Annals of Oncology 24: 895–900, 2013
Published online 21 November 2012
Prevalence of depression in adults with cancer: a
J. Walker1*, C. Holm Hansen2, P. Martin2, A. Sawhney2, P. Thekkumpurath2, C. Beale2,
S. Symeonides3, L. Wall3, G. Murray4& M. Sharpe1
1Psychological Medicine Research Department of Psychiatry, University of Oxford, Oxford;2Psychological Medicine Research, Edinburgh Cancer Research Centre,
University of Edinburgh;3Edinburgh Cancer Centre, Western General Hospital;4Centre for Population Health Sciences, University of Edinburgh, Edinburgh, UK
Received 31 October 2011; revised 27 April 2012 & 11 September 2012; accepted 28 September 2012
Background: Depression has substantial effects on cancer patients’ quality of life. Estimates of its prevalence vary
widely. We aimed to systematically review published studies to obtain the best estimate of the prevalence of depression
in clinically meaningful subgroups of cancer patients.
Design: Systematic review that addressed the limitations of previous reviews by (i) including only studies that used
diagnostic interviews; (ii) including only studies that met basic quality criteria (random or consecutive sampling, ≥70%
response rate, clear definition of depression caseness, sample size ≥100); (iii) grouping studies into clinically meaningful
subgroups; (iv) describing the effect on prevalence estimates of different methods of diagnosing depression.
Results: Of 66 relevant studies, only 15 (23%) met quality criteria. The estimated prevalence of depression in the
defined subgroups was as follows: 5% to 16% in outpatients, 4% to 14% in inpatients, 4% to 11% in mixed outpatient
and inpatient samples and 7% to 49% in palliative care. Studies which used expert interviewers (psychiatrists or clinical
psychologists) reported lower prevalence estimates.
Conclusions: Of the large number of relevant studies, few met our inclusion criteria, and prevalence estimates are
consequently imprecise. We propose that future studies should be designed to meet basic quality criteria and employ
Key words: cancer, depression, prevalence, review, systematic
Depression is a major public health problem and has an
especially large effect on health when comorbid with a chronic
medical condition [1, 2]. Clinicians working in cancer services
have recognised that depression is often undiagnosed and
untreated and that these shortcomings in care can have
substantial effects, not only on patients’ quality of life but also
on their acceptance of cancer treatments [3–5]. Important
advances have been made: screening systems can help to
identify depressed patients; oncologists have better ways to
discuss psychological problems with their patients through
advanced communication skills training and there are also new
evidence-based interventions designed specifically for
depressed patients attending cancer services [4, 6–9]. However,
in order to plan the implementation of these advances,
oncology teams need to know how many of their patients are
likely to have depression.
At first glance, this information appears easy to come by.
The briefest of electronic searches reveals that there are
hundreds of articles that might be relevant, reflecting the
importance of and interest in the topic. A number of reviews,
including systematic reviews and meta-analyses have also been
published [10–22]. However, a closer inspection of these
reviews reveals that, despite the wealth of research publications
summarised, the prevalence of depression in clinically
meaningful subgroups of people with cancer remains unclear
with widely varying estimates that are difficult to apply
clinically. This is because the published reviews have been
limited by one or more of the following problems. The first
problem is the inclusion of studies that have not used
diagnostic interviews to assess whether participants were
depressed. The most commonly used diagnostic criteria in
psychiatry are those of the Diagnostic and Statistical Manual of
Mental Disorders (DSM) and the International Classification
of Diseases (ICD) [23, 24]. These diagnostic criteria describe
the nature, severity and duration of symptoms required to
make an interview-based diagnosis of depression. Although
rating scales can be used to identify patients who require
*Correspondence to: Dr J. Walker, Psychological Medicine Research, University of
Oxford Department of Psychiatry, Warneford Hospital, Oxford, OX3 7JX, UK. Tel: +44-
1865-226477; Fax: +44-1865-793101; E-mail: firstname.lastname@example.org
Annals of Oncology
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by guest on September 13, 2015
further assessment (e.g. as a first stage in screening), or to
monitor the course of diagnosed depression, they cannot be
used to diagnose depression. The second problem is the
inclusion of studies of varying methodological quality. Lack of
attention to study quality is a common problem in reviews of
observational studies and is important because the results of
low-quality studies are likely to be biased and therefore to
provide misleading estimates . The third problem concerns
the pooling of data from heterogeneous samples into one
overall estimate of depression prevalence for all cancer patients.
This strategy makes the questionable assumptions that the
prevalence is the same in different patient subgroups and that a
pooled estimate is clinically meaningful. The final problem is a
failure to consider the effect of different methods of diagnosing
depression on prevalence estimates. Diagnostic criteria can be
applied using different interview schedules administered by
people with a range of expertise. In addition, the most
commonly used diagnostic criteria include a number of
physical symptoms which may also arise from having cancer or
cancer treatments. Researchers may decide to apply these
criteria without any assessment of the cause of patients’
physical symptoms (the ‘inclusive approach’), to exclude
symptoms they judge to be cancer-related or to use alternative
criteria without physical symptoms.
Although previous reviews have tried to address one or more
of these problems, none has addressed all of them. We,
therefore, aimed to answer the question, ‘How common is
depression in people with cancer?’ by conducting a systematic
review of relevant published studies in a way that addressed all
the aforementioned problems by (i) including only studies that
used diagnostic interviews to determine depression caseness;
(ii) including only studies that met basic quality criteria;
(iii) grouping studies into clinically meaningful subgroups of
people with cancer; (iv) describing the effect on prevalence
estimates of different methods of diagnosing depression.
We identified relevant published research articles by a systematic search of
the following electronic databases conducted in January 2012: Medline
(1950 to 2012), PsycINFO (1806 to 2012), EMBASE Classic+EMBASE
(1947 to 2012), Web of Science and BIOSIS. Searches were run for the
combination of ‘prevalence’, ‘cancer’ and ‘depression’, using both
standardised subject terms and free text terms, including synonyms and
alternative spellings. Full details of the searches used are given in the
supplementary appendix, available at Annals of Oncology online. We also
manually searched the reference lists of all the study reports selected for
inclusion in the review and of review articles obtained through the
We judged studies to be relevant if they met all the following criteria:
(i) the study clearly aimed to estimate the prevalence of depression
(i.e. studies that were designed to address a different research question but
happened to include a prevalence estimate, such as clinical trials or
questionnaire validation studies, were not included); (ii) all study
participants were adults (aged 18 or older); (iii) all study participants (or a
clearly defined subgroup for which there was an estimate of depression
prevalence) had a definite cancer diagnosis (e.g. histological diagnosis or
attending for cancer treatment); (iv) depression caseness was determined
using diagnostic interviews.
We included only primary studies (i.e. not reviews) for which we could
obtain the full paper for data extraction. We also applied quality criteria to
the study methods. To ensure a consistent and transparent approach to
quality assessment, we developed and used a checklist of specific inclusion
criteria, informed by the work of Loney et al., rather than using a
continuous quality score [26–29]. We included only studies that met all of
the following criteria which we considered to be basic and relatively
undemanding markers of quality: (i) the study sample was obtained using a
random or consecutive sampling method; (ii) data were available for
analysis on at least 70% of the eligible patients (either as reported by the
authors or derived from presented data); (iii) depression caseness was
defined using standard diagnostic criteria, for example major depression
from the DSM or depressive episode from the ICD [23, 24]; (iv) at least
100 study participants were assessed for depression. The first two of these
criteria relate to the minimisation of selection bias, where participants are
not representative of the target population. The third criterion was
included to ensure that estimates could be compared across studies. The
final (sample size) criterion was included because a small sample,
although not in itself an indicator of bias, is prone to result in chance and
inaccurate findings and, when reported individually, can be misleading. An
error rate of ±5% has, therefore, been recommended for prevalence studies
. We included studies of 100 participants or more, thereby striking a
balance between having a reasonable number of studies in our own
review and including studies of reasonable accuracy (100 participants
are required to estimate an expected prevalence of 10% with a <6%
data collection and analysis
We imported all articles identified by the searches into a database and
screened their titles and abstracts to determine whether each might meet
the selection criteria. We reviewed the full text of the article, with the help
of a translator where necessary, if there was any possibility that it might be
relevant. This process was conducted independently by two researchers and
a decision whether to include each study was made by consensus. Two
researchers independently extracted data from all the articles judged
relevant, using a specially designed, standardised data extraction form, and
with the help of a translator for non-English papers. We extracted data on
study setting and design, number and characteristics of participants
included, method of depression diagnosis (including interviewer expertise,
diagnostic criteria used and how these were applied) and reported the
prevalence of depression in the sample. For cohort studies, we reported
depression prevalence at the first time point only. If studies assessed both
current and previous depression, we reported current depression
prevalence. If studies compared the prevalence of depression in patients
with cancer with that in a non-cancer population, we used only the
prevalence in the cancer sample. We assessed the methodological quality of
each study at the same time as data extraction. In order to provide
subgroups that might be meaningful to clinicians, we aimed to group
studies by clinical setting (outpatient, inpatient, palliative care) and
further subdivide these by primary cancer site and disease stage. For each
subgroup, we reported the prevalence of depression found in the
primary studies and considered whether meta-analysis was appropriate for
statistical synthesis of their findings. We also considered whether the data
were adequate to test the hypothesis that depression prevalence is the same
across cancer subgroups. We used a forest plot to display the results of the
primary studies graphically. In order to describe the effect of different
methods of diagnosing depression, we described the diagnostic criteria that
Annals of Oncology
| Walker et al. Volume 24 | No. 4 | April 2013
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were used in each study and how these were applied as well as the interview
schedules employed and the interviewers’ expertise.
Searches and initial screening of titles and abstracts yielded 499
potentially eligible studies, of which 42 required translation.
After reviewing the full articles, 433 were considered not
relevant (the most common reason was that the study was not
designed to estimate depression prevalence or depression was
not diagnosed using an interview), leaving 66 relevant studies.
Of these, 15 (23%) met our quality criteria and were included
[4, 30–43]; 12 of the included studies had a cross-sectional
design and 3 were prospective cohort studies. Sample sizes
ranged from 100 to 3938 (median 129, mean 399). Full details
are shown in the supplementary flowchart, available at Annals
of Oncology online.
quality of studies
During data extraction, we noted that reporting was often
unclear, both for the methods used and results obtained; few of
the publications had adhered to current reporting guidelines
. Of the 15 studies we included, only 2 reported confidence
intervals for their estimate of depression prevalence.
characteristics of study participants
The studies had been carried out in seven different countries
and included samples from a range of settings; the majority
were in specialist cancer or palliative care services. Five studies
focused on a specific primary cancer (e.g. only two included
patients with breast cancer) and the remaining 10 included
patients with various cancer types. Further details are given in
the supplementary tables, available at Annals of Oncology
Thirteen studies used the diagnostic criteria for major
depression from DSM to define caseness, and the other two
used the ICD criteria. Four studies reported that they had
taken an inclusive approach to diagnosis (including all
potential symptoms of depression without attempting to judge
what might have caused them); one noted that the interviewer
had not judged whether patients were impaired by their
symptoms; two had excluded all symptoms that the interviewer
judged to be related to the patient’s cancer or its treatments
and one noted that ‘attention had been paid’ to physical
symptoms. The other seven studies did not specify how they
had applied the diagnostic criteria. One study also reported the
number of participants who met the Endicott diagnostic
criteria for depression in which physical symptoms are
substituted by other criteria .
The most commonly used interview schedule was the
Structured Clinical Interview for DSM-IV (SCID), some form
of which was used by 10 studies to diagnose major depression,
including one study that used a two-stage procedure to identify
depressed participants ; 14 of the 15 studies reported the
interviewers’ professions; 10 studies had employed a
psychiatrist or clinical psychologist to conduct the diagnostic
interviews and the other 4 had used research assistants,
research nurses, oncologists and students. References were
made to interviewer training in a number of the publications,
but there was little description of what the training had
involved or how the interviewers (especially those who were
not mental health professionals) had been deemed competent.
prevalence of depression
Figure 1 shows the prevalence of depression in each study,
together with our calculated confidence intervals, grouped by
clinical setting. We were unable to further subdivide the studies
by primary cancer site and disease stage due to the small
number of studies available. We had considered using meta-
analysis to combine the prevalence estimates within subgroups,
but in the light of the degree of clinical heterogeneity (e.g.
cancer sites and treatment being received) and variety of
methods of diagnosing depression, we considered meta-
analysis to be inappropriate. There were also insufficient data
to test the hypothesis that depression prevalence is equal across
Six studies were of cancer outpatients and reported a current
depression prevalence ranging from 5% to 16%. Two of these
assessed women with breast cancer for major depression and
reported prevalence of 9% and 16%. In the first study, a clinical
psychologist administered the SCID to women with all stages
of disease, whereas in the latter a research nurse used the Mini
Neuropsychiatric Interview to assess women whose cancer was
in remission. One study was of patients 1 month after surgery
for lung cancer and found a depression prevalence of 5% using
the SCID administered by psychiatrists. The other three studies
included patients with various primary cancer sites attending
for outpatient treatment or follow-up: one used trained
researchers to administer the interview, the second used a
psychiatrist and the third used untrained oncologists; they
reported prevalence of 8%, 8% and 12%, respectively.
Three studies used psychiatrists to assess cancer inpatients for
major depression, using the SCID: one study focused on
patients with head and neck cancer and found that 4% of
newly diagnosed patients admitted for initial treatment had
major depression. The other two were of patients with various
cancer types; one reported a current depression prevalence of
14%, while the second reported that 30% of participants had
had major depression at some time in the previous 12 months.
outpatients and inpatients
Three studies included both inpatients and outpatients. One
used a psychiatrist-administered SCID to assess patients with
unresectable lung cancer and reported a prevalence of 5%. The
other two assessed patients with various cancer types; one of
these reported prevalence of 4% for current depression as
assessed by a clinical psychologist or psychiatrist and the other
reported that 11% of participants had major depression as
assessed by a psychiatrist.
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Three studies were of patients with various cancer types who
had been referred for palliative care: one reported that 49% of
patients had major depression in interviews administered by
trained psychology students, a second found a prevalence of
7% using psychiatrist-delivered interviews and a third reported
that 22% of patients had depression using ‘trained
effect on prevalence estimates of different
methods of diagnosing depression
Cases of depression were defined using DSM and ICD criteria
in all the studies we included. Some attempted to address the
concern that cancer-related physical symptoms might result in
an overestimate of depression prevalence by judging the cause
of these symptoms in individual patients. We were not able to
discern a clear pattern in prevalence estimates based on these
approaches (i.e. it was not clear that using an inclusive
approach led to higher prevalence estimates within the
subgroups). One study reported two prevalence estimates, one
using DSM criteria for major depression and a much lower
prevalence using the Endicott criteria when these were applied
by the same interviewers.
In the ‘outpatients’ subgroup, two studies used the SCID alone,
one used a two-stage process that included the SCID and the
other three studies each used a different interview schedule.
While the small number of studies makes comparisons
difficult, those using the SCID tended to report lower
depression prevalence (range 5% to 9%) compared with those
that used other interviews (range 8% to 16%). However, it
should be noted that two of the SCID-based studies used
The ‘outpatients’ and ‘palliative care’ clinical subgroups
included studies that used expert interviewers (psychiatrists or
clinical psychologists) as well as those that used less expert
interviewers. In outpatients, the range of depression prevalence
was 5% to 9% when assessed by experts and 8% to 16% when
assessed by less expert interviewers. In palliative care settings,
there were fewer studies but the one study that used expert
assessments reported a prevalence of 7% compared with 22%
and 49% in the other two studies.
Of 66 relevant studies, it was notable that only 15 (23%) met
our basic quality criteria for inclusion in this review. The
reporting of both study methods and results was often unclear,
even in the studies we included, and few publications had
adhered to current reporting guidelines. There were too few
comparable studies in the subgroups for us to conduct meta-
analyses that would be likely to yield meaningful results. The
studies we reviewed reported current depression prevalence
estimates ranging from 5% to 16% in outpatients, 4% to 14%
in inpatients, 4% to 11% in mixed outpatient and inpatient
samples and 7% to 49% in palliative care. Despite the fact that
all studies used standard diagnostic criteria to define
depression caseness, those in which an expert (psychiatrist or
clinical psychologist) administered interviews reported a lower
estimate of current depression prevalence than studies that
employed less expert interviewers.
Figure 1. Forest plot of depression prevalence estimates and (exact) 95% confidence intervals. Squares indicate point prevalence and are approximately
proportional in size to the size of the study they refer to.1Estimate represents 12-month prevalence.
Annals of Oncology
| Walker et al. Volume 24 | No. 4 | April 2013
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Our finding that there are a large number of publications
reporting the prevalence of depression in patients with cancer,
but that few of these reported studies met basic quality criteria,
echoes observations made in previous systematic reviews and
their accompanying editorials . To the best of our
knowledge, our review is the first to use a systematic checklist
of transparent quality criteria to determine which studies
should be included in the review. We were unable to find any
consistent pattern in prevalence estimates based on the
approaches that researchers had taken to physical symptoms.
This is consistent with other work that suggests that the effect
of such modifications to diagnostic criteria may be smaller
than previously thought [48, 49]. It is noteworthy that a recent
meta-analysis of all interview-based studies found a pooled
prevalence of ∼16%, which is substantially higher than the
estimates we obtained from the subset of studies in which an
expert had administered the interviews . Wasteson et al.
 have previously commented that lack of consistent
measurement and definition of depression in people with
cancer makes comparisons of prevalence estimates problematic
and that the range of experience and training of interviewers
employed in prevalence studies adds to this problem.
strengths and limitations
This review has a number of strengths. We searched for articles
systematically and included studies using clearly defined
criteria to minimise selection bias. We also judged studies’
methodological quality and excluded those that had specific
design flaws rather than merely assigning quality scores,
thereby maximising the transparency and reproducibility of the
review [51, 52]. Our review also has limitations. First, while
our quality criteria were based on relevant literature, guidelines
for assessing the quality of observational studies are less well-
defined than those for clinical trials, making some of the
criteria we used, such as sample size, relatively arbitrary.
However, we believe that our quality criteria may be
considered a reasonable minimum and were not over stringent
(e.g. a sample of 100 participants is lower than that
recommended). Second, our assessments of studies, both for
relevance and quality, were based on the information available
in the published reports. This may mean that we excluded
studies that were well conducted but simply poorly reported.
However, even if this were the case, it would be unlikely to
explain much of the methodological shortcomings apparent in
the reports. Third, we grouped studies using clinically relevant
settings, as patients attending outpatient clinics are likely to be
less unwell than inpatients and those receiving palliative care.
However, these groups are not homogenous, and the wide
range of depression prevalence estimates in the palliative care
setting, for example, may reflect the contributions of cultural
and treatment factors to depression causation that we were
unable to study. Finally, we did not attempt to include grey
literature by contacting relevant experts for unpublished
manuscripts. However, we did make substantial efforts to find
all relevant published studies through inclusive search
strategies and the use of translators.
Depression is an important and potentially fatal but treatable
complication of cancer. As well as having substantial effects on
quality of life, depression contributes to non-adherence to
medical treatments . In order to plan effective services, we
need accurate estimates of its prevalence in clinically
meaningful subgroups of cancer patients.
Despite a large number of relevant publications, it was
striking that few studies met our basic quality criteria and we,
therefore, currently lack adequately precise and useful data on
the prevalence of depression in clinically relevant subgroups of
cancer patients. Studies that used expert interviewers to
diagnose depression were more consistent in their findings and
reported a lower prevalence than studies that used less expert
interviewers. Finally, we wish to make a plea for an
improvement in the quality of the research published in this
area and suggest that the quality criteria used in this review,
along with the use of expert interviewers, are a prerequisite for
the funding and publication of future studies on this topic.
The authors would like to acknowledge the support of Anne
Byrne and Marshall Dozier.
This work was supported by Cancer Research UK (grant
The authors have declared no conflicts of interest.
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| Walker et al.Volume 24 | No. 4 | April 2013
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