Once-Daily Fluticasone Furoate/Vilanterol Versus Once-Daily Fluticasone Furoate in Asthma Patients Aged 5-17 Years.

BACKGROUND: Limited data exist comparing inhaled corticosteroid (ICS) plus adjunctive therapy versus ICS alone in pediatric asthma patients. OBJECTIVE: Evaluate the efficacy and safety of fluticasone furoate/vilanterol (FF/VI) versus FF in children and adolescents with asthma. METHODS: This Phase 3, randomized, double-blind, multicenter study (NCT03248128) included participants aged 5-17 years with ≥6 months' asthma history uncontrolled on ICS monotherapy. Participants received 4 weeks' open-label fluticasone propionate (100 µg) twice daily before 1:1 randomization to 24 weeks' double-blind FF (50 µg:100 µg) or FF/VI (50/25 µg:100/25 µg) once daily. Two populations with different primary endpoints were analyzed to meet United States (Week 12 weighted mean forced expiratory volume in 1 second [FEV1; 0-4 hours]; participants aged 5-17 years) and European (change from baseline pre-dose morning peak expiratory flow [ΔAM PEF] averaged over Weeks 1-12; participants aged 5-11 years) regulator requirements. RESULTS: Overall, 902 participants were randomized and treated, including 673 children aged 5-11 years. In participants aged 5-17, Week 12 weighted mean FEV1 (0-4 hours) was greater with FF/VI versus FF (difference: 0.083 L; P < .001). In participants aged 5-11, ΔAM PEF over Weeks 1-12 showed numerical improvement with FF/VI versus FF but was not statistically significant (difference: 3.2 L/minute; P = .228). No drug-related serious adverse events or deaths were reported. CONCLUSION: FF/VI significantly improved weighted mean FEV1 (0-4 hours; participants aged 5-17 years), but not ΔAM PEF (participants aged 5-11 years) versus FF. No new safety concerns were apparent.

Longitudinal Associations Between Exclusive and Dual Use of Electronic Nicotine Delivery Systems and Cigarettes and Self-Reported Incident Diagnosed Cardiovascular Disease Among Adults.

INTRODUCTION: The cardiovascular health effects of electronic nicotine delivery systems (ENDS) use are not well characterized, making it difficult to assess ENDS as a potential harm reduction tool for adults who use cigarettes. AIMS AND METHODS: Using waves 1-5 of the Population Assessment of Tobacco and Health Study (2013-2019), we analyzed the risk of self-reported incident diagnosed myocardial infarction (MI; 280 incident cases) and stroke (186 incident cases) associated with ENDS and/or cigarette use among adults aged 40 + using discrete time survival models. We employed a time-varying exposure lagged by one wave, defined as exclusive or dual established use of ENDS and/or cigarettes every day or some days, and controlled for demographics, clinical factors, and past smoking history. RESULTS: The analytic samples (MI = 11 031; stroke = 11 076) were predominantly female and non-Hispanic White with a mean age of 58 years. At baseline, 14.2% of respondents exclusively smoked cigarettes, 0.6% exclusively used ENDS, and 1.0% used both products. Incident MI and stroke were rare during follow-up (< 1% at each wave). Compared to no cigarette or ENDS use, exclusive cigarette use increased the risk of MI (aHR 1.99, 95% CI = 1.40-2.84) and stroke (aHR 2.26, 95% CI = 1.51-3.39), while exclusive ENDS use (MI: aHR 0.61, 95% CI = 0.12-3.04; stroke: aHR 1.74, 95% CI = 0.55-5.49) and dual use (MI: aHR 1.84, 95% CI = 0.64-5.30; stroke: aHR 1.12, 95% CI = 0.33-3.79) were not significantly associated with the risk of either outcome. CONCLUSIONS: Compared to non-use, exclusive cigarette use was associated with an increased risk of self-reported incident diagnosed cardiovascular disease over a 5-year period, while ENDS use was not associated with a statistically significant increase in the outcomes. IMPLICATIONS: Existing literature on the health effects of ENDS use has important limitations, including potential reverse causation and improper control for cigarette smoking. We accounted for these issues by using a prospective design and adjusting for current and former smoking status and cigarette pack-years. In this context, we did not find that ENDS use was associated with a statistically significant increase in self-reported incident diagnosed myocardial infarction or stroke over a 5-year period. While more studies are needed, this analysis provides an important foundation and key methodological considerations for future research on the health effects of ENDS use.

Latent class analysis of use frequencies for multiple tobacco products in US adults.

A persistent challenge is characterizing patterns of tobacco use in terms of product combinations and frequency. Using Wave 4 (2016-17) Population Assessment of Tobacco and Health Study adult data, we conducted latent class analyses (LCA) of past 30-day frequency of use for 9 tobacco products. One-step LCA with joint multinomial logistic regression models compared sociodemographic factors between users (n = 13,716) and non-users (n = 17,457), and between latent classes of users. We accounted for survey design and weights. Our analyses identified 6 classes: in addition to non-users (C0: 75.7%), we found 5 distinct latent classes of users: daily exclusive cigarette users (C1: 15.5%); occasional cigarette and polytobacco users (C2: 3.8%); frequent e-product and occasional cigarette users (C3: 2.2%); daily smokeless tobacco (SLT) and infrequent cigarette users (C4: 2.0%); and occasional cigar users (C5: 0.8%). Compared to C1: C2 and C3 had higher odds of being male (versus female), younger (especially 18-24 versus 55 years), and having higher education; C2 had higher, while C3 and C4 had lower, odds of being a racial/ethnic minority (versus Non-Hispanic White); C4 and C5 had much higher odds of being male (versus female) and heterosexual (versus sexual minority) and having higher income; and C5 had higher odds of college or more education. We identified three classes of daily or frequent users of a primary product (cigarettes, SLT or e-products) and two classes of occasional users (cigarettes, cigars and polytobacco). Sociodemographic differences in class membership may influence tobacco-related health disparities associated with specific patterns of use.

Transitions between cigarette, ENDS and dual use in adults in the PATH study (waves 1-4): multistate transition modelling accounting for complex survey design.

INTRODUCTION: Even prior to 2018, electronic nicotine delivery systems (ENDS) began to dramatically change the landscape of tobacco products and product use patterns in the USA. METHODS: Using a Markov multistate transition model accounting for complex survey design, transition rates between never, non-current, cigarette, ENDS and dual use states were estimated for 23 253 adult participants in waves 1-4 (approximately 2013-2017) of the Population Assessment of Tobacco and Health study. We made short-term transition projections and estimated HRs for age, sex, race/ethnicity, education and income. RESULTS: Cigarette use was persistent among adults, with 89.7% (95% CI 89.1% to 90.3%) of exclusive cigarette users and 86.1% (95% CI 84.4% to 87.9%) of dual users remaining cigarette users (either exclusive or dual) after one wave. In contrast, ENDS use was less persistent, with 72.1% (95% CI 69.6% to 74.6%) of exclusive ENDS users and 50.5% (95% CI 47.8% to 53.3%) of dual users remaining ENDS users (with or without cigarettes) after one wave. Exclusive ENDS users were more likely to start cigarette use after one wave than either never users (HR 25.2; 95% CI 20.9 to 30.5) or non-current users (HR 5.0; 95% CI 4.3 to 5.8). Dual users of ENDS and cigarettes were more likely to stop using cigarettes than exclusive cigarette users (HR 1.9; 95% CI 1.6 to 2.3). Transition rates varied among sociodemographic groups. CONCLUSIONS: Multistate transition models are an effective tool for uncovering and characterising longitudinal patterns and determinants of tobacco use from complex survey data. ENDS use among US adults was less persistent than cigarette use prior to 2018.

Chemotherapy decisions and patient experience with the recurrence score assay for early-stage breast cancer.

BACKGROUND: The 21-gene recurrence score (RS) assay stratifies early-stage, estrogen receptor-positive breast cancer by recurrence risk. Few studies have examined the ways in which physicians use the RS to recommend adjuvant systemic chemotherapy or patients' experiences with testing and decision making. METHODS: This study surveyed 3880 women treated for breast cancer in 2013-2014; they were identified from the Los Angeles County and Georgia Surveillance, Epidemiology, and End Results registries (response rate, 71%). Women reported chemotherapy recommendations, the receipt of chemotherapy, testing experiences, and decision satisfaction. Registries linked the tumor data, RS, and surveys. Regression models examined factors associated with chemotherapy recommendations and receipt by the RS and subgroups. RESULTS: There were 1527 patients with stage I/II, estrogen receptor/progesterone receptor-positive, human epidermal growth factor 2-negative disease: 778 received an RS (62.6% of patients with node-negative, favorable disease, 24.3% of patients with node-negative, unfavorable disease, and 13.0% of patients with node-positive disease; P < .001). Overall, 47.2% of the patients received a recommendation against chemotherapy, and 40.5% received a recommendation for it. RS results correlated with recommendations: nearly all patients with high scores (31-100) received a chemotherapy recommendation (86.9%-96.5% across clinical subgroups), whereas the majority of the patients with low-risk results (0-18) received a recommendation against it (65.9%-78.2% across subgroups). Most patients with high RSs received chemotherapy (87.0%, 91.1%, and 100% across subgroups), whereas few patients with low scores received it (2.9%, 9.5%, and 26.6% across subgroups). There were no substantial racial/ethnic differences in testing or treatment. Women were largely satisfied with the RS and chemotherapy decisions. CONCLUSIONS: Oncologists use the RS to personalize treatment, even for those with node-positive disease. High satisfaction and an absence of disparities in testing and treatment suggest that precision-medicine advances have improved systemic breast cancer treatment. Cancer 2017;43-51. © 2016 American Cancer Society.

Oncologists' influence on receipt of adjuvant chemotherapy: does it matter whom you see for treatment of curable breast cancer?

PURPOSE: We know little about whether it matters which oncologist a breast cancer patient sees with regard to receipt of chemotherapy. We examined oncologists' influence on use of recurrence score (RS) testing and chemotherapy in the community. METHODS: We identified 7810 women with stages 0-II breast cancer treated in 2013-15 through the SEER registries of Georgia and Los Angeles County. Surveys were sent 2 months post-surgery, (70% response rate, n = 5080). Patients identified their oncologists (n = 504) of whom 304 responded to surveys (60%). We conducted multi-level analyses on patients with ER-positive HER2-negative invasive disease (N = 2973) to examine oncologists' influence on variation in RS testing and chemotherapy receipt, using patient and oncologist survey responses merged to SEER data. RESULTS: Half of patients (52.8%) received RS testing and 27.7% chemotherapy. One-third (35.9%) of oncologists treated >50 new breast cancer patients annually; mean years in practice was 15.8. Oncologists explained 17% of the variation in RS testing but little of the variation in chemotherapy receipt (3%) controlling for clinical factors. Patients seeing an oncologist who was one standard deviation above the mean use of RS testing had over two-times higher odds of receiving RS (2.47, 95% CI 1.47-4.15), but a parallel estimate of the association of oncologist with the odds of receiving chemotherapy was much smaller (1.39, CI 1.03-1.88). CONCLUSIONS: Clinical algorithms have markedly reduced variation in chemotherapy use across oncologists. Oncologists' large influence on variation in RS use suggests that they variably seek tumor profiling to inform treatment decisions.

The influence of 21-gene recurrence score assay on chemotherapy use in a population-based sample of breast cancer patients.

PURPOSE: To quantify the influence of RS assay on changing chemotherapy plans in a general practice setting using causal inference methods. METHODS: We surveyed 3880 newly diagnosed breast cancer patients in Los Angeles and Georgia in 2013-14. We used inverse propensity weighting and multiple imputations to derive complete information for each patient about treatment status with and without testing. RESULTS: A half of the 1545 women eligible for testing (ER+ or PR+, HER2-, and stage I-II) received RS. We estimate that 30% (95% confidence interval (CI) 10-49%) of patients would have changed their treatment selections after RS assay, with 10% (CI 0-20%) being encouraged to undergo chemotherapy and 20% (CI 10-30%) being discouraged from chemotherapy. The subgroups whose treatment selections would be changed the most by RS were patients with positive nodes (44%; CI 24-64%), larger tumor (43% for tumor size >2 cm; CI 23-62%), or younger age (41% for <50 years, CI 23-58%). The assay was associated with a net reduction in chemotherapy use by 10% (CI 4-16%). The reduction was much greater for women with positive nodes (31%; CI 21-41%), larger tumor (30% for tumor size >2 cm; CI 22-38%), or younger age (22% for <50 years; CI 9-35%). CONCLUSION: RS substantially changed chemotherapy treatment selections with the largest influence among patients with less favorable pre-test prognosis. Whether this is optimal awaits the results of clinical trials addressing the utility of RS testing in selected subgroups.

Graphical and numerical diagnostic tools to assess suitability of multiple imputations and imputation models.

Multiple imputation has become a popular approach for analyzing incomplete data. Many software packages are available to multiply impute the missing values and to analyze the resulting completed data sets. However, diagnostic tools to check the validity of the imputations are limited, and the majority of the currently available methods need considerable knowledge of the imputation model. In many practical settings, however, the imputer and the analyst may be different individuals or from different organizations, and the analyst model may or may not be congenial to the model used by the imputer. This article develops and evaluates a set of graphical and numerical diagnostic tools for two practical purposes: (i) for an analyst to determine whether the imputations are reasonable under his/her model assumptions without actually knowing the imputation model assumptions; and (ii) for an imputer to fine tune the imputation model by checking the key characteristics of the observed and imputed values. The tools are based on the numerical and graphical comparisons of the distributions of the observed and imputed values conditional on the propensity of response. The methodology is illustrated using simulated data sets created under a variety of scenarios. The examples focus on continuous and binary variables, but the principles can be used to extend methods for other types of variables. Copyright © 2016 John Wiley & Sons, Ltd.

Propensity score-based diagnostics for categorical response regression models.

For binary or categorical response models, most goodness-of-fit statistics are based on the notion of partitioning the subjects into groups or regions and comparing the observed and predicted responses in these regions by a suitable chi-squared distribution. Existing strategies create this partition based on the predicted response probabilities, or propensity scores, from the fitted model. In this paper, we follow a retrospective approach, borrowing the notion of balancing scores used in causal inference to inspect the conditional distribution of the predictors, given the propensity scores, in each category of the response to assess model adequacy. We can use this diagnostic under both prospective and retrospective sampling designs, and it may ascertain general forms of misspecification. We first present simple graphical and numerical summaries that can be used in a binary logistic model. We then generalize the tools to propose model diagnostics for the proportional odds model. We illustrate the methods with simulation studies and two data examples: (i) a case-control study of the association between cumulative lead exposure and Parkinson's disease in the Boston, Massachusetts, area and (ii) and a cohort study of biomarkers possibly associated with diabetes, from the VA Normative Aging Study.

Conscious Self-Regulation as a Meta-Resource of Academic Achievement and Psychological Well-Being of Young Adolescents.

Background: The role of conscious self-regulation in determining students' psychological well-being and academic performance is considered in the context of the fundamental problem of the regularities of young adolescents' development. Objective: To reveal the role of meta-resources of conscious self-regulation in determining young adolescents' psychological well-being and academic performance. Design: Sample: 500 students in 4th- to 6th grade (10-12) in general schools, 149 of whom participated in a three-year longitudinal study. The Self-Regulation Profile of Learning Activity and the Well-Being Manifestation scales were used. Results: Conscious self-regulation and academic performance increase significantly in fifth grade and decrease in sixth grade. On the contrary, psychological well-being is characterized by a systemic positive dynamic. A typological analysis identified the levels of psychological well-being of students growing, stable, and declining during the transition period. It was found that the general level of conscious self-regulation made a significant positive contribution and is a universal resource for students' psychological well-being and academic performance. Special regulatory resources for academic performance are described, depending on the trajectory of changes in psychological well-being. Increased well-being is determined by the regulatory competencies of Planning and Evaluation of results and its stability by Planning, Modelling, Flexibility, and Responsibility. The general level of self-regulation, regulatory competencies, Planning, Programming and Responsibility mediate in the relationship between student psychological well-being and academic performance. A longitudinal study found that self-regulation has a long-term positive effect on student psychological well-being and academic performance. Conclusion: Conscious self-regulation is a meta-resource that makes a significant contribution to both the psychological well-being and academic performance. Mediator and prognostic effects of self-regulation on these properties create a psychological basis for practical work.

Assessment of Electronic Nicotine Delivery Systems With Cigarette Use and Self-reported Wheezing in the US Adult Population.

Importance: The prevalence of electronic nicotine delivery systems (ENDS) use has increased, leading to a concern about their respiratory health outcomes. It is unclear whether ENDS use increases the risk of wheezing, a common symptom of respiratory conditions. Objective: To provide an analysis of the longitudinal association between ENDS and cigarette use and self-reported wheezing among US adults. Design, Setting, and Participants: The US nationally representative Population Assessment of Tobacco and Health (PATH) Study was used. Longitudinal data for adults 18 years or older from wave 1 (2013-2014) to wave 5 (2018-2019) were analyzed. Data were analyzed from August 2021 to January 2023. Main Outcomes and Measures: The prevalence of self-reported wheezing (waves 2-5) was estimated for 6 strata of tobacco product use (never cigarette and noncurrent ENDS use, never cigarette and current ENDS use, current cigarette and noncurrent ENDS use, current cigarette and current ENDS use, former cigarette and noncurrent ENDS use, and former cigarette and current ENDS use). A generalized estimating equations framework evaluated the association between cigarette and ENDS use and self-reported wheezing at the subsequent wave. An interaction term between cigarette and ENDS use was added to estimate the association between joint cigarette and ENDS use categories and the association of ENDS within strata of cigarette use. Results: The analytical sample consisted of 17 075 US adults with a mean (SD) age of 45.4 (17) years, of whom 8922 (51%) were female and 10 242 (66%) were Non-Hispanic White. When compared with never cigarette and noncurrent ENDS use, the greatest association in reporting wheezing was for current cigarette and current ENDS use (adjusted odds ratio [AOR], 3.26; 95% CI, 2.82-3.77), which was similar to current cigarette and noncurrent ENDS use (AOR, 3.20; 95% CI, 2.91-3.51) and substantially greater than former cigarette and current ENDS use (AOR, 1.94; 95% CI, 1.57-2.41). Associations were small and not statistically significant for the odds of self-reported wheezing among never cigarette and current ENDS use when compared with never cigarette and noncurrent ENDS use (AOR, 1.20; 95% CI, 0.83-1.72), and for odds of wheezing and current cigarette and current ENDS use when compared with current cigarette and noncurrent ENDS use (AOR, 1.02; 95% CI, 0.91-1.15). Conclusions and Relevance: In this cohort study, exclusive ENDS use was not associated with an increase in the risk of self-reported wheezing. However, a small increase in risk between ENDS use and wheezing was reported by individuals who use cigarettes. This study adds to the literature about the potential health effects associated with ENDS use.

Time-varying association between cigarette and ENDS use on incident hypertension among US adults: a prospective longitudinal study.

OBJECTIVE: Electronic nicotine delivery systems (ENDS) products have emerged as the most popular alternative to combustible cigarettes. However, ENDS products contain potentially dangerous toxicants and chemical compounds, and little is known about their health effects. The aim of the present study was to examine the prospective association between cigarette and ENDS use on self-reported incident hypertension. DESIGN: Longitudinal cohort study. SETTING: Nationally representative sample of the civilian, non-institutionalised population in the USA. PARTICIPANTS: 17 539 adults aged 18 or older who participated at follow-up and had no self-reported heart condition or previous diagnosis of hypertension or high cholesterol at baseline. MEASURES: We constructed a time-varying tobacco exposure, lagged by one wave, defined as no use, exclusive established use (every day or some days) of ENDS or cigarettes, and dual use. We controlled for demographics (age, sex, race/ethnicity and household income), clinical risk factors (family history of heart attack, obesity, diabetes and binge drinking) and smoking history (cigarette pack-years). OUTCOMES: Self-reported incident hypertension diagnosis. RESULTS: The self-reported incidence of hypertension was 3.7% between wave 2 and wave 5. At baseline, 18.0% (n=5570) of respondents exclusively smoked cigarettes; 1.1% (n=336) exclusively used ENDS; and 1.7% (n=570) were dual users. In adjusted models, exclusive cigarette use was associated with an increased risk of self-reported incident hypertension compared with non-use (adjusted HR (aHR) 1.21, 95% CI 1.06 to 1.38), while exclusive ENDS use (aHR 1.00, 95% CI 0.68 to 1.47) and dual use (aHR 1.15, 95% CI 0.87 to 1.52) were not. CONCLUSIONS: We found that smoking increased the risk of self-reported hypertension, but ENDS use did not. These results highlight the importance of using prospective longitudinal data to examine the health effects of ENDS use.

Conscious Self-regulation, Motivational Factors, and Personality Traits as Predictors of Students' Academic Performance: A Linear Empirical Model.

Background: The theoretical basis of this study was the resource approach (Morosanova 2014, 2017), in which the conscious self-regulation of learning activity is understood as a meta-resource for students, allowing them to consciously and independently set learning goals and manage their achievement. This approach made it possible to create models of direct and mediate contributions of self-regulation and school engagement not only to academic performance, but also to other motivational and personal competencies. Objective: Our study aimed to investigate the impact of conscious self-regulation, school engagement, motivation, and personality on academic achievement, while taking into account the effects of mediation. Design: A quantitative research design was applied, using data collected from more than 1524 students from the 5th to 11th grades in Russian schools and applying Structural Equation Modelling (SEM). Results: The results allowed us to construct a statistical model of predictors of students' academic achievement. The model was verified on the total sample, as well as samples differing in gender and age. The results show that conscious self-regulation is central to non-cognitive predictors of academic achievement. For the first time, a study has revealed and described the reciprocal relationship between self-regulation, academic motivation, school engagement, and academic performance. The resulting model demonstrates that behavioral and cognitive engagement make a significant contribution to academic performance, while emotional and social engagement do not find significant links with it, although they determine other areas of school life. Conclusion: Our paper investigates the nature and strength of the effects of major non-cognitive predictors of academic achievement. The study results substantiated the resource role of conscious self-regulation not only for students' academic performance, but also for their academic motivation, school engagement, and attitude toward learning. The predictor model of academic achievement we developed will provide a foundation for combining existing heterogeneous concepts into a single integrated model and clarify the contradictions between them.

Association of Genetic Testing Results With Mortality Among Women With Breast Cancer or Ovarian Cancer.

BACKGROUND: Breast cancer and ovarian cancer patients increasingly undergo germline genetic testing. However, little is known about cancer-specific mortality among carriers of a pathogenic variant (PV) in BRCA1/2 or other genes in a population-based setting. METHODS: Georgia and California Surveillance Epidemiology and End Results (SEER) registry records were linked to clinical genetic testing results. Women were included who had stages I-IV breast cancer or ovarian cancer diagnosed in 2013-2017, received chemotherapy, and were linked to genetic testing results. Multivariable Cox proportional hazard models were used to examine the association of genetic results with cancer-specific mortality. RESULTS: 22 495 breast cancer and 4320 ovarian cancer patients were analyzed, with a median follow-up of 41 months. PVs were present in 12.7% of breast cancer patients with estrogen and/or progesterone receptor-positive, HER2-negative cancer, 9.8% with HER2-positive cancer, 16.8% with triple-negative breast cancer, and 17.2% with ovarian cancer. Among triple-negative breast cancer patients, cancer-specific mortality was lower with BRCA1 (hazard ratio [HR] = 0.49, 95% confidence interval [CI] = 0.35 to 0.69) and BRCA2 PVs (HR = 0.60, 95% CI = 0.41 to 0.89), and equivalent with PVs in other genes (HR = 0.65, 95% CI = 0.37 to 1.13), vs noncarriers. Among ovarian cancer patients, cancer-specific mortality was lower with PVs in BRCA2 (HR = 0.35, 95% CI = 0.25 to 0.49) and genes other than BRCA1/2 (HR = 0.47, 95% CI = 0.32 to 0.69). No PV was associated with higher cancer-specific mortality. CONCLUSIONS: Among breast cancer and ovarian cancer patients treated with chemotherapy in the community, BRCA1/2 and other gene PV carriers had equivalent or lower short-term cancer-specific mortality than noncarriers. These results may reassure newly diagnosed patients, and longer follow-up is ongoing.

The Dynamics of the Interrelationships between Conscious Self-regulation, Psychological Well-being and School-related Subjective Well-being in Adolescents: A Three-year Cross-lagged Panel Study.

Background: Recently, research on psychological well-being and its dynamics and predictors in adolescence, has gained special attention, due to the importance of well-being for mental and physical health, as well as for success in different activities. Self-regulation (SR) is considered a significant resource for maintaining psychological and school-related subjective well-being. Objective: The purpose of our study was to identify the role of conscious SR in maintaining pupils' satisfaction with school life, and to assess the contribution of conscious SR to the development of psychological well-being in adolescence. Design: Two three-year longitudinal studies were carried out on samples of young adolescents in Russian schools (N = 148; N = 132; 10-13 years). The studies utilized methods for assessing conscious SR, psychological well-being (PWB), and school-related subjective well-being (SWB), the latter being the cognitive component of life satisfaction. Results: Our research revealed differences in the dynamics of PWB and SWB levels in adolescents during their transition from primary to basic secondary school. It also identified the specifics of longitudinal relationships between conscious SR, PWB, and SWB in adolescence. We showed that there was a reciprocal relationship between them. However, the most significant cross-longitudinal effects were established between SR and school-related SWB. These effects changed over time: at the beginning, well-being acted as a significant factor of self-regulation, while later self-regulation acted as a significant resource for maintaining adolescent well-being in the subsequent years. Conclusion: School-related SWB is characterized by the most pronounced trajectory of change, while PWB is characterized by greater stability and insignificant growth. Our three-year longitudinal study demonstrated that the link between self-regulation and well-being is consistently reproduced. Conscious self-regulation is a significant resource for both the psychological and school subjective well-being of adolescents.

Using multiple imputation to classify potential outcomes subgroups.

With medical tests becoming increasingly available, concerns about over-testing, over-treatment and health care cost dramatically increase. Hence, it is important to understand the influence of testing on treatment selection in general practice. Most statistical methods focus on average effects of testing on treatment decisions. However, this may be ill-advised, particularly for patient subgroups that tend not to benefit from such tests. Furthermore, missing data are common, representing large and often unaddressed threats to the validity of most statistical methods. Finally, it is often desirable to conduct analyses that can be interpreted causally. Using the Rubin Causal Model framework, we propose to classify patients into four potential outcomes subgroups, defined by whether or not a patient's treatment selection is changed by the test result and by the direction of how the test result changes treatment selection. This subgroup classification naturally captures the differential influence of medical testing on treatment selections for different patients, which can suggest targets to improve the utilization of medical tests. We can then examine patient characteristics associated with patient potential outcomes subgroup memberships. We used multiple imputation methods to simultaneously impute the missing potential outcomes as well as regular missing values. This approach can also provide estimates of many traditional causal quantities of interest. We find that explicitly incorporating causal inference assumptions into the multiple imputation process can improve the precision for some causal estimates of interest. We also find that bias can occur when the potential outcomes conditional independence assumption is violated; sensitivity analyses are proposed to assess the impact of this violation. We applied the proposed methods to examine the influence of 21-gene assay, the most commonly used genomic test in the United States, on chemotherapy selection among breast cancer patients.

Multiple imputation with missing data indicators.

Multiple imputation is a well-established general technique for analyzing data with missing values. A convenient way to implement multiple imputation is sequential regression multiple imputation, also called chained equations multiple imputation. In this approach, we impute missing values using regression models for each variable, conditional on the other variables in the data. This approach, however, assumes that the missingness mechanism is missing at random, and it is not well-justified under not-at-random missingness without additional modification. In this paper, we describe how we can generalize the sequential regression multiple imputation imputation procedure to handle missingness not at random in the setting where missingness may depend on other variables that are also missing but not on the missing variable itself, conditioning on fully observed variables. We provide algebraic justification for several generalizations of standard sequential regression multiple imputation using Taylor series and other approximations of the target imputation distribution under missingness not at random. Resulting regression model approximations include indicators for missingness, interactions, or other functions of the missingness not at random missingness model and observed data. In a simulation study, we demonstrate that the proposed sequential regression multiple imputation modifications result in reduced bias in the final analysis compared to standard sequential regression multiple imputation, with an approximation strategy involving inclusion of an offset in the imputation model performing the best overall. The method is illustrated in a breast cancer study, where the goal is to estimate the prevalence of a specific genetic pathogenic variant.

Symptom clusters predict risk of metabolic-syndrome and diabetes in midlife: the Study of Women's Health Across the Nation.

PURPOSE: Women's cardio-metabolic risk increases in midlife. Previous work relating menopause symptoms to diabetes/Metabolic Syndrome (MetS) does not consider the adverse impact of multiple concurrent physical and psychological symptoms in midlife. METHODS: Data are from 3097 participants in the Study of Women's Health Across the Nation, a cohort of midlife women followed for over 20 years. Baseline latent symptom classes (LSC) were derived from 58 questions assessing physical, psychological and menopausal symptoms. Six identified LSCs ranged from 1 (most symptoms present at high severity) to 6 (few symptoms present at low severity). Accelerated failure time models estimated time to onset of type 2 diabetes and MetS for each LSC. RESULTS: Women with multiple high/moderate severity symptoms had an earlier onset of diabetes (13.2%, 14.1% and 20.8% earlier onset in LSCs 1, 2, 3, respectively) and MetS (15.5%, 13.0% and 19.7% earlier onset in LSCs 1, 2, 3, respectively) than women with few/low severity symptoms. CONCLUSIONS: Having multiple concurrent moderate to high intensity physical and psychological symptoms in midlife are associated with early onset of diabetes and MetS. Monitoring and subsequent intervention on a broad range of symptoms in midlife may significantly mitigate cardio-metabolic risk during this critical life stage.

Time Trends in Receipt of Germline Genetic Testing and Results for Women Diagnosed With Breast Cancer or Ovarian Cancer, 2012-2019.

PURPOSE: Genetic testing is important for breast and ovarian cancer risk reduction and treatment, yet little is known about its evolving use. METHODS: SEER records of women of age ≥ 20 years diagnosed with breast or ovarian cancer from 2013 to 2017 in California or Georgia were linked to the results of clinical germline testing through 2019. We measured testing trends, rates of variants of uncertain significance (VUS), and pathogenic variants (PVs). RESULTS: One quarter (25.2%) of 187,535 patients with breast cancer and one third (34.3%) of 14,689 patients with ovarian cancer were tested; annually, testing increased by 2%, whereas the number of genes tested increased by 28%. The prevalence of test results by gene category for breast cancer cases in 2017 were BRCA1/2, PVs 5.2%, and VUS 0.8%; breast cancer-associated genes or ovarian cancer-associated genes (ATM, BARD1, BRIP1, CDH1, CHEK2, EPCAM, MLH1, MSH2, MSH6, NBN, NF1, PALB2, PMS2, PTEN, RAD51C, RAD51D, STK11, and TP53), PVs 3.7%, and VUS 12.0%; other actionable genes (APC, BMPR1A, MEN1, MUTYH, NF2, RB1, RET, SDHAF2, SDHB, SDHC, SDHD, SMAD4, TSC1, TSC2, and VHL) PVs 0.6%, and VUS 0.5%; and other genes, PVs 0.3%, and VUS 2.6%. For ovarian cancer cases in 2017, the prevalence of test results were BRCA1/2, PVs 11.0%, and VUS 0.9%; breast or ovarian genes, PVs 4.0%, and VUS 12.6%; other actionable genes, PVs 0.7%, and VUS 0.4%; and other genes, PVs 0.3%, and VUS 0.6%. VUS rates doubled over time (2013 diagnoses: 11.2%; 2017 diagnoses: 26.8%), particularly for racial or ethnic minorities (47.8% Asian and 46.0% Black, v 24.6% non-Hispanic White patients; P < .001). CONCLUSION: A testing gap persists for patients with ovarian cancer (34.3% tested v nearly all recommended), whereas adding more genes widened a racial or ethnic gap in VUS results. Most PVs were in 20 breast cancer-associated genes or ovarian cancer-associated genes; testing other genes yielded mostly VUS. Quality improvement should focus on testing indicated patients rather than adding more genes.

Improving on analyses of self-reported data in a large-scale health survey by using information from an examination-based survey.

Common data sources for assessing the health of a population of interest include large-scale surveys based on interviews that often pose questions requiring a self-report, such as, 'Has a doctor or other health professional ever told you that you have health condition of interest?' or 'What is your (height/weight)?' Answers to such questions might not always reflect the true prevalences of health conditions (for example, if a respondent misreports height/weight or does not have access to a doctor or other health professional). Such 'measurement error' in health data could affect inferences about measures of health and health disparities. Drawing on two surveys conducted by the National Center for Health Statistics, this paper describes an imputation-based strategy for using clinical information from an examination-based health survey to improve on analyses of self-reported data in a larger interview-based health survey. Models predicting clinical values from self-reported values and covariates are fitted to data from the National Health and Nutrition Examination Survey (NHANES), which asks self-report questions during an interview component and also obtains clinical measurements during a physical examination component. The fitted models are used to multiply impute clinical values for the National Health Interview Survey (NHIS), a larger survey that obtains data solely via interviews. Illustrations involving hypertension, diabetes, and obesity suggest that estimates of health measures based on the multiply imputed clinical values are different from those based on the NHIS self-reported data alone and have smaller estimated standard errors than those based solely on the NHANES clinical data. The paper discusses the relationship of the methods used in the study to two-phase/two-stage/validation sampling and estimation, along with limitations, practical considerations, and areas for future research.