Skip to main content
NIHPA Author Manuscripts logoLink to NIHPA Author Manuscripts
. Author manuscript; available in PMC: 2013 May 15.
Published in final edited form as: Cancer. 2011 Oct 11;118(10):2735–2743. doi: 10.1002/cncr.26603

Is Screening Effective in Detecting Untreated Psychiatric Disorder Among Newly Diagnosed Breast Cancer Patients?

Steven C Palmer 1, Alison Taggi 1, Angela DeMichele 2, James C Coyne 1
PMCID: PMC3421028  NIHMSID: NIHMS325398  PMID: 21989608

Abstract

BACKGROUND

A key purpose of routine distress screening is to ensure that cancer patients receive appropriate mental health care. Most studies validating screening instruments overestimate the effectiveness of screening by not differentiating between patients with untreated disorder and those already being treated. This study adopts the novel strategy of evaluating the effectiveness of screening after correcting for disorder for which treatment is already being provided.

METHODS

437 recently diagnosed breast cancer patients received in-clinic distress screening and telephone-based psychiatric interviews. Analyses were conducted using receipt of psychotropic medication for mental health difficulties in the context of a psychiatric disorder as a proxy for identification and treatment.

RESULTS

Rates of elevated distress (33%), MDD (8%), minor depression (6%), dysthymia (2%), or GAD (3%) were similar to those in other samples. Thirty-six percent of the sample received psychotropic medication around the time of cancer diagnosis, including 64% of those with a current psychiatric diagnosis. Although 39% of those with elevated distress had a psychiatric disorder, the positive predictive value of screening fell to 15% for an untreated psychiatric disorder and 6% had untreated depression.

CONCLUSION

Given high rates of existing treatment, screening may not be efficient for identifying untreated disorder. Almost two-thirds of patients with treated disorders remain symptomatic. Use of symptom scales might reasonably be expanded to surveillance of treatment response or ruling out disorder. Substantial resources would likely be required to coordinate or manage psychiatric care among patients, as would a willingness to intervene in existing relationships with other providers.

Keywords: Adaptation, Psychological, Breast Neoplasms/Psychology, Psychotropic drugs/therapeutic use, Depression


A NIH Consensus Conference Statement1 and an IOM report 2 have identified detection and management of distress and psychiatric disorder among cancer patients as a priority. Screening is often proposed as a first step in providing appropriate psychosocial and mental health care, and as a means of reducing morbidity and improving quality of life 35. Evidence-based guidelines for managing distress, however, are still being developed 6. Moreover, a considerable proportion of positive screens for distress represents psychiatric disorder, typically 30 to 45%78. Such disorders tend to be chronic, episodic, and recurrent. They require more intensive care and longer follow-up, but have the advantage of an agreed upon nosology and well-defined, empirically-based treatment guidelines. Evaluations of screening instruments, therefore, typically make gold standard comparisons against validated diagnostic interviews for psychiatric disorders910.

Questions have been raised about the appropriateness of particular screening instruments for specific subgroups of cancer patients 1112, though most screening instruments appear to have moderate performance compared to diagnoses based on psychiatric interviews10. Even the best performing instrument cannot be used diagnostically, and so screening is best construed as an initial step in a process in which positive screens are followed by a diagnostic interview13. Given the modest prevalence of psychiatric disorder in most cancer populations, however, most positive screens will be found to be false positives, rendering screening potentially inefficient8.

Routine screening programs assume that screening provides a means of uncovering distress and psychiatric disorder that would not otherwise be identified and treated1415. In clinical practice, the interest is not in detecting patients already being treated, but in those who would otherwise be missed. A shortcoming of existing studies of the accuracy and yield of screening tools in cancer care is that they are almost always conducted with all available patients, including patients who have already been recognized and are receiving treatment for psychiatric disorder, inflating estimates of the number of patients in need of treatment that screening can yield. A recent systematic review of the diagnostic accuracy of screening instruments for depression found only 8 of 197 (4.1%) unique publications from 17 systematic reviews and meta-analyses specifically excluded patients already diagnosed or being treated for depression15. Only 2 of the 8 concerned cancer patients11,17, both of which were from the same sample, and these simply excluded diagnosed or currently treated depression without determining the effect of doing so on screening performance.

Patients with a psychiatric disorder who are already in treatment may differ from those who are not by having more conspicuous disorder or more positive attitudes about treatment 18. Patients for whom screening represents the only means of identifying psychiatric morbidity may, therefore, be more difficult to diagnose and require additional resources to overcome resistance to treatment, while those already in treatment but remaining sufficiently symptomatic to screen positive may require improved surveillance and greater coordination of care with outside providers. Routine care for depression in the community tends to be inadequate, with low adherence, high rates of unsupervised discontinuation of treatment, and a lack of scheduled follow-up visits1920. These problems suggest the value of surveillance of existing treatment, with a recognition that the clinical resources required would differ substantially from those required if the goal were simply initiation of new treatment based on screening.

We sought to evaluate the performance of screening among newly diagnosed breast cancer patients, comparing screening results to a validated diagnostic interview, first, as is typically done, ignoring whether patients were already in treatment, and, second, taking existing psychotropic treatment into account. We chose newly diagnosed patients as there is evidence that distress is most prominent early in the cancer trajectory 2126 and predicts long term adaptation27. Our objectives were to (1) evaluate the ability of a screening instrument to detect depression and other psychiatric disorders among a sample of patients in early treatment for breast cancer, and (2) determine how screening performance is affected when existing treatment for disorder is taken into account.

METHOD

Participants

Recently diagnosed breast cancer patients seeking treatment at a comprehensive cancer center were eligible to participate. Inclusion criteria included age 18 to 85 years, ability to understand and speak English, and enrollment within 5 months of diagnosis and prior to chemotherapy. Exclusion criteria included current recurrence of cancer within 5 years, current substance abuse, and history of bipolar or psychotic disorders.

Procedure

Potential participants were approached following their first medical oncology or post-operative surgical visit and asked to participate in a longitudinal study of the psychosocial impact of breast cancer and its treatment. Those expressing interest provided informed consent. Participants were given questionnaires to be completed and returned by mail within one week. Questionnaires included the distress screening measure, demographics, and additional psychosocial measures. Patients who did not return their questionnaires within two weeks received a telephone call to prompt return of the packet. A semi-structured mental health telephone interview was scheduled within two weeks, and only took place following receipt of screening materials. During the interview, the purpose of the study was reviewed and participant questions answered. Interviews were recorded for reliability purposes. Ethics approval was granted by the University of Pennsylvania Institutional Review Board and the Clinical Trials and Scientific Monitoring Committee of the Abramson Cancer Center.

Measures

Demographics

Demographics included age, race, education, marital status, and household income.

Psychopharmacological Treatment

Prescription of psychotropic medication for psychiatric disorder was assessed by interview. We were concerned about participants reporting medications received for non-mental health reasons (e.g., hot flashes, pain), so participants were asked if they had been “given a prescription in the past six months for problems with stress, emotions, nerves, drugs, alcohol or mental health.” Medication names and dosages were reported by direct patient inspection of available bottles, and medications were coded into Antidepressant, Anxiolytic or Other (e.g., hypnotic) categories. For current analyses, only anxiolytic and antidepressant prescriptions were examined.

Chart Abstraction/Clinical Characteristics

Cancer treatment information, disease staging, diagnosis date, and occurrence of metastases/recurrences were abstracted from charts by a trained medical abstractor.

Distress Screening

The 25-item 28 Hopkins Symptom Checklist 29 (HSCL-25) was used to screen for psychological distress. The items of the HSCL-25 and either overlap with or have inconsequential differences from items on various versions of the Brief Symptom Inventory 3032. As a group, this family of instruments is widely used among cancer patients3336. Hough and colleagues28 found that the HSCL-25 was comparable or superior to the CES-D37 in detecting psychiatric disorder among general medical patients. The HSCL-25 has demonstrated reliability 3840. In the current sample, Cronbach’s alpha was good (0.93).

Psychiatric Diagnosis

Diagnoses were obtained using the Structured Clinical Interview for DSM-IV/NP (SCID) 41, a DSM-IV 42 based semi-structured interview. Modules for current Major Depressive Disorder (MDD) and life-time history of past MDD, Dysthymic Disorder, and Generalized Anxiety Disorder (GAD) were telephone-administered by trained research staff blind to participant responses on questionnaires. Studies have shown good concordance between telephone and face-to-face diagnostic interviews 4346. Inter-rater reliability was assessed on 10% (n=44) of interviews for MDD and past MDD diagnoses. Agreement at the symptom level was high (91%) and reliability was adequate (kappa = 0.70 – 0.85).

Primary Data Analysis

Using the standard cut point of 44 on the HSCL-25, sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) were calculated for the presence of: 1) MDD and 2) a category combining “any psychiatric disorder,” which included MDD, minor depression, dysthymia, and GAD. Ninety-five percent confidence intervals (CIs) for proportions were constructed using the modified Wald method 47. Next, patients with a psychiatric diagnosis that was already being treated pharmacologically were removed from the sample and performance characteristics were recalculated to estimate performance for the non-treated patients who would be of greatest interest in clinical practice. All hypothesis tests were two-tailed.

RESULTS

Characteristics of Sample

652 patients were approached to participate and 588 consented (90%). Of these, 535 (91%) contributed questionnaire or interview data, and 437 of these (82%) contributed both and are included in the current analysis for an overall participation rate of 67%. Patients contributing both questionnaire and interview data did not differ from those contributing one but not the other for presence of any psychiatric disorder, psychotropic medication, distress, cancer stage, race, income, or marital status (p ranges 0.10–0.80). Table 1 provides demographic information for the sample.

Table 1.

Sample Descriptives

M (SD) Range
Age (years) 54.2 (11.7) 27–83
Time Since Diagnosis (days) 56.1 (33.1) 0–160
Percent of Sample
Race White 73%
African American 20%
Other 7%
Marital Status Married/Married-like 67%
Separated/Divorced 14%
Single 11%
Widowed 8%
Income (year) > $80,000 49%
$40,000–$80,000 28%
< $40,000 23%
Education ≥ College Graduate 55%
At Least High School 97%
Employment (current) Full-time 49%
Part-time 16%
Retired 18%
Other/Homemaker 17%
Stage at Diagnosis Stage 0 18%
Stage I 37%
Stage IIa 23%
Stage IIb 11%
Stage IIIa 8%
Stage IIIb 3%
ER Status Positive 80%
PR Status Positive 70%
Her2/Neu Status Positive 15%

NOTE: ER = Estrogen Receptor; PR = Progesterone Receptor; Her2/Neu = Human Epidermal growth factor Receptor 2

Distress, Psychiatric Diagnosis, and Psychotropic Medication

Overall, psychological distress was moderate (M = 40.2, SD = 10.7) and significantly below the cut-point of 44 indicating “elevated distress” (t(436) = −7.3, p < .001). However, 33% of the sample (CI = 28–37%; n=142) scored above the established cut-point.

Criteria for current MDD were met in 8% of the sample (CI = 6–11%; n = 36), while 2% (CI=0.7–3%; n = 7) met criteria for dysthymia and 3% (CI = 2–5%; n = 14) for GAD. Minor depression research criteria were met in 6% (CI = 4–9%; n = 26). Criteria for at least one of these psychiatric disorders were met by 17% of participants (CI =14–21%, n=74). Approximately 20% (CI=16–24%, n=87) of the sample reported a past history of MDD on the SCID.

At interview, 36% (N=158) had a prescription for a psychotropic medication. Twenty percent of the sample (n=88) had a prescription for an antidepressant, 26% an anxiolytic (n=112), and 10% (n=42) both. Almost two-thirds (64%, n=47) of participants with a current psychiatric diagnosis were receiving psychotropic medication (X2(1) = 28.89, p ≤ .001), with 46% (n=34) receiving antidepressants and 42% (n=31) receiving anxiolytics. With respect to specific diagnoses (Table 2), more than three-quarters of those with current MDD (n=28) were receiving psychotropic medication, with similar proportions of antidepressant (n=20) or anxiolytic (n=19) prescriptions. Minor depression and dysthymia were less likely to have been treated, while GAD was treated at a rate of 71% (n=10), with antidepressants (n=7) and anxiolytics (n=7) being equally likely to have been prescribed. Close to half of patients with a history of MDD but without current disorder (n=27) were receiving treatment. However, prescriptions were non-specific, and more than one quarter (28%; n=81) of patients with neither current nor past disorder received psychotropic medication, accounting for 53% of all psychotropic prescriptions.

Table 2.

Rates of Psychotropic Medication Prescription

Any Psychotropic Antidepressant Anxiolytic
MDD 78%* (n=28) 56%* (n=20) 53%* (n=19)
Minor Depression 50% (n=13) 39%*(n=10) 35%(n=9)
Dysthymia 43%(n=3) 43%(n=3) 14%(n=1)
GAD 71%*(n=10) 50%*(n=7) 50%*(n=7)
Past MDD – No Current Dx 48%*(n=27) 30%*(n=17) 34%*(n=19)
No Current or Past Dx 27%(n=81) 12%(n=36) 20%(n=59)
*

p < 0.05 in X2 analyses compared to individuals without disorder.

NOTE: MDD = Major Depressive Disorder; GAD = Generalized Anxiety Disorder; Dx = Diagnosis

Detecting Psychiatric Disorder Through Screening

Elevated distress on the HSCL-25 related significantly to the presence of current MDD (X2(1) = 67.88, p ≤ .001). This association translated into modest screening efficiency (Table 3). Although only 2 patients of 36 with current MDD were missed, 76% of those who screened positive did not have MDD (n=109), and, reflecting the overall prevalence of MDD in this sample, a patient screening positive would be 3.2 times more likely to not have MDD than to have MDD. A negative screen, however, was very efficient in ruling out MDD (NPV=0.99)

Table 3.

Screening Characteristics for Disorder and Untreated Disorder

Sensitivity (95% CI) Specificity (95% CI) PPV (95% CI) NPV (95% CI) True Positive (n) False Positive (n) True Negative (n) False Negative (n)
MDD .94 (.82–.99) .73 (.72–.73) .24 (.21–.25) .99 (.98–1.0) 34 109 292 2
Any Disorder .74 (.65–.82) .76 (.74–.78) .39 (.34–.43) .94 (.91–.97) 55 88 275 19
Untreated MDD .88 (.53–.98) .73 (.72–.73) .06 (.04–.07) 1.0 (.99–1.0) 7 109 292 1
Any Untreated Disorder .56 (.38–.72) .76 (.75–.77) .15 (.10–.19) .96 (.94–.97) 15 88 275 12
Untreated MDD+ .88 (.47–.99) .78 (.77–.79) .11 (.06–.12) 1.0 (.98–1.0) 7 59 212 1
Any Untreated Disorder+ .56 (.38–.73) .80 (.78–.82) .23 (.15–.30) .94 (.92–.97) 15 51 201 12
+

For these analyses all individuals receiving medication were removed from consideration.

NOTE: PPV = Positive Predictive Value; NPV = Negative Predictive Value; MDD = Major Depressive Disorder

HSCL-25 scores were significantly related to the presence of any psychiatric disorder (X2(1) = 70.03, p ≤ .001). However, the HSCL-25 missed 26% (n=19) of those with a current disorder, while 24% (n=88) of those with no current disorder screened positive, accounting for 61% of positive screens.

Detecting Untreated Psychiatric Disorders

When patients with treated MDD were removed from the analysis, a positive screen for distress remained significantly related to the presence of MDD (X2(1) = 14.05, p < .001). Screening missed only one of eight patients with MDD; however, 95% (n=109) of those patients receiving positive screens (n=115) did not have MDD. Moreover, although 28% of the sample (n=116) screened positive, only 6% of these (n=7) had MDD that had not already been identified and treated1.

When all patients with treated disorder were removed from analysis, a positive screen for distress still significantly predicted presence of any untreated psychiatric disorder (X2(1) = 12.68, p < .001). However, a positive screen for distress missed 44% (n=12) of untreated psychiatric disorders (n=27), whereas 24% (n=88) of those without disorder continued to screen positive, accounting for 85% of all positive screens.

To examine whether high rates of prescription of psychotropic medication in this sample reflected potentially appropriate maintenance or prophylactic treatment of past major depressive disorder, we analyzed data excluding patients with current treated disorder and/or past MDD receiving current treatment. For untreated MDD, results were similar to those in Table 3 (sensitivity = 0.83, specificity = 0.78, PPV = 0.06, NPV = 1.0), as were those obtained considering presence of any untreated disorder (sensitivity = 0.57. specificity = 0.79, PPV = 0.13, NPV = .97).

Finally, to approximate more closely what would happen in clinical practice if decisions about screening were based only on information at hand (e.g., whether or not a patient is receiving treatment), we reanalyzed data excluding all participants receiving psychotropic medication regardless of presence of disorder. Results were substantially similar using the HSCL-25 for both detection of untreated MDD (X2(1) = 18.69, p < .001; sensitivity = 0.88, specificity = 0.79, PPV = 0.11, NPV = 1.0) and any untreated current disorder (X2(1) = 16.84, p < .001; sensitivity = 0.57, specificity = 0.80, PPV = 0.23, NPV = .94).

DISCUSSION

When evaluated against a diagnostic interview with no adjustment for prior identification, the HSCL-25 performed comparably to other instruments10. A negative screen was an accurate indicator of the absence of psychiatric disorder. However, the number of true positive cases was dwarfed by false positives. Moreover, when patients with a psychiatric disorder that had already been identified and treated were excluded from analyses, the ratio of true positive identifications relative to false positives was further reduced. Given that sensitivity varies only slightly and specificity not at all, this effect largely results from the lower prevalence rate for untreated participants relative to the entire sample. That is, removal of treated individuals reduces the prevalence of disorder from approximately 16% (74/437) to 7% (27/390). Our results raise questions about the efficiency of routine screening as a means of identifying psychiatric disorder that would otherwise go untreated, and point to the need for future studies validating screening instruments to take existing treatment into account.

The prevalence of distress in our sample was comparable to what is found in other samples 4849. Prevalence estimates of MDD or other disorders in past research vary widely, largely due to methodological differences 50. However rates that are lower and similar to those in the current study are obtained when research interviews, rather than self-report instruments, are used to determine caseness 49, 5152. An expert consensus statement has concluded that rates of psychiatric disorder among cancer patients are comparable to those found in other medical populations, but higher than the general population 53.

The high rates of prescription of psychotropic medication were striking and need to be interpreted in the context of escalating rates of prescription in the general population 5455. In a previous study of longer term breast cancer survivors7 we found similar prescription rates, but that sample was heterogeneous with respect to time since diagnosis and 66% of the sample had been diagnosed 2 or more years previously. The present sample was less than two months from diagnosis, on average. It is, however, unclear whether psychotropic medication had been prescribed following diagnosis of cancer or prior to diagnosis.

There are few data concerning prescription of antidepressants in cancer care, but there are suggestions that rates are high relative to the prevalence of MDD. Ashbury et al. 56 found that 19.2% of breast cancer patients received an antidepressant prescription in the two years following diagnosis, and that prescription related to receipt of pain medication. This likely underestimates prescription, as Asbury et al. included only those prescriptions obtained or recorded through oncology services, and many patients receive prescriptions through primary care 57. A study of terminally ill cancer patients found 40% had an antidepressant prescription, although the prevalence of MDD was only 17%58. Previous work has suggested that repeated contact with non-mental health specialty physicians increases rate of prescription of psychotropic medications, but not necessarily quality of care 59. Future reports from our dataset will examine type of provider and changes in prescription rates out to a year after diagnosis.

Psychotropic prescriptions appeared non-specific, and more than a quarter of those with neither current nor past psychiatric diagnosis were receiving medication for “stress, emotions, nerves, drugs, alcohol or mental health” around cancer diagnosis. Another study7 suggests that non-specific prescription increases over time, rather than plateauing. In that study, 48% of long term breast cancer survivors with neither current nor past psychiatric diagnosis received an anxiolytic or antidepressant. Clearly, there is a need to examine whether this leads to improved outcomes, though the literature on treatment of subsyndromal depression would suggest that this is unlikely 60-.

We found that the proportion of patients with unidentified and untreated psychiatric disorder was considerably less than the proportion of those who were receiving treatment but remaining syndromal. If replicated, our results may suggest that focusing efforts away from detecting untreated disorder toward surveillance of clinical response of already treated patients and using this information to improve quality of care may be worthwhile. Instruments that have been used for screening have been used as symptom scales to monitor treatment outcomes 6264 and there have been demonstrations that improving consistency and quality of care provided to already identified patients with MDD would have a larger impact on a population basis than would increasing the number of patients introduced to treatment 65. Other data suggest that among cancer patients as few as 15% of those with MDD receive treatment at a therapeutic level 66. The quality of routine depression care in the community is generally poor, particularly in general and tertiary non-psychiatric medical settings 6768 and there may be particular problems ensuring high quality care within the competing demands of cancer. As well, assuming responsibility for insuring appropriate care of patients already receiving prescriptions would probably require different staffing, resources, and relations with prescribing providers than those currently present in oncology care.

Other data suggest that it may prove challenging to engage those patients who have untreated psychiatric disorder in appropriate treatment. A recent study examining screening for “high risk” medical patients 69 found that of the 1687 patients invited for screening, only 71 were identified with MDD and 36 were already in treatment. Fourteen of the remaining 35 refused treatment, and another four did not show for an appointment. Ultimately, the number needed to be invited for screening in order for one previously unidentified depressed patient to receive treatment was 118. It seems likely that negative attitudes toward depression treatment are at least partially responsible for patients having their depression unidentified 18, 70, and will further complicate engaging them in treatment.

This study had the benefit of a high participation rate, a relatively large sample, and use of a validated psychiatric interview. It is limited by having been conducted at a single institution with a well-resourced population, and we cannot evaluate the degree to which results generalize to lower resourced settings or populations. The low prevalence of psychiatric disorder led to a small number of patients with any given disorder, particularly when examining untreated disorder, though confidence intervals take this into account. Our results likely underestimate the degree to which psychiatric disorder is already identified, as we do not have data concerning non-pharmacologic interventions or whether patients may have been offered but declined treatments. Thus, our estimates of the effects of taking existing treatment into account should be seen as conservative in that consideration of psychotherapy and other psychosocial interventions would have increased the number of patients classified as receiving treatment.

We ascertained prescriptions by self-report. Although there are limitations to self-report, participants were asked to have all medication bottles available during the interview, and we inquired specifically about medications provided for “problems with stress, emotions, nerves, drugs, alcohol or mental health.” However, we lacked systematic data about timing, indications, and sources of prescriptions, as well as adherence. It remains possible that some prescriptions were made for off-label indications. However, our interviews specified prescriptions for mental health-related difficulties, we ignored prescriptions for non-antidepressant or anxiolytic medications (e.g., Zolpiden), and significant relationships between psychiatric diagnosis and receipt of prescription suggest that this was not a primary reason for prescriptions. It is possible that some prescriptions were missed through self-report, though rectifying this would likely strengthen rather than attenuate results. Finally, we did not take into account nonpharmacological treatment, treatment refusal, or adherence. Although some psychotherapy for depression is evidence-supported71, the availability of empirically supported psychotherapeutic interventions among patients drawn from nonpsychiatric medical settings is likely to be low 72.

In conclusion, our data indicate that screening may be less efficient as a means of identifying untreated psychiatric disorder among newly diagnosed breast cancer patients than would be inferred from estimates in the current literature of the efficiency of screening. Given the high proportion of patients with disorders who are treated without adequate remission of symptoms, and the difficulties likely to be experienced engaging non-identified patients in treatment, screening measures might be better utilized as an initial step in monitoring the effectiveness of ongoing treatment, ruling out disorder, 8 or as a prompt for improving communication surrounding psychosocial issues rather than a means of identifying individuals with untreated disorder. Clinicians in cancer care settings, however, will require significant resources if they are to effectively coordinate or manage psychiatric care among patients, in addition to having a willingness to intervene in existing treatment relationships with other providers.

Acknowledgments

Supported by Grant Number R01MH63172 from the National Institute of Mental Health and the National Cancer Institute.

Footnotes

1

A more conservative approach would be to exclude as treated those individuals with MDD who were receiving antidepressant medication only rather than antidepressants or anxiolytics combined, as antidepressants are the preferred medication for MDD. Results of analysis using this method are quite similar to those removing individuals receiving either medication (X2(1) = 32.6, p < .001; sensitivity = 0.94, specificity = 0.72, PPV = 0.12, NPV = 1.0).

No Financial Disclosures By Any Authors.

References

  • 1.Patrick DL, Ferketich SL, Frame PS National Institutes of Health State-of-the-Science Conference Statement. Symptom management in cancer: pain, depression, and fatigue. July 15–17, 2002. J Natl Cancer Inst. 2004;32:9–16. doi: 10.1093/jncimonographs/djg014. [DOI] [PubMed] [Google Scholar]
  • 2.Adler NE, Page AEK, editors. Cancer Care for the Whole Patient: Meeting Psychosocial Health Needs. Washington, DC: The National Academies Press; 2007. [PubMed] [Google Scholar]
  • 3.Holland JC, Bultz BD. The NCCN guideline for distress management: a case for making distress the sixth vital sign. J Natl Compr Canc Netw. 2007;5:3–7. [PubMed] [Google Scholar]
  • 4.Middleton H, Shaw I, Hull S, et al. NICE guidelines for the management of depression. BMJ. 2005;330:267–268. doi: 10.1136/bmj.330.7486.267. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 5.United States Preventive Services Task Force. Screening for depression: recommendations and rationale. Ann Intern Med. 2002;136:760–764. doi: 10.7326/0003-4819-136-10-200205210-00012. [DOI] [PubMed] [Google Scholar]
  • 6.Jacobsen PB, Ransom S. Implementation of NCCN distress management guidelines by member institutions. J Natl Compr Canc Netw. 2007;5:99–103. doi: 10.6004/jnccn.2007.0010. [DOI] [PubMed] [Google Scholar]
  • 7.Coyne JC, Palmer SC, Shapiro PJ, et al. Distress, psychiatric morbidity and prescriptions for psychotropic medication in a breast cancer waiting room sample. Gen Hosp Psychiatry. 2004;26:121–128. doi: 10.1016/j.genhosppsych.2003.08.012. [DOI] [PubMed] [Google Scholar]
  • 8.Mitchell AJ. Short screening tools for cancer-related distress: a review and diagnostic validity meta-analysis. J Natl Compr Canc Netw. 2010;8:487–494. doi: 10.6004/jnccn.2010.0035. [DOI] [PubMed] [Google Scholar]
  • 9.Mitchell AJ. Are one or two simple questions sufficient to detect depression in cancer and palliative care? A Bayesian meta-analysis. Br J Cancer. 2008;98(12):1934–1943. doi: 10.1038/sj.bjc.6604396. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 10.Vodermaier A, Linden W, Siu C. Screening for emotional distress in cancer patients: a systematic review of assessment instruments. JNCI Journal of the National Cancer Institute. 2009;101(21):1464–1488. doi: 10.1093/jnci/djp336. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 11.Lloyd-Williams M, Friedman T, Rudd N. An analysis of the validity of the Hospital Anxiety and Depression scale as a screening tool in patients with advanced metastatic cancer. J Pain Symptom Manage. 2001;22:990–996. doi: 10.1016/s0885-3924(01)00358-x. [DOI] [PubMed] [Google Scholar]
  • 12.Nelson CJ, Cho C, Berk AR, et al. Are gold standard depression measures appropriate for use in geriatric cancer patients? A systematic evaluation of self-report depression instruments used with geriatric, cancer, and geriatric cancer samples. J Clin Oncol. 2010;28:348–356. doi: 10.1200/JCO.2009.23.0201. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 13.Mitchell AJ. Pooled results from 38 analyses of the accuracy of distress thermometer and other ultra-short methods of detecting cancer-related mood disorder. J Clin Oncol. 25:4670–4681. 200. doi: 10.1200/JCO.2006.10.0438. [DOI] [PubMed] [Google Scholar]
  • 14.Coyne JC, Thompson R, Palmer SC, et al. Should we screen for depression? Caveats and potential pitfalls. Appl Prev Psychol. 2000;9:101–121. [Google Scholar]
  • 15.Palmer SC, Coyne JC. Screening for depression in medical care: pitfalls, alternatives, and revised priorities. J Psychosom Res. 2003;54:279–287. doi: 10.1016/s0022-3999(02)00640-2. [DOI] [PubMed] [Google Scholar]
  • 16.Thombs BD, Arthurs E, El-Baalbaki G, et al. Risk of bias from inclusion of already diagnosed or treated patients in diagnostic accuracy studies of depression screening tools: A systematic review. BMJ. doi: 10.1136/bmj.d4825. In press. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 17.Lloyd-Williams M, Friedman T, Rudd N. Criterion validation of the Edinburgh Postnatal Depression Scale as a screening tool for depression in patients with advanced metastatic cancer. J Pain Symptom Manage. 2000;20(4):259–265. doi: 10.1016/s0885-3924(00)00182-2. [DOI] [PubMed] [Google Scholar]
  • 18.Pyne JM, Rost KM, Farahati F, et al. One size fits some: the impact of patient treatment attitudes on the cost-effectiveness of a depression primary-care intervention. Psychol Med. 2005;35:839–854. doi: 10.1017/s0033291704003332. [DOI] [PubMed] [Google Scholar]
  • 19.Fernandez A, Haro JM, Martinez-Alonso M, et al. Treatment adequacy for anxiety and depressive disorders in six European countries. Br J Psychiatry. 2007;190:172–173. doi: 10.1192/bjp.bp.106.023507. [DOI] [PubMed] [Google Scholar]
  • 20.Mojtabai R, Olfson M. National patterns in antidepressant treatment by psychiatrists and general medical providers: Results from the National Comorbidity Survey replication. J Clin Psychiatry. 2008;69:1064–1074. doi: 10.4088/jcp.v69n0704. [DOI] [PubMed] [Google Scholar]
  • 21.Hinnen C, Ranchor AV, Sanderman R, et al. Course of distress in breast cancer patients, their partners, and matched control couples. Ann Behav Med. 2008;36:141–148. doi: 10.1007/s12160-008-9061-8. [DOI] [PubMed] [Google Scholar]
  • 22.Henselmans I, Helgeson VS, Seltman H, et al. Identification and prediction of distress trajectories in the first year after a breast cancer diagnosis. Health Psych. 2010;29:160–168. doi: 10.1037/a0017806. [DOI] [PubMed] [Google Scholar]
  • 23.Henselmans I, Sanderman R, Baas, et al. Personal control after a breast cancer diagnosis: Stability and adaptive value. Psycho-Oncology. 2009;18:104–108. doi: 10.1002/pon.1333. [DOI] [PubMed] [Google Scholar]
  • 24.Lam WWT, Bonanno GA, Mancini AD, et al. Trajectories of psychological distress among Chinese women diagnosed with breast cancer. Psycho-Oncology. 2010;19:1044–1051. doi: 10.1002/pon.1658. [DOI] [PubMed] [Google Scholar]
  • 25.Millar K, Purushotham AD, McLatchie E, et al. A 1-year prospective study of individual variation in distress, and illness perceptions, after treatment for breast cancer. J Psychosom Res. 2005;58:335–342. doi: 10.1016/j.jpsychores.2004.10.005. [DOI] [PubMed] [Google Scholar]
  • 26.Stanton A, Danoff-Burg S, Huggins M. The first year after breast cancer diagnosis: Hope and coping strategies as predictors of adjustment. Psycho-Oncology. 2002;11:93–102. doi: 10.1002/pon.574. [DOI] [PubMed] [Google Scholar]
  • 27.Hartl K, Engel J, Herschbach P, et al. Personality traits and psychosocial stress: quality of life over 2 years following breast cancer diagnosis and psychological impact factors. Psycho-oncology. 2010;19:160–169. doi: 10.1002/pon.1536. [DOI] [PubMed] [Google Scholar]
  • 28.Hough RL, Landsverk JA, Stone JD, et al. Comparison of psychiatric screening questionnaires for primary care patients. Final report for NIMH Contract. 278–0036 (DB) 1982 [Google Scholar]
  • 29.Derogatis LR, Cleary PA. Factorial invariance across gender for the primary symptom dimensions of the SCL-90. Br J Soc Clin Psychol. 1977;16:347–356. doi: 10.1111/j.2044-8260.1977.tb00241.x. [DOI] [PubMed] [Google Scholar]
  • 30.Hesbacher P, Rickels K, Downing RW, et al. Assessment of psychiatric-illness severity by family physicians. Soc Sci Med. 1978;12:45–47. [Google Scholar]
  • 31.Strong V, Waters R, Hibberd C, et al. Management of depression for people with cancer (SMaRT oncology 1): a randomized trial. Lancet. 2008;372:40–48. doi: 10.1016/S0140-6736(08)60991-5. [DOI] [PubMed] [Google Scholar]
  • 32.Kroenke K, Theobald D, Wu J, et al. Effect of telecare management on pain and depression in patients with cancer: a randomized trial. JAMA. 2010;304:163–171. doi: 10.1001/jama.2010.944. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 33.van Scheppingen C, Schroevers MJ, Smink A, et al. Does screening for distress efficiently uncover meetable unmet needs in cancer patients? Psycho-Oncology. 2011;20:655–663. doi: 10.1002/pon.1939. [DOI] [PubMed] [Google Scholar]
  • 34.Kroenke K, Theobald D, Wu J, et al. Effect of telecare management on pain and depression in patients with cancer: a randomized trial. JAMA. 2010;304:163–71. doi: 10.1001/jama.2010.944. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 35.Schilder CM, Seynaeve C, Beex LV, et al. Effects of tamoxifen and exemestane on cognitive functioning of postmenopausal patients with breast cancer: results from the neuropsychological side study of the tamoxifen and exemestane adjuvant multinational trial. J Clin Oncol. doi: 10.1200/JCO.2008.21.3553. [DOI] [PubMed] [Google Scholar]
  • 36.Salzer MS, Palmer SC, Kaplan K, et al. A randomized, controlled study of Internet peer-to-peer interactions among women newly diagnosed with breast cancer. Psycho-Oncology. 2010;19:441–446. doi: 10.1002/pon.1586. [DOI] [PubMed] [Google Scholar]
  • 37.Radloff LS. The CES-D scale: a self-report depression scale for research in the general population. Appl Psychol Meas. 1977;1:385–401. [Google Scholar]
  • 38.Cohen NJ, Coyne JC, Duvall J. Adopted and biological children in the clinic: family, parental, and child characteristics. J Child Psychol Psychiat. 1993;34:542–562. doi: 10.1111/j.1469-7610.1993.tb01035.x. [DOI] [PubMed] [Google Scholar]
  • 39.Cranford JA, Coyne JC, Sonnega J, et al. Psychological distress among male and female congestive heart failure patients and their spouses. Psychosom Med. 1998;60:105. [Google Scholar]
  • 40.Hesbacher PT, Rickels K, Morris RJ, et al. Psychiatric illness in family practice. J Clin Psychiat. 1980;41:6–10. [PubMed] [Google Scholar]
  • 41.First MB, Spitzer RL, Gibbon M, et al. Structured clinical interview for DSM-IV-TR Axis I disorders, research version, non-patient edition. New York: Biometrics Research, New York State Psychiatric Institute; 2001. [Google Scholar]
  • 42.American Psychiatric Association. Diagnostic and statistical manual of mental disorders. 4. Washington, DC: American Psychiatric Association; 1994. [Google Scholar]
  • 43.Baer L, Brown-Beasley MW, Sorce J, et al. Computer-assisted telephone administration of a structured interview for obsessive compulsive disorder. Am J Psychiatry. 1993;150:1737–1738. doi: 10.1176/ajp.150.11.1737. [DOI] [PubMed] [Google Scholar]
  • 44.Kendler KS, Neale MC, Kessler RC, et al. A population based twin study of major depression in women: the impact of varying definitions of illness. Arch Gen Psychiatry. 1992;49:257–266. doi: 10.1001/archpsyc.1992.01820040009001. [DOI] [PubMed] [Google Scholar]
  • 45.Rhode P, Lewinsohn PM, Seeley JR. Comparability of telephone and face-to-face interviews in assessing axis I and II disorders. Am J Psychiatry. 1997;154:1593–1598. doi: 10.1176/ajp.154.11.1593. [DOI] [PubMed] [Google Scholar]
  • 46.Wells KB, Burnam MA, Leake B, et al. Agreement between face-to-face and telephone administered versions of the depression section of NIMH Diagnostic Interview Schedule. J Psychiatr Res. 1988;22:207–220. doi: 10.1016/0022-3956(88)90006-4. [DOI] [PubMed] [Google Scholar]
  • 47.Agresti A, Coull BA. Approximate is better than “Exact” for interval estimation of binomial proportions. Am Stat. 1998;52:119–126. [Google Scholar]
  • 48.Zabora J, BrintzenhofeSzoc K, Curbow B, et al. The prevalence of psychological distress by cancer site. Psychooncology. 2001;10:19–28. doi: 10.1002/1099-1611(200101/02)10:1<19::aid-pon501>3.0.co;2-6. [DOI] [PubMed] [Google Scholar]
  • 49.Trask PC. Assessment of depression in cancer patients. J Natl Cancer Inst Monogr. 2004;32:80–92. doi: 10.1093/jncimonographs/lgh013. [DOI] [PubMed] [Google Scholar]
  • 50.Sharpe M, Strong V, Allen K, et al. Major depression in outpatients attending a regional cancer centre: screening and unmet treatment needs. Br J Cancer. 2004;90:314–320. doi: 10.1038/sj.bjc.6601578. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 51.Walker J, Postma K, McHugh GS, et al. Performance of the Hospital Anxiety and Depression Scale as a screening tool for major depressive disorder in cancer patients. J Psychosom Res. 2007;63:83–91. doi: 10.1016/j.jpsychores.2007.01.009. [DOI] [PubMed] [Google Scholar]
  • 52.Evans DL, Charney DS, Lewis L, et al. Mood disorders in the medically ill: scientific review and recommendations. Biol Psychiatry. 2005;58:175–189. doi: 10.1016/j.biopsych.2005.05.001. [DOI] [PubMed] [Google Scholar]
  • 53.Olfson M, Marcus SC, Druss B, et al. National trends in the outpatient treatment of depression. JAMA. 2002;287:203–209. doi: 10.1001/jama.287.2.203. [DOI] [PubMed] [Google Scholar]
  • 54.Kessler RC, Demler O, Frank RG, et al. Prevalence and treatment of mental disorders, 1990 to 2003. N Engl J Med. 2005;352:2515–2523. doi: 10.1056/NEJMsa043266. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 55.Olfson M, Marcus SC. National patterns in antidepressant medication treatment. Arch Gen Psychiatry. 2009;66:848–856. doi: 10.1001/archgenpsychiatry.2009.81. [DOI] [PubMed] [Google Scholar]
  • 56.Ashbury FD, Madlensky L, Raich P, et al. Antidepressant prescribing in community cancer care. Support Care Cancer. 2003;11:278–285. doi: 10.1007/s00520-003-0446-8. [DOI] [PubMed] [Google Scholar]
  • 57.Klabunde CN, Ambs A, Keating NL, et al. The role of primary care physicians in cancer care. J Gen Intern Med. 2009;24:1029–1036. doi: 10.1007/s11606-009-1058-x. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 58.Breitbart W, Rosenfeld B, Pessin H, et al. Depression, hopelessness, and desire for hastened death in terminally ill patients with cancer. JAMA. 2000;284:2907–2911. doi: 10.1001/jama.284.22.2907. [DOI] [PubMed] [Google Scholar]
  • 59.Benazon NR, Mamdani MM, Coyne JC. Trends in the prescribing of antidepressants following acute myocardial infarction, 1993–2002. Psychosom Med. 2005;67:916–920. doi: 10.1097/01.psy.0000188399.80167.aa. [DOI] [PubMed] [Google Scholar]
  • 60.DeRubeis RJ, Hollon SD, Dimidjian S. Antidepressant drug effects and depression severity: a patient-level meta-analysis. JAMA. 2010;303:47–53. doi: 10.1001/jama.2009.1943. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 61.Ackermann RT, Williams JW., Jr National treatment choices for non-major depressions in primary care: an evidence-based review. J Gen Intern Med. 2002;17:293–301. doi: 10.1046/j.1525-1497.2002.10350.x. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 62.Löwe B, Unützer J, Callahan CM, et al. Monitoring depression treatment outcomes with the patient health questionnaire-9. Med Care. 2004;42(12):1194–1201. doi: 10.1097/00005650-200412000-00006. [DOI] [PubMed] [Google Scholar]
  • 63.Löwe B, Kroenke K, Gräfe K. Detecting and monitoring depression with a two-item questionnaire (PHQ-2) J Psychosom Res. 2005;58:163–171. doi: 10.1016/j.jpsychores.2004.09.006. [DOI] [PubMed] [Google Scholar]
  • 64.Simon GE, VonKorff M, Rutter C, Wagner E. Randomised trial of monitoring, feedback, and management of care by telephone to improve treatment of depression in primary care. BMJ. 2000;320:550–554. doi: 10.1136/bmj.320.7234.550. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 65.Patten SB. A framework for describing the impact of antidepressant medications on population health status. Pharmacoepidemiol Drug Saf. 2002;11:549–559. doi: 10.1002/pds.746. [DOI] [PubMed] [Google Scholar]
  • 66.Sharpe M, Strong V, Allen K, et al. Major depression in outpatients attending a regional cancer centre: screening and unmet treatment needs. Br J Cancer. 2004;90:314–320. doi: 10.1038/sj.bjc.6601578. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 67.Young AS, Klap R, Sherbourne CD, et al. The quality of care for depressive and anxiety disorders in the United States. Arch Gen Psychiatry. 2001;58:55–61. doi: 10.1001/archpsyc.58.1.55. [DOI] [PubMed] [Google Scholar]
  • 68.Kessler RC, Berglund P, Demler O, et al. The epidemiology of major depressive disorder: results from the National Comorbidity Survey Replication (NCS-R) JAMA. 2003;289:3095–3105. doi: 10.1001/jama.289.23.3095. [DOI] [PubMed] [Google Scholar]
  • 69.Baas KD, Wittkampf KA, van Weert HC, et al. Screening for depression in high-risk groups: prospective cohort study in general practice. Br J Psychiatry. 2009;194:399–403. doi: 10.1192/bjp.bp.107.046052. [DOI] [PubMed] [Google Scholar]
  • 70.Nutting PA, Rost K, Dickinson M, et al. Barriers to initiating depression treatment in primary care practice. J Gen Intern Med. 2002;17:103–111. doi: 10.1046/j.1525-1497.2002.10128.x. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 71.Chambless DL, Ollendick TH. Empirically supported psychological interventions: controversies and evidence. Annu Rev Psychol. 2001;52:685–716. doi: 10.1146/annurev.psych.52.1.685. [DOI] [PubMed] [Google Scholar]
  • 72.Kessler R. The difficulty of making psychology research and clinical practice relevant to medicine: experiences and observations. J Clin Psychol Med Settings. 2008;15:65–72. doi: 10.1007/s10880-008-9096-9. [DOI] [PubMed] [Google Scholar]

RESOURCES