Two-step screening for depressive symptoms in patients treated with kidney replacement therapies: a cross-sectional analysis.

BACKGROUND: Systematic screening for depressive symptoms may identify patients who may benefit from clinical assessment and psychosocial support. Here we assess a two-step screening using ultrabrief pre-screeners [Edmonton Symptom Assessment Survey-revised Depression item (ESASr-D) or Patient Health Questionnaire-2 (PHQ-2)] followed by the Patient-Reported Outcomes Measurement Information System Depression questionnaire (PROMIS-D) to identify depressive symptoms in patients on kidney replacement therapies. METHODS: We conducted a cross-sectional study of adults (kidney transplant recipients or treated with dialysis) in Toronto, ON, Canada. We simulated various two-step screening scenarios where only patients above a pre-screening cut-off score on the ESASr-D or PHQ-2 would move to step 2 (PROMIS-D). Screening performance was evaluated by sensitivity, specificity and positive and negative predictive values using the Patient Health Questionnaire-9 (PHQ-9) as the referent. The average number of items completed by patients in different scenarios was reported. RESULTS: Of 480 participants, 60% were male with a mean age of 55 years. Based on PHQ-9, 19% of patients had moderate or severe depressive symptoms. Pre-screening with a PHQ-2 score ≥1 combined with a PROMIS-D score of ≥53 provided the best two-step results (sensitivity 0.81, specificity 0.84, NPV 0.95). Two-step screening also reduces question burden. CONCLUSIONS: A two-step screening using a PHQ-2 score ≥1 followed by a PROMIS-D score ≥53 has good sensitivity and specificity for identifying potentially significant depressive symptoms among patients on kidney replacement therapies. This approach has lower question burden. Screened-in patients will need further clinical assessment to establish a diagnosis.

Phase I trial of pembrolizumab plus vemurafenib and cobimetinib in patients with metastatic melanoma.

Background: Preclinical and translational evidence suggest BRAF/MEK inhibitors modulate the tumor microenvironment (TME), providing rationale for combination with immunotherapy. Methods: This investigator-initiated, phase I trial evaluated pembrolizumab, vemurafenib, and cobimetinib in patients with untreated, BRAFV600E/K mutant advanced melanoma. The first 4 patients received vemurafenib with pembrolizumab, and the next 5 patients received vemurafenib and cobimetinib with pembrolizumab. Primary endpoints: safety and maximum tolerated dose of the triplet. Secondary endpoints: objective response rate (ORR), progression-free survival (PFS), overall survival (OS), and quality of life (QoL). The trial was closed after enrollment of 9 (planned 30) patients due to dose-limiting toxicity (DLT). Study NCT02818023 was approved by the IRB, and all patients provided informed consent. Results: Patients received a median of 6 cycles of therapy. 8 of 9 experienced drug-related grade 3/4 AEs. DLTs included dermatitis (n=8), hepatitis (n=1), QTc prolongation (n=1), and arthralgias (n=1 each). QoL assessments identified a clinically significant decrease in self assessed QoL at 1 year compared to baseline (0.38 v 0.43). Median PFS was 20.7 months and median OS was 23.8 months for vemurafenib with pembrolizumab. Median PFS and OS were not reached for patients receiving triple therapy. ORR in the overall cohort was 78% (7/9). 2 patients experienced a complete response, 5 had a partial response, 1 had stable disease, and 1 had progressive disease. 4 patients had ongoing responses at data analysis. Peripheral blood flow cytometry identified significantly decreased PD1 expression on CD4+ T-cells at 3 and 9 weeks compared to baseline, not corresponding to clinical response. Conclusions: Triple therapy with vemurafenib, cobimetinib and pembrolizumab is associated with high response rates but significant adverse events, leading to early study closure.

Do patients want clinicians to ask about social needs and include this information in their medical record?

BACKGROUND: Social needs screening in primary care may be valuable for addressing non-medical health-related factors, such as housing insecurity, that interfere with optimal medical care. Yet it is unclear if patients welcome such screening and how comfortable they are having this information included in electronic health records (EHR). OBJECTIVE: To assess patient attitudes toward inclusion of social needs information in the EHR and key correlates, such as sociodemographic status, self-rated health, and trust in health care. DESIGN, PARTICIPANTS, AND MAIN MEASURES: In a cross-sectional survey of patients attending a primary care clinic for annual or employment exams, 218/560 (38%) consented and completed a web survey or personal interview between 8/20/20-8/23/21. Patients provided social needs information using the Accountable Care Communities Screening Tool. For the primary outcome, patients were asked, "Would you be comfortable having these kinds of needs included in your health record (also known as your medical record or chart)?" ANALYSES: Regression models were estimated to assess correlates of patient comfort with including social needs information in medical records. KEY RESULTS: The median age was 45, 68.8% were female, and 78% were white. Median income was $75,000 and 84% reported education beyond high school. 85% of patients reported they were very or somewhat comfortable with questions about social needs, including patients reporting social needs. Social need ranged from 5.5% (utilities) to 26.6% (housing), and nonwhite and gender-nonconforming patients reported greater need. 20% reported "some" or "complete" discomfort with social needs information included in the EHR. Adjusting for age, gender, race, education, trust, and self-rated health, each additional reported social need significantly increased discomfort with the EHR for documenting social needs. CONCLUSIONS: People with greater social needs were more wary of having this information placed in the EHR. This is a concerning finding, since one rationale for collecting social need data is to use this information (presumably in the EHR) for addressing needs.

The diagnosis of asymptomatic disease is associated with fewer healthy days: A cross sectional analysis from the national health and nutrition examination survey.

OBJECTIVE: To examine the effect of the diagnosis of asymptomatic disease on health-related quality of life (HRQoL). DESIGN: Secondary analysis of a national data set. METHOD: We analysed adult participants in the 2011-2012 National Health and Nutrition Examination Survey (NHANES) of the civilian non-institutionalized US general population. Across three asymptomatic diseases (glucose intolerance, hyperlipidaemia, and hypertension), we examined four groups (without disease; with disease but no diagnosis; with disease and diagnosis but no treatment; and with disease, diagnosis, and treatment). For each asymptomatic disease, we examined group differences in self-rated health (ordinal logistic regression) and Healthy Days outcomes (number of the last 30 days that physical health was not good, mental health was not good, or inactive; regression). Models were adjusted for age, sex, smoking status, insurance status, income, education, race, body mass index, and comorbid conditions. RESULTS: Analyses included 6012 respondents (glucose intolerance), 2772 respondents (hyperlipidaemia), and 5524 respondents (hypertension). In adjusted models, those who did not know about their disease had the same self-rated health scores as those without the disease, those with the disease without treatment, and those with disease and treatment. In adjusted analyses of the Healthy Days questions, those with unknown disease reported the same number of unhealthy days as those without disease with the exception of glucose intolerance. Conversely, in four of the nine possible comparisons, those with known disease without treatment reported more unhealthy days than those with who did not know about their disease. CONCLUSIONS: In adjusted analyses, individuals knowing about their asymptomatic disease are more likely to experience decrements in healthy days compared to those without knowledge of their asymptomatic disease. Statement of contribution What is already known on this subject? There has been sparse evidence that diagnosis of asymptomatic diseases is related to reduced health-related quality of life in population studies. Previous studies have included patients receiving treatment, which impedes the ability to isolate the effects of diagnosis from the effects of treatment. What does this study add? This report examines three asymptomatic health conditions: glucose intolerance, hyperlipidaemia, and hypertension. Those who did not know about their health condition generally had the same health-related quality of life scores as those without health conditions. Conversely, those diagnosed with disease but not receiving treatment reported worse health-related quality of life.

Association Between Palliative Care and Patient and Caregiver Outcomes: A Systematic Review and Meta-analysis.

Importance: The use of palliative care programs and the number of trials assessing their effectiveness have increased. Objective: To determine the association of palliative care with quality of life (QOL), symptom burden, survival, and other outcomes for people with life-limiting illness and for their caregivers. Data Sources: MEDLINE, EMBASE, CINAHL, and Cochrane CENTRAL to July 2016. Study Selection: Randomized clinical trials of palliative care interventions in adults with life-limiting illness. Data Extraction and Synthesis: Two reviewers independently extracted data. Narrative synthesis was conducted for all trials. Quality of life, symptom burden, and survival were analyzed using random-effects meta-analysis, with estimates of QOL translated to units of the Functional Assessment of Chronic Illness Therapy-palliative care scale (FACIT-Pal) instrument (range, 0-184 [worst-best]; minimal clinically important difference [MCID], 9 points); and symptom burden translated to the Edmonton Symptom Assessment Scale (ESAS) (range, 0-90 [best-worst]; MCID, 5.7 points). Main Outcomes and Measures: Quality of life, symptom burden, survival, mood, advance care planning, site of death, health care satisfaction, resource utilization, and health care expenditures. Results: Forty-three RCTs provided data on 12 731 patients (mean age, 67 years) and 2479 caregivers. Thirty-five trials used usual care as the control, and 14 took place in the ambulatory setting. In the meta-analysis, palliative care was associated with statistically and clinically significant improvements in patient QOL at the 1- to 3-month follow-up (standardized mean difference, 0.46; 95% CI, 0.08 to 0.83; FACIT-Pal mean difference, 11.36] and symptom burden at the 1- to 3-month follow-up (standardized mean difference, -0.66; 95% CI, -1.25 to -0.07; ESAS mean difference, -10.30). When analyses were limited to trials at low risk of bias (n = 5), the association between palliative care and QOL was attenuated but remained statistically significant (standardized mean difference, 0.20; 95% CI, 0.06 to 0.34; FACIT-Pal mean difference, 4.94), whereas the association with symptom burden was not statistically significant (standardized mean difference, -0.21; 95% CI, -0.42 to 0.00; ESAS mean difference, -3.28). There was no association between palliative care and survival (hazard ratio, 0.90; 95% CI, 0.69 to 1.17). Palliative care was associated consistently with improvements in advance care planning, patient and caregiver satisfaction, and lower health care utilization. Evidence of associations with other outcomes was mixed. Conclusions and Relevance: In this meta-analysis, palliative care interventions were associated with improvements in patient QOL and symptom burden. Findings for caregiver outcomes were inconsistent. However, many associations were no longer significant when limited to trials at low risk of bias, and there was no significant association between palliative care and survival.

Chronic Conditions and Utility-Based Health-Related Quality of Life in Adult Childhood Cancer Survivors.

Health utility, a summary measure of quality of life, has not been previously used to compare outcomes among childhood cancer survivors and individuals without a cancer history. We estimated health utility (0, death; 1, perfect health) using the Short Form-6D (SF-6D) in survivors (n = 7105) and siblings of survivors (n = 372) (using the Childhood Cancer Survivor Study cohort) and the general population (n = 12 803) (using the Medical Expenditures Panel Survey). Survivors had statistically significantly lower SF-6D scores than the general population (mean = 0.769, 95% confidence interval [CI] = 0.766 to 0.771, vs mean = 0.809, 95% CI = 0.806 to 0.813, respectively, ITALIC! P< .001, two-sided). Young adult survivors (age 18-29 years) reported scores comparable with general population estimates for people age 40 to 49 years. Among survivors, SF-6D scores were largely determined by number and severity of chronic conditions. No clinically meaningful differences were identified between siblings and the general population (mean = 0.793, 95% CI = 0.782 to 0.805, vs mean = 0.809, 95% CI = 0.806 to 0.813, respectively). This analysis illustrates the importance of chronic conditions on long-term survivor quality of life and provides encouraging results on sibling well-being. Preference-based utilities are informative tools for outcomes research in cancer survivors.

Health Care Use, Health Behaviors, and Medical Conditions Among Individuals in Same-Sex and Opposite-Sex Partnerships: A Cross-Sectional Observational Analysis of the Medical Expenditures Panel Survey (MEPS), 2003-2011.

BACKGROUND: Prior research documents disparities between sexual minority and nonsexual minority individuals regarding health behaviors and health services utilization. However, little is known regarding differences in the prevalence of medical conditions. OBJECTIVES: To examine associations between sexual minority status and medical conditions. RESEARCH DESIGN: We conducted multiple logistic regression analyses of the Medical Expenditure Panel Survey (2003-2011). We identified individuals who reported being partnered with an individual of the same sex, and constructed a matched cohort of individuals in opposite-sex partnerships. SUBJECTS: A total of 494 individuals in same-sex partnerships and 494 individuals in opposite-sex partnerships. MEASURES: Measures of health risk (eg, smoking status), health services utilization (eg, physician office visits), and presence of 15 medical conditions (eg, cancer, diabetes, arthritis, HIV, alcohol disorders). RESULTS: Same-sex partnered men had nearly 4 times the odds of reporting a mood disorder than did opposite-sex partnered men [adjusted odds ratio (aOR)=3.96; 95% confidence interval (CI), 1.85-8.48]. Compared with opposite-sex partnered women, same-sex partnered women had greater odds of heart disease (aOR=2.59; 95% CI, 1.19-5.62), diabetes (aOR=2.75; 95% CI, 1.10-6.90), obesity (aOR=1.92; 95% CI, 1.26-2.94), high cholesterol (aOR=1.89; 95% CI, 1.03-3.50), and asthma (aOR=1.90; 95% CI, 1.02-1.19). Even after adjusting for sociodemographics, health risk behaviors, and health conditions, individuals in same-sex partnerships had 67% increased odds of past-year emergency department utilization and 51% greater odds of ≥3 physician visits in the last year compared with opposite-sex partnered individuals. CONCLUSIONS: A combination of individual-level, provider-level, and system-level approaches are needed to reduce disparities in medical conditions and health care utilization among sexual minority individuals.

Relative disutilities of 47 risk factors and conditions assessed with seven preference-based health status measures in a national U.S. sample: toward consistency in cost-effectiveness analyses.

BACKGROUND: Preference-based health measures yield summary scores that are compatible with cost-effectiveness analyses. There is limited comparative information, however, about how different measures weight health conditions in the U.S. population. METHODS: We examined data from 11,421 adults in the 2000 Medical Expenditure Panel Survey, a nationally representative sample of the U.S. general population, using information on sociodemographics (age, gender, race/ethnicity, income, and education), health status (EQ-5D, EQ-VAS, and SF-12), 4 risk factors (smoking, overweight, obesity, and lacking health insurance), and 43 conditions. From the EQ-5D, we derived summary scores using U.K. [EQ(UK)] and U.S. weights. From the SF-12 we derived SF-6D, and regression-predicted EQ-5D (U.S. and U.K. weights) and Health Utility Index scores. Each of the 7 preference measures was regressed on each of the 47 problems (risk factors and conditions) to determine the disutility associated with the problem, adjusting for socio-demographics. RESULTS: The adjusted disutilities averaged across the 47 problems for the 7 preference measures ranged from 0.059 for the SF-6D to 0.104 for the EQ(UK). Correlations between each of the measures of the adjusted disutilities ranged from 0.85-1.0. Standardization, using linear regression, attenuated between measure differences in disutilities. CONCLUSIONS: Absolute incremental cost-effectiveness analyses of a given problem would likely vary depending on the measure used, whereas the relative ordering of incremental cost-effectiveness analyses of a series of problems would likely be similar regardless of the measure chosen, as long as the same measure is used in each series of analyses. Absolute consistency across measures may be enhanced by standardization.