Multiple Outcomes Of Interest Research Articles

Exploring the physiological factors relating to energy balance in women with polycystic ovary syndrome: a scoping review.

Polycystic ovary syndrome (PCOS) occurs in 8%-13% of reproductive-aged women and is associated with reproductive, metabolic, and psychological dysfunction. Overweight and obesity are prevalent and exacerbate the features of PCOS. The aim of this review is to evaluate the extent of evidence examining the physiological factors affecting energy homeostasis, which may impact weight gain, weight loss, and weight maintenance in PCOS, and identify research gaps and recommendations for future research. Literature searches using MEDLINE, EMBASE, PsycInfo, AMED, CINAHL, and Cochrane Central Register of Controlled Trials were conducted up to June 22, 2022. Abstracts, non-English-language articles, and reviews were excluded. A total of n = 78 (n = 55 energy intake and n = 23 energy expenditure) primary research papers were included. Papers with multiple outcomes of interest were counted as separate studies. Energy-intake studies (n = 89) focussed on assessing food, nutrient, or supplements stimuli and were grouped into the outcomes of gastrointestinal appetite hormones (n = 43), adipokines (n = 34), subjective appetite (n = 9), functional brain imaging (n = 3), and neuropeptides (n = 0). Energy-expenditure studies (n = 29) were grouped into total energy expenditure (n = 1), resting energy expenditure (n = 15), meal-induced thermogenesis (n = 3), nutrient oxidation (n = 5), and metabolic flexibility (n = 5). Across both energy-intake and -expenditure papers, 60% of the studies compared outcome responses in women with PCOS with a control group. Results were inconsistent, with 57% reporting no differences and 43% reporting altered responses in PCOS compared with controls, including blunted appetite hormone responses, metabolic inflexibility, and reduced energy expenditure. The authors identified that there is inconsistent, yet preliminary, evidence of possible altered physiological factors, which may impact energy balance and weight management. Further work is needed to act on the identified clinical and research gaps to support women with PCOS and health professionals in informing and achieving realistic weight-management goals for women with PCOS. Systematic Review Registration: The protocol was prospectively registered on the Open Science Framework on February 16, 2021 (https://osf.io/9jnsm).

Appropriate design and reporting of superiority, equivalence and non-inferiority clinical trials incorporating a benefit-risk assessment: the BRAINS study including expert workshop.

Randomised controlled trials are designed to assess the superiority, equivalence or non-inferiority of a new health technology, but which trial design should be used is not always obvious in practice. In particular, when using equivalence or non-inferiority designs, multiple outcomes of interest may be important for the success of a trial, despite the fact that usually only a single primary outcome is used to design the trial. Benefit-risk methods are used in the regulatory clinical trial setting to assess multiple outcomes and consider the trade-off of the benefits against the risks, but are not regularly implemented in publicly funded trials. The aim of the project is to aid the design of clinical trials with multiple outcomes of interest by defining when each trial design is appropriate to use and identifying when to use benefit-risk methods to assess outcome trade-offs (qualitatively or quantitatively) in a publicly funded trial setting. A range of methods was used to elicit expert opinion to answer the project objectives, including a web-based survey of relevant researchers, a rapid review of current literature and a 2-day consensus workshop of experts (in 2019). We created a list of 19 factors to aid researchers in selecting the most appropriate trial design, containing the following overarching sections: population, intervention, comparator, outcomes, feasibility and perspectives. Six key reasons that indicate a benefit-risk method should be considered within a trial were identified: (1) when the success of the trial depends on more than one outcome; (2) when important outcomes within the trial are in competing directions (i.e. a health technology is better for one outcome, but worse for another); (3) to allow patient preferences to be included and directly influence trial results; (4) to provide transparency on subjective recommendations from a trial; (5) to provide consistency in the approach to presenting results from a trial; and (6) to synthesise multiple outcomes into a single metric. Further information was provided to support the use of benefit-risk methods in appropriate circumstances, including the following: methods identified from the review were collated into different groupings and described to aid the selection of a method; potential implementation of methods throughout the trial process were provided and discussed (with examples); and general considerations were described for those using benefit-risk methods. Finally, a checklist of five pieces of information that should be present when reporting benefit-risk methods was defined, with two additional items specifically for reporting the results. These recommendations will assist research teams in selecting which trial design to use and deciding whether or not a benefit-risk method could be included to ensure research questions are answered appropriately. Additional information is provided to support consistent use and clear reporting of benefit-risk methods in the future. The recommendations can also be used by funding committees to confirm that appropriate considerations of the trial design have been made. This research was limited in scope and should be considered in conjunction with other trial design methodologies to assess appropriateness. In addition, further research is needed to provide concrete information about which benefit-risk methods are best to use in publicly funded trials, along with recommendations that are specific to each method. The rapid review is registered as PROSPERO CRD42019144882. Funded by the Medical Research Council UK and the National Institute for Health and Care Research as part of the Medical Research Council-National Institute for Health and Care Research Methodology Research programme.

Two-stage multivariate Mendelian randomization on multiple outcomes with mixed distributions.

In clinical research, it is important to study whether certain clinical factors or exposures have causal effects on clinical and patient-reported outcomes such as toxicities, quality of life, and self-reported symptoms, which can help improve patient care. Usually, such outcomes are recorded as multiple variables with different distributions. Mendelian randomization (MR) is a commonly used technique for causal inference with the help of genetic instrumental variables to deal with observed and unobserved confounders. Nevertheless, the current methodology of MR for multiple outcomes only focuses on one outcome at a time, meaning that it does not consider the correlation structure of multiple outcomes, which may lead to a loss of statistical power. In situations with multiple outcomes of interest, especially when there are mixed correlated outcomes with different distributions, it is much more desirable to jointly analyze them with a multivariate approach. Some multivariate methods have been proposed to model mixed outcomes; however, they do not incorporate instrumental variables and cannot handle unmeasured confounders. To overcome the above challenges, we propose a two-stage multivariate Mendelian randomization method (MRMO) that can perform multivariate analysis of mixed outcomes using genetic instrumental variables. We demonstrate that our proposed MRMO algorithm can gain power over the existing univariate MR method through simulation studies and a clinical application on a randomized Phase III clinical trial study on colorectal cancer patients.

Suicidal Behaviour, including Ideation and Self-Harm, in Young Migrants: A Systematic Review

Young people experience high rates of suicidal ideation, self-harm, suicide attempt and death due to suicide. As a result of increasing globalisation, young people are increasingly mobile and can migrate from one country to another seeking educational and employment opportunities. With a growing number of young migrants, it is important to understand the prevalence of suicidal behaviour among this population group. We systematically searched Medline, Embase, and PsycINFO from inception until 31 March 2022. Eligible studies were those providing data on suicidal ideation, self-harm, suicide attempt, and death due to suicide. Seventeen studies were included in the review, some of which provided data on multiple outcomes of interest. Twelve studies provided data on suicidal ideation, five provided data on self-harm, eight provided data on suicide attempt, and one study had data on suicide death among young migrants. The quality of the included studies was varied and limited. The studies included in this review commonly reported that young migrants experience higher rates of self-harm and suicide attempt, but no major differences in suicidal ideation and suicide death compared to non-migrant young people. However, the limited number of studies focused on suicidal behaviour among young migrants highlights the need for further high-quality studies to capture accurate information. This will enable the development of policies and interventions that reduce the risk of suicidal behaviour among young migrants.

Military service experiences and reasons for service separation among lesbian, gay, and bisexual individuals in a large military cohort

BackgroundThe well-being of lesbian, gay, and bisexual (LGB) individuals is a topic of increasing concern within the military where significant institutional barriers, targeted aggression, and differential organizational policies such as “Don’t Ask Don’t Tell” have historically contributed to experiences of exclusion and discrimination. However, limited research has examined specific military and post-separation experiences among LGB service members and veterans. The goal of this study was to examine differences in military and service separation experiences by sexual orientation among a large representative sample of United States service members and veterans.MethodsSurvey data from the 2016 Millennium Cohort Study follow-up questionnaire were used to assess sexual orientation and multiple outcomes of interest: military experiences (morale, feelings about the military, missed workdays) and service separation experiences (reasons for separation, post-separation employment). The associations between sexual orientation (LGB versus heterosexual) and each of these outcomes were evaluated in a series of adjusted logistic regression models, stratified by sex when interactions were observed.ResultsOf the 99,599 participants, 3.4% identified as LGB. In adjusted models, LGB service members had significantly higher odds than heterosexual service members of feeling: unimpressed by the quality of unit leadership, unsupported by the military, and negative about the military overall. Bisexual women were more likely than heterosexual women to feel less unit camaraderie; both gay and bisexual men felt less camaraderie than heterosexual men. LGB veterans were more likely than heterosexual peers of the same sex to separate from service due to unplanned administrative reasons. Compared to heterosexual women, lesbian and bisexual women were more likely to separate from service due to dissatisfaction with promotions/pay and disability/medical reasons, while bisexual women specifically separated due to dissatisfaction with leadership and incompatibility with the military. Gay and bisexual men also reported separating due to incompatibility with the military, but only bisexual men were more likely to report separating due to disability/medical reasons compared to heterosexual men.ConclusionsLess positive military- and separation-specific experiences disproportionately affected LGB service members in this study. Promoting inclusion and increasing support for LGB service members may improve satisfaction with military service and retention.

The Hassan Neonatal Morbidity Composite Scale and Neonatal Length of Stay-A Validation Study.

Obstetric studies often report neonatal morbidity as a composite score. Composite scores can simplify data analysis when multiple outcomes of interest are present and allows researchers to conduct smaller, more manageable trials. The Hassan scale is a neonatal morbidity composite scale that assigns high scores to infants with multiple morbidities and low scores to infants without or with single morbidities. The objective of this study was to validate the association between scores on the Hassan scale and neonatal intensive care unit (NICU) length of stay STUDY DESIGN: We conducted a cohort study of all infants born between 22 and 366/7 weeks' gestation and cared for within 419 neonatal units in the Pediatrix Medical Group between 1997 and 2018. Each infant was assigned a Hassan's score based on the number of neonatal morbidity events that occurred during the delivery hospitalization. The association between Hassan's scores and neonatal length of stay was evaluated using linear regression. Multivariable models were constructed to determine if the Hassan score was independently associated with neonatal length of stay. There were 760,037 infants included. The median (interquartile range [IQR]) gestational age of delivery was 34 (31, 35) weeks and the median (IQR) birth weight at delivery was 2,000 (1,503, 2,430) g. The median length of stay for infants discharged home was 17 (10-33) days. A Hassan's score was able to be assigned to 699,206 (92%) patients. Neonatal morbidities included in the Hassan scale were more common among infants born earlier in gestation. On adjusted analysis, the Hassan scale was found to be independently associated with neonatal length of stay (p < 0.001, coefficient = 10.4 days [95% confidence interval (CI): 10.3, 10.4 days]) with higher scores associated with longer lengths of stay. The Hassan scale, more than a binary composite score, is able to differentiate preterm infants with prolonged hospitalizations from those with short hospitalizations. · The Hassan scale is an independent predictor of neonatal length of stay.. · Classification of infants based on number of morbidities correlates with neonatal length of stay.. · The Hassan scale provided better discrimination than binary composite morbidity scores.. · The Hassan scale may be an economic predictor of health-related costs..

A comparison between the piecewise and parallel-process piecewise latent growth models

The piecewise latent growth models (PWLGMs) can be used to study changes in the growth trajectory of an outcome due to an event or condition, such as exposure to an intervention. When there are multiple outcomes of interest, a researcher may choose to fit a series of PWLGMs or a single parallel-process PWLGM. A comparison of these models is provided with an illustrative example using data from the Early Childhood Longitudinal Study, Kindergarten Class of 2010-11 (ECLS-K:2011), and a Monte Carlo simulation study. Conditions manipulated included sample size, location of the transition point, the number of time points, and covariate effect size. The results showed that the power to test parameter estimates with both models depended on the two-way interaction of sample size and covariate effect, and the three-way interaction of sample size by the number of time points by transition point location. Parameter coverage also depended on the three-way interaction of sample size by the number of time points by the transition point location. Recommendations for the use of the PWLGM are provided.

COVID-19 Outcomes in Individuals with Sickle Cell Disease and Sickle Cell Trait Compared to Blacks without Sickle Cell Disease or Trait

Introduction: By August 1, 2020 in the United States, more than 3 million cases of Coronavirus disease 2019 (COVID-19) had been reported with more than 150,000 deaths due to this disease. Growing evidence suggests that individuals with the pre-existing conditions of hypertension, diabetes, cardiovascular disease and obesity are at a higher risk of more serious COVID-19 illness. However, the impact of COVID-19 on individuals with sickle cell disease and sickle cell trait as compared to those without sickle cell disease or trait is not known. The objective of this study was to determine the rate of hospitalization, disease symptoms and deaths due to COVID-19, in patients with sickle cell disease and sickle cell trait compared to Blacks without sickle cell disease or trait.Methods: We leveraged existing electronic health record (EHR) data from multiple sites that contribute data to a research network, TriNetX. TriNetX query platform was used to identify patients with COVID-19 infection based on ICD diagnoses codes or a positive COVID-19 result from a nucleic acid amplification with probe-based detection test, present any time after January 20, 2020 (this is when the first COVID-19 case was detected in the United States) within the patients’ EHR data. We report rates of specific COVID-19 related outcomes among individuals with sickle cell disease and trait, calculated as % of patients in cohort with the particular outcome. Our outcomes of interest included COVD-19 related symptoms, hospitalization, and death, which occurred within 2 weeks of COVID diagnosis. We used propensity score matching (greedy nearest-neighbor matching algorithm with a caliper of 0.1 pooled standard deviations) to create balanced cohorts for comparing outcomes between individuals with sickle cell disease or trait and Blacks without sickle cell disease or trait. Risk ratios and risk differences are reported along with 95% confidence intervals. Given multiple outcomes of interest, we considered a more stringent two-sided alpha of less than <0.01, based on a z-test, to determine statistical significance for differences in outcome rates.Results: As of July 15, 2020, there were 122 COVID-19 patients who had sickle cell disease and 172 COVID-19 patients who had sickle cell trait. Our comparator groups included 15,762 Blacks who were diagnosed with COVID-19 but did not have sickle cell trait/disease. COVID-19 patients with sickle cell disease were significantly younger and a higher proportion had asthma, type 1 diabetes and pre-existing liver conditions compared to Blacks without sickle cell trait/disease (Table 1). COVID-19 patients with sickle cell trait were significantly younger, a higher proportion were females, overweight/obese, and a higher proportion had asthma or type 1 diabetes compared to Blacks without sickle cell trait/disease (Table 1). The rate of respective outcomes for the three groups is shown in Figure 1. Propensity score matching yielded a cohort of patients such that there were no significant differences in demographic and clinical characteristics between patients with sickle cell disease/trait compared to Blacks without sickle cell trait/disease. After matching, COVID patients with sickle cell disease remained at a higher risk of hospitalization, pneumonia and pain compared to Blacks without sickle cell trait/disease (Table 2). The case fatality rates were not significantly different between those with sickle cell disease compared to Blacks. There were no significant differences in COVID outcomes between sickle cell trait and Blacks without sickle cell trait/disease, within the matched cohort.Conclusions: These data provide evidence that sickle cell disease imposes additional risk of severe COVID-19 illness and hospitalization, after balancing for age, gender and other preexisting conditions. The death rate between sickle cell disease and Blacks without sickle cell trait/disease was not significantly different. There are no significant differences in COVID-19 outcomes between sickle cell trait and Blacks without sickle cell trait/disease, after balancing for age, gender and other pre-existing conditions.DisclosuresBrandow:NIH / NHLBI: Research Funding; Greater Milwaukee Foundation: Research Funding. Panepinto:HRSA: Research Funding; NINDS: Research Funding; NINDS: Research Funding; NHLBI: Research Funding.

Systematic scoping review of frameworks used to develop rehabilitation interventions for older adults

ObjectivesRehabilitation interventions for older adults are complex as they involve a number of interacting components, have multiple outcomes of interest and are influenced by a number of contextual factors. The...

Multiple hypothesis testing in experimental economics

The analysis of data from experiments in economics routinely involves testing multiple null hypotheses simultaneously. These different null hypotheses arise naturally in this setting for at least three different reasons: when there are multiple outcomes of interest and it is desired to determine on which of these outcomes a treatment has an effect; when the effect of a treatment may be heterogeneous in that it varies across subgroups defined by observed characteristics and it is desired to determine for which of these subgroups a treatment has an effect; and finally when there are multiple treatments of interest and it is desired to determine which treatments have an effect relative to either the control or relative to each of the other treatments. In this paper, we provide a bootstrap-based procedure for testing these null hypotheses simultaneously using experimental data in which simple random sampling is used to assign treatment status to units. Using the general results in Romano and Wolf (Ann Stat 38:598–633, 2010), we show under weak assumptions that our procedure (1) asymptotically controls the familywise error rate—the probability of one or more false rejections—and (2) is asymptotically balanced in that the marginal probability of rejecting any true null hypothesis is approximately equal in large samples. Importantly, by incorporating information about dependence ignored in classical multiple testing procedures, such as the Bonferroni and Holm corrections, our procedure has much greater ability to detect truly false null hypotheses. In the presence of multiple treatments, we additionally show how to exploit logical restrictions across null hypotheses to further improve power. We illustrate our methodology by revisiting the study by Karlan and List (Am Econ Rev 97(5):1774–1793, 2007) of why people give to charitable causes.

What Is Known: Examining the Empirical Literature in Resident Work Hours Using 30 Influential Articles.

Examining influential, highly cited articles can show the advancement of knowledge about the effect of resident physicians' long work hours, as well as the benefits and drawbacks of work hour limits. A narrative review of 30 articles, selected for their contribution to the literature, explored outcomes of interest in the research on work hours-including patient safety, learning, and resident well-being. Articles were selected from a comprehensive review. Citation volume, quality, and contribution to the evolving thinking on work hours and to the Accreditation Council for Graduate Medical Education standards were assessed. Duty hour limits are supported by the scientific literature, particularly limits on weekly hours and reducing the frequency of overnight call. The literature shows declining hours and call frequency over 4 decades of study, although the impact on patient safety, learning, and resident well-being is not clear. The review highlighted limitations of the scientific literature on resident hours, including small samples and reduced generalizability for intervention studies, and the inability to rule out confounders in large studies using administrative data. Key areas remain underinvestigated, and accepted methodology is challenged when assessing the impact of interventions on the multiple outcomes of interest. The influential literature, while showing the beneficial effect of work hour limits, does not answer all questions of interest in determining optimal limits on resident hours. Future research should use methods that permit a broader, collective examination of the multiple, often competing attributes of the learning environment that collectively promote patient safety and resident learning and well-being.

Analyzing Multiple Outcomes: Is it Really Worth the use of Multivariate Linear Regression?

In health related research it is common to have multiple outcomes of interest in a single study. These outcomes are often analysed separately, ignoring the correlation between them. One would expect that a multivariate approach would be a more efficient alternative to individual analyses of each outcome. Surprisingly, this is not always the case. In this article we discuss different settings of linear models and compare the multivariate and univariate approaches. We show that for linear regression models, the estimates of the regression parameters associated with covariates that are shared across the outcomes are the same for the multivariate and univariate models while for outcome-specific covariates the multivariate model performs better in terms of efficiency.

Complications following young femoral neck fractures

BackgroundFemoral neck fractures in patients 60 years of age or younger are challenging injuries to treat because of the high-energy trauma mechanisms and the displaced fracture patterns typically found in this patient population. Understanding the burden of disease is an important first step in addressing treatment controversies in this population. The purpose of the current study is to quantitatively pool the incidence of patient important complications following internal fixation of young femoral neck fractures. MethodsA comprehensive search of the Medline, Embase, CINAHL, Cochrane Database of Systematic Reviews, and Central databases was completed under the direction of a biomedical librarian. Multiple outcomes of interest (complications) were collected and included: reoperation, femoral head avascular necrosis, fracture non-union, infection, implant failure, and malunion. Results1558 fractures from 41 studies were included in the meta-analysis. An18.0% pooled reoperation incidence was observed for isolated femoral neck fractures. The total pooled incidence of avascular necrosis (AVN) was 14.3%, and the total incidence of nonunion was 9.3%. When stratified for fracture displacement displaced fractures were more likely to undergo reoperation and to result in AVN or non-union. The total incidence of malunion was 7.1%, implant failure was 9.7%, and surgical site infection was 5.1%. Complications associated with a femoral neck fracture treated in conjunction with an ipsilateral femoral shaft fracture were lower overall than the pooled estimates for isolated neck fractures. ConclusionsThe results of our analysis demonstrate that the incidence of complications experienced by young femoral neck fracture patients is relatively high. Reoperation following internal fixation of isolated femoral neck fractures occurred in nearly 20% of cases, and AVN and nonunion were the most common complications that likely contributed to repeat surgeries. These results highlight the importance of further efforts to improve the clinical outcomes in this population.

Joint Hypothesis Testing and Gatekeeping Procedures for Studies with Multiple Endpoints

A claim of superiority of one intervention over another often depends naturally on results from several outcomes of interest. For such studies the common practice of making conclusions about individual outcomes in isolation can be problematic. For example, an intervention might be shown to improve one outcome (e.g., pain score) but worsen another (e.g., opioid consumption), making interpretation difficult. We thus advocate joint hypothesis testing, in which the decision rule used to claim success of an intervention over its comparator with regard to the multiple outcomes are specified a priori, and the overall type I error is protected. Success might be claimed only if there is a significant improvement detected in all primary outcomes, or alternatively, in at least one of them. We focus more specifically on demonstrating superiority on at least one outcome and noninferiority (i.e., not worse) on the rest. We also advocate the more general "gatekeeping" procedures (both serial and parallel), in which primary and secondary hypotheses of interest are a priori organized into ordered sets, and testing does not proceed to the next set, i.e., through the "gate," unless the significance criteria for the previous sets are satisfied, thus protecting the overall type I error. We demonstrate methods using data from a randomized controlled trial assessing the effects of transdermal nicotine on pain and opioids after pelvic gynecological surgery. Joint hypothesis testing and gatekeeping procedures are shown to substantially improve the efficiency and interpretation of randomized and nonrandomized studies having multiple outcomes of interest.

Continuously monitored stopping boundary methodologies: the issues of sensitivity, association and trial suspension.

Thall et al. consider a continuous monitoring strategy for multiple discrete outcomes to determine whether a trial should terminate early. We evaluate important issues raised in the application of a continuous monitoring strategy for multiple outcomes. Specifically, we evaluate: (i) the sensitivity of such a methodology to small perturbations in the stopping boundaries; (ii) the need to employ accrual buffers when a trial approaches a stopping boundary-a large buffer implying that temporary suspension is unwarranted; and (iii) the role of association among the multiple outcomes of interest. Simulation studies demonstrate that the methodology is sensitive to small perturbations in the stopping boundaries, that the size of an accrual buffer can vary widely over the course of a trial, and that the extent of association among multiple outcomes plays a large role in determining the stopping properties of a trial. We illustrate these issues using the HLA non-identical donor bone marrow transplant trial, with two discrete outcomes.