All together now: findings from a PCORI workshop to align patient-reported outcomes in the electronic health record

In recent years, patient-reported outcomes have become increasingly collected and integrated into electronic health records. However, there are few cross-cutting recommendations and limited guidance available in this rapidly developing research area. Our goal is to report key findings from a 2013 Patient-Centered Outcomes Research Institute workshop on this topic and a summary of actions that followed from the workshop, and present resulting recommendations that address patient, clinical and research/quality improvement barriers to regular use. These findings provide actionable guidance across research and practice settings to promote and sustain widespread adoption of patient-reported outcomes across patient populations, healthcare settings and electronic health record systems

Sleep quality in individuals diagnosed with colorectal cancer: Factors associated with sleep disturbance as patients transition off treatment

To identify patient characteristics associated with sleep disturbance and worsening of sleep in individuals diagnosed with localized colorectal cancer and assess heterogeneity in these relationships. Methods: Data were from the MY-Health study, a community-based observational study of adults diagnosed with cancer. Patient-Reported Outcomes Measurement Information System® Sleep Disturbance, Anxiety, Depression, Fatigue, and Pain Interference measures were administered. Participants self-reported demographics, comorbidities, and treatment information. Regression mixture and multiple regression models were used to evaluate the relationship between sleep disturbance and patient characteristics cross-sectionally at an average of 10 months after diagnosis (n = 613) as well as change in sleep disturbance over a 6-month period (n = 361). Results: Pain, anxiety, fatigue, and the existence of multiple comorbid conditions had statistically significant relationships with sleep disturbance (B = 0.09, 0.22, 0.29, and 1.53, respectively; P < 0.05). Retirement (B = -2.49) was associated with sleep quality in the cross-sectional model. Worsening anxiety (B = 0.14) and fatigue (B = 0.20) were associated with worsening sleep disturbance, and more severe sleep disturbance 10 months after diagnosis (B = -0.21) was associated with improvement in sleep quality after diagnosis (P < 0.05). No evidence of latent subgroups of patients (heterogeneity) was present. Conclusions: Pain, anxiety, fatigue, employment, and comorbid conditions were associated with sleep disturbance, but regression coefficients were small (< |2.5|). Results suggest that screening for anxiety, depression, fatigue, or pain is not sufficient for identifying sleep disturbance. Given the negative consequences of sleep disturbance, sleep disturbance screening may be warranted

Relationship between sleep and exercise as colorectal cancer survivors transition off treatment

Purpose The primary objective of this study was to evaluate the relationship between exercise and sleep disturbance in a sample of individuals diagnosed with stage I, II, and III colorectal cancer (CRC) as patients transitioned off first-line treatment. We also sought to identify heterogeneity in the relationship between sleep disturbance and exercise. Methods Data were obtained from the MY-Health study, a community-based observational study of adults diagnosed with cancer. Patient-Reported Outcomes Measurement Information System® (PROMIS) measures (e.g., PROMIS Sleep) were administered, and participants self-reported demographics, comorbidities, cancer treatment, and exercise. Regression mixture and multiple regression models were used to evaluate the relationship between sleep disturbance and exercise cross-sectionally at an average of 10 months after diagnosis, and the change in sleep disturbance over a 7-month period, from approximately 10 to 17 months post-diagnosis. Results Patients whose exercise was categorized as likely at or above American College of Sports Medicine’s guidelines did not report statistically better sleep quality compared to patients who were classified as not active. However, retirement (B = − 2.4), anxiety (B = 0.21), and fatigue (B = 0.24) had statistically significant relationships with sleep disturbance (p < 0.05). Increase in exercise was not significantly associated with a decrease in sleep disturbance. No statistical heterogeneity was revealed in the relationship between sleep and exercise. Conclusions Further prospective research using an objective measure of exercise is warranted to confirm or refute the nature of the relationship between exercise and sleep disturbance in individuals diagnosed with CRC transitioning off first-line treatment

Impact of diagnosis and treatment of clinically localized prostate cancer on health-related quality of life for older Americans: A population-based study

Few studies have measured the longitudinal change in health-related quality of life (HRQOL) of prostate cancer patients starting prior to cancer diagnosis, or provide simultaneous comparisons with a matched non-cancer cohort. Our study addresses these gaps by providing unique estimates of the effects of a cancer diagnosis on HRQOL accounting for the confounding effects of ageing and comorbidity

The challenge of measuring intra-individual change in fatigue during cancer treatment

Evaluate how well three different patient-reported outcomes (PROs) measure individual change

Validation of the PROMIS physical function measures in a diverse US population-based cohort of cancer patients

To evaluate the validity of the Patient-Reported Outcomes Measurement Information System (PROMIS) Physical Function measures in a diverse, population-based cancer sample

Is the meiofauna a good indicator for climate change and anthropogenic impacts?

Our planet is changing, and one of the most pressing challenges facing the scientific community revolves around understanding how ecological communities respond to global changes. From coastal to deep-sea ecosystems, ecologists are exploring new areas of research to find model organisms that help predict the future of life on our planet. Among the different categories of organisms, meiofauna offer several advantages for the study of marine benthic ecosystems. This paper reviews the advances in the study of meiofauna with regard to climate change and anthropogenic impacts. Four taxonomic groups are valuable for predicting global changes: foraminifers (especially calcareous forms), nematodes, copepods and ostracods. Environmental variables are fundamental in the interpretation of meiofaunal patterns and multistressor experiments are more informative than single stressor ones, revealing complex ecological and biological interactions. Global change has a general negative effect on meiofauna, with important consequences on benthic food webs. However, some meiofaunal species can be favoured by the extreme conditions induced by global change, as they can exhibit remarkable physiological adaptations. This review highlights the need to incorporate studies on taxonomy, genetics and function of meiofaunal taxa into global change impact research