Person:

Berry, Donna

Background: Clinical interpretation of health related quality of life (HRQOL) scores is challenging. The purpose of this analysis was to interpret score changes and identify minimal clinically important differences (MCID) on the European Organization for Research and Treatment of Cancer Quality of Life Questionnaire-Core 30 (QLQ-C30) before (T1) and during (T2) cancer treatment. Methods: Patients (N = 627) in stem cell transplant (SCT) and medical (MED) or radiation (RAD) oncology at two comprehensive cancer centers, enrolled in the Electronic Self-Report Assessment-Cancer study and completed the QLQ-C30 at T1 and T2. Perceived changes in five QOL domains, physical (PF), emotional (EF), social (SF), cognitive functioning (CF) and global quality of life (QOL), were reported using the Subject Significance Questionnaire (SSQ) at T2. Anchored on SSQ ratings indicating “improvement”, “the same”, or “deterioration”, means and effect sizes were calculated for QLQ-C30 score changes. MCID was calculated as the mean difference in QLQ-C30 score changes reflecting one category change on SSQ rating, using a two-piece linear regression model. Results: A majority of SCT patients (54%) perceived deteriorating global HRQOL versus improvement (17%), while approximately equal proportions of MED/RAD patients perceived improvement (25%) and deterioration (26%). Global QOL decreased 14.2 (SCT) and 2.0 (MED/RAD) units, respectively, among patients reporting “the same” in the SSQ. The MCID ranged 5.7-11.4 (SCT) and 7.2-11.8 (MED/RAD) units among patients reporting deteriorated HRQOL; ranged 2.7-3.4 units among MED/RAD patients reporting improvement. Excepting for the global QOL (MCID =6.9), no meaningful MCID was identified among SCT patients reporting improvement. Conclusions: Cancer treatment has greater impact on HRQOL among SCT patients than MED/RAD patients. The MCID for QLQ-C30 score change differed across domains, and differed for perceived improvement and deterioration, suggesting different standards for self-evaluating changes in HRQOL during cancer treatment. Specifically, clinical attention can be focused on patients who report at least a 6 point decrease, and for patients who report at least a 3 point increase on QLQ-C30 domains. Trial registration The trial was registered with ClinicalTrials.gov: NCT00852852

Overview: Patient–provider communication is vital to quality patient care in oncology settings and impacts health outcomes. Newer communication datasets contain patient symptom reports, real-time audiofiles of visits, coded communication data, and visit outcomes. The purpose of this paper is to: (1) review the complex communication processes during patient–provider interaction during oncology care; (2) describe methods of gathering and coding communication data; (3) suggest logical approaches to analyses; and (4) describe one new dataset that allows linking of patient symptoms and communication processes with visit outcomes. Challenges: Patient–provider communication research is complex due to numerous issues, including human subjects’ concerns, methods of data collection, numerous coding schemes, and varying analytic techniques. Data collection and coding: Coding of communication data is determined by the research question(s) and variables of interest. Subsequent coding and timestamping the behaviors provides categorical data and determines the interval between and patterns of behaviors. Analytic approaches: Sequential analyses move from descriptive statistics to explanatory analyses to direct analyses and conditional probabilities. In the final stage, explanatory modeling is used to predict outcomes from communication elements. Examples of patient and provider communication in the ambulatory oncology setting are provided from the new Electronic Self Report Assessment-Cancer II dataset. Summary: More complex communication data sets provide opportunities to link elements of patient–provider communication with visit outcomes. Given more complex datasets, a step-wise approach is necessary to analyze and identify predictive variables. Sequential analyses move from descriptive results to predictive models with communication data, creating links between patient symptoms and concerns, real-time audiotaped communication, and visit outcomes. The results of these analyses will be useful in developing evidence-based interventions to enhance communication and improve psychosocial outcomes in oncology settings.

Background:. Chronic low back pain (CLBP) among nurses is a growing health concern. The multimodal nature of mind-body exercises has potential to impact physiological and psychological processes associated with chronic pain, affording possible advantages over conventional unimodal therapies. This paper summarizes the prevalence of and risk factors for CLBP among nurses, reviews the effectiveness in treating pain and disability of mind-body exercises (yoga and tai chi) for CLBP among the general and nursing population, and describes implications. Methods. Articles, published during or prior to 2015, were systematically identified through the PubMed/MEDLINE, Web of Science, and ScienceDirect databases using the following search terms: nurses, mind-body, integrative, biopsychosocial, yoga, tai chi, back pain, and/or risk factors. Results. Prevalence estimates of CLBP among nurses ranged from 50% to 80%. Associated risk factors for CLBP included lifestyle and physical, psychological, psychosocial, and occupational factors. No published studies were identified that evaluated yoga or tai chi for nurses with CLBP. Studies in the general population suggested that these interventions are effective in reducing pain and disability and may improve factors/processes predictive of CLBP. Conclusion. This review suggests that evaluating the impact of multimodal interventions such as yoga and tai chi for nurses with CLBP warrants investigation.

Background: Therapeutic cancer chemotherapy is most successful when complete dosing is achieved. Because many newer therapeutic agents are oral and self-administered by the patient, adherence is a concern. The purpose of our analysis was to explore relationships between adherence, patient characteristics, and barriers to adherence. Methods: This secondary analysis utilized self-reported data from a randomized trial of self-care management conducted at two cancer centers in the US. Symptom distress was measured using the 15-item Symptom Distress Scale (SDS-15) and depression with the Patient Health Questionnaire-9 (PHQ-9). Adherence to oral medication was self-reported using the 8-item Morisky Medication Adherence Scale (MMAS-8). Measures were collected via Web-based, study-specific software ~8 weeks after treatment start date. Odds of low/medium adherence (score <8) were explored using univariate logistic regression. Given the number of factors and possible relationships among factors, a classification tree was built in lieu of a multivariable logistic regression model. Results: Of the eligible participants enrolled, 77 were on oral therapy and 70 had an MMAS score. Forty-nine (70%) reported a high adherence score (=8). Higher odds of low/medium adherence were associated with greater symptom distress (P=0.09), more depression (P=0.05), chemotherapy vs hormonal oral medication (P=0.03), being female (P=0.02), and being randomized to the control group in the parent trial (P=0.09). Conversely, high adherence was associated with working (P=0.08), being married/partnered (P=0.004), and being older (P=0.02). Factors identified as significantly related to low/medium adherence from the univariate logistic regression analyses were supported by the classification tree results. Conclusion: Nonadherence to therapeutic oral medications in patients with cancer was associated with being unmarried/unpartnered, symptom distress, younger age, not working, and female sex. These findings may help to identify patients at risk for nonadherence and for whom supportive interventions to enhance adherence may be needed.

Introduction: Frequently reported symptoms and treatment side effects may not be the most bothersome issues to patients with cancer. The purpose of this study was to investigate patient-reported symptom distress and bothersome issues among participants with cancer. Methods: Participants completed the Symptom Distress Scale-15 before treatment (T1) and during cancer treatment (T2) and reported up to two most bothersome issues among symptoms rated with moderate-to-severe distress. We compared symptom ratings and perceived bother and explored two approaches predicting patients’ most bothersome issues: worst absolute symptom score or worst change from pretreatment. Results: Significantly, (P≤0.0002) more patients reported moderate-to-severe distress at T2 for eight of 13 symptoms. At T1, 81% of patients reported one and 56% reported multiple symptoms with moderate-to-severe distress, while at T2, 89% reported one and 69% reported multiple symptoms with moderate-to-severe distress. Impact on sexual activity/interest, pain, fatigue, and insomnia were the most prevalent symptoms with moderate-to-severe distress. Fatigue, pain, and insomnia were perceived most often as bothersome. When one symptom was rated moderate-to-severe, predictive accuracy of the absolute score was 46% and 48% (T1 & T2) and 38% with the change score (T2–T1). When two or more symptoms were rated moderate-to-severe, predictive accuracy of the absolute score was 76% and 79% (T1 & T2) and 70% with the change score (T2–T1). Conclusion: More patients experienced moderate-to-severe symptom distress after treatment initiation. Patient identification of bothersome issues could not be assumed based on prevalence of symptoms reported with moderate-to-severe distress. The absolute symptom distress scores identified patients’ most bothersome issues with good accuracy, outperforming change scores.

Objective: To describe the psychosocial distress of head-and-neck cancer patients at the completion of therapy and the interest in and the preferred method of delivery of mind–body interventions (MBIs) among head-and-neck cancer patients. Materials and methods A descriptive, cross-sectional design was used to measure sleep disturbance, depression, anxiety, and the interest in and the preference for MBIs using anonymous, self-report questionnaires among a convenience sample of 30 males at their 3-month follow-up. Questionnaires included the Pittsburgh Sleep Quality Index, Hospital Anxiety and Depression Scale, and the self-created Survey for Preferred Methods of MBI. Frequency distributions and descriptive statistics were used to describe the sample demographic and clinical characteristics. Results: The mean age of the sample was 59 years. Oral cancer (63%) was the most common type of cancer. Nineteen participants (63%, 90% CI 47%–78%) had some interest in MBIs. Of interested participants, 8 (42%) preferred participating in MBIs alone, 10 (53%) preferred participating in MBIs at homes, 10 (53%) preferred participating in MBIs using a computer or mobile device, and 8 (42%) preferred participating in MBIs after the diagnosis, but before treatment started. Mean depression, anxiety, and sleep disturbance scores were 8.25 (SD 2.93), 5.41 (SD 3.52), and 6.3 (SD 3.86), respectively. Results from the independent-samples t-test and Mann–Whitney U tests revealed no significant differences in anxiety, depression, and sleep disturbance by MBI interest. Conclusion: Asking about depression, anxiety, and sleep disturbances may help to identify head-and-neck cancer patients at risk for psychosocial distress. These findings suggest an interest in MBIs, but further research is warranted.