- Email: [email protected]
Prediction of outcome in drug dependence
Addict&
Behmiors. Vol
I. pp. 103-I IO.
Pergamon Press 1’976. Prmted in Great Britain.
PREDICTION
OF OUTCOME
IN DRUG
DEPENDENCE*
Bo FRYKHOLM,LARS-M. GUNNE and B. HUITFELDT University of Uppsala Abstract-Two-hundred and fifty subjects dependent on amphetamine (88%) or opiates (12%) were subjected to a time-programmed follow-up at 2,4,6 weeks, 3,6 months and 1,2 and 3 yr after discharge from the clinic. Follow-up data were compared with socio-psychiatric background data obtained by standardized forms and (based on information from 200 cases) a prognostic instrument was constructed by stepwise discriminant analysis according to Dixon (1973). The instrument was validated on a random sample of 50 selected from the total material of 250 patients and was found to contain a prediction power of 66-88% according to different systems of classification. Two background variables stood out as the most important ones, the first describing the degree of involvement with drugs (“number of injections”) and the second describing number of remaining social contacts with drug-free persons (“contacts with relatives”). These two variables nearly exhausted the predictive potential of the prognostic instrument.
For a proper evaluation of the outcome of treatment a thorough knowledge of the natural course of drug dependence is of importance. Various attempts to classify drug addicts according to the severity of their condition have been undertaken with the aim of predicting the individual prognosis (O’Donnell, 1965). In the present paper a prognostic instrument was constructed, based on an analysis of 200 drug-dependent subjects. The analysis consisted of (1) a prospective study of the relapse rate during the early follow-up period and (2) socio-psychiatric background data obtained by standardized forms during the preceding inpatient period. Furthermore, the prognostic instrument was validated on another 50 patients. MATERIAL
AND METHODS
The total material consisted of 250 former inpatients of a clinic specialized for the treatment of drug dependence (174 male, 76 female). These patients constitute the total number of abusers of central stimulants and opiates admitted for treatment in a drugfree rehabilitation program during 1 Jan., 1970-31 March, 1971 (the collecting period). Figure 1 illustrates the age distribution and number of admissions per patient during this time. Certain small groups of drug abusers treated at our clinic during the same period were not included in the study, namely 10 abusers of cannabis or barbiturates and 17 opiate addicts receiving methadone maintenance treatment. Eighty-two per cent of the patients were mainly dependent on central stimulants and 18% on opiates. Ninety-seven per cent were intravenous, versus 3% oral abusers. The average duration of drug abuse was 4.3 yr (range 0.5-13 yr). During the inpatient period the patients were interviewed and their history was recorded by means of a standardized questionnaire, which allows computer analysis. Twentysix background variables from the questionnaire (Table 1) were studied for their relevance for the short-term prognosis. Data from variables 12-20 were pooled forming one variable (psychiatric problems during childhood). Follow-up data were collected continuously according to a special system. Each patient was asked to give the address and telephone number of a (preferably non-addicted) friend, relative, employer or other person able to give information about him after he had left the hospital. After 2, 4 and 6 weeks, 3 and 6 months and then yearly the patient and whenever necessary also the contact person was approached by a nurse and information was gathered regarding work, residence and drug-taking among the patients. For patients admitted more than once during the collecting period the results after the last stay are given. Answers were classified in categories A-D (Fig. 2). Among category Al (drugfree since discharge) were also included patients who admitted occasional use of drugs (less than one administration/month). As a first step towards establishing a prognostic instrument two systems of classification were *Requests for reprints should be sent to Lars-M. Gunne, Psychiatric Uppsala, Sweden.
Research Center, Uileraker Hospital, S-750 17
104
B.
FRYKHOLM
rt al.
100 -
60
-
t? & 2
60.
B
S z 20 -
2
LO.L 20 200
E .= “a 5
30
40
50
Age
-
100
i z
2
50 .
150. o-i 2 Number
Fig. I. Age distribution
3
4
5
-
of treatment
(above) and number of treatment (below).
6
7
6
9
IO
11
pwmds per putrent periods per patient during the collecting period
Table I. Background variables as obtained by medical record using standardized forms. Data from variables 12-20 were pooled forming one variable (psychiatric problems during childhood) Demographic data I. Sex 2. Age 3. Professional occupation Drug 4. 5. 6. 7. 8.
(months)
data Age at drug debut Years of drug abuse Number of intravenous injections Number of drugs abused Earlier drug dependence (alcohol included, nicotine excluded)
Criminality 9. Violations of narcotics IO. Crimes of violence Il. Other crimes
law
Sociopsychiatric data I?. Measures taken bv children’s welfare department 13. Taken out of family before 3 years of age 14. Broken home 15. Abuse of alcohol with parent(s) 16. Psychiatric disturbance with parent(s) 17. Other severe disturbances at home 18. Treated in institution for child psychiatry 19. Problems at school 20. Left school before finishing 8th grade ?I. Psychotic only during periods of drug abuse 2. Psvchotic also during periods of abstinence 23. Time spent in institutions (months) Social 24. ?S. 26.
or temperance
contacts Remaining contacts with relatives Remaining contacts with parole officers, social workers etc. Remaining contacts with drug-free friends
board
Prediction of outcome in drug dependence
[0
No ~ntorrnot~on
105
1
Fig. 2. System of classification of follow-up data.
defined, based on the follow-up
results:
System 1 al. Patients who had stayed drug-free for more than 6 months. b,. Patients who had stayed drug-free for 2 weeks but not 6 months. cl. Patients who had relapsed before 2 weeks. System 2 at. Patients who had remained drug-free for a year. bz. Patients who had relapsed within a year. A random sample of 50 patients were selected from the total material of 250 patients to serve as a test group for validation of the prognostic instrument. The material was distributed in the following way according to the two systems of classification:
System 1 Group used for construction of prognostic instrument al
b, CI Total
Test group used for validation of instrument Total
58 67 15
17 10 23
7s 77 98
200
50
250
System 2 Group used for construction of prognostic instrument
a2
Test group used for validation of instrument Total
bs
36 164
9 41
45 205
Total
200
50
250
Statistical method Background data (Table 1) from the 200 patients used for construction of the instrument were treated according to multiple discriminant analysis. The statistical theory underlying this multivariate statistical method, has been described by Rao (1952). The method gives an estimate of those linear combinations of variables which discriminate best between pre-chosen groups of patients. When background data consist of many interrelated A.B. Vol. 1, No. 2-B
106
B. FRYKHOLMet al
variables it is generally difficult by ordinary discriminant analysis to decide the discriminatory potential of individual variables. In such situations it may be advantageous to work with a stepwise procedure, by which variables are included successively one by one, according to criteria selecting the combination of variables in each step which has a maximal discriminatory power. Such a procedure will deliver information as to which selection of variables contributes most effectively to discrimination by background data. The program packet BMD contains the computer program BMD-07M, which allows such a method of analysis (stepwise discriminant analysis, Dixon 1973). RESULTS
Follow-up of 250 cases Table 2 shows the distribution of cases on various follow-up occasions. A high percentage of cases could be traced and the figure for the group “no information” never exceeded 6.4% (at 3 yr). As many as 39% had a relapse into drugtaking before the first follow-up occasion at 2 weeks after discharge. The solid line in Fig. 3 shows the size of group Al (drug-free since discharge) at different time points. Twenty-nine cases (12%) reached the 3 yr point without relapse. However as many as 67 (27%) were drugfree at the same time point, having recovered spontaneously or after another treatment period (Table 2). For group A (drug-free on follow-up occasion) and group Bl (suspected or verified relapse) the data for living residence and employment are presented in Tables 3 and 4. The results within each group seem to be consistent between the yearly check-ups. Thus in group A about 80% had a stable residence (i.e. had not moved during the last 6 months), whereas in group Bl the corresponding figure was about 30%. Between 65 and 68% of group A had regular employment or were studying, but only 3% of group B 1 were employed. The drugtaking group (B 1) on the other Table 2. Distribution of 250 patients on different followup occasions 2weeks A. Drug-free on follow-up occasion Al. Drug-free since discharge A2. Relapse-spontaneous recovery A3. Rehospitalization-recovery B. Relapse into drugtaking Bl. Suspected or verified relapse B2. In hospital or prison C. Deceased D. No information
4weeks
152 152 0 0 98 92 6 0 0
hweeks
127 127 0 0 123 I IO 13 0 0
115 115 0 0 135 Ill 24 0 0
FOIIOW-UP of 250 drug
(174 mole. Per
3months 102 95 3 4 148 I13 35 0 0
6months 84 75 3 6 166 127 39 0 0
I yr
2yr
3yr
57 45 3 9 189 149 40 4 0
63 34 4 25 166 135 31 6 15
67 29 4 34 160 132 28 7 I6
oddtcts
76 female)
cent drugfree
100
75
50
25
Orugfree
since
discharge
2
3 Years
OJ,
1 P Discharge Fig. 3. Percentage
distribution
,
of patients found to be drug-free on different follow-up occasions discharge from the clinic (time point 0).
after
107
Prediction of outcome in drug dependence Table 3. Percentage distribution of residence and employment in subjects who were drugfree on follow-up occasions (group A in Fig. 2)
Stable residence* Employed or studying Sick insurance benefit Unemployment or social security benefit *Address unchanged
1 Yr (n = 57)
2 yr (n = 63)
3 yr (n = 67)
83 65 26
81 68 22
78 66 21
9
10
13
during last 6 months.
Table 4. Percentage residence and employment in subjects with relapse into drugtaking suspected or verified (group B 1 in Fig. 2)
1yr (n = 149) Stable residence* Employed or studying Sick insurance benefit Unemployment or social security benefit
2yr 3 yr (n = 135) (n = 132)
29 3 75
29 3 76
32 3 73
22
21
24
*Address unchanged during last 6 months.
hand, utilized the state sick insurance as well as unemployment and social security benefits to a much greater extent than the drug-free group. Thus, drug status was highly related to residence and employment variables. Predictive factors in 200 cases Matching the background variables of Table 1 with the follow-up results it was found that for both systems of classification (system 1 and 2) two variables had the best discriminatory potential. One belonged to the “drug data”-category (6. The patient’s self-rating of the number of injections taken according to the following alternatives: no i.v. administration = 0, l-99 injections = 1, 100-999 injections = 2, more than 1000 injections = 3). The second important variable belonged to the category of remaining social contacts (24. “remaining friendly contacts with relatives”). It was found that each of these variables was closely correlated with other variables within the same groups, i.e. the “drug data” and “social contacts” groups respectively. The ranking of the rest of the variables differed much between system 1 and 2 (Table 5). Table 5. Ranking list of background variables obtained by stepwise discriminant analysis of a follow-up material of 250 patients subdivided according to two different systems System 1
System 2
1. Number of i.v. injections 2. Remaining contacts with relatives 3. Remaining contacts with parole officers, social workers 4. 5. 6. 7. 8. 9. 10. 11. 12. 13. 14. 15. 16. 17. 18.
Earlier drug dependence Remaining contacts with drug free friends Professional occupation Number of drugs abused Years of drug abuse Psychotic only during periods of drug abuse Psychotic also during periods of abstinence Other crimes Measures taken by children’s welfare department temperance board Time spent in institutions Crimes of violence Psychiatric problems during childhood Age of drug debut Age Violations of narcotics law
or
Number of i.v. injections Remaining contacts with relatives Measures taken by children’s welfare department temperance board Psychotic only during periods of drug abuse Years of drug abuse Age Earlier drug dependence Age of drug debut Other crimes Professional occupation Crimes of violence Violations of narcotics law
or
Psychotic also during periods of abstinence Remaining contacts with drug free friends Time spent in institutions Number of drugs abused Remaining contacts with parole officers, social workers etc. Psychiatric problems during childhood
B. FRYKHOLMet al.
108
Validation of the prognostic instrument on 50 cases In order to validate the estimated discriminant functions these were used to classify the patients in the test group. The following results were obtained:
System
I According to follow-up data belonging to Total a, c1 h,
By background data classified as
a, b, C!
Total
IO 5 2
0 7 3
0 7 16
10 19 21
17
IO
23
50
System 2 According to follow-up data belonging to Total a2 bz By background data classified as ;r Total
4 5
1 40
5 45
9
41
50
The sum of the frequencies in the main diagonal of the tables above gives the number of correct classifications. For system 1 the correct classifications were 33 (66%) with most of the erroneous classifications in groups adjacent to the correct one. For system 2 the proportion of correct classifications was 88%. DISCUSSION
The results of the present study fall into two different categories: (1) follow-up data and (2) prognostic factors. One possible way to study effects of treatment on relapse behaviour is afforded by repeated contacts during the early follow-up period. It seems likely that percentage figures for drug-free and socially adjusted patients at a later stage, which have been the main interest of most follow-up studies, mainly reflect other characteristics of the material besides treatment effects, e.g. selection of patients and background factors. Our method of time-programmed follow-up has revealed that, particularly during the first year after discharge from the clinic, there were rapid changes in the percentage of drug-free patients in the material. These changes could only be revealed by the time-programmed design, i.e. the patients must be contacted at predetermined time intervals following the discharge of each individual. In this way it was shown that as many as 39% had relapsed within two weeks. On the other hand the curve showing percentage of drug-free at different time points (Fig. 3) indicated, that a year after discharge most of the relapses to be expected had already occurred. The number of patients who were found drug-free at 2 and 3 yr after discharge tented to increase compared with the situation at one year. This is in accordance with Duvall, Locke & Brill (1963) who also recorded a gradual improvement during the late follow-up period. In spite of the fact that our material was dominated by amphetamine abusers (82%), the overall outcome did not seem to differ much from findings in heroin dependent subjects (O’Donnell, 1965). Similar results have been reported earlier in a different material of 74 amphetamine abusers (Gunne, AnggHrd & Jonsson, 1970). As might be expected there was a high correlation between jobs and stable residence on one hand and abstaining from drugs on the other. These findings support the validity of the follow-up data. The second part of the study which dealt with prognostic factors seemed to assign a high prediction potential to two different background variables: one describing the degree of involvement with drugs (“number of injections”) and one dealing with remaining social contacts with non-drug-addicts (“remaining contacts with relatives”). Several other studies using various techniques have emphasized the importance of similar factors. Thus Davies, Shepard & Myers
Prediction of outcome in drug dependence
109
(1951), Straus & Bacon (19_51),Kissin, Rosenblatt & Machover (1968), Gillis & Keet (1969) have stressed the importance of remaining social contacts with non-alcoholic persons for the outcome of alcoholism. The degree of involvement with drugs was labeled as prognostically important in alcoholics (Miller, 1944) and drug addicts (Smith, 1972) since it was found that a periodic type of abuse was prognostically more favourable than daily abuse. Retterstol & Sund (1964) in a study of abusers of sedatives, among other factors found evidence for a better prognosis in cases with a short history of abuse, whereas Anchersen (1947) and Kielholz (1952) found no connection between outcome and the duration of abuse. Haastrup (1973) similarly found evidence for a poor prognosis in subjects who reported to have injected themselves more than one hundred times. It seem possible, however, that the degree of involvement with drugs measured in various ways, has a direct bearing on the prognosis only during a limited period of the drug career. The majority of the patients appearing in the present study had been abusers for 2-5 yr, whereas according to clinical observations the desire to leave the drug habits may appear later. Other reports rather focus on the importance of other factors: older age (Hunt & Odoroff, 1962; Duvall, Locke & Brill, 1963; Paulus, 1968; Glatt, 1969), late drug debut (Lemere, 1953; Brotman & Freedman, 1968) or certain psychological characteristics like high anxiety level (Kaplan & Meyerowitz, 1969; Levy & Tracy, 1971). Certain authors have attributed prognostic significance to a variety of factors selected on the basis of clinical intuition (Prescor, 1941, Tamerin & Neumann, 1971; Cohen & Klein, 1971). However, these factors have not been validated in prospective studies. The technique used in the present study allows an analysis of the discriminatory power of isolated background variables as predictors of outcome. In order to evaluate to what extent background data do better than pure chance it is necessary to determine the probability of correct classifications using a random procedure. If the distribution over groups in the material used for construction of the prognostic instrument are assumed to be valid also in the test group, the probability of correct classification in system 1 is about 33% and in system 2 about 70%. Thus for system 1 there has been a substantial increase in the proportion of correct classifications (from 33 to 66%). The relatively modest increase in the corresponding proportion for system 2 (from 70 to 88%) is mainly due to the fact that the assumed distribution already contains so much information. The results of the statistical analysis, however, should be looked upon as conditional. This means that the inference from the results are valid mainly for the same set up of variables measured and coded as in the present study. This uncertainty makes the importance of individual variables difficult to assess. Except for the two variables ranked highest according to both systems of classification (system 1 and 2) which nearly exhausted the prediction power of the prognostic instrument, the other variables seemed to act more on a joint basis. The practical applications of a prognostic instrument in the treatment of drug dependent subjects can be manifold. A knowledge of the statistical prognosis of cases would facilitate a classification of drug dependent subjects according to the severity of the condition. This may lead to the elaboration of new treatment approaches aiming specifically at subgroups which do not seem to benefit from the present therapeutic programmes. Also in the evaluation of treatment some knowledge of the chances of recovery between groups may allow meaningful comparisons between institutions which receive different selections of patients. Finally some background variables found to be important in our system seem to indicate social deficiencies which might be compensated for by active measures. Thus for instance a lack of social contacts with drug-free people could lead to therapeutic efforts to establish new such relationships. The finding that remaining contacts with relatives influences the outcome, might indicate the importance of family therapy. The present results will be pursued in a future study in an attempt to construct a prognostic instrument for practical clinical use. REFERENCES Anchersen, P., On the prognosis of narcomania (euphomania). (to clarify some problems of narcomania.) Acta Psychiarric Scandanauia, 1947, 22, 153-193. Brotman, R., & Freedman, A., Targets, goals and methods for intervention, US Dept of HEW. A Community Health Approach to Drug Addiction. Washington, D. C.: Government Printing Office, 1%8, 30-39. Cohen, M., & Klein, D. F., Drug abuse in a young psychiatric population. American Journal of Orthopsychiatry, 1971, 40, 448-455.
110
B. FRYKH~LMet al.
Davies, D. L., Shepard, M., & Myers, E., The two-years’ prognosis of 50 alcohol addicts after treatment in hospital. Quarterly Journal of Studies on Alcohol, 1951, 12, 231-260. Dixon, W. .I., BMD Biomedical Computer Programs. Berkeley, Calif.: University of California Press, 1973. Duvall, I., Locke, B. L., & Brill, L., Follow-up study of narcotic drug addicts five years after hospitalization. Public Health Reports, 1%3, 78, 185. Gillis, L. S., & Keet, M., Prognostic factors and treatment results in hospitalized alcoholics. Quarterly Journal of Studies on Alcohol, 1969, 30, 426-437. Glatt, M. M.. Rehabilitation of the addict. Brittish Journal of the Addictions, 1969, 64, 165-182. Gunne, L. M., Anggard, E. & Jonsson, L. E., Blockade of amphetamine effects in human subjects. In Tongue & Tongue (Eds.) I.C.A.A. paper 249, Lausanne, 1970. Haastrup, S., Young Drug Abusers. 350 Patients Interviewed at Admission and Followed Up Three Years Laler. Kopenhamn: Munksgaard, 1973. Hunt, G. H. & Odoroff, M. E., Follow-up study of narcotic drug addicts after hospitalization. Public Health Reports, 1962,77, 41. Kaplan, H. B., & Meyerowitz, J. H., Psychosocial predictors of post-institutional adjustment among male drug addicts. Achives of General Psychiatry, 20, 278-284. Kielholz, P., Behandlung und Prognose des chronischen Morphinismus. Schweiz. med. Wschr, 1952, 82, 1325-1329. Kissin, B., Rosenblatt, S. M. & Machover, S., Prognostic factors in alcoholism. Psychiatric Research Reports, 1968, 24, 22-43. Lemere, F., What happens to alcoholics. American Journal of Psychiatry, 1953, 109, 674-676. Levy, M. & Tracy, F., Prediction of success of drug addicts in outpatient release status based upon a personality inventory. International Journal of the Addictions. 1971, 6, 533-541. Miller, M. M., Prognosis in periodic and daily inebriates. Quarterly Journal of Studies on Alcohol, 1944, 5, 430-433. O’Donnell, J. A., The relapse rate in narcotic addiction: A critique of follow-up studies. In D. M. Wilner & G. G. Kassebaum (Eds.) Narcotics. Los Angeles: University of California Press, 1965. Paulus, I., A comparative study of long-term and short-term withdrawal of narcotic addicts voluntarily seeking comprehensive treatment. British Journal of the Addictions, 1968, 63, 129-141. Pescor, M., Prognosis in drug addiction. American Journal of Psychiatry, 1941. 97, 119-133. Rao, R., Advanced statistical methods in biometric research. New York: John Wiley, 1952. Retterstol, N., & Sund, A., Drug Addiction and Habituation (Norwegian Monographs on Medical Science) Oslo: Universitetsforlaget, 1964. Smith, D. E., A physician’s view of the adolescent drug scene. In C. J. D. Zarafonetis (Ed.) Drug Abuse: Proceedings of the lntemational Conference. New York: Lea & Febiger, 1972. Straus, R., & Bacon, S. D., Alcoholism and social stability: A study of occupational integration in 2023 male clinic patients. Quarterly Journal of Studies on Alcohol, 1951, 12, 231-260. Tamerin, J. S., & Neumann, C. P.. Prognostic factors in the evaluation of addicted individuals, International Pharmacopsychiatry, 1971, 6, 69-76.
Behmiors. Vol
I. pp. 103-I IO.
Pergamon Press 1’976. Prmted in Great Britain.
PREDICTION
OF OUTCOME
IN DRUG
DEPENDENCE*
Bo FRYKHOLM,LARS-M. GUNNE and B. HUITFELDT University of Uppsala Abstract-Two-hundred and fifty subjects dependent on amphetamine (88%) or opiates (12%) were subjected to a time-programmed follow-up at 2,4,6 weeks, 3,6 months and 1,2 and 3 yr after discharge from the clinic. Follow-up data were compared with socio-psychiatric background data obtained by standardized forms and (based on information from 200 cases) a prognostic instrument was constructed by stepwise discriminant analysis according to Dixon (1973). The instrument was validated on a random sample of 50 selected from the total material of 250 patients and was found to contain a prediction power of 66-88% according to different systems of classification. Two background variables stood out as the most important ones, the first describing the degree of involvement with drugs (“number of injections”) and the second describing number of remaining social contacts with drug-free persons (“contacts with relatives”). These two variables nearly exhausted the predictive potential of the prognostic instrument.
For a proper evaluation of the outcome of treatment a thorough knowledge of the natural course of drug dependence is of importance. Various attempts to classify drug addicts according to the severity of their condition have been undertaken with the aim of predicting the individual prognosis (O’Donnell, 1965). In the present paper a prognostic instrument was constructed, based on an analysis of 200 drug-dependent subjects. The analysis consisted of (1) a prospective study of the relapse rate during the early follow-up period and (2) socio-psychiatric background data obtained by standardized forms during the preceding inpatient period. Furthermore, the prognostic instrument was validated on another 50 patients. MATERIAL
AND METHODS
The total material consisted of 250 former inpatients of a clinic specialized for the treatment of drug dependence (174 male, 76 female). These patients constitute the total number of abusers of central stimulants and opiates admitted for treatment in a drugfree rehabilitation program during 1 Jan., 1970-31 March, 1971 (the collecting period). Figure 1 illustrates the age distribution and number of admissions per patient during this time. Certain small groups of drug abusers treated at our clinic during the same period were not included in the study, namely 10 abusers of cannabis or barbiturates and 17 opiate addicts receiving methadone maintenance treatment. Eighty-two per cent of the patients were mainly dependent on central stimulants and 18% on opiates. Ninety-seven per cent were intravenous, versus 3% oral abusers. The average duration of drug abuse was 4.3 yr (range 0.5-13 yr). During the inpatient period the patients were interviewed and their history was recorded by means of a standardized questionnaire, which allows computer analysis. Twentysix background variables from the questionnaire (Table 1) were studied for their relevance for the short-term prognosis. Data from variables 12-20 were pooled forming one variable (psychiatric problems during childhood). Follow-up data were collected continuously according to a special system. Each patient was asked to give the address and telephone number of a (preferably non-addicted) friend, relative, employer or other person able to give information about him after he had left the hospital. After 2, 4 and 6 weeks, 3 and 6 months and then yearly the patient and whenever necessary also the contact person was approached by a nurse and information was gathered regarding work, residence and drug-taking among the patients. For patients admitted more than once during the collecting period the results after the last stay are given. Answers were classified in categories A-D (Fig. 2). Among category Al (drugfree since discharge) were also included patients who admitted occasional use of drugs (less than one administration/month). As a first step towards establishing a prognostic instrument two systems of classification were *Requests for reprints should be sent to Lars-M. Gunne, Psychiatric Uppsala, Sweden.
Research Center, Uileraker Hospital, S-750 17
104
B.
FRYKHOLM
rt al.
100 -
60
-
t? & 2
60.
B
S z 20 -
2
LO.L 20 200
E .= “a 5
30
40
50
Age
-
100
i z
2
50 .
150. o-i 2 Number
Fig. I. Age distribution
3
4
5
-
of treatment
(above) and number of treatment (below).
6
7
6
9
IO
11
pwmds per putrent periods per patient during the collecting period
Table I. Background variables as obtained by medical record using standardized forms. Data from variables 12-20 were pooled forming one variable (psychiatric problems during childhood) Demographic data I. Sex 2. Age 3. Professional occupation Drug 4. 5. 6. 7. 8.
(months)
data Age at drug debut Years of drug abuse Number of intravenous injections Number of drugs abused Earlier drug dependence (alcohol included, nicotine excluded)
Criminality 9. Violations of narcotics IO. Crimes of violence Il. Other crimes
law
Sociopsychiatric data I?. Measures taken bv children’s welfare department 13. Taken out of family before 3 years of age 14. Broken home 15. Abuse of alcohol with parent(s) 16. Psychiatric disturbance with parent(s) 17. Other severe disturbances at home 18. Treated in institution for child psychiatry 19. Problems at school 20. Left school before finishing 8th grade ?I. Psychotic only during periods of drug abuse 2. Psvchotic also during periods of abstinence 23. Time spent in institutions (months) Social 24. ?S. 26.
or temperance
contacts Remaining contacts with relatives Remaining contacts with parole officers, social workers etc. Remaining contacts with drug-free friends
board
Prediction of outcome in drug dependence
[0
No ~ntorrnot~on
105
1
Fig. 2. System of classification of follow-up data.
defined, based on the follow-up
results:
System 1 al. Patients who had stayed drug-free for more than 6 months. b,. Patients who had stayed drug-free for 2 weeks but not 6 months. cl. Patients who had relapsed before 2 weeks. System 2 at. Patients who had remained drug-free for a year. bz. Patients who had relapsed within a year. A random sample of 50 patients were selected from the total material of 250 patients to serve as a test group for validation of the prognostic instrument. The material was distributed in the following way according to the two systems of classification:
System 1 Group used for construction of prognostic instrument al
b, CI Total
Test group used for validation of instrument Total
58 67 15
17 10 23
7s 77 98
200
50
250
System 2 Group used for construction of prognostic instrument
a2
Test group used for validation of instrument Total
bs
36 164
9 41
45 205
Total
200
50
250
Statistical method Background data (Table 1) from the 200 patients used for construction of the instrument were treated according to multiple discriminant analysis. The statistical theory underlying this multivariate statistical method, has been described by Rao (1952). The method gives an estimate of those linear combinations of variables which discriminate best between pre-chosen groups of patients. When background data consist of many interrelated A.B. Vol. 1, No. 2-B
106
B. FRYKHOLMet al
variables it is generally difficult by ordinary discriminant analysis to decide the discriminatory potential of individual variables. In such situations it may be advantageous to work with a stepwise procedure, by which variables are included successively one by one, according to criteria selecting the combination of variables in each step which has a maximal discriminatory power. Such a procedure will deliver information as to which selection of variables contributes most effectively to discrimination by background data. The program packet BMD contains the computer program BMD-07M, which allows such a method of analysis (stepwise discriminant analysis, Dixon 1973). RESULTS
Follow-up of 250 cases Table 2 shows the distribution of cases on various follow-up occasions. A high percentage of cases could be traced and the figure for the group “no information” never exceeded 6.4% (at 3 yr). As many as 39% had a relapse into drugtaking before the first follow-up occasion at 2 weeks after discharge. The solid line in Fig. 3 shows the size of group Al (drug-free since discharge) at different time points. Twenty-nine cases (12%) reached the 3 yr point without relapse. However as many as 67 (27%) were drugfree at the same time point, having recovered spontaneously or after another treatment period (Table 2). For group A (drug-free on follow-up occasion) and group Bl (suspected or verified relapse) the data for living residence and employment are presented in Tables 3 and 4. The results within each group seem to be consistent between the yearly check-ups. Thus in group A about 80% had a stable residence (i.e. had not moved during the last 6 months), whereas in group Bl the corresponding figure was about 30%. Between 65 and 68% of group A had regular employment or were studying, but only 3% of group B 1 were employed. The drugtaking group (B 1) on the other Table 2. Distribution of 250 patients on different followup occasions 2weeks A. Drug-free on follow-up occasion Al. Drug-free since discharge A2. Relapse-spontaneous recovery A3. Rehospitalization-recovery B. Relapse into drugtaking Bl. Suspected or verified relapse B2. In hospital or prison C. Deceased D. No information
4weeks
152 152 0 0 98 92 6 0 0
hweeks
127 127 0 0 123 I IO 13 0 0
115 115 0 0 135 Ill 24 0 0
FOIIOW-UP of 250 drug
(174 mole. Per
3months 102 95 3 4 148 I13 35 0 0
6months 84 75 3 6 166 127 39 0 0
I yr
2yr
3yr
57 45 3 9 189 149 40 4 0
63 34 4 25 166 135 31 6 15
67 29 4 34 160 132 28 7 I6
oddtcts
76 female)
cent drugfree
100
75
50
25
Orugfree
since
discharge
2
3 Years
OJ,
1 P Discharge Fig. 3. Percentage
distribution
,
of patients found to be drug-free on different follow-up occasions discharge from the clinic (time point 0).
after
107
Prediction of outcome in drug dependence Table 3. Percentage distribution of residence and employment in subjects who were drugfree on follow-up occasions (group A in Fig. 2)
Stable residence* Employed or studying Sick insurance benefit Unemployment or social security benefit *Address unchanged
1 Yr (n = 57)
2 yr (n = 63)
3 yr (n = 67)
83 65 26
81 68 22
78 66 21
9
10
13
during last 6 months.
Table 4. Percentage residence and employment in subjects with relapse into drugtaking suspected or verified (group B 1 in Fig. 2)
1yr (n = 149) Stable residence* Employed or studying Sick insurance benefit Unemployment or social security benefit
2yr 3 yr (n = 135) (n = 132)
29 3 75
29 3 76
32 3 73
22
21
24
*Address unchanged during last 6 months.
hand, utilized the state sick insurance as well as unemployment and social security benefits to a much greater extent than the drug-free group. Thus, drug status was highly related to residence and employment variables. Predictive factors in 200 cases Matching the background variables of Table 1 with the follow-up results it was found that for both systems of classification (system 1 and 2) two variables had the best discriminatory potential. One belonged to the “drug data”-category (6. The patient’s self-rating of the number of injections taken according to the following alternatives: no i.v. administration = 0, l-99 injections = 1, 100-999 injections = 2, more than 1000 injections = 3). The second important variable belonged to the category of remaining social contacts (24. “remaining friendly contacts with relatives”). It was found that each of these variables was closely correlated with other variables within the same groups, i.e. the “drug data” and “social contacts” groups respectively. The ranking of the rest of the variables differed much between system 1 and 2 (Table 5). Table 5. Ranking list of background variables obtained by stepwise discriminant analysis of a follow-up material of 250 patients subdivided according to two different systems System 1
System 2
1. Number of i.v. injections 2. Remaining contacts with relatives 3. Remaining contacts with parole officers, social workers 4. 5. 6. 7. 8. 9. 10. 11. 12. 13. 14. 15. 16. 17. 18.
Earlier drug dependence Remaining contacts with drug free friends Professional occupation Number of drugs abused Years of drug abuse Psychotic only during periods of drug abuse Psychotic also during periods of abstinence Other crimes Measures taken by children’s welfare department temperance board Time spent in institutions Crimes of violence Psychiatric problems during childhood Age of drug debut Age Violations of narcotics law
or
Number of i.v. injections Remaining contacts with relatives Measures taken by children’s welfare department temperance board Psychotic only during periods of drug abuse Years of drug abuse Age Earlier drug dependence Age of drug debut Other crimes Professional occupation Crimes of violence Violations of narcotics law
or
Psychotic also during periods of abstinence Remaining contacts with drug free friends Time spent in institutions Number of drugs abused Remaining contacts with parole officers, social workers etc. Psychiatric problems during childhood
B. FRYKHOLMet al.
108
Validation of the prognostic instrument on 50 cases In order to validate the estimated discriminant functions these were used to classify the patients in the test group. The following results were obtained:
System
I According to follow-up data belonging to Total a, c1 h,
By background data classified as
a, b, C!
Total
IO 5 2
0 7 3
0 7 16
10 19 21
17
IO
23
50
System 2 According to follow-up data belonging to Total a2 bz By background data classified as ;r Total
4 5
1 40
5 45
9
41
50
The sum of the frequencies in the main diagonal of the tables above gives the number of correct classifications. For system 1 the correct classifications were 33 (66%) with most of the erroneous classifications in groups adjacent to the correct one. For system 2 the proportion of correct classifications was 88%. DISCUSSION
The results of the present study fall into two different categories: (1) follow-up data and (2) prognostic factors. One possible way to study effects of treatment on relapse behaviour is afforded by repeated contacts during the early follow-up period. It seems likely that percentage figures for drug-free and socially adjusted patients at a later stage, which have been the main interest of most follow-up studies, mainly reflect other characteristics of the material besides treatment effects, e.g. selection of patients and background factors. Our method of time-programmed follow-up has revealed that, particularly during the first year after discharge from the clinic, there were rapid changes in the percentage of drug-free patients in the material. These changes could only be revealed by the time-programmed design, i.e. the patients must be contacted at predetermined time intervals following the discharge of each individual. In this way it was shown that as many as 39% had relapsed within two weeks. On the other hand the curve showing percentage of drug-free at different time points (Fig. 3) indicated, that a year after discharge most of the relapses to be expected had already occurred. The number of patients who were found drug-free at 2 and 3 yr after discharge tented to increase compared with the situation at one year. This is in accordance with Duvall, Locke & Brill (1963) who also recorded a gradual improvement during the late follow-up period. In spite of the fact that our material was dominated by amphetamine abusers (82%), the overall outcome did not seem to differ much from findings in heroin dependent subjects (O’Donnell, 1965). Similar results have been reported earlier in a different material of 74 amphetamine abusers (Gunne, AnggHrd & Jonsson, 1970). As might be expected there was a high correlation between jobs and stable residence on one hand and abstaining from drugs on the other. These findings support the validity of the follow-up data. The second part of the study which dealt with prognostic factors seemed to assign a high prediction potential to two different background variables: one describing the degree of involvement with drugs (“number of injections”) and one dealing with remaining social contacts with non-drug-addicts (“remaining contacts with relatives”). Several other studies using various techniques have emphasized the importance of similar factors. Thus Davies, Shepard & Myers
Prediction of outcome in drug dependence
109
(1951), Straus & Bacon (19_51),Kissin, Rosenblatt & Machover (1968), Gillis & Keet (1969) have stressed the importance of remaining social contacts with non-alcoholic persons for the outcome of alcoholism. The degree of involvement with drugs was labeled as prognostically important in alcoholics (Miller, 1944) and drug addicts (Smith, 1972) since it was found that a periodic type of abuse was prognostically more favourable than daily abuse. Retterstol & Sund (1964) in a study of abusers of sedatives, among other factors found evidence for a better prognosis in cases with a short history of abuse, whereas Anchersen (1947) and Kielholz (1952) found no connection between outcome and the duration of abuse. Haastrup (1973) similarly found evidence for a poor prognosis in subjects who reported to have injected themselves more than one hundred times. It seem possible, however, that the degree of involvement with drugs measured in various ways, has a direct bearing on the prognosis only during a limited period of the drug career. The majority of the patients appearing in the present study had been abusers for 2-5 yr, whereas according to clinical observations the desire to leave the drug habits may appear later. Other reports rather focus on the importance of other factors: older age (Hunt & Odoroff, 1962; Duvall, Locke & Brill, 1963; Paulus, 1968; Glatt, 1969), late drug debut (Lemere, 1953; Brotman & Freedman, 1968) or certain psychological characteristics like high anxiety level (Kaplan & Meyerowitz, 1969; Levy & Tracy, 1971). Certain authors have attributed prognostic significance to a variety of factors selected on the basis of clinical intuition (Prescor, 1941, Tamerin & Neumann, 1971; Cohen & Klein, 1971). However, these factors have not been validated in prospective studies. The technique used in the present study allows an analysis of the discriminatory power of isolated background variables as predictors of outcome. In order to evaluate to what extent background data do better than pure chance it is necessary to determine the probability of correct classifications using a random procedure. If the distribution over groups in the material used for construction of the prognostic instrument are assumed to be valid also in the test group, the probability of correct classification in system 1 is about 33% and in system 2 about 70%. Thus for system 1 there has been a substantial increase in the proportion of correct classifications (from 33 to 66%). The relatively modest increase in the corresponding proportion for system 2 (from 70 to 88%) is mainly due to the fact that the assumed distribution already contains so much information. The results of the statistical analysis, however, should be looked upon as conditional. This means that the inference from the results are valid mainly for the same set up of variables measured and coded as in the present study. This uncertainty makes the importance of individual variables difficult to assess. Except for the two variables ranked highest according to both systems of classification (system 1 and 2) which nearly exhausted the prediction power of the prognostic instrument, the other variables seemed to act more on a joint basis. The practical applications of a prognostic instrument in the treatment of drug dependent subjects can be manifold. A knowledge of the statistical prognosis of cases would facilitate a classification of drug dependent subjects according to the severity of the condition. This may lead to the elaboration of new treatment approaches aiming specifically at subgroups which do not seem to benefit from the present therapeutic programmes. Also in the evaluation of treatment some knowledge of the chances of recovery between groups may allow meaningful comparisons between institutions which receive different selections of patients. Finally some background variables found to be important in our system seem to indicate social deficiencies which might be compensated for by active measures. Thus for instance a lack of social contacts with drug-free people could lead to therapeutic efforts to establish new such relationships. The finding that remaining contacts with relatives influences the outcome, might indicate the importance of family therapy. The present results will be pursued in a future study in an attempt to construct a prognostic instrument for practical clinical use. REFERENCES Anchersen, P., On the prognosis of narcomania (euphomania). (to clarify some problems of narcomania.) Acta Psychiarric Scandanauia, 1947, 22, 153-193. Brotman, R., & Freedman, A., Targets, goals and methods for intervention, US Dept of HEW. A Community Health Approach to Drug Addiction. Washington, D. C.: Government Printing Office, 1%8, 30-39. Cohen, M., & Klein, D. F., Drug abuse in a young psychiatric population. American Journal of Orthopsychiatry, 1971, 40, 448-455.
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Davies, D. L., Shepard, M., & Myers, E., The two-years’ prognosis of 50 alcohol addicts after treatment in hospital. Quarterly Journal of Studies on Alcohol, 1951, 12, 231-260. Dixon, W. .I., BMD Biomedical Computer Programs. Berkeley, Calif.: University of California Press, 1973. Duvall, I., Locke, B. L., & Brill, L., Follow-up study of narcotic drug addicts five years after hospitalization. Public Health Reports, 1%3, 78, 185. Gillis, L. S., & Keet, M., Prognostic factors and treatment results in hospitalized alcoholics. Quarterly Journal of Studies on Alcohol, 1969, 30, 426-437. Glatt, M. M.. Rehabilitation of the addict. Brittish Journal of the Addictions, 1969, 64, 165-182. Gunne, L. M., Anggard, E. & Jonsson, L. E., Blockade of amphetamine effects in human subjects. In Tongue & Tongue (Eds.) I.C.A.A. paper 249, Lausanne, 1970. Haastrup, S., Young Drug Abusers. 350 Patients Interviewed at Admission and Followed Up Three Years Laler. Kopenhamn: Munksgaard, 1973. Hunt, G. H. & Odoroff, M. E., Follow-up study of narcotic drug addicts after hospitalization. Public Health Reports, 1962,77, 41. Kaplan, H. B., & Meyerowitz, J. H., Psychosocial predictors of post-institutional adjustment among male drug addicts. Achives of General Psychiatry, 20, 278-284. Kielholz, P., Behandlung und Prognose des chronischen Morphinismus. Schweiz. med. Wschr, 1952, 82, 1325-1329. Kissin, B., Rosenblatt, S. M. & Machover, S., Prognostic factors in alcoholism. Psychiatric Research Reports, 1968, 24, 22-43. Lemere, F., What happens to alcoholics. American Journal of Psychiatry, 1953, 109, 674-676. Levy, M. & Tracy, F., Prediction of success of drug addicts in outpatient release status based upon a personality inventory. International Journal of the Addictions. 1971, 6, 533-541. Miller, M. M., Prognosis in periodic and daily inebriates. Quarterly Journal of Studies on Alcohol, 1944, 5, 430-433. O’Donnell, J. A., The relapse rate in narcotic addiction: A critique of follow-up studies. In D. M. Wilner & G. G. Kassebaum (Eds.) Narcotics. Los Angeles: University of California Press, 1965. Paulus, I., A comparative study of long-term and short-term withdrawal of narcotic addicts voluntarily seeking comprehensive treatment. British Journal of the Addictions, 1968, 63, 129-141. Pescor, M., Prognosis in drug addiction. American Journal of Psychiatry, 1941. 97, 119-133. Rao, R., Advanced statistical methods in biometric research. New York: John Wiley, 1952. Retterstol, N., & Sund, A., Drug Addiction and Habituation (Norwegian Monographs on Medical Science) Oslo: Universitetsforlaget, 1964. Smith, D. E., A physician’s view of the adolescent drug scene. In C. J. D. Zarafonetis (Ed.) Drug Abuse: Proceedings of the lntemational Conference. New York: Lea & Febiger, 1972. Straus, R., & Bacon, S. D., Alcoholism and social stability: A study of occupational integration in 2023 male clinic patients. Quarterly Journal of Studies on Alcohol, 1951, 12, 231-260. Tamerin, J. S., & Neumann, C. P.. Prognostic factors in the evaluation of addicted individuals, International Pharmacopsychiatry, 1971, 6, 69-76.