Institute of Psychiatry, Kings College, London, UK
Universidad Nacional Pedro Henriquez Ureña (UNPHU), Santo Domingo, Dominican Republic
Chinese University of Hong Kong, Hong Kong, SAR
University of Liverpool, Liverpool, UK
Institute of Psychiatry, Kings College, London, UK
University of São Paulo, São Paulo, Brazil
National Institute of Mental Health and Neurological Sciences, Bangalore, India
the 10/66 Dementia Research Group
Correspondence: Professor Martin Prince, Institute of Psychiatry, De Crespigny Park, London SE5 8AF, UK. Tel: +44 20 7848 0136; fax: +44 20 7277 0283; e-mail: m.prince{at}iop.kcl.ac.uk
![]() |
ABSTRACT |
---|
![]() ![]() ![]() ![]() ![]() ![]() ![]() ![]() ![]() |
---|
Aims To assess the validity of GMS/AGECAT organicity and depression diagnoses in 26 centres in India, China, Latin America and Africa.
Method We studied 2941 persons aged 60 years and over: 742 people
with dementia and three groups free of dementia (697 with depression, 719 with
high and 783 with low levels of education). Local clinicians diagnosed
dementia (DSMIV) and depression (MontgomeryÅsberg
Depression Rating Scale score 18).
Results For dementia diagnosis GMS/AGECAT performed well in many centres but educational bias was evident. Specificity was poor in India and sensitivity sub-optimal in Latin America. A predictive algorithm excluding certain orientation items but including interviewer judgements improved upon the AGECAT algorithm. For depression, sensitivity was high. The EUROD depression scale, derived from GMS items using European data, has a similar factor structure in Latin America, India and, to a lesser extent, China.
Conclusions Valid, comprehensive mental status assessment across cultures seems achievable in principle.
![]() |
INTRODUCTION |
---|
![]() ![]() ![]() ![]() ![]() ![]() ![]() ![]() ![]() |
---|
![]() |
METHOD |
---|
![]() ![]() ![]() ![]() ![]() ![]() ![]() ![]() ![]() |
---|
Measures
All study instruments were translated and back-translated by bilingual
local investigators and the resulting local language version was reviewed by
local key informants to check its face validity. The GMS is a 25-50 min
clinical interview generating, from a computerised algorithm (AGE-CAT), nine
diagnostic clusters: organicity (dementia and other organic brain syndromes),
schizophrenia (and related psychoses), mania, neurotic depression, psychotic
depression, hypochondriasis, phobias, obsessional neurosis and anxiety
neurosis. A diagnostic confidence level for each syndrome ranges from 0 (no
symptoms) to 5 (very severely affected). Levels 3 and greater represent likely
cases, a degree of severity warranting professional intervention; levels 1 and
2 are sub-cases. Stage 1 diagnoses are then organised into final stage 2
diagnoses on the basis of precedence determined by a hierarchically structured
algorithm. We used the original A3 version of the GMS. A briefer B3
community version of the GMS omits those sections that assess
syndromes with a low prevalence in the general community: mania,
obsessive-compulsive disorder, hypochondriasis and some ratings of
hallu-cinations and delusions. It is possible to generate B3 AGECAT diagnoses
from A3 data-sets as if the briefer interview had been administered
instead.
A subset of 12 GMS items contribute particularly towards the determination of the stage 1 organicity diagnostic confidence level. These comprise tests of cognitive ability (knowledge of date of birth and age; discrepancy between stated date of birth and age; orientation to day, month, year and address; recall of name of interviewer; name of their countrys current and previous political leader) and two judgements made by the interviewer (presence of memory deficit, and problems with memory worse than problems with thinking). Twelve symptoms of depression in the GMS (depression, pessimism, wishing death, guilt, sleep, interest, irritability, appetite, fatigue, concentration, enjoyment, tearfulness) are used to generate the EURO-D 12-item depression symptom scale (Prince et al, 1999). The EURO-D was internally consistent and captured the essence of its parent instrument. Across Europe a two-factor solution seemed appropriate: depression, tearfulness and wishing to die loaded on the first factor (affective suffering); and loss of interest, poor concentration and lack of enjoyment loaded on the second factor (motivation).
Training
All centres were trained in the use of the GMS. M.P. and J.C. trained the
Chinese and Indian centres, using English. For Latin America the Brazilian
(Portuguese-speaking) and Hispanic 10/66 network coordinators were trained by
M.P., using English. They subsequently trained investigators from the 14 Latin
American centres using their own languages. Over 2-3 days, each trainee viewed
and co-rated two training tapes, completed and rated a supervised training
interview and co-rated a further four to six training interviews. This
represented a necessary compression of the more conventional 5-day training
period for the GMS.
Analyses
Dementia diagnosis
Depression diagnosis
We estimated in each region:
![]() |
RESULTS |
---|
![]() ![]() ![]() ![]() ![]() ![]() ![]() ![]() ![]() |
---|
Dementia
At regional level, the GMS-A3/AGECAT stage 2 organicity rating has
reasonable validity against the gold standard clinical diagnosis of dementia
(Table 1). Sensitivity appears
to be better in Indian and Chinese centres than in Latin American. The
false-positive rate among those with little education is worse in India.
However, at centre level the performance is patchy. In Thrissur and Goa in
Southern India, although sensitivity is excellent, one-half and two-thirds,
respectively, of the least well educated are misdiagnosed. In Latin America in
Venezuela, Argentina, Chile and Mexico (Guadalajara) less than half of
dementia cases are correctly identified. The GMS-B3 stage 2 organicity rating
was identical to the A3 rating in most centres and is therefore not cited
here. Where it differed significantly, sensitivity was superior with little or
no decline in specificity. Thus, in Guadalajara, sensitivity with version B3
was 50% against 13% for A3, in Chile it was 67% compared with 42% and in
Argentina it was 57% compared with 50%.
|
|
|
Depression
The sensitivity of the GMS/AGECAT stage 1 diagnosis of depression for the
MADRS-defined depression case criterion was close to 90% in each of the three
main regions (Table 4). This
figure dropped to around 70-80% in AGECAT stage 2, mainly because the
depressive symptoms had been trumped by the organicity (dementia) ratings in
the hierarchical diagnosis. Because dementia was an exclusion criterion for
selection into the depression group, this suggested misclassification by the
stage 2 AGECAT algorithm. The high levels of apparent comorbidity in the
dementia case groups are noteworthy, as is the apparent high proportion of
those with depression in the high- and low-education control groups in Latin
America and the Caribbean compared with Indian and Chinese centres. Case-level
depression was neither screened for nor excluded from the high- and
low-education or dementia groups, so we could not estimate the specificity of
the AGECAT depression diagnosis.
|
The distribution of the EURO-D scale, within diagnostic groups, was similar
across the three main regions (Table
4). In each region the mean scores were much higher in the
depression group than in the dementia or high- and low-education control
groups. Internal consistency (Cronbachs ) was universally
satisfactory. For India it was 0.91 (range for centres: 0.87-0.95), for Latin
America and the Caribbean it was 0.83 (range for centres: 0.64-0.91) and for
China and south-east Asia (both centres) it was 0.88. The other two regions
were represented by only one centre each Anambra in Africa
(
=0.93) and Moscow in Russia (
=0.86). Principal component
analysis was attempted for three regions: India; China and south-east Asia;
and Latin America and the Caribbean. Two factor solutions were applied in each
region following inspection of scree plots. Similar factors were extracted for
India and for Latin America and the Caribbean (see
Table 5), conforming to the
affective suffering (depression, suicidality, tearfulness) and motivation
(enjoyment, interest) factors previously reported for EURO-D
(Prince et al, 1999).
In the Chinese centres all of these items loaded on a single factor, whereas
the second factor was characterised by guilt and pessimism.
|
Dementia
Across the developing-country centres included in this study, the GMS was
highly effective at discriminating between dementia cases and high-education
controls, therefore the data presented here are entirely consistent with
earlier reports of the satisfactory validity of GMS/AGECAT when used in
well-educated developed-country populations
(Livingston et al,
1990; Collinghan et
al, 1993). It was in this context that the GMS was first
developed and the AGECAT algorithm calibrated. In the
Medical Research Council Cognitive Function
and Ageing Study (MRC CFAS; 1998) the age-specific prevalence of
GMS/AGECAT organicity was very similar to that consistently reported from
other major European and North American population-based surveys.
In developing countries the GMS is a useful adjunct to dementia diagnosis. Our earlier analyses have demonstrated that it adds to the discriminating power of an algorithm, including informant report of decline in cognitive and functional ability (from the CSI-D) and cognitive testing (from the CSI-D and the CERAD ten-word list learning test) (Prince et al, 2003). More detailed findings presented here underline a tendency for the GMS to overdiagnose dementia in low-education groups in some but not all centres, and for a relative insensitivity to the presence of dementia in others. Given that the items contributing to the AGECAT organicity algorithm can be used to generate an algorithm that is much less educationally biased, one can infer that, in Latin America, AGECAT gives more weight to some of those items that we have identified as relatively educationally biased and gives less weight to items that are sensitive to the presence of dementia.
Our data also suggest that the briefer B3 community version of the GMS may, paradoxically, be a more valid assessment for dementia than the more comprehensive GMS-A3. In a few centres it would appear that ratings for the sections excluded from B3 (mania, obsessive-compulsive disorder, hypochondriasis and some ratings of hallu-cinations and delusions) were sub-optimal, giving rise to implausible diagnoses. Thus, in Guadalajara, Mexico, 43% of all dementia true cases were rated by stage 2 as cases of mania. Similar but less extreme problems were noted for some other Latin American centres. Extensive training was provided in all Latin American centres by the regional coordinator but it was not possible logistically after training to supervise directly the conduct of the research in each and every centre. Our collective experience as trainers is that those elements of the GMS-A3 version omitted in the B3 are the most problematic with respect to achieving reliable and accurate ratings, particularly with non-clinical interviewers. Given the low prevalence of these symptoms in community samples it would seem advisable to use the B3 version.
Depression
There is ample evidence from our data for the core validity of the AGECAT
depression algorithm, at least with respect to its sensitivity to the
relatively severe form of depression implied by our independent-clinician
inclusion criterion of a MADRS score of 18 or over. It is possible that
applying the diagnostic hierarchy in stage 2 may lead to misclassification of
depression as dementia. Alternatively, given the typically high rates of
dementia incidence in cases clinically diagnosed as depressive pseudodementia,
false positives may reflect an incipient dementia process that
was not apparent to the independent clinician recruiting the depression cases.
Misclassification will be more marked in low-education samples, and use of the
AGECAT patch should again remedy this problem. Alternatively,
this pitfall may be avoided by using instead the non-hierarchical AGECAT stage
1 diagnosis; this strategy also permits analysis of comorbidity with dementia,
which our data demonstrate to be a phenomenon prevalent in all of the
countries and cultures under study.
The EURO-D scale, derived from just 12 GMS items and extensively validated across Europe, would seem to have similar internal validity properties in other cultures. The underlying two-factor solutions for the Indian and Latin American centres were both similar to each other and generally concordant with those derived previously across the 14 EURODEP European centres. The factor solution for the Chinese centres was somewhat different but difficult to interpret, given the small numbers studied.
![]() |
DISCUSSION |
---|
![]() ![]() ![]() ![]() ![]() ![]() ![]() ![]() ![]() |
---|
More work is required to clarify the cross-cultural validity of GMS/AGECAT. This certainly should include the predictive validity of the organicity rating for future clinical deterioration. Clinicopathological correlation studies are superficially attractive but problematic. In the UK MRC CFAS study, GMS/AGECAT organicity diagnosis predicted the presence upon autopsy of neuropathological features associated with the most prevalent dementia sub-types Alzheimers disease, vascular dementia, Lewy-body dementia and frontotemporal dementia (Medical Research Council Cognitive Function and Ageing Study, 2001). However, these features were also prevalent among those who did not have an AGECAT organicity diagnosis in vivo. This may reflect upon the suitability of these pathological indicators as gold standards for clinical dementia diagnosis rather than on the specificity of the GMS/AGECAT algorithm.
![]() |
APPENDIX |
---|
![]() ![]() ![]() ![]() ![]() ![]() ![]() ![]() ![]() |
---|
Coordinating Centre
Professor Martin Prince, 10/66 Coordinator, Institute of Psychiatry,
London; Ms Seema Quraishi, 10/66 Administrator, Institute of Psychiatry,
London; Professor John Copeland, University of Liverpool; Dr Michael Dewey,
Institute of Psychiatry, London.
10/66 India (Regional Coordinator Additional Professor Mathew Varghese)
Bangalore: Professor Mathew Varghese, Dr Srikala Bharath, NIMHANS,
Bangalore; Chennai (SCARF): Ms Latha Srinivasan, Dr R. Thara,
Schizophrenia Research Foundation; Chennai (VHS): Mr Ravi Samuel, Dr
E. S. Krishnamoorthy, Voluntary Health Services; Goa: Dr Vikram
Patel, Sangath, Dr Amit Dias, Goa Medical College; Hyderabad: Dr K.
Chandrasekhar, Dr M. Ajay Verma, Heritage Hospitals; Thrissur:
Assistant Professor K. S. Shaji, Professor K. Praveen Lal, Medical College,
Thrissur; Vellore: Professor K.S. Jacob, Dr Arockia Philip Raj,
Christian Medical College.
10/66 China and ES Asia (Regional Coordinator Professor Helen Chiu)
China (Beijing): Professor Li Shuran, Dr Jin Liu, Beijing
University; China (Hong Kong SAR): Professor Linda Lam, Dr Teresa
Chan, Chinese University of Hong Kong; Taiwan (Taipei): Dr Shen-Ing
Liu, Mackay Memorial Hospital, Professor P. K. Yip, National Taiwan University
Hospital.
10/66 Latin America and Caribbean (Regional Coordinators Dr Daisy Acosta (Dominican Republic) and Dr Marcia Scazufca (Brazil))
Argentina (Buenos Aires): Dr Raúl Luciano Arizaga, Hospital
Santojanni (GCBA), Dr Ricardo F. Allegri, Hospital Zubizarreta (GBCA Y
CONICET); Brazil (São Paulo): Dr Marcia Scazufca, Dr Paulo
Rossi Menezes, Universidade de São Paulo; Brazil (Botucatu):
Dr Ana Teresa de A.R. Cerquerira, Botucatu Medical School, UNESP; Brazil
(São Jose do Rio Preto): M. Cristina O. S. Miyazaki, Neide A.
Micelli Domingos, FAMERP Medical School; Chile
(Santiago/Concepción/Valparaiso): Dr Patricio Fuentes, G. Hospital
Del Salvador, Santiago, Dr Pilar Quoroga, L. Universidad de Concepción;
Concepción; Cuba (Havana): Dr Juan de J. Llibre Rodriguez, Dr
Hector Bayarre Vea, Facultad de Medicina Finlay-Albarran,
Universidad Medica de la Habana; Dominican Republic (Santo Domingo):
Dr Daisy Acosta, Universidad Nacional Pedro Henriquez Ureña (UNPHU),
Lic. Guillermina Rodriguez, Asociación; Dominicana de Alzheimer (ADA);
Guatemala (Guatemala City): Dr Carlos A. Mayorga Ruiz, Dr Mario Luna
de Floran; Mexico (Mexico City): Dr Ana Luisa Sosa, Dr Yaneth
Rodriguez Agudelo, National Institute of Neurology and Neurosurgery;
Mexico (Guadalajara):Dr Genaro G. Ortiz, Lab
Desarrollo/Envejecimiento, CIBO/IMSS, Dr Elva D. Arias-Merino, Gerontologia,
Universidad de Guadalajara; Panama (Panama City): Dr Gloriela R. de
Alba, Paitilla Medical Center Hospital, Dr Gloria Grimaldo, Santa Fe Hospital;
Peru (Lima): Dr Mariella Guerra, Instituto Nacional de Salud Mental
Honorio Delgado-Hideyo Noguchi, Universidad Peruana Cauetano
Heredia, M. Victor González, Instituto Peruano de Seguridad Social,
ESSALUD; Uruguay (Montevideo): Dr Roberto Ventura, Dr Nair Raciope,
University of Uruguay; Venezuela (Caracas): Dr Aquiles Salas,
Universidad Central de Venezuela, Faculty of Medicine, Dr Ciro Gaona
Yánez, Fundación; Alzheimers Venezuela.
10/66 Africa
Nigeria (Anambra): Dr Richard Uwakwe, Nnamdi Azikiwe University
Teaching Hospital.
10/66 Russia
Moscow (Russia): Professor Svetlana Gavrilova, Dr Grigory Jarikov,
Alzheimers Disease Research Center, Mental Health Research Center of
Russian Academy of Medical Sciences.
![]() |
Clinical Implications and Limitations |
---|
![]() ![]() ![]() ![]() ![]() ![]() ![]() ![]() ![]() |
---|
LIMITATIONS
![]() |
REFERENCES |
---|
![]() ![]() ![]() ![]() ![]() ![]() ![]() ![]() ![]() |
---|
Collinghan, G., MacDonald, A., Herzberg, J., et al (1993) An evaluation of the multidisciplinary approach to psychiatric diagnosis in elderly people. BMJ, 306, 821 -824.[Medline]
Copeland, J. R., Dewey, M. E. & Griffith-Jones, H. M. (1986) A computerised psychiatric diagnostic system and case nomenclature for elderly subjects: GMS and AGECAT. Psychological Medicine, 16, 89 -99.[Medline]
Copeland, J. R., Prince, M., Wilson, K. C., et al (2002) The Geriatric Mental State Examination in the 21st century. International Journal of Geriatric Psychiatry, 17, 729 -732.[CrossRef][Medline]
Ganguli, M., Chandra, V. & Gilbey, J. (1996) Cognitive test performance in a community-based non demented elderly sample in rural India: the Indo-US cross national dementia epidemiology study. International Psychogeriatrics, 8, 507-524.[Medline]
Hall, K. S., Hendrie, H. H., Brittain, H. M., et al (1993) The development of a dementia screening interview in two distinct languages. International Journal of Methods in Psychiatric Research, 3, 1 -28.
Livingston, G., Sax, K., Willison, J., et al (1990) The Gospel Oak Study stage II: the diagnosis of dementia in the community. Psychological Medicine, 20, 137 -146.[Medline]
Medical Research Council Cognitive Function and Ageing Study (MRC CFAS) (1998) Cognitive function and dementia in six areas of England and Wales: the distribution of MMSE and prevalence of GMS organicity level in the MRC CFA Study. Psychological Medicine, 28, 319 -335.[CrossRef][Medline]
Medical Research Council Cognitive Function and Ageing Study Neuropathology Group (MRC CFAS) (2001) Pathological correlates of late-onset dementia in a multicentre, community-based population in England and Wales. Lancet, 357, 169 -175.[CrossRef][Medline]
Montgomery, S. A. & Åsberg, M. (1979) A new depression scale designed to be sensitive to change. British Journal of Psychiatry, 134, 382 -389.[Abstract]
Morris, J. C. (1993) The Clinical Dementia Rating (CDR): current version and scoring rules. Neurology, 43, 2412 -2414.[Medline]
Prince, M. J., Reischies, F., Beekman, A. T. F., et al (1999) The development of the EUROD scale a European Union initiative to compare symptoms of depression in 14 European centres. British Journal of Psychiatry, 174, 330 -338.[Abstract]
Prince, M., Acosta, D., Chiu, H., et al (2003) Dementia diagnosis in developing countries: a cross-cultural validation study. Lancet, 361, 909 -917.[CrossRef][Medline]
Received for publication May 7, 2003. Revision received May 27, 2004. Accepted for publication June 26, 2004.
HOME | HELP | FEEDBACK | SUBSCRIPTIONS | ARCHIVE | SEARCH | TABLE OF CONTENTS |
Psychiatric Bulletin | Advances in Psychiatric Treatment | All RCPsych Journals |