Experiences With Chiropractic Care for Patients With Low Back or Neck Pain.

BackgroundMusculoskeletal disorders are the second leading cause of disability worldwide.ObjectiveExamine experiences of chiropractic patients in the United States with chronic low back or neck pain.MethodObservational study of 1853 chronic low back pain and neck pain patients (74% female) who completed an online questionnaire at the 3-month follow-up that included Consumer Assessment of Healthcare Providers and Systems (CAHPS) items assessing their experiences with care.ResultsWe found similar reports of communication for the chiropractic sample and patients in the 2016 CAHPS National Database, but 85% in the database versus 79% in the chiropractic sample gave the most positive response to the time spent with provider item. More patients in the CAHPS database rated their provider at the top of the scale (8 percentage points). More chiropractic patients reported always getting answers to questions the same day (16 percentage points) and always being seen within 15 minutes of their appointment time (29 percentage points).ConclusionsThe positive experiences of patients with chronic back and neck pain are supportive of their use of chiropractic care

Responsiveness of PROMIS® to change in chronic obstructive pulmonary disease.

BackgroundChronic obstructive pulmonary disease (COPD) is a progressive chronic disease characterized by airflow obstruction that leads to shortness of breath and substantial negative impacts on health-related quality of life (HRQL). The course of COPD includes periodic acute exacerbations that require changes in treatment and/or hospitalizations. This study was designed to examine the responsiveness of Patient-Reported Outcomes Measurement Information System® (PROMIS®) measures to changes associated with COPD exacerbation recovery.MethodsA longitudinal analysis using mixed-effects models was conducted of people who were enrolled while stable (n = 100) and those who experienced an acute exacerbation (n = 85). PROMIS (physical function, pain interference, pain behavior, fatigue, anxiety, depression, anger, social roles, discretionary social activities, Global Health, dyspnea severity and dyspnea functional limitations) and COPD-targeted HRQL measures were completed at baseline and at 12 weeks.ResultsWe administered PROMIS measures using computer adaptive testing (CAT), followed by administration of any remaining short form (SF) items that had not yet been administered by CAT. Examination of the difference between group differences from baseline to 12 weeks in the stable and exacerbation groups revealed that the exacerbation group changed (improved) significantly more than the stable group in anxiety (p < .001 to p < .01; f2 effect size [ES] = 0.023/0.021), fatigue (p < .0001; ES = 0.036/0.047) and social roles (p < .001 to p < .05; ES = 0.035/0.024). All effect sizes were small in magnitude and smaller than hypothesized. Depression was also statistically significant (p < .05, SF only) but the ES was trivial. For all other PROMIS domains, the differences were not significant and ES were trivial.ConclusionsThis longitudinal study provides some support for the validity of the PROMIS fatigue, anxiety, and social roles domains in COPD, but further evaluation of responsiveness is warranted

Development of physical and mental health summary scores from the patient-reported outcomes measurement information system (PROMIS) global items

The use of global health items permits an efficient way of gathering general perceptions of health. These items provide useful summary information about health and are predictive of health care utilization and subsequent mortality. Analyses of 10 self-reported global health items obtained from an internet survey as part of the Patient-Reported Outcome Measurement Information System (PROMIS) project. We derived summary scores from the global health items. We estimated the associations of the summary scores with the EQ-5D index score and the PROMIS physical function, pain, fatigue, emotional distress, and social health domain scores. Exploratory and confirmatory factor analyses supported a two-factor model. Global physical health (GPH; 4 items on overall physical health, physical function, pain, and fatigue) and global mental health (GMH; 4 items on quality of life, mental health, satisfaction with social activities, and emotional problems) scales were created. The scales had internal consistency reliability coefficients of 0.81 and 0.86, respectively. GPH correlated more strongly with the EQ-5D than did GMH (r = 0.76 vs. 0.59). GPH correlated most strongly with pain impact (r = −0.75) whereas GMH correlated most strongly with depressive symptoms (r = −0.71). Two dimensions representing physical and mental health underlie the global health items in PROMIS. These global health scales can be used to efficiently summarize physical and mental health in patient-reported outcome studies

U.S. General Population Estimate for “Excellent” to “Poor” Self-Rated Health Item

BACKGROUND: The most commonly used self-reported health question asks people to rate their general health from excellent to poor. This is one of the Patient-Reported Outcomes Measurement Information System (PROMIS) global health items. Four other items are used for scoring on the PROMIS global physical health scale. Because the single item is used on the majority of large national health surveys in the U.S., it is useful to construct scores that can be compared to U.S. general population norms. OBJECTIVE: To estimate the PROMIS global physical health scale score from the responses to the single excellent to poor self-rated health question for use in public health surveillance, research, and clinical assessment. DESIGN: A cross-sectional survey of 21,133 individuals, weighted to be representative of the U.S. general population. PARTICIPANTS: The PROMIS items were administered via a Web-based survey to 19,601 persons in a national panel and 1,532 subjects from PROMIS research sites. The average age of individuals in the sample was 53 years, 52 % were female, 80 % were non-Hispanic white, and 19 % had a high school degree or lower level of education. MAIN OUTCOME MEASURES: PROMIS global physical health scale. KEY RESULTS: The product–moment correlation of the single item with the PROMIS global physical health scale score was 0.81. The estimated scale score based on responses to the single item ranged from 29 (poor self-rated health, 2.1 SDs worse than the general population mean) to 62 (excellent self-rated health, 1.2 SDs better than the general population mean) on a T-score metric (mean of 50). CONCLUSIONS: This item can be used to estimate scores for the PROMIS global physical health scale for use in monitoring population health and achieving public health objectives. The item may also be used for individual assessment, but its reliability (0.52) is lower than that of the PROMIS global health scale (0.81)

Cell-free DNA profiling of metastatic prostate cancer reveals microsatellite instability, structural rearrangements and clonal hematopoiesis.

This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.BACKGROUND: There are multiple existing and emerging therapeutic avenues for metastatic prostate cancer, with a common denominator, which is the need for predictive biomarkers. Circulating tumor DNA (ctDNA) has the potential to cost-efficiently accelerate precision medicine trials to improve clinical efficacy and diminish costs and toxicity. However, comprehensive ctDNA profiling in metastatic prostate cancer to date has been limited. METHODS: A combination of targeted and low-pass whole genome sequencing was performed on plasma cell-free DNA and matched white blood cell germline DNA in 364 blood samples from 217 metastatic prostate cancer patients. RESULTS: ctDNA was detected in 85.9% of baseline samples, correlated to line of therapy and was mirrored by circulating tumor cell enumeration of synchronous blood samples. Comprehensive profiling of the androgen receptor (AR) revealed a continuous increase in the fraction of patients with intra-AR structural variation, from 15.4% during first-line metastatic castration-resistant prostate cancer therapy to 45.2% in fourth line, indicating a continuous evolution of AR during the course of the disease. Patients displayed frequent alterations in DNA repair deficiency genes (18.0%). Additionally, the microsatellite instability phenotype was identified in 3.81% of eligible samples (≥ 0.1 ctDNA fraction). Sequencing of non-repetitive intronic and exonic regions of PTEN, RB1, and TP53 detected biallelic inactivation in 47.5%, 20.3%, and 44.1% of samples with ≥ 0.2 ctDNA fraction, respectively. Only one patient carried a clonal high-impact variant without a detectable second hit. Intronic high-impact structural variation was twice as common as exonic mutations in PTEN and RB1. Finally, 14.6% of patients presented false positive variants due to clonal hematopoiesis, commonly ignored in commercially available assays. CONCLUSIONS: ctDNA profiles appear to mirror the genomic landscape of metastatic prostate cancer tissue and may cost-efficiently provide somatic information in clinical trials designed to identify predictive biomarkers. However, intronic sequencing of the interrogated tumor suppressors challenges the ubiquitous focus on coding regions and is vital, together with profiling of synchronous white blood cells, to minimize erroneous assignments which in turn may confound results and impede true associations in clinical trials.The Belgian Foundation Against Cancer (grant number C/2014/227); Kom op tegen Kanker (Stand up to Cancer), the Flemish Cancer Society (grant number 00000000116000000206); Royal College of Surgeons/Cancer Research UK (C19198/A1533); The Cancer Research Funds of Radiumhemmet, through the PCM program at KI (grant number 163012); The Erling-Persson family foundation (grant number 4-2689-2016); the Swedish Research Council (grant number K2010-70X-20430-04-3), and the Swedish Cancer Foundation (grant number 09-0677)

Impact of common cardio-metabolic risk factors on fatal and non-fatal cardiovascular disease in Latin America and the Caribbean: an individual-level pooled analysis of 31 cohort studies

Background: Estimates of the burden of cardio-metabolic risk factors in Latin America and the Caribbean (LAC) rely on relative risks (RRs) from non-LAC countries. Whether these RRs apply to LAC remains un- known. Methods: We pooled LAC cohorts. We estimated RRs per unit of exposure to body mass index (BMI), systolic blood pressure (SBP), fasting plasma glucose (FPG), total cholesterol (TC) and non-HDL cholesterol on fatal (31 cohorts, n = 168,287) and non-fatal (13 cohorts, n = 27,554) cardiovascular diseases, adjusting for regression dilution bias. We used these RRs and national data on mean risk factor levels to estimate the number of cardiovascular deaths attributable to non-optimal levels of each risk factor. Results: Our RRs for SBP, FPG and TC were like those observed in cohorts conducted in high-income countries; however, for BMI, our RRs were consistently smaller in people below 75 years of age. Across risk factors, we observed smaller RRs among older ages. Non-optimal SBP was responsible for the largest number of attributable cardiovascular deaths ranging from 38 per 10 0,0 0 0 women and 54 men in Peru, to 261 (Dominica, women) and 282 (Guyana, men). For non-HDL cholesterol, the lowest attributable rate was for women in Peru (21) and men in Guatemala (25), and the largest in men (158) and women (142) from Guyana. Interpretation: RRs for BMI from studies conducted in high-income countries may overestimate disease burden metrics in LAC; conversely, RRs for SBP, FPG and TC from LAC cohorts are similar to those esti- mated from cohorts in high-income countries

Using Item Response Theory to Identify Responders to Treatment: Examples with the Patient-Reported Outcomes Measurement Information System (PROMIS®) Physical Function Scale and Emotional Distress Composite.

The reliable change index has been used to evaluate the significance of individual change in health-related quality of life. We estimate reliable change for two measures (physical function and emotional distress) in the Patient-Reported Outcomes Measurement Information System (PROMIS®) 29-item health-related quality of life measure (PROMIS-29 v2.1). Using two waves of data collected 3 months apart in a longitudinal observational study of chronic low back pain and chronic neck pain patients receiving chiropractic care, and simulations, we compare estimates of reliable change from classical test theory fixed standard errors with item response theory standard errors from the graded response model. We find that unless true change in the PROMIS physical function and emotional distress scales is substantial, classical test theory estimates of significant individual change are much more optimistic than estimates of change based on item response theory

Alternative Approaches to Addressing Non-Normal Distributions in the Application of IRT Models to Personality Measures.

It is generally assumed that the latent trait is normally distributed in the population when estimating logistic item response theory (IRT) model parameters. This assumption requires that the latent trait be fully continuous and the population homogenous (i.e., not a mixture). When this normality assumption is violated, models are misspecified, and item and person parameter estimates are inaccurate. When normality cannot be assumed, it might be appropriate to consider alternative modeling approaches: (a) a zero-inflated mixture, (b) a log-logistic, (c) a Ramsay curve, or (d) a heteroskedastic-skew model. The first 2 models were developed to address modeling problems associated with so-called quasi-continuous or unipolar constructs, which apply only to a subset of the population, or are meaningful at one end of the continuum only. The second 2 models were developed to address non-normal latent trait distributions and violations of homogeneity of error variance, respectively. To introduce these alternative IRT models and illustrate their strengths and weaknesses, we performed real data application comparing results to those from a graded response model. We review both statistical and theoretical challenges in applying these models and choosing among them. Future applications of these and other alternative models (e.g., unfolding, diffusion) are needed to advance understanding about model choice in particular situations

PROMIS®-29 v2.0 profile physical and mental health summary scores.

PurposeThe PROMIS-29 v2.0 profile assesses pain intensity using a single 0-10 numeric rating item and seven health domains (physical function, fatigue, pain interference, depressive symptoms, anxiety, ability to participate in social roles and activities, and sleep disturbance) using four items per domain. This paper describes the development of physical and mental health summary scores for the PROMIS-29 v2.0.MethodWe conducted factor analyses of PROMIS-29 scales on data collected from two internet panels (n = 3000 and 2000).ResultsConfirmatory factor analyses provided support for a physical health factor defined by physical function, pain (interference and intensity), and ability to participate in social roles and activities, and a mental health factor defined primarily by emotional distress (anxiety and depressive symptoms). Reliabilities for these two summary scores were 0.98 (physical health) and 0.97 (mental health). Correlations of the PROMIS-29 v2.0 physical and mental health summary scores with chronic conditions and other health-related quality of life measures were consistent with a priori hypotheses.ConclusionsThis study develops and provides preliminary evidence supporting the reliability and validity of PROMIS-29 v2.0 physical and mental health summary scores that can be used in future studies to assess impacts of health care interventions and track changes in health over time. Further evaluation of these and alternative summary measures is recommended