Niazi, Shehzad K.

Abstract Background: Cancer diagnosis and treatment are important risk factors for developing clinical depression. Validated tools for screening distress and depression, such as Cancer Distress Thermometer (DT) and PHQ9 (Patient Health Questionnaire), are underutilized, despite endorsement by NCCN and Institute of Medicine. We investigated patient and treatment characteristics as well as patient endorsement of depression or anhedonia to predict those at risk of having depression. Methods: The PHQ9 and/or DT were administered prospectively to patients with hematologic malignancies (HM) before they started antineoplastic therapy at Mayo Clinic in Florida. Patient endorsement of depression or anhedonia was collected from the current visit information survey. Patient demographics, disease and treatment characteristics, chronic medication burden, Charlson comorbidity index, living situation, clinic/hospital visit burden in the month prior to screening and number of psychiatric medications for every patient were recorded. Intergroup comparison of categorical and continuous variables was done by Chi-square and Wilcoxon rank-sum tests, respectively. Linear or logistic regression models were used to compare PHQ9 score with DT (continuous) or endorsing depression or anhedonia (categorical) respectively. Multivariate models were constructed using the stepwise selection technique using all potential variables in the models. All analyses were completed using SAS v9.3. Results: Final analysis included 246 patients with a median age at diagnosis 64.5 (range: 18-94) years, diagnosed between 6/30/93-10/9/14 and screened between 1/13/11-2/13/15. PHQ9 score of ≥9 and DT score ≥5 suggested a high risk of depression and distress, respectively, as per published literature. Patient characteristics at time of survey and analysis are noted in table 1. PHQ9, DT and answers to two questions about depression and anhedonia were available on 129, 129 and 246 patients, respectively. 63% of patients were chemotherapy naïve. In multivariate analysis, PHQ9 score ≥9 was associated with living alone (p=0.003) (Fig.1a) and non-White race (p=0.043) (Fig.1b), while a DT score ≥5 was associated with being currently married (p=0.048) and female gender (p=0.02). The only characteristic significant on univariate but not on multivariate analysis being chemotherapy naive, associated with a DT score ≥5 (p=0.049). Answering "no" to both the questions regarding depression or anhedonia was significantly associated with a low score on PHQ9 (p=0.007). Age at diagnosis, Charlson comorbidity score, chronic medication or visit burden, daily psychiatric medication use or type of malignancy were not associated with scores on any screen. Conclusions: Causes of depression in patients with HM have not been fully explored. We validated previously known risk factors for depression, such as living alone. We also reported for the first time that non-White race independently predicts depression in these patients. Female patients and those currently married are at a higher risk of psychological distress, possibly due to fear of abandoning family. We also found that simply asking a patient two questions about feelings of depression or anhedonia significantly correlates with the well-established PHQ9. Our analysis provides simple tools and reveals at-risk patient subgroups with HM where depression and distress screening should be aggressively instituted for better resource utilization and survivorship. Table 1. Patient Characteristic N % Gender Male Female 146 100 59.4 40.6 Race White Non-White 216 30 87.8 12.2 Marital Status Married Not married* 180 66 73.2 26.8 Living Situation Alone With others 37 209 15 85 Type of Malignancy Aggressive lymphoid Indolent lymphoid Aggressive myeloid Indolent myeloid 124 94 25 3 50.4 38.2 10.2 1.2 Prior Cancer Treatment Yes No 91 155 37 63 Daily Psych Meds Yes No 52 194 21.1 78.9 Patient Status Alive Dead 191 55 77.6 22.4 *Not currently married=single, divorced, widowed or unknown Disclosures No relevant conflicts of interest to declare.

Abstract Background: Cost of cancer care is projected to reach $173 billion by 2020, a 39% increase from 2010. Several factors including psychiatric (psych) comorbidities contribute to this increase. Within the oncology setting, 29-38% of the patients (pts) are reported to have mood disorders and 15% have major depression. Depression alone is associated with increased healthcare utilization in pts with breast, colon, lung and prostate cancers. A 2015 report noted that the presence of at least one psychiatric comorbidity in 300 Leukemia pts was associated with an extra $55,000 per pt in just one year. Similarly, in pts treated with systemic steroids, the incidence of neuropsychiatric disorders can be as high as 75%. However, no such data is available for MM, where more than 90% of pts are treated with steroids, likely increasing risk for mood problems and impacting treatment cost. As such, the aim of our study was to analyze the SEER-Medicare database for healthcare utilization trends and acute cost of care (cost incurred during 6 months after MM diagnosis) in MM pts with or without psych comorbidities. Methods: Pts diagnosed with MM between 1991-2010 with continuous Medicare coverage (1 year prior to diagnosis-date of death/end of 2012) were included. Pts were categorized as: MM with any psych disorder (MM+P), MM with depression (MM+D) and MM only. Presence of ³1 inpatient (ipt) or ³2 outpatient (opt) ICD9 diagnosis codes were used to assign pts to the psych categories. Within MM+P and MM+D groups were subdivided by presence of psych or depression diagnosis prior to MM (MM+P PRE or MM+D PRE). Medicare claims adjusted for inflation (2013) within the first 6 months (mth)/total MM care were summed by drug and total charges. Univariate and multivariate logistic regression models (adjusted for age, year, sex, race, and the Charlson Comorbidity Index; CCI) were performed to determine associations with ipt, opt, and any emergency department (ED) charges after MM diagnosis. Associations between psych conditions prior to MM diagnosis and costs of care after MM diagnosis were assessed using univariate and multivariate proportional odds models. Results: The study population included 36,007 eligible MM pts with a median follow-up of 1.8 years. 15168 (42%) pts had a psych condition at any time (MM+P), while 9355 (26%) were diagnosed prior to MM diagnosis (MM+P PRE). Depression was present in 8421 pts (23%), 4546 (13%) of those occurring prior to MM diagnosis. In comparison to MM pts, MM+P and MM+D pts tended to be female, White, and had a higher CCI (all p<0.001). When compared to MM pts, those with MM+P PRE and MM+D PRE had significantly higher incidence of MM-related complications (hypercalcemia, renal dysfunction, anemia, fractures and dialysis) at the time of or after MM diagnosis and also required increased overall care (all p<0.001). Both, MM+P and MM+D had higher odds of ipt visits (OR 1.48 and 1.41, resp., p<0.001), ED care (OR 1.48 and 1.37, resp., p<0.001) and opt visits (OR 1.25 and 1.22, resp., p<0.001) as compared to MM only pts. Cost of care analysis showed that MM+P and MM+D pts had a significantly higher cost of opt (OR 1.36 and 1.39, resp., p<0.001), ipt (OR 1.49 and 1.54, resp., p<0.001) and total care (OR 1.52 and 1.55, resp., p<0.001) as compared to MM only pts during first 6 mth after MM diagnosis (Figure 1). Total costs of care for MM+P and MM+D were also higher than MM only but the differences were less significant. Cost of care differences existed within first 6 mth of MM diagnosis by pt race as well with MM+P among Hispanic and Asian pts being more strongly associated with higher costs than Whites and African-Americans (AA) (p<0.001). MM+D had similar trends but not significant after adjustment for multiple comparisons. Conclusion: Psych comorbidities are associated with significant increase in healthcare utilization and cost of care in MM pts and may contribute to higher MM-related complications. More research is needed to study whether a multidisciplinary approach to identify and manage MM pts with psych conditions may help mitigate these trends. Disclosures Ailawadhi: Pharmacyclics: Consultancy; Novartis: Consultancy; Amgen Inc: Consultancy; Takeda Oncology: Consultancy.

AbstractRational, aims, and objectivesUnderstanding of barriers and successes associated with the implementation of electronic patient self‐reported measures (ePSRMs) within clinical settings are limited and have not been pursued utilizing implementation science frameworks. This qualitative study is designed to assess staff perceptions of an ePSRM implementation.MethodsThe study took place in an academic hospital's Consultation Liaison Psychiatry practice. Qualitative interviews were conducted with the staff and clinicians from the practice. Participants were directly involved with the implementation and use of the ePSRM system within the Psychiatry practice. Interviews were structured around the Reach, Effectiveness, Adoption, Implementation, Maintenance (RE‐AIM) framework.ResultsParticipants reported increased patient engagement as well as efficiency and time savings. The intervention was perceived to be more challenging for older patients. Facilitators include communicating the ePSRM to patients prior to the care visit, having enough trained staff or super‐users who can assist with technical problems, and having a shorter questionnaire.ConclusionsOverall, assessment of the ePSRM implementation was positive. Staff and clinicians indicated benefits in time, effectiveness, and improvements in patient treatment. Results indicate that defining how the system would fit within the clinical workflow was key, as was a flexible and user‐friendly technology platform. The ePSRM implementation was dependent upon clinical involvement and interest in adoption, while barriers were associated with technical challenges as well as some patient difficulties, such as cognitive impairment. The use of the RE‐AIM framework is valuable as it allows for systematic assessment of the implementation and identifies areas in that implementation has succeeded or is lacking.

Key PointsCoexisting psychiatric comorbidities are associated with greater increased health care utilization and cost of care in patients with MM. Clinical complications of MM are seen more frequently in patients with coexisting psychiatric conditions.

232 Background: Screening for distress in cancer patients (pts) is recommended by several national guidelines. High distress scores are associated with increased depression. We established universal depression screening and investigated its impact on cancer patient management. Methods: Patient Health Questionnaire (PHQ9) was administered to newly diagnosed cancer patients prior to receiving their first non-oral antineoplastic agent. Patient demographics, disease characteristics, chronic medication load, antidepressant use, treatment interruptions, weight change, referral and adherence to psychiatry were recorded. Pts with high (> 9) and low (< 4) PHQ9 scores were compared using Chi-square and Wilcoxon rank-sum tests. Results: Screening was performed in 1,190 consecutive pts over an 18 month period at Mayo Clinic. Responses were received from 1055 (89%) pts, of which 144 had high score (PHQ-H). These were compared with 99 randomly selected low score (PHQ-L) pts. The 243 pts (median age 65; range 18-92 years) in the final analysis included: 53.5% females, 90% Caucasians, 74% married and 77% living with others. Diagnosis was solid organ cancer in 81% and metastatic disease in 54% patients, and 13% were on antidepressants for preexisting depression. PHQ-H were more likely to be on antidepressants than PHQ-L (19% vs. 3%; p = 0.0002), be referred to psychiatry (69% vs. 12%; p < 0.0001), attend psychiatry appointment (45% vs. 12%; p < 0.0001) and require behavioral therapy (50% vs 8%; p = 0.0065). PHQ-H did not have a significantly increased antidepressant use, treatment interruptions (p = 0.5) or weight change (p = 0.4). Race, gender, chronic medication load, marital status, living situation, metastatic disease and type of cancer were not significantly different between PHQ-H and PHQ-L. Conclusions: We implemented a universal depression screening and management plan for cancer pts and noted that previously being on antidepressants was associated with higher patient distress. Higher score led to more frequent behavioral therapy, possibly preventing non-compliance or need for increased psychotropic medications. Our model identifies cancer pts with depression and implements an effective management plan for their care.