Journal of Personality Disorders, 28(4), 577-593, 2014 © 2014 The Guilford Press PERSONALITY DISORDER AND DEPRESSION NEWTON-HOWES ET AL.

INFLUENCE OF PERSONALITY ON THE OUTCOME OF TREATMENT IN DEPRESSION: SYSTEMATIC REVIEW AND META-ANALYSIS Giles Newton-Howes, MRCPsych, FRANZCP, Peter Tyrer, MD, FMedSci, Tony Johnson, PhD, Roger Mulder, PhD, FRANZCP, Simone Kool, MD, Jack Dekker, PhD, and Robert Schoevers, MD

There continues to be debate about the influence of personality disorder on the outcome of depressive disorders and is relative interactions with treatment. To determine whether personality disorder, both generically and in terms of individual clusters, leads to a worse outcome in patients with depressive disorders and whether this is influenced by type of treatment, a systematic electronic search of MEDLINE, CINAHL, and PsycINFO from 1966, 1982, and 1882, respectively, until February 2007 was undertaken. The keyword terms depression, mental illness, and personality disorder were used. All references were reviewed and personal correspondence was undertaken. Only English language papers were considered. Any English language paper studying a depressed adult population was considered for inclusion. Studies needed to clearly define depression and personality disorder using peer-reviewed instruments or International Classification of Disease/ Diagnostic Statistical Manual criteria. Outcome assessment at greater than 3 weeks was necessary. Final inclusion papers were agreed on by consensus by at least two reviewers. All data were extracted using predetermined criteria for depression by at least two reviewers in parallel. Disagreement was settled by consensus. Complex data extraction was confirmed within the study group. Data were synthesized using log odds ratios in the Cochrane RevMan 5 program. The finding of comorbid personality disorder and depression was associated with a more than double the odds of a poor outcome for depression compared with those with no personality disorder (OR 2.16, CI 1.83–2.56). This effect was not ameliorated by the treatment modality used for the depressive disorder. This finding led to the conclusion that personality disorder has a negative impact on the outcome of depression. This finding is important in considering prognosis in depressive disorders. This article was accepted under the editorship of Paul S. Links. From the Department of Psychological Medicine, University of Otago, Wellington, New Zealand (G. N.H.); Department of Psychological Medicine, University of Otago, Christchurch, New Zealand, (R. M.); Department of Psychological Medicine, Imperial College London (G. N.-H., P. T.); Arkin Mental Health Institute, Amsterdam (S. K.; J. D.); Free University Amsterdam (J. D.); MRC Biostatistics Unit, University of Cambridge Institute of Public Health, Cambridge, and MRC Clinical Trials Unit, London (T. J.); Department of Psychiatry, University Medical Center Groningen, University of Groningen, Groningen, The Netherlands (R. S.). Address correspondence: to Giles Newton-Howes, Department of Psychological Medicine, School of Medicine and Health Sciences, University of Otago, Wellington, PO Box 7343, Wellington South, New Zealand; E-mail: [email protected]

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There has been a long-standing debate within psychiatry about the diagnostic position of personality disorders and their influence on the course of mental state disorders. This is particularly true of the influence of personality status on depression with the literature stretching back more than 60 years (Hobson, 1953). As it is becoming increasingly clear that depression can be both an acute and a chronic disorder (Eaton et al., 2008), understanding the factors that are linked to a poorer prognosis is becoming increasingly important. The impact of personality has been studied with some commentators challenging the “received wisdom” of poorer outcome in depression with comorbid personality disorder. In an important narrative review, Mulder (2002) reported no impact on outcome in depression with personality pathology, and this stance has been supported by others in the field using a variety of methodologies to combine the literature (Kool, et al., 2005). Not all reviews have come to this conclusion. An inclusive systematic review and meta-analysis, including papers with cohort, case-control, and randomized control methodologies, found poorer outcomes for the comorbid group (Newton-Howes, Johnson, & Tyrer, 2006), supporting an earlier negative narrative review (Reich, 2003). Such an approach to systematic reviews, including all methodologies, has a sound basis (Concato, Shah, & Horwitz, 2000) and increases the number of patients able to be included in any analysis. This question has clinical importance because the implication of poorer prognosis in the presence of comorbid personality disorder both aids prognostic accuracy and implies that interventions focused on the comorbid personality disorder as well as depression may be of benefit. There is a growing body of evidence that a variety of pharmacological (Coccaro & Kavoussi, 1997; Nickel et al., 2006; Nickel et al., 2005; Sheard, Marini, Bridges, & Wagner, 1976), psychological (Bateman & Fonagy, 2008; Blum et al., 2008; Giesen-Bloo et al., 2006; Linehan et al., 2006; McMain et al., 2009; Tyrer et al., 2004), and social interventions (Tyrer & Tyrer, 2008) can improve outcomes in personality disorder. If in fact personality disorder does not have any impact in Axis I disorder, then it does not need to be a primary focus of treatment in depressed patients as is commonly the case within current dayto-day psychiatric practice (Tyrer et al., 2007). There is, however, evidence that this is not the case generally (Crawford et al., 2008), and a degree of personality–mood interaction would be expected. Despite the numerous clinical papers and recent reviews on this topic, the best analysis of the current data is unclear. In order to address this issue, the authors of the most recent reviews came together as the Personality Disorder and Depression Outcome Group (PDDOG) to reexamine the data and to include all recently published studies. The aim of the meta-analysis was to examine both (1) the outcome of depressive disorders, irrespective of treatment, in research studies in which both personality status and depression were measured at baseline, and (2) whether different modalities for treatment for depression had their outcomes altered by the presence of comorbid personality disorder. The goal was to provide clear clinical advice to practicing psychiatrists as to the impact of personality disorder in depression.

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METHODS SELECTION AND STUDY CHARACTERISTICS

We selected all papers that studied the outcome of depression in patients with a diagnosis of comorbid personality disorder. As the diagnostic criteria for personality disorder (and depression) have evolved over time, any paper that clearly diagnosed these conditions over time was eligible for selection. Inclusion criteria were kept broad in order to maximize included studies. Only papers written in English were reviewed. The principal exclusion criterion for this review was lack of a categorical diagnosis for either personality disorder or depression. Many papers comment on personality function using dimensional criteria. Although there is some evidence that this approach may reflect the structure of personality more appropriately (Livesley, 2007), it does not accord with clinical decision making and generally has been critiqued as having less clinical utility (Rottman, Ahn, Sanislow, & Kim, 2009; Skodol & Bender, 2009). Because the review aimed to assist psychiatrists with clinical prognosis, categorical diagnosis was considered essential. SEARCH STRATEGY

A broad search strategy was employed to ensure maximum coverage of the literature. Initially a search of the databases MEDLINE (from January 1, 1966), CINAHL (from January 1, 1982) and PsycINFO (from January 1, 1882) was undertaken in April 2002 and repeated in February 2007. The key words depression, mental illness, and personality disorder were entered and combined. To supplement the electronic search, the Journal of Affective Disorders was hand searched by one of the authors (G.N.-H.), the references of all articles were reviewed, and experts in the field were contacted. The Quality of Reporting of Meta-Analysis statement (Moher et al., 1999) and other work (McAuley, Pham, Tugwell, & Moher, 2000) has highlighted the possibilities of publication bias if unreported studies are not included, and this was considered by the PDDOG group. The gray literature was, however, not consulted because it was not considered likely that studies would be “buried” for commercial gain in this area; no obvious source of gray literature (such as the FDA) could be identified; and due to the difficult nature of accurately diagnosing personality disorder, the rigor of peer review was felt to provide an extra safeguard to ensure like was compared to like. PRINCIPAL OUTCOME

The principal outcome was the odds of an altered outcome in the treatment of depression in the presence of a personality disorder. The outcome for each paper was dichotomized and recovered versus chronic/nonrecovered outcomes compared between personality disordered and nonpersonality disordered groups. Recovery was identified by a sustained treatment response for the duration of the trial. In this way recovery was differentiated from re-

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sponse, whereby patients may have initially responded but not sustained that response to the intervention provided. Authors identified a variety of methods for defining recovery, although cutoff scores for the standard measures used to rate depressive symptomatology were common, such as a Hamilton Depression rating scale score of less than 7. DATA EXTRACTION

Two-by-two tables were designed to ensure uniformity of the data extracted. As far as possible, all information extracted was stratified by treatment type and personality cluster. Numbers were extracted directly from the papers where possible and derived from summary percentages, or reconstructed from summary statistics such as chi squares when direct extraction was not possible. All information extracted from each paper was cross-checked against the other information provided within each paper (by counts, percentages, summaries, or test statistics) to check for and resolve inconsistencies. Where dichotomous outcomes were not reported for depression outcome, but outcomes were presented as means and standard deviations on a rating scale, “recovered outcome” was used to derive a dichotomous pairing using the method of Whitehead, Bailey, and Elbourne (1999). All data were extracted by at least two of the authors with all disagreements resolved by consensus within the group. QUANTITATIVE DATA SYNTHESIS

RevMan is the Cochrane Collaboration’s electronic meta-analysis software (Higgins & Green, 2009). It allows for combination of data and construction of forest plots and grouped outcomes. Furthermore, its random effects analysis takes into account the lack of a gold standard baseline that is problematic in studies of personality disorder. All dichotomized data were therefore entered into RevMan 5 and combined using a random effect meta-analysis. The standard error was used for purposes of comparison, and total numbers of patients allowed for the weighting of individual papers. RESULTS THE SEARCH

The combined 2002 and 2007 searches revealed in excess of 5,000 potential papers. This very large number was expected secondary to the wide search criteria used. Of these papers, the majority were rejected on reviewing the title and abstract as obviously containing no usable data. The primary reason for rejection of papers was no usable data. For example, some papers reported on basic science, used continuous measures of personality only, were not outcome studies, or presented no data. The hand search of the Journal of Affective Disorders revealed no additional papers. This indicated that the electronic search strategy was sound. As with any review, new papers on the topic continued to be published; however, no paper after the 2007 search

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was eligible for inclusion. Fifty-eight papers were eligible for inclusion in the review. CHARACTERISTICS OF THE INCLUDED STUDIES

The characteristics of the included studies are summarized in Table 1. The studies range in publication date from 1981 to 2006, the cutoff date for inclusion being February 2007. Fifty-two percent of the included studies were from North America, and a further 38% came from Europe and Britain. Of the remaining five studies, one was based in Japan and the other four in Australasia. When multiple papers are published by a single study group, the paper from which the data were extracted is presented in Table 1. When it was not clear whether papers were from one or multiple sources, the authors were contacted for clarification. Of the included studies, the majority (35) were prospective case series and 17 were randomized controlled trials (RCTs). RCTs did not become more common over time. Slightly more than half the papers focused on outpatients. The measurement of recovery varied widely within the included studies, although the Hamilton Rating Scale for Depression (HAM-D) and the Montgomery-Åsberg Depression Rating Scale (MADRS) were the most commonly used tools (in 24 papers). These characteristics allowed for sensitivity analyses on the primary result according to study type and depression rating. ASSESSMENT OF PUBLICATION BIAS

Examination of the funnel plot of the included studies was undertaken to assess for publication bias (see Figure 1). Funnel plotting was assessed using a fixed effects model. In the absence of publication bias, data should be symmetrical around the pooled odds ratio (OR). This appeared to be the case for the included studies and did not suggest that unpublished data were skewing the findings. ODDS RATIOS FOR THE PRINCIPAL OUTCOME

The overall odds of a poorer outcome in patients with a diagnosis of depression with a personality disorder were 2.16 (1.83–2.56). This finding was undertaken using a random effects model, taking into account the variation in the included data. Sensitivity analysis of the data set was undertaken in two ways: to examine the effect of using only one type of depression rating (the HAM-D), and by study design. It was assumed that using a single rating scale for depression in the analysis would give a lower odds ratio with a smaller confidence interval in a subgroup of patients’ whose depression was assessed in a uniform way, removing some of the heterogeneity of the data. The analysis of the data by study design was expected to show a gradation in odds ratios: the greatest odds ratio (with widest confidence intervals) for the least methodologically robust design (case series) to a lower odds ratio with narrower confidence ratios for RCTs.

Depression DSM-III HAM-D DSM-III RDC ICD DSM-III DSM-III DSM-III RDC RDC DSM-III, RDC DSM-III DSM-III RDC RDC DSM-III DSM-III DSM-III DSM-III-R DSM-III-R, RDC DSM-III-R DSM-III-R DSM-III-R DSM-III DSM-III-R DSM-III-R DSM-III DSM-III DSM-III-R DSM-III DSM-III-R DSM-III-R DSM-III-R

First Author (year)

Charney (1981) Tyrer (1983) Pfohl (1984,1987) Davidson (1985) Shawcross (1985) Sauer (1986) Black (1988) Goethe (1988) Pilkonis (1988) Thompson (1988) Joffe (1989) Keitner (1989) Kocsis (1989) Reich (1990) Shea (1990)

Tyrer (1990) Ansseau (1991) Black (1991) Stuart (1992) Diguer (1993) Kunik (1993) Sato (1993) Fava (1994) Peselow (1994) Sullivan (1994) Vine (1994) Hardy (1995) Patience (1995) Casey (1996) Alnaes (1997) Ilardi (1997) Ekselius (1998) Hirschfeld (1998)

Criteriaa

PAS DSM-III DSM-III DSM-III-R DSM-III-R DSM-III-R DSM-III-R DSM-III-R DSM-III DSM-III-R DSM-III-R DSM-III-R PAS PAS DSM-III DSM-III-R SCID DSM-III-R

DSM-III PAS DSM-III DSM-III PAS DSM-III DSM-III DSM-III (?) DSM-III DSM-III DSM-III DSM-III (?) Clinical PDQ, GAS DSM-III

PD

Responseb

MADRS < 6 HAM-D + dropout Recovered—case-note review HAM-D < 7 for 4+ wks. BDI (cont) Complex (3) Complex (4) HAMD (cont) Complex (5) HAM-D < 8 Complex (6) BDI < 7 (?) HAM-D < 7 Re-admission Depressive relapse Depressive relapse Complex (7) Complex (8)

Good or complete 50+%↓ HAM-D, HAM-A 50+%↓ HAM-D HAM-D (cont) Clinical judgment 50+%↓ HAM-D Recovered—case notes Clinical judgment Complex (1) No MDD HAM-D < 5 HAM-D < 7 for 3 mos. Complex (2) GAS HAM-D < 7

TABLE 1. Characteristics of Studies Reporting Association Between Personality Disorder and Outcome in Depression

TCA TCA, CBT, Dynamic, Counseling Unclear SSRI Unclear CBT Dynamic Various Various SSRI TCA TCA Various CBT, Dynamic CBT, TCA ECT Various Various SSRI TCA, SSRI

Unclear Unclear Unclear MAOIs TCA+ TCA ECT, TCA, Counseling Various TCA + Dynamic CBT, Dynamic TCA Various

Treatmentc

10 8 6 16 ~16 5 17 8 5 6 120 NK 16 52 312 26 24 12

12 4 4 (mean) 4 60 (mean) 3 NK 20 (mean) 16+ 24 5 26 6 26 16

Timed (weeks)

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DSM-III-R DSM-III-R DSM-IV DSM-III-R DSM-III-R ICD-10 DSM-IV ICD-10 DSM-IV DSM-III-R DSM-IV DSM-III-R DSM-III-R DSM-IV DSM-III-R DSM-III-R DSM-III-R ICD-10, DSM-IV DSM-IV DSM-III-R DSM-IV DSM-IV HAM-D DSM-IV Clinical (SCL-90)

DSM-III-R DSM-III-R DSM-IV DSM-III-R DSM-III-R ICD-10 DSM-IV ICD-10 DSM-IV SCID-P DSM-IV DSM-III-R SCID-II-P DSM-III-R DSM-III-R DSM-III-R SCID-II PAS DSM-IV DSM-III-R DSM-III-R DSM-IV DSM-III-R DSM-IV Clinical

LIFE – 8 wks. no/minimal symptoms HAMD < 8 BDI (cont) BDI < 10 HAM-D 70 Complex (9) BDI (cont) HAM-D < 8, 2 weeks CDRS (cont) HAM-D (cont) Complex (10) Complex (11) BDI 59%↓ HAMD < 8 BDI < 14 HAM-D > 49%↓ BDI < 7 HAM-D < 8 HAM-D < 11 Below MDE criteria 2 months symptom-free HAM-D < 11 for 3 weeks HAM-D (cont) < 2 SDs above SCL-90 mean Unclear Unclear SSRI Various Unclear Various TCA + SSRI Various TCA+ Various Unclear Drugs, PSY ECT Unclear SSRI TCA + Dynamic Various CBT+

TCA+

Various CBT CBT

125 26 10 (mean) 5 32 4 ~12 26 9 (mean) 8 12 365 26 6 24 16 (mid) 6 12 52 4 78 108 38 3 (mean) 18 (mean)

Notes. a BDI: Beck Depression Inventory; HAM-A: Hamilton Rating Scale for Depression and Anxiety; HAM-D: Hamilton Rating Scale for Depression; GAS: Global Assessment Scale; ICD-10: International Classification of Diseases, 10th ed.; MADRS: Montgomery-Åsberg Depression Rating Scale; PAS: Personality Assessment Schedule; PDQ: Personality Diagnostic Questionnaire; RDC: Research Diagnostic Criteria; SCID: Structured Clinical Interview for DSM-IV; SCL-90: Symptom Checklist-90. b cont = continuous outcome only reported (no dichotomy); complex (1) = algorithm of Frank et al. (1984); complex (2) = HAM-D < 7, > 9-point improvement on GAS, and absence of sufficient symptoms to meet DSM-III dysthymic disorder; complex (3) = HAM-D < 10, or relative decrease > 50%; complex (4) = HAM-D-17 < 6, and full recovery of social functioning 16 weeks after starting treatment, and no sign of recurrence of depression during 4 weeks after first two criteria met; complex (5) = 50% decrease in HAM-D, final CGI (Clinical Global Impression) < 3, and final HAM-D < 12; complex (6) = does not meet criteria for DSM-III-R depressive disorder, no symptoms for more than 2 weeks during follow-up, no inpatient treatment, and no change in outpatient treatment; complex (7) = 50+% reduction in MADRS at 24 weeks, CGI severity score 1–3, and CGI improvement rated at least “much improved”; complex (8) = CGI-I 1 or 2, and HAM-D < 7, or HAM-D 50+% reduction with HAM-D < 15 and CGI severity 3; complex (9) = Bech-Rafaelsen Melancholia Scale decline > 50%, and < 10 within 4 weeks; complex (10) = PSR (Psychiatric Rating Scale) rating of one, or one or more symptoms of no more than a mild degree (PSR of two) over preceding two weeks; complex (11) = no residual symptoms, no readmissions, depressed < 50% of time, or relapse with readmission and depressed < 50% of time. c 1. Physical: ECT = electroconvulsive therapy, 2. Drugs: TCA = tricyclic antidepressants (except clomipramine), SSRI = selective serotonin reuptake inhibitors (including clomipramine), MAOI = monoamine oxidase inhibitors, 3. Therapy: CBT = cognitive-behavioral therapies, Dynamic = dynamic psychotherapies, Counseling = counseling therapies (all as defined by NICE guidelines for depression, pp. 134–159), 4. Other unclear = authors do not discuss treatments given, various = multiple treatments are given, comma = either/or treatment, + = both treatments given. d Interval from start to outcome evaluation.

Klein (1998) Ezquiaga (1999) Leibbrand (1999) Ball (2000) Brown (2000) Bschor (2001) Kuyken (2001) O’Leary (2001) Brieger (2002) Fava (2002) Meyers (2002) Stek (2002) Viinamäki (2002) Joyce (2003) Kool (2003) Merrill (2003) Papakostas (2003) Casey (2004) Ezquiaga (2004) Feske (2004) Melartin (2004) Szádóczky (2004) Morse (2005) Schiavone (2006) Van den Hout (2006)

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Sensitivity analysis when separating the included studies by assessment type gave an odds ratio of 1.95 (1.55–2.44) in studies that used only the Hamilton assessment tool, indicating a poorer outcome in patients with comorbid personality disorder. Separation of the data by study design also produced the expected result. The pooled case series odds ratio was 2.43 (1.83–3.22), the cohort studies odds ratio was 2.68 (2.08–3.46), and the pooled RCT odds ratio was 1.52 (1.23–1.87). Although the latter ratio was significantly lower than for the cohort studies, it was still significant. ODDS RATIOS FOR OUTCOME BY TREATMENT TYPE

Included papers were also stratified by treatment type in order to assess if a particular treatment modality produced a favorable outcome in depressed patients with a personality disorder. These finding are presented in Tables 2 and 3. This plot shows that, irrespective of treatment modality, patients with a personality disorder have a poorer outcome in the treatment of their depression than if no personality disorder is present. Interestingly, this is not the case only for the placebo group. This greatest divergence between groups occurred if drug therapy was used, irrespective of augmentation with psychotherapy or not (OR 2.16, CI 1.65–2.83, drugs alone; OR 2.16, CI 1.63– 2.87, drugs and psychotherapy). All measures of outcome are included in this analysis. CONCLUSIONS

This is now the largest systematic review of the impact of personality disorder on the outcome of depression and demonstrates that personality disorder has a negative impact on the outcome of depressive episodes. The findings are consistent with the “received wisdom,” a previous meta-analysis, and narrative reviews. This finding builds on previous work, and in the spirit of systematic reviews, this revision is an important component of improving and updating this topic, one of the seven essential components outlined by the Cochrane Collaboration. The 5-year time frame between the 2002 search and the 2007 search is at the limit for median survival for a review without the potential need for revision, making this work timely (Shojania et al., 2007). The conclusions of the negative effect of personality disorder in depression are now much stronger because of the larger number of studies and the collective pooling of information from the Personality Disorder and Depression Outcome Group. This highlights the importance of assessing for personality disorder in this group and allows clinicians to be more certain in their prognosis: Presence of a comorbid personality disorder doubles the likelihood of nonresponse to treatment for depressive disorders. The findings with regard to treatment modality are less robust. All types of treatment show a poorer response in the personality disordered group, and there is no clear evidence that type of treatment influences this despite some recent comparative trials showing a worse outcome in those given cog-

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FIGURE 1. Funnel Plot of Studies Included in the Meta-analysis.

nitive therapy (Fournier et al., 2008). This data set does not allow us to make definitive treatment recommendations in order to improve outcome. It interesting to note, however, that in the studies examined, treatment for the coexisting personality pathology was not undertaken; rather, depressive disorders were treated. One could therefore speculate that the poorer response is related to the untreated personality pathology and treatment of it would not only be sensible but also necessary for recovery. This meta-analysis, like all approaches, has a number of strengths and weaknesses that are in many cases opposite sides of the same coin. For example, we have taken a very broad view of both personality disorder and depression—simply requiring that both are adequately referenced by a peerreviewed technique, a recommendation made by Mulder (2002). This allows for the data set to be reflective of a “normal” clinical population and subsequently minimizes the question of generalizability of the results to dayto-day patients. The same basic assumption does, however, lead to a degree of heterogeneity in the populations included and as such assumes efficacy of treatment, as its effectiveness is what is examined. Such methodological assumptions are a direct consequence of the aims of applying the data to the real-world setting, and generalizability was considered of greater importance than the heterogeneity problem a priori. Interestingly, this approach (“go broad”) would also be expected to lead to a statistical narrowing to the mean, strengthening the differences we have found. This review has also only included studies that provide a categorical definition of personality disorder, which potentially limits its power. The nosology of personality pathology is currently in flux, and even experts in the field cannot decide how to best classify patients with disrupted personality structures, although most agree that the present system is flawed (Bernstein, Iscan, & Maser, 2007). It is likely, therefore, that personality disorder as it

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TABLE 2. Random Effects Meta-analysis, Dividing the Data by Treatment Choice Study or Subgroup

log[Odds Ratio]

SE

PD Total

No PD Total

1.5.1 Placebo Kocsis (1989) -0.7732 1.1152 8 15 Shea (1990) 0.3825 0.6266 48 14 Tyrer (1990) 1.6094 0.8682 11 7 Subtotal (95% CI) 67 36 Heterogeneity: Tau² = 0.35; Chi² = 2.97, df = 2 (P = 0.23); I² = 33% Test for overall effect: Z = 0.88 (P = 0.38) 1.5.2 ECT Black (19t88) 1.0622 0.7247 10 41 Casey (1996) 0.1446 0.6427 18 22 Feske (2004) 1.0704 0.3929 54 60 Pfohl (1984) 0.2007 1.0445 8 14 Subtotal (95% CI) 90 137 Heterogeneity: Tau² = 0.00; Chi² = 1.97, df = 3 (P = 0.58); I² = 0% Test for overall effect: Z = 2.77 (P = 0.006) 1.5.3 Drugs Ansseau (1991) -0.9585 0.7666 22 24 Black (1988) 0.7489 0.4 39 83 Black (1991) 0.8246 0.2162 100 1210 Bschor (2001) 1.0549 0.7389 10 58 Davidson (1985) 0.5541 0.7311 15 20 Ekselius (1998) 0.252 0.4262 189 119 Fava (1994) 0.6429 0.4081 62 21 Fava (2002) 0.194 0.1981 243 135 Goethe (1988) 0.8199 0.2982 124 77 Hirschfeld (1998) 0.1581 0.1605 306 317 Ilardi (1997) 3.0155 0.742 22 28 Joffe (1989) 1.3134 0.8742 33 9 Joyce (2003) -0.0393 0.312 75 91 Kocsis (1989) 0.5108 0.8612 9 14 Kool (2003) 0.5741 0.6445 36 20 Melartin (2004) 0.3001 0.6494 85 113 O’Leary (2001) 1.4994 0.8746 29 45 Papakostas (2003) 0.6686 0.451 34 58 Peselow (1994) 0.401 0.4964 29 39 Pfohl (1984) 1.6582 0.7054 25 20 Reich (1990) 0.1643 0.7609 25 10 Sato (1993) 0.9039 0.4377 52 44 Sauer (1986) 1.673 1.3878 13 37 Shawcross (1985) 2.5982 0.7205 17 33 Shea (1990) 0.7404 0.5253 44 13 Stek (2002) 1.8632 0.8035 15 32 Sullivan (1994) -0.2003 0.4035 53 46 Szadocsky (2004) 2.7444 0.5816 57 60 Tyrer (1983) 2.1256 0.7151 32 28 Tyrer (1990) 1.204 1.2156 7 14 Subtotal (95% CI) 1802 2818 Heterogeneity: Tau² = 0.26; Chi² = 71.36, df = 29 (P < 0.0001); I² = 59% Test for overall effect: Z = 5.60 (P < 0.00001)

Weight

Odds Ratio IV, Random, 95% CI

0.5% 1.2% 0.7% 2.4%

0.46 [0.05, 4.11] 1.47 [0.43, 5.01] 5.00 [0.91, 27.41] 1.68 [0.53, 5.32]

1.0% 1.1% 2.0% 0.5% 4.6%

2.89 [0.70, 11.97] 1.16 [0.33, 4.07] 2.92 [1.35, 6.30] 1.22 [0.16, 9.47] 2.25 [1.27, 3.98]

0.9% 2.0% 3.0% 0.9% 0.9% 1.9% 2.0% 3.1% 2.5% 3.3% 0.9% 0.7% 2.5% 0.7% 1.1% 1.1% 0.7% 1.8% 1.6% 1.0% 0.9% 1.8% 0.3% 1.0% 1.5% 0.8% 2.0% 1.3% 1.0% 0.4% 43.6%

0.38 [0.09, 1.72] 2.11 [0.97, 4.63] 2.28 [1.49, 3.48] 2.87 [0.67, 12.22] 1.74 [0.42, 7.29] 1.29 [0.56, 2.97] 1.90 [0.85, 4.23] 1.21 [0.82, 1.79] 2.27 [1.27, 4.07] 1.17 [0.86, 1.60] 20.40 [4.76, 87.34] 3.72 [0.67, 20.63] 0.96 [0.52, 1.77] 1.67 [0.31, 9.01] 1.78 [0.50, 6.28] 1.35 [0.38, 4.82] 4.48 [0.81, 24.87] 1.95 [0.81, 4.72] 1.49 [0.56, 3.95] 5.25 [1.32, 20.92] 1.18 [0.27, 5.24] 2.47 [1.05, 5.82] 5.33 [0.35, 80.89] 13.44 [3.27, 55.17] 2.10 [0.75, 5.87] 6.44 [1.33, 31.13] 0.82 [0.37, 1.80] 15.56 [4.98, 48.63] 8.38 [2.06, 34.03] 3.33 [0.31, 36.11] 2.16 [1.65, 2.83]

is classified today will not identify the same patients in the future. The initial outline of the working group for DSM-V would support this position. Nonetheless, by taking a general approach to personality and allowing the use of any peer-reviewed instrument, this paper gives a reasonable “snapshot” of the current clinical understanding of personality pathology in patients with depression. The broad inclusion criteria of this study minimize the possibility of bias introduced by using a tool derived by a single center and provides

PERSONALITY DISORDER AND DEPRESSION 587 TABLE 2. (continued) log[Odds Ratio]

SE

PD Total

No PD Total

Weight

Odds Ratio IV, Random, 95% CI

1.6487 0.6731 0.7061 1.5489 0.5787 0.3674 -0.1815 1.3

0.842 0.5587 0.3634 0.9184 0.4455 0.6259 0.5425 0.59

49 27 54 12 27 102 39 27

7 28 249 13 85 7 18 124

0.8% 1.4% 2.2% 0.7% 1.8% 1.2% 1.4% 1.3%

5.20 [1.00, 27.09] 1.96 [0.66, 5.86] 2.03 [0.99, 4.13] 4.71 [0.78, 28.47] 1.78 [0.74, 4.27] 1.44 [0.42, 4.92] 0.83 [0.29, 2.42] 3.67 [1.15, 11.66]

Persons (1988) 1.5404 0.5327 36 30 Pfohl (1984) 1.7918 1.3944 8 3 Shea (1990) 0.2109 0.356 86 34 Stuart (1992) 0.3629 0.6259 14 39 Thompson (1988) 1.3063 0.5341 25 50 Tyrer (1990) -0.0488 1.0374 13 9 Subtotal (95% CI) 519 696 Heterogeneity: Tau² = 0.01; Chi² = 13.25, df = 13 (P = 0.43); I² = 2% Test for overall effect: Z = 4.68 (P < 0.00001) 1.5.5 Drugs and Psychotherapy Alnaes (1997) 0.2485 0.7194 77 11 Brieger (2002) 0.4329 0.4271 60 57 Brown (2000) 0.8969 0.3295 125 56 Charney (1981) 2.3979 0.8034 40 24 DeRubeis (2005) -0.0905 0.3009 90 90 Ezquiaga (1999) 2.0503 0.6039 25 62 Ezquiaga (2004) 0.8109 0.6103 20 30 Keitner (1989) 0.6332 0.8526 8 70 Klein (1998) 0.9808 0.4581 44 42 Kool (2003) -0.506 0.5231 49 23 Kunik (1993) 0.4261 0.3802 37 117 Meyers (2002) 0.8129 0.3466 101 63 Morse (2005) 0.4218 0.3609 55 105 Patience (1995) 0.7985 0.4207 38 63 Pilkonis (1988) 1.2144 0.4149 49 53 Schiavone (2006) 0.587 0.3221 155 92 Van den Hout (2006) 1.3063 0.7596 25 15 Viinamaki (2002) 1.8589 0.4579 52 65 Vine (1994) 0.991 0.589 18 38 Subtotal (95% CI) 1068 1076 Heterogeneity: Tau² = 0.17; Chi² = 33.45, df = 18 (P = 0.01); I² = 46% Test for overall effect: Z = 5.34 (P < 0.00001) Total (95% CI) 3546 4763 Heterogeneity: Tau² = 0.17; Chi² = 125.49, df = 69 (P < 0.0001); I² = 45% Test for overall effect: Z = 9.13 (P < 0.00001)

1.5% 0.3% 2.2% 1.2% 1.4% 0.5% 17.8%

4.67 [1.64, 13.26] 6.00 [0.39, 92.28] 1.23 [0.61, 2.48] 1.44 [0.42, 4.90] 3.69 [1.30, 10.52] 0.95 [0.12, 7.28] 2.01 [1.50, 2.69]

1.0% 1.9% 2.4% 0.8% 2.5% 1.2% 1.2% 0.7% 1.7% 1.5% 2.1% 2.3% 2.2% 1.9% 1.9% 2.4% 0.9% 1.7% 1.3% 31.6%

1.28 [0.31, 5.25] 1.54 [0.67, 3.56] 2.45 [1.29, 4.68] 11.00 [2.28, 53.12] 0.91 [0.51, 1.65] 7.77 [2.38, 25.38] 2.25 [0.68, 7.44] 1.88 [0.35, 10.02] 2.67 [1.09, 6.54] 0.60 [0.22, 1.68] 1.53 [0.73, 3.23] 2.25 [1.14, 4.45] 1.52 [0.75, 3.09] 2.22 [0.97, 5.07] 3.37 [1.49, 7.60] 1.80 [0.96, 3.38 3.69 [0.83, 16.36] 6.42 [2.62, 15.74] 2.69 [0.85, 8.55] 2.16 [1.63, 2.87]

100.0%

2.11 [1.79, 2.47]

Study or Subgroup 1.5.4 Psychotherapy Ball (2000) Black (1988) Casey (2004) Diguer (1993) Hardy (1995) Kuyken (2001) Leibbrand (1999) Merrill (2003)

for a reasonable group of personality disordered patients to be captured— another recommendation from Mulder (2002). More broadly, there are empirical questions about the position of personality disorders as diagnostic entities in the presence of depression. The issue of whether two disorders are comorbid or consanguineous is a diagnostic challenge in psychiatry, both for multiple Axis I and Axis I/Axis II “comorbidity” (Tyrer, 1996). Some authors argue that alternate classifications better typify these presentations (Shedler & Westen, 2004); however, such debate is beyond the scope of this review, which captures the current conceptualization of depression and personality pathology.

588

NEWTON-HOWES ET AL.

TABLE 3. Random Effects Meta-analysis, Dividing the Data by Trial Design Study or Subgroup

log[Odds Ratio]

SE

PD Total No PD Total

1.6.1 Randomized clinical trials Davidson (1985) 0.5541 0.7311 15 20 Tyrer (1983) 2.1256 0.7151 32 28 Joyce (2003) -0.0393 0.312 75 91 Kocsis (1989) -0.0357 0.6405 17 29 Papakostas (2003) 0.6686 0.451 34 58 Sullivan (1994) -0.2003 0.4035 53 46 Fava (1994) 0.6429 0.4081 62 21 Fava (2002) 0.194 0.1981 243 135 Tyrer (1990) 0.9555 0.6233 31 30 Casey (2004) 0.7061 0.3634 54 249 Hardy (1995) 0.5787 0.4455 27 85 Hirschfeld (1998) 0.1581 0.1605 306 317 DeRubeis (2005) -0.0905 0.3009 90 90 Patience (1995) 0.7985 0.4207 38 63 Shea (1990) 0.7985 0.3036 178 61 Ekselius (1998) 0.252 0.4262 189 119 Kool (2003) -0.1221 0.3968 85 43 Thompson (1988) 1.3063 0.5341 25 50 Brown (2000) 0.8969 0.3295 125 56 Subtotal (95% CI) 1679 1591 Heterogeneity: Tau² = 0.07; Chi² = 28.14, df = 18 (P = 0.06); I² = 36% Test for overall effect: Z = 3.91 (P < 0.0001) 1.6.2 Cohort studies Sauer (1986) 1.7509 1.0985 13 37 Schiavone (2006) 0.587 0.3221 155 92 Pfohl (1984) 1.5144 0.4944 41 37 Kunik (1993) 0.4261 0.3802 37 117 Peselow (1994) 0.401 0.4964 29 39 Ball (2000) 1.6487 0.842 49 7 Joffe (1989) 1.3134 0.8742 33 9 Ansseau (1991) -0.9585 0.7666 22 24 Feske (2004) 1.0704 0.3929 54 60 Brieger (2002) 0.4329 0.4271 60 57 Leibbrand (1999) -0.1815 0.5425 39 18 Meyers (2002) 0.8129 0.3466 101 63 Stuart (1992) 0.3629 0.6259 14 39 Diguer (1993) 1.5489 0.9184 12 13 Kuyken (2001) 0.3674 0.6259 102 7 Pilkonis (1988) 1.2144 0.4149 49 53 Merrill (2003) 1.3 0.59 27 124 Sato (1993) 0.9039 0.4377 52 44

Weight

Odds Ratio IV, Random, 95% CI

1.0% 1.0% 2.6% 1.2% 1.9% 2.1% 2.1% 3.2% 1.3% 2.3% 1.9% 3.4% 2.6% 2.0% 2.6% 2.0% 2.1% 1.5% 2.5% 39.2%

1.74 [0.42, 7.29] 8.38 [2.06, 34.03] 0.96 [0.52, 1.77] 0.96 [0.27, 3.39] 1.95 [0.81, 4.72] 0.82 [0.37, 1.80] 1.90 [0.85, 4.23] 1.21 [0.82, 1.79] 2.60 [0.77, 8.82] 2.03 [0.99, 4.13] 1.78 [0.74, 4.27] 1.17 [0.86, 1.60] 0.91 [0.51, 1.65] 2.22 [0.97, 5.07] 2.22 [1.23, 4.03] 1.29 [0.56, 2.97] 0.89 [0.41, 1.93] 3.69 [1.30, 10.52] 2.45 [1.29, 4.68] 1.52 [1.23, 1.87]

0.5% 2.5% 1.7% 2.2% 1.7% 0.8% 0.8% 0.9% 2.1% 2.0% 1.5% 2.4% 1.3% 0.7% 1.3% 2.0% 1.4% 1.9%

5.76 [0.67, 49.60] 1.80 [0.96, 3.38] 4.55 [1.73, 11.98] 1.53 [0.73, 3.23] 1.49 [0.56, 3.95] 5.20 [1.00, 27.09] 3.72 [0.67, 20.63] 0.38 [0.09, 1.72] 2.92 [1.35, 6.30] 1.54 [0.67, 3.56] 0.83 [0.29, 2.42] 2.25 [1.14, 4.45] 1.44 [0.42, 4.90] 4.71 [0.78, 28.47] 1.44 [0.42, 4.92] 3.37 [1.49, 7.60] 3.67 [1.15, 11.66] 2.47 [1.05, 5.82]

This paper reports that patients with personality disorder and depression do more poorly than their counterparts with depression alone. It emphasizes the importance of assessing personality status in depression and highlights one of the potential reasons for the “treatment resistance” so often encountered in clinical practice—where personality structure often takes a back seat to any Axis I disorder. As well as recognizing personality disorder as an aid in prognosis, this paper highlights the need for ongoing assessment and research into the management of personality disorders in this patient group to assess if treatments developed for the management of personality disorder improve overall outcome in this patient group.

PERSONALITY DISORDER AND DEPRESSION 589 TABLE 3. (continued) PD Total No PD Total

Weight

Odds Ratio IV, Random, 95% CI

Van den Hout (2006) 1.3063 0.7596 25 15 Ezquiaga (1999) 2.0503 0.6039 25 62 Ilardi (1997) 3.0155 0.742 22 28 Keitner (1989) 0.6332 0.8526 8 70 Reich (1990) 0.1643 0.7609 25 10 Viinamaki (2002) 1.8589 0.4579 52 65 O’Leary (2001) 1.4994 0.8746 29 45 Morse (2005) 0.4218 0.3609 55 105 Casey (1996) 0.1446 0.6427 18 22 Ezquiaga (2004) 0.8109 0.6103 20 30 Shawcross (1985) 2.5982 0.7205 17 33 Melartin (2004) 0.3001 0.6494 85 113 Szadocsky (2004) 2.7444 0.5816 57 60 Klein (1998) 0.9808 0.4581 44 42 Vine (1994) 0.991 0.589 18 38 Stek (2002) 1.8632 0.8035 15 32 Subtotal (95% CI) 1404 1610 Heterogeneity: Tau² = 0.24; Chi² = 59.90, df = 33 (P = 0.003); I² = 45% Test for overall effect: Z = 7.58 (P < 0.00001) 1.6.3 Case series reviews 0.8246 0.2162 100 1210 Black (1991) 1.0549 0.7389 10 58 Bschor (2001) 0.7184 0.2852 76 152 Black (1988) 2.3979 0.8034 40 24 Charney (1981) 0.8199 0.2982 124 77 Goethe (1988) 1.5404 0.5327 36 30 Persons (1988) 0.2485 0.7194 77 11 Alnaes (1997) 463 1562 Subtotal (95% CI) Heterogeneity: Tau² = 0.01; Chi² = 6.36, df = 6 (P = 0.38); I² = 6% Test for overall effect: Z = 6.13 (P < 0.00001) 3546 4763 Total (95% CI) Heterogeneity: Tau² = 0.19; Chi² = 121.24, df = 59 (P < 0.00001); I² = 51% Test for overall effect: Z = 8.98 (P < 0.00001)

1.0% 1.3% 1.0% 0.8% 1.0% 1.8% 0.8% 2.3% 1.2% 1.3% 1.0% 1.2% 1.4% 1.8% 1.4% 0.9% 47.9%

3.69 [0.83, 16.36] 7.77 [2.38, 25.38] 20.40 [4.76, 87.34] 1.88 [0.35, 10.02] 1.18 [0.27, 5.24] 6.42 [2.62, 15.74] 4.48 [0.81, 24.87] 1.52 [0.75, 3.09] 1.16 [0.33, 4.07] 2.25 [0.68, 7.44] 13.44 [3.27, 55.17] 1.35 [0.38, 4.82] 15.56 [4.98, 48.63] 2.67 [1.09, 6.54] 2.69 [0.85, 8.55] 6.44 [1.33, 31.13] 2.68 [2.08, 3.46]

Study or Subgroup

log[Odds Ratio]

SE

3.1% 1.0% 2.7% 0.9% 2.6% 1.6% 1.0% 12.9%

2.28 [1.49, 3.48] 2.87 [0.67, 12.22] 2.05 [1.17, 3.59] 11.00 [2.28, 53.12] 2.27 [1.27, 4.07] 4.67 [1.64, 13.26] 1.28 [0.31, 5.25] 2.43 [1.83, 3.22]

100.0%

2.16 [1.83, 2.56]

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