PMCCPMCCPMCC

Search tips
Search criteria 

Advanced

 
Logo of jcoHomeThis ArticleSearchSubmitASCO JCO Homepage
 
J Clin Oncol. 2008 September 20; 26(27): 4488–4496.
PMCID: PMC2653113

Randomized Controlled Trial of Collaborative Care Management of Depression Among Low-Income Patients With Cancer

Abstract

Purpose

To determine the effectiveness of the Alleviating Depression Among Patients With Cancer (ADAPt-C) collaborative care management for major depression or dysthymia.

Patients and Methods

Study patients included 472 low-income, predominantly female Hispanic patients with cancer age ≥ 18 years with major depression (49%), dysthymia (5%), or both (46%). Patients were randomly assigned to intervention (n = 242) or enhanced usual care (EUC; n = 230). Intervention patients had access for up to 12 months to a depression clinical specialist (supervised by a psychiatrist) who offered education, structured psychotherapy, and maintenance/relapse prevention support. The psychiatrist prescribed antidepressant medications for patients preferring or assessed to require medication.

Results

At 12 months, 63% of intervention patients had a 50% or greater reduction in depressive symptoms from baseline as assessed by the Patient Health Questionnaire-9 (PHQ-9) depression scale compared with 50% of EUC patients (odds ratio [OR] = 1.98; 95% CI, 1.16 to 3.38; P = .01). Improvement was also found for 5-point decrease in PHQ-9 score among 72.2% of intervention patients compared with 59.7% of EUC patients (OR = 1.99; 95% CI, 1.14 to 3.50; P = .02). Intervention patients also experienced greater rates of depression treatment (72.3% v 10.4% of EUC patients; P < .0001) and significantly better quality-of-life outcomes, including social/family (adjusted mean difference between groups, 2.7; 95% CI, 1.22 to 4.17; P < .001), emotional (adjusted mean difference, 1.29; 95% CI, 0.26 to 2.22; P = .01), functional (adjusted mean difference, 1.34; 95% CI, 0.08 to 2.59; P = .04), and physical well-being (adjusted mean difference, 2.79; 95% CI, 0.49 to 5.1; P = .02).

Conclusion

ADAPt-C collaborative care is feasible and results in significant reduction in depressive symptoms, improvement in quality of life, and lower pain levels compared with EUC for patients with depressive disorders in a low-income, predominantly Hispanic population in public sector oncology clinics.

INTRODUCTION

Depressive disorders affect up to 38% of patients with cancer,1-3 worsen over the course of cancer treatment,4 persist long after cancer therapy,5 reoccur with the recurrence of cancer,6 and negatively affect quality of life.7-10 Unfortunately, clinicians and patients may perceive depression as an expected reaction to cancer; thus, depression is frequently under-recognized and undertreated in oncology practice.11-20 Two Institute of Medicine reports highlight failure to adequately address depression among cancer patients.21,22 Low-income and uninsured patients with cancer have less access to mental health services.23-25 Unmet treatment preferences,26,27 economic stress, and practical barriers may impede access to depression care as well as contribute to depression.28 However, there is also evidence that underserved populations benefit from quality of care improvement interventions.29-31

A recent analytic review of antidepressant medication (AM) or psychotherapy trials with cancer patients found insufficient data to judge the efficacy of either AM or psychotherapy alone, underscoring a need for studies in which patients are selected on the basis of a diagnosis of major depression and studies that monitor use of multiple therapies.32 We are aware of three preliminary studies of collaborative care among cancer patients; these include a subgroup analysis33 from the Improving Mood-Promoting Access to Collaborative Treatment (IMPACT) trial,34 a trial in Scotland,35 and our pilot trial,36 in which intervention patients had significantly better depression outcomes.

We enrolled 472 depressed patients with cancer from medical oncology clinics in a randomized trial of collaborative care with study recruitment and intervention protocols specifically adapted for low-income, minority patients. We hypothesized that intervention patients would experience significant reductions in depressive symptoms and improvement in quality of life.

PATIENTS AND METHODS

The Los Angeles County and University of Southern California Medical Center provides oncology care to a low-income, predominantly Hispanic population. The study was approved by the University of Southern California-Health Sciences Institutional Review Board. Bilingual study recruiters identified potentially eligible patients by reviewing daily medical oncology clinic charts, assessing patient language preference, and obtaining brief verbal consent to be screened for depressive symptoms. All eligible patients provided written informed consent to study participation. The baseline interview was conducted before random assignment. Patients were assigned to intervention or enhanced usual care (EUC) via the recruiter providing the patient with a choice from five sealed envelopes that contained one sheet of paper indicating a study group randomly determined by computer algorithm. EUC patients received standard oncology care and were given patient/family depression and cancer educational pamphlets and a listing of center/community financial, social services, transportation, and childcare resources. The treating oncologist was informed of patients’ depression status. Treating oncologists attended a depression treatment didactic session by the study psychiatrist at the beginning of the study and yearly thereafter. Oncologists were free to prescribe AMs or to refer patients for any usually available mental health treatment, and patients were free to seek care in the community.

Sample

Patients ≥ 90 days after cancer diagnosis and receiving acute or follow-up care in oncology clinics were eligible for the study if they were ≥ 18 years and had one of the two cardinal depression symptoms more than half of the days to nearly every day plus a Patient Health Questionnaire-9 (PHQ-9) depression scale score of ≥ 10 indicating major depression37-39 and/or two questions from the Structured Clinical Interview for Diagnostic and Statistical Manual of Mental Disorders, 4th Edition40 indicating dysthymia. Patients were excluded for the following reasons: acute suicidal ideation, advanced cancer or other condition that limited remaining life expectancy to less than 6 months, a score of 8 or greater on the Alcohol Use Disorders Identification Test alcohol assessment,41 recently used lithium/antipsychotic medication, a self-reported adaptation of the Karnofsky Performance Status Scale42 score of 2 or less on an 11-point scale representing severe functional impairment in cancer patients, and inability to speak English or Spanish (Fig 1).

Fig 1.
Alleviating Depression Among Patients With Cancer (ADAPt-C) CONSORT flowchart. (*) Declined included patients who declined further study participation or who were no longer living in the United States or receiving care at Los Angeles County and ...

Intervention

The Alleviating Depression Among Patients With Cancer (ADAPt-C) intervention adapted the IMPACT stepped care model,43 including the following key evidence-based components: cancer depression clinical specialists (CDCS; bilingual social workers with master's degrees) provided psychotherapy; community services navigation by the CDCS or a patient navigator under CDCS direction; a psychiatrist who supervised the CDCS and prescribed AMs; a personalized treatment plan that included patient AM or problem-solving therapy (PST) preferences; a structured algorithm for stepped care management and protocol for PST; and CDCS telephone maintenance/relapse prevention and outcomes monitoring over 12 months. The algorithm (based on the IMPACT algorithm for depression in primary care, as well as National Comprehensive Cancer Network44 guidelines for the treatment of depression in cancer patients) was used to ensure that patients received care consistent with their clinical presentations.

The initial CDCS visit(s) included a semistructured psychiatric/psychosocial assessment; patient depression, psychotherapy, and antidepressant education; consideration of initial treatment choice; and provision of patient navigation assistance and included family members at patient request. Subsequent visits provided structured PST45 and/or AM monitoring. A full-time CDCS could manage 35 to 40 patients in active/follow-up care. The psychiatrist held weekly telephone supervision to review the CDCS caseload focusing on new patients and those not improving as expected, provided in-person assessment, conducted in-person evaluation of patients who initially chose AM or did not respond to PST, and prescribed AM and additional psychotropic medications such as an antianxiety agent or sedative-hypnotic, if clinically indicated. A clinical data tracking secure Web site facilitated CDCS and psychiatrist patient care management.

PST that is effective with primary care33 and cancer patients34,46-48 uses behavioral activation components emphasizing patient assessment of personal contextual problems and building self-management skills.49 Weekly sessions ranging from 6 to 12 weeks are highly structured.49 Homework materials were linguistically and idiomatically adapted. Each CDCS received structured training in PST (and the study algorithms), and an independent expert conducted quality assurance structured assessments on five audiotaped patient sessions.37 After acute treatment, patients received a treatment maintenance and relapse prevention program, including CDCS monthly telephone contacts up to 12 months after treatment initiation to monitor symptoms (with additional in-person visits if indicated), behavioral activation support for engaging in pleasant activities, and motivational support for ongoing use of PST skills and medication adherence.50

Data Collection

The PHQ-9 was used as both a screen and outcome measure because it provides a dichotomous diagnosis of major depression as well as a continuous severity score,38,51 measures a common concept of depression across racial and ethnic groups,52 has been used with cancer patients,53 and was believed to be practically feasible and sustainable in real-world oncology clinics. In recent years, the PHQ-9 has emerged as a reliable depression screening tool in primary care, with a demonstrated ability to identify clinically important depression, to make accurate diagnoses of major depression, to track severity of depression over time, and to monitor significant improvement in response to therapy.54-61 Health-related quality of life was assessed using the Functional Assessment of Cancer Therapy–General (FACT-G) scale (a 27-item questionnaire with Spanish translation62,63 and subscale scores for physical, functional, social, and emotional well-being, as well as satisfaction with the treatment relationship) and the Medical Outcomes Study 12-Item Short Form health survey (SF-12)64 Physical and Mental Component Summary norm-based scores. The Brief Pain Inventory Short Form clinically significant cutoff score of ≥ 28 on a scale of 40 indicates severe pain.65,66

Analyses

Baseline demographics, clinical characteristics, depression, and quality-of-life outcomes were compared between EUC and intervention groups by independent t test and analysis of variance for continuous variables and Pearson χ2 test for categoric variables. The intent-to-treat analysis approach was adopted to evaluate intervention effects. To evaluate effects on depression, a 50% reduction of PHQ-9 score or a 5-point reduction was considered a clinically meaningful improvement in depressive symptoms.59 Logistic regression models were conducted. To evaluate intervention effects on PHQ-9 score and quality-of-life outcomes, general linear mixed-effects models implemented in SAS Proc Mixed (SAS Institute Inc, Cary, NC) were fitted with longitudinal data from baseline to 6- and 12-month follow-ups.67,68 Unstructured covariance was specified in the mixed-effects model to account for within-patient correlations of repeated observations over time.68 The fixed effects of time and intervention condition and their interactions were examined. Both logistic regression and linear mixed-effects models were adjusted for baseline depression severity, anxiety, and dysthymia; cancer stage, type, and treatment status; sex; race; and years in the United States. All analyses were conducted using SAS software, version 9.1 (SAS Institute Inc).

In view of known barriers to participation in cancer trials and to depression treatment retention in low-income minority populations, efforts were made to facilitate recruitment and acceptance of the intervention and to minimize study attrition.69 These efforts included the following: Spanish-speaking research staff and study and intervention materials in Spanish that were adapted for literacy and idiomatic content; telephone data collection and intervention option; evening and weekend telephone visits and scheduling depression treatment visits to coincide with oncology appointments; patient navigation/case management intervention to address barriers to both cancer and depression treatment and need for community services; and attention to family member roles. Staff received self-administered brief training in cultural competency.70 Blinded independent study interviewers and the clinical team made multiple attempts to reach patients. Study participants were reimbursed for time in completing outcome interviews and for transportation and copays for AM if indicated.

The rates of mortality and patients lost to follow-up were not significantly different between groups (Fig 1). By 12 months, total attrition had increased to 214 patients (45.3%), with 68 known patient deaths (14.4%), three patients (0.6%) in hospice or palliative care, and 143 patients (30.3%) lost to follow-up (with 62 patients declining further study participation and 81 patients being unable to be located). In the attrition group versus the participant group, there were relatively more non-Hispanics (16.8% v 8.1%, respectively; P = .004), males (20.1% v 11.6%, respectively; P = .01), patients age ≥ 50 years (55.1% v 44.6%, respectively; P = .02), and patients receiving acute cancer treatment (57.5% v 47.3%, respectively; P = .03). Baseline depression and most quality-of-life outcomes were not significantly different between patients lost to the trial versus those who remained in the trial except that attrition patients had poorer baseline physical well-being scores (15.66 v 17.56, respectively; P = .001) and functional well-being scores (10.73 v 11.75, respectively; P = .03). In this article, we present results with all available data. In addition, we also conducted multiple imputations with the predictive model–based approach implemented in SOLAS software, version 3.2 (Statistical Solution Ltd, Saugus, MA, http://www.statsol.ie/html/solas/solas_resources.html). Five imputed data sets were generated, analysis of results across the five imputed data sets were aggregated by averaging, and SEs were adjusted to reflect both within- and between-imputation variability.71,72 Intervention effects on depression and quality-of-life outcomes analyzed with imputed data were consistent with the results analyzed with all available data.

RESULTS

Sample Characteristics

Patient baseline demographic, clinical, and quality-of-life characteristics are listed in Table 1. Patients were predominantly Latino, foreign born, in the United States for 10 years or more, and had not completed high school. Nearly 72% of patients had unstaged or stage I or II cancer, and nearly 50% of patients had comorbid medical conditions. Representation of cancer type was consistent with study site 2006 cancer census data contributing to high representation of women (consistent with national data finding significantly higher rates of depression among women and significantly higher study participation refusal by men; 33.6% of men v 13.5% of women, P < .0001).

Table 1.
Patient Demographic, Clinical, and Quality-of-Life Characteristics at Baseline

Intervention Implementation

Over the course of 12 months, only 24 EUC patients (10.4%) received depression treatment (13 received AM, four received psychotherapy, and seven received both), whereas 72.3% of intervention patients received depression treatment (odds ratio [OR] = 30.88; P < .0001). Patients reported receiving guideline starting dosage, with one patient reporting an increased dosage at 12 months. Seven patients reported having seen a psychiatrist, and of these, four patients also saw a psychologist; five patients saw only a psychologist, and 15 patients saw a social worker. Implementation in the intervention group is summarized in Figure 2. Of 37 intervention patients who received neither PST nor AM at 6 months, 15 received PST (four were also prescribed AM) by 12 months. The CDCS and/or patient navigator made multiple attempts to locate and invite patients to participate up to 1 year after enrollment and to provide/offer patient navigation supportive services, including an offer of in-hospital or telephone depression care to patients with worsening clinical course or hospitalization. Patients self-reported greater satisfaction with PST compared with AM (satisfied to extremely satisfied with PST: 84.4% of 77 respondents at 6 months and 92.3% of 52 respondents at 12 months; and satisfied to extremely satisfied with AM: 40.5% of 37 respondents at 6 months and 42.3% of 26 respondents at 12 months). We estimate the mean cost of the ADAPt-C services to be $524 per intervention patient over 12 months, including costs for the CDCS and patient navigation services, telephone and in-person supervision, evaluation and prescription by the study psychiatrist, and educational brochures and relaxation tapes.

Fig 2.
Treatment implementation. CDCS, cancer depression clinical specialists; AM, antidepressant medication; PST, problem-solving therapy; SD, standard deviation.

Depression Outcomes

Intervention effects on 50% reduction of PHQ-9 scores were evaluated at the 6- and 12-month follow-ups (Table 2). Intervention patients had significantly higher rates of treatment response (at least 50% reduction in the PHQ-9 score from baseline) than EUC patients at 12 months. The percentage of patients with 50% PHQ-9 reduction was 63% in intervention group and 50% in EUC group, with a significant adjusted OR of 1.92 (95% CI, 1.14 to 3.26), indicating 92% greater odds of reaching a 50% reduction among patients in the intervention group than in the EUC group. A significantly greater proportion of patients in the intervention group (72.2%) than in the EUC group (59.7%) achieved a 5-point decrease in PHQ-9 scores at 12 months (adjusted OR = 1.99; 95% CI, 1.14 to 3.50; P = .02). Comparison of the mean PHQ-9 scores between EUC and intervention groups indicated a positive improvement trend with average PHQ-9 scores of 7.34 in the intervention group and 8.14 in the EUC group at 6 months and 6.4 in the intervention group and 7.14 in the EUC group at 12 months. Change in mean PHQ-9 scores across time between groups was borderline significant (P = .06). There were no significant interaction effects between study groups and race, baseline cancer site, cancer stage, or severity of depression on depression outcome improvement.

Table 2.
Comparison of PHQ-9 Outcomes Between Groups

Maintenance of remission and relapse status among 129 intervention patients who completed both the 6- and 12-month interviews found that 50% received PST, 37% received PST and AM, 0.8% received AM alone, and 12% refused treatment or were nonadherent. Of the 114 treated patients, 80 (70%) responded to treatment and no longer had major depression at 6 months. At 12 months, 16 of these patients (14%) had experienced a relapse, 19 (17%) had responded to treatment, and 15 (13%) had not responded to treatment. We are unaware of any attempted or completed suicides in either the intervention or EUC group.

Quality-of-Life Outcomes

Comparing changes across time between groups found significantly greater improvement among intervention patients over time in FACT-G emotional and social well-being and mental components of SF-12 (P < .01). Comparisons of adjusted mean scores between patient groups (Table 3) found that, at 6 months, intervention patients had significantly higher scores on FACT-G physical functioning and functional well-being and the SF-12 mental component. At 12 months, intervention patients had significantly better social/family (adjusted mean difference between scores, 2.7; 95% CI, 1.22 to 4.17; P < .001), emotional (adjusted mean difference, 1.29; 95% CI, 0.26 to 2.32; P = .01), and functional well-being scores (adjusted mean difference, 1.34; 95% CI, 0.108 to 2.59; P = .04) and SF-12 physical component scores (adjusted mean difference, 2.79; 95% CI, 0.49 to 5.1; P = .02). Borderline significant pain reduction was also found (adjusted mean difference, −2.72; 95% CI, −5.44 to 0.01; P = .05). There were no significant interaction effects between study groups and race, baseline cancer site, cancer stage, or severity of depression on quality-of-life outcomes.

Table 3.
Comparison of Depression and Quality-of-Life Outcomes Between Groups

DISCUSSION

To our knowledge, this is the first large-scale trial of collaborative care for predominantly female patients with cancer who met depression diagnostic criteria.32 Study results are responsive to recent calls for improving receipt of depression care among cancer patients21,22 and indicate, in conjunction with other recent studies, that quality of care improvement strategies are effective among low-income and minority populations.29-31 Findings suggest that a collaborative care model adapted for low-income, minority patients results in significant reductions in depressive symptoms and improvements in quality of life, particularly among women without advanced cancers. Improvement in the intervention group is likely attributable to increased access to and choice of treatment, as well as patient navigation services and attention to accessibility within the medical center and via telephone.

Noteworthy is the high rate of patients who indicated a strong preference for PST over AM, a preference consistent with previous studies.33,73 In this trial, the better outcomes of PST alone or in combination with AM raise important questions for future studies about patient treatment adherence, the long-term effects of psychotherapy versus medication or combined care models, and the cost of care, particularly within clinics serving low-income patients.

Not all patients improved, and significant improvement required up to 1 year. An important consideration may be that cancer-related symptoms, including pain, progressive disease over time, and the economic stresses28 associated with the study population, may have contributed to ongoing depressive symptoms. The relatively high rate of improvement in the EUC group may have resulted from enhancements, particularly routine screening, notification of oncologists, and information about site and community psychosocial supportive services.

The rates of death and patients lost to follow-up were high but were not significantly different between the intervention and EUC groups. Moreover, comparison of patients who did and did not remain in the trial found no significant difference in baseline depression severity or quality-of-life outcomes. Known death (we are unable to confirm deaths that may have occurred in other countries), palliative care, and attrition rates were high but were consistent with our previous studies. Perhaps advancing illness influenced patients to leave the area (ie, baseline differences between attrition and nonattrition groups found that patients lost to the trial had poorer baseline physical and functional status).

The ADAPt-C collaborative care model seems to be feasible and significantly more effective than screening and modest care enhancements for depression in a low-income, predominantly Hispanic population in public sector oncology clinics with the potential to reduce disparities in receipt of mental health care among low-income and minority patients. Information on long-term treatment response will be reported in a subsequent article on 18- and 24-month outcomes. There is a need for future multisite collaborative care trials with representation from different racial/ethnic groups and economic strata. There is also need for the implementation of practice guidelines for treating depression in cancer patients.21,22,74

AUTHORS’ DISCLOSURES OF POTENTIAL CONFLICTS OF INTEREST

The author(s) indicated no potential conflicts of interest.

AUTHOR CONTRIBUTIONS

Conception and design: Kathleen Ell, Brenda Quon, Megan Dwight-Johnson

Financial support: Kathleen Ell

Administrative support: Kathleen Ell, Brenda Quon, David I. Quinn, Pey-Jiuan Lee

Provision of study materials or patients: Kathleen Ell, David I. Quinn

Collection and assembly of data: Kathleen Ell, Pey-Jiuan Lee

Data analysis and interpretation: Kathleen Ell, Bin Xie, Pey-Jiuan Lee

Manuscript writing: Kathleen Ell, Bin Xie, Brenda Quon, Megan Dwight-Johnson, Pey-Jiuan Lee

Final approval of manuscript: Kathleen Ell, Bin Xie, Brenda Quon, David I. Quinn, Megan Dwight-Johnson, Pey-Jiuan Lee

Acknowledgments

We acknowledge the contributions of patients, oncologists, and clinic staff. We also acknowledge the contributions of Jürgen Unützer, MD, University of Washington; Patricia Areán, PhD, University of California, San Francisco; and Maria Aranda, PhD, University of Southern California, who provided consultation on the study design, intervention protocols, and cultural adaptations.

Notes

Supported by Grant No. R01CA105269 (K.E.) from the National Cancer Institute, Office of Cancer Survivorship, Bethesda, MD.

Authors’ disclosures of potential conflicts of interest and author contributions are found at the end of this article.

Clinical trial information can be found for the following: NCT00565110.

REFERENCES

1. Honda K, Goodwin RD: Cancer and mental disorders in a national community sample: Findings from the national comorbidity survey. Psychother Psychosom 73:235-242, 2004. [PubMed]
2. Massie MJ: Prevalence of depression in patients with cancer. J Natl Cancer Inst Monogr 32:57-71, 2004. [PubMed]
3. Pirl WF: Evidence report on the occurrence, assessment, and treatment of depression in cancer patients. J Natl Cancer Inst Monogr 32:32-39, 2004. [PubMed]
4. Miovic M, Block S: Psychiatric disorders in advanced cancer. Cancer 110:1665-1676, 2007. [PubMed]
5. Thompson DS, Shear MK: Psychiatric disorders and gynecological oncology: A review of the literature. Gen Hosp Psychiatry 20:241-247, 1998. [PubMed]
6. Okano Y, Okamura H, Watanabe T, et al: Mental adjustment to first recurrence and correlated factors in patients with breast cancer. Breast Cancer Res Treat 67:255-262, 2001. [PubMed]
7. Ahlberg K, Ekman T, Wallgren A, et al: Fatigue, psychological distress, coping and quality of life in patients with uterine cancer. J Adv Nurs 45:205-213, 2004. [PubMed]
8. Brown KW, Levy AR, Rosberger Z, et al: Psychological distress and cancer survival: A follow-up 10 years after diagnosis. Psychosom Med 65:636-643, 2003. [PubMed]
9. Goodwin JS, Zhang DD, Ostir GV: Effect of depression on diagnosis, treatment, and survival of older women with breast cancer. J Am Geriatr Soc 52:106-111, 2004. [PMC free article] [PubMed]
10. Hjerl K, Andersen EW, Keiding N, et al: Depression as a prognostic factor for breast cancer mortality. Psychosomatics 44:24-30, 2003. [PubMed]
11. Gross AF, Smith FA, Stern TA: Is depression an appropriate response to having cancer? A discussion of diagnostic criteria and treatment decisions. Prim Care Companion J Clin Psychiatry 9:382-387, 2007. [PubMed]
12. Passik SD, Dugan W, McDonald MV, et al: Oncologists’ recognition of depression in their patients with cancer. J Clin Oncol 16:1594-1600, 1998. [PubMed]
13. Ashbury FD, Madlensky L, Raich P, et al: Antidepressant prescribing in community cancer care. Support Care Cancer 11:278-285, 2003. [PubMed]
14. Fallowfield L, Ratcliffe D, Jenkins V, et al: Psychiatric morbidity and its recognition by doctors in patients with cancer. Br J Cancer 84:1011-1015, 2001. [PMC free article] [PubMed]
15. McDonald MV, Passik SD, Dugan W, et al: Nurses’ recognition of depression in their patients with cancer. Oncol Nurs Forum 26:593-599, 1999. [PubMed]
16. Newell S, Sanson-Fisher RW, Girgis A, et al: How well do medical oncologists’ perceptions reflect their patients’ reported physical and psychosocial problems? Data from a survey of five oncologists. Cancer 83:1640-1651, 1998. [PubMed]
17. 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 90:314-320, 2004. [PMC free article] [PubMed]
18. Strong V, Sharpe M, Cull A, et al: Can oncology nurses treat depression? A pilot project. J Adv Nurs 46:542-548, 2004. [PubMed]
19. Prieto JM, Atala J, Blanch J, et al: Role of depression as a predictor of mortality among cancer patients after stem-cell transplantation. J Clin Oncol 23:6063-6071, 2005. [PubMed]
20. Jones LE, Doebbeling CC: Suboptimal depression screening following cancer diagnosis. Gen Hosp Psychiatry 29:547-554, 2007. [PubMed]
21. Institute of Medicine: From Cancer Patient to Cancer Survivor: Lost in Transition. Washington, DC, The National Academies Press, 2006.
22. Institute of Medicine: Cancer Care for the Whole Patient: Meeting Psychosocial Health Needs. Washington, DC, The National Academies Press, 2007.
23. Hewitt M, Rowland JH: Mental health service use among adult cancer survivors: Analyses of the National Health Interview Study. J Clin Oncol 20:4581-4590, 2002. [PubMed]
24. Ell K, Sanchez K, Vourlekis B, et al: Depression, receipt of depression care, and correlates of depression among low-income women with breast or gynecological cancer. J Clin Oncol 23:3052-3060, 2005. [PMC free article] [PubMed]
25. Guidry JJ, Adav LA, Zhang D, et al: The role of informal and formal social support networks for patients with cancer. Cancer Pract 5:241-246, 1997. [PubMed]
26. Cooper-Patrick L, Powe NR, Jenckes MW, et al: Identification of patient attitudes and preferences regarding treatment of depression. J Gen Intern Med 12:431-438, 1997. [PMC free article] [PubMed]
27. Dwight-Johnson M, Sherbourne CD, Liao D, et al: Treatment preferences among depressed primary care patients. J Gen Intern Med 15:527-534, 2000. [PMC free article] [PubMed]
28. Ell K, Xie B, Wells A, et al: Economic stress among low-income patients with cancer: Effects on quality of life. Cancer 112:616-625, 2008. [PubMed]
29. Miranda J, Duan N, Sherbourne CD, et al: Improving care for minorities: Can quality improvement intervention improve care and outcomes for depressed minorities? Health Serv Res 38:613-630, 2003. [PMC free article] [PubMed]
30. Miranda J, Chung JY, Green BL, et al: Treating depression in predominantly low-income young minority women: A randomized controlled trial. JAMA 290:57-65, 2003. [PubMed]
31. Areán PA, Gum AM, Tang L, et al: Service use and outcomes among elderly persons with low incomes being treated for depression. Psychiatr Serv 58:1057-1064, 2007. [PubMed]
32. Williams S, Dale J: The effectiveness of treatment for depression/depressive symptoms in adults with cancer: A systematic review. Br J Cancer 94:372-390, 2006. [PMC free article] [PubMed]
33. Unützer J, Katon W, Callahan CM, et al: Collaborative care management of late-life depression in the primary care setting: A randomized controlled trial. JAMA 288:2836-2845, 2002. [PubMed]
34. Unützer J: Depression care in older patients with cancer. Presented at the 49th Annual Meeting of the Academy of Psychosomatic Medicine, Tucson, AZ, November 14, 2002.
35. Sharpe M, Strong V, Allen K, et al: Management of major depression in outpatients attending a cancer centre: A preliminary evaluation of a multi-component cancer nurse delivered intervention needs. Br J Cancer 90:310-313, 2004. [PMC free article] [PubMed]
36. Dwight-Johnson M, Ell K, Jiuan-Lee P: Can collaborative care address the needs of low-income Latinas with comorbid depression and cancer? Results from a randomized pilot study. Psychosomatics 46:224-232, 2005. [PubMed]
37. Spitzer RL, Kroenke K, Williams JB: Validation and utility of a self-report version of PRIME-MD: The PHQ primary care study—Primary Care Evaluation of Mental Disorders, Patient Health Questionnaire. JAMA 282:1737-1744, 1999. [PubMed]
38. Kroenke K, Spitzer RL, Williams JB: The PHQ-9: Validity of a brief depression severity measure. J Gen Intern Med 16:606-613, 2001. [PMC free article] [PubMed]
39. Cannon DS, Tiffany ST, Coon H, et al: The PHQ-9 as a brief assessment of lifetime major depression. Psychol Assess 19:247-251, 2007. [PubMed]
40. First MB, Spitzer RL, Gibbon M, et al: Structured Clinical Interview for DSM-IV Axis 1 Disorders (SCID). Washington, DC, American Psychiatric Press Inc, 1996.
41. Vinson DC, Galliher JM, Reidinger C, et al: Comfortably engaging: Which approach to alcohol screening should we use? Ann Fam Med 2:398-404, 2004. [PubMed]
42. Mor V, Laliberte L, Morris JN, et al: The Karnofsky Performance Status Scale: An examination of its reliability and validity in a research setting. Cancer 53:2002-2007, 1984. [PubMed]
43. Ell K, Quon B, Quinn D, et al: Improving treatment of depression among low-income patients with cancer: The design of the ADAPt-C study. Gen Hosp Psychiatry 29:223-231, 2007. [PMC free article] [PubMed]
44. National Comprehensive Cancer Network: Clinical practice guidelines in oncology: Distress management assessment tool. http://www.nccn.org/professionals/physician_gls/default.asp.
45. Nezu A, Nezu C, Houts P, et al: Cancer and psychological distress: Two investigations regarding the role of social problem-solving. J Psychosoc Oncol 16:27-40, 1999.
46. Allen SM, Shah AC, Nezu AM, et al: A problem-solving approach to stress reduction among younger women with breast carcinoma: A randomized controlled trial. Cancer 94:3089-3100, 2002. [PubMed]
47. Nezu AM, Nezu CM, Houts PS, et al: Relevance of problem-solving therapy to psychosocial oncology. J Psychosoc Oncol 16:5-26, 1999.
48. Nezu A, Nezu C, Perri MG: Problem-Solving Therapy for Depression: Theory, Research and Clinical Guidelines. New York, NY, Wiley, 1989.
49. Nezu A, Nezu CM, Friedman SH, et al: A Problem-Solving Approach: Helping Cancer Patients Cope. Washington, DC, American Psychological Association, 1998.
50. Katon W, Rutter C, Ludman E, et al: A randomized trial of relapse prevention of depression in primary care. Arch Gen Psychiatry 58:241-247, 2001. [PubMed]
51. Löwe B, Spitzer RL, Gräfe K, et al: Comparative validity of three screening questionnaires for DSM-IV depressive disorders and physicians’ diagnoses. J Affect Disord 78:131-140, 2004. [PubMed]
52. Huang FY, Chung H, Kroenke K, et al: Using the Patient Health Questionnaire-9 to measure depression among racially and ethnically diverse primary care patients. J Gen Intern Med 21:547-552, 2006. [PMC free article] [PubMed]
53. Leopold KA, Ahles TA, Walch S, et al: Prevalence of mood disorders and utility of the Prime-MD in patients undergoing radiation therapy. Int J Radiat Oncol Biol Phys 42:1105-1112, 1998. [PubMed]
54. Löwe B, Kroenke K, Herzog W, et al: Measuring depression outcome with a brief self-report instrument: Sensitivity to change of the Patient Health Questionnaire (PHQ-9). J Affect Disord 81:61-66, 2004. [PubMed]
55. Löwe B, Gräfe K, Zipfel S, et al: Diagnosing ICD-10 depressive episodes: Superior criterion validity of the Patient Health Questionnaire. Psychother Psychosom 73:386-390, 2005. [PubMed]
56. Löwe B, Unützer J, Callahan CM, et al: Monitoring depression treatment outcomes with the PHQ-9. Med Care 42:1194-1201, 2004. [PubMed]
57. Wittkampf KA, Naeije L, Schene AH, et al: Diagnostic accuracy of the mood module of the Patient Health Questionnaire: A systematic review. Gen Hosp Psychiatry 29:388-395, 2007. [PubMed]
58. Lee PW, Schulberg HC, Raue PJ, et al: Concordance between the PHQ-9 and the HSCL-20 in depressed primary care patients. J Affect Disord 99:139-145, 2007. [PubMed]
59. Löwe B, Schenkel I, Carney-Doebbeling C, et al: Responsiveness of the PHQ-9 to psychopharmacological depression treatment. Psychosomatics 47:62-67, 2006. [PubMed]
60. Simon GE, Ludman EJ, Tutty S, et al: Telephone psychotherapy and telephone care management for primary care patients starting antidepressant treatment: A randomized controlled trial. JAMA 292:935-942, 2004. [PubMed]
61. Cameron IM, Crawford JR, Lawton K, et al: Psychometric comparison of PHQ-9 and HADS for measuring depression severity in primary care. Br J Gen Pract 58:32-36, 2008. [PMC free article] [PubMed]
62. Cella D, Hernandez L, Bonomi AE, et al: Spanish language translation and initial validation of the Functional Assessment of Cancer Therapy Quality-of-Life Instrument. Med Care 36:1407-1418, 1998. [PubMed]
63. Cella DF, Tulsky DS, Gray G, et al: The Functional Assessment of Cancer Therapy Scale: Development and validation of the general measure. J Clin Oncol 11:570-579, 1993. [PubMed]
64. Ware JE, Sherbourne CD: The MOS-36 item short-form health survey (SF-36). Med Care 30:473-483, 1992. [PubMed]
65. Cleeland CS: Measurement of pain by subjective report, in Chapman CR, Loeser JD (eds): Issues in Pain Mean Measurement. New York, NY, Raven Press, 1989, pp 391-403.
66. Cleeland CS: Pain assessment in cancer, in Osaba D (ed): Effect of Cancer on Quality of Life. Boca Raton, FL, CRC Press, 1991, pp 293-305.
67. Littell RC, Milliken GA, Stoup WW, et al: SAS System for Mixed Models. Cary, NC, SAS Institute Inc, 1996.
68. Fitzmaurice GM, Laird NM, Ware JH: Applied Longitudinal Analysis. Hoboken, NJ, John Wiley & Sons, Inc, 2004.
69. Skaff MM, Chesla CA, Mycue VS, et al: Lessons in cultural competence: Adapting research methodology for Latino participants. J Commun Psychol 30:305-323, 2002.
70. Ell K, Vourlekis B, Lee PJ, et al: Patient navigation and case management following an abnormal cancer screen: A randomized clinical trial. Prev Med 44:26-33, 2007. [PubMed]
71. Little RJ: Regression with missing X's: A review. J Am Stat Assoc 87:1227-1237, 1992.
72. Rubin DB: Multiple Imputation for Nonresponse in Surveys. New York, NY, John Wiley & Sons, 1987.
73. Areán PA, Unützer J: Inequities in depression management in low-income, minority, and old-old adults: A matter of access to preferred treatments? J Am Geriatr Soc 51:1808-1809, 2003. [PubMed]
74. Rodin G, Katz M, Lloyd N, et al: Treatment of depression in cancer patients. Curr Oncol 14:180-188, 2007. [PMC free article] [PubMed]

Articles from Journal of Clinical Oncology are provided here courtesy of American Society of Clinical Oncology