Qual Life Res (2010) 19:1105–1113 DOI 10.1007/s11136-010-9671-z Using the Short Form-36 mental summary score as an indicator of depressive symptoms in patients with coronary heart disease Rosanna Tavella • Tracy Air • Graeme Tucker • Robert Adams • John F. Beltrame • Geoffrey Schrader Accepted: 21 April 2010 / Published online: 13 May 2010 Ó Springer Science+Business Media B.V. 2010 Abstract Background Depression is common in patients with cardiac disease; however, the use of depression-specific health instruments is limited by their increased responder and analyst burden. The study aimed to define a threshold value on the Short Form-36 (SF-36) mental component summary score (MCS) that identified depressed cardiac patients as measured by the Centre for Epidemiologic Studies Depression Scale (CES-D). Methods An optimal threshold was determined using receiver-operating characteristic (ROC) curves on SF-36 and CES-D data from a large cardiac cohort (N = 1,221). The performance of this threshold was evaluated in a further two cardiac populations. Results In the index cohort, an SF-36 MCS score of B45 was revealed as an optimal threshold according to maximal Youden Index, with high sensitivity (77%, 95% CI = 74– 80%) and specificity (73%, 95% CI = 69–77%). At this threshold, in a second sample of hospital cardiac patients, R. Tavella (&)
J. F. Beltrame Cardiology Research Unit, The Queen Elizabeth Hospital, University of Adelaide, 28 Woodville Rd, Woodville South, 5011 Adelaide, SA, Australia e-mail: rosanna.tavella@adelaide.edu.au T. Air
G. Schrader Discipline of Psychiatry, University of Adelaide, Adelaide, SA, Australia R. Adams Discipline of Medicine, University of Adelaide, Adelaide, SA, Australia G. Tucker Health Statistics Unit, Department of Health, Adelaide, SA, Australia sensitivity was 93% (95% CI = 76–99%) and specificity was 64% (95% CI = 49–77%). In a final sample generated from a community population, specificity was 100% (95% CI = 85–100%) and sensitivity was 68% (95% CI = 61– 74%) at the cut-off of 45. Conclusion The SF-36 MCS may be a useful research tool to aid in the classification of cardiac patients according to the presence or absence of depressive symptoms. Keywords Coronary heart disease
Short-Form 36 mental summary score
Centre for Epidemiologic Studies Depression Scale
Depression
Optimal threshold Abbreviations AUC Area under the curve CABG Coronary artery bypass grafting CAD Coronary artery disease CES-D Centre for Epidemiologic Studies Depression Scale CHD Coronary heart disease DM Diabetes mellitus HRQoL Health-related quality of life HT/Chol Hypertension and/or high cholesterol IDACC Identifying depression as a comorbid condition NPV Negative predictive value NWAHS North West Adelaide Health Service PCI Percutaneous coronary intervention PPV Positive predictive value ROC Receiver-operating characteristic SF-36 Short-Form 36 SF-36 MCS Short-Form 36 mental summary score SF-36 PCS Short-Form 36 physical summary score 123 1106 Introduction Depression is an independent risk factor for adverse cardiovascular outcomes in patients with Coronary heart disease (CHD) [1]. Studies have shown that the prevalence of depression in patients with CHD ranges from 14% to as high as 47% [2]. Although contemporary data does not indicate an improvement in cardiovascular events with the use of antidepressants in patients with CHD, these agents can be safely used to improve depressive symptoms [3–5]. The gold standard for the diagnosis of depression requires a clinical assessment with criteria defined by the Diagnostic and Statistical Manual of the American Psychiatric Association (DSM). This labour-intensive assessment is impractical for both screening procedures and research studies so that self-rated measures of depression have been developed [6]. Self-rated depression scales are among the best established health measurements, and many of them have similar degrees of validity and reliability to a clinical interview [7, 8]. The Centre for Epidemiologic Studies Depression Scale (CES-D) is a purpose-built scale that has received extensive assessment in numerous studies [9–11]. It was developed to identify depression in the general population and has shown strong internal consistency, good reliability and has been validated against clinical and self-report criteria [12]. Measuring patient-perceived health-related quality of life (HRQoL) is an important outcome in cardiac care. [13]. Many instruments have been developed to quantify patient’s HRQoL with the most commonly used general instrument being the Short Form 36 (SF-36) [14, 15]. The SF-36 profiles eight health domains that are relevant to general functional status and well-being. The eight scales are aggregated into two summary scales, a physical component score (PCS) and mental component score (MCS). The component scores are empirically valid and provide an interpretation of physical and mental dimensions of health status [16]. The SF-36 has been validated extensively [17, 18] and has been established as the best generic measure of HRQoL among people with CHD due to its sound psychometric properties [19, 20]. Although the Mental Health (MH-5) subscale of the SF-36 has been shown to be an indicator of depression [21], and also related to mental health status of coronary patients [22], a comprehensive evaluation of depression requires more than a measure of mental health itself, but an assessment of limitations in daily roles and social functioning [23]. The SF-36 MCS is a psychometrically sound measure capturing overall functioning as a result of mental health. In addition, in general health populations, the SF-36 MCS has exceeded performance of the MH-5 in both tests of self-reported mental health and the effects of clinical depression in crosssectional and longitudinal studies [24]. The SF-36 MCS 123 Qual Life Res (2010) 19:1105–1113 has also been shown to be a good indicator of depression in both general and diseased populations [25–27]. However, there is no data demonstrating the use of the SF-36 MCS in identifying cardiac patients who exhibit depressive symptoms. Hence, defining the effectiveness of the SF-36 MCS in identifying depressed cardiac patients would be a useful research tool. This is particularly pertinent as many studies have utilised the SF-36 but few have employed specific depression measures; thus, retrospective identification of depressed CHD cohorts would increase research capabilities in this field. Therefore, the objective of this study was to define a threshold score on the SF-36 MCS that would categorise a population with cardiac disease into depressed and non-depressed as benchmarked by the CES-D. Methods In order to establish a depression threshold score for the SF-36 MCS, three patient cohorts with cardiac disease were utilised as outlined below. The threshold was defined in the first study cohort (IDACC) and then assessed in the remaining two cohorts, each with differing clinical characteristics and varying prevalence of depression. All three cohorts were primarily recruited from the same geographic location, namely the north-western suburbs of Adelaide. Study cohorts IDACC cohort The Identifying Depression as a Comorbid Condition (IDACC) study was a randomised controlled trial assessing the impact of psychiatric liaison with general practitioners on depressive symptoms in patients with cardiac conditions. The study protocol has been previously published [28] and only patients with confirmed CHD were included in the analysis. This was defined by hospital admission or documented history of myocardial infarction, unstable angina, coronary artery bypass grafting or percutaneous coronary intervention. All patients completed an SF-36 and CES-D at baseline, which have been obtained for this analysis. NWAHS cohort The North Western Adelaide Health Service (NWAHS) study was a population-based biomedical cohort investigating the prevalence of a number of chronic conditions and health-related risk factors along a continuum [29]. Patients in this study were randomly recruited using the telephone to conduct interviews and the Electronic White Qual Life Res (2010) 19:1105–1113 Pages as the sampling frame resulting in a representative population sample for the Northwest region of Adelaide as detailed in previous studies [29, 30]. A selection of patients recruited for baseline examination was defined as the cardiac subset. Studies have indicated that self-reported cardiovascular events show good concordance with medical records and hospital diagnostic codes [31–33]. Therefore, the inclusion criterion for this group was the self-report of patients responding to a history of events, either angina or myocardial infarction, as diagnosed by a doctor. Several days prior to an appointment for biomedical examination, participants were mailed a questionnaire pack containing the SF-36 and CES-D to be self-administered and then checked for accuracy during the examination. Coronary angiogram cohort The final cohort included consecutively recruited patients undergoing coronary angiography at the Queen Elizabeth Hospital for the investigation of chest pain. The purpose of the study was to assess 12-month health outcomes in these patients. A small subgroup of these patients completed the SF-36 and CES-D at baseline which were utilised for this study. Study definitions The cardiovascular risk factors were predominantly based upon self-report. The existence of coronary artery disease (CAD) was confirmed angiographically in the coronary angiogram cohort, hospital admission diagnosis or documented history in the IDACC cohort and by self-reported MI and/or angina in the NWAHS cohort. Consistent with previous research, current depression and severe depression were defined by CES-D total scoring of C16, and C27, respectively [34, 35]. In each cohort, demographic data was obtained via self-report or extracted from hospital records. Socio-economic status was defined by the Australian Bureau of Statistics’ Socio-Economic Indexes for Areas scores, an accepted proxy measure for socio-economic status based on regional analyses in Australia [36]. Data analysis Using the above cross-sectional baseline data from the 3 independent cohorts, all analyses were performed with STATA (Version 10, StataCorp, Texas, USA). Prior to defining an SF-36 MCS depression threshold, the relationship between the SF-36 MCS and CES-D was determined using Pearson’s correlation coefficients. Receiver operating characteristic (ROC) curves were then used to determine the relative sensitivity and specificity of the SF-36 MCS relative to the CES-D gold standard. As 1107 established in previous studies, a CES-D score of C16 was used to define the presence of depression [34, 35]. From the ROC analysis on the IDACC data, a specific threshold value was derived demonstrating a maximal Youden Index (sensitivity ? specificity - 1) [37]. This optimal threshold from the IDACC cohort was then evaluated in the NWAHS and coronary angiogram cohorts in conjunction with their respective ROC curves. In addition, positive predictive values (PPV) and negative predictive values (NPV) were measured for different threshold scores in the central range of the SF-36 MCS scores. Independent samples’ t-tests compared SF-36 MCS mean scores between depressed and not depressed groups according to CES-D scoring. Clinical characteristics between the three groups were compared using Fishers’ exact test for categorical variables and ANOVA for continuous data. Power calculation The prevalence of depression in the overall IDACC population was 46% (674 out of 1,455). Previous studies determining SF-36 MCS thresholds relative to CES-D data in chronic spinal pain patients [38] reported 80% sensitivity and 90% specificity. Therefore, in the primary analysis in the derivation cohort (IDACC), and according to the prevalence inflation method [39], using a maximum acceptable width of 10% for the confidence intervals (i.e. a precision of 5%), to achieve 95% confidence intervals in sensitivity and specificity, 532 and 258 patients would be required, respectively. Results Study cohorts’ patient characteristics The patient characteristics and HRQoL scores for the IDACC, NWAHS and coronary angiogram cohorts are summarised in Table 1. The three cohorts were of similar gender distribution; however, the NWAHS cohort was older (P \ 0.01). There was also heterogeneity in the coronary risk factors with the prevalence of smoking, diabetes, hypertension and hypercholesterolaemia being higher in the IDACC cohort compared to the NWAHS cohort (P \ 0.01). In addition, prevalence of depressive symptoms and history of mental illness was higher in the IDACC patients compared to NWAHS (P \ 0.01). There was a significant negative correlation between SF-36 MCS and CES-D scores for the IDACC (r = -0.68, P \ 0.01), NWAHS (r = -0.65, P \ 0.01) and coronary angiogram cohorts (r = -0.77, P \ 0.01). The SF-36 MCS scores for IDACC, NWAHS and angiogram cohort were significantly lower in the depressed patients (CES-D 123 1108 Qual Life Res (2010) 19:1105–1113 Table 1 Clinical characteristics and HRQoL scores (mean ± SD) for the study cohorts Characteristic IDACC (n = 1,221 NWAHS (n = 222) Angiogram (n = 80) Age 62 ± 12* 69 ± 11 61 ± 11 Females 31% 31% 32% Risk factors Current smoker 23%* 12% 15% DM 22%* 31% 31% HT/Chol 66%* 82% 85%^ HRQoL SF-36 PCS 35 ± 11* 41 ± 13 43 ± 10^ SF-36 MCS 46 ± 12 47 ± 12 37 ± 10^ CES-D 17 ± 11* 7±9 14 ± 9 Depressed CES-D C 16 Severe depression CES-D C 27 44%* 19%* 13% 5% 38% 13%^ History of mental illness 28%* 14% 15%^ Married/defacto 66%* 59% 73% Separated/divorced 16% 15% 16% Widowed 12%* 21% 4% Never married 5% 5% 7% Employed 22% 17% 37% Unemployed 3% 2% 2% Home duties/retired 67%* 78% 14%^ Pensioner/other 6%* 3% 46%^ Low advantage 28% 24% 23% Medium advantage 45%* 37% 35%^ High advantage 23%* 17% 38%^ Marital status Work status Socio-economic status DM, diabetes mellitus; HT/Chol, hypertension and/or high cholesterol; CAD, coronary artery disease; SF-36 PCS, SF-36 physical summary score; SF-36 MCS, SF-36 mental summary score; CES-D, centre for epidemiologic studies depression scale P values for ANOVA for continuous variables and Fishers exact test for categorical variables * P \ 0.01 IDACC versus NWAHS, ^ P \ 0.01 IDACC versus coronary angiogram cohort, cohort score C 16), (39 ± 11, 30 ± 10, 35 ± 6, respectively) compared with those not depressed (52 ± 9, 49 ± 10, 48 ± 8, respectively). ROC characteristics in IDACC sample Using ROC analysis, overall there was a significant prediction for the CES-D scores as measured by the SF-36 MCS scores (AUC = 0.82 SE 0.01, 95% CI 0.8–0.85). Utilising a high specificity (90%, 95% CI = 87–92%), at the SF-36 MCS threshold value of 39, 72% of patients were appropriately assigned as being depressed as per the CESD scores. However, the sensitivity of this SF-36 MCS threshold value was 50% (95% CI = 46–54%), indicating that half of the patients depressed as per the CES-D scores were identified correctly. 123 P \ 0.01 NWAHS versus coronary angiogram Using the maximal Youden Index, the optimal SF-36 MCS threshold value for detecting depressive symptoms was 45 (PPV = 72%, 95% CI = 68–76; NPV = 79%, 95% CI = 75–82. At this threshold, sensitivity was 73% (95% CI = 69–77%), so that 27% of patients were falsely identified as experiencing depressive symptoms. Specificity was increased to 77% (95% CI = 74–80%), and 76% of patients were appropriately classified. The operating characteristics, NPVs and PPVs are summarised in Table 2. Accuracy of the SF-36 mental summary score in NWAHS and coronary angiogram cohorts To establish the usefulness of the SF-36 MCS in detecting depressive symptoms, the ROC curves were analysed separately in a cohort with a low prevalence of depression Qual Life Res (2010) 19:1105–1113 1109 Table 2 Operating characteristics for the central range of SF-36 MCS cut-points in the IDACC cohort SF-36 MCS cut-off Sensitivity 95% CI Specificity 95% CI Appropriately classified (%) PPV 95% CI NPV 95% CI B39 50%(46–54) 90% (87–92) 72 80% (75–84) 70% (66–73) B40 55% (50–59) 88% (85–90) 73 78% (74–82) 71% (68–74) B41 58% (54–62) 87% (84–89) 74 77% (73–81) 72% (69–75) B42 61% (57–65) 85% (82–87) 74 76% (72–80) 73% (70–77) B43 65% (61–69) 82% (79–85) 75 74% (70–78) 75% (71–78) B44 69% (65–73) 79% (76–82) 75 73% (68–76) 76% (73–79) B45* 73% (69–77) 77% (74–80) 76 72% (68–76) 79% (75–82) B46 76% (72–79) 75% (71–78) 75 70% (66–74) 80% (76–83) B47 78% (74–81) 71% (68–75) 74 68% (64–72) 80% (77–83) B48 80% (78–84) 69% (63–71) 74 69% (65–72) 80% (76–83) SF-36 MCS, SF-36 mental summary score; PPV, positive predictive value; NPV, negative predictive values Data obtained from receiver-operating characteristics for 1,221 observations * Optimal threshold according to maximal Youden Index (sensitivity ? specificity - 1) Table 3 Screening abilities of the central range of SF-36 MCS cut-points for the NWAHS and angiogram cohorts SF-36 MCS cut-off NWAHS Coronary angiogram Sensitivity Specificity PPV NPV Sensitivity Specificity PPV NPV B40 86% (67–95) 79% (73–85) 38% (27–51) 97% (93–99) 77% (57–89) 86% (73–94) 77% (57–89) 86% (73–94) B41 86% (67–95) 77% (70–82) 36% (25–48) 97% (93–99) 80% (61–92) 86% (73–94) 77% (58–90) 88% (75–95) B42 86% (67–94) 75% (68–80) 34% (23–46) 97% (93–99) 80% (61–92) 84% (70–92) 75% (56–88) 88% (74–95) B43 90% (72–97) 73% (66–79) 33% (23–45) 98% (93–99) 90% (72–97) 74% (59–85) 68% (51–81) 93% (79–98) B44 93% (76–99) 71% (64–77) 33% (23–44) 99% (94–100) 90% (72–97) 70% (55–82) 64% (48–78) 92% (78–98) B45 100% (85–100) 68% (61–74) 32% (23–43) 100% (96–100) 93% (76–99) 64% (49–77) 61% (45–75) 94% (79–99) SF-36 MCS, SF-36 mental summary score; PPV, positive predictive value; NPV, negative predictive value Data obtained from receiver-operating characteristics for 222 observations for the NWAHS sample and for 80 observations in the coronary angiogram cohort. Sensitivity, specificity, PPV and NPV are presented with 95% CI (NWAHS cohort) and one with a similar prevalence to the IDACC cohort (the coronary angiogram cohort). The overall accuracy for predicting depressive symptoms as measured by the AUC for the NWAHS and coronary angiogram populations were 0.91 (SE 0.02, 95% CI 0.87– 96) and 0.89 (SE 0.04, 95% CI 0.8–0.95), respectively. Using the optimal SF-36 MCS threshold value of 45 derived from the IDACC cohort, ROC analysis of the NWAHS cohort elucidated a sensitivity of 100% (95% CI = 85–100%) and specificity of 68% (95% CI = 61– 74%). Positive and negative predictive values were 32% (95% CI = 23–43%) and 100% (95% CI = 96–100%), respectively. Similar levels of accuracy were observed for the coronary angiogram cohort with this SF-36 MCS threshold value of 45 (sensitivity = 93%, 95% CI = 76– 99%, specificity = 64%, 95% CI = 49–77%; PPV = 61%, 95% CI = 45–75%; and NPV = 94%, 95% CI = 79–99%, Table 3). According to maximal Youden Index, the optimal threshold found in the NWAHS cohort was also 45, and in the coronary angiogram cohort, the optimal threshold was 41 (sensitivity = 80%, 95% CI 61–92; specificity = 86%, 95% CI = 73–94; PPV = 77%, 95% CI 58–90; and NPV = 88%, 95% CI = 75–95). At the optimal threshold of 45, the proportion of patients appropriately identified as depressed on the SF-36 MCS according to CES-D scoring for the NWAHS and coronary angiogram cohort was 71 and 75%, respectively, compared to 76% in IDACC (Table 4). Discussion This investigation has first established that the SF-36 MCS is correlated with the CES-D scores in CHD populations. Secondly, the SF-36 MCS threshold value of 45 derived from ROC analysis according to the maximal Youden Index could identify a depressed subgroup in the index (IDACC) cohort (Table 2), as defined by the CES-D, with sensitivity of 73% and specificity of 77%. Moreover, when 123 1110 Qual Life Res (2010) 19:1105–1113 Table 4 Proportion of patients appropriately classified by the SF-36 MCS for the central range of cut-points for each study cohort SF-36 MCS cut-off Appropriately classified IDACC (%) (n = 1,221) NWAHS (%) (n = 222) Angiogram (%) (n = 80) B40 73 80 83 B41 74 78 84 B42 74 76 83 B43 75 75 80 B44 75 73 78 B45 76 71 75 Data obtained from receiver-operating characteristic SF-36 MCS, SF-36 mental summary score prospectively applying this threshold value to CHD cohorts with a low and high prevalence of depression (NWAHS and coronary angiogram cohorts, respectively), similar levels of accuracy were observed (Table 3). To our knowledge, this is the first study to establish the accuracy of the SF-36 MCS as an indicator of depressive symptoms in a cardiac population. It must be recognised that the use of the SF-36 MCS threshold has not been confirmed as a screening or diagnostic tool but as a research tool for group observations utilising a generic measure and that interpretations of individual scores should not be made. Accordingly, studies where specific depression questionnaires were not administered to CHD cohorts may utilise the SF36 MCS as a surrogate method to define a subgroup experiencing depressive symptoms. This will enable further investigation of depression in cardiac patients particularly in studying the relationships between depressive symptoms and other variables. The strength of the above findings includes the following: (a) three well-characterised study cohorts, (b) use of an index cohort to establish the SF-36 MCS threshold criteria with subsequent validation in independent populations and (c) variable prevalence of depression within the study cohorts. This later feature is particularly important as disease prevalence within a population substantially influences the predictive ability of the instrument. The difference between the prevalence of depression among the cohorts reflects the recruitment strategy and further illustrates the diversity of the study population. The IDACC cohort was recruited from in-hospital patients, which may account for the higher prevalence of depression. In contrast, the NWAHS cohort was recruited from the general population by telephone interview. The coronary angiogram cohort was recruited from those undergoing angiography with 59% being undertaken electively as day cases. Hence, the cohorts are representative of the spectrum of patients with CHD. 123 As illustrated in Table 2, assigning a threshold value for the SF-36 MCS is difficult considering the trade-off between sensitivity and specificity. In order to achieve a balanced threshold, the Youden Index was employed. This index provides the optimal threshold value for which sensitivity ? specificity - 1 is maximised, representing the point on the ROC curve farthest from chance. Although other indices are available to establish threshold values, the Youden Index was chosen as it is well established and not dependent on prevalence rates [40] and has been previously used in cardiovascular studies [41]. The relationship of the SF-36 MCS to depressive symptoms has been reported previously. The Medical Outcomes Study (MOS) investigated the functioning and well-being of depressed patients and showed that depression has an additive adverse effect on patient functional status and well-being as indicated by scores on the SF-36 [25]. In addition, the SF-36 MCS scale has been evaluated as a screening tool for clinical depression using a two-stage screening approach in which positive CES-D results were followed by a clinical interview. ROC analysis showed that the best all around cut-off for the SF-36 MCS for detecting depressive disorder was at a score of 42 or below in a community sample of MOS patients with chronic conditions [16]. Other studies have investigated the use of the SF-36 MCS in disease-specific samples. Discriminate function analysis showed that the SF-36 MCS had a positive predictive value of 98% in differentiating major depression from minor or no depression in patients with chronic pain after controlling for age, gender and pain diagnosis [27]. In a sample of patients with asthma, depressive symptoms had an important role in patient-derived functional status and health-related quality of life as measured by the MCS of the SF-36, even after adjusting for current disease activity [26]. Walsh et al. [38] confirmed the effectiveness of the SF-36 MCS in detecting depression in a chronic spinal pain population. The CESD was also used a gold standard and a score of 35 on the MSS was identified as an optimal cut-off. This lower threshold could be attributed to a higher cut-off of 19 on CES-D scoring to indicate depression. Thus, the SF-36 has been shown to be a good indicator of depression in both general and diseased populations. Previous studies have demonstrated the ability of the various depressive screening instruments to identify cardiac patients with depression [42, 43]; however, there are no previous studies confirming this for the SF-36 as a generic health measure in cardiac patients. Our study has evaluated the effectiveness of the SF-36 MCS in detecting depressive symptoms in cardiac patients, by determining an optimal threshold value on one patient population and then applying this value to two different Qual Life Res (2010) 19:1105–1113 1111 Table 5 Optimal threshold in index cohort and validation cohorts IDACC NWAHS Coronary angiogram SF-36 MCS threshold 45* 45*^ 45* 41^ Sensitivity 73% (69–77) 100% (85–100) 93% (76–99) 80% (61–92) Specificity 77% (74–80) 68% (61–74) 64% (49–77) 86% (73–94) PPV 72% (68–76) 32% (23–43) 61% (45–75) 77% (58–90) NPV 79% (75–82) 100% (96–100) 94% (79–99) 88% (75–95) Appropriately classified 76% 71% 75% 84% * Optimal threshold in index cohort according to maximal Youden Index ^ Optimal threshold in individual cohort according to maximal Youden Index SF-36 MCS, SF-36 mental summary score; PPV, positive predictive value; NPV, negative predictive value. Data obtained from receiveroperating characteristic for 1,221 observations for IDACC study, 222 observations for the NWAHS sample and for 80 observations in the coronary angiogram cohort. Sensitivity, specificity, PPV and NPV are presented with 95% CI ‘‘test cohorts’’ with clinically diverse characteristics. Thus, we have illustrated the variation in sensitivity, specificity and predictive value between the different samples, and also for different optimal thresholds (Table 5). Accordingly, differences in the populations being sampled will lead to differences in levels of accuracy and misclassification. The prevalence of depression (CES-D C 16) was similar in the IDACC and coronary angiogram cohorts, but it was much lower in the NWAHS cohort, reflecting the lowest PPV. There were also several differences in the average of SF-36 MCS and CES-D values, and also in the age and risk factor distribution between the three samples. Since sensitivity and specificity are independent of disease prevalence, these differences may contribute to the variability noted in the capabilities of the SF-36 MCS in detecting depressive symptoms. The main limitation of this study is the absence of a structured diagnostic interview to formally confirm the presence of depression in the study cohorts. However, as discussed previously, such a comparison is unlikely to be undertaken in population studies given the extensive workload and costs that would be involved. As an alternative, we have used the CES-D questionnaire which is a well-established, reliable instrument that has been validated against the structured diagnostic interview [35]. The CES-D was chosen as it was available in the cohorts studied and compares favourably with other depressionspecific instruments (Table 6). We acknowledge that the threshold presented may vary with an alternative diagnostic tool, such as the DSM criteria, resulting in varying estimates of sensitivity and specificity. Our results are also limited by the lack of generalizability since the cohorts were recruited from a single region. In addition, wide confidence intervals noted in the NWAHS and angiographic cohorts limit the precision of the estimates. Another limitation of this study relates to the potential of the SF-36 MCS to misclassify depression. However, since depression is a disorder which lies on a continuum scale, every dichotomous assessment, even when developed from the gold standard, will contend with inappropriate classification to some degree. In this case, it would introduce a degree of non-differential misclassification, which would tend to bias any difference towards the null and therefore potentially miss relationships that may exist with depression. Lastly, it would have been desirable to confirm the self-reported CHD in the NWAHS cohort. Future studies are needed to validate the findings in large and diverse CHD populations. Table 6 Performances of self-rating scales in screening for depressive symptoms Scale Cut-off n Patient population PR (%) Sensitivity (%) Specificity (%) PPV Gold standard Reference HADS 9/21 501 Outpatients 13 85 76 35% DSM-IV Lowe et al. [44] PHQ 11/27 501 Outpatients 13 98 80 43% DMS-IV Lowe et al. [44] BDI 9/10 298 Community 9 85 86 37% DSM-III Oliver and Simmons [45] CESD 16/60 80 Stroke 32 90 86 80% DSM-III Parikh et al. [46] GDS 11/30 134 Community 26 68 89 49% SCID Gerety et al. [47] SDS 59/60 55 Outpatients 31 76 82 65% DSM-III Okimoto [48] HADS, hospital anxiety and depression scale; PHQ, patient health questionnaire; BDI, beck depression inventory; CESD, centre for epidemiological studies depression scale; SDS, self-rating depression scale; GDS, geriatric depression scale; PR, prevalence of major depressive disorder; PPV, positive predictive value; DSM, diagnostic and statistical manual of mental disorders; SCID, structured clinical interview for DSM disorders 123 1112 This study has described a SF-36 MCS threshold that will enable CHD populations to be classified into depressed and non-depressed groups relative to CESD scoring, thereby enabling important analyses to be undertaken in large cardiac cohorts that have completed the widely utilised SF-36 questionnaire. 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