There is a general consensus that it is important to recognise and treat depression during the course of cancer, especially in palliative stages where particular emphasis is on quality of life (Stiefel et al, 2001; Noorani and Montagnini, 2007). Distress, anxiety and depression powerfully influence quality of life as well as satisfaction with care and participation in medical treatment (Skarstein et al, 2000; Stark et al, 2002; Kennard et al, 2004; Bui et al, 2005). Studies that have used structured psychiatric interviews suggest that the median prevalence of major depressive disorder is 15% in advanced cancer (Hotopf et al, 2002). Four large-scale studies using severity scales suggest that the overall prevalence of distress in unselected cancer patients is above 30% (Pascoe et al, 2000; Fallowfield et al, 2001; Zabora et al, 2001; Carlson et al, 2004). Yet, it is well known that syndromal anxiety and depression are often overlooked by busy cancer professionals in palliative and non-palliative settings (Ford et al, 1994; Fallowfield et al, 2001; Sollner et al, 2001; Stiefel et al, 2001; Durkin et al, 2003; Sharpe et al, 2004) and the majority of patients will not gain access to mental health services (Kadan-Lottick et al, 2005). In part, this is because cancer specialists have difficulty in identifying emotional complications and tend to have communication behaviours that systematically focus on physical rather than psychological concerns (Durkin et al, 2003).

More than 50 questionnaires have been developed to aid the detection of depression or severe distress, but most have been validated in primary care rather than cancer settings (Lloyd-Williams et al, 2003b). Perhaps, best known of all depression scales is the Patient Health Questionnaire (in either nine or two item forms) (Spitzer et al, 1999). This scale has some merit in primary care and appears highly acceptable (Mitchell and Coyne, 2007) but has yet to be rigorously tested in cancer settings. Indeed, only a handful of tools have been studied specifically in palliative care (Le Fevre et al, 1999; Holtom and Barraclough, 2000; Lloyd-Williams et al, 2001, 2004; Love et al, 2004; Thekkumpurath et al, 2007). Their main limitation, however, is that they are often too long for routine use (Mitchell et al, 2008). In response to this problem, short versions of many common depression scales have been developed. These include 7 and 6 item versions of the Hamilton Depression Rating Scale (HAMD) (McIntyre et al, 2005; Guo et al, 2006; Serrano-Duen and Soledad, 2008); 13, 7 and 2 item versions of the Beck Depression Inventory (BDI) (Steer et al, 1999; Furlanetto et al, 2005; Huffman et al 2006); 13, 10 and 6 item versions of the Center for Epidemiologic Studies Depression Scale (CES-D) (Burnam et al, 1988; Cole et al, 2004; Covic et al, 2007); 5, 4 and 2 item versions of the Geriatric Depression Scale (GDS) (Andresen et al, 1994; van Marwijk et al, 1995; Hoyl et al, 1999); and 8, 6 and 5 item versions of the Edinburgh Depression scale (EPDS) (Pallant et al, 2006; Eberhard-Gran et al, 2007; Lloyd-Williams et al, 2007). Occasionally, authors have developed entirely new short scales, such as the four item case-find for depression (Jefford et al, 2004), or attempted to develop a short scale specifically for palliative settings (Lloyd-Williams et al, 2007).

In the 1990s, several groups working in cancer settings suggested that two questions, or in some cases just a single question, might be sufficient to detect depression in palliative care. Usually, these ultra-short tests formed part of symptom checklists and were not validated against an accepted standard (Miller and Walsh, 1991; Donnelly et al, 1995; Conill et al, 1997; Brunelli et al, 1998; Edmonds et al, 1998; Ng and von Gunten, 1998; Pratheepawanit et al, 1999). At the same time, simple (non-verbal) visual-analogue methods of assessing depression, anxiety or distress were developed, exemplified by the NCCN Distress Thermometer and Edmonton Symptom Assessment (Hürny et al, 1996; Vignaroli et al, 2006). The accuracy of these methods was reviewed in mixed cancer settings with the finding that they had reasonable rule-out accuracy but limited case-finding ability (Mitchell, 2007). Yet, it is not clear how simple verbal questions perform alone and when used specifically for patients with advanced cancer.

The aim of this study is to examine the diagnostic accuracy of simple verbal questions to detect depression in cancer and palliative care and to ascertain whether clinicians should rely upon either one question or two questions to detect major depression compared with more established screening tools.

Materials and methods


A systematic literature search, critical appraisal of the collected studies and pooled analysis were conducted. The following abstract databases were searched: Medline 1966-January 2008, PsycINFO 1887-January 2008, Embase 1980-January 2008 and CINAHL 1982-January 2008. In these databases, the keywords (MeSH terms) were ‘distress or anxi$ or depress$ or mood’ and ‘screen$ or detect$ or case-finding or recogni$ or diagnos$ or recogni$’ and ‘cancer or oncology or malignant or transplant or tumour or metastatic.’ Four full text collections including Science Direct, Ingenta Select, Ovid Full text and Wiley Interscience were searched. In these online databases, the same search terms were used but as a full text search and citation search. The abstract database Web of Knowledge (4.0, ISI) was searched, using the above terms as a text word search, and using key papers in a reverse citation search. Conference abstracts from IPOS 2006 and 2007 were examined. Non-English language papers and abstracts were included but, where necessary, authors were contacted directly for primary data and data in press.

Critical appraisal

The review guidelines for diagnostic tests recently outlined in Evidence Based Medicine were followed (Pai et al, 2004). Questions for each report included the setting, the data integrity, the choice of reference criterion, the method of application of the screening questionnaire and, importantly, the type of outcome measured. Quality appraisal standards are listed in Table 1.

Table 1 Methodological aspects of simple verbal questions for depression in cancer

Pooled analysis and meta-analysis

Two methods are possible in combining diagnostic validity studies (Midgette et al, 1993; Irwig et al, 1995). (a) Simple pooling of the raw data and re-calculation of the cumulative sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV). This method assumes a consistent prevalence between studies and in future work. (b) Correction for the variance in prevalence by relying on the stability of sensitivity and specificity by calculating a pooled weighted rate of sensitivity and specificity and then calculating PPV and NPV according to local prevalence data (Glasziou and Irwig, 1998). In this case, a Bayesian curve can be constructed of all post-test probabilities if a given test is positive or negative. Overall accuracy was calculated using the identificiation index which is the fraction correct minus faction incorrect. The reciprocal of the identification index is the number needed to screen (Mitchell, 2009).

Standards of accuracy

Performance was taken as follows: <0.2 poor, >0.20.4 fair, >0.40.6 moderate, >0.60.8 good and >0.81 very good; adapted from that originally proposed by Landis and Koch (Landis and Koch, 1977).

Outcome measures

The majority of studies defined depression using a psychiatric interview (applied in a semistructured or clinical interview) but a minority utilised standardised rating scales (Murphy, 2002).


Systematic literature search

The search identified 98 analyses specifically examining ultra-short methods (Figure 1). Studies that examined one or two question methods in non-cancer medical patients or in primary care were excluded. A total of 39 studies had no gold standard and 29 examined visual-analogue methods and were therefore excluded. Thirteen studies were not sufficiently detailed for inclusion. Thus, 17 analyses of verbal/written questions to detect depression in cancer were included. No attempt was made to separate questions read by investigators (verbal) from questions read by the patients (written). The data extraction is illustrated in Figure 1 in accordance with Quality of Reporting of Meta-analyses guidelines (Moher et al, 1999).

Figure 1
figure 1

Quorom diagram of studies.

Of 17 analyses, 9 examined one single depression question: Chochinov et al (1997); Lloyd-Williams et al (2003a); Meyer et al (2003a); Jefford et al (2004); Akechi et al (2006); Kawase et al (2006); Ohno et al (2006); Payne et al (2007); and Mitchell et al (2008). Three analyses examined one single interest item: Akechi et al (2006); Payne et al (2007); and Mitchell et al (2008). Five analyses examined a combination of two questions: Akechi et al (2006); 65 Payne et al (2007); Chochinov et al (1997); Gessler et al (2007); and Mitchell et al (2008).

Critical appraisal

The mean sample size was 165.8 (s.d. 55.7). However, several studies examined different verbal methods in the same sample and thus there were actually 1579 unique patients under study. Eleven studies took place in palliative settings and/or specifically in those with late-stage cancer. Three took place in mixed stages and three in predominantly early cancers. All but two studies used DSM criteria by clinical interview or by structured clinical interview. Four looked at major or minor depression combined and the remainder looked at major depression alone.

The most common question for depression was simply ‘Are you depressed?’ but variations included ‘Describe your mood over the last week’ and the PHQ2 question two ‘Over the last 2 weeks, how often have you been bothered by feeling down, depressed or hopeless?’ The loss of interest question was asked in three different ways, namely ‘Have you lost interest?’, ‘Have you experienced loss of interest in things or activities that you would normally enjoy?’ and the PHQ2 question one ‘Over the last 2 weeks, how often have you been bothered by little interest or pleasure in doing things?’ The two-question approach was always asked as question 1 (Q1) or question 2 (Q2), which favours sensitivity at the expense of specificity compared to the Q1 and Q2 approach (Coyne and Mitchell, 2007). Further details of the studies are shown in Tables 1 and 2.

Table 2 Statistical summary of simple verbal questions for depression in cancer

Pooled analysis and meta-analysis

Single depression/mood question

Across nine studies, the prevalence of depression was 16%. Using the simple pooled method, the single depression question enabled the detection of depression in 160 out of 223 true cases, a sensitivity of 72% (95% CI 66.3–76.8%) and correctly reassured 964 out of 1166 non-depressed cancer sufferers, a specificity of 83% (95% CI 81.6–83.6). Thus, the PPV was 44% and the NPV was 94%. The Youden score was 0.544 (95% CI 47.9–60.3). Using the meta-analytic approach, the weighted sensitivity was 74.1% (95% CI=0.68–0.80) and the specificity was 85.8% (95% CI 83.7–87.7).

Analysing the results by natural frequencies, out of every 100 screening applications, the single depression question would correctly rule out 69 non-depressed, rule in 11 out of 18 cases, missing 5 and also giving 15 false-positive diagnoses (Figure 2). Thus, the identification index (net gain) would be 61.8% and the number needed to screen in order to yield one additional correct identification would be 1.62.

Figure 2
figure 2

Natural screening accuracy of simple verbal questions in the detection of cancer-related depression.

Single interest question

There were only three studies examining the ‘loss-of-interest’ question, with a pooled prevalence of 14%. Using the simple pooled method, this question allowed the detection of 60 out of 72 cases (sensitivity 83%) (95% CI 74.2–89.9) and excluded 394 from 459 non-depressed cases (specificity of 86%) (95% CI 84.4–89.9). The PPV was 48% and the NPV 97%. The Youden score was 0.692 (95% CI 0.586–0.768). Using the meta-analytic approach, the weighted sensitivity was 82.4% (95% CI=73.0–90.0) and the specificity was 86.4 (95% CI=83.0–89.3).

Analysing the results by natural frequencies, out of every 100 screening applications, the single loss of interest question would correctly rule out 74 non-depressed, rule in 11 out of 14 cases, missing 2 and also giving 12 false-positive diagnoses (Figure 2). Thus, the identification index (net gain) would be 71% and the number needed to screen in order to yield one additional correct identification would be 1.41.

Two questions (low mood and low interest)

In five studies using a two-question combination (Q1 or Q2), the prevalence of depression was 17%. Using the simple pooled method, the two-question combination facilitated a diagnosis of depression in 138 of 151 true cases (sensitivity 91.4%) (95% CI 86.4–94.8) and gave correct reassurance to 645 of 749 non-cases (specificity 86%) (95% CI 85.1–86.8). The PPV was 57% and the NPV 98%. The Youden score was 0.775 (95% CI 0.771–0.816), significantly higher than either of the single questions used alone. Using the meta-analytic approach, the weighted sensitivity was 92.7% (95% CI=88.1–96.3) and specificity 87.4% (95% CI=84.9–89.7).

Analysing the results by natural frequencies, out of every 100 screening applications, these two questions would correctly rule out 72 non-depressed, rule in 15 out of 18 cases, overlooking 1 true case and also giving 12 false-positive diagnoses (Figure 2). Thus, the identification index (net gain) would be 74% and the number needed to screen in order to yield one additional correct identification would be 1.35.

Bayesian pre-test–post-test gain

Assuming sensitivity and specificity hold for different rates of depression, a Bayesian curve was constructed of all post-test probabilities where a test result was either positive or negative. This illustrates the pre-test–post-test gain for each method and the predictive value conditional upon different baseline rates of depression. Figure 3 demonstrated the superior difference in gain for the two-question approach with the depression question alone.

Figure 3
figure 3

Bayesian graph: test probability (PPV and NPV) as function of test result – depression question vs combination question.


A previous pooled analysis found eight diagnostic validity analyses of one or two single item questions in the detection of depression in cancer settings (Mitchell, 2007). This study updates the previous analysis to include 17 analyses, 13 involving late-stage cancer and/or palliative settings. It is important to note that the average prevalence of depression across these studies was 16% (range 7–38%), which means that any case-finding method is likely to have difficulty detecting true cases without generating false positives. Results show that the loss of interest question is somewhat better than the depression question when used alone. This corresponds to research showing that, of many symptoms of depression, loss of interest best discriminated between patients with and without diagnosis of comorbid affective disorder (Reuter et al, 2004). However, two questions are significantly better than any one question for detecting depression (Youden score was 0.78 for two questions, 0.54 for the depression question and 0.69 for the interest question). In fact, two questions are better for both ruling in and ruling out a diagnosis than either question alone, although the loss of interest question is also an excellent method of excluding depression. No method achieved a case-finding accuracy of more than 60% according to the PPVs. This means that at best there would be 43 false positives out of each 100 positive screens.

There has been increasing interest in short verbal and non-verbal screening methods. Lloyd-Williams and colleagues (Lawrie et al, 2004) found that among consultants working in palliative medicine, 10% asked the patient ‘are you depressed’ to detect depression. Mitchell et al (2008) and colleagues found that simple verbal questions were the most preferred active method of detecting depression, used by 30% of cancer professionals. However, this meta-analysis raises an important caution for all those using one or two questions. Assuming use of the two-question combination, this would mean that out of every 100 screening applications answering yes to either of these two questions, only 1 true case would be missed but 12 false-positive diagnoses would be generated (Figure 2). Thus, a second method with better PPV would be required. This could be a thorough clinical assessment by someone confidently able to diagnose depression or it could be a longer validated depression severity scale (Robinson and Crawford, 2005). However, there is no agreement on which is the optimal case-finding method and rarely has any method shown a case-finding (PPV) accuracy that exceeds 0.80. (Lloyd-Williams et al, 2003b; Trask, 2004). There is also no agreement on how often a tool should be applied (Lloyd-Williams and Riddleston, 2002). For example, Love et al (2004) found that the HADS depression subscale had a PPV of 0.79 when a cut-off of 7v8 was used. Using the same cut-off, Le Fevre et al (1999) found a PPV of 0.42 in a palliative settings. Recently, Lloyd-Williams et al (2007) showed that a six-item adaptation of the EPDS had a PPV of 0.65, also in a palliative setting.

In conclusion, no method has been shown to be sufficiently accurate to be considered the definitive screening or case-finding tool for cancer-related depression. Simple questions should be considered as a method of exclusion or combined with more detailed tests. Future work should move beyond screening for psychopathology alone to also consider unmet needs. That is, those individuals with emotional disorders (distress, anxiety, depression and anger) who require and desire professional help (Graves et al, 2007).