Clinical Decision Support for Hypertension Management in Chronic Kidney Disease: A Randomized Clinical Trial.

Importance: Chronic kidney disease (CKD) affects 37 million adults in the United States, and for patients with CKD, hypertension is a key risk factor for adverse outcomes, such as kidney failure, cardiovascular events, and death. Objective: To evaluate a computerized clinical decision support (CDS) system for the management of uncontrolled hypertension in patients with CKD. Design, Setting, and Participants: This multiclinic, randomized clinical trial randomized primary care practitioners (PCPs) at a primary care network, including 15 hospital-based, ambulatory, and community health center-based clinics, through a stratified, matched-pair randomization approach February 2021 to February 2022. All adult patients with a visit to a PCP in the last 2 years were eligible and those with evidence of CKD and hypertension were included. Intervention: The intervention consisted of a CDS system based on behavioral economic principles and human-centered design methods that delivered tailored, evidence-based recommendations, including initiation or titration of renin-angiotensin-aldosterone system inhibitors. The patients in the control group received usual care from PCPs with the CDS system operating in silent mode. Main Outcomes and Measures: The primary outcome was the change in mean systolic blood pressure (SBP) between baseline and 180 days compared between groups. The primary analysis was a repeated measures linear mixed model, using SBP at baseline, 90 days, and 180 days in an intention-to-treat repeated measures model to account for missing data. Secondary outcomes included blood pressure (BP) control and outcomes such as percentage of patients who received an action that aligned with the CDS recommendations. Results: The study included 174 PCPs and 2026 patients (mean [SD] age, 75.3 [0.3] years; 1223 [60.4%] female; mean [SD] SBP at baseline, 154.0 [14.3] mm Hg), with 87 PCPs and 1029 patients randomized to the intervention and 87 PCPs and 997 patients randomized to usual care. Overall, 1714 patients (84.6%) were treated for hypertension at baseline. There were 1623 patients (80.1%) with an SBP measurement at 180 days. From the linear mixed model, there was a statistically significant difference in mean SBP change in the intervention group compared with the usual care group (change, -14.6 [95% CI, -13.1 to -16.0] mm Hg vs -11.7 [-10.2 to -13.1] mm Hg; P = .005). There was no difference in the percentage of patients who achieved BP control in the intervention group compared with the control group (50.4% [95% CI, 46.5% to 54.3%] vs 47.1% [95% CI, 43.3% to 51.0%]). More patients received an action aligned with the CDS recommendations in the intervention group than in the usual care group (49.9% [95% CI, 45.1% to 54.8%] vs 34.6% [95% CI, 29.8% to 39.4%]; P < .001). Conclusions and Relevance: These findings suggest that implementing this computerized CDS system could lead to improved management of uncontrolled hypertension and potentially improved clinical outcomes at the population level for patients with CKD. Trial Registration: ClinicalTrials.gov Identifier: NCT03679247.

Implementation of a Scalable Online Weight Management Programme in Clinical Settings: Protocol for the PROPS 2.0 Programme (Partnerships for Reducing Overweight and Obesity with Patient-Centered Strategies 2.0).

INTRODUCTION: There is an urgent need for scalable strategies for treating overweight and obesity in clinical settings. PROPS 2.0 (Partnerships for Reducing Overweight and Obesity with Patient-Centered Strategies 2.0) aims to adapt and implement the combined intervention from the PROPS Study at scale, in a diverse cross-section of patients and providers. METHODS AND ANALYSIS: We are implementing PROPS 2.0 across a variety of clinics at Brigham and Women's Hospital, targeting enrolment of 5000 patients. Providers can refer patients or patients can self-refer. Eligible patients must be ≥20 years old and have a body mass index (BMI) of ≥30 kg/m2 or a BMI of 25-29.9 kg/m2 plus another cardiovascular risk factor or obesity-related condition. After enrolment, patients register for the RestoreHealth online programme/app (HealthFleet Inc.) and participate for 12 months. Patients can engage with the programme and receive personalized feedback from a coach. Patient navigators help to enrol patients, enter updates in the electronic health record, and refer patients to additional resources. The RE-AIM (Reach, Effectiveness, Adoption, Implementation, and Maintenance) framework is guiding the evaluation. ETHICS AND DISSEMINATION: The Mass General Brigham Human Research Committee approved this protocol. An implementation guide will be created and disseminated, to help other sites adopt the intervention in the future. TRIAL REGISTRATION NUMBER: NCT0555925.

Childhood adiposity, serum metabolites and breast density in young women.

BACKGROUND: Childhood adiposity is inversely associated with young adult percent dense breast volume (%DBV) and absolute dense breast volume (ADBV), which could contribute to its protective effect for breast cancer later in life. The objective of this study was to identify metabolites in childhood serum that may mediate the inverse association between childhood adiposity and young adult breast density. METHODS: Longitudinal data from 182 female participants in the Dietary Intervention Study in Children (DISC) and the DISC 2006 (DISC06) Follow-Up Study were analyzed. Childhood adiposity was assessed by anthropometry at the DISC visit with serum available that occurred closest to menarche and expressed as a body mass index (BMI) z-score. Serum metabolites were measured by untargeted metabolomics using ultra-high-performance liquid chromatography-tandem mass spectrometry. %DBV and ADBV were measured by magnetic resonance imaging at the DISC06 visit when participants were 25-29 years old. Robust mixed effects linear regression was used to identify serum metabolites associated with childhood BMI z-scores and breast density, and the R package mediation was used to quantify mediation. RESULTS: Of the 115 metabolites associated with BMI z-scores (FDR < 0.20), 4 were significantly associated with %DBV and 6 with ADBV before, though not after, adjustment for multiple comparisons. Mediation analysis identified 2 unnamed metabolites, X-16576 and X-24588, as potential mediators of the inverse association between childhood adiposity and dense breast volume. X-16576 mediated 14% (95% confidence interval (CI) = 0.002, 0.46; P = 0.04) of the association of childhood adiposity with %DBV and 11% (95% CI = 0.01, 0.26; P = 0.02) of its association with ADBV. X-24588 also mediated 7% (95% CI = 0.001, 0.18; P = 0.05) of the association of childhood adiposity with ADBV. None of the other metabolites examined contributed to mediation of the childhood adiposity-%DBV association, though there was some support for contributions of lysine, valine and 7-methylguanine to mediation of the inverse association of childhood adiposity with ADBV. CONCLUSIONS: Additional large longitudinal studies are needed to identify metabolites and other biomarkers that mediate the inverse association of childhood adiposity with breast density and possibly breast cancer risk.

Primary care patients' and providers' perspectives about an online weight management program integrated with population health management: Post-intervention qualitative results from the PROPS study.

Objective: To assess patients' and providers' attitudes about the online weight management program and population health management approach in the PROPS Study, which examined the effectiveness of these strategies in primary care. Methods: We conducted semi-structured interviews with 22 patients and nine providers. Using thematic analysis, we analyzed transcripts of the interviews to identify key themes. Results: Most patients found the online program to be well-structured and easy to use, although a few noted that the information was overwhelming or could be more personalized. Patients mentioned that the support from the population health managers was critical for their success, and several reported that they would have liked more involvement from their primary care provider or a dietitian. Providers also were satisfied with the interventions, and several stated that the population health management support was helpful because it added accountability. Providers suggested that the interventions could be improved by tailoring the information and integrating the online program with the electronic health record. Conclusion: Most patients and providers were satisfied with the interventions, with several recommendations for improvements. Innovation: These findings give additional information about patients' and providers' experience with this innovative approach for managing overweight and obesity in primary care.

The Association Between Active Transportation and Serum Total 25-Hydroxyvitamin D Levels Among US Childbearing-Aged Women.

BACKGROUND: Serum total 25-hydroxyvitamin D (25[OH]D) and physical activity (PA) both play important roles in maternal-fetal health. However, a high prevalence of vitamin D and PA insufficiency has been observed in women of childbearing age. Active transportation may increase overall PA levels and potentially boost serum 25(OH)D levels. METHODS: Data from the National Health and Nutrition Examination Survey between 2007 and 2014 were used. A total of 5601 women aged 18-49 years were included. Transportation PA (TPA) was quantified as metabolic equivalents of task and serum 25(OH)D levels was measured. Multivariable logistic regression models adjusted for potential confounders were conducted. RESULTS: The corresponding adjusted odds ratios associated with vitamin D insufficiency (<50 nmol/L) were 1.09 (95% confidence interval, 0.87-1.37) for 1 to 499 MET minutes per week of TPA, 0.69 (0.52-0.91) for 500 to 1000 MET minutes per week of TPA, and 0.95 (0.72-1.26) for >1000 MET minutes per week of TPA, respectively, compared with no TPA. Using vitamin D deficiency (<30 nmol/L) as the outcome led to similar results. The association between TPA and serum 25(OH)D levels was more robust in high sedentary time. CONCLUSIONS: A moderate level of TPA is related to lower odds of suboptimal vitamin D status among women of childbearing age.

Multicomponent intervention to improve blood pressure management in chronic kidney disease: a protocol for a pragmatic clinical trial.

INTRODUCTION: The purpose of this study is to incorporate behavioural economic principles and user-centred design principles into a multicomponent intervention for the management of uncontrolled hypertension (HTN) in chronic kidney disease (CKD) in primary care. METHODS AND ANALYSIS: This is a multicentre, pragmatic, controlled trial cluster-randomised at the clinician level at The Brigham and Women's Practice -Based Research Network of 15 practices. Of 220 total clinicians, 184 were eligible to be enrolled, and the remainder were excluded (residents and clinicians who see urgent care or walk-in patients); no clinicians opted out. The intervention consists of a clinical decision support system based in behavioural economic and user-centred design principles that will: (1) synthesise existing laboratory tests, medication orders and vital sign data; (2) increase recognition of CKD, (3) increase recognition of uncontrolled HTN in CKD patients and (4) deliver evidence-based CKD and HTN management recommendations. The primary endpoint is the change in mean systolic blood pressure between baseline and 6 months compared across arms. We will use the Reach Effectiveness Adoption Implementation Maintenance framework. At the conclusion of this study, we will have: (1) validated an intervention that combines laboratory tests, medication records and clinical information collected by electronic health records to recognise uncontrolled HTN in CKD patients and recommend a course of care, (2) tested the effectiveness of said intervention and (3) collected information about the implementation of the intervention that will aid in dissemination of the intervention to other practice settings. ETHICS AND DISSEMINATION: The Human Subjects Institutional Review Board at Brigham and Women's Hospital provided an expedited review and approval for this study protocol, and a Data Safety Monitoring Board will ensure the ongoing safety of the trial. TRIAL REGISTRATION NUMBER: NCT03679247.

The association of urine osmolality with decreased kidney function and/or albuminuria in the United States.

BACKGROUND: Decreased kidney function is commonly caused by hypovolemia. When hypovolemic, the kidney reabsorbs water resulting in concentrated urine. Osmolality is a measure of urine concentration which is more objective than self-reported fluid intake. It has a positive association with hypovolemia. However, it remains controversial whether osmolality is associated with decreased kidney function and/or albuminuria. METHODS: We conducted a cross-sectional analysis of the 2009-2012 National Health and Nutrition Examination Survey, a standardized survey in the U.S. POPULATION: Participants aged 18-70 years old with random urine osmolality were included. Osmolality was categorized as quartiles. Decreased kidney function was defined by estimated glomerular filtration rate (eGFR) < 60 mL/min/1.73m2 and albuminuria was defined by albumin-to-creatinine ratio ≥ 30 mg/gm. We performed multivariable regression via four sequential models. RESULTS: Our study sample included 7,373 participants. The mean age was 42.9 ± 0.4 years. Overall, 51.4% were male and 67.3% were white. The mean osmolality was 603.8 mOsm/kg and 629.1 mOsm/kg in those with and without decreased eGFR and/or albuminuria, respectively. The number of cases was 610 (6.7%). The prevalence from the lowest to highest quartiles of osmolality was 116 (6.2%), 213 (8.6%), 179 (7.5%), and 102 (4.3%), respectively (p-value for trend = 0.02). The relationship between osmolality and eGFR appeared nonlinear. After adjustment for demographic, social, cardiovascular, and dietary risk factors, there was no significant association of osmolality quartiles with decreased eGFR and/or albuminuria (odds ratio [OR] 0.77, 95% confidence interval [CI] 0.56, 1.07). In sensitivity analyses, osmolality ≥ 500 mOsm/kg was associated with lower eGFR (adjusted ß -1.13, 95% CI -1.98, -0.28). In pre-specified subgroup analyses, osmolality had a statistically significant negative correlation with eGFR among individuals with eGFR ≥ 60 mL/min/1.73m2, but a positive correlation among those with eGFR < 60 mL/min/1.73m2 (adjusted ß -0.19, 95% CI -0.36, -0.01 versus adjusted ß 0.50, 95% CI 0.05, 0.96; p-value for interaction = 0.016). CONCLUSIONS: Higher osmolality was significantly associated with lower eGFR among adults with eGFR ≥ 60 mL/min/1.73m2 Future research should examine the relationship between osmolality and change in kidney function over time among adults with normal eGFR.

Transport Time and Mortality in Critically Ill Patients with Severe Traumatic Brain Injury.

PURPOSE: Severe traumatic brain injury (TBI) is a major cause of morbidity and mortality in critically ill patients. Pre-hospital care and transportation time may impact their outcomes. METHODS: Using the British Columbia Trauma Registry, we included 2,860 adult (≥18 years) patients with severe TBI (abbreviated injury scale head score ≥4), who were admitted to an intensive care unit (ICU) in a centre with neurosurgical services from January 1, 2000 to March 31, 2013. We evaluated the impact of transportation time (time of injury to time of arrival at a neurosurgical trauma centre) on in-hospital mortality and discharge disposition, adjusting for age, sex, year of injury, injury severity score (ISS), revised trauma score at the scene, location of injury, socio-economic status and direct versus indirect transfer. RESULTS: Patients had a median age of 43 years (interquartile range [IQR] 26-59) and 676 (23.6%) were female. They had a median ISS of 33 (IQR 26-43). Median transportation time was 80 minutes (IQR 40-315). ICU and hospital length of stay were 6 days (IQR 2-12) and 20 days (IQR 7-42), respectively. Six hundred and ninety-six (24.3%) patients died in hospital. After adjustment, there was no significant impact of transportation time on in-hospital mortality (odds ratio 0.98, 95% confidence interval 0.95-1.01). There was also no significant effect on discharge disposition. CONCLUSIONS: No association was found between pre-hospital transportation time and in-hospital mortality in critically ill patients with severe TBI.

Effect of an Online Weight Management Program Integrated With Population Health Management on Weight Change: A Randomized Clinical Trial.

Importance: Online programs may help with weight loss but have not been widely implemented in routine primary care. Objective: To compare the effectiveness of a combined intervention, including an online weight management program plus population health management, with the online program only and with usual care. Design, Setting, and Participants: Cluster randomized trial with enrollment from July 19, 2016, through August 10, 2017, at 15 primary care practices in the US. Eligible participants had a scheduled primary care visit and were aged 20 to 70 years, had a body mass index between 27 and less than 40, and had a diagnosis of hypertension or type 2 diabetes. Follow-up ended on May 8, 2019. Interventions: Participants in the usual care group (n = 326) were mailed general information about weight management. Participants in the online program only group (n = 216) and the combined intervention group (n = 298) were registered for the online program. The participants in the combined intervention group also received weight-related population health management, which included additional support from nonclinical staff who monitored their progress in the online program and conducted periodic outreach. Main Outcomes and Measures: The primary outcome was weight change at 12 months based on measured weights recorded in the electronic health record. Weight change at 18 months was a secondary outcome. Results: Among the 840 participants who enrolled (mean age, 59.3 years [SD, 8.6 years]; 60% female; 76.8% White), 732 (87.1%) had a recorded weight at 12 months and the missing weights for the remaining participants were imputed. There was a significant difference in weight change at 12 months by group with a mean weight change of -1.2 kg (95% CI, -2.1 to -0.3 kg) in the usual care group, -1.9 kg (95% CI, -2.6 to -1.1 kg) in the online program only group, and -3.1 kg (95% CI, -3.7 to -2.5 kg) in the combined intervention group (P < .001). The difference in weight change between the combined intervention group and the usual care group was -1.9 kg (97.5% CI, -2.9 to -0.9 kg; P < .001) and the difference between the combined intervention group and the online program only group was -1.2 kg (95% CI, -2.2 to -0.3 kg; P = .01). At 18 months, the mean weight change was -1.9 kg (95% CI, -2.8 to -1.0 kg) in the usual care group, -1.1 kg (95% CI, -2.0 to -0.3 kg) in the online program only group, and -2.8 kg (95% CI, -3.5 to -2.0 kg) in the combined intervention group (P < .001). Conclusions and Relevance: Among primary care patients with overweight or obesity and hypertension or type 2 diabetes, combining population health management with an online program resulted in a small but statistically significant greater weight loss at 12 months compared with usual care or the online program only. Further research is needed to understand the generalizability, scalability, and durability of these findings. Trial Registration: ClinicalTrials.gov Identifier: NCT02656693.

Integrating an online weight management program with population health management in primary care: Design, methods, and baseline data from the PROPS randomized controlled trial (Partnerships for Reducing Overweight and Obesity with Patient-centered Strategies).

BACKGROUND: Scalable, low-cost weight management strategies are needed in primary care. We conducted a pragmatic, cluster-randomized controlled trial to examine the effectiveness of an online weight management program integrated with population health management support. METHODS: We adapted an online weight management program and integrated it with population health management support in 15 primary care practices (24 clinics). We randomized the 24 clinics to usual care (UC), online program alone (OP), or combined intervention (CI). Eligible participants had to be ages 20 to 70 and have a recent primary care visit, body mass index (BMI) ≥ 27 and < 40 kg/m2, and a diagnosis of hypertension or type 2 diabetes. Participants attended routine visits and completed surveys over 18 months. The primary outcome is absolute weight change at 12 months (± 90 days) after enrollment, calculated from weights measured at primary care visits and recorded in the electronic health record. RESULTS: We enrolled 840 participants between July 2016 and August 2017 (326 UC, 216 OP, and 298 CI.) At enrollment, participants' mean age was 59.3 years, their mean weight was 203.1 pounds, and their mean BMI was 32.5 kg/m2; 60% of participants were female, 76.8% were white, 96.4% had hypertension, and 24.4% had type 2 diabetes. CONCLUSION: It is feasible to adapt an online weight management program and integrate it with population health management support in primary care. The results of this trial will provide valuable information about the effectiveness of these strategies in primary care settings. ClinicalTrials.govregistration number:NCT02656693.

Primary Care Patients' and Providers' Perspectives about an Online Weight Management Program: a Qualitative Study.

BACKGROUND: Primary care providers (PCPs) often take the lead role in caring for patients with overweight and obesity; however, few PCPs counsel patients about weight loss. Online weight management programs that are integrated within primary care may help address this gap in care. OBJECTIVE: To identify perceptions of and experience with online weight management programs in general and with a proposed online program, to identify barriers to use, and to improve the design and content of our intervention, which included an online program plus population health management (PHM) support from primary care practices. DESIGN: A mixed qualitative methods study including three patient focus groups and seven semi-structured interviews with healthcare providers. PARTICIPANTS: A total of 13 adult patients (age range, 20-70) with body mass index (BMI) 27-35 kg/m2 attended the focus groups. In-person semi-structured interviews were conducted with seven healthcare providers (three PCPs, two population health managers, one primary care nurse, and one registered dietitian). MAIN MEASURES: We developed and used semi-structured focus groups and interview guides. The focus group and interviews were recorded and transcribed. Using grounded theory, we analyzed the transcripts to identify and extract common concepts and themes. KEY RESULTS: Although patients and healthcare providers expressed positive opinions about online weight management programs, few patients had experience with them, and providers stated that such programs are not being widely implemented in primary care settings. Some participants highlighted the flexibility and low cost as strengths of online weight management tools compared with in-person programs. All participants had favorable opinions about our proposed intervention and were overwhelmingly positive about the combination of an online program and PHM support. CONCLUSIONS: This study highlights the potential value of online weight management programs and PHM support in primary care. CLINICAL TRIALS REGISTRATION: NCT02656693.

Accuracy of self-perceived risk for common conditions.

BACKGROUND: Accurate awareness of common disease risk is necessary to promote healthy lifestyles and to prevent unnecessary anxiety and evaluation. Our objective is to identify characteristics of patients who do not accurately perceive their risk of developing coronary heart disease (CHD), diabetes (DM), breast cancer (BC) and colorectal cancer (CRC). METHODS: Using personalized disease risk reports and risk perception surveys, subjects (n = 4703) were classified as high or low/average risk and high or low/average perceived risk for each condition. Models were used to examine factors associated with risk under-estimation by high risk patients and risk over-estimation by low/average risk patients. RESULTS: Patients at high risk for DM, BC and CRC often (60%-75% of the time) under-estimated their risk, while low/average risk patients overestimated their risk 13%-40% of the time. For CHD, under-estimation by high risk individuals approximated over-estimation by low/average individuals. Compared to normal weight patients at high risk for cancer, obese patients were more likely to under-estimate their risk for BC (OR 3.1, CI 1.9-5.0) and CRC (2.6, 1.5-4.5) as were overweight patients. Overweight and obese patients at low/average risk of DM or CHD were more likely than normal weight patients to over-estimate their risk. Low/average risk women were more likely than men to over-estimate their risk of DM (1.3, 1.1-1.5) and CHD (1.8, 1.5-2.1). CONCLUSIONS: Our data show that body mass index is the factor most consistently associated with incorrect risk perceptions for several common conditions.

Prediction Model of In-Hospital Mortality After Hip Fracture Surgery.

OBJECTIVES: Mortality in elderly patients after the surgical treatment of hip fractures remains high. Although individual clinical risk factors have been widely studied, there has been limited research on prediction models in this population. The purpose of this study was to develop a prediction model for in-hospital mortality after hip fracture surgery and to evaluate the performance of this model. METHODS: Using the National Inpatient Sample database from 2012 to 2013, we collected data on 535,475 patients older than 50 years who had hip fracture surgery. Patient characteristics, surgery-specific factors, and Elixhauser comorbidities were used as candidate variables. The patients were randomly divided into training and testing cohorts. The Lasso (least absolute shrinkage and selection operator) method was used to select predictor variables, and points were assigned to each variable based on its coefficient. RESULTS: We identified 8 essential predictors (age, timing of surgery, male sex, congestive heart failure, pulmonary circulation disease, renal failure, weight loss, and fluid and electrolyte disorders) for mortality, with a maximum prediction score of 20. The model's area under the curve was 0.74, and the Hosmer-Lemeshow test P value was 0.59 on the testing set. With the application of cutoff values (scores 0-5, 6-9, and 10-20), the observed in-hospital postoperative mortality was 0.6%, 2.5%, and 7.5%, respectively. CONCLUSIONS: We built a simple prediction model with 8 essential clinical factors that predict in-hospital mortality after hip fracture surgery. This model may assist in counseling patients and families and measuring hospital quality of care. LEVEL OF EVIDENCE: Prognostic Level III. See Instructions for Authors for a complete description of levels of evidence.

Steroid withdrawal after renal transplantation: a retrospective cohort study.

BACKGROUND: Immunosuppressive regimens in renal transplantation frequently contain corticosteroids, but many centers withdraw steroids as a consequence of unwanted side effects of steroids. The optimal timing to withdraw steroids after transplantation, however, remains unclear. The aim of this study was to determine an optimal time point following kidney transplantation that is associated with reduced mortality without jeopardizing the allograft to allow safe discontinuation of steroids. METHODS: We conducted a retrospective cohort study and computed a concatenated landmark-stratified Cox supermodel to estimate hazard ratios and 95% confidence intervals for mortality and graft loss using dynamic propensity score matching to adjust for confounding by indication. RESULTS: A total of 6070 first kidney transplant recipients in the Austrian Dialysis and Transplant Registry who were transplanted between 1990 and 2012 were evaluated and classified according to steroid treatment status throughout follow-up after kidney transplantation; 2142 patients were withdrawn from steroids during the study period. Overall, 1131 patients lost their graft and 821 patients in the study cohort died. Steroid withdrawal within 18 months after transplantation was associated with an increased rate of graft loss compared to steroid maintenance during that time (6 months after transplantation: HR = 1.8; 95% CI, 1.3 to 2.6; 18 months after transplantation: HR = 1.3; 95% CI, 1.1 to 1.6; 24 months after transplantation: HR = 1.2; 95% CI, 0.9 to 1.5), while mortality was not different between groups. CONCLUSIONS: Our findings suggest that steroid withdrawal after anti-IL-2 induction in the first 18 months after transplantation is associated with an increased risk of allograft loss.

A Cluster Randomized Trial of a Personalized Multi-Condition Risk Assessment in Primary Care.

INTRODUCTION: Personal risk for multiple conditions should be assessed in primary care. This study evaluated whether collection of risk factors to generate electronic health record (EHR)-linked health risk appraisal (HRA) for coronary heart disease, diabetes, breast cancer, and colorectal cancer was associated with improved patient-provider communication, risk assessment, and plans for breast cancer screening. METHODS: This pragmatic trial recruited adults with upcoming visits to 11 primary care practices during 2013-2014 (N=3,703). Pre-visit, intervention patients completed a risk factor and perception assessment and received an HRA; coded risk factor data were sent to the EHR. Post-visit, intervention patients reported risk perception. Pre-visit, control patients only completed the risk perception assessment; post-visit they also completed the risk factor assessment and received the HRA. No data were sent to the EHR for controls. Accuracy/improvement of self-perceived risk was assessed by comparing self-perceived to calculated risk. RESULTS: The intervention was associated with improvement of patient-provider communication of changes to improve health (78.5% vs 74.1%, AOR=1.67, 99% CI=1.07, 2.60). There was a similar trend for discussion of risk (54.1% vs 45.5%, AOR=1.34, 95% CI=0.97, 1.85). The intervention was associated with greater improvement in accuracy of self-perceived risk for diabetes (16.0% vs 12.6%, p=0.006) and colorectal cancer (27.9% vs 17.2%, p<0.001) with a similar trend for coronary heart disease and breast cancer. There were no changes in plans for breast cancer screening. CONCLUSIONS: Patient-reported risk factors and EHR-linked multi-condition HRAs in primary care can modestly improve communication and promote accuracy of self-perceived risk.

Early Life Body Fatness, Serum Anti-Müllerian Hormone, and Breast Density in Young Adult Women.

BACKGROUND: Emerging evidence suggests positive associations between serum anti-Müllerian hormone (AMH), a marker of ovarian function, and breast cancer risk. Body size at young ages may influence AMH levels, but few studies have examined this. Also, no studies have examined the relation of AMH levels with breast density, a strong predictor of breast cancer risk. METHODS: We examined associations of early life body fatness, AMH concentrations, and breast density among 172 women in the Dietary Intervention Study in Children (DISC). Height and weight were measured at baseline (ages 8-10) and throughout adolescence. Serum AMH concentrations and breast density were assessed at ages 25-29 at the DISC 2006 Follow-up visit. We used linear mixed effects models to quantify associations of AMH (dependent variable) with quartiles of age-specific youth body mass index (BMI) Z-scores (independent variable). We assessed cross-sectional associations of breast density (dependent variable) with AMH concentration (independent variable). RESULTS: Neither early life BMI nor current adult BMI was associated with AMH concentrations. There were no associations between AMH and percent or absolute dense breast volume. In contrast, women with higher AMH concentrations had significantly lower absolute nondense breast volume (Ptrend < 0.01). CONCLUSIONS: We found no evidence that current or early life BMI influences AMH concentrations in later life. Women with higher concentrations of AMH had similar percent and absolute dense breast volume, but lower nondense volume. IMPACT: These results suggest that AMH may be associated with lower absolute nondense breast volume; however, future prospective studies are needed to establish temporality. Cancer Epidemiol Biomarkers Prev; 25(7); 1151-7. ©2016 AACR.

Validation of a risk prediction tool for coronary heart disease in middle-aged women.

BACKGROUND: Health risk appraisal tools may be useful for identifying individuals who would benefit from lifestyle changes and increased surveillance. We evaluated the validity of the Your Disease Risk tool (YDR) for estimating relative risk of coronary heart disease (CHD) among middle-aged women. METHODS: We included 55,802 women in the Nurses' Health Study who completed a mailed questionnaire about risk factors in 1994 and had no history of heart disease at that time. Participants were followed through 2004 for the occurrence of CHD. We estimated each woman's 10-year relative risk of CHD using YDR, and we compared the estimated YDR relative risk category (ranging from "very much below average" to "very much above average") to the observed relative risk for each category using logistic regression. We also examined the discriminatory accuracy of YDR using concordance statistics (c-statistics). RESULTS: There were 1165 CHD events during the 10-year follow-up period. Compared to the "about average" category, the observed age-adjusted relative risk was 0.43 (95 % confidence interval: 0.33, 0.56) for the "very much below average" category and 2.48 (95 % confidence interval: 1.68, 3.67) for the "very much above average" category. The age-adjusted c-statistic for the model including the YDR relative risk category was 0.71 (95 % confidence interval: 0.69, 0.72). The model performed better in younger than older women. CONCLUSION: The YDR tool appears to have moderate validity for estimating 10-year relative risk of CHD in this population of middle-aged women. Further research should aim to improve the tool's performance and to examine its validity in other populations.

Body fatness during childhood and adolescence and breast density in young women: a prospective analysis.

INTRODUCTION: Overweight and obesity in childhood and adolescence are associated with reduced breast cancer risk, independent of adult body mass index (BMI). These associations may be mediated through breast density. METHODS: We prospectively examined associations of early life body fatness with adult breast density measured by MRI in 182 women in the Dietary Intervention Study in Children (DISC) who were ages 25-29 at follow-up. Height, weight, and other factors were measured at baseline (ages 8-10) and annual clinic visits through adolescence. We used linear mixed-effects models to quantify associations of percent breast density and dense and non-dense breast volume at ages 25-29 with quartiles of age-specific youth body mass index (BMI) Z-scores, adjusting for clinic, treatment group, current adult BMI, and other well-established risk factors for breast cancer and predictors of breast density. RESULTS: We observed inverse associations between age-specific BMI Z-scores at all youth clinic visits and percent breast density, adjusting for current adult BMI and other covariates (all p values <0.01). Women whose baseline BMI Z-scores (at ages 8-10 years) were in the top quartile had significantly lower adult breast density, after adjusting for current adult BMI and other covariates [least squares mean (LSM): 23.4 %; 95 % confidence interval (CI): 18.0 %, 28.8 %] compared to those in the bottom quartile (LSM: 31.8 %; 95 % CI: 25.2 %, 38.4 %) (p trend <0.01). Significant inverse associations were also observed for absolute dense breast volume (all p values <0.01), whereas there were no clear associations with non-dense breast volume. CONCLUSIONS: These results support the hypothesis that body fatness during childhood and adolescence may play an important role in premenopausal breast density, independent of current BMI, and further suggest direct or indirect influences on absolute dense breast volume. CLINICAL TRIALS REGISTRATION NUMBER: NCT00458588 ; April 9, 2007.