Using qualitative exit interviews to explore schizophrenia burden and treatment experience in clinical trial patients

IntroductionQualitative research methods can be used to obtain a deeper understanding of patient experience by collecting information in the patients’ own words about their encounters, perspectives, and feelings. In this study, patients with schizophrenia were interviewed to capture their voice and to complement the quantitative data typically obtained in clinical trials.MethodsSemi-structured exit interviews were conducted with 41 patients who completed or prematurely discontinued from a phase 3, open-label trial (NCT02873208). The interview guide included open-ended questions on current and prior disease burden, symptoms, quality of life, and treatment experiences. Steps taken to reduce interview stress and secure the validity of data included interviewer sensitivity training specific to mental health conditions and schizophrenia, use of in-person interviews whenever possible and use of videoconferencing for remote interviews to promote trust and comfort, and working closely with clinical site staff to identify patient eligibility and willingness to participate. Transcripts based on audio recordings were content coded and analyzed using thematic analysis; a post-hoc quantitative content analysis was conducted.ResultsPatients reported that the symptoms of schizophrenia negatively impacted their work, relationships, self-esteem, emotional health, and daily activities. Most patients had positive experiences with medications that alleviated hallucinations, depression, and anxiety. However, side effects of medications were associated with negative impacts on physical, emotional, behavioral, and cognitive health. Lack of energy/drowsiness, weight gain, mood changes, and involuntary movements were the most common side effects reported with the use of antipsychotic medications. Patients reported unmet treatment needs related to better symptom control and to improved social and physical functioning.ConclusionCollection of qualitative information within a schizophrenia clinical development process provides value and insights into patients’ views on burden of illness, experiences with previous medications, and experiences following participation in a clinical trial and can inform design for future studies

Secondary findings from clinical genomic sequencing: prevalence, patient perspectives, family history assessment, and health-care costs from a multisite study

Purpose Clinical sequencing emerging in health care may result in secondary findings (SFs). Methods Seventy-four of 6240 (1.2%) participants who underwent genome or exome sequencing through the Clinical Sequencing Exploratory Research (CSER) Consortium received one or more SFs from the original American College of Medical Genetics and Genomics (ACMG) recommended 56 gene–condition pair list; we assessed clinical and psychosocial actions. Results The overall adjusted prevalence of SFs in the ACMG 56 genes across the CSER consortium was 1.7%. Initially 32% of the family histories were positive, and post disclosure, this increased to 48%. The average cost of follow-up medical actions per finding up to a 1-year period was $128 (observed, range:$0–$678) and$421 (recommended, range: $141–$1114). Case reports revealed variability in the frequency of and follow-up on medical recommendations patients received associated with each SF gene–condition pair. Participants did not report adverse psychosocial impact associated with receiving SFs; this was corroborated by 18 participant (or parent) interviews. All interviewed participants shared findings with relatives and reported that relatives did not pursue additional testing or care. Conclusion Our results suggest that disclosure of SFs shows little to no adverse impact on participants and adds only modestly to near-term health-care costs; additional studies are needed to confirm these findings

Correction: Secondary findings from clinical genomic sequencing: prevalence, patient perspectives, family history assessment, and health-care costs from a multisite study

Correction to: Secondary findings from clinical genomic sequencing: prevalence, patient perspectives, family history assessment, and health-care costs from a multisite stud

Proceedings of the Thirteenth International Society of Sports Nutrition (ISSN) Conference and Expo

Meeting Abstracts: Proceedings of the Thirteenth International Society of Sports Nutrition (ISSN) Conference and Expo Clearwater Beach, FL, USA. 9-11 June 201

The longitudinal relationship between immune cell profiles and frailty in patients with breast cancer receiving chemotherapy

Abstract Background Frailty is associated with an increased risk of chemotherapy toxicity. Cellular markers of inflammation can help identify patients with frailty characteristics. However, the role of cellular markers of inflammation in identifying patients at risk of developing chemotherapy-induced frailty and their clinical utility are not fully understood. Methods This study was a secondary analysis of a large nationwide cohort study of women with stage I–IIIC breast cancer (n = 581, mean age 53.4; range 22–81). Measures were completed pre-chemotherapy (T1), post-chemotherapy (T2), and 6 months post-chemotherapy (T3). Frailty was assessed at all three time points using a modified Fried score consisting of four self-reported measures (weakness, exhaustion, physical activity, and walking speed; 0–4, 1 point for each). Immune cell counts as well as neutrophil to lymphocyte ratio (NLR) and lymphocyte to monocyte ratio (LMR) were obtained at T1 and T2 time points. Separate linear regressions were used to evaluate the associations of (1) cell counts at T1 with frailty at T1, T2, and T3 and (2) change in cell counts (T2–T1) with frailty at T2 and T3. We controlled for relevant covariates and frailty at the T1 time point. Results From T1 to T2, the mean frailty score increased (1.3 vs 2.0; p &lt; 0.01) and returned to T1 levels by the T3 time point (1.3 vs 1.3; p = 0.85). At the T1 time point, there was a positive association between cellular markers of inflammation and frailty: WBC (β = 0.04; p &lt; 0.05), neutrophils (β = 0.04; p &lt; 0.05), and NLR (β = 0.04; p &lt; 0.01). From T1 to T2, a greater increase in cellular markers of inflammation was associated with frailty at T2 (WBC: β = 0.02, p &lt; 0.05; neutrophils: β = 0.03, p &lt; 0.05; NLR: β = 0.03; p &lt; 0.01). These associations remained significant after controlling for the receipt of growth factors with chemotherapy and the time between when laboratory data was provided and the start or end of chemotherapy. Conclusions In patients with breast cancer undergoing chemotherapy, cellular markers of inflammation are associated with frailty. Immune cell counts may help clinicians identify patients at risk of frailty during chemotherapy. Trial registration ClinicalTrials.gov, NCT01382082 </jats:sec

The Longitudinal Relationship Between Immune Cell Profiles and Frailty in Patients with Breast Cancer receiving Chemotherapy

Abstract Background: Frailty is associated with an increased risk of chemotherapy toxicity. Cellular markers of inflammation can help identify patients with frailty characteristics. However, the role of cellular markers of inflammation in identifying patients at risk of developing chemotherapy-induced frailty and their clinical utility are not fully understood.Methods: This study was a secondary analysis of a large nationwide cohort study of women with stage I-IIIC breast cancer (n=581, mean age 53.4; range 22-81). Measures were completed pre-chemotherapy (T1; ≤7 days before first cycle), post-chemotherapy (T2; ≤ 1 month after last cycle), and 6 months post-chemotherapy (T3). Frailty was assessed at all three time-points using a modified Fried score consisting of four self-reported measures (weakness, exhaustion, physical activity, and walking speed; 0-4, 1 point for each). Immune cell counts as well as neutrophil to lymphocyte ratio (NLR) and lymphocyte to monocyte ratio (LMR) were obtained at T1 and T2 time-points. Separate linear regressions were used to evaluate the associations of: 1) cell counts at T1 with frailty at T1, T2, and T3 and 2) change in cell counts (T2-T1) with frailty at T2 and T3. We controlled for relevant covariates and frailty at the T1 time-point. Results: From T1 to T2, the mean frailty score increased (1.3 vs 2.0; p&lt;0.01) and returned to T1 levels by the T3 time-point (1.3 vs 1.3; p=0.85). At the T1 time-point, there was a positive association between cellular markers of inflammation and frailty: WBC (β=0.04; p&lt;0.05), neutrophils (β=0.04; p&lt;0.05), and NLR (β=0.04; p&lt;0.01). From T1 to T2, a greater increase in cellular markers of inflammation was associated with frailty at T2 (WBC: β=0.02; p&lt;0.05, neutrophils: β=0.03; p&lt;0.05, NLR: β=0.03; p&lt;0.01). These associations remained significant after controlling for the receipt of growth factors with chemotherapy. Conclusions: In patients with breast cancer undergoing chemotherapy, cellular markers of inflammation are associated with frailty. Immune cell counts may help clinicians identify patients at risk of frailty during chemotherapy. Trial Registration: ClinicalTrials.gov Identifier: NCT01382082</jats:p