Epidemiological studies that rely on biomarkers of exposure typically estimate each subject’s exposure from measurements on that individual. If repeated measurements of biomarkers of exposure are obtained on an individual, they are typically averaged. This averaging helps to reduce error from within-person variability if average exposure is a better measure of the biologically effective dose than the instantaneous one. However, these analyses then often ignore the residual within-person variation in the averages of measurements. Not considering this variation can bias effect estimates and lead to inaccurate risk assessment. We developed software (“calculators”) that help design studies of continuous and binary outcomes that rely on biomarkers of exposure. An independent panel of experts was employed to peer review the models and answer questions regarding their use and best practices for the design of epidemiology studies that utilize biomonitoring data for the exposure assessment. Web-based tools were developed to estimate the required sample sizes, number of repeated measurements, and the trade-offs between power and bias in simple linear and logistic regression models under classical (independent, additive, normally distributed, homogeneous variance) measurement error assumptions. Application of the calculators was illustrated in case studies of investigation of the associations between urinary levels of bisphenols during pregnancy and fetal growth, and urinary levels of triclosan and neurodevelopment in children. Best practices are recommended for the design of epidemiology studies that utilize biomonitoring data for the exposure assessment. Calculators have been developed and vetted by a panel of experts. They are designed to estimate sample size (number of individuals sampled and number of samples per individual), power and bias in epidemiological studies that use biomonitoring to assess each subject’s exposure in the presence of classical measurement errors. These user-friendly tools account for measurement error and allow researchers to design more accurate and appropriately powered studies, ultimately improving quality of public health research.

The authors have withdrawn this manuscript because of software coding issues discovered post-submission. Therefore, the authors do not wish this work to be cited as reference for the project. If you have any questions, please contact the corresponding author.

BACKGROUND:Studies show that foetal and birthweight-for-gestational age centiles are poor predictors of serious neonatal morbidity and neonatal mortality (SNMM) in univariable models. OBJECTIVE:We assessed the predictive performance of multivariable SNMM models based on maternal/pregnancy characteristics, with and without birthweight centiles. METHODS:The study was based on all live births in the United States, 2019-2021, with data obtained from the period live birth-infant death files of the National Center for Health Statistics. SNMM was defined as any one or more of the following: 5-minute Apgar score < 4, seizures, assisted ventilation for> 30 or neonatal death. SNMM was modelled by log-linear regression on maternal/pregnancy characteristics as predictors, with and without birthweight centiles. Models were developed for live births at 24-42 weeks' and 39 weeks' gestation to all women and those with hypertensive disorders or pre-existing diabetes. Model performance was assessed using area under the curve (AUC). RESULTS:The study population included 10,487,243 live births and 221,728 SNMM cases (2.1 per 100 live births). The models with all live births at 24-42 weeks' gestation had AUCs of 0.83 (95% confidence interval [CI] 0.82, 0.83) based on maternal/pregnancy characteristics and 0.83 (95% CI 0.83, 0.84) based on maternal/pregnancy characteristics and birthweight centiles. However, AUCs of models based on all live births at 39 weeks' gestation were 0.66 (95% CI 0.64, 0.68) with maternal/pregnancy characteristics and 0.69 (95% CI 0.68, 0.71) with maternal/pregnancy characteristics and birthweight centiles. AUCs of the models with live births at 39 weeks' gestation to women with pre-existing diabetes were 0.69 (95% CI 0.66, 0.72) based on maternal/pregnancy characteristics, and 0.77 (95% CI 0.74, 0.79) with the addition of birthweight centiles. CONCLUSIONS:Birthweight centiles improve multivariable SNMM predictive performance in specific subpopulations, although evaluation of decision thresholds is required to determine the clinical importance of improvement in predictive ability.

PURPOSE:To examine factors associated with moving during pregnancy and impacts of assigning nSES at enrollment, delivery, or a time-weighted average on birth outcomes (birthweight, birthweight-for-gestational-age z-score, low birthweight, gestational age, small-for-gestational age, preterm birth). METHODS:We used data from the Environmental influences on Child Health Outcomes (ECHO) Cohort Study (2010-2019) with nSES data from the American Community Survey (ACS) matched by time and location to monthly residential histories. We used multivariable logistic models with Generalized Estimating Equations to identify factors associated with moving and quantify exposure misclassification in model estimates. RESULTS:Approximately 7 % of 15,376 participants moved at least once during pregnancy. Maternal age (OR: 0.97, 95 % CI: 0.95, 0.98) and other race vs. White (OR: 0.39, 95 % CI: 0.20, 0.80) were associated with lower odds of moving; lower neighborhood-level education (OR: 1.34, 95 % CI: 1.11, 1.62) and living in urban neighborhoods (OR: 3.03, 95 % CI: 1.39, 6.59) were associated with higher odds. Among movers, estimates between nSES and birth outcomes changed ≥ 16 % by address assignment; birthweight-for-gestational-age z-score was significant only when using nSES at delivery. CONCLUSION:Sociodemographic and nSES characteristics are associated with moving during pregnancy; movers may experience exposure misclassification and underestimated effects on birth outcomes.

Prior work suggests that living among people who share similar identities may be protective against psychosis, but the meaning of this association in the context of racialized residential segregation is not well understood. We investigated the effects of evenness and exposure residential segregation on persistent, distressing psychotic-like experiences (PLEs) in Black and White adolescents living in urban neighborhoods with high and low social cohesion in the United States. Data from the Adolescent Brain Cognitive Development Study were used (N = 5871), measuring evenness and exposure segregation in metropolitan statistical areas using the Dissimilarity Index (DI) and Exposure-Interaction Index (EII), respectively. Multi-level log binomial generalized estimating equations estimated the relative risk of PLEs by exposure to each domain of segregation. Evenness and exposure segregation were associated with risk of PLE (DI: aRR = 1.11, 95 % CI 1.06-1.17; EII: aRR = 0.82, 95 % CI 0.78-0.87). When both domains were present in the same model, the effect of evenness, but not exposure, was attenuated (DI: aRR = 0.98, 95 % CI 0.92-1.05; EII: aRR = 0.81, 95 % 0.75-0.88). These associations were not statistically significantly different for levels of race (p-values ranged 0.08-0.86) or neighborhood social cohesion (p-values ranged 0.16-0.56). Sensitivity analysis indicated the main effect was not altered by duration of exposure. Lower exposure to exposure domain segregation may be protective against risk of PLEs in young adolescents in urban areas. The association was similar in comparisons of Black-White racial groups and high-low neighborhood social cohesion groups.

OBJECTIVES:Socioeconomic inequities in early access to kidney transplantation among patients with end-stage kidney disease (ESKD) are well documented. It is unknown whether these inequities can be mitigated through access to nephrology care prior to starting dialysis. This study evaluated whether pre-ESKD nephrology care meaningfully explained the association between neighborhood poverty and referral for kidney transplantation among patients initiating treatment for ESKD. STUDY DESIGN AND SETTING:In this retrospective cohort study using United States Renal Data System data (January 1, 2012 to June 30, 2021), we identified 192,318 adults with incident ESKD from dialysis facilities in Southeast, Northeast, New York, and Ohio River Valley US regions. Neighborhood poverty exposure was dichotomized based on zip code poverty rates (≥20% vs 0%-19%), and referral outcomes were assessed from 28 transplant centers. We used marginal structural Cox models with inverse probability of treatment weighting to estimate the direct effect of neighborhood poverty on referral for kidney transplantation, controlling for access to pre-ESKD nephrology care (controlled direct effect). RESULTS:Findings show that 68% had pre-ESKD nephrology care, and 25% lived in high-poverty areas. Pre-ESKD nephrology care was associated with increased referral (hazard ratio (HR): 1.26, 95% CI: 1.22, 1.30). Adjusted analyses using marginal structural Cox models with inverse probability weighting revealed that pre-ESKD nephrology care did not fully explain the association between neighborhood poverty and referral for kidney transplantation (controlled direct effect HR: 0.87, 95% CI: 0.85, 0.89; total effect HR: 0.90, 95% CI: 0.88, 0.91). CONCLUSION:These results underscore the beneficial role of pre-ESKD nephrology care in enhancing transplant referral access. However, persistent disparities linked to neighborhood poverty remain evident. The study emphasizes the continued importance of pre-ESKD nephrology care as a clinical standard for all patients with ESKD. Future research should explore interventions earlier in the kidney disease continuum to address socioeconomic disparities and improve equitable access to kidney transplantation. PLAIN LANGUAGE SUMMARY:For people with end-stage kidney disease (ESKD), survival depends on either regular dialysis treatments or a kidney transplant. For most people, a kidney transplant offers the best long-term survival and quality of life compared to dialysis. People living in poorer neighborhoods face significant challenges in getting referred for a kidney transplant. Our study aimed to investigate if receiving care from a kidney specialist (nephrologist) before needing dialysis (pre-ESKD nephrology care) could help overcome these income-related disparities in transplant access. We looked at records from nearly 200,000 adults across 4 US regions who started treatment for ESKD. We categorized neighborhoods as "high-poverty" (where 20% or more residents live below the poverty line) or "low-poverty" areas. Using advanced statistical methods, we analyzed how neighborhood poverty affected transplant referral, specifically assessing the role of pre-ESKD nephrology care. Our findings showed that most patients (68%) had seen a nephrologist before dialysis. Seeing a nephrologist was associated with a 26% higher chance of being referred for a transplant. However, even among those who received predialysis nephrology care, living in a high-poverty neighborhood still meant they were 13% less likely to be referred for a transplant. This study highlights that while pre-ESKD nephrology care is beneficial and increases the likelihood of transplant referral, it alone does not fully close the gap in access influenced by neighborhood poverty. To achieve equitable access to kidney transplantation for all patients, future efforts must target broader interventions that address the underlying socioeconomic factors affecting health throughout a patient's kidney disease journey.

OBJECTIVE:To estimate associations between the length of state-level eviction moratoria enacted in March and April 2020 in the United States and perinatal outcomes. METHODS:We used data from natality files, 2020-2021 to identify individuals with Medicaid or no insurance who conceived in March-May 2020. The exposure was the number of months exposed to a moratorium (0 (referent, no state-level moratoria), 1-2, 3-4, 5 or more). Outcomes included preterm birth (PTB, < 37 weeks gestation), very preterm birth (VPTB, < 32 weeks gestation), low birthweight (LBW, < 2500 g), very low birthweight (VLBW, < 1500 g), primary cesarean, or maternal morbidity. We estimated risk ratios (RRs) using log-binomial regression, including individual, county, and state-level confounders. We conducted several sensitivity analyses to rule out residual state-level confounding including a negative control analysis of 2019 conceptions and difference-in-difference analysis. RESULTS:We included 375,821 births. Following adjustment, having a moratorium in place for 5 or more months was associated with slightly reduced risk of PTB (RR: 0.95, 95 % CI: 0.88, 1.02), VPTB (RR: 0.90, 95 % CI: 0.8-1.01), LBW (RR: 0.95, 95 % CI: 0.9-1.01), and VLBW (RR: 0.91, 95 % CI: 0.81-1.02) compared to states without a moratorium. There was no association with cesarean or maternal morbidity. Sensitivity analyses showed that all or most of the observed associations may be explained by residual state-level confounding. CONCLUSIONS:State-level eviction moratoria were associated with improved birth outcomes, yet it is likely that all or most of the observed association is due to other policy actions or characteristics of enacting states.

OBJECTIVES:To understand place-based drivers of racial disparities in stroke mortality in the United States by investigating the relationship between county-level measures of structural racism and racial disparities in stroke mortality. METHODS:We constructed an additive structural racism score from census-based indicators of racial disproportionality (income, poverty, unemployment, home ownership, education, health insurance) and residential segregation (evenness, isolation), as well as county-level jail incarceration data from the Vera Institute of Justice. We utilized age-standardized, spatially smoothed stroke death rates in 2021 for Black and White adults aged 35-64 years in the United States. We fit linear regression models, both unadjusted and adjusted for overall county-level conditions, and assessed interaction between structural racism and gender. RESULTS:Among 935 included counties, median structural racism score was 13.29 (range: 2.83-32.43). In unadjusted models, a 1-unit increase in structural racism was associated with 0.37 (95% CI 0.26, 0.46) additional stroke deaths per 100,000 Black residents compared to White residents of a county. Adjusted results were similar. This association was stronger among men (0.67 [95% CI 0.50, 0.83]) than women (0.35 [95% CI 0.19, 0.51]) (P = 0.003). CONCLUSIONS:Structural racism may drive racial disparities in stroke mortality, particularly among men.

Overdoses are a leading cause of maternal mortality in the US, but limited evidence exists about patterns of nonfatal overdose, a key risk factor for subsequent fatal overdose, or of other drug-related harms. Here, we estimate prevalences of nonfatal overdose and injection-related endocarditis and abscesses/cellulitis across the 21 months spanning pregnancy and the postpartum year. Among people who experienced an in-hospital birth in New York State between 9/1/2016 and 1/1/2018 (N = 330,872), we estimated the prevalences of hospital-based diagnoses of nonfatal overdose and of injection-related bacterial infections (i.e., endocarditis, abscesses, and cellulitis) across these 21 months; by trimester and postpartum quarter; and by social position (e.g., race/ethnicity, rurality, payor). The 21-month nonfatal overdose prevalence was 158/100,000 births (CI: 145/100,000, 172/100,000); the 21-month prevalence of injection-related bacterial infections was 56/100,000 births (CI: 49/100,000, 65/100,000). There was a trend such that rates of overdose and of injection-related bacterial infections declined as pregnancy progressed and rebounded postpartum. Rates of all outcomes were highest outside of large metropolitan areas and among publicly insured residents. The trend toward diminished rates during pregnancy is supported by past qualitative studies. If confirmed by future research in other geographical regions and with larger sample sizes, this finding holds promise for programmatic and policy interventions. Interventions co-designed with people who use drugs could complement and support harm reduction efforts that pregnant people are already engaging in independently. Such efforts can help people who use drugs survive the pregnancy and postpartum year. Fatal overdoses are a leading cause of maternal mortality in the US. Little evidence exists, however, about patterns of nonfatal overdose, a strong predictor of future fatal overdose, or about other serious injection-related bacterial infections. We find trends suggesting that rates of nonfatal overdose and injection-related bacterial infections decline during pregnancy and then rebound postpartum. These findings, if confirmed in future research, suggest a clear path toward intervention development: partnering with people who use drugs to design interventions that complement and support their existing harm reduction interventions during pregnancy and in the postpartum period.

Rationale & Objective: Little is known about the relative importance of dialysis facilities and transplant centers on variability in starting an evaluation among patients referred for kidney transplant. The primary objective of this study was to leverage cross- classified multilevel modeling to simultaneously examine the contextual effects of dialysis facilities and transplant centers on variation in the start of the transplant evaluation process. Study Design: Retrospective cohort study. Setting & Participants: Dialysis patients referred for kidney transplant to transplant centers across the Southeast, Northeast, New York, or Ohio River Valley US regions from January 1, 2012, to December 31, 2020, were identified from the United States Renal Data System and the Early Steps to Transplant Access Registry and followed through June 30, 2021. A total of N=25,48 8 referred patients were nested with 1,720 dialysis facilities and 26 transplant centers. Outcomes: Starting an evaluation for kidney transplant at a transplant center within 6 months of referral. Analytical Approach: A series of multilevel models were performed to estimate the variability in starting an evaluation for kidney transplant within 6 months of referral. The between-dialysis facility and/or transplant center variation in starting an evaluation was quantified using the median OR. Results: Among 25,488 dialysis patients referred for kidney transplantation, 51% of patients started an evaluation at a transplant center within 6 months of referral. In multilevel models, the median OR between transplant centers was higher (indicating higher unexplained variability) than the dialysis facility median OR, regardless of measured patient, dialysis facility, and transplant center characteristics. Limitations: Early transplant access data was limited to 20 of 48 transplant centers across these 4 regions. Conclusions: When taking dialysis facilities and transplant centers into account, variation in starting an evaluation for kidney transplant appeared at both the dialysis facility and transplant center-level but was more apparent among transplant centers.

Despite similar incidence rates, nationwide breast cancer mortality is 40% higher among non-Hispanic Black (NHB) than non-Hispanic White (NHW) women. The racial disparity persists even among women who have early-stage disease, prognostically favorable subtypes, or indicators of high socioeconomic status, and is not evenly distributed throughout the United States. Understanding geographic differences may provide additional insight into the drivers of the disparity. However, current data are geographically limited, based primarily on death certificate information, do not incorporate incidence, and often do not provide estimates or account for areas with small populations or sparse case data. Using a Bayesian framework, we estimated the local racial disparity in 5-year mortality for nonmetastatic breast cancer diagnosed during 2005-2013 across counties in Georgia, a racially and geographically diverse state. Overall, during the study period, 5-year breast cancer mortality was 43% higher among NHB than NHW women. The racial disparity varied across Georgia with more pronounced disparity observed in the central and southeast and less pronounced disparity in the southwest. County-level rurality and the proportion of owner-occupied housing were associated with the magnitude of the disparity, but only after accounting for other area-level covariates. This approach can help guide decisions and resource allocation at the local level.

BACKGROUND: Studies find that delivery hospital explains a significant portion of the Black-White gap in severe maternal morbidity. No such studies have focused on the US Southeast, where racial disparities are widest, and few have examined the relative contribution of hospital, residential, and maternal factors. OBJECTIVE: This study aimed to estimate the portion of Georgia's Black-White gap in severe maternal morbidity during delivery through 42 days postpartum explained by hospital, residential, and maternal factors. STUDY DESIGN: Using linked Georgia hospital discharge, birth, and fetal death records for 2016 through 2020, we identified 413,124 deliveries to non-Hispanic White (229,357; 56%) or Black (183,767; 44%) individuals. We linked hospital data from the American Hospital Association and Center for Medicare and Medicaid Services, and area data from the Area Resource File and American Community Survey. We identified severe maternal morbidity indicator conditions during delivery or subsequent hospitalizations through 42 days postpartum. Using race-specific logistic models followed by a decomposition technique, we estimated the portion of the Black-White severe maternal morbidity gap explained by the following: (1) sociodemographic factors (age, education, marital status, and nativity), (2) medical conditions (diabetes mellitus, gestational diabetes, chronic hypertension, gestational hypertension or preeclampsia, and smoking), (3) obstetrical factors (singleton or multiple, and birth order); (4) access to care (no or third trimester care, and payer), (5) hospital factors that are time-varying (delivery volume, deliveries per full-time equivalent nurse, doctor communication, patient safety, and adverse event composite score) or measured time-invariant characteristics (ownership, profit status, religious affiliation, teaching status, and perinatal level), and (6) residential factors (county urban/rural classification, percent uninsured women of reproductive age, obstetrician-gynecologists per women of reproductive age, number of federally-qualified and community health centers, medically-underserved area [yes/no], and census tract neighborhood deprivation index). We estimated models with and without hospital fixed-effects, which account for unobserved time-invariant hospital characteristics such as within-hospital care processes or unmeasured hospital-specific factors. RESULTS: There was 1.8 times the rate of severe maternal morbidity per 100 discharges among non-Hispanic Black (3.15) than among White (1.73) individuals, with an explained proportion of 30.4% in models without and 49.8% in models with hospital fixed-effects. In the latter, hospital fixed-effects explained the largest portion of the Black-White severe maternal morbidity gap (15.1%) followed by access to care (14.9%) and sociodemographic factors (14.4%), with residential factors being protective for Black individuals (-7.5%). Smaller proportions were explained by medical (5.6%), obstetrical (4.0%), and time-varying hospital factors (3.2%). Within each category, the largest explanatory portion was payer type (13.3%) for access to care, marital status (10.3%) for sociodemographic, gestational hypertension (3.3%) for medical, birth order (3.6%) for obstetrical, and patient safety indicator (3.1%) for time-varying hospital factors. CONCLUSION: Models with hospital fixed-effects explain a greater proportion of Georgia's Black-White severe maternal morbidity gap than models without them, thereby supporting the point that differences in care processes or other unmeasured factors within the same hospital translate into racial differences in severe maternal morbidity during delivery through 42 days postpartum. Research is needed to discern and ameliorate sources of within-hospital differences in care. The substantial proportion of the gap attributable to racial differences in access to care and sociodemographic factors points to other needed policy interventions.

We develop county-level measures of structural and institutional barriers to care, and test associations between these barriers and birth outcomes for US-born Black and White mothers using national birth records for 2014-2017. Results indicate elevated odds of greater preterm birth severity for Black mothers in counties with higher uninsurance rates among Black adults, fewer Black physicians per Black residents, and fewer publiclyfunded contraceptive services. Most structural barriers were not associated with small-for-gestational-age birth, and barriers defined for Black residents were not associated with birth outcomes for White mothers, with the exception of Black uninsurance rate. Structural determinants of care may influence preterm birth risk for Black Americans.

Disparities in maternal-child health outcomes by race and ethnicity highlight structural differences in the opportunity for optimal health in the United States. Examples of these differences include access to state-level social policies that promote maternal-child health. States vary in their racial and ethnic composition as a result of the complex history of policies and laws related to slavery, Indigenous genocide and relocation, segregation, immigration, and settlement in the United States. States also vary in the social policies they enact. As a result, correlations exist between the demographic makeup of a state's population and the presence or absence of social policies in that state. These correlations become a mechanism by which racial and ethnic disparities in maternal-child health outcomes can operate. In this commentary, we use the example of 3 labor-related policies actively under consideration at state and federal levels (paid parental leave, paid sick leave, and reasonable accommodations during pregnancy) to demonstrate how correlations between state demographics and presence of these state policies could cause or exacerbate racial and ethnic disparities in maternal-child health outcomes. We conclude with a call for researchers to consider how the geographic distribution of racialized populations and state policies could contribute to maternal-child health disparities.

Racial disparities in sexually transmitted infections (STIs) in the United States have been linked to social inequities. Gentrification instigates population-level shifts in housing markets and neighborhood racial/ethnic composition in ways that may impact the spatial distribution of STIs. This study assessed overlap in clusters of STIs, gentrification, social and economic disadvantage, and rental cost burden in Atlanta, Georgia, between 2005 and 2018. Overlap between gentrification and STIs among Black people was greater than that observed for the overlap between gentrification and STIs among White people. Overlap of STIs with social disadvantage and rental cost burden was more prominent among White people than Black people over time. Additional investigation into the factors behind the spatial dynamics observed in this study, and explanations for their variation by race, are necessary to inform where place-based efforts are targeted to reduce racial disparities in STI transmission in gentrifying cities.

To examine US in-hospital exclusive breastfeeding (EBF) and the associations with Baby-Friendly designation and neighborhood sociodemographic factors. Hospital data from the 2018 Maternity Practices in Infant Nutrition and Care survey were linked to hospital zip code tabulation area (ZCTA) sociodemographic data from the 2014–2018 American Community Survey (n = 2,024). The percentages of residents in the hospital ZCTA were dichotomized based on the relative mean percentage of the hospital’s metropolitan area, which were exposure variables (high/low Black hospitals, high/low poverty hospitals, high/low educational attainment hospitals) along with Baby-Friendly designation. Using linear regression, we examined the associations and effect measure modification between Baby-Friendly designation and hospital sociodemographic factors with in-hospital EBF prevalence. US mean in-hospital EBF prevalence was 55.1

Goal: Housing insecurity is associated with poor perinatal outcomes. However, we lack information on whether supportive housing policies improve perinatal health. Our goal was to estimate the effect of expiration of a statelevel eviction moratoria on adverse maternal and infant outcomes among Medicaid insured individuals residing in states with a state-level moratorium in place at conception in the United States. Methods: We used data from the US natality files, 2020-2022 and the Eviction Moratoria & Housing Policy dataset to link individuals with moratoria. We compared those for whom the moratorium expired prior to conception, in the first trimester, or second trimester (exposed) with those fully protected through gestation (unexposed) We fit log binomial models to estimated risk ratios (RRs) and 95% confidence intervals (CIs) for each outcome separately (preterm birth (PTB), very preterm birth (VPTB), low birthweight birth (LBW), very low birthweight birth (VLBW), primary cesarean, maternal morbidity, or adequate/adequate plus prenatal care utilization) using generalized estimating equations, controlling for month/year of conception, state (unemployment, monthly covid death rates per 100,000, median household income, governor's party affiliation 2019), and individual (primiparity, age, race/ethnicity) confounders. We also fit difference in difference models as an alternate approach. Results: We included 2,562,067 births (PTB: 12.5%, LBW: 8.1%, primary cesarean:14.1%). All adverse outcomes were more common for births where the moratoria expired prior to conception or during the first trimester. Following adjustment, risk remained significantly elevated for primary cesarean (preconception v. fully protected: RR: 1.08, 95% CI: 1.02, 1.14; first trimester: 1.05, 95% CI: 0.99, 1.11) but not other outcomes. Results from difference in difference models were consistent with multilevel models. Conclusions: Expiration of an eviction moratoria during the first or second trimester of pregnancy was not associated with increased risk of adverse birth outcomes, beyond ongoing state and temporal factors for people birthing in the United States during the COVID-19 global pandemic.

Introduction The prognosis of patients with acute myeloid leukemia (AML) is influenced by multiple factors, including patient-related characteristics, disease specifics, and treatment response. Measurable residual disease (MRD) monitoring during therapy and follow-up offers prognostic information essential for individualized treatment decisions. MRD positivity (MRDpos) prior to allogeneic hematopoietic cell transplantation (alloHCT) is associated with higher relapse rates. Alongside these factors, immunological interactions also influence the outcome of alloHCT. Some therapeutic interventions such as modifying conditioning intensity, require the prompt availability of the MRD status prior to transplant. Aims This study evaluated the prognostic value of a standardized, rapid (less than 5 minutes per sample) multiparametric flow cytometry (MFC) MRD approach (Röhnert, Leukemia 2022) before alloHCT. Additionally, we assessed the impact of HLA-DR expression before alloHCT on post-transplant outcomes as a potential prognostic biomarker of immune escape. Methods Bone marrow (BM) aspirates from AML patients undergoing alloHCT at the University Hospital TU Dresden were analyzed for MRD presence immediately before conditioning therapy. This MFC MRD approach allows the simultaneous MRD detection by the leukemia-associated immunophenotype (LAIP) and the different from normal (DfN) method. Our LAIP-based DfN analysis employs a hierarchical gating strategy with fixed gates, encompassing the core antigens recommended by ELN, including HLA-DR. The analysis checks simultaneously for 32 aberrant populations (both HLA-DRpos and HLA-DRneg). The MFC MRD results were not used to guide treatment decisions. Results From 2016 to 2022, we consecutively analyzed 185 patients by MFC-based MRD assessment within a median of 9 days (IQR 7-14 days) before alloHCT. The median follow-up time for the entire cohort was 32.7 months after alloHCT. Patients with an increased blast percentage (n=69) were included due to the increasing uncertainty about the importance of cytological remission before alloHCT. Before the start of the conditioning, a total of 76% (140/185) of patients were MRDpos. MRDpos before alloHCT was significantly correlated with inferior overall survival (OS) and relapse-free survival (RFS). The 2-year OS rate was significantly lower in the MRDpos cohort compared to MRDneg patients (65% vs. 89%, HR 4.3, p=0.002). Of all 185 patients, 116 were in hematologic remission before HCT. In this subgroup, the proportion of MRDpos patients was significantly lower compared to patients with persistent disease (63% versus 97%, p<0.001); remarkably 3% (2/69) of patients not in hematologic remission, were still MRDneg. Remarkably, the two patients who were not in remission by cytomorphology but were MRDneg by MFC did not relapse after alloHCT and showed an OS comparable with the MRDneg responder group. Among patients in hematologic remission before alloHCT (n=116), MRDpos patients exhibited higher relapse rates compared to MRDneg patients (33% vs. 14%, p=0.025), leading to significantly shorter 2-year OS (74% vs. 88%, HR 2.8, p=0.037) and 2-year RFS (59% vs. 81%, HR 2.1, p=0.048). Multivariable Cox regression models confirmed the prognostic significance of the MRD status. Notably, MRDpos patients with preserved HLA-DR expression (n=14) before alloHCT demonstrated a more favorable 2-year OS (89% vs. 62%, HR 0.3, p=0.08) compared to those with HLA-DR loss (n=126), with outcomes comparable to MRDneg patients. Molecular MRD assessment complemented MFC methods, showing concordant results in 75% of patients. Conclusions Our rapid semi-automated method of MRD evaluation by MFC allows a personalized risk prediction in AML patients undergoing alloHCT as a potential base for individual surveillance strategies. The association between pre-transplant HLA-DR expression on residual leukemic cells and post-transplant outcome indicates a possible interaction between phenotype and susceptibility to Graft-versus-Leukemia effect. Further research is warranted to elucidate the mechanistic basis of immune escape and its implications for post-transplant relapse, guiding the development of novel therapeutic strategies.