Predicting 10-year quality-of-life outcomes of patients with schizophrenia and schizoaffective disorders.

Psychiatry and Clinical Neurosciences 2014; 68: 308–317

doi:10.1111/pcn.12135

Regular Article

Predicting 10-year quality-of-life outcomes of patients with schizophrenia and schizoaffective disorders Michael S. Ritsner, MD, PhD,* Alexander Lisker, MD and Alexander Grinshpoon, MD, PhD Sha’ar Menashe Mental Health Center, Israel Affiliated to the Rappaport Faculty of Medicine, Technion – Israel Institute of Technology, Haifa, Israel

Aims: This study aimed to determine predictors for 10-year good versus poor perceived general quality of life (QOL) outcomes from baseline variables in people with schizophrenia and schizoaffective disorder. Methods: We compared patients with poor versus good 10-year QOL outcomes using baseline clinical, personality-related variables, demographic and background characteristics. Logistic regression analysis was used for predicting the 10-year QOL outcomes from baseline data. One-hundred-eight patients completed the Quality-of-Life Enjoyment and Life Satisfaction Questionnaire, the Positive and Negative Syndromes Scale (PANSS), the Talbieh Brief Distress Inventory, and psychosocial questionnaires at baseline and 10 years later.

3.1), PANSS general psychopathology (OR 1.1), obsessiveness (OR 0.84), hostility (OR 0.4), PANSS positive scale scores (OR 0.4), and general QOL index (OR 0.4). This model classified 80.6% of the sample with good sensitivity (87% correctly identified ‘poor outcome’), and specificity (71% correctly identified ‘good outcome’).

Conclusion: This study provides a pattern of baseline predictors for long-term QOL outcomes. Identified predictors are factors that can potentially be ameliorated, and thereby enhance the QOL of people with schizophrenia and schizoaffective disorder. Key words: long-term follow up, predictors, quality of life, severe mental illness.

Results: Logistic regression revealed six predictors of QOL outcomes: paranoid ideations (odds ratio [OR]

HE IMPORTANCE OF health-related quality of life (QOL) as an outcome variable in psychiatry has increasingly been recognized.1 Emerging evidence suggests that poor QOL or a QOL impairment2 in schizophrenia (SZ) and schizoaffective disorder (SA) is associated with emotional distress,3 sideeffects of antipsychotic agents,4,5 depressive and negative symptoms.6,7 The negative effect of positive

T

*Correspondence: Michael S. Ritsner, MD, PhD, Sha’ar Menashe Mental Health Center, Mobile Post Hefer 37806, Israel. Email: [email protected] Received 13 February 2013; revised 29 August 2013; accepted 16 October 2013.

308

symptoms are scanty and controversial.2,7 Such psychosocial factors as self-esteem, self-efficacy, and some coping styles with stressful situations, expressed emotion and social support have been found to play a significant role in satisfaction with QOL.3,8–10 The relations of these variables with QOL outcomes in SZ/SA have been interpreted using the vulnerabilitystress-coping model, a mediational model,11,12 a ‘conceptual model’ developed with particular focus on the impact of antipsychotics on QOL,13 and the Distress/Protection Vulnerability model, which is broad enough to be applicable for prediction, interventions and research.3,14 Reported longitudinal data demonstrated that a change in general QOL scores was inversely corre-

© 2014 The Authors Psychiatry and Clinical Neurosciences © 2014 Japanese Society of Psychiatry and Neurology


lated with a change in depression severity15,16 and changes in anxiety among outpatients diagnosed with SZ/SA.17 Predictors of change in QOL of schizophrenia patients evaluated at admission and 16 months later included emotional distress, paranoid symptoms, side-effects, and insight that were inversely associated with variability of scores in domain-specific QOL. Changes in self-efficacy, selfesteem, and social support positively correlated with improvement in QOL scores.9 Furthermore, improved general QOL of schizophrenia patients is associated with reduced paranoia, obsessiveness, somatization, self-reported symptoms and increased self-efficacy and self-esteem ratings.10 The European Schizophrenia Cohort Study reported that financial situation, depressive and positive symptoms had a general effect on almost all subjective QOL domains over a period of 2 years.18 Among first-admission SZ patients, the most important predictors of 4–6-year QOL outcomes were psychopathology and duration of untreated psychosis.19 Psychological status, selfesteem and satisfaction with service were the most important predictors of subjective QOL over up to 6 years.20 These studies generally had a small number of QOL-related factors that were assessed over time, and a short follow-up period. In the present study, we analyzed data from baseline and 10-year follow-up assessments in the framework of a project that was initiated in 1998 in Israel.3 Obtained follow-up findings from this project were previously published. Specifically, descriptive findings regarding the 10-year course of QOL and independent clinical and psychosocial variables among patients with schizophrenia and schizoaffective disorder with focus on predicting change in QOL domains and index scores (dependent variables) from changes in the ratings of independent variables have been reported.21,22 Findings regarding the relation of QOL impairments with hedonic capacity23 and unmet needs24 have also been published. The present report aims to provide baseline predictors for 10-year general QOL outcomes. According to our knowledge, this study is the first to determine predictors for 10-year good and poor perceived QOL outcomes from baseline variables. We conducted multidimensional assessment of 108 patients at baseline and over a 10-year period and hypothesized that significant predictors of the long-term poor and good QOL outcomes might be found among baseline clinical, personality-related, demographic and background variables.

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METHOD Study design and source of data Inclusion criteria were: (i) DSM-IV criteria (31) for SZ, SA, major depression and bipolar I disorders; (ii) age 18–65 years; (iii) inpatient status; and (iv) the ability to provide written informed consent for participation in the study. Patients with associated diagnoses of mental retardation, organic brain diseases, severe physical disorders, drug/alcohol abuse, and those with low comprehension skills as well as recent immigrants (with length of residence in the country less than 5 years) were not enrolled in the study. The Sha’ar Menashe Internal Review Board and the Israel Ministry of Health approved the study. All participants provided written informed consent for participation in the study after receiving a comprehensive explanation of study procedures.

Participants One-hundred-eight patients who met DSM-IV criteria for SZ/SA disorder and were followed for 10 years participated in this study. Description of this sample and 10-year follow-up findings were reported elsewhere.21,22 Briefly, the 10-year follow-up sample included 82 (75.9%) men, mean age 48.1 years (SD = 9.3), 63 (58.3%) were single, 23 (21.3%) were married, and the remaining 22 (20.4%) were divorced, separated or widowed. Mean extent of education was 10.6 years (SD = 2.6); 11 (10.2%) lived alone independently, 21 (19.5%) with their own families, 15 (13.9%) with parents, 21 (19.5%) in a group home, and 40 (37.0%) in a hostel. Seventy-one patients were unemployed, 26 were in sheltered employment, nine were paid or self-employed, and two were retired. Mean age of application for psychiatric care was 22.9 years (SD = 7.6), and mean duration of disorder was 25.1 years (SD = 9.2). None of the participants had exacerbation of their physical disorders at the follow-up assessment.

Assessments Diagnosis was based on a face-to-face interview, medical records, and consensus between two senior psychiatrists. QOL at baseline and follow-up points was measured with the Quality of Life Enjoyment and Life Satisfaction Questionnaire (Q-LES-Q).25 Responses


310 M. S. Ritsner et al.


are scored on a 1- to 5-point scale (1 = ‘not at all or never’ to 5 = ‘frequently or all the time’), with higher scores indicating better enjoyment and satisfaction with specific life domains. In this study, we evaluated the general QOL (measured with Q-LES-Q index) and seven domains: physical health, subjective feelings, leisure time activities, social relationships, general activities, medication satisfaction, and life satisfaction. Mean scores are presented as an average of the scores of the items.2,3 ‘Poor’ and ‘good’ general QOL (Q-LES-Q index) outcomes were defined by using the median cut-off point scores (4.18) obtained from healthy subjects26 (pages 85–86). In the present sample, 82 patients had poor 10-year QOL outcomes: 69 patients were ‘dissatisfied’ both at baseline and in the 10-year follow-up assessment, and 13 patients who were ‘satisfied’ at baseline assessment, reported ‘dissatisfied’ at the 10-year follow-up assessment. At the same time, 26 patients were defined as having good QOL outcomes: 17 patients improved their QOL (they reported ‘dissatisfied’ at baseline, and ‘satisfied’ at follow up), while nine patients remained satisfied with general QOL from baseline to end-of-study.21 Severity of illness and psychopathology were assessed using the Clinical Global Impression Scale (CGI-S),27 and the Positive and Negative Syndromes Scale (PANSS).28 Inter-rater reliability scores for the CGI-S, and PANSS ratings were 0.85–0.90. Assessment of emotional distress was done using the Talbieh Brief Distress Inventory (TBDI).29,30 Distress symptom scores are the mean scores for the items of each of the six subscales: obsessiveness, hostility, anxiety, and paranoid ideations (each with three items), sensitivity (four items), and depression (seven items). Responses are 0 to 4, with higher scores indicating greater intensity of emotional distress. Task-, emotion- and avoidance-oriented coping styles were evaluated with the Coping Inventory for Stressful Situations (CISS).31 The General Self-Efficacy Scale is a 10-item standard abridged version of the GSES for evaluating a sense of personal competence in stressful situations.32 The Rosenberg Self-Esteem scale is a well-known 10-item self-report questionnaire for measuring self-esteem and self-regard (RSES).33 The Multidimensional Scale of Perceived Social Support (MSPSS)34 was used as a measure of a satisfaction with perceived social support from family, friends and significant others. For the present sample, self-report instruments demonstrated high

reliability (Cronbach’s α): Q-LES-Q (α = 0.82–0.91), TBDI (α = 0.62–0.92), CISS (α = 0.75–0.88), GSES (α = 0.82), RSES (α = 0.77), and MSPSS (α = 0.88– 0.93).

Study variables Predictors Four domains of predictors were used: baseline clinical status (CGI-S, PANSS, TBDI, antipsychotic treatment), baseline personality-related variables (CISS, GSES, RSES, MSPSS), demographic and background variables (sex, age, age of onset, illness duration, marital status, and educational level). Marital status was classified into ‘married’, ‘divorced/separated/ widowed’ and ‘never married’. Antipsychotic treatment was classified by first-generation antipsychotics (FGA), second-generation antipsychotics (SGA), and combination of antipsychotic agents (COMB = FGA + SGA). Criterion variable The dependent variable was ‘poor’ and ‘good’ general QOL (Q-LES-Q index) determined at the 10-year examination.

Data analysis Two steps of data analysis were performed. First, univariate comparisons between good and poor QOL outcome patient groups were evaluated with the χ2-test for equality of proportions for categorical variables and the 2-tailed t-test, or the Wilcoxon signed rank test (z) for assessing continuous variables. Mean values with standard deviation (SD) or standard error (SE) are presented. Second, to determine predictors of the dichotomous variable (poor versus good QOL) we performed logistic regression controlling for sociodemographic variables (age, sex) and antipsychotic treatment. Optimal prediction of general QOL outcome was assessed with stepwise logistic regression. Specifically, individual variables were screened for entry into the analysis by a two-step procedure: (i) variables that differentiated good from poor outcome groups in univariate comparisons were used in single-variable logistic regression models; (ii) variables that were significantly predictive of outcome status in singlevariable models were then eligible for entry into the multiple-variable logistic regression model. This




approach avoided the inflation of the type I error rate associated with stepwise entry procedures.35 By logistic regression analyses, we estimated odds ratios (OR) for particular variables, controlling for the other variables. The OR is a measure of effect size, describing the strength of association or nonindependence between two binary data values. It is used as a descriptive statistic, and plays an important role in logistic regression. Based on findings obtained from the final logistic regression model, diagnostic test evaluation was performed (http://www.vassarstats.net/clin1.html). Quantities typically used to evaluate the prognostic accuracy of binary variables are sensitivity, specificity, positive predictive values (PPV), negative predictive values (NPV), positive likelihood ratio (+LR) and negative likelihood ratio (–LR) (see Table 4 for definitions), whereas an assessment of the overall prognostic accuracy is typically assessed by a geometric approach (the area under the corresponding receiver– operator curve [ROC]).36,37 A slightly lower value of sensitivity than required for symptoms (≥0.25) and a value of PPV (≥0.70) were chosen as selection criteria. For all analyses, the level of statistical significance was defined as α less than 0.05. All statistical analyses were performed using the Number Cruncher Statistical Systems.38

P < 0.001), subjective feeling (t = 2.2, P = 0.031), general activities (t = 3.2, P = 0.001), life satisfaction (t = 4.0, P < 0.001), and satisfaction with medicine (t = 3.4, P < 0.001) excepting leisure time activities (t = 0.8, P = 0.38), and social relationships (t = 1.3, P = 0.17) (Fig. 1). Patients with poor QOL outcomes reported Q-LES-Q index values (mean ± SD) at baseline and after 10 years of 3.4 ± 0.7 and 3.2 ± 0.6 scores, respectively, and these changed by – 0.23 ± 0.8 or –3.2% from baseline value. Patients with good QOL outcomes reported Q-LES-Q index values (mean ± SD) at baseline and after 10 years of 3.9 ± 0.6 (t = 2.8, P = 0.006), and 4.5 ± 0.2 (t = 10.3, P < 0.001), respectively, and these changed by 0.62 ± 0.7 or 16.5% from baseline value (t = 4.2, P < 0.001). As shown in Table 2, the poor QOL group patients scored significantly higher on the PANSS general psychopathology scale (t = 2.3, P = 0.024) and on the following items measuring guilty feelings (G3, t = 2.0, P = 0.048), depression (G6, t = 2.2, P = 0.027), motor retardation (G7, t = 2.0, P = 0.046), disturbance of volition (G13, t = 2.5, P = 0.012) and active social avoidance (G16, t = 2.6, P < 0.01), as well as, on paranoid ideations (TBDI; t = 2.1, P = 0.034) (Table 2). PANSS Negative symptoms tended to be more severe in the poor QOL outcome group (t = 1.9, P = 0.061), especially, passive/ apathetic social withdrawal (N4, t = 2.0, P = 0.044). Good QOL outcome was clearly related to higher friend support scores (t = 2.2, P = 0.034). These patient groups did not differ on CGI-S scores, PANSS, total scores, PANSS positive scale, selfesteem, self-efficacy, task-oriented coping, emotionoriented coping, and avoidance-oriented coping style (all P > 0.05).

RESULTS Univariate analysis of baseline data Tables 1 and 2 compare groups of patients with good and poor QOL outcome. Notably, no significant between-group differences were found with respect to patients’ age, age of onset, sex, marital status, education, diagnosis, illness duration, CGI-S, PANSS total scores, and antipsychotic treatment (Table 1). Cross-sectional comparisons between SZ and SA disorder patients did not reach significant levels in the Q-LES-Qindex and domain scores at the initial assessment and after 10 years (MANOVA, Hotelling– Lawley Trace; F8,108 = 0.97, P = 0.47 and F8,108 = 0.81, P = 0.59, respectively). Therefore, the following analyses were conducted on the SZ/SA sample. At baseline assessment, patients with poor QOL outcome compared to patients with good QOL outcome reported significantly lower satisfaction in the Q-LES-Q domains: physical health (t = 3.6,

Logistic regression analysis Table 3 presents a summary of the final multiple logistic regression model (overall likelihood ratio = –44.00; d.f. = 9, R2 = 0.26, P < 0.001). The OR of the QOL outcome in the two groups was 9.3 (P = 0.0001). The model predicts membership in the poor versus good QOL outcome group using six significant variables: (i) paranoid ideation (P = 0.005); (ii) PANSS general psychopathology (P = 0.011); (iii) hostility (P = 0.042); (iv) obsessiveness (P = 0.046); (v) PANSS positive scale (P = 0.050); and (vi) general QOL (P = 0.046). Other variables entered into the model did not make a significant contribution.




Table 1. Background characteristics of the initial sample and 10-year follow-up sample (at initial and 10-year follow-up assessments) Good outcome n = 26 Baseline characteristics Sex Male Female Marital status Never married Married Divorced, separated, widowed Diagnosis (DSM-IV) Schizophrenia, disorganized type (295.1) Schizophrenia, paranoid type (295.3) Schizophrenia, residual type (295.6) Schizophrenia, undifferentiated type (295.9) Schizoaffective disorder (295.7) Antipsychotic drugs FGA SGA COMB

Education (years) Age (years) Age of onset (years) Illness duration (years) CGI-S score PANSS, total score

Poor outcome n = 82

Significance

n

%

n

%

χ2-test

P

19 17

73.1 26.9

63 19

76.8 23.2

0.2 d.f. = 1

0.69

17 5 4

65.4 19.2 15.4

49 21 12

59.8 25.6 14.7

1.8 d.f. = 2

0.63

1 14 6 0 5

3.8 53.8 23.1 0 19.2

0 48 14 3 17

0 58.5 17.1 3.7 20.7

4.6 d.f. = 4

0.33

10 10 6

38.5 38.5 23.1

51 20 11

62.2 24.4 13.4

4.5 d.f. = 2

0.10

Mean

SD

Mean

SD

t

p

11.0 36.3 21.9 13.2 4.5 76.5

2.2 8.9 6.9 8.1 0.8 20.7

10.4 39.5 23.3 15.4 4.3 83.7

2.7 9.8 7.8 9.3 1.0 19.3

1.5 1.0 0.9 1.1 0.6 1.6

0.13 0.31 0.40 0.27 0.54 0.10

CGI-S, Clinical Global Impression Scale; COMB, combination of antipsychotic agents (FGA+SGA); FGA, first-generation antipsychotics; PANSS, positive and negative syndromes scale; SGA, second-generation antipsychotics.

Predictive accuracy of the logistic model According to this logistic regression model, 92.7% (76/82) of patients with poor QOL outcomes and 42.3% (11/26) of those with good QOL outcomes were correctly classified. The final model correctly categorized 80.6% (87/108) of the subjects to one of the two groups, and has an adequate goodness-of-fit to the data. As can be seen in Table 4, classifying the QOL outcome as ‘good’ – or ‘poor’ – provided a sensitivity of 87.4%, specificity of 71.4%, PPV of 92.6%, NPV of 57.3%, clinically important +LR 12.7, and small difference in –LR 0.73. The ROC predict QOL outcome groups (poor/good) over time plotted in Figure 2. The ROC are used to find the best cut-off points for

classification. The area under the ROC was 0.8302 for the poor QOL group, and 0.8358 for the good QOL group, which means that 83% of the classification of the QOL outcome was correct with this regression model.

DISCUSSION This study compared patients with poor versus good 10-year QOL outcomes using baseline characteristics and logistic regression analysis for predicting the 10-year QOL outcomes from the baseline data. As SZ and SA disordered patients had similar ratings on all QOL domains we combined these subgroups for the univariate and logistic regression analyses. Three major findings emerged from this study.




Table 2. Baseline rating scale scores of 108 patients with schizophrenia and schizoaffective disorders: good versus poor quality-of-life outcomes after 10-year follow-up period Good outcome (n = 26)

Poor outcome (n = 82)

Significance

Baseline values

Mean

SD

Mean

SD

Difference

t or z test

P

PANSS Positive scale PANSS Negative scale N4 Passive/apathetic social withdrawal PANSS General Psychopathology G3 Guilt feelings G6 Depression G7 Motor retardation G13 Disturbance of volition G16 Active social avoidance Emotional distress (TBDI): Hostility Obsessiveness Paranoid ideations Friend support (MSPSS)

17.8 21.5 2.6 37.1 1.3 1.5 1.4 2.9 2.8

7.4 5.3 1.0 10.4 0.7 0.7 0.7 1.0 1.4

16.8 24.4 3.2 42.4 1.7 2.1 1.9 3.6 3.6

5.9 7.3 1.4 10.1 1.0 1.2 1.1 1.2 1.4

1.0 −2.9 −0.6 −5.3 −0.4 −0.5 −0.4 −0.6 −0.8

0.7 1.9 2.0 2.3 2.0 2.2 2.0 2.5 2.6

0.47 0.061 0.044 0.024 0.048 0.027 0.046 0.012 0.009

0.9 1.2 0.9 18.7

0.9 1.1 1.0 7.6

0.9 1.2 1.4 15.1

0.8 0.8 1.0 7.4

0.04 −0.04 −0.5 3.6

0.2 0.2 2.1 2.2

0.83 0.83 0.034 0.034

MSPSS, Mu ltidimensional Scale of Perceived Social Support; PANSS, positive and negative syndromes scale; TBDI, Talbieh brief distress inventory.

Mean score

The first was that significantly lower satisfaction with general QOL in five specific domains (physical health, subjective feeling, general activities, life satisfaction, and satisfaction with medicine), but not leisure time activities, and social relationships at baseline examination predicted poor QOL outcomes

4.7 4.5 4.3 4.1 3.9 3.7 3.5 3.3 3.1 2.9 2.7 2.5 General Physical Subjective Leisure Social General Life Satisfaction quality health feelings with time relationships activities satisfaction of life (P < 0.001) (P = 0.031) activities (P > 0.05) (P = 0.001) (P < 0.001) medicine (P = 0.006) (P < 0.001) (P > 0.05)

Q-LES-Q index and domain scores

Figure 1. Mean baseline values of quality of life dimensions: ( ) good versus ( ) poor outcome group patients. Q-LES-Q, Quality of Life Enjoyment and Life Satisfaction Questionnaire.

in SZ/SA patients over the subsequent 10 years (Fig. 1). Our second set of findings was that higher baseline scores of self-reported paranoid ideations (TBDI) on the PANSS general psychopathology scale (guilty feelings, depression, motor retardation, disturbance of volition and active social avoidance), passive/ apathetic social withdrawal (PANSS, N4), and lower scores on friend support (MSPSS) predicted poor QOL outcomes in SZ/SA patients over the follow-up period. These findings replicated significant associations of QOL obtained from previous cross-sectional, and short-term prospective studies. In particular, those with emotional distress symptoms (paranoid ideations, obsessiveness, and somatization,3,10,39 depression,15–18,40 anxiety17) and negative symptoms, psychosis and paranoia components18,19 are fairly good indicators of poorer QOL, whereas positive affective balance and higher social support3 indicate higher QOL. Our third finding was obtained using a logistic regression model that showed good discriminative ability (80.6% of 108 patients were correctly classified on poor/good QOL groups; OR 9.3). In order to magnify the OR, predictors were self-reported paranoid ideations (OR 3.1), PANSS general psychopathology (OR 1.1), obsessiveness (OR 0.84), hostility




Table 3. Summary of multinomial logistic regression to predict 10-year general QOL outcomes from baseline variable scores (final model)

Baseline values

β (beta)

SE

Waldm z-value (β = 0)

1. 2. 3. 4. 5. 6. 7.

−1.13 −0.10 0.82 0.84 0.95 0.12

0.39 0.04 0.40 0.37 0.48 0.06

2.8 2.5 2.0 2.2 2.0 2.0

0.005 0.011 0.042 0.027 0.046 0.050

3.1 1.1 0.4 0.4 0.4 0.9

1.4 1.0 0.2 0.2 0.1 0.7

6.7 1.2 1.0 0.9 1.0 1.0

0.61 0.87

0.62 0.79

1.0 1.1

0.32 0.27

0.5 0.4

0.2 0.1

1.8 2.0

Paranoid Ideations (TBDI) PANSS General Psychopathology Hostility (TBDI) Obsessiveness (TBDI) General quality of life (Q-LES-Q) PANSS Positive scale Antipsychotic agents SGA COMB

OR† P

OR

Lower 95%CI

Upper 95%CI

PANSS, TBDI, and Q-LES-Q are entered into final model controlling for antipsychotic agents, and they are presented if significant. Model’s properties: dependent variable = QOL outcomes; number of groups = 2 (good vs poor); likelihood iterations = 6; maximum iterations = 1000; final log likelihood = −44.00; model R2 = 0.26; model d.f. = 9. † Odds ratio is associated with regression coefficient (β). A poor QOL outcome group was a reference group (in the analysis, the good QOL outcome group was compared to this group). CI, confidence interval; COMB, combination of antipsychotic agents (FGA+SGA); FGA, first-generation antipsychotics; PANSS, Positive and Negative Syndromes Scale; Q-LES-Q, Quality of Life Enjoyment and Life Satisfaction Questionnaire, Q-LES-Q index; QOL, quality of life; SGA, second-generation antipsychotics; TBDI, Talbieh Brief Distress Inventory.

(OR 0.4), PANSS positive scale scores (OR 0.4), and general QOL (OR 0.4). The type of antipsychotic treatment (FGA, SGA and COMB) did not reach a significant level as a predictor. This model correctly showed good sensitivity (87% correctly identified ‘poor outcome’), specificity (71% correctly identified ‘good outcome’), PPV (92%), NPV (57%), clinically important +LR (12.7), and small differences in –LR (0.73). It should be taken into account that the logistic regression model achieves R2 = 0.26. In standard linear regression, R2 gives a parameter of a power of the regressive equation: an R2 close to 1 is a very strong prediction. There is no direct equivalent of R2 for logistic regression. For the logistic model, accounts in the range of R2 = 0.10–0.35 are quite reasonable.2,35 Cross-sectional data provided strong evidence that heightening of self-esteem, self-efficacy, coping styles, and social support is significantly associated with better general QOL outcomes.3,8,9,41,42 However, these psychosocial factors did not reach significant predictive values regarding long-term QOL outcomes in the present study. Furthermore, consistent with the empirical findings from a rather large body of studies,3,10,20 our findings also suggest that sociode-

mographic (age, marital status, length of education) and background (age of illness onset, duration of disorder) variables were not useful for predicting subsequent long-term QOL outcomes. Although women were underrepresented in the sample, no significant main effect of unequal distribution of sex on QOL outcomes was indicated. Thus, baseline predictors of long-term QOL outcomes included self-reported emotional distress symptoms (paranoid ideations, hostility, and obsessiveness), perceived general QOL, and observer-rated variables (PANSS general psychopathology and positive scale). Elevated emotional distress, a reaction of an individual to external and internal stressors experienced by schizophrenia patients, is positively associated with symptom expression,43–45 sideeffects of antipsychotic agents,5,46 temperament types, emotion-oriented coping, weak self-constructs,47 and with a positive family history of schizophrenia.48 Consistent with the stress-vulnerability model,49,50 persistent elevated emotional distress might represent an impaired stress reactivity associated with genetic vulnerability to SZ/SA. We acknowledge several limitations in this prospective observational study. First, even in longitudi-




Table 4. Diagnostic test evaluation of the prediction of 10-year QOL outcomes based on a final logistic regression model 95%CI Parameters

Estimated Value

Lower Limit

Prevalence (%) 80.6 71.6 Sensitivity (%) 87.4 78.1 Specificity (%) 71.4 47.7 For any particular test result, the probability that it will be any QOL outcomes Positive: poor outcome (%) 75.9 66.6 Negative: good outcome (%) 24.1 16.6 For any particular positive test result, the probability that it is poor QOL outcome True positive 92.6 84.1 PPV False positive 7.3 3.0 For any particular negative test result, the probability that it is good QOL outcome True negative 57.3 37.1 NPV False negative 42.3 23.9 Likelihood Ratios (weighted by prevalence) Positive likelihood ratio 12.7 5.8 Negative likelihood ratio 0.73 0.44

Upper Limit 87.3 93.2 87.8 83.4 33.4 96.9 15.8 76.0 62.8 27.4 1.21

Entered data from regression model Condition General QOL

Absent

Present

Total

Poor outcome Good outcome Totals

6 15 21

76 11 87

82 26 108

Using these entered data, midpoints and 95%CI were calculated. The sensitivity, i.e. correctly identified ‘poor outcome’ (true positive rate), and the specificity, i.e. correctly identified ‘good outcome’ (true negative rate). PPV is probability that the poor QOL outcome is present when the test is positive. NPV is probability that the good QOL outcome is not present when the test is negative. Positive likelihood ratio is ratio between the probability of a positive test result given the presence of the poor QOL outcome and the probability of a positive test result given the absence of the poor QOL outcome, i.e. = true positive rate /false positive rate = sensitivity/ (1-specificity). Negative likelihood ratio is ratio between the probability of a negative test result given the presence of the good QOL outcome and the probability of a negative test result given the absence of the poor or good QOL outcome, i.e. = false negative rate /true negative rate = (1-sensitivity) /specificity. CI, confidence interval; NPV, negative predictive value; PPV, positive predictive value; QOL, quality of life.

nal investigations, issues of causality cannot be established with certainty as the findings remain associational in nature. Second, logistic regression models should be taken as suggestive as the sample size is small and hence the confidence limits for the estimated OR show a wide range. Third, the results of the present study might apply only to treatmentcompliant and cooperative patients. The last limitation is common for most studies using self-report methodology for investigating QOL in severely ill psychiatric patients.

In conclusion, the most important finding of this study is that long-term subjective QOL outcomes were successfully predicted by self-reported paranoid ideations, hostility, obsessiveness, and general QOL together with observer-rated general psychopathology, and positive scale scores. In terms of the clinical projections of this research, poor subjective QOL can be targeted for treatment interventions. Identified predictors of long-term QOL outcomes might be useful in the development of new treatment strategies that can potentially ameliorate




1.00

Sensitivity

0.75

0.50

0.25

0.00 0.00

0.25

0.50 Specificity

0.75

1.00

Figure 2. The receiver–operator curves (ROC) predict qualityof-life (QOL) outcome groups (poor/good) over time. Bold line, good QOL; dashed line, poor QOL. The closer the ROC is to the upper left corner (100% sensitivity, 100% specificity), the higher the overall accuracy of the test.

factors that predict poor subjective QOL, and thereby benefit patients with SZ/SA disorders by potentially enhancing their well-being.

ACKNOWLEDGMENTS The study was not funded. The authors have no conflicts of interest to report. We are grateful to individuals who participated in this study and to the clinical staff of Sha’ar Menashe Mental Health Center. Thanks to Rena Kurs for editing this manuscript.

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