Copyright # Munksgaard 2000

Acta Psychiatr Scand 2000: 101: 21±28
Printed in UK. All rights reserved

ACTA PSYCHIATRICA
SCANDINAVICAISSN 0902-4441

Subtyping depression by clinical features:
the Australasian database
Parker G, Roy K, Hadzi-Pavlovic D, Mitchell P, Wilhelm K,
Menkes DB, Snowdon J, Loo C, Schweitzer I. Subtyping depression byclinical features: the Australasian database.
Acta Psychiatr Scand 2000: 101: 21±28. # Munksgaard 2000.

G. Parker1, K. Roy1,
D. Hadzi-Pavlovic1, P. Mitchell1,
K. Wilhelm1, D. B. Menkes2,
J. Snowdon3, C. Loo1, I. Schweitzer4
1

Objective: To distinguish psychotic, melancholic and a residual nonmelancholic class on the basis of clinical features alone. Previous studies
at our Mood Disorders Unit (MDU) favour a hierarchical model, withthe classes able to be distinguished by two speci®c clinical features, but
any such intramural study risks rater bias and requires external
replication.
Method: This replication study involved 27 Australasian psychiatrist
raters, thus extending the sample and raters beyond the MDU facility.
They collected clinical feature data using a standardized assessment withprecoded rating options. A psychotic depression (PD) class was derived
by respecting DSM-IV decision rules while a cluster analysis
distinguished melancholic (MEL) and non-melancholic classes.
Results: The MELs were distinguished virtually entirely by the presenceof signi®cant psychomotor disturbance (PMD), as rated by theobservationally based CORE measure, with over-representation on only
three of an extensive set of `endogeneity symptoms'.
Conclusion: In comparison to PMD, endogeneity symptoms appear to bepoor indicators of `melancholic' type, confounding typology withseverity. Results again support the hierarchical model.

Introduction

Over the last decade, research at the Mood
Disorders Unit (MDU) in Sydney has focusedon distinguishing psychotic depression and melancholic depression from a more heterogeneous
residue of non-melancholic depressive disorders
on the basis of clinical features. Early studies
identi®ed the importance of behaviourally rated
psychomotor disturbance (PMD) as a `core'feature distinguishing psychotic and melancholic
depression from non-melancholic depression,
with the ®nal development of the then-labelled`CORE' measure of PMD occurring in the
CORE-II study of 413 patients (1, 2). The
measure has three scales, assessing a central`non-interactiveness' (or cognitive processing)dimension, as well as motoric `retardation' and`agitation', with the ®nal CORE score being thesummed scale scores.

School of Psychiatry, University of New South Wales,
Kensington, NSW, 2Department of Psychological
Medicine, Dunedin Hospital, Dunedin, New Zealand,
3
Department of Psychogeriatrics, Rozelle Hospital,
Rozelle, NSW and 4The Melbourne Clinic,
130 Church Street, Richmond, Victoria, Australia

Key words: depression subtyping;melancholic and non-melancholic depression;
CORE measure
Prof. G. Parker, School of Psychiatry,
University of New South Wales,
Prince of Wales Hospital, Randwick 2031,
Australia
Accepted for publication September 15, 1999

In the development study (2), a total CORE
score of 8 or more was found to be an ef®cient
cut-off score for distinguishing melancholicfrom non-melancholic depression. We examined
whether PMD (as so de®ned) was both `necessary
and suf®cient' for the de®nition of melancholia(3). `Necessary' meant that all those with `true'melancholia would score above the cut-off score
and, examined against three measures of melancholia: (respectively, in relation to DSM-III-R,
Newcastle and MDU `clinical' criteria) 51%, 73%
and 85% of the sample met that criterion Ð areasonable but not perfect result. `Suf®cient'meant that the CORE score alone would predict
diagnostic allocation without any additionalbene®t from the addition of a set of endogeneity
symptoms. Analyses revealed that, once the
CORE score was entered as a predictor, diagnostic class allocation was not improved by
21

Parker et al.
adding the endogeneity symptom predictor set ina logistic regression analysis. It was slightly
improved, however, in relation to DSM-III-R
allocations when analysed using a neural network(4).
Subsequently, the MDU recruited anothersample of 269 depressed in-patients and outpatients (the PAL study). As in the CORE-II
study, each of the so-called endogeneity symptoms
failed to show distinct speci®city to the psychotic,
melancholic or non-melancholic depressive classes(5). For example, anhedonia was reported by 97%,
100% and 88% of those class members, respectively, suggesting that it was an ubiquitous feature.
Several other endogeneity symptoms showed agradient (e.g. terminal insomnia being reported by
67%, 53% and 43%, respectively) in being morecommon in psychotic and melancholic depression,
but still common in non-melancholic depression. If
any such endogeneity symptom has true speci®city
to melancholia, it should not have been reported
by any non-melancholic subject. We therefore
argued (as in the previous study) that theendogeneity symptoms more re¯ect variation in
the severity or expression of the underlying moodstate component shared across all depressive
disorders rather than having any distinct subtyping
capacity.
The distinction between melancholic and nonmelancholic depression in this PAL sample wasagain driven principally by observationally rated
psychomotor disturbance (PMD) Ð as quanti®edby the CORE measure. PMD strongly met both`necessary and suf®cient' criteria here, suggesting its
impressive ef®ciency as a discriminator as well as
indicating that endogeneity symptoms wereredundant in distinguishing melancholic and nonmelancholic depression once CORE scores wereconsidered. Distinction of psychotic from melancholic depression in the CORE-II study was driven
by the speci®c presence of psychotic features, but
assisted by signi®cantly greater PMD, and asigni®cantly greater chance of the subjects reporting
appetite/weight loss, terminal insomnia and constipation. In the PAL study, however, only thepresence of psychotic features and the greater
severity of PMD distinguished psychotic frommelancholic depression.
If con®rmed, the identi®cation of features havingclass speci®city, as against merely being overrepresented in psychotic and melancholic depression, allows a hierarchical model (detailed later) for
distinguishing the three classes more incisively,
while also assisting the development of ef®cient
subtyping algorithms.
As both studies have involved ratings by MDU
research psychiatrists only, it is possible that22

results may have been driven by a response bias.
Thus, if the MDU psychiatrists were suf®ciently
sophisticated as clinicians to validly distinguishmelancholic and non-melancholic depression, theymight `rate up' the presence of PMD in theformer group and `rate down' in the second
group, so contriving the suggested ef®ciency of
CORE-rated PMD. As a consequence, we reexamine the postulates using a wider sample ofAustralasian psychiatrist raters, and examine
whether earlier results are replicated. Here (inour Australasian Data Base, or ADB, study),
regional psychiatric clinicians and researchers
were requested to collect clinical data on patientswith a clinical depressive episode and according toa structured format. The dataset required CORE
measure ratings, but the non-MDU psychiatrists
did not receive any direct training in the CORE
system. The derived database thus provides athird (and presumably more heterogeneous)
sample for identifying those clinical features thatmight best distinguish psychotic, melancholic andnon-melancholic depression.
Material and methods
Procedure and sample

Interest in participating in the ADB was canvassed via direct mailout and given publicity in avariety of professional meetings. Those psychiatrists expressing interest received written details
about the study design, protocols, potential usesof the database and a complete interview kit. The
psychiatrists were requested to enrol (consecutively, randomly or on some regular basis such as
day/week) patients presenting with a signi®cantdepressive disorder (either ®rst episode or a ®rst
presentation of a new episode). Contributing
patients and psychiatrists were given ID numbers,
and no identifying details were collected on any
patient, while Ethics Committee clearances wereobtained from relevant institutions. Recruitment
occurred over a 2-year period, with a total of 385
forms returned. Substantively incomplete data
resulted in 16 forms being excluded, with current
analyses undertaken on the remaining 369 subjects
contributed by 27 psychiatrists (with ®ve fully
trained in the use of the CORE measure).
The dataset`Form A' was completed by the patient and soughtdata addressing sociodemographic variables together with information on medical problems,
lifetime depression, mood state items for the current
depressive episode and details on depressive symptoms judged as able to be assessed by self-report.

Subtyping depression by clinical features
Some of these data allowed binary ratings (e.g. yes
vs. no) and some used dimensional ratings (e.g.
assessing the persistence of any feature across theday, or its severity, with the latter generally using
four-point rating options).
`Form B' was completed by the psychiatrist. In
addition to obtaining further details on lifetime
depressive and (any) manic episodes, items
requiring sophisticated clinical assessment were
included (e.g. family history of depression,
symptoms such as `distinct quality', psychotic
features, whether the depression was primary or
secondary). For a number of items (e.g. loss ofinterest, anhedonia, guilt, shame), precise de®nitions were given, although four-point rating
options of severity or persistence were preserved.
In addition, categorical rating options were
provided for some items. For example `overvalued ideas' were distinguished from `possibledelusions'. Identi®cation of any delusion thenrequired choosing between mood congruent andmood incongruent options, while a category
allowed for delusions that occurred `in the context
of a distinct borderline personality'. A similar
subdivision occurred for hallucinations. Guilt was®rst rated as being present or not. If present,
assessment required judging whether it was
explainable in terms of the patient's personality
and/or current circumstances. If more severe thanwarranted by those factors, it could then be rated
as `severe' (but not marked by morbid remorse),
at the level of an `over-valued idea', or at a`delusional' level.
The interviewing psychiatrist was required tocomplete the CORE measure of PMD according
to the standardized printed instructions (2) andcomplete a 17-item Hamilton form (6), while thepatient was requested to complete the AUSSI(Affect Underpinned by Severity and Social
Impairment) State Depression Measure (7), a
measure of both mood severity and disability
with a combined total score. Psychiatrists were
not required to make a clinical or formal
diagnosis. Subsequently, an algorithm allowed
DSM-IV diagnoses to be generated on returned
datasets.

Results
Characteristics of the sample

The 369 subjects comprised 235 (64%) females, witha mean age of 45.7 (SD 16.3) years; with 95 (26%)
being single, 175 (47%) being married or in a defacto relationship and 99 (27%) being separated,divorced or widowed. Seventy-seven (21%) were in
full-time employment, 90 (24%) were involved inhome duties or had part-time employment, 14 (4%)
were students, 110 (30%) were receiving a pension
or sickness bene®ts, 31 (8%) were retired and 47(13%) were unemployed. The average duration of
the current depressive episode was 75 (SD 150)
weeks, 365 (99%) judged that their mood state wasassociated with signi®cant functional impairment
and 280 (76%) judged that they were at or near theepisode nadir in terms of severity. Forty-three (12%)
were judged as having had a previous manic,
hypomanic or mixed episode `de®nitely' or as`highly probable', and a further 46 (13%) as`possibly' having such a bipolar history. A family
history of likely psychotic or melancholic depression was recorded for 161 (44%) of the subjects.
DSM-IV diagnoses

All 369 patients met the symptom required by
DSM-IV for major depression; 386 (98.6%) had
been depressed for a minimum of 2 weeks, one for
only 1 week, while duration data were missing foranother four patients. Of those with major depression, 28 (7.6%) had the speci®er of `psychotic
features', 119 (32.2%) the speci®er of `melancholicfeatures' and 269 (72.9%) had a `recurrent' major
depression.
Distinguishing those with psychotic depression

As the DSM-IV criteria for major depression withpsychotic features include delusions and/or hallucinations, and as these features were the only ones toshow speci®city in the PAL study, we assigned 28
subjects to such a `psychotic depression' (PD) classby the presence of one or both features.
Distinguishing melancholic from non-melancholic depression

Statistical analyses

In contrast to our two previous studies Ð where wehave used latent class analysis Ð here (after deletingthe 28 PDs) we used a K-means cluster analysis(with a two-cluster solution imposed) as ourprincipal strategy to distinguish melancholic andnon-melancholic depressed subjects. Comparison ofclinical features was made by t-tests and chi-squareanalyses.

For the cluster analysis, six `endogeneity symptoms' (i.e. non-reactive mood, loss of interest or
anticipatory anhedonia, consummatory anhedonia, appetite and/or weight loss, diurnal moodvariation, terminal insomnia) examined in ourprevious studies were included in the endogeneity
item set, in addition to the total CORE score
quantifying PMD. That analysis assigned 98(26.6%) to a putative melancholic (`MEL') clusterand 243 (65.8%) to the residual non-melancholic23Parker et al.
(`non-MEL') cluster. Assignment was predictably
in agreement with DSM-IV assignment for thePDs. DSM-IV and cluster solution-assignment tomelancholic and non-melancholic classes were inmoderate agreement only (i.e. of the non-MELs,
75% were so assigned by DSM-IV rules, and of
the MELs, 66% were so assigned by DSM-IV),giving an overall classi®cation agreement of
72.4%. In Table 1 and subsequent tables, we
examine for (i) overall group differences, (ii)differences between PD and MEL subjects and(iii) differences between MEL and non-MEL
subjects. Such analyses provide an opportunity
to determine whether our class `cleavage' rules
generate clinical pictures compatible with the`givens' for psychotic and melancholic depression.
Because of the large number of analyses, weapplied a Bonferroni correction to determine

whether or not differences were signi®cant. No
differences were established between PDs and MELs
for Table 1 variables. Comparison of MELs andnon-MELs established that the non-MELs wereyounger (and presumably with that age difference
driving differences evident on marital status andemployment variables), developed their ®rst depressive episode (and received initial treatment) at a
younger age and had had more depressive episodes.
Group differences were not identi®ed on the family
history of depression or life event variables, or inreporting an antecedent life event stressor. The PDs
scored non-signi®cantly higher on the Hamilton
than the MELs (presumably re¯ecting the psychotic
items in the Hamilton scale) who, in turn, scoredhigher than the non-MELs (again presumablyre¯ecting inclusion of the observable psychomotor
items in the Hamilton scale). The non-MELs scored

Table 1. Comparisons of demographic and depression history variables across psychotic, melancholic and non-melancholic classes
Class

Variable
Socio-demographic
Age
Gender: female
Marital status
Married/de facto
Separated/divorced
WidowedNever married
Employment
Full time
Part time
Home duties
P/t work+home duties
Student
Pensioner/sickness bene®ts
Retired
Unemployed
Years education completed
Depression history
Family history (dep/bipolar/psych)
Age at ®rst depression episodeAge ®rst treated for depression
Age ®rst clinically signi®cant dep
Number of lifetime episodes
Hospitalized for previous episodeSuicide attempt Ð past episodeLife events
Stressful events in 12 months prior dep
Severity of stressful life events
Severity of acute stressors
Severity of enduring circumstances
Depression severity
AUSSI mood
AUSSI disability
AUSSI total
Hamilton

Psychotic (N=28)

Melancholic (N=98)

%

%

Mean

55.9

%

53.0
60.2

64.6

42.9
14.3
25.0
17.9

50.0
21.5
12.2
16.3

46.9
18.9
3.7
30.5

10.7
0.0
14.3
0.0
7.1
46.4
14.3
7.1

17.3
6.1
16.3
0.0
1.0
31.6
16.3
11.2

23.5
11.1
9.1
6.2
4.5
27.2
4.5
14.0

10.7
37.0

11.6
52.1

39.1
36.7
41.1
7.5
63.0
21.4

Contrast
Psych vs. MEL

MEL vs. non-MEL

t=6.2**

x2=14.6*

13.4

x2=28.0**
t=x3.8**

25.6
29.8
28.6
18.0

t=4.3**
t=4.4**
t=5.1**
t=x3.6**

42.1
34.0
39.0
38.0
7.7

54.1
20.4

64.3

Mean

41.6

67.9

44.0
25.1

77.6

78.6

3.3
2.3
2.1

3.4
2.5
2.3

3.4
2.5
2.4

12.3
9.9
22.2
27.7

12.6
9.9
22.4
24.9

11.5
7.8
19.4
18.7

Under Bonferroni correction, *f0.025; **f0.005; ***f0.0005.

24

Mean

Non-melancholic (N=243)

t=4.4**
t=3.1**
t=9.2***

Subtyping depression by clinical features
the prevalence data for the PDs and MELs werevery similar Ð both for commonly regarded
endogeneity symptoms as well as for psychomotor
disturbance when assessed as a symptom.
We then examined the extent to which PMD
was speci®c to melancholia. A latent class analysisof the CORE signs revealed a similar pattern ofprobability loadings as revealed in the CORE-IIand PAL studies. This is an important ®nding inindicating a similar structure to the CORE signs
across independent samples. A logistic regression
suggested that a CORE cut-off of 9 was optimal
in distinguishing two subgroups on the basis of
CORE scores, thus almost identical to the 8 ormore cut-off derived in the CORE-II study. In
this ADB sample, comparison of the MELs andnon-MELs demonstrates distinctly higher CORE
scores in the MELs (i.e. 16.4 vs. 4.1). As our
optimal cut-off in this study (of 9 or more) was
close to that derived in the CORE-II development
study, we preserved the latter (i.e. 8 or more) here

as less depressed on the AUSSI Disability Scale andtotal score.
In Table 2 we tabulate clinical feature data to
determine those features distinguishing the derived
classes. Most prevalence data for dimensional items
contrast those who scored `3' or `2' (i.e. severe or
moderate), against those who returned or received a`1' (mild) or `0' (absent) rating Ð as inclusion of a
`1' rating made some endogeneity symptoms
virtually ubiquitous across the sample.
Comparison of the PDs and MELs indicatesthat delusions (whether examined as an overall
category, or within subcategories of guilt, shameor the sense of feeling `deserving of punishment')
were essentially ubiquitous to the PD class (i.e.
delusions being elicited in 86% and hallucinations
evident in 32% of the PDs). In addition, the PDs
returned higher CORE scores than the MELs
(total scores=19.9 vs. 16.4), contributed principally by higher agitation and non-interactiveness
CORE scale scores. For the remaining features,

Table 2. Comparisons of symptoms and signs for current depression episode across groups where `Psychotic' group based on delusions/hallucinations, then `Melancholic' and`Non-melancholic' depression derived from cluster analysis
Classes

Variable
Symptoms
Appetite/weight loss
Mood worse a.m.
Anhedonia
Terminal insomnia
Loss of interest
Non-reactive moodNon-varying mood
Feels physically slowed
Feels restless
Mood not like bereavement
Loss interest in sex
Unpleasant thoughts
Concentration dif®cultDif®cult to make decisions
Delusions
Hallucinations
Guilt, severe
Guilt, over-valued idea
Guilt, delusional
Shame, delusional
Deserving of punishment, over-valued idea
Deserving of punishment, delusional
Constipated before medication taken
Signs
CORE: scale scores
Non-interactivenessRetardation
Agitation
Total CORE mean score
COREo8

Psychotic

Melancholic

Non-melancholic(N=28)(N=98)(N=243)

Total sample prevalence(%) or mean

%

68.4%
32.0%
55.9%
58.8%
83.4%
67.4%
18.0%
78.5%
23.6%
66.6%
65.1%
70.1%
78.3%
73.4%
6.5%
2.4%
20.3%
8.4%
2.7%
2.2%
6.0%
1.6%
14.2%

81.5
30.8
60.7
66.7
82.1
82.1
42.3
71.4
25.0
64.3
40.7
57.1
71.4
64.3
85.7
32.1
7.1
14.3
35.7
28.6
17.9
21.4
21.4

3.15
3.60
1.85
8.60
45.8%

Mean

%

72.4
32.0
57.1
61.5
93.9
77.6
24.7
86.7
25.5
73.5
71.1
75.5
80.6
78.6
0.0
0.0
26.5
19.4
0.0
0.0
13.3
0.0
17.3

7.8
7.9
4.2
19.9
100

Mean

%

100

MEL vs.
non-MELx2=10.7**x2=8.0*x2=7.3*>x2=103.8***x2=33.9***x2=24.8***2

x =38.0***x2=29.9***x2=19.9***x2=22.0***

1.4
1.6
1.2
4.1
17.7

Psych vs.
MEL

Mean

65.3
32.1
54.8
56.8
79.3
61.5
12.8
76.0
22.7
64.0
65.4
69.4
78.1
72.3
0.0
0.0
19.3
3.3
0.0
0.0
1.6
0.0
12.0

6.2
7.3
2.9
16.4

Contrast

t=3.7***
t=3.5***
t=3.8***

t=20.9***t=20.6***t=7.9***
t=24.2***x2=195.1***

Under Bonferroni correction, *f0.025; **f0.005; ***f0.0005.

25

Parker et al.
Ð with all PDs and all MELs in this ADB
study scoring above that cut-off, against 18% of
the assigned non-MELs, suggesting quite impressive speci®city of PMD to melancholic andpsychotic depression. By contrast, when psychomotor disturbance was assessed as a symptom,
no differences were evident across the MELs
and non-MELs Ð with 87% and 76% respectively
reporting that they felt slowed down, and 25%
and 23% respectively reporting feeling restless.
Most of the endogeneity symptoms showeddistinct prevalences in both the MEL and nonMEL clusters, indicating lack of speci®city tomelancholia. While several were signi®cantly more
likely in the MELs (i.e. loss of interest, nonreactive mood, non-varying mood, over-valued
ideas of guilt and being deserving of punishment),others (i.e. loss of appetite and weight, diurnal
mood variation, anhedonia, terminal insomnia)
were non-differentiating.
As in our two previous studies (CORE-II and
PAL), we sought to examine the comparative
utility of CORE-rated PMD and endogeneity
symptoms to the de®nition of melancholia. In the
CORE-II study, we ®rst examined for associations
between a re®ned set of endogeneity symptoms(i.e. appetite and/or weight loss; mood and/or
energy worse in the morning; anhedonia; terminal
insomnia; loss of interest; and non-reactive mood)and total CORE scores, with individual correlation coef®cients ranging from 0.25 to 0.50 (andthus suggesting some overlap or shared variance).
In this study, all such associations were trivial or
non-existent for those features. The lack of any
association between CORE scores and the endogeneity symptom set indicated that there was noshared variance, and that there was little likelihood of the symptom set predicting melancholicstatus. In further analyses, we regarded the six
endogeneity symptoms as forming a polythetic set(i.e. each symptom essentially being regarded asof equivalent weight to the other). We thussought, as in recent DSM manuals, to determine
the optimal cut-off in symptom numbers fordifferentiation. All possible cut-off scores (ranging
from 1 or more to all six symptoms) suggested
poor differentiation (quanti®ed by low kappa
coef®cients, ranging from 0.00 to 0.09). That is,no cut-off could be derived in symptom numbersthat differentiated MEL or non-MEL status toany degree. By comparison, using the criterion ofa CORE score of 8 or more (derived in the
CORE-II study as a cut-off score for MEL andnon-MEL de®ned by latent class analysis) produced a kappa coef®cient of 0.73. Thus, PMD
demonstrated strong speci®city, while all endogeneity symptom sets lacked speci®city.
26

Discussion

As noted in the introduction, we have previously
reported two studies similarly seeking distinction
between psychotic, melancholic and a residual nonmelancholic class on the basis of clinical features. In
both, distinction between the two latter classes has
appeared largely determined by the presence ofobserver-rated psychomotor disturbance (PMD) as
assessed by the CORE measure. The concern aboutsuch studies is one of observer bias Ð that the
MDU research psychiatrists might rate the CORE
measure so as to derive such a result, whether
conscious or not of any such rating bias. The
identi®ed speci®city of CORE-rated PMD to themelancholic class established in this study argues
against any MDU bias determining idiosyncratic
results in the earlier study. A second concern about
the two previous samples is that they have been
derived from patients attending our tertiary referral
MDU, obviously weighting samples to patients withsevere and treatment-resistant conditions, andpresumably increasing the representation of thosewith true psychotic and melancholic depression.
By establishing the ADB or clinical panel, wesought to widen clinical assessment outside MDU
clinicians and obtain a more heterogeneous sample.
A limitation was that most of the non-MDU
psychiatrists were not trained in the CORE
system. The CORE rating sheet, however, had
precise descriptors of each item together with clearly
identi®ed anchor points. While 22 non-MDU
psychiatrists did contribute patients to our current
sample, there was the informal impression ofdisproportionately higher returns from academic
psychiatrists working in services assessing patients
not necessarily that different from the MDU
service. Nevertheless, if we compare the identi®ed
prevalence of the three classes across the two MDU
samples (CORE-II and PAL) with the current ADB
sample, we ®nd respective prevalences of 10%, 11%
and 8% for the PDs, and 45%, 34% and 27% for the
MELs. Thus, the current sample strategy did resultin a lower representation of putative PDs andMELs. Other variables constant across the studies(e.g. mean Hamilton scores, lifetime number of
episodes, etc.) also suggested that the current
sample was (overall) slightly less severely ill anddisabled over time by their depressive disorders.
The current study differed methodologically inthree principal ways. For many clinical featuresassessed by the rating psychiatrist, we provided
extremely precise de®nitions of terms such as`anticipatory anhedonia' and went to some trouble
to distinguish between qualitative and quantitative
nuances of features such as guilt, which can range
from normal guilt to over-valued ideas to delusional

Subtyping depression by clinical featuresintensity. Secondly, as our previous studies havesuggested that most depressed subjects (and not
merely `melancholic' ones) will af®rm nearly all ofthe `endogeneity symptoms', we imposed a minimum severity rating of `moderate' before mostdimensionally assessed symptoms could be rated
positively. Thirdly, we used a cluster analysis
to distinguish melancholic and non-melancholicclasses, whereas we have principally used a latentclass analytic strategy in the two previous samples.
We respected the DSM-IV de®nition of psychotic
depression to determine PD status, as this had been
supported in our previous PAL study. While DSMIV views psychotic depression as a subtype of major
depression, we view it a subtype of melancholia (2),although we have not resolved whether it is a more
severe or differing expression of melancholia.
Current results also favour viewing it as having amelancholic base. Thus, our PDs resembled the
MELs on a wide range of variables (including age,
age of onset, number of lifetime episodes and on theprevalence of most of the endogeneity symptoms).
The PD class differed from MEL by only one
dimensional variable (i.e. higher mean CORE
scores) and by several unique Ð albeit de®nitionalÐ categorical variables (i.e. delusions and hallucinations), with delusions about guilt and shame
showing impressive speci®city. Differentiation in
CORE scores was not as distinctive as in the earlier
CORE-II and PAL studies, suggesting that sometrue PDs may have been assigned to the MEL class,an issue considered shortly. The PDs did not differ
from the MELs in the prevalence of over-valued
ideas. This could re¯ect reality or, more likely, thedif®culty in operationalizing over-valued ideas on
either a categorical or dimensional basis Ð and weclearly favour the latter explanation. Such a pattern(i.e. PD de®ned by psychotic features, having more
severe PMD than rated in MEL subjects, and not
differing by severity of endogeneity symptoms) iscompletely compatible with our PAL data results.
This pattern is, however, not compatible with ourearlier CORE-II study, where our analyses identi®ed some PD subjects who denied any psychotic
features but had severe or profound PMD. There
we hypothesized that their PMD was so severe (i.e.
making them mute or otherwise uncommunicative)that they could not admit to psychotic features(which were later established after improvement
had occurred), and suggested that very severe PMD
should encourage the clinician to be suspicious of
PD status, with severe PMD thus acting as apossible diagnostic proxy. While we pursued such a
possibility in this study (by undertaking a numberof cluster analyses seeking to distinguish the PDs
and MELs), lack of support suggested that weshould alternately respect the DSM-IV decisionrules. However, previous formal classi®catory
systems (see 2) have allowed such a diagnosis to
be made on the basis of depressive stupor alone. It is
possible that there were no such patients in the ADB
sample, or that our clinician raters may havepursued psychotic features assiduously in thosewith severe PMD.
Our cluster-derived MELs differed from theresidual non-MELs on a number of the givens forthat disorder (see 2). They were older (currently andat ®rst episode), had a more severe depression,tended to have been more likely to have been
hospitalized, and were more likely to have received
ECT (this and other treatment nuances will beconsidered in another publication), although there
was no suggestion that antecedent life-event stressors were less common (as would be expected if
melancholia is viewed as an endogenous depression). Such differentiation on those illness course
variables offers some support (in the absence of any
de®nitive gold standard) for the view that the cluster
analytic strategy did separate out melancholic andnon-melancholic depressive classes. In terms ofdifferential clinical features, the groups were thenmost clearly distinguished by the presence andseverity of PMD, and somewhat by the overrepresentation of three endogeneity symptoms (i.e.
loss of interest, non-reactive mood and non-varyingmood). Nevertheless, the presence of the ®rst two
symptoms was also quite substantive in the nonMELs (i.e. 79% and 61%). This ®nding, together
with the lack of differentiation effected by the otherendogeneity symptoms examined, again challenges
the long assumed capacity of such symptoms tode®ne endogeneous/melancholic depression. As in
our previous studies we suggest that most symptoms
re¯ect depression severity per se, or if they dopossess any greater likelihood of occurrence inmelancholia, then it is either slight or confoundedby dif®culties in measurement.
The data from this and our two preceding studies
again support a hierarchical or tiered model for
distinguishing three substantive depressive classeson the basis of clinical features alone, as detailed
recently (5). The model is based on cleavage
between those classes (i.e. psychotic, melancholicand non-melancholic) being driven entirely by thepresence of class-speci®c features. Thus the residual
non-melancholic class has no class-speci®c features,with any intraclass variation being driven only bymood state severity and by varying contributions of
personality or temperament style (i.e. a spectrum
model). Proceeding to the next class (melancholia)
the mood disorder is more severe, but the class isde®ned by a speci®c feature (i.e. observable PMD).
Proceeding to the next class (i.e. psychotic depression) both the mood disorder and PMD are more
27

Parker et al.
severe, but the class is de®ned by the speci®cpresence of psychotic features. Thus, the system
concedes long-standing recognition of varying
mood severity but Ð as the mood state is nonspeci®c and common to all the depressive classes Ð
does not seek to differentiate on such a variable. We
would argue that failure to recognize that latter
point has confounded and limited previous attempts
to de®ne melancholia and certainly confounds thecurrent DSM-IV de®nition of melancholia, with theendogeneity symptoms more measuring depression
severity rather than depressive type. We supported
this argument in our PAL study (5) by comparing
the capacity of our CORE-based with DSM-IV
decision rules for melancholia, and demonstrated
clear superiority to the former approach against arange of clinical validators. Such an argument
would nevertheless be advanced by further studies
testing the comparative capacities of the contrastingmodels to demonstrate differences across a range ofneurobiological measures and response to various
antidepressant treatments.
Acknowledgements
We thank the NHMRC (Program Grant 993208) and threepharmaceutical companies (P®zer, Wyeth and Eli Lilly) for
funding, support staff (Kerrie Eyers, Gemma Gladstone,
Christine Taylor and Yvonne Foy), as well as the many other28

psychiatrists who contributed patients to this study (i.e. MariePaule Austin, Gary Barnes, Philip Boyce, Simon Byrne, Robert
Eidus, David Grounds, Scott Henderson, Ian Hickie, Alison
Hickey, Bernard Hughson, Adrien Keller, Ohn Kyaw, Cathy
Mason, Mark Montebello, Russell Pargiter, Robert Parker,
Elizabeth Scott, Paul Skerritt, Cathy Stringer and Kipling
Walker).

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