Characterizing quantile-varying covariate effects under the accelerated failure time model.

An important task in survival analysis is choosing a structure for the relationship between covariates of interest and the time-to-event outcome. For example, the accelerated failure time (AFT) model structures each covariate effect as a constant multiplicative shift in the outcome distribution across all survival quantiles. Though parsimonious, this structure cannot detect or capture effects that differ across quantiles of the distribution, a limitation that is analogous to only permitting proportional hazards in the Cox model. To address this, we propose a general framework for quantile-varying multiplicative effects under the AFT model. Specifically, we embed flexible regression structures within the AFT model and derive a novel formula for interpretable effects on the quantile scale. A regression standardization scheme based on the g-formula is proposed to enable the estimation of both covariate-conditional and marginal effects for an exposure of interest. We implement a user-friendly Bayesian approach for the estimation and quantification of uncertainty while accounting for left truncation and complex censoring. We emphasize the intuitive interpretation of this model through numerical and graphical tools and illustrate its performance through simulation and application to a study of Alzheimer's disease and dementia.

Disparities in cancer incidence by sexual orientation.

INTRODUCTION: Cancer risk factors are more common among sexual minority populations (e.g., lesbian, bisexual) than their heterosexual peers, yet little is known about cancer incidence across sexual orientation groups. METHODS: The 1989-2017 data from the Nurses' Health Study II, a longitudinal cohort of female nurses across the United States, were analyzed (N = 101,543). Sexual orientation-related cancer disparities were quantified by comparing any cancer incidence among four sexual minority groups based on self-disclosure-(1) heterosexual with past same-sex attractions/partners/identity; (2) mostly heterosexual; (3) bisexual; and (4) lesbian women-to completely heterosexual women using age-adjusted incidence rate ratios (aIRR) calculated by the Mantel-Haenszel method. Additionally, subanalyses at 21 cancer disease sites (e.g., breast, colon/rectum) were conducted. RESULTS: For all-cancer analyses, there were no statistically significant differences in cancer incidence at the 5% type I error cutoff among sexual minority groups when compared to completely heterosexual women; the aIRR was 1.17 (95% CI,0.99-1.38) among lesbian women and 0.80 (0.58-1.10) among bisexual women. For the site-specific analyses, incidences at multiple sites were significantly higher among lesbian women compared to completely heterosexual women: thyroid cancer (aIRR, 1.87 [1.03-3.41]), basal cell carcinoma (aIRR, 1.85 [1.09-3.14]), and non-Hodgkin lymphoma (aIRR, 2.13 [1.10-4.12]). CONCLUSION: Lesbian women may be disproportionately burdened by cancer relative to their heterosexual peers. Sexual minority populations must be explicitly included in cancer prevention efforts. Comprehensive and standardized sexual orientation data must be systematically collected so nuanced sexual orientation-related cancer disparities can be accurately assessed for both common and rare cancers.

Two-phase stratified sampling and analysis for predicting binary outcomes.

The two-phase study design is a cost-efficient sampling strategy when certain data elements are expensive and, thus, can only be collected on a sub-sample of subjects. To date guidance on how best to allocate resources within the design has assumed that primary interest lies in estimating association parameters. When primary interest lies in the development and evaluation of a risk prediction tool, however, such guidance may, in fact, be detrimental. To resolve this, we propose a novel strategy for resource allocation based on oversampling cases and subjects who have more extreme risk estimates according to a preliminary model developed using fully observed predictors. Key to the proposed strategy is that it focuses on enhancing efficiency regarding estimation of measures of predictive accuracy, rather than on efficiency regarding association parameters which is the standard paradigm. Towards valid estimation and inference for accuracy measures using the resultant data, we extend an existing semiparametric maximum likelihood ethod for estimating odds ratio association parameters to accommodate the biased sampling scheme and data incompleteness. Motivated by our sampling design, we additionally propose a general post-stratification scheme for analyzing general two-phase data for estimating predictive accuracy measures. Through theoretical calculations and simulation studies, we show that the proposed sampling strategy and post-stratification scheme achieve the promised efficiency improvement. Finally, we apply the proposed methods to develop and evaluate a preliminary model for predicting the risk of hospital readmission after cardiac surgery using data from the Pennsylvania Health Care Cost Containment Council.

Differences in medically assisted reproduction use by sexual identity and partnership: a prospective cohort of cisgender women.

STUDY QUESTION: Does medically assisted reproduction (MAR) use among cisgender women differ among those with same-sex partners or lesbian/bisexual identities compared to peers with different-sex partners or heterosexual identities? SUMMARY ANSWER: Women with same-sex partners or lesbian/bisexual identities are more likely to utilize any MAR but are no more likely to use ART (i.e. IVF, reciprocal IVF, embryo transfer, unspecified ART, ICSI, and gamete or zygote intrafallopian transfer) compared to non-ART MAR (i.e. IUI, ovulation induction, and intravaginal or intracervical insemination) than their different-sex partnered and completely heterosexual peers. WHAT IS KNOWN ALREADY: Sexual minority women (SMW) form families in myriad ways, including through fostering, adoption, genetic, and/or biological routes. Emerging evidence suggests this population increasingly wants to form genetic and/or biological families, yet little is known about their family formation processes and conception needs. STUDY DESIGN, SIZE, DURATION: The Growing Up Today Study is a US-based prospective cohort (n = 27 805). Participants were 9-17 years of age at enrollment (1996 and 2004). Biennial follow-up is ongoing, with data collected through 2021. PARTICIPANTS/MATERIALS, SETTING, METHODS: Cisgender women who met the following criteria were included in this sample: endorsed ever being pregnant; attempted a pregnancy in 2019 or 2021; and endorsed either a male- or female-sex partner OR responded to questions regarding their sexual identity during their conception window. The main outcome was any MAR use including ART (i.e. procedures involving micromanipulation of gametes) and non-ART MAR (i.e. nonmanipulation of gametes). Secondary outcomes included specific MAR procedures, time to conception, and trends across time. We assessed differences in any MAR use using weighted modified Poisson generalized estimating equations. MAIN RESULTS AND THE ROLE OF CHANCE: Among 3519 participants, there were 6935 pregnancies/pregnancy attempts and 19.4% involved MAR. A total of 47 pregnancies or pregnancy attempts were among the same-sex partnered participants, while 91 were among bisexual participants and 37 among lesbian participants. Participants with same-sex, compared to different-sex partners were almost five times as likely to use MAR (risk ratio [95% CI]: 4.78 [4.06, 5.61]). Compared to completely heterosexual participants, there was greater MAR use among lesbian (4.00 [3.10, 5.16]) and bisexual (2.22 [1.60, 3.07]) participants compared to no MAR use; mostly heterosexual participants were also more likely to use ART (1.42 [1.11, 1.82]) compared to non-ART MAR. Among first pregnancies conceived using MAR, conception pathways differed by partnership and sexual identity groups; differences were largest for IUI, intravaginal insemination, and timed intercourse with ovulation induction. From 2002 to 2021, MAR use increased proportionally to total pregnancies/pregnancy attempts; ART use was increasingly common in later years among same-sex partnered and lesbian participants. LIMITATIONS, REASONS FOR CAUTION: Our results are limited by the small number of SMW, the homogenous sample of mostly White, educated participants, the potential misclassification of MAR use when creating conception pathways unique to SMW, and the questionnaire's skip logic, which excluded certain participants from receiving MAR questions. WIDER IMPLICATIONS OF THE FINDINGS: Previous studies on SMW family formation have primarily focused on clinical outcomes from ART procedures and perinatal outcomes by conception method, and have been almost exclusively limited to European, clinical samples that relied on partnership data only. Despite the small sample of SMW within a nonrepresentative study, this is the first study to our knowledge to use a nonclinical sample of cisgender women from across the USA to elucidate family formation pathways by partnership as well as sexual identity, including pathways that may be unique to SMW. This was made possible by our innovative approach to MAR categorization within a large, prospective dataset that collected detailed sexual orientation data. Specifically, lesbian, bisexual, and same-sex partnered participants used both ART and non-ART MAR at similar frequencies compared to heterosexual and different-sex partnered participants. This may signal differential access to conception pathways owing to structural barriers, emerging conception trends as family formation among SMW has increased, and a need for conception support beyond specialized providers and fertility clinics. STUDY FUNDING/COMPETING INTEREST(S): The research reported in this publication was supported by the National Institute on Minority Health and Health Disparities of the National Institutes of Health (NIH), under award number R01MD015256. Additionally, KRSS is supported by NCI grant T32CA009001, AKH by the NCI T32CA057711, PC by the NHLBI T32HL098048, BM by the Stanford Maternal Child Health Research Institute Clinical Trainee Support Grant and the Diversity Fellowship from the American Society for Reproductive Medicine Research Institute, BGE by NICHD R01HD091405, and SM by the Thomas O. Pyle Fellowship through the Harvard Pilgrim Health Care Foundation and Harvard University, NHLBI T32HL098048, NIMH R01MH112384, and the William T. Grant Foundation grant number 187958. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health. The first author recently had a leadership role in the not-for-profit program, The Lesbian Health Fund, a research fund focused on improving the health and wellbeing of LGBTQ+ women and girls. The fund did not have any role in this study and the author's relationship with the fund did not bias the findings of this manuscript. TRIAL REGISTRATION NUMBER: N/A.

Post-traumatic stress disorder symptom remission and cognition in a large cohort of civilian women.

BACKGROUND: Post-traumatic stress disorder (PTSD) is associated with cognitive impairments. It is unclear whether problems persist after PTSD symptoms remit. METHODS: Data came from 12 270 trauma-exposed women in the Nurses' Health Study II. Trauma and PTSD symptoms were assessed using validated scales to determine PTSD status as of 2008 (trauma/no PTSD, remitted PTSD, unresolved PTSD) and symptom severity (lifetime and past-month). Starting in 2014, cognitive function was assessed using the Cogstate Brief Battery every 6 or 12 months for up to 24 months. PTSD associations with baseline cognition and longitudinal cognitive changes were estimated by covariate-adjusted linear regression and linear mixed-effects models, respectively. RESULTS: Compared to women with trauma/no PTSD, women with remitted PTSD symptoms had a similar cognitive function at baseline, while women with unresolved PTSD symptoms had worse psychomotor speed/attention and learning/working memory. In women with unresolved PTSD symptoms, past-month PTSD symptom severity was inversely associated with baseline cognition. Over follow-up, both women with remitted and unresolved PTSD symptoms in 2008, especially those with high levels of symptoms, had a faster decline in learning/working memory than women with trauma/no PTSD. In women with remitted PTSD symptoms, higher lifetime PTSD symptom severity was associated with a faster decline in learning/working memory. Results were robust to the adjustment for sociodemographic, biobehavioral, and health factors and were partially attenuated when adjusted for depression. CONCLUSION: Unresolved but not remitted PTSD was associated with worse cognitive function assessed six years later. Accelerated cognitive decline was observed among women with either unresolved or remitted PTSD symptoms.

An augmented illness-death model for semi-competing risks with clinically immediate terminal events.

Preeclampsia is a pregnancy-associated condition posing risks of both fetal and maternal mortality and morbidity that can only resolve following delivery and removal of the placenta. Because in its typical form preeclampsia can arise before delivery, but not after, these two events exemplify the time-to-event setting of "semi-competing risks" in which a non-terminal event of interest is subject to the occurrence of a terminal event of interest. The semi-competing risks framework presents a valuable opportunity to simultaneously address two clinically meaningful risk modeling tasks: (i) characterizing risk of developing preeclampsia, and (ii) characterizing time to delivery after onset of preeclampsia. However, some people with preeclampsia deliver immediately upon diagnosis, while others are admitted and monitored for an extended period before giving birth, resulting in two distinct trajectories following the non-terminal event, which we call "clinically immediate" and "non-immediate" terminal events. Though such phenomena arise in many clinical contexts, to-date there have not been methods developed to acknowledge the complex dependencies between such outcomes, nor leverage these phenomena to gain new insight into individualized risk. We address this gap by proposing a novel augmented frailty-based illness-death model with a binary submodel to distinguish risk of immediate terminal event following the non-terminal event. The model admits direct dependence of the terminal event on the non-terminal event through flexible regression specification, as well as indirect dependence via a shared frailty term linking each submodel. We develop an efficient Bayesian sampler for estimation and corresponding model fit metrics, and derive formulae for dynamic risk prediction. In an extended example using pregnancy outcome data from an electronic health record, we demonstrate the proposed model's direct applicability to address a broad range of clinical questions.

Sexual orientation disparities in gestational diabetes and hypertensive disorders of pregnancy.

BACKGROUND: Sexual minority (SM) individuals (e.g., those with same-sex attractions/partners or who identify as lesbian/gay/bisexual) experience a host of physical and mental health disparities. However, little is known about sexual orientation-related disparities in gestational diabetes mellitus (GDM) and hypertensive disorders of pregnancy (HDP; gestational hypertension [gHTN] and preeclampsia). OBJECTIVE: To estimate disparities in GDM, gHTN and preeclampsia by sexual orientation. METHODS: We used data from the Nurses' Health Study II-a cohort of nurses across the US enrolled in 1989 at 25-42 years of age-restricted to those with pregnancies ≥20 weeks gestation and non-missing sexual orientation data (63,518 participants; 146,079 pregnancies). Our primary outcomes were GDM, gHTN and preeclampsia, which participants reported for each of their pregnancies. Participants also reported their sexual orientation identity and same-sex attractions/partners. We compared the risk of each outcome in pregnancies among heterosexual participants with no same-sex experience (reference) to those among SM participants overall and within subgroups: (1) heterosexual with same-sex experience, (2) mostly heterosexual, (3) bisexual and (4) lesbian/gay participants. We used modified Poisson models to estimate risk ratios (RR) and 95% confidence intervals (CI), fit via weighted generalised estimating equations, to account for multiple pregnancies per person over time and informative cluster sizes. RESULTS: The overall prevalence of each outcome was ≤5%. Mostly heterosexual participants had a 31% higher risk of gHTN (RR 1.31, 95% CI 1.03, 1.66), and heterosexual participants with same-sex experience had a 31% higher risk of GDM (RR 1.31, 95% CI 1.13, 1.50), compared to heterosexual participants with no same-sex experience. The magnitudes of the risk ratios were high among bisexual participants for gHTN and preeclampsia and among lesbian/gay participants for gHTN. CONCLUSIONS: Some SM groups may be disparately burdened by GDM and HDP. Elucidating modifiable mechanisms (e.g., structural barriers, discrimination) for reducing adverse pregnancy outcomes among SM populations is critical.

Recommendations for Additional Imaging on Head and Neck Imaging Examinations: Interradiologist Variation and Associated Factors.

BACKGROUND. A paucity of relevant guidelines may lead to pronounced variation among radiologists in issuing recommendations for additional imaging (RAI) for head and neck imaging. OBJECTIVE. The purpose of this article was to explore associations of RAI for head and neck imaging examinations with examination, patient, and radiologist factors and to assess the role of individual radiologist-specific behavior in issuing such RAI. METHODS. This retrospective study included 39,200 patients (median age, 58 years; 21,855 women, 17,315 men, 30 with missing sex information) who underwent 39,200 head and neck CT or MRI examinations, interpreted by 61 radiologists, from June 1, 2021, through May 31, 2022. A natural language processing (NLP) tool with manual review of NLP results was used to identify RAI in report impressions. Interradiologist variation in RAI rates was assessed. A generalized mixed-effects model was used to assess associations between RAI and examination, patient, and radiologist factors. RESULTS. A total of 2943 (7.5%) reports contained RAI. Individual radiologist RAI rates ranged from 0.8% to 22.0% (median, 7.1%; IQR, 5.2-10.2%), representing a 27.5-fold difference between minimum and a maximum values and 1.8-fold difference between 25th and 75th percentiles. In multivariable analysis, RAI likelihood was higher for CTA than for CT examinations (OR, 1.32), for examinations that included a trainee in report generation (OR, 1.23), and for patients with self-identified race of Black or African American versus White (OR, 1.25); was lower for male than female patients (OR, 0.90); and was associated with increasing patient age (OR, 1.09 per decade) and inversely associated with radiologist years since training (OR, 0.90 per 5 years). The model accounted for 10.9% of the likelihood of RAI. Of explainable likelihood of RAI, 25.7% was attributable to examination, patient, and radiologist factors; 74.3% was attributable to radiologist-specific behavior. CONCLUSION. Interradiologist variation in RAI rates for head and neck imaging was substantial. RAI appear to be more substantially associated with individual radiologist-specific behavior than with measurable systemic factors. CLINICAL IMPACT. Quality improvement initiatives, incorporating best practices for incidental findings management, may help reduce radiologist preference-sensitive decision-making in issuing RAI for head and neck imaging and associated care variation.

Disparities in Mortality by Sexual Orientation in a Large, Prospective Cohort of Female Nurses.

Importance: Extensive evidence documents health disparities for lesbian, gay, and bisexual (LGB) women, including worse physical, mental, and behavioral health than heterosexual women. These factors have been linked to premature mortality, yet few studies have investigated premature mortality disparities among LGB women and whether they differ by lesbian or bisexual identity. Objective: To examine differences in mortality by sexual orientation. Design, Setting, and Participants: This prospective cohort study examined differences in time to mortality across sexual orientation, adjusting for birth cohort. Participants were female nurses born between 1945 and 1964, initially recruited in the US in 1989 for the Nurses' Health Study II, and followed up through April 2022. Exposures: Sexual orientation (lesbian, bisexual, or heterosexual) assessed in 1995. Main Outcome and Measure: Time to all-cause mortality from assessment of exposure analyzed using accelerated failure time models. Results: Among 116 149 eligible participants, 90 833 (78%) had valid sexual orientation data. Of these 90 833 participants, 89 821 (98.9%) identified as heterosexual, 694 (0.8%) identified as lesbian, and 318 (0.4%) identified as bisexual. Of the 4227 deaths reported, the majority were among heterosexual participants (n = 4146; cumulative mortality of 4.6%), followed by lesbian participants (n = 49; cumulative mortality of 7.0%) and bisexual participants (n = 32; cumulative mortality of 10.1%). Compared with heterosexual participants, LGB participants had earlier mortality (adjusted acceleration factor, 0.74 [95% CI, 0.64-0.84]). These differences were greatest among bisexual participants (adjusted acceleration factor, 0.63 [95% CI, 0.51-0.78]) followed by lesbian participants (adjusted acceleration factor, 0.80 [95% CI, 0.68-0.95]). Conclusions and Relevance: In an otherwise largely homogeneous sample of female nurses, participants identifying as lesbian or bisexual had markedly earlier mortality during the study period compared with heterosexual women. These differences in mortality timing highlight the urgency of addressing modifiable risks and upstream social forces that propagate and perpetuate disparities.

Comparative Effectiveness and Safety of Seizure Prophylaxis Among Adults After Acute Ischemic Stroke.

BACKGROUND: Older adults occasionally receive seizure prophylaxis in an acute ischemic stroke (AIS) setting, despite safety concerns. There are no trial data available about the net impact of early seizure prophylaxis on post-AIS survival. METHODS: Using a stroke registry (American Heart Association's Get With The Guidelines) individually linked to electronic health records, we examined the effect of initiating seizure prophylaxis (ie, epilepsy-specific antiseizure drugs) within 7 days of an AIS admission versus not initiating in patients ≥65 years admitted for a new, nonsevere AIS (National Institutes of Health Stroke Severity score ≤20) between 2014 and 2021 with no recorded use of epilepsy-specific antiseizure drugs in the previous 3 months. We addressed confounding by using inverse-probability weights. We performed standardization accounting for pertinent clinical and health care factors (eg, National Institutes of Health Stroke Severity scale, prescription counts, seizure-like events). RESULTS: The study sample included 151 patients who received antiseizure drugs and 3020 who did not. The crude 30-day mortality risks were 219 deaths per 1000 patients among epilepsy-specific antiseizure drugs initiators and 120 deaths per 1000 among noninitiators. After standardization, the estimated mortality was 251 (95% CI, 190-307) deaths per 1000 among initiators and 120 (95% CI, 86-144) deaths per 1000 among noninitiators, corresponding to a risk difference of 131 (95% CI, 65-200) excess deaths per 1000 patients. In the prespecified subgroup analyses, the risk difference was 52 (95% CI, 11-72) among patients with minor AIS and 138 (95% CI, 52-222) among moderate-to-severe AIS patients. Similarly, the risk differences were 86 (95% CI, 18-118) and 157 (95% CI, 57-219) among patients aged 65 to 74 years and ≥75 years, respectively. CONCLUSIONS: There was a higher risk of 30-day mortality associated with initiating versus not initiating seizure prophylaxis within 7 days post-AIS. This study does not support the role of seizure prophylaxis in reducing 30-day poststroke mortality.

Experience with the US health care system for Black and White patients with advanced prostate cancer.

OBJECTIVE: The purpose of this study was to assess differences in reported information about treatment, integration into care, and respect by self-identified Black and White individuals with advanced prostate cancer in the United States. PATIENTS AND METHODS: This is a prospective cohort study of 701 participants (20% identifying as Black) enrolled in the International Registry for Men with Advanced Prostate Cancer at 37 US sites from 2017 to 2022. Participants were asked six questions from the Cancer Australia National Cancer Control Indicators about their experience with care at study enrollment. Prevalence differences by self-reported race were estimated using marginal standardization of logistic-normal mixed effects models (adjusted for age at enrollment and disease state at enrollment), and 95% CIs were estimated using parametric bootstrapping. RESULTS: Most participants reported a high quality of care for each question. Black participants generally reported higher care quality compared with White participants. Black participants reported more frequently that they were offered a written assessment and care plan (71%) compared with White participants (58%; adjusted difference, 13 percentage points; 95% CI, 4-23). Black participants also reported more frequently being given the name of nonphysician personnel who would support them (64%) than White participants (52%; adjusted difference, 10; 95% CI, 1-20). Prevalence differences did not differ by disease state at enrollment. CONCLUSIONS: Black participants generally reported a higher quality of care compared with White participants. This study calls attention to the need to study potential mediating factors and interpersonal aspects of care in this population to improve survivorship.

Reduction in Long-term Mortality After Sleeve Gastrectomy and Gastric Bypass Compared to Nonsurgical Patients With Severe Obesity.

OBJECTIVE: To separately compare the long-term risk of mortality among bariatric surgical patients undergoing either Roux-en-Y gastric bypass (RYGB) or sleeve gastrectomy (SG) to large, matched, population-based cohorts of patients with severe obesity who did not undergo surgery. BACKGROUND: Bariatric surgery has been associated with reduced long-term mortality compared to usual care for severe obesity which is particularly relevant in the COVID-19 era. Most prior studies involved the RYGB operation and there is less long-term data on the SG. METHODS: In this retrospective, matched cohort study, patients with a body mass index ≥35 kg/m 2 who underwent bariatric surgery from January 2005 to September 2015 in three integrated health systems in the United States were matched to nonsurgical patients on site, age, sex, body mass index, diabetes status, insulin use, race/ethnicity, combined Charlson/Elixhauser comorbidity score, and prior health care utilization, with follow-up through September 2015. Each procedure (RYGB, SG) was compared to its own control group and the two surgical procedures were not directly compared to each other. Multivariable-adjusted Cox regression analysis investigated time to all-cause mortality (primary outcome) comparing each of the bariatric procedures to usual care. Secondary outcomes separately examined the incidence of cardiovascular-related death, cancer related-death, and diabetes related-death. RESULTS: Among 13,900 SG, 17,258 RYGB, and 87,965 nonsurgical patients, the 5-year follow-up rate was 70.9%, 72.0%, and 64.5%, respectively. RYGB and SG were each associated with a significantly lower risk of all-cause mortality compared to nonsurgical patients at 5-years of follow-up (RYGB: HR = 0.43; 95% CI: 0.35,0.54; SG: HR = 0.28; 95% CI: 0.13,0.57) Similarly, RYGB was associated with a significantly lower 5-year risk of cardiovascular-(HR = 0.27; 95% CI: 0.20, 0.37), cancer- (HR = 0.54; 95% CI: 0.39, 0.76), and diabetes-related mortality (HR = 0.23; 95% CI:0.15, 0.36). There was not enough follow-up time to assess 5-year cause-specific mortality in SG patients, but at 3-years follow-up, there was significantly lower risk of cardiovascular- (HR = 0.33; 95% CI:0.19, 0.58), cancer- (HR = 0.26; 95% CI:0.11, 0.59), and diabetes-related (HR = 0.15; 95% CI:0.04, 0.53) mortality for SG patients. CONCLUSION: This study confirms and extends prior findings of an association with better survival following bariatric surgery in RYGB patients compared to controls and separately demonstrates that the SG operation also appears to be associated with lower mortality compared to matched control patients with severe obesity that received usual care. These results help to inform the tradeoffs between long-term benefits and risks of bariatric surgery.

Neo-Traditional and Industrialized Dietary Patterns Coexist and Are Differentially Associated with Cardiometabolic Health among Adults in Puerto Rico.

BACKGROUND: An increasingly industrialized food system has marginalized local, traditional food cultures in Puerto Rico (PR). Recent efforts to decolonize diets have promoted local food intake; however, how resulting dietary patterns may influence cardiometabolic disease remains unknown. OBJECTIVES: This study aimed to 1) identify dietary patterns in PR and 2) determine their associations with metabolic syndrome (MetS) and its components. METHODS: Data were obtained from participants (30-75 y) in PROSPECT (PR Observational Study of Psychosocial, Environmental, and Chronic Disease Trends; n = 989). Dietary patterns were derived using partial least squares analysis with food frequency questionnaire data, using nutrients associated with local food purchasing (dietary fiber, magnesium, saturated fat) as response variables. MetS was classified using harmonized criteria from clinical and laboratory measures and medication use. Fully adjusted generalized linear models tested associations between tertiles of dietary patterns and MetS. RESULTS: Approximately half (52%) of the participants were classified with MetS. Four dietary patterns were revealed: conventional (legumes, coffee, and dairy), industrialized starch and meat-centric (red/processed meats, pasta, and starchy roots), industrialized sugar-centric (rice, sugary beverages, and refined grains), and neo-traditional (local plants and seafood). Individuals in the highest (compared with lowest) tertile of the industrialized starch and meat-centric dietary pattern had higher mean waist circumference (102 compared with 99 cm) (P = 0.01), fasting glucose (106 compared with 98 mg/dL) (P = 0.019), and systolic blood pressure (123 compared with 119 mmHg) (P = 0.022). Individuals in the highest (compared with lowest) tertile of the neo-traditional diet were 0.69 (0.49, 0.97) times less likely to have MetS (P = 0.035) and had 4.1 cm lower mean waist circumference (P = 0.002). CONCLUSIONS: Promoting a neo-traditional diet and curbing industrialized starch and meat-centric diets may improve cardiometabolic health in PR. Results can guide local food promotion as a healthful, decolonizing approach in island settings.

Long-term associations between early-life family functioning and preadolescent white matter microstructure.

BACKGROUND: Causes of childhood behavior problems remain poorly understood. Enriched family environments and corresponding brain development may reduce the risk of their onset, but research investigating white matter neurodevelopmental pathways explaining associations between the family environment and behavior remains limited. We hypothesized that more positive prenatal and mid-childhood family functioning - a measure of a family's problem solving and supportive capacity - would be associated with two markers of preadolescent white matter neurodevelopment related to reduced behavior problems: higher global fractional anisotropy (FA) and lower global mean diffusivity (MD). METHODS: Data are from 2727 families in the Generation R Study, the Netherlands. Mothers reported family functioning (McMaster Family Assessment Device, range 1-4, higher scores indicate healthier functioning) prenatally and in mid-childhood (mean age 6.1 years). In preadolescence (mean age 10.1), the study collected diffusion-weighted scans. We computed standardized global MD and FA values by averaging metrics from 27 white matter tracts, and we fit linear models adjusting for possible confounders to examine global and tract-specific outcomes. RESULTS: Prenatal and mid-childhood family functioning scores were moderately correlated, r = 0.38. However, only prenatal family functioning - and not mid-childhood functioning - was associated with higher global FA and lower global MD in preadolescence in fully adjusted models: ßglobal FA = 0.11 (95% CI 0.00, 0.21) and ßglobal MD = -0.15 (95% CI -0.28, -0.03) per one-unit increase in functioning score. Sensitivity and tract-specific analyses supported these global findings. CONCLUSIONS: These results suggest high-functioning prenatal or perinatal family environments may confer lasting white matter neurodevelopmental benefits into preadolescence.

A novel approach to joint prediction of preeclampsia and delivery timing using semicompeting risks.

BACKGROUND: Preeclampsia is a pregnancy complication that contributes substantially to perinatal morbidity and mortality worldwide. Existing approaches to modeling and prediction of preeclampsia typically focus either on predicting preeclampsia risk alone, or on the timing of delivery following a diagnosis of preeclampsia. As such, they are misaligned with typical healthcare interactions during which the 2 events are generally considered simultaneously. OBJECTIVE: This study aimed to describe the "semicompeting risks" framework as an innovative approach for jointly modeling the risk and timing of preeclampsia and the timing of delivery simultaneously. Through this approach, one can obtain, at any point during the pregnancy, clinically relevant summaries of an individual's predicted outcome trajectories in 4 risk categories: not developing preeclampsia and not having delivered, not developing preeclampsia but having delivered because of other causes, developing preeclampsia but not having delivered, and developing preeclampsia and having delivered. STUDY DESIGN: To illustrate the semicompeting risks methodology, we presented an example analysis of a pregnancy cohort from the electronic health record of an urban, academic medical center in Boston, Massachusetts (n=9161 pregnancies). We fit an illness-death model with proportional-hazards regression specifications describing 3 hazards for timings of preeclampsia, delivery in the absence of preeclampsia, and delivery following preeclampsia diagnosis. RESULTS: The results indicated nuanced relationships between a variety of risk factors and the timings of preeclampsia diagnosis and delivery, including maternal age, race/ethnicity, parity, body mass index, diabetes mellitus, chronic hypertension, cigarette use, and proteinuria at 20 weeks' gestation. Sample predictions for a diverse set of individuals highlighted differences in projected outcome trajectories with regard to preeclampsia risk and timing, and timing of delivery either before or after preeclampsia diagnosis. CONCLUSION: The semicompeting risks framework enables characterization of the joint risk and timing of preeclampsia and delivery, providing enhanced, meaningful information regarding clinical decision-making throughout the pregnancy.

Assessing exposure-time treatment effect heterogeneity in stepped-wedge cluster randomized trials.

A stepped-wedge cluster randomized trial (CRT) is a unidirectional crossover study in which timings of treatment initiation for clusters are randomized. Because the timing of treatment initiation is different for each cluster, an emerging question is whether the treatment effect depends on the exposure time, namely, the time duration since the initiation of treatment. Existing approaches for assessing exposure-time treatment effect heterogeneity either assume a parametric functional form of exposure time or model the exposure time as a categorical variable, in which case the number of parameters increases with the number of exposure-time periods, leading to a potential loss in efficiency. In this article, we propose a new model formulation for assessing treatment effect heterogeneity over exposure time. Rather than a categorical term for each level of exposure time, the proposed model includes a random effect to represent varying treatment effects by exposure time. This allows for pooling information across exposure-time periods and may result in more precise average and exposure-time-specific treatment effect estimates. In addition, we develop an accompanying permutation test for the variance component of the heterogeneous treatment effect parameters. We conduct simulation studies to compare the proposed model and permutation test to alternative methods to elucidate their finite-sample operating characteristics, and to generate practical guidance on model choices for assessing exposure-time treatment effect heterogeneity in stepped-wedge CRTs.

Penalized estimation of frailty-based illness-death models for semi-competing risks.

Semi-competing risks refer to the time-to-event analysis setting, where the occurrence of a non-terminal event is subject to whether a terminal event has occurred, but not vice versa. Semi-competing risks arise in a broad range of clinical contexts, including studies of preeclampsia, a condition that may arise during pregnancy and for which delivery is a terminal event. Models that acknowledge semi-competing risks enable investigation of relationships between covariates and the joint timing of the outcomes, but methods for model selection and prediction of semi-competing risks in high dimensions are lacking. Moreover, in such settings researchers commonly analyze only a single or composite outcome, losing valuable information and limiting clinical utility-in the obstetric setting, this means ignoring valuable insight into timing of delivery after preeclampsia has onset. To address this gap, we propose a novel penalized estimation framework for frailty-based illness-death multi-state modeling of semi-competing risks. Our approach combines non-convex and structured fusion penalization, inducing global sparsity as well as parsimony across submodels. We perform estimation and model selection via a pathwise routine for non-convex optimization, and prove statistical error rate results in this setting. We present a simulation study investigating estimation error and model selection performance, and a comprehensive application of the method to joint risk modeling of preeclampsia and timing of delivery using pregnancy data from an electronic health record.

Practical strategies for operationalizing optimal allocation in stratified cluster-based outcome-dependent sampling designs.

Cluster-based outcome-dependent sampling (ODS) has the potential to yield efficiency gains when the outcome of interest is relatively rare, and resource constraints allow only a certain number of clusters to be visited for data collection. Previous research has shown that when the intended analysis is inverse-probability weighted generalized estimating equations, and the number of clusters that can be sampled is fixed, optimal allocation of the (cluster-level) sample size across strata defined by auxiliary variables readily available at the design stage has the potential to increase efficiency in the estimation of the parameter(s) of interest. In such a setting, the optimal allocation formulae depend on quantities that are unknown in practice, currently making such designs difficult to implement. In this paper, we consider a two-wave adaptive sampling approach, in which data is collected from a first wave sample, and subsequently used to compute the optimal second wave stratum-specific sample sizes. We consider two strategies for estimating the necessary components using the first wave data: an inverse-probability weighting (IPW) approach and a multiple imputation (MI) approach. In a comprehensive simulation study, we show that the adaptive sampling approach performs well, and that the MI approach yields designs that are very near-optimal, regardless of the covariate type. The IPW approach, on the other hand, has mixed results. Finally, we illustrate the proposed adaptive sampling procedures with data on maternal characteristics and birth outcomes among women enrolled in the Safer Deliveries program in Zanzibar, Tanzania.

Sample size requirements for testing treatment effect heterogeneity in cluster randomized trials with binary outcomes.

Cluster randomized trials (CRTs) refer to a popular class of experiments in which randomization is carried out at the group level. While methods have been developed for planning CRTs to study the average treatment effect, and more recently, to study the heterogeneous treatment effect, the development for the latter objective has currently been limited to a continuous outcome. Despite the prevalence of binary outcomes in CRTs, determining the necessary sample size and statistical power for detecting differential treatment effects in CRTs with a binary outcome remain unclear. To address this methodological gap, we develop sample size procedures for testing treatment effect heterogeneity in two-level CRTs under a generalized linear mixed model. Closed-form sample size expressions are derived for a binary effect modifier, and in addition, a computationally efficient Monte Carlo approach is developed for a continuous effect modifier. Extensions to multiple effect modifiers are also discussed. We conduct simulations to examine the accuracy of the proposed sample size methods. We present several numerical illustrations to elucidate features of the proposed formulas and to compare our method to the approximate sample size calculation under a linear mixed model. Finally, we use data from the Strategies and Opportunities to Stop Colon Cancer in Priority Populations (STOP CRC) CRT to illustrate the proposed sample size procedure for testing treatment effect heterogeneity.

Sensitivity analysis using bias functions for studies extending inferences from a randomized trial to a target population.

Extending (i.e., generalizing or transporting) causal inferences from a randomized trial to a target population requires assumptions that randomized and nonrandomized individuals are exchangeable conditional on baseline covariates. These assumptions are made on the basis of background knowledge, which is often uncertain or controversial, and need to be subjected to sensitivity analysis. We present simple methods for sensitivity analyses that directly parameterize violations of the assumptions using bias functions and do not require detailed background knowledge about specific unknown or unmeasured determinants of the outcome or modifiers of the treatment effect. We show how the methods can be applied to non-nested trial designs, where the trial data are combined with a separately obtained sample of nonrandomized individuals, as well as to nested trial designs, where the trial is embedded within a cohort sampled from the target population.