contextual factors and lack of information on interven-
tions provided (Friis et al. 2003).
Moreover, most FEP research has been conducted in
experimental or academic services (Malla & Norman,
2006). Naturalistic follow-up studies on large samples
of patients receiving care in ‘real world’ services
(both academic and non-academic, research and rou-
tine) are still lacking. Studies providing information
on the outcome of patients treated in routine conditions
are extremely useful as a basis for healthcare planning.
Psychiatric service delivery has undergone significant
organizational changes over the past 20 years in
many western countries, while facing a dramatic
reduction in structural and personnel resources. This
represents a major challenge for mental health service
planning and delivery: a sound basis of evidence is
therefore needed to develop more effective and efficient
strategiesfor treating persons
Therefore, large naturalistic long-term studies per-
formed in routine services may provide a positive
feedback loop from ‘real world’ health services research
into clinical practice (Lasalvia & Ruggeri, 2007).
Another important issue in FEP research is the diag-
nostic boundary of patients under scrutiny. Most
studies have restricted their focus to first-episode
psychoses or affective psychoses (AP). Although this
reflects the understandable wish to obtain as homo-
geneous a sample of subjects as possible, it neverthe-
less creates a number of difficulties. Diagnosis, which
is often made on the basis of cross-sectional interviews,
may be subject to change as the clinical picture devel-
ops over the initial 6–12 months after presentation
(Addingtonet al. 2006;
Therefore, FEP research should adopt as broad a con-
cept of psychosis as possible. Studies on FEP popu-
lations, in fact, have the advantage of examining
large samples of patients who, while diagnostically
heterogeneous, share some common elements of
psychopathology. Although major distinctions in
diagnosis can be made relatively early on between
non-affective psychoses (NAP) and AP, some degree
of overlap becomes apparent only over time (Malla &
Conflicting findings have also been reported about
the clinical presentation of FEP patients: it is unclear
Salvatoreet al. 2009).
whether patients experiencing a first episode of psy-
chosis display a specific profile of psychopathological
symptoms. Some studies reported a relatively low
prevalence of negative symptoms in FEP patients
(Malla et al. 2002; Harris et al. 2005) and an increasing
frequency of negative symptoms with a longer dur-
ation of illness (Bottlender et al. 2001). Other studies
failed to identify marked differences between first epi-
sode and chronic schizophrenic disorders with respect
to psychopathological symptoms (Moritz et al. 2001),
neuropsychological function (Moritz et al. 2002) or
social deficits (Grant et al. 2001). More research is there-
fore needed to gain a clear-cut picture of the clinical
presentation of FEP, in order to define more focused
and early treatment strategies.
Although symptom severity and remission are
important measures of outcome, researchers have
increasingly focused their attention on various aspects
of psychosocial functioning to gain a more comprehen-
sive measure of outcome in FEP (Ruggeri et al. 2004). It
has been argued that functional dimensions of outcome
are relatively independent from symptom reduction
and may be more reliably predicted by pre-morbid
adjustment (Larsen et al. 2004). Assessing psychosocial
functioning in FEP patients allows one to understand
the impact of psychosis on the patient’s general well
being, role functioning and community integration
(Malla & Payne, 2005). Moreover, with the shift in treat-
ment of schizophrenic patients from long-term hospital-
ization to an outpatient community service, research on
important. This is a major area of interest when plan-
ning intervention and evaluating treatment outcome
in a recovery perspective (Wunderink et al. 2009) and
should therefore be systematically addressed.
(McGorry et al. 2000) and despite major advances in
their treatment a significant percentage may have a
poor outcome (Emsley et al. 2008; van Os & Kapur,
2009). Reasons for these variations are still inade-
quately understood. The identification of consistent
and reliable prognostic indicators has proved to be a
challenge. The last systematic review on the topic
(Menezes et al. 2006) provided rather disappointing
findings (i.e. being recruited from non-representative
samples, living in a developing country and being
treatment-naive at study entry were the only consist-
ent predictors of a good outcome, whereas use of typi-
cal antipsychotics at study entry was a predictor of
poor outcome). These inconclusive results probably
reflect inherent methodological limitations of the pub-
lished studies, which included a lack of baseline
standardized measures, the variation in definitions
of ‘outcome’, and the limited length of follow-up
periods (which, on average, hardly exceeded 2 years)
has become increasingly
282A. Lasalvia et al.
(Menezes et al. 2006). To better understand the predic-
tors of outcomes in FEP patients, future longitudinal
research should incorporate standard design features
that include: prospective follow-up of more than 2
measures; confirmation of diagnosis at least 1 year
later; a large epidemiologically representative sample
including both in- and outpatients; multi-dimensional
models of outcome incorporating symptomatic, func-
tional and personal variables measured at multiple
time points; use of standard and reliable scales for
measuring outcome; inclusion of potential determi-
nants of outcome such as treatment adherence, sub-
stance use, co-morbidity, pre-morbid functioning,
cognitive status, etc.); recording of all interventions
(Menezes et al. 2006).
Future research should also pay specific attention to
the mediating processes involved in the complex
relationships that exist between predictors and trajec-
tories of outcome. Problems in integrating findings
from multiple methods of investigation (e.g. epidemio-
logical, genetic and brain-imaging) to explain vari-
ations in trajectories of outcome still remain major
challenges (Malla & Payne, 2005). A further important
limitation of outcome research on FEP is that most
studies do not systematically consider the role of bio-
logical variables, among which genetic factors and
abnormalities in brain morphology and functioning
play a crucial role. As far as we know, the only
population-based research that considered clinical,
environmental and biological
patients is the ÆSOP study (Fearon et al. 2006;
Morgan et al. 2006), which, however, did not include
the geneticprofile of
In recent years, an increasing number of studies have
chosis. None of them, however, have been unambigu-
ously linked to dysfunctions leading to psychosis. A
thousand association studies involving over 700 candi-
date genes supported the role of some genes [i.e.
neuregulin 1 (NRG1), dysbindin (DTNBP1), dopamine
receptors D1–4 (DRD1–4)
in-schizophrenia-1 (DISC1)] in the development of psy-
chosis (Allen et al. 2008). However, even for these
promising genes, there has been a remarkable failure to
alleles in the development of psychosis (Alkelai et al.
2008; Sanders et al. 2008; Sullivan, 2008). Moreover,
none of the genome-wide association study (GWAS) on
schizophrenia or bipolar disorder so far implicated any
of the previously involved candidate genes (Shi et al.
2011; Bergen & Petryshen, 2012). These inconclusive
results seem to suggest that phenotype characterization
might be particularly important when identifying true
and valid candidate genes and that several genes might
interact to determine a particular phenotype.
To overcome the difficulties that are inherent in
research on multifactorial phenotypes, such as psycho-
sis, an approach based on phenotypic dissection has
been proposed (Rietkerk et al. 2008). This approach
into phenotypes based on symptoms, and then corre-
lates particular phenotypes with genetic variants
(Jablensky, 2006). The prospective of a dimensional,
symptom-based approach focused on an individual
and subsyndromal phenotype is attractive since it
may provide a model for studying the heterogeneity
of schizophrenia and the underlying pathophysiology
of the disorder (Carpenter et al. 1993). To date, rela-
tively limited work has been done to identify genetic
variants associated with specific clinical phenotypes.
Gene–symptom relationships have emerged primarily
from follow-up studies of putative schizophrenia risk
genes, with only a handful of replicated findings
(DeRosse et al. 2006; Tosato et al. 2007). This approach
will make it possible to define persistent aspects of
the schizophrenic profile which are more likely to
represent an underlying biological pathogenesis as
opposed to fluctuating, possibly environmentally
Although genetic research has achieved some encoura-
ging findings (Cook & Scherer, 2008; Maier, 2008), the
specific genotype–phenotype relation of psychosis still
The integration of clinical and genetic assessment
with brain imaging techniques has also been unsyste-
matic. Numerous imaging studies have revealed struc-
tural brain abnormalities in schizophrenia and related
NAP, with the most consistent findings being enlarged
lateral ventricles and reduced medial temporal and
prefrontal lobe volumes (Shenton et al. 2001; Liddle
& Pantelis, 2003). Although such abnormalities are
likely to be subtle (Weinberger, 1995), the nature, tim-
ing and course of the associated neurobiological
changes have proved difficult to elucidate (Harrison
& Lewis, 2003). There is evidence that these brain
abnormalities are already present prior to illness
onset or at onset (Pantelis et al. 2005; Arango et al.
2008) and that progressive changes in a number of
brain regions occur over time (Gogtay et al. 2011);
their associations, however, with clinical and func-
tional outcomes have so far proved to be inconsistent
(Cahn et al. 2002; Ho et al. 2003; DeLisi et al. 2004;
DeLisi & Hoff, 2005; Price et al. 2006). Moreover,
most recent MRI longitudinal studies on FEP suffer
from some methodological flaws, including the fact
that many so-called first-episode studies included
& Lasalvia, 2009).
Psychosis Incident Cohort Outcome Study (PICOS) 283
patients who had already been ill for a number of
years, the relatively small sample sizes (average num-
ber of patients per study: 32, S.D.=26.9) and the sample
selected patients) (Steen et al. 2006). Finally, longitudi-
nal investigations are needed to take into account the
interplay of various likely aetiological factors (both
environmental and biological) in understanding the
evolution of brain structural as well as functional def-
icits in FEP (Pantelis et al. 2005).
To fill these gaps a research project was undertaken
– Psychosis Incident Cohort Outcome Study (PICOS) –
aiming at integrating clinical, psychosocial and bio-
logical perspectives into research on FEP to better
understand possible mechanisms underlying treat-
ment outcomes. PICOS is a large multisite naturalistic
research that aimed at examining the relative role of
clinical, social, genetic and morpho-functional brain
factors in predicting symptomatic and functional out-
comes in a large cohort of FEP patients receiving care
from public mental health services located in a broad
area of the Veneto region (north-eastern Italy).
Specifically, PICOS is aimed at: (a) characterizing
new cases of psychosis at onset, in terms of clinical
presentation and social functioning; (b) determining
symptomatic and functional outcomes of both affective
and non-affective FEP patients treated in routine non-
experimental settings; (c) exploring to what extent
clinical, psychosocial and biological factors (i.e. gen-
etics and brain functional/structural characteristics)
influence the outcome of FEP patients and examine
their mutual interactions; (d) developing a comprehen-
sive predictive model of outcome for FEP and identify-
ing predictors of ‘good’ and ‘poor’ outcomes that
might be useful for both clinical and research pur-
poses. In this paper, we aim at providing an overview
of methodology and design of PICOS and to give some
initial baseline findings.
In order to achieve its aims, PICOS was designed with
a modular structure.
Module 1 – Clinical and social evaluations
It includes the assessment of a number of patients’
clinical and social characteristics, such as pre-morbid
IQ, pre-morbid social adjustment, stressful life events,
psychopathology, social disability, insight of illness,
subjective quality of life, needs for care and service sat-
isfaction. This information was collected by using a set
of well-known international standardized measures
(see below). In addition, the perceptions of relatives
(or informal caregivers) were also assessed using a
set of standardized measures, with specific regard to
burden of care, psychological distress and service sat-
isfaction (see below). This module also includes the
quantification of structural and human resources of
mental health facilities located in PICOS participating
sites (Lasalvia et al. 2007). A thorough assessment
was also made of the emotional and organizational
well-being of the staff working at the participating
sites (Lasalvia et al. 2009). The assumption behind
this data collection is that, along with patients’ per-
sonal and clinical characteristics, contextual factors
(e.g. services’ structural characteristics and resources,
emotional atmosphere of the therapeutic milieu and
degree of staff burnout) play a crucial role in explain-
ing treatment outcomes.
Module 2 – Genetics
It focuses on the assessment of family history of psy-
chiatric disorders and genetic liability to psychoses.
This module includes the reconstruction of probands’
family trees for psychotic disorders and the assess-
ment of Neurological Soft Signs. Moreover, for each
subject recruited to the study (both patients and
their first-degree biological relatives), venous blood
samples (15 ml) were collected in EDTA-containing
tubes. DNA was extracted from blood leukocytes
and it was stored. To perform a case-control study,
controls, selected from a population ethnically similar
to the patients, were recruited from repeat blood
donors via the Blood Transfusion Service from the
same area of Verona. The policy of the Blood
Transfusion Centre is not to collect blood from indi-
viduals who are on medication. The absence of a per-
sonal or family history of psychotic disorders was
ascertained using the SCID-NP and the Family
Interview for Genetics Study (FIGS; Maxwell, 1992).
The place of birth of both parents and grandparents
was ascertained in order to match controls by ethni-
city. DNA from patients, relatives and controls was
used to genotype the SNPs belonging to the different
candidate genes. The SNPs were selected using
PLINK software, in order to identify for each gene
in the study the minimal number of SNPs necessary
for the identification of the maximal haplotypic varia-
bility in Caucasian population. All genotyping ana-
lyses were performed blind to status. The quality
control criteria were: (i) genotypes form three distinct
clusters; (ii) water controls are negative; (iii) number
of genotypes callable is >90% and (iv) minor allele fre-
quency is greater than 2%. In addition, inter-plate and
intra-plate duplicate testing of known DNAs was
284 A. Lasalvia et al.
Module 3 – Brain imaging
This module includes the evaluation of brain features
using MRI scans and a series of neuropsychological
tests, with the aim of exploring brain structure and
cognitive dimensions. All
Module 1 who agreed to undergo MRI were enrolled
in Module 3 and contacted by clinical research psy-
chologists by phone to arrange an appointment and
to check the absence of MRI counter-indications
(i.e. pregnancy and metallic prosthesis). With respect
to the research exclusion criteria adopted by Module
1, further criteria were applied in Module 3: history
of traumatic head injury with loss of consciousness,
major medical diseases, alcohol or substance abuse in
the 6 months preceding MRI. All the 1.5 T MRI scans
(Magnetom Symphony Maestro class syngo MR
2002B – Siemens) were performed in the Section of
Radiology at the Verona University Hospital and
evaluation of structural, cerebral blood and white mat-
ter microstructure organization, respectively). In order
to minimize any anxiety symptoms, clinical research
psychologists carefully provided full information on
MRI and personally accompanied research subjects to
the MRI centre, waiting for them until the end of the
session. On the same day, patients received a full neu-
ropsychological assessment, including the following
tasks: Iowa Gambling Task (Bechara et al. 1994),
Continuous Performance Task (Nuechterlein, 1991),
Wisconsin Card Sorting Test (Heaton, 1981), Span of
N-back Test (Kirchner, 1958) for the evaluation of
decision making, sustained attention, executive func-
tions and working memory; narrative/conversational
task and syntactic comprehension task for the assess-
ment of linguistic production and comprehension.
Also, a visual-motor task (Poffenberger paradigm)
(Marzi, 1999; Bellani et al. 2010) was administered in
order to explore inter-hemispheric communication.
Finally, Papagno’s test (Papagno et al. 1995) for the
investigation of concrete thought was administered
and the Mini Mental State Examination (Folstein et al.
1975), while Raven’s Progressive Matrices (Raven
et al. 2003) were used to measure overall cognitive
PICOS is a naturalistic study, conducted with a pro-
spective longitudinal design. Evaluations of both
patients and relatives were carried out at baseline
and at 1, 2 and 5 years (currently underway).
The geographical context
The Veneto region has a population of approximately
4.6 million inhabitants (Census data, 2001), represent-
ing 8% of Italy’s total population. Nearly 2.5 million
of these inhabitants are aged 15–54 years and are
thus considered a population at risk for psychosis.
The region’s population structure is in line with the
national average in terms of older inhabitants (>65
years=7%), whereas the number of younger people
is slightly below the national average (<25 years=
23.8%, v. 25.8%). The vast majority of residents are of
Caucasian background, making up an ethnically
homogeneous population. Over the last 10 years, how-
ever, the proportion of foreign immigrants with
respect to the total population increased from 6.76%
in 2001 (Census data, 2001) to 9.30% in 2008
(Administrative data, Veneto region). The urban struc-
ture of the region is polycentric, with only a few
large-scale cities (i.e. Venice, Padua and Verona,
which exceed 200 000 inhabitants) and many mid-
and smaller-scale cities. An entrepreneurial system of
small- and mid-size businesses located throughout
the region makes the economic system very competi-
tive, which has led Veneto to become one of Italy’s
most affluent regions.
Overall, 25 collaborating sites took part in PICOS, cov-
ering a catchment area of nearly 3.3 million inhabi-
tants, corresponding to 76% of the inhabitants living
in the entire Veneto. PICOS was coordinated by the
Section of Psychiatry and Clinical Psychology at the
Medicine, University of Verona. The collaborating
sites were homogeneously distributed across the
regional territory and
Departments of Mental Health (DMHs) (n=9) or single
departmental units (n=16). In addition, two private
psychiatric inpatient facilities took part in the study
(Lasalvia et al. 2007). For a detailed list of participating
sites, together with the respective local research teams
see the Appendix.
The care context
community-based mental health services, established
according to the 1978 psychiatric legislation reform
and which operate in the Italian National Health
Service (NHS) context. Psychiatric care in the Veneto
region is delivered by the NHS through its DMHs,
each of which has
participating sites wereroutinepublic
et al. (Tansella2006).
Psychosis Incident Cohort Outcome Study (PICOS)285
Multi-disciplinary teams operating these DMHs pro-
vide a wide range of comprehensive and integrated
programmes for the local adult population, including
inpatient care, day care, rehabilitation, outpatient
care, home visits, 24-h emergency services and residen-
tial facilities for long-term patients (Tello et al. 2005).
Standard care for FEP patients generally consists of
personalized outpatient psychopharmacological treat-
ment, combined with non-specific supportive clinical
management atthe Community
Centre level or – when required – in patients’ homes
(Lasalvia et al. 2007). When necessary, brief hospital
stays can also be arranged in small inpatient psychia-
tric units located in public general hospitals (Lasalvia
& Tansella, 2010).
All psychiatric facilities located in the area covered by
PICOS were asked to refer to the local research teams
all potential cases of psychosis at first service contact
during the index period (1st January 2005–31st
December 2007). There were no formal diagnostic cri-
teria for entry into the study (only psychopathological
criteria were used). Based on the over-inclusive screen-
ing methodology adopted in the WHO ten-country
study (Screening Schedule for Psychosis; Jablensky
et al. 1992), the inclusion criteria were: (1) age 15–54
years; (2) residence in the Veneto region; (3) presence
of (a) at least one of the following symptoms: halluci-
nations, delusions, qualitative speech disorder, quali-
inappropriate behaviour, or (b) at least two of the fol-
lowing symptoms: loss of interest, initiative and drive,
social withdrawal, episodic severe excitement, purpo-
seless destructiveness, overwhelming fear, marked
self-neglect; (4) first lifetime contact with any mental
health service located in PICOS area during the
study period occasioned by symptoms enumerated in
(3). The exclusion criteria were: (1) prior treatment
with an antipsychotic agent for more than 3 months;
(2) mental disorders due to a general medical con-
dition; (3) moderate to severe mental retardation.
The screening instrument was administered to all
potentially eligible patients as soon as possible after
their first service contact (and in all cases within 30
days of first contact). The instrument was completed
by a face-to-face interview with the patient and/or
using case notes and information provided by the
treating staff. Each patient who met the inclusion cri-
teria was approached and invited to undertake
standardized assessments (see below). Patients’ inter-
views were carried out by local mental health staff
trained in the use of study instruments. The assess-
ment would take place only after having gained
written informed consent, as approved by both the
Ethics Committee of the coordinating centre and the
local Ethics Committees of participating sites. All sub-
jects provided written informed consent for study pro-
cedures and for anonymous and aggregate reporting
of clinical findings. The participants were informed
that they might withdraw consent to the assessments
at any time. The eligible patients were also asked for
consent to involve a key family member in the assess-
ments. If the patient or the family member did not
agree to be assessed, the local research staff would
briefly record their reasons for not agreeing, whenever
possible. The patients and family members who
refused to participate in the study were re-contacted
at monthly intervals up to three more times.
Routine case ascertainment was conducted through
ongoing liaison between the local PICOS research
teams at each study site and local mental health ser-
vices. The clinical staff were encouraged to refer all
people who met the initial screening criteria to the
study offices, using a variety of agreed routes includ-
ing telephone, 24-h answering services, postal pro-
forma and dedicated fax returns. There was regular
phone or face-to-face contact between study teams
and both the in-patient and community mental health
teams serving the populations at risk. Regular training
events for clinical teams ensured that all staff
knew about PICOS, regardless of staff turnover.
Promotional materials were made available in all clini-
cal settings to ensure awareness and continuation of
referrals and presentations were made to user and
carer groups within the relevant areas. A ‘leakage
study’, based on the method described by Fearon
et al. (2006), was also undertaken at 14 PICOS sites,
in order to further assess the accuracy of the recruit-
ment procedure and to identify any cases missed
through the routine procedures. All electronic and
paper information systems were carefully scrutinized
for any cases aged 15–54 years, presenting to the ser-
vices for the first time during the index period, with
ICD-10 diagnostic codes of psychosis (F1x.4; F1x.5;
F1x.7; F20-29; F30.2, F31.2, F31.5, F31.6, F32.3, F33.3).
This information was compared with case records to
made six months after inception using the Item Group
Checklist (IGC)of the
Assessment in Neuropsychiatry (SCAN; World Health
Organization, 1992a). At that time, two psychiatrists,
formal best-estimate researchdiagnosis was
286A. Lasalvia et al.
one who had reviewed the subject initially and one who
had not, independently reviewed the relevant baseline
and follow-up information and formulated the ICD-10
diagnosis. In the cases where a consensus was not
reached, the opinion of a third psychiatrist was solicited
to clarify diagnostic problems. Only patients with a con-
firmed ICD-10 diagnosis of psychosis, either non-
affective or affective (F1x.4; F1x.5; F1x.7; F20–29; F30.2,
F31.2, F31.5, F31.6, F32.3, F33.3), were suitable for
re-assessment at the later follow-up stages.
Clinical and psychosocial assessment
A comprehensive set of well-known standardized
measures was used to collect patients’ clinical and
psychosocial information. Face-to-face interviews were
conducted at baseline (during or shortly after discharge
from the hospital for the most part) and at 1- and 2-
and 5-year follow-up. Table 1 presents an overview of
The duration of untreated psychosis (DUP) was also
established for each patient by reviewing relevant
information in the case notes and questioning the
patient and relatives and/or caregiver and was opera-
tionally defined as the time from onset of psychotic
symptoms to first treatment with antipsychotic medi-
cation (Norman & Malla, 2001).
The patients were also asked for consent to involve
their key family members in the assessment, and when
given, the family members who provided written
informed consent were also assessed at baseline and
re-assessed at subsequent follow-up points.
Within each participating site a small multi-disciplinary
local research team was established, composed of rou-
tine mental health staff (e.g. psychiatrists, clinical psy-
therapists), who were preliminarily trained in the use
of the study instruments. In fact, prior to the recruit-
ment of the patients, all local mental health service
staff involved in the standardized evaluations (n=101)
received a specific 3-day training in administering the
study’s instruments. The training of the interviewers
included sessions for discussion of all standardized
assessment schedules used in the study and interview
of patients with psychosis by each interviewer, watched
by all remaining interviewers and coordinators of the
study, followed by a discussion. There was constant
supervision of the interviewers during the study, with
a discussion of the difficulties and doubts in any of
the schedules of the study protocol. In order to deter-
mine the training effectiveness and to test the consist-
encyof the evaluations
inter-rater reliability exercise was carried out on the
clinical measures (such as the PANSS) by involving
the local staff trained in the use of the study’s instru-
ments (see Results).
Sample size and power calculation
For power calculation, we considered the difference
between total PANSS scores of two time points to be
the outcome measure, specifically the first and second
follow-up because this appears to be the most conser-
vative approach due to reduced sample sizes. At the
first follow up, 209 patients were assessed using the
PANSS and the mean total score was 53.32 (S.D.
19.59); at the second follow up, 190 patients were
assessed, with a mean score of 48.43 (S.D. 17.93). The
Pearson correlation coefficient between observations
at first and second follow-up is 0.4. Assuming an
alpha level of 0.05, these parameters made it possible
to achieve 87% power.
Participants’ evaluation was carried out at baseline
and at 1, 2 and 5 years. Since there are many issues
measurements, mixture of non-time-varying and time-
varying covariates and missing data) which make the
analysis of longitudinal data complicated, it will be
necessary to adopt specific statistical techniques to
take these effects into account. Longitudinal data can
be viewed as multilevel data, with repeated measures
nested within individuals. In its simplest form, this
leads to a two-level model, with the series of repeated
measures at the lowest level and the individuals at the
highest level. In order to take into account the within
subject correlation in the presence of missing data,
multilevel regression models will be estimated by linear
regression equations, with different regression coeffi-
cients for different individuals (Hox, 2002; Leyland &
Goldestein, 2003). Using multilevel models to analyse
repeated measures data will have several advantages.
First, by modelling varying regression coefficients at
the occasion level, we have growth curves that are
different for each person. Second, the number of
repeated measures may differ across persons. Third,
the co-variances between the repeated measures can
be modelled by specifying a definite structure for the
variances and co-variances. Fourth, if we have
balanced data and use RML estimation, the usual
repeated measures analysis of variance can be derived
from the multilevel regression results. Fifth, it is
straightforward to include time varying or time
Psychosis Incident Cohort Outcome Study (PICOS) 287
constant explanatory variables in the model, which
allow us to model both the average group develop-
ment and the development of different individuals.
Since multilevel regression models do not require
balanced data, this will allow for the inclusion of
data from patients with incomplete observations at fol-
low ups. We will allow for the presence of missing out-
come data under the assumption that the data are
Table 1. Assessment instruments and measures used in PICOS
Variable Instrument BL
Familiarity for psychosis
Family Interview for Genetics (FIGS)a,b
Positive and Negative Syndrome Scale (PANSS)a
Hamilton Rating Scale for Depression (HAM-D)a
Bech-Rafaelsen Mania Rating Scale (BRMS)a
Life Chart Schedule (LCS)a,c
Ad hoc schedulea,c
Life events Psychosocial and Environmental Stressors
Premorbid Social Adjustment Scale (PSA)a,b
Parental Bonding Instrument (PBI)a
Global Assessment of Functioning (GAF)a
Disability Assessment Schedule (DAS-II)a,b
Schedule of Assessment of Insight, expanded
Camberwell Assessment of Need (CAN-EU)a
Clinical Drug Alcohol Use Scale (CDAUS)a
Manchester Short Assessment of Quality of Life
Involvement Evaluation Questionnaire
General Health Questionnaire (GHQ)b
Verona Service Satisfaction Scale (VSSS-EU)a,b
Verona Interview for Treatment Termination
Ad hoc schedulea,c
Insight of illness
Needs for care
Subjective quality of Life
Socio-demographics and service
Neurological soft signs
Extrapyramidal side effects
Italian NART, Test Intelligenza Breve (TIB)a
Ad hoc schedule
Neurological Evaluation Scale (NES)a
Simpson-Angus Scale (SAS)a
Barnes Akathisia Rating Scale (BAS)a
Neuropsychological tests batterya
Magnetic Resonance Imaginga,b
Used to collect data from:apatients;brelatives;ccase records.
FIGS (Maxwell, 1992), PANSS (Kay et al. 1987), HAM-D (Hamilton (1960), BRMRS (Bech et al. 1978), LCS (World Health
Organization, 1992b; Lasalvia et al. 2004), PSA (Foerster et al. 1991), PBI (Parker et al. 1979), GAF (APA, 1994), DAS-II (World
Health Organization, 1988), SAI-E (David et al. 1992), CAN-EU (McCrone et al. 2000), MANSA (Priebe et al. 1999), CDAUS
(Mueser et al. 1995), IEQ-EU (van Wijngaarden et al. 2000), GHQ (Goldberg & Williams, 1988), VSSS-EU (Ruggeri et al. 2000),
VITreT (Ruggeri et al. 2007), TIB (Nelson, 1982; Colombo et al. 2002), SAS (Simpson & Angus, 1970), BARS (Barnes, 1989),
NES (Buchanan & Heinrichs, 1989).
288A. Lasalvia et al.
missing completely at random conditional on the cov-
ariates included in the models [i.e. missing at random,
using the terminology of Little & Rubin (2002)].
Statistical significance is defined at two-sided p<
0.05. All analyses will be performed using STATA 9.0
The level of agreement between the raters was tested
by the Intra-class Correlation Coefficient (ICC). The
agreement was considered to be high if ICC was
equal to or greater than 0.75. Each rater independently
patients. High levels of agreement (mean percentage
on the items of each scale) were reached between
each coder and the clinician. In detail, 85% for positive
scale, 70% for negative scale and 82% for general scale.
The intra-class correlation coefficient reached a value
Recruitment and baseline evaluation
The flow diagram in Figure 1 gives an overview of
patients’ recruitment and baseline evaluations.
Of all the patients referred to PICOS research staff as
potentially eligible cases, 517 had a confirmed ICD-10
diagnosis of psychosis. The majority (75%) were
directly approached by the research staff and asked
to be interviewed, while 25% could not be approached
for the reasons detailed in Figure 1. However, every
effort was made by the research staff to gain as
much information as possible on the patients who
were not approached: specifically, all available case
records and/or all other clinical documentation were
carefully scrutinized and the treating clinicians were
interviewed by the research staff in order to allow
the completion of the core set of assessment instru-
ments (i.e. PANSS, HAM-D, BRMRS, DAS and GAF);
using this procedure, clinical information was col-
lected on a further 37 patients. Of the patients
approached (n=388), 288 were interviewed face-to
face by the research staff with the full range of the
study instruments, whereas 100 did not consent to
meet local researchers for the assessment. It was poss-
ible, however, to complete the core study instruments
for 72 of them on the basis of the clinical information
drawn from the case records and/or from treating clin-
icians’ interviews. Therefore, a total of 397 patients
were assessed with the core set of study instruments,
and they represent the baseline sample of this study.
found between those who were assessed with the full
range of study instruments and the others.
Follow-up assessments were conducted within each
participating site by the same research staff that had
performed the baseline evaluations, and took place in
chronological order of initial contact with psychiatric
services. The patients currently in psychiatric care
were approached through their treating clinicians or
key-workers. The patients who had left the area of
residence since the original intake were traced by con-
tacting family members or their general practitioner.
The patients living in the area covered by PICOS but
no longer in contact with the services were contacted
through their former treating clinicians and were
asked to be approached for the follow-up evaluations
(this was done following confirmation with their for-
mer treating clinicians that such an approach was
appropriate). The follow-up assessments included
face-to-face interviews with subjects, family members
and the treating psychiatric teams and perusal of
psychiatric case notes, general medical notes and com-
munity mental health team notes. Figure 2 shows the
flow diagram of the 1-year and the 2-year follow-up
assessments. Since PICOS was conducted in a large
number of ‘real world’ mental health services spread
across a broad geographical area and involved an
unselected sample of patients reflecting the compo-
sition of routine patients on the caseloads of public
services, the follow-up design is quite complex.
Of the patients interviewed face-to-face at baseline
(n=288) (Fig. 2a, left side, upper part), three had
died duringthe follow-up
approached at 1 year and re-evaluated face-to face
with the full range of the study instruments, 67 were
assessed at 1 year with the core set of clinical measures
(PANSS, HAM-D, BRMS, DAS and GAF) on the basis
of information drawn from case notes and/or after
having interviewed treating clinicians. Overall, 224
patients were assessed at 1 year, resulting in a
follow-up rate of nearly 79%. It should be noted that
every effort was made by the local research staff and
by the coordination centre to trace, approach and
assess both patients who had refused to be interviewed
at baseline and those who had not been approached at
baseline. Of the patients who had refused to be inter-
viewed face-to-face at baseline (Fig. 2a, right side,
upper part), 10 consented to be interviewed face-to
face at 1 year and 26 were assessed with the core set
the study instrument on the basis of clinical infor-
mation drawn from case records and/or from treating
approached at baseline (Fig. 2b, upper part), 26
Psychosis Incident Cohort Outcome Study (PICOS) 289
Figure 1. Flow diagram of recruitment and baseline evaluation.
A. Lasalvia et al.
Figure 2. (a) Flow diagram of 1-year and 2-year follow-up: patients approached. (b) Flow diagram of 1-year and 2-year follow-up: patients not approached.
Psychosis Incident Cohort Outcome Study (PICOS)
Figure 2. Continued.
292 A. Lasalvia et al.
additional patients were assessed at 1 year, either
face-to face (n=8) or on the basis of information
drawn from case records or treating clinicians’ inter-
views (n=18), thus yielding a total of 286 patients
with a 1-year follow-up assessment available. No sig-
nificant differences in socio-demographic, diagnostic
and clinical characteristics were found between those
followed for 1 year and those lost to follow up.
At 2 years, of the patients interviewed face-to-face at
baseline (Fig. 2a, left side, lower part) one had died
during the follow-up interval, 135 were re-interviewed
face-to-face with the full range of the study instru-
ments and 51 were assessed with the core set of clinical
measures (PANSS, HAM-D, BRMS, DAS and GAF) on
the basis of information drawn from case records and/
or treating clinicians’ interviews. Overall, 186 patients
were re-assessed at 2 years, resulting in a follow-up
rate of 65.5%. It should be noted that also at 2 years,
every effort was made to trace and approach both
patients who had refused to be interviewed at baseline
and those who had not been approached at baseline:
from the former group (Fig. 2a, left side, lower part)
29 patients were assessed at 2 years either face-to
face (n=9) or on the basis of information drawn from
case records or treating clinicians’ interviews (n=19),
and from the latter group (Fig. 2b, lower part) 19
additional patients were assessed either face-to face
(n=9) or on the basis of information drawn from
case records or treating clinicians’ interviews (n=10),
thus yielding a total of 233 patients with 2-year
follow-up assessment available. No significant differ-
ences were found in terms of socio-demographic or
diagnostic characteristics between those followed for
2 years and those lost to follow-up. With respect to
baseline clinical assessment, the groups did not differ
for PANSS negative symptoms and DAS, whereas
PANSS positive symptoms [3.27, S.D. 1.05 v 3.02, S.D.
1.01; p=0.018 t-test], PANSS general symptoms [2.77,
S.D. 0.75 v 2.59, S.D. 0.76; p=0.021 t-test], PANSS total
score [2.85, S.D. 0.74 v 2.66, S.D. 0.71; p=0.011 t-test]
and GAF [37.92, S.D. 10.15 v 40.40, S.D. 10.98; p=0.021
t-test] were higher among patients assessed at 2
years than among those lost to follow-up.
Findings from the leakage study
On the basis of the existing literature, annual treated
incidence for schizophrenia and related functional psy-
choses in the Veneto ranges from around 17/100 000
(de Salvia et al. 1993) to 11/100 000 (Tansella et al.
1991). Some PICOS sites recruited a number of inci-
dent cases lower than expected. Specifically, among
the 25 PICOS sites, the cases were lower than expected
in 11 sites (n=101; person-years: 1 505 739; incidence
rate: 6.7/100 000). The 14 remaining sites recruited a
number of cases (n=426; person-years: 3 144 483; inci-
dence rate: 13.5/100 000) that was substantially in line
with the numbers reported in previous incidence
Through the ‘leakage study’ procedure it was found
that in seven sites the proportion of missed cases was
negligible (missed cases n=27; 12%; recruited cases n=
183; person-years: 1 311 493; incidence rate: 16/100
000), whereas in the remaining seven sites the pro-
portion of missed cases was higher (missed cases n=
152; 39.9%; recruited cases n=229; person-years: 1
832 990; incidence rate: 20.8/100 000). So a conservative
assumption was made that the sub-sample recruited in
the former seven sites was fully representative of new
cases of psychosis living in their respective catchment
areas. Overall, on the basis of the leakage study, the
treated incidence rate of psychosis in the Veneto region
is 18.8/100 000 a year (further details on incidence data
in PICOS area will be given in future publications).
Clinical and social characteristics of patients
Of patients assessed at baseline (n=397), 25.6% were
diagnosed with ‘Acute and transient psychotic dis-
order’ (F23), 22.1% with ‘Schizophrenia’ (F20), 13.4%
with ‘Psychosis NOS’ (F29), 12.1% with ‘Depressive
episode, severe with psychotic symptoms’/‘Bipolar dis-
order, current episode depressed, severe, with psycho-
tic features’ (F32.3, F31.5), 9.2% with ‘Delusional
disorder’ (F22), 8.0% with ‘Manic episode, severe
with psychotic symptoms/’Bipolar affective disorder,
current episode manic with psychotic symptoms/
‘Bipolar affective disorder, current episode mixed’
(F30.2, F31.2, F31.6), 7.4% with ‘Schizoaffective dis-
order’ (F25), 1.2% with ‘Schizotypal disorder’ (F21),
1.0% with ‘Substance-induced psychoses’ (F11–19). For
the purpose of analysis, the specific ICD-10 categories
were aggregated into three main diagnostic groups,
‘Schizophrenia’ (F20), ‘Non Affective Psychoses’ (NAP)
(F11-19, F22, F23, F25, F29) and ‘Affective Psychoses’
(AP) (F32.3, F31.5, F30.2, F31.2, F31.6).
Table 2 shows the baseline patients’ demographic
information by diagnostic group.
As expected, significant differences were found
between the diagnostic groups in terms of age, gender,
marital status, living conditions and employment
Table 3 shows comparisons between baseline rat-
ings of the PANSS in the three diagnostic groups.
Significant differences were found in a number of
psychopathological dimensions, with schizophrenic
patients showing more severe delusions (ANOVA,
p<0.01), conceptual disorganization (ANOVA, p<
0.05), hallucinations (ANOVA, p<0.01), mannerisms
and posturing, uncooperativeness, attention deficit,
Psychosis Incident Cohort Outcome Study (PICOS) 293
lack of judgment and insight, disturbance of volition
and active social avoidance (ANOVA, p<0.05). On
the other hand, patients with AP showed higher
levels of grandiosity (ANOVA, p<0.05), higher levels
of guilt feelings (ANOVA, p<0.001) and more severe
depressed mood (ANOVA, p<0.05).
Table 4 shows baseline levels of patients’ disability
in social roles in the three diagnostic groups.
Patients with schizophrenia also displayed poorer
overall social functioning (ANOVA, p<0.01). From
item analyses it emerged that from one third to nearly
one half of the patients (with non-significant differ-
ences between groups) displayed severe disability in
occupational role, friction in social contact and partici-
pation in their households at illness onset. It is also
interesting to note that for schizophrenic patients,
over 80% of the items regarding relationship with part-
ner and parental role were ‘not applicable’, as well as
over 50% of items relating to occupation. It should
be noted that among NAP and AP patients too, the
items most frequently ‘not applicable’ were found in
parental role and relationship with partner, though
toa lesserdegree than
Of the patients assessed, 218 (55%) agreed to give a
venous blood sample for DNA analysis. Regarding
ethnicity, 198 patients were Caucasian (91% from
Italy and 9% from Eastern Europe, mainly Romania),
nine were Black Africans, six North Africans and five
were of other origins (two Chinese, two Brazilians,
one Indian). This sample included 47 (22%) patients
with schizophrenia (F20), 127 (58%) with non schizo-
phrenic NAP (F21–F29) and 44 (20%) with AP (F30–
F32). The frequency of first-degree relatives with a his-
tory of psychosis was explored using the FIGS and
compared in the three diagnostic groups. The FIGS
was completed by 291 subjects (100% of the subjects
Table 2. Baseline socio-demographic characteristics by main diagnostic category (n=397)
SCZ (n= 88)
AP (n= 80)
Gender (1 missing)
Age (years) (2 missing)
Educational level (163 missing)
Low (primary-middle school)
High (secondary school, university)
Marital status (178 missing)
Widowed, separated, divorced
Living condition (159 missing)
With partner and/or children
With other relatives
Working status (162 missing)
Housewife. student. retired
Nationality (1 missing)
61.5 53.534.3 0.000
SCZ=schizophrenia, NAP=non affective psychoses, AP= affective psychoses
294 A. Lasalvia et al.
Table 3. Baseline mean scores and frequency distribution of symptom levels for the PANSS subscales (moderate/severe symptoms >3.5) and PANSS items (moderate/severe symptoms ≥4) (n=397)
(ANOVA and Chi-square)
SCZ (n=88)NAP (n= 229) AP (n= 80)
symptoms (%)Mean (S.D.)
symptoms (%)Mean (S.D.)
Passive social withdrawal
Difficulty in abstract
Lack of spontaneity
Mannerisms and posturing
Unusual thought content
Psychosis Incident Cohort Outcome Study (PICOS)
from whom blood samples were obtained). The preva-
lence of first-degree relatives with a history of psycho-
sis was 8.5% in the schizophrenic group, 15% in the
non-schizophrenic NAP group and 13.6% in the AP
group. The prevalence of first-degree relatives with a
history of other psychiatric disorders was 36.2% in
the schizophrenic group, 42.5% in non-schizophrenic
NAP group and 43.2% in the AP group. Moreover,
142 first-degree relatives of patients assessed in
PICOS (78% of relatives approached) also gave a
blood sample for the DNA analysis: specifically, 76
were mothers, 56 fathers, 10 brothers or sisters; 50
trios were also available. In addition, 514 healthy con-
trol subjects selected from a population similar to the
patients in ethnicity and area of residence were
recruited from the Blood Transfusion Service at the
Verona University Hospital and were genotyped.
A sub-sample of 116 subjects was approached for
the neurological examination. Of these, 29 were
excluded due to ethnicity and 19 refused the examin-
ation. Consequently, 68 subjects were assessed using
MRI and neuropsychological data
Eighty-three patients of those approached (mean age
31.02, S.D. 9.59; 36 females and 47 males) were enrolled
in Module 3 at baseline. After at least 1 year, 39
patients (mean age 33.23, S.D. 9.30; 17 females, 22
males) repeated MRI and 34 (mean age 33.32, S.D.
9.47; 15 females, 19 males) of them also completed
the battery of neuropsychological tests.
All the MRI and cognitive data were subsequently
transferred to a PC workstation. Region of Interest
(ROI) structural analyses, voxel-wise investigation of
gray matter density and exploration of white matter
microstructure will be implemented using specific
This study gave an overview of the background and the
methodology of PICOS, a large population-based epide-
miological study of FEP patients receiving care from
public mental health services located within a broad
area of the Veneto region. This report also provided
results of the recruitment process and of the 1- and
2-year follow-up evaluations and gave a preliminary
account of baseline findings on the demographic, diag-
nostic and clinical characteristics of the study sample.
PICOS presents a number of strengths compared
with previous research on FEP patients. First, it was
conducted on the largest catchment area ever reported
in theliterature, covering76% oftheoverall
Table 3. Continued
NAP (n= 229)
AP (n= 80)
Lack of judgment and
Disturbance of volition
Poor impulse control
Active social avoidance
PANSS total score
296A. Lasalvia et al.
Table 4. Baseline DAS mean scores and frequency distribution of disability levels (n=334) (DAS items: ‘severe/very severe disability’: ≥3; DAS total score, ‘severe disability’: >3
SCZ (n=73)NAP (n=192)AP (n=69)
Friction in social
72 2.37 (1.58)45.2183 1.88 (1.51)31.8 63 1.98 (1.34)31.9 0.059 0.104
102.20 (1.40) 6.8 702.19 (1.46) 16.1322.09 (1.09)15.9 0.947 0.133
6 1.83 (1.17)
482.17 (1.31) 24.71451.74 (1.51) 25.0511.78 (1.30) 21.7 0.2020.860
severe disability (%)nMean
severe disability (%)n Mean
severe disability (%)
DAS total score 73 2.46 34.21921.97 17.769 2.01 15.9 0.009 0.007
Psychosis Incident Cohort Outcome Study (PICOS)
population of the Veneto region, corresponding to over
3 million inhabitants. No previous study has been per-
formed on such a large population or has covered such
a broad geographical area (over 12 000 square kilo-
metres). Second, PICOS was conducted by examining
a large epidemiologically-based cohort of FEP patients,
composed of both AP and NAP, so as to reduce the
sampling. Third, this study provided information on
one of the largest epidemiological FEP samples to
date; moreover, unlike clinical trials, the present
study imposed no selection criteria and made no
attempt to influence treatment (as such, the findings
of PICOS provide a more accurate picture of routine
treatment of out-patients than is possible from clinical
trials). Fourth, this study aimed to monitor the course
of illness over the short and medium term (i.e. 1, 2 and
5 years) in an area with relatively low mobility. Fifth,
PICOS was carried out in ‘real world’ public mental
health services which have been operational for several
years – an approach that obviated the limitations of
research programmes run in dedicated research
centres. Sixth, this study included an extensive set of
environmental, clinical, psychosocial and neurobiolo-
gical variables, measured in both patients and their
family members. Seventh, this study investigated the
relationship between genetic patterns and clinical
and social characteristics of FEP patients, both at the
cross-sectional and longitudinal level and explored
possible correlations with neurobiological data drawn
from both structural and functional MRI. Eighth, an
extensive and thorough assessment of service and
treatment variables was also undertaken, with a
specific emphasis on the contextual factors characteris-
ing each treatment setting (including staff burnout,
staff quality of life and emotional atmosphere of men-
tal health services) which are assumed to impact on
patients’ outcomes. Ninth, evaluations were conducted
by local mental health service staff, specifically trained
in the use of a set of well-known standardized assess-
researchers: mental health staff who were systemati-
cally involved in the assessment process demonstrated
that it is feasible to implement a carefully developed
routine outcome assessment in mental health services
by involving healthcare providers and at the same
time to guarantee a satisfactory quality of data col-
lected, provided that training in the correct use of the
standardized instruments and regular checks on the
quality of data are conducted.
This study also has some limitations. Specifically,
the patients’ DUP information was self-reported and
not corroborated by ‘objective’ standardized evalu-
ation. Moreover, it was not always possible to ask
adjustment and this type of information was also fre-
quently self-reported. In addition, only some of the
PICOS sites provided a number of patients in line
with the number of expected cases and could therefore
be considered representative of all FEP patients treated
in the overall PICOS catchment area. It is, however,
noteworthy that analyses separately conducted on
patients recruited in ‘non-representative sites’ yielded
no patterns significantly different from those found
in the overall study sample, which shows a good
level of stability of this study’s results (Bertani et al.
2012). Finally, PICOS substantially recruited FEP
patients who had been treated within the public sector
(with the exception of two small private specialist hos-
pitals located near Verona); it is therefore likely that
the patients going to private clinicians or private facili-
ties would have been excluded. However, this should
not be considered a major problem, since previous
research has shown that in the Veneto only a negligible
fraction of psychotic patients are treated in private hos-
pitals or in private practice alone and that it is stan-
dard practice for a GP to refer all psychosis cases to
the public mental health services (Amaddeo et al.
Preliminary findings indicate that: (1) a project of
this type is feasible; (2) the participation rate is accep-
table; (3) the demographic characteristics of the sample
cover a broad spectrum, and (4) the clinical presenta-
tions are heterogeneous, both before and at the time
of the first service contact.
This study has outlined the characteristics of a care-
fully characterized sample of young people presenting
their first episode of psychosis to a range of treatment
facilities in an epidemiologically-based catchment
area. This paper serves as an introduction to a complex
longitudinal project. Further longitudinal examination
will help to confirm the diagnoses, check for change in
diagnosis and provide far more detailed information
about the variation of psychopathology and outcome.
PICOS will also chart the course of illness and its
predictors. Identification of specific predictors of
course and outcome in FEP patients is expected to have
considerable benefits in clinical practice. Early identifi-
cation of poor responders to treatment would allow
timely adjustments to management programmes. In
addition, as some predictors are modifiable, they may
provide specific treatment targets. Unfortunately, most
of the predictors so far identified in the literature, such
as DUP, pre-morbid functioning and family history are
not ‘modifiable’ predictors for patients suffering from
psychosis (Nasrallah et al. 2011). Thus, the challenge is
to identify significant individual predictors that can be
nitive behavioral therapy for early psychosis) and
psycho-educational treatment programmes also show
298A. Lasalvia et al.
sustained interventions) (Fowler et al. 2011; Jackson et al.
2011; Onwumere et al. 2011). In short, we would advo-
cate that future outcome studies be designed more pro-
grammatically by including and testing potentially
‘modifiable’ risk factors that can subsequently be evalu-
ated in experimental clinical research (Bromet et al.
2005). PICOS was designed with the aim of making a
substantial contribution to these important research
and clinical questions. It is our hope that the research
strategies adopted in PICOS will enhance the conver-
gence of methodologies across ongoing and future
studies on FEP patients.
This study was supported by the Ricerca Sanitaria
Finalizzata 2004, Giunta Regionale del Veneto with a
grant to Prof M. Ruggeri, Ricerca Sanitaria Finalizzata
2005, Giunta Regionale del Veneto with a grant to Dr
A. Lasalvia, and by the Fondazione Cariverona,
which provideda 3-year
Collaborating Centre for Research and Training in
Mental Health and Service Organization at the
University of Verona, directed by Prof M. Tansella.
The grant (‘Promoting research to improve quality of
care. The Verona WHO Centre for mental health
research’) supports the main research projects of the
Epidemiology and Mental Health Economics (Head:
Prof F. Amaddeo); Clinical Psychopharmacology &
Drug Epidemiology (Head:
Environmental, Clinical and Genetic Determinants of
Outcome of Mental Disorders (Head: Prof M. Ruggeri).
grant tothe WHO
Dr C. Barbui);
Declaration of interests
All authors declare that they have no conflicts of
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Appendix. The PICOS-VENETO group
A. Lasalvia, M. Bertani, C. Bonetto, P. Brambilla,
S. Tosato, D. Cristofalo, G. Marrella, S. Bissoli,
M. Zanoni, C. Perlini, A. Ferro, S. Cerruti, M. Bellani,
V. Marinelli, G. Rambaldelli.
STAFF: M. TansellaM. Ruggeri,
COLLABORATING SITES: Bassano del Grappa: P. Tito,
M.Lunardon, F. Gava,
M. Paliotto, L. Roggia. Thiene: A. Danieli, C. Poloni,
M.R. Altiero, F. Piazza. Monteccchio M.: E. Ceccato,
C. Busana, A. Campi, A. Zanconato. Vicenza 1 UO:
302 A. Lasalvia et al.
P. Zamorani, R. Binotto, A. Caneva, E. Lazzarin, Download full-text
G. Zordan. Vicenza 2 UO: C. Dolce, G.B. Fanchin,
C. Negro. Vicenza 3 UO: F. Gardellin, M. Crestale,
L. Paiola, A. Sale. Pieve di Soligo: I. Morandin,
E. Biondi, A. Cordella G. Favaretto, S. Geatti,
J. Spessotto, R. Penelope, L. Grando, M. Sgnaolin,
C. Tozzini, G. Visentin, L. Schiavon. Portogruaro: B.
Gentile, M.G. Bolacchi, L. Marzotto, F. Moni, L. Rossi.
San Donà di Piave: I. Amalric, C. Miceli, M.R. De
Zordo, L. Ramon, S. Russo. Venezia: R. Rossi,
G. Casagrande,V. De
F. Ramaciotti. Mirano: V. Marangon, G. Coppola,
A. Marcolin, P. Meneghini, F. Sbraccia, C. Segato.
M. Cutugno, L. Meneghetti, L. Longhin, B. Paoleschi.
Cittadella: D. Scalabrin, L. Antonello, A. Purgato,
G. Santucci, C. Tosin, R. Volpato, R. Zurlo. Padova 2
De Rossi, G.Zanatta,
Riolo, L. Cappellari,
L. Pavan, M. Semenzin, L. Sifari, F. Zorzi. Rovigo:
M.M. Martucci, N. Magno, G. Meloni, E. Toniolo.
Adria: M. Pavanati, E. Destro, L. Finotti. Verona 1
Serv.: R. Fiorio, A. Marsilio, N. Pedrocco, P. Pollola.
Verona 2 Serv.: L. Lazzarotto, F. Nosè, P. Rossin,
V. Vivenza. Verona 3 Serv.: A. Lasalvia, M. Bertani,
S. Bissoli, K. De Santi, G. Marrella, R. Mazzoncini,
M. Ruggeri. Verona 4 Serv.: A. Urbani, L. Bianchi,
G. Carcereri, L. Lunardi, G. Migliorini, G. Perdonà,
C. Piazza. Legnago: D. Lamonaca, G. D’Agostini
I. Boggian, G. Piccione, E. Saladini. Domegliara: F.
Gomez, S. Frazzingaro. Isola della Scala: S. Nicolaou,
L. Cordioli, G. Bertolazzi, V. Pagliuca. Villa Santa
Chiara: M. Abate, M. Bortolomasi, M. Giacopuzzi,
M. Segala. Villa Santa Giuliana: F. De Nardi,
F. Basetto, C. Bernardis, A. Bezzetto, M. Santi.
Psychosis Incident Cohort Outcome Study (PICOS)303