The incidence and causes of different subtypes ofdepression in prostate cancer patients: implications forcancer care

C.F. SHARPLEY, BSC, MSC, PHD, PROFESSOR, Brain-Behaviour Research Group, University of New England, Armidale,New South Wales, V. BITSIKA, BBSC(HONS), MPSYCH, PHD, PROFESSOR, Brain-Behaviour Research Group, Bond University,Gold Coast, Queensland, & D.R.H. CHRISTIE, MB, CHB, RADIATION ONCOLOGIST, Premion, Tugun, Queensland,

Australia

SHARPLEY C.F., BITSIKA V. & CHRISTIE D.R.H. (2013) European Journal of Cancer Care 22, 815–823The incidence and causes of different subtypes of depression in prostate cancer patients: implications forcancer care

Although depression occurs in prostate cancer patients at a higher incidence than in age-matched non-cancerpeers, little is known about the relative incidence of subtypes of depression among these patients. To examinethis issue, 507 prostate cancer patients completed a survey questionnaire of background factors, depressionsymptoms, and common prostate cancer-related stressors. Five common subtypes of depression were definedfrom the wider literature, and patients’ depressive symptomatology was used to determine their scores oneach of the five depression subtypes. Nearly half of the patients had scores which could be classified asclinically significant for at least one of the five depression subtypes, with some patients showing clinicallysignificant scores for multiple depression subtypes. Different depression subtypes were predicted by differentprostate-cancer-related stressors. Because each of the five depressive subtypes examined here has differentsymptomatologies and treatment recommendations, these data suggest that treatment goals for prostate cancerpatients might vary according to the type of depression a patient presents.

Keywords: oncology, cancer, prostate, depression, stress.

INTRODUCTION

As commented by Prince et al. (2007), many diseasesshow causal associations with depression, and mental dis-orders such as depression in turn contribute to increasedmortality. As has been demonstrated, receiving a diag-nosis of prostate cancer (PCa) is a risk factor for develop-ment of depression (Bennet & Badger 2005), whichmay then be associated with increased emergency roomvisits, hospitalisation, outpatient visits, and mortality

(Jayadevappa et al. 2011). In addition, depression can havepowerful and extended effects by hindering treatment com-pliance and decision-making (Christie et al. 2009), perhapsreducing patients’ chances of recovery (Thomas et al.2009). Thus, accurate assessment and treatment planningfor depression in this patient group is essential to effec-tively address its direct and indirect effects.

However, a major challenge to interventions aimed atreducing the psychological distress that is associated withPCa patients’ depression (Lintz et al. 2003; Hersch et al.2009; Peeters et al. 2009) is that the precise nature ofdepression which PCa patients experience has receivedlittle attention, despite this issue having been raised forcancer in general (Raison & Miller 2003). One way inwhich depression might vary across PCa patients isin terms of its underlying biology. For example, severalcomments have focussed upon the differences between

Correspondence address: Christopher F. Sharpley, PO Box 378,Coolangatta, Qld 4225, Astralia (e-mail: csharpley@onthenet.com.au).

Accepted 28 May 2013DOI: 10.1111/ecc.12090

European Journal of Cancer Care, 2013, 22, 815–823

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Original article

© 2013 John Wiley & Sons Ltd

depression as it is more commonly diagnosed and ‘atypicaldepression’, which has different neuroendocrine patho-physiology (Parker et al. 2002; Murck 2003; Antonijevic2006). Another way in which depression has beenconceptualised is in terms of the number of symptomspresent, as in the constructs of ‘subsyndromal depression’(Judd et al. 1994) or ‘minor depression’ (Rapaport et al.2002), which can approximate the disease burden of MajorDepressive Episode (MDE) despite the patient showingonly a subset of the symptoms of that disorder (Juddet al. 1996). Other models of depression are reflected inthe DSM-IV-TR diagnostic criteria profiles which patientsmay present, such as melancholic depression, depressionin which physiological reactivity plays a central role,and depression with catatonic features (APA 2000). Theseand other subtypes of depression have been investigatedin several previous studies of non-PCa samples (e.g.Leckman et al. 1984; Yang & Dunner 2001; Singh &Williams 2006; Kessing 2007).

Different subtypes of depression may also require differ-ent treatments. For example, melancholic depressionis relatively resistant to psychotherapy (Feinberg 1992).Additionally, whichever of the two major DSM-IV-TR cri-teria for MDE is present (i.e. depressed mood vs. anhedo-nia) may also be an important factor in deciding ontreatment goals, since anhedonic patients are less likely tobe able to form close personal relationships with theirpsychotherapists, or to undertake the kinds of cognitive-behavioural ‘homework’ activities that are designed tohelp them build more satisfying lifestyles and whichmay be used with patients who exhibit depressed moodwithout anhedonia (Pelle et al. 2010). Depression inwhich physiological or somatic symptoms are more preva-lent may also require a different focus to that in which thepredominant symptomatology is emotion- or cognitive-based (Beck et al. 1979; Chan & Tsoi 1984; Silverstein2002). As may be gathered, accurate assessment of depres-sion therefore includes consideration of these various sub-types of depression.

It is also valuable to gather assessment informationabout the specific ‘causes’ of these subtypes of depressionin PCa patients. Such information can help differentiatetreatment targets, as well as clarify how patients actuallycame to develop the particular constellation of depressivesymptoms they present. As noted by Raison and Miller(2003), receiving a diagnosis of cancer is ‘one of life’s mostdisturbing and dispiriting events’ (p. 283), and constitutesthe particular kind of major stressor that can lead to whatwas previously termed ‘reactive’ depression (e.g. Bissonet al. 2002; Bennet & Badger 2005). In research designed toexplore and identify these stressors, we have previously

identified the major aversive stressors of PCa and its treat-ment (Sharpley et al. 2009, 2010), and have shown thatthese stressors may be grouped into various componentsthat predict clinically significant depression. However,that work was performed using a unitary measure – totaldepression scale scores – and did not examine the associa-tions between PCa-related stressors and the subtypes ofdepression such as those mentioned above.

More effective treatment choices may emerge from anunderstanding of the incidence of subtypes of depressionin PCa, and of the relationships between the specificstressor components of PCa and particular subtypesof depression that men with PCa present. Therefore,this study was designed to investigate the incidence of,and relationships between, five subtypes of depression(described below) that occur in men with PCa, and thekinds of PCa-related stressors that were most powerfullyassociated with those subtypes of depression.

METHODS

Sample

From 965 PCa patients in Brisbane, Australia, who wereinvited by letter to participate, 507 (52.22%) completedusable questionnaires. All participants had cancerslimited to the primary site and regional draining lymphnodes using conventional staging investigations. Treat-ments included radiotherapy, plus hormone therapy andsurgery when required.

Measures

Background questionnaire: age, living situation, monthand year of first diagnosis, treatments received and con-tinuing (surgery, radiation therapy, anti-androgen therapy),present status of their cancer (present, in remission,returned after remission).

Depression: The Zung Self-Rating Depression Scale(SDS) (Zung 1965) is a standardised paper and pencil test ofdepression that has been used in studies of depression inPCa patients. Having been developed on the basis of factoranalytic studies of the syndrome of depression whichunderlie the DSM definition (APA 2000), the SDS includesitems for all of the current DSM-IV-TR criteria for MDE.Respondents are asked to indicate the frequency ‘duringthe last two weeks’ of each of the depressive symptomscontained in the 20 items of the SDS by answering in oneof four possible ways: ‘None or a little of the time’, ‘Someof the time’, ‘Good part of the time’, or ‘Most or all of thetime’. Raw scores range from 20 to 80, with higher scores

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being indicative of more severe depression. The SDS hasdemonstrated split-half reliability of 0.81 (Zung 1965),0.79 (DeJonge & Baneke 1989) and 0.94 (Gabrys & Peters1985). Internal consistency (alpha) has been reported as0.88 for depressed patients and 0.93 for non-depressedpatients (Schaefer et al. 1985), and as 0.84 for a previousAustralian PCa samples (Sharpley & Christie 2007). Thevalidity of the SDS has been shown to be superior to theMinnesota Multiphasic Personality Inventory DepressionScale and the Beck Depression Inventory for assessingdepression in male psychiatric inpatients (Schaefer et al.1985). SDS scores of 40 or above indicate the presence of‘clinically significant depression’ (Zung 1973, p. 335). SDSraw scores were used in this study.

Depression subtypes: Five subtypes of MDE wereselected for examination because (i) they are commonlyreported in the wider literature, (ii) they represent signifi-cant aspects of the DSM-IV-TR symptomatology forthis disorder, (iii) their basic symptomatology overlapsonly marginally if at all, and (iv) because they havebeen shown to require different treatment approaches.These subtypes were: Melancholic, Depressed Mood,Anhedonic, Somatic, and Cognitive depression. Becausethe SDS taps all the symptoms of MDE, it can also be usedto measure the subset of SDS items which are features ofthese subtypes of MDE. In addition, there may be someconfound between certain physiological symptoms of anillness and MDE (described as ‘Mood Disorder due to aGeneral Medical Condition’ in the DSM-IV-TR, whichmay occur when ‘the mood disturbance is judged to be thedirect physiological consequence of a specific medicalcondition’ (APA 2000, p. 374). Therefore, consideration ofthe particular symptoms that have been associated with adisease or its treatment in laboratory and field observa-tions needs to be undertaken when determining if theMDE symptoms are present.

Two steps were taken to identify the relevant SDS itemsfor each depression subtype. First, in order to identifywhich SDS items tapped the symptoms of MDE, the firstand second authors (both clinical psychologists whobetween them had over five decades experience in assess-ing and diagnosing MDE) blindly allocated each of the 20SDS items to the various MDE criteria from the DSM-IV-TR. Second, by reference to the DSM-IV-TR symptoms,the various SDS items were then allocated to each of thefive depression subtypes using the same blind process,and with reference to major definitions of each of thefive subtypes (Feinberg 1992; APA 2000; Parker et al.2002; Antonijevic 2006; Pelle et al. 2010). Inter-rateragreement for this task was 96% and any disagreementswere resolved by consensus.

Melancholic depression is indicated by extreme and per-sistent anhedonia, plus psychomotor retardation or agita-tion, excessive guilt or hopelessness, suicidal features,and appetite disturbances or weight changes (Marcos &Salamero 1990; Clark & Watson 1991; Leventhal & Rehm2005), and the SDS items which tapped these symptomswere allocated to this subtype. The SDS items that wereallocated to Depressed mood, Anhedonic depression andCognitive depression subtypes were relatively easy toidentify and were allocated to those subtypes. For Somaticdepression, it was necessary to ensure that any somaticoutcomes of PCa or its treatment were not included in theSDS items used to measure this subtype of depression.Mishel et al. (2002) reported that PCa-related somaticcomplaints included incontinence and impotence, urinarycontrol and sexual function, and bowel dysfunction. Stege(2000) also mentioned that tumour flare, hot flashes,fatigue and gynecomastia may follow anti-androgen treat-ments. Dearnaley et al. (1999) suggested that proctitis andbleeding might be included in this list. However, apartfrom SDS item 6 (‘I still enjoy sex’) and item 10 (‘I gettired for no reason’), none of these somatic symptoms areincluded in the SDS. Therefore, the SDS items used todefine Somatic depression were those which correspondedwith DSM criteria 3, 4, 5 (i.e. weight loss or gain/lossof appetite, insomnia or hypersomnia, psychomotoragitation/retardation). SDS items 6 and 10 were deletedfrom this list. In addition, the third author (an oncologist)also inspected each patient’s data set to determine if anyof the somatic symptoms that were identified as relatingto Somatic depression were likely to be a ‘direct physi-ological consequence’ of the PCa or treatment, and anyinstances of this were eliminated from the data set.Finally, as described below, there were no significant rela-tionships between any disease or treatment factors andany of the depression subtypes. Sexual function was alsodeleted from the lists of SDS items used to assess Melan-cholic and Anhedonic depression. Table 1 shows each ofthe five depression subtypes, plus a list of the relevantSDS items which reflected the symptoms of those depres-sion subtypes that were found in the wider literature. Inorder to enable direct comparisons between depressionsubtype scores, the mean scores for each of these fivesubsets of SDS items were used and each had a range from1 to 4.

Prostate-cancer-related stressors: The Effects of ProstateCancer on Lifestyle Questionnaire (EPCLQ: Sharpleyet al. 2010) is a 36-item scale which presents participantswith ‘a number of lifestyle changes that you may haveexperienced as a result of either receiving a diagnosis ofprostate cancer and/or any treatment that you may have

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© 2013 John Wiley & Sons Ltd 817

received for prostate cancer’. Patients respond by ticking abox on a four-point scale the same as for the SDS, and totalEPCLQ scores range from 36 to 144. The EPCLQ signifi-cantly correlates with anxiety (r = 0.626) and depression(r = 0.609), and has been shown to possess satisfactoryreliability (Sharpley et al. 2010). Factor analytic studiesindicate that it is comprised of six independent compo-nents [Adverse emotions & social withdrawal, Reducedrecreation and exercise, Lack of improved functioning,Physiological symptoms, Employment problems, and Lossof cognitive ability (Sharpley et al. 2010)]. These factorswere used in the current study.

Ethical approval for this study was obtained from theWesley Human Research Ethics Committee, Brisbane. Allparticipants gave written consent to take part in the study.

RESULTS

Demographic data

Table 2 shows the background variable data, none ofwhich correlated significantly with total SDS or depres-sion subtype scores.

Psychometric data

Reliability (Cronbach’s alpha) was satisfactory for the SDS(0.84) and the EPCLQ (0.88), allowing further examinationT

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Table 2. Demographic data

Variable Sample characteristics

Age (years) M = 67.1 (SD = 7.12),range = 26–87

Living situationWith wife/partner 86.1%With children 12.3%With other family 2.6%With non-family persons 6.3%Widowed 4.7%Divorced 6.0%Never married/partnered 2.9%

Time since diagnosis (months) M = 13.6 (SD = 17.9),range = 1–96

Treatments receivedRadiotherapy 31.8%Surgery 24.1%Hormone therapy 29.7%

Current treatmentRadiotherapy 24.4%Surgery 2.4%Hormone therapy 38.8%

Present statusCancer still present, undergoing

treatment70.4%

In remission (no signs) 24.4%Cancer recurring after previous

treatment5.3%

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© 2013 John Wiley & Sons Ltd818

of these data (Anastasi 1982). The mean SDS score was34.92 out of a possible score of 80 (SD = 8.81), rangingfrom 20 to 66. The 5% trimmed mean was 34.58, only 0.34less than the sample mean, thus discounting outliereffects. Skewness, kurtosis, boxplot inspection and exami-nation of the Normal Q–Q Plot and Detrended NormalQ–Q Plot argued for the normality of these SDS data. Themean total score for the EPCLQ was 65.69 out of a possi-ble score of 144 (SD = 13.12), with scores ranging from 38to 134. The 5% trimmed mean was 64.76, only 0.92 lessthan the sample mean, indicating that outlier effects werenegligible. Skewness, kurtosis and inspection of the his-togram and the Normal Q–Q Plot and Detrended NormalQ–Q Plot showed that these EPCLQ data satisfied normal-ity requirements.

Table 1 shows the mean, median, SD and ranges foreach depression subtype. Skewness and kurtosis werewithin normal limits for each of the depression subtypes.As mentioned above, a raw score of 40 or more has beendesignated by Zung (1973) as indicative of ‘clinically sig-nificant’ depression. Because 40 is half of the possible totalSDS raw score of 80, it may be extrapolated that scores of50% out of the possible total score for each depressionsubtype may be accepted as also indicative of a ‘clinicallysignificant’ response for those depression subtypes. There-fore, participants whose mean scores were greater than50% of the possible total score for the particular depres-sion subtype were identified as having ‘clinically signifi-cant’ scores on each of the relevant depression subtype.This procedure produced some overlap in participants’scores for the five depression subtypes, with subsamplesof 100 (19.3%) participants who had scores above 50%for Melancholic depression, 49 (9.3%) for DepressedMood, 147 (28%) for Anhedonic depression, 46 (8.8%) forSomatic depression, and 187 (35.8%) for Cognitive depres-sion. In addition, 89 participants (17.3%) scored above50% for one of the five subtypes of depression, 54 (10.5%)did so for two of the depression subtypes, 60 (11.7%) didso for three subtypes, 17 (3.3%) scored in this way forfour depression subtypes, and 15 (2.9%) scored above50% on all five depression subtypes. These data suggestthat, although most of the sample of PCa patients didnot present with clinically significant scores on any ofthe five subtypes of depression, the remaining 45.7% didhave SDS responses which indicated clinically significantscores for at least one of the subtypes of depression, sup-porting the use of the subtype approach over simply clas-sifying PCa patients as ‘depressed’ according to a unitaryconstruct.

Relationships between depressive subtypes and EPCLQcomponents and items.

(i) EPCLQ Factors: A series of multiple regressions wasused to test the associations between the six EPCLQcomponents and each depressive subtype. All assump-tions were met for each regression analysis. Table 3presents the results of these analyses, and indicatesthat the EPCLQ component of ‘Adverse emotions andsocial withdrawal’ was the most powerful predictorfor all of the depression subtypes except for Cognitivedepression, where it was the second most powerfulpredictor after ‘Loss of cognitive ability’. AlthoughMelancholic depression was also significantly pre-dicted by the EPCLQ components of ‘Employmentproblems’ and ‘Loss of cognitive ability’, hierarchi-cal regression revealed these two EPCLQ compo-nents explained only an additional 1.1% and 0.8%of the variance of Melancholic depression respec-tively. Similar hierarchical regressions revealed that‘Employment problems’ explained only an additional2.5% of the variance for Anhedonic depression;(ii) ‘Lack of improved functioning’ explained an addi-tional 4.2% of the variance for Somatic depression;and ‘Adverse emotions and social withdrawal’explained an additional 2.9% of the variance forCognitive depression. That is, the primary predictivepower of the various EPCLQ components for each ofthe subtypes of depression is that which is underlinedin Table 3.

(ii) EPCLQ items: However, these EPCLQ componentsare comprised of several EPCLQ items each. For‘Adverse emotions and social withdrawal’ there were10 EPCLQ items, and ‘Loss of cognitive ability’ wasbased on scores from four EPCLQ items. Therefore, inorder to investigate which (if any) of these variousEPCLQ items was the most powerful subcomponentof the two major EPCLQ components, Linear regres-sion was conducted for the 10 EPCLQ items compris-ing ‘Adverse emotions and social withdrawal’ onMelancholic depression, Depressed mood, Anhedonicdepression, and Somatic depression, with all resultsbeing significant at the P < 0.001 level. A similarlinear regression was conducted using the four EPCLQitems for ‘Loss of cognitive ability’ on the Cognitivesubtype of (P < 0.001). Figure 1 shows the correlationsbetween the five depressive subtypes, plus the EPCLQitems (italics) which were significant predictors foreach subtype (statistically significant β values areshown in italics).

From Figure 1, the interrelationships between the fivedepression subtypes may be grouped into three categoriesFirst, Melancholic depression correlated strongly with all

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four other depression subtypes, and accounted for between39.3% of the variance with Depressed Mood, 43.4% withCognitive depression, 47.6% with Somatic depression(as may be expected from the presence of some SDSitem overlap) and over 70% with Anhedonia (also partiallydue to SDS item overlap). Second (and less powerful),Depressed Mood accounted for over 40% of the variancein Somatic depression, for over 35% of the variance inAnhedonic depression, and for over 28% of the variancein Cognitive depression (and vice versa). Third, a lower set

of interrelationships was apparent between Anhedonicand Somatic depression (15.92% of the variance) andAnhedonic and Cognitive depression (22.65%), andbetween Cognitive and Somatic depression subtypes(16.2% of the variance). All these relationships werebidirectional, as shown by the double-ended arrowsjoining the various depression subtypes. However,although these associations between depression subtypeswere considerable, they were all well short of 100% ofthe variance, with even the strongest such relationship

Table 3. Beta (standardised) coefficients and regression outcomes for six EPCLQ components against each of the five depressive subtypes

EPCLQ component Melancholic Depressed mood Anhedonic Somatic Cognitive

1. Adverse emotions/social withdrawal 0.482* 0.554* 0.327* 0.438* 0.193*2. Reduced recreation/exercise 0.033 0.030 0.002 0.046 0.0003. Lack of improved functioning 0.017 0.046 0.015 0.212* 0.0034. Physiological symptoms 0.010 0.040 0.003 0.025 0.0085. Employment problems 0.112* 0.050 0.163* 0.047 0.0786. Loss of cognitive ability 0.100* 0.027 0.104* 0.091 0.313*R square 0.329 0.369 0.196 0.416 0.214F 29.790 35.448 14.778 43.199 16.565P <0.001 <0.001 <0.001 <0.001 <0.001

*P < 0.05.EPCLQ, Effects of Prostate Cancer on Lifestyle Questionnaire.

Cogni ve Depressedmood

Soma c Anhedonia

Melancholic

0.596

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Depressed

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0.289

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0.112

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Depressed

Figure 1. Five depression subtypes, interrelationships, and contributing EPCLQ items.

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leaving nearly a third of the variance unaccounted for, andthe weakest relationship leaving nearly 85% of the vari-ance accounted for. Thus, although the five depressionsubtypes measured here shared some degree of common-ality, each depression subtype was relatively independentof the others, to a greater or lesser degree according tosubtype, and therefore further justifying considerationof these five subtypes of depression when assessing PCapatients’ mood status.

Also shown in Figure 1 are the various EPCLQ items(in italics) that had statistically significant β values (alsoin italics) for each of the five depression subtypes. Somecommonalities are apparent in these data. First, ‘Feelingnauseous’ and ‘Feeling depressed’ were significant contrib-uting stressors for all of the depression subtypes exceptCognitive depression. Second, ‘Withdrawing from others’significantly contributed to Melancholic depression,Depressed mood and Anhedonic depression. Third,‘Feeling tired’ was a significant stressor for Depressedmood and Somatic depression. When these EPCLQ itemswere taken out of Figure 1, only four stressors remained:‘Feeling sadder’ (which contributed only to Depressedmood), ‘Being less tolerant of others’ (which contributedonly to Somatic depression) and the two unique EPCLQitems that contributed only to Cognitive depression(‘Decreased memory ability’ and ‘Becoming “fuzzy” aboutthings’).

A caution should be noted regarding the presence ofsome stressors that were also symptoms of depression.For example, ‘Feeling depressed’ and ‘Feeling sadder’ wereidentified EPCLQ stressors but also are a component ofdepression, tapped by SDS item ‘I feel downhearted andblue’. Similarly, ‘Tired’ (EPCLQ) is probably also tappingthe same state as the SDS item which was deleted becauseof its potential to overlap with the purely physiologicalmanifestations of PCa. Taken as a linear causal process,the development of depression might include such self-reports of patient emotional/behavioural states that func-tion both as stressors which contribute to depression aswell as symptoms of depression itself. That is, depressivesymptomatology most likely develops over time ratherthan all symptoms occurring simultaneously, and somestressors may incite certain depression symptoms whileremaining to become symptoms of depression themselves.This is particularly likely in the case of the EPCLQ items‘Feeling depressed’/‘Feeling sadder’ and the SDS item ‘Ifeel downhearted and blue’. The underlying sadness ordepression might conceivably act as a (1) stressor whichelicited further depression symptoms and also (2) remainas a symptom of depression as it is defined by APA criteria(APA 2000).

DISCUSSION

Several major findings emerged from this study. First,each of the five depression subtypes selected for investi-gation was observable in a typical sample of PCa patients,thus justifying their investigation. In clinical terms, thesefindings argue for a more comprehensive and detailedassessment of depression than is usually undertaken whenusing standardised clinical interviews of rating scales,which produce a single score or classification. Second,despite some correlations between the subtypes, a greatdeal of the variance in those relationships was unac-counted for, suggesting that each depression subtypeshould be considered independently, at least in the firstconsideration of the clinical implications of an assess-ment for depression. Because these depression subtypes,as defined earlier in this paper and in the wider literature,reflect different psychological and physiological patholo-gies, they should be considered as identifiable aspects of adepression ‘mosaic’ which supplants unitary or dichoto-mous definitions of what is, in effect, a relatively largegroup of diagnostic criteria. Third, the fact that almosthalf of the sample had scores in the ‘clinically significant’range for at least one of the particular depression subtypesfurther argues for the consideration of those subtypeswhen assessing depression in PCa patients. When consid-ered with the fact that nearly 12% of the sample alsopresented with clinically significant scores for three ofthe subtypes of depression, it could be argued that manyPCa patients present with a combination of sufficientlydifferent subtypes of depression to seriously challengetreatment manual approaches which assume a unitaryconstruct of depression.

The fourth point to be made from these data is that theyextend the previous finding that PCa patients are alsomore likely to present with anhedonia than their same-agebut PCa-free peers (Sharpley et al. 2012) by showing thatsocial withdrawal was a major predictor of four of the fivesubtypes of depression (except Cognitive depression). Thisfinding has implications for treatment choices as dis-cussed in the Introduction to this paper, such as thefact that anhedonic patients have a relative inability toform the kind of close personal relationships needed fortherapist–patient ‘bond’ within traditional verbal psycho-therapy or to undertake the commonly-used ‘homework’tasks set by behavioural psychotherapy approaches.The fifth point refers to the need to distinguish patientswho present with Cognitive depression from others, sincethese patients are most likely to have started feelingdepressed because of their loss of cognitive function.While this may be a function of old age (and therefore not

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directly related to PCa), it may also be an outcome ofanti-androgen hormone treatments that are commonlyused with these patients. Thus, therapy approaches mightinclude informing patients that the cognitive deficits theyare experiences may pass with the end of their hormonetreatment, and/or exercises to boost cognitive abilities.The final point to be made can act to summarise thosepreviously made by suggesting that diagnosis of depres-sion among PCa patients, and the development of treat-ment plans to address this problem, may be more likelyto benefit from an individualised ‘ideographic’ approachrather than a ‘one-size-fits-all’ nomothetic approach todepression. This perspective reflects that taken by severalauthors who have argued for a focus upon the individualcharacteristics of patients so as to develop truly ‘person-alized treatments’, which is one of the most importantchallenges for mental health researchers in the nextdecades (Cuijpers et al. 2012).

Therefore, it may be concluded that the assessmentof depression in PCa patients might be more effectiveif these five subtypes of depression are calculated fromthe overall symptomatology of the men in this popula-tion rather than simply applying a unitary ‘depression’assessment based on the total score of whichever test orscale is used to assess patients’ depression. Collection ofdepression subtype data can also inform treatmentchoices for therapists working with PCa patients whopresent with depression. Some of these depression sub-types may be more amenable to medication than psy-chotherapy approaches, and the accurate allocation ofPCa patients to the most appropriate treatment typefor their depression subtype profile may help to alleviatepatient distress more efficiently. At the very least,depression subtype scores can assist therapists andtheir patients to target specific depression symptoms fortreatment.

Limitations of this study include generalisation to othergeographic and cultural populations, the collection ofdepression symptomatology via self-report (although this

is the most common method for doing this in studies ofPCa depression), and the fact that data were gathered froma cross-section ‘snapshot’ survey which does not permitanalysis of changes in patients’ depression subtypes overtime following diagnosis and treatment. Some overlap inSDS items across a number of the depression subtypesis unavoidable, but each subtype was unique in terms ofits symptomatology, and therefore this overlap does notinvalidate consideration of each of these five depressionsubtypes in the clinical assessment of PCa patients.Further investigation is required to confirm the findingsreported in Figure 1, and those data will further elucidatethe relationships between specific PCa-related stressorsand the various subtypes of depression investigatedhere.

In conclusion, these data provide an initial insight intothe ways in which PCa patients may experience depres-sion according to its symptomatologies, how the varioussubtypes of depression examined here relate to each other,what are the most powerful stressors that are associatedwith them, and how treatment options might more effec-tively focus upon the nature of (and stressors for) theparticular type of depression that a PCa patient may beexperiencing. These findings therefore inform and supporta more individualised approach to understanding andtreating PCa depression, and suggest that treatmentchoice may benefit from being more informed about theprofile of depression subtype that each patient presentsrather than simply the severity of the score obtained fromclinical interview or standardised scales.

ACKNOWLEDGEMENT

The authors acknowledge the contribution made bythe Collaborative Research Network on Mental Healthand Well-being in Rural Communities, supported by theDepartment of Industry, Innovation, Science, Researchand Tertiary Education, Commonwealth Government ofAustralia.

REFERENCES

Anastasi A. (1982) Psychological Testing,5th edn. Collier Macmillan, New York,NY, USA.

Antonijevic I. (2006) Depressive disorders –is it time to endorse different pathophy-siologies? Psychoneuroendocrinology 31,1–15.

APA (2000) Diagnostic and StatisticalManual of Mental Disorders, 4th edn,

Text Revision. American PsychiatricAssociation, Washington, DC, USA.

Beck A., Rush A., Shaw B. & Emery G.(1979) Cognitive Theory of Depression.Guilford, New York, NY, USA.

Bennet G. & Badger T.A. (2005) Depressionin men with prostate cancer. OncologyNursing Forum 32, 545–556.

Bisson J.I., Chubb H.L., Bennett S.,Mason M., Jones D. & Kynaston H.(2002) The prevalence and predictors of

psychological distress in patients withearly localized prostate cancer. BritishJournal of Urology International 90,56–61.

Chan C.-M. & Tsoi M. (1984) The BDIand stimulus determinants of cognitive-related depression among Chinesecollege students. Cognitive Therapy andResearch 8, 501–507.

Christie K.M., Meyerowitz B.E.,Giedzinska-Simons A., Gross M. &

SHARPLEY ET AL.

© 2013 John Wiley & Sons Ltd822

Agus D.B. (2009) Predictors of affectfollowing treatment decision-makingfor prostate cancer: conversations, cogni-tive processing, and coping. Psycho-Oncology 18, 508–514.

Clark L. & Watson D. (1991) Tripartitemodel of anxiety and depression: psycho-metric evidence and taxonomic implica-tions. Journal of Abnormal Psychology100, 316–335.

Cuijpers P., Reynolds C., Donker T., Li J.Z.,Andersson G. & Beekman A.T.F. (2012)Personalized treatment of adult depres-sion: medication, psychotherapy, orboth? A systematic review. Depressionand Anxiety 29, 855–864.

Dearnaley D., Khoo V., Norman A., MeyerL., Nahum A., Tait D., Yarnold J. &Horwich A. (1999) Comparison of radia-tion side-effects of conformal and con-ventional radiotherapy in prostatecancer: a randomised trial. The Lancet353, 267–272.

Dejonge J. & Baneke J. (1989) The ZungSelf-rating Depression Scale: a replica-tion study on reliability, validity andprediction. Psychological Reports 64,833–834.

Feinberg M. (1992) Subtypes of depressionand response to treatment. Journal ofConsulting and Clinical Psychology 60,670–674.

Gabrys J. & Peters K. (1985) Reliability, dis-criminant and predictive validity of theZung Self-Rating Depression Scale. Psy-chological Reports 57, 1091–1096.

Hersch J., Juraskova I., Price M. & MullanB. (2009) Psychosocial interventions andquality of life in gynaecological patients:a systematic review. Psycho-Oncology18, 795–810.

Jayadevappa R., Malkowicz S., Chhatre S.,Johnson J. & Gallo J. (2011) The burdenof depression in prostate cancer. Psycho-Oncology 21, 1338–1345.

Judd L., Rapaport M., Paulus M. & Brown J.(1994) Subsyndromal symptomaticdepression: a new mood disorder? Journalof Clinical Psychiatry 55, 18–28.

Judd L., Paulus M., Wells K. & RapaportM. (1996) Socioeconomic burden ofsubsyndromal depressive symptoms andmajor depression in a sample of thegeneral population. American Journal ofPsychiatry 163, 1411–1417.

Kessing L. (2007) Epidemiology of subtypesof depression. Acta Psychiatrica Scandi-navia 115, 85–89.

Leckman J., Weissman M., Prusoff B.,Caruso K., Merikangas K., Pauls D. &

Kidd K. (1984) Subtypes of depression.Archives of General Psychiatry 41, 833–838.

Leventhal A.M. & Rehm L.P. (2005) Theempirical status of melancholia: implica-tions for psychology. Clinical PsychologyReview 25, 25–44.

Lintz K., Moynihan C., Steginga S.,Norman A., Eeles R., Huddart R.,Dearnaley D. & Watson M. (2003) Pros-tate cancer patients’ support and psy-chological care needs: survey from anon-surgical oncology clinic. Psycho-Oncology 12, 769–783.

Marcos T. & Salamero M. (1990) Factorstudy of the Hamilton Ratings Scale forDepression and the Beck MelancholicScale. Acta Psychiatrica Scandinica 82,178–181.

Mishel M.H., Belyea M., Germino B.,Stewart J., Bailey D., Jr, Robertson C. &Mohler J. (2002) Helping patients withlocalized prostate carcinoma manageuncertainty and treatment side effects:nurse-delivered psychoeducational inter-vention over the telephone. Cancer 94,1854–1866.

Murck H. (2003) Atypical depression spec-trum disorder – neurobiology and treat-ment. Acta Neuropsychiatrica 15, 227–241.

Parker G., Roy K., Mitchell P., WilhelmK., Malhi G. & Hadzi-Pavlovic D.(2002) Atypical depression: a reappraisal.American Journal of Psychiatry 159,1470–1479.

Peeters C., Stewart A., Segal R., WouterlootE., Scott C.G. & Aubry T. (2009) Evalua-tion of a cancer exercise program: patientand physical benefits. Psycho-Oncology18, 898–902.

Pelle A., Pedersen S., Erdman R., KazemierM., Spiering M., Van Domburg R. &Denollet J. (2010) Anhedonia is associ-ated with poor health status and moresomatic and cognitive symptoms inpatients with coronary artery disease.Quality of Life Research 20, 643–651.

Prince M., Patel V., Saxena S., Maj M.,Maselko J., Phillips M. & Rahman A.(2007) No health without mental health.The Lancet 370, 859–977.

Raison C. & Miller A. (2003) Depressionin cancer: new developments regardingdiagnosis and treatment. Biological Psy-chiatry 54, 283–294.

Rapaport M.H., Judd L.L., Schettler P.J.,Yonkers K.A., Thase M.E., Kupfer D.J.,Frank E., Plewes J.M., Tollefson G.D. &Rush A.J. (2002) A descriptive analysis of

minor depression. American Journal ofPsychiatry 159, 637–643.

Schaefer A., Brown J., Watson C., Plenel D.,Demotts J., Howard M., Petrik N. &Ballweg B. (1985) Comparison of thevalidities of the Beck, Zung and MMPIdepression scales. Journal of Consult-ing and Clinical Psychology 53, 415–418.

Sharpley C. & Christie D. (2007) An analy-sis of the psychometric structure andfrequency of anxiety and depression inAustralian men with prostate cancer.Psycho-Oncology 16, 660–667.

Sharpley C., Bitsika V. & Christie D.(2009) Understanding the causes ofdepression among prostate cancerpatients: development of the Effects ofProstate Cancer on Lifestyle Question-naire. Psycho-Oncology 18, 162–168.

Sharpley C., Bitsika V. & Christie D. (2010)‘Why I feel bad’: refinement of the Effectsof Prostate Cancer upon Lifestyle Ques-tionnaire and an initial exploration ofits links with anxiety and depressionamong prostate cancer patients. Psycho-Oncology 19, 839–846.

Sharpley C., Bitsika V. & Christie D. (2012)Do prostate cancer patients suffer morefrom depressed mood or anhedonia?Psycho-Oncology. Article publishedonline 27 September 2012. doi: 10.1002/pon.3203.

Silverstein B. (2002) Gender differencesin the prevalence of somatic versuspure depression: a replication. AmericanJournal of Psychiatry 159, 1051–1052.

Singh T. & Williams K. (2006) Atypicaldepression. Psychiatry 3, 33–39.

Stege R. (2000) Potential side-effects ofendocrine treatment of long durationin prostate cancer. The Prostate 10,38–42.

Thomas B., Thomas I., Nandamohan V.,Nair M. & Pandey M. (2009) Screening fordistress can predict loss of follow-up andtreatment in cancer patients: results ofdevelopment and validation of the Dis-tress Inventory for Cancer Version 2.Psycho-Oncology 18, 524–533.

Yang T. & Dunner D. (2001) Differentialsubtyping of depression. Depression andAnxiety 13, 11–17.

Zung W. (1965) A self-rating depressionscale. Archives of General Psychiatry 12,63–70.

Zung W. (1973) From art to science: thediagnosis and treatment of depression.Archives of General Psychiatry 29,328–337.

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