Publications by authors named "Paul S Albert"

246 Publications

Rejoinder to discussion on Is group testing ready for prime-time in disease identification?

Stat Med 2021 Jul;40(17):3892-3894

Biostatistics Branch, Division of Cancer Epidemiology and Genetics, National Cancer Institute, Rockville, Maryland, USA.

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http://dx.doi.org/10.1002/sim.9033DOI Listing
July 2021

Utility of interim blood tests for cancer screening in Li-Fraumeni syndrome.

Fam Cancer 2021 Jun 2. Epub 2021 Jun 2.

Clinical Genetics Branch, Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, 9609 Medical Center Drive, Bethesda, 20892, USA.

Comprehensive annual screening reduces cancer-related mortality in Li-Fraumeni syndrome (LFS), a cancer-prone disorder caused by pathogenic germline TP53 variants. Blood tests at months 4 and 8 between annual screening are recommended but their effectiveness in early cancer detection has not been established. Interim blood counts and inflammatory biomarkers were evaluated in 132 individuals with LFS (112 adults, 87 female, median age 36 years [range 3-68], median follow-up 37 months [range 2-70]) and test abnormalities were observed in 225 (35%). Thirteen cancers in 12 individuals were diagnosed between annual screenings but only one cancer (colorectal adenocarcinoma) was diagnosed due to an abnormal interim blood test. Fisher's exact test and generalized estimating equation models found no statistical associations between cancer diagnoses and any test abnormality. Four- and 8-monthly interim screening blood tests may not be of independent benefit for cancer detection in LFS, but annual cancer screening and personalized follow-up remain essential.
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http://dx.doi.org/10.1007/s10689-021-00265-xDOI Listing
June 2021

Simultaneous modeling of detection rate and exposure concentration using semi-continuous models to identify exposure determinants when left-censored data may be a true zero.

J Expo Sci Environ Epidemiol 2021 May 18. Epub 2021 May 18.

National Cancer Institute, Division of Cancer Epidemiology & Genetics, Biostatistics Branch, Rockville, MD, USA.

Background: Most methods for treating left-censored data assume the analyte is present but not quantified. Biased estimates may result if the analyte is absent such that the unobserved data represents a mixed exposure distribution with an unknown proportion clustered at zero.

Objective: We used semi-continuous models to identify time and industry trends in 52,457 OSHA inspection lead sample results.

Method: The first component of the semi-continuous model predicted the probability of detecting concentrations ≥ 0.007 mg/m (highest estimated detection limit, 62% of measurements). The second component predicted the median concentration of measurements ≥ 0.007 mg/m. Both components included a random-effect for industry and fixed-effects for year, industry group, analytical method, and other variables. We used the two components together to predict median industry- and time-specific lead concentrations.

Results: The probabilities of detectable concentrations and the median detected concentrations decreased with year; both were also lower for measurements analyzed for multiple (vs. one) metals and for those analyzed by inductively-coupled plasma (vs. atomic absorption spectroscopy). The covariance was 0.30 (standard error = 0.06), confirming the two components were correlated.

Significance: We identified determinants of exposure in data with over 60% left-censored, while accounting for correlated relationships and without assuming a distribution for the censored data.
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http://dx.doi.org/10.1038/s41370-021-00331-7DOI Listing
May 2021

Combination of Fundal Height and Ultrasound to Predict Small for Gestational Age at Birth.

Am J Perinatol 2021 May 3. Epub 2021 May 3.

Biostatistics Branch, Division of Cancer Epidemiology and Genetics, National Cancer Institute, Rockville, Maryland.

Objective:  The objective of the study was to determine whether adding longitudinal measures of fundal height (FH) to the standard cross-sectional FH to trigger third trimester ultrasound estimated fetal weight (EFW) would improve small for gestational age (SGA) prediction.

Study Design:  We developed a longitudinal FH calculator in a secondary analysis of a prospective cohort study of 1,939 nonobese pregnant women who underwent serial FH evaluations at 12 U.S. clinical sites. We evaluated cross-sectional FH measurement ≤ -3 cm at visit 3 (mean: 32.0 ± 1.6 weeks) versus the addition of longitudinal FH up to and including visit 3 to trigger an ultrasound to diagnose SGA defined as birthweight <10th percentile. If the FH cut points were not met, the SGA screen was classified as negative. If FH cut points were met and EFW was <10th percentile, the SGA screen was considered positive. If EFW was ≥10th percentile, the SGA screen was also considered negative. Sensitivity, specificity, and positive predictive value (PPV) and negative predictive value (NPV) were computed.

Results:  In a comparison of methods, 5.8% of women were classified as at risk of SGA by both cross-sectional and longitudinal classification methods; cross-sectional FH identified an additional 4.0%, and longitudinal fundal height identified a separate, additional 4.5%.Using cross-sectional FH as an ultrasound trigger, EFW had a PPV and NPV for SGA of 69 and 92%, respectively. After adding longitudinal FH, PPV increased to 74%, whereas NPV of 92% remained unchanged; however, the number of women who underwent triggered EFW decreased from 9.7 to 5.7%.

Conclusion:  An innovative approach for calculating longitudinal FH to the standard cross-sectional FH improved identification of SGA birthweight, while simultaneously reducing the number of triggered ultrasounds. As an essentially free-of-charge screening test, our novel method has potential to decrease costs as well as perinatal morbidity and mortality (through better prediction of SGA).

Key Points: · We have developed an innovative calculator for fundal height trajectory.. · Longitudinal fundal height improves detection of SGA.. · As a low cost screening test, the fundal height calculator may decrease costs and morbidity through better prediction of SGA..
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http://dx.doi.org/10.1055/s-0041-1728837DOI Listing
May 2021

Is group testing ready for prime-time in disease identification?

Stat Med 2021 Jul 28;40(17):3865-3880. Epub 2021 Apr 28.

Biostatistics Branch, Division of Cancer Epidemiology and Genetics, National Cancer Institute, Rockville, Maryland, USA.

Large-scale disease screening is a complicated process in which high costs must be balanced against pressing public health needs. When the goal is screening for infectious disease, one approach is group testing in which samples are initially tested in pools and individual samples are retested only if the initial pooled test was positive. Intuitively, if the prevalence of infection is small, this could result in a large reduction of the total number of tests required. Despite this, the use of group testing in medical studies has been limited, largely due to skepticism about the impact of pooling on the accuracy of a given assay. While there is a large body of research addressing the issue of testing errors in group testing studies, it is customary to assume that the misclassification parameters are known from an external population and/or that the values do not change with the group size. Both of these assumptions are highly questionable for many medical practitioners considering group testing in their study design. In this article, we explore how the failure of these assumptions might impact the efficacy of a group testing design and, consequently, whether group testing is currently feasible for medical screening. Specifically, we look at how incorrect assumptions about the sensitivity function at the design stage can lead to poor estimation of a procedure's overall sensitivity and expected number of tests. Furthermore, if a validation study is used to estimate the pooled misclassification parameters of a given assay, we show that the sample sizes required are so large as to be prohibitive in all but the largest screening programs.
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http://dx.doi.org/10.1002/sim.9003DOI Listing
July 2021

IFN-λ4 is associated with increased risk and earlier occurrence of several common infections in African children.

Genes Immun 2021 May 13;22(1):44-55. Epub 2021 Apr 13.

Laboratory of Malaria Immunology and Vaccinology, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, MD, 20892, USA.

Genetic polymorphisms within the IFNL3/IFNL4 genomic region, which encodes type III interferons, have been strongly associated with clearance of hepatitis C virus. We hypothesized that type III interferons might be important for the immune response to other pathogens as well. In a cohort of 914 Malian children, we genotyped functional variants IFNL4-rs368234815, IFNL4-rs117648444, and IFNL3-rs4803217 and analyzed episodes of malaria, gastrointestinal, and respiratory infections recorded at 30,626 clinic visits from birth up to 5 years of age. Compared to children with the rs368234815-TT/TT genotype (IFN-λ4-Null), rs368234815-dG allele was most strongly associated with an earlier time-to-first episode of gastrointestinal infections (p = 0.003). The risk of experiencing an infection episode during the follow-up was also significantly increased with rs368234815-dG allele, with OR = 1.53, 95%CI (1.13-2.07), p = 0.005 for gastrointestinal infections and OR = 1.30, 95%CI (1.02-1.65), p = 0.033 for malaria. All the associations for the moderately linked rs4803217 (r = 0.78 in this set) were weaker and lost significance after adjusting for rs368234815. We also analyzed all outcomes in relation to IFN-λ4-P70S groups. Our results implicate IFN-λ4 and not IFN-λ3 as the primary functional cause of genetic associations with increased overall risk and younger age at first clinical episodes but not with recurrence or intensity of several common pediatric infections.
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http://dx.doi.org/10.1038/s41435-021-00127-7DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8042471PMC
May 2021

Hidden mover-stayer model for disease progression accounting for misclassified and partially observed diagnostic tests: Application to the natural history of human papillomavirus and cervical precancer.

Stat Med 2021 07 12;40(15):3460-3476. Epub 2021 Apr 12.

Biostatistics Branch, Division of Cancer and Epidemiology, National Cancer Institute, Rockville, Maryland, USA.

Hidden Markov models (HMMs) have been proposed to model the natural history of diseases while accounting for misclassification in state identification. We introduce a discrete time HMM for human papillomavirus (HPV) and cervical precancer/cancer where the hidden and observed state spaces are defined by all possible combinations of HPV, cytology, and colposcopy results. Because the population of women undergoing cervical cancer screening is heterogeneous with respect to sexual behavior, and therefore risk of HPV acquisition and subsequent precancers, we use a mover-stayer mixture model that assumes a proportion of the population will stay in the healthy state and are not subject to disease progression. As each state is a combination of three distinct tests that characterize the cervix, partially observed data arise when at least one but not every test is observed. The standard forward-backward algorithm, used for evaluating the E-step within the E-M algorithm for maximum-likelihood estimation of HMMs, cannot incorporate time points with partially observed data. We propose a new forward-backward algorithm that considers all possible fully observed states that could have occurred across a participant's follow-up visits. We apply our method to data from a large management trial for women with low-grade cervical abnormalities. Our simulation study found that our method has relatively little bias and out preforms simpler methods that resulted in larger bias.
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http://dx.doi.org/10.1002/sim.8977DOI Listing
July 2021

Nighttime features derived from topic models for classification of patients with COPD.

Comput Biol Med 2021 05 10;132:104322. Epub 2021 Mar 10.

Philips Research, Data Science Department, Eindhoven, the Netherlands.

Nighttime symptoms are important indicators of impairment for many diseases and particularly for respiratory diseases such as chronic obstructive pulmonary disease (COPD). The use of wearable sensors to assess sleep in COPD has mainly been limited to the monitoring of limb motions or the duration and continuity of sleep. In this paper we present an approach to concisely describe sleep patterns in subjects with and without COPD. The methodology converts multimodal sleep data into a text representation and uses topic modeling to identify patterns across the dataset composed of more than 6000 assessed nights. This approach enables the discovery of higher level features resembling unique sleep characteristics that are then used to discriminate between healthy subjects and those with COPD and to evaluate patients' disease severity and dyspnea level. Compared to standard features, the discovered latent structures in nighttime data seem to capture important aspects of subjects sleeping behavior related to the effects of COPD and dyspnea.
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http://dx.doi.org/10.1016/j.compbiomed.2021.104322DOI Listing
May 2021

New insights into modeling exposure measurements below the limit of detection.

Environ Epidemiol 2021 Feb 16;5(1):e116. Epub 2020 Dec 16.

Biostatistics Branch, Division Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, Maryland; and.

In environmental epidemiology, it is of interest to assess the health effects of environmental exposures. Some exposure analytes present values that are below the laboratory limit of detection (LOD). There have been many methods proposed for handling this issue to incorporate exposures subject to LOD in risk modeling using logistic regression. We present a fresh look at proposed methods to handle exposure analytes that present values that are below the LOD.

Methods: We performed comparisons through an extensive simulation study and a cancer epidemiology example. The methods we considered were a maximum-likelihood approach, multiple imputation, Cox regression, complete case analysis, filling in values below the LOD with , and a missing indicator method.

Results: We found that the logistic regression coefficient associated with the exposure (subject to LOD) can be severely biased when underlying assumptions are not met, even with a relatively small proportion (under 20%) of measurements below the LOD.

Conclusions: We propose the use of a simple method where the relationship between the analyte and disease risk is modeled only above the detection limit with an intercept term at the LOD and a slope parameter, which makes no assumptions about what happens below the LOD. In most practical situations, our results suggest that this simple method may be the best choice for analyzing analytes with detection limits.
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http://dx.doi.org/10.1097/EE9.0000000000000116DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7939440PMC
February 2021

Plasma lipidomics profile in pregnancy and gestational diabetes risk: a prospective study in a multiracial/ethnic cohort.

BMJ Open Diabetes Res Care 2021 03;9(1)

Epidemiology Branch, Division of Intramural Population Health Research, Eunice Kennedy Shriver National Institute of Child Health and Human Development, Bethesda, Maryland, USA

Introduction: Disruption of lipid metabolism is implicated in gestational diabetes (GDM). However, prospective studies on lipidomics and GDM risk in race/ethnically diverse populations are sparse. Here, we aimed to (1) identify lipid networks in early pregnancy to mid-pregnancy that are associated with subsequent GDM risk and (2) examine the associations of lipid networks with glycemic biomarkers to understand the underlying mechanisms.

Research Design And Methods: This study included 107 GDM cases confirmed using the Carpenter and Coustan criteria and 214 non-GDM matched controls from the National Institute of Child Health and Human Development Fetal Growth Studies-Singleton cohort, untargeted lipidomics data of 420 metabolites (328 annotated and 92 unannotated), and information on glycemic biomarkers in maternal plasma at visit 0 (10-14 weeks) and visit 1 (15-26 weeks). We constructed lipid networks using weighted correlation network analysis technique. We examined prospective associations of lipid networks and individual lipids with GDM risk using linear mixed effect models. Furthermore, we calculated Pearson's partial correlation for GDM-related lipid networks and individual lipids with plasma glucose, insulin, C-peptide and glycated hemoglobin at both study visits.

Results: Lipid networks primarily characterized by elevated plasma diglycerides and short, saturated/low unsaturated triglycerides and lower plasma cholesteryl esters, sphingomyelins and phosphatidylcholines were associated with higher risk of developing GDM (false discovery rate (FDR) <0.05). Among individual lipids, 58 metabolites at visit 0 and 96 metabolites at visit 1 (40 metabolites at both time points) significantly differed between women who developed GDM and who did not (FDR <0.05). Furthermore, GDM-related lipid networks and individual lipids showed consistent correlations with maternal glycemic markers particularly in early pregnancy at visit 0.

Conclusions: Plasma lipid metabolites in early pregnancy both individually and interactively in distinct networks were associated with subsequent GDM risk in race/ethnically diverse US women. Future research is warranted to assess lipid metabolites as etiologic markers of GDM.
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http://dx.doi.org/10.1136/bmjdrc-2020-001551DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7939004PMC
March 2021

Nutrition during Pregnancy: Findings from the National Institute of Child Health and Human Development (NICHD) Fetal Growth Studies-Singleton Cohort.

Curr Dev Nutr 2021 Jan 24;5(1):nzaa182. Epub 2020 Dec 24.

Division of Intramural Population Health Research, Eunice Kennedy Shriver National Institute of Child Health and Human Development, NIH, Bethesda, MD, USA.

Background: Accumulating evidence indicates that maternal diets are important for optimizing maternal and offspring health. Existing research lacks comprehensive profiles of maternal diets throughout pregnancy, especially in a racially/ethnically diverse obstetrical population.

Objective: The aim was to characterize diets in a longitudinal US pregnancy cohort by trimester, race/ethnicity, and prepregnancy BMI.

Methods: Data were obtained from pregnant women in the National Institute of Child Health and Human Development (NICHD) Fetal Growth Studies-Singleton cohort (2009-2013). A food-frequency questionnaire (FFQ) at 8-13 wk of gestation assessed periconception and first-trimester diet (= 1615). Automated, self-administered, 24-h dietary recalls targeted at 16-22, 24-29, 30-33, and 34-37 wk of gestation assessed second- and third-trimester diets (= 1817 women/6791 recalls). The Healthy Eating Index-2010 (HEI-2010) assessed diet quality (i.e., adherence to US Dietary Guidelines). Variations in weighted energy-adjusted means for foods and nutrients were examined by trimester, self-identified race/ethnicity, and self-reported prepregnancy BMI.

Results: Mean (95% CI) HEI-2010 was 65.9 (64.9, 67.0) during periconception to the first trimester assessed with an FFQ and 51.6 (50.8, 52.4) and 51.5 (50.7, 52.3) during the second trimester and third trimester, respectively, assessed using 24-h recalls. No significant differences were observed between the second and third trimester in macronutrients, micronutrients, foods, or HEI-2010 components (≥ 0.05). Periconception to first-trimester HEI-2010 was highest among Asian/Pacific Islander [67.2 (65.9, 68.6)] and lowest among non-Hispanic Black [58.7 (57.5, 60.0)] women and highest among women with normal weight [67.2 (66.1, 68.4)] and lowest among women with obesity [63.5 (62.1, 64.9)]. Similar rankings were observed in the second/third trimesters.

Conclusions: Most pregnant women in this cohort reported dietary intakes that, on average, did not meet US Dietary Guidelines for nonpregnant individuals. Also, diet differed across race/ethnic groups and by prepregnancy BMI, with the lowest overall dietary quality in all trimesters among non-Hispanic Black women and women with obesity. No meaningful changes in dietary intake were observed between the second and third trimesters.
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http://dx.doi.org/10.1093/cdn/nzaa182DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7846139PMC
January 2021

Impact of Population Growth and Aging on Estimates of Excess U.S. Deaths During the COVID-19 Pandemic, March to August 2020.

Ann Intern Med 2021 04 15;174(4):437-443. Epub 2020 Dec 15.

National Cancer Institute, Rockville, Maryland (M.S.S., J.S.A., M.G., P.S.A., N.D.F., A.B.D.).

Background: Excess death estimates quantify the full impact of the coronavirus disease 2019 (COVID-19) pandemic. Widely reported U.S. excess death estimates have not accounted for recent population changes, especially increases in the population older than 65 years.

Objective: To estimate excess deaths in the United States in 2020, after accounting for population changes.

Design: Surveillance study.

Setting: United States, March to August 2020.

Participants: All decedents.

Measurements: Age-specific excess deaths in the United States from 1 March to 31 August 2020 compared with 2015 to 2019 were estimated, after changes in population size and age were taken into account, by using Centers for Disease Control and Prevention provisional death data and U.S. Census Bureau population estimates. Cause-specific excess deaths were estimated by month and age.

Results: From March through August 2020, 1 671 400 deaths were registered in the United States, including 173 300 COVID-19 deaths. An average of 1 370 000 deaths were reported over the same months during 2015 to 2019, for a crude excess of 301 400 deaths (128 100 non-COVID-19 deaths). However, the 2020 U.S. population includes 5.04 million more persons aged 65 years and older than the average population in 2015 to 2019 (a 10% increase). After population changes were taken into account, an estimated 217 900 excess deaths occurred from March through August 2020 (173 300 COVID-19 and 44 600 non-COVID-19 deaths). Most excess non-COVID-19 deaths occurred in April, July, and August, and 34 900 (78%) were in persons aged 25 to 64 years. Diabetes, Alzheimer disease, and heart disease caused the most non-COVID-19 excess deaths.

Limitation: Provisional death data are underestimated because of reporting delays.

Conclusion: The COVID-19 pandemic resulted in an estimated 218 000 excess deaths in the United States between March and August 2020, and 80% of those deaths had COVID-19 as the underlying cause. Accounting for population changes substantially reduced the excess non-COVID-19 death estimates, providing important information for guiding future clinical and public health interventions.

Primary Funding Source: National Cancer Institute.
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http://dx.doi.org/10.7326/M20-7385DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7901655PMC
April 2021

Common variants in signaling transcription-factor-binding sites drive phenotypic variability in red blood cell traits.

Nat Genet 2020 12 23;52(12):1333-1345. Epub 2020 Nov 23.

Division of Genetics, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA.

Genome-wide association studies identify genomic variants associated with human traits and diseases. Most trait-associated variants are located within cell-type-specific enhancers, but the molecular mechanisms governing phenotypic variation are less well understood. Here, we show that many enhancer variants associated with red blood cell (RBC) traits map to enhancers that are co-bound by lineage-specific master transcription factors (MTFs) and signaling transcription factors (STFs) responsive to extracellular signals. The majority of enhancer variants reside on STF and not MTF motifs, perturbing DNA binding by various STFs (BMP/TGF-β-directed SMADs or WNT-induced TCFs) and affecting target gene expression. Analyses of engineered human blood cells and expression quantitative trait loci verify that disrupted STF binding leads to altered gene expression. Our results propose that the majority of the RBC-trait-associated variants that reside on transcription-factor-binding sequences fall in STF target sequences, suggesting that the phenotypic variation of RBC traits could stem from altered responsiveness to extracellular stimuli.
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http://dx.doi.org/10.1038/s41588-020-00738-2DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7876911PMC
December 2020

Methylated DNA Markers of Esophageal Squamous Cancer and Dysplasia: An International Study.

Cancer Epidemiol Biomarkers Prev 2020 12 18;29(12):2642-2650. Epub 2020 Sep 18.

Department of Gastroenterology and Hepatology, Mayo Clinic, Rochester, Minnesota.

Background: Discovery of methylated DNA markers (MDM) of esophageal squamous cell carcinoma (ESCC) has sparked interest in assessing these markers in tissue. We evaluated MDMs in ESCC from three geographically and ethnically distinct populations, and explored the feasibility of assaying MDMs from DNA obtained by swallowed balloon devices.

Methods: MDMs were assayed in ESCC and normal tissues obtained from the populations of United States, Iran, and China, and from exfoliative cytology specimens obtained by balloons in a Chinese population. Areas under the receiver operating curve (AUC) of MDMs discriminating ESCC from normal tissues were calculated. Random forest prediction models were built, trained on U.S. cases and controls, and calibrated to U.S.-only controls (model 1) and three-country controls (model 2). Statistical tests were used to assess the relationship between dysplasia and MDM levels in balloons.

Results: Extracted DNA from 333 ESCC and 322 normal tissues was analyzed, in addition to archival DNA from 98 balloons. For ESCC, model 1 validated in Iranian and Chinese tissues with AUCs of 0.90 and 0.87, and model 2 yielded AUCs of 0.99, 0.96, and 0.94 in tissues from the United States, Iran, and China, respectively. In Chinese balloons, MDMs showed a statistically significant trend of increasing levels with increasing grades of dysplasia ( < 0.004).

Conclusions: MDMs accurately discriminate ESCC from normal esophagus in tissues obtained from high- and low-incidence countries. Preliminary data suggest that levels of MDMs assayed in DNA from swallowed balloon devices increase with dysplasia grade. Larger studies are needed to validate these results.

Impact: MDMs coupled with minimally invasive collection methods have the potential for worldwide application in ESCC screening.
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http://dx.doi.org/10.1158/1055-9965.EPI-20-0616DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7710574PMC
December 2020

Statistical approaches using longitudinal biomarkers for disease early detection: A comparison of methodologies.

Stat Med 2020 12 16;39(29):4405-4420. Epub 2020 Sep 16.

Biostatistics Branch, Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, Maryland, USA.

Early detection of clinical outcomes such as cancer may be predicted using longitudinal biomarker measurements. Tracking longitudinal biomarkers as a way to identify early disease onset may help to reduce mortality from diseases like ovarian cancer that are more treatable if detected early. Two disease risk prediction frameworks, the shared random effects model (SREM) and the pattern mixture model (PMM) could be used to assess longitudinal biomarkers on disease early detection. In this article, we studied the discrimination and calibration performances of SREM and PMM on disease early detection through an application to ovarian cancer, where early detection using the risk of ovarian cancer algorithm (ROCA) has been evaluated. Comparisons of the above three approaches were performed via analyses of the ovarian cancer data from the Prostate, Lung, Colorectal, and Ovarian Cancer Screening Trial. Discrimination was evaluated by the time-dependent receiver operating characteristic curve and its area, while calibration was assessed using calibration plot and the ratio of observed to expected number of diseased subjects. The out-of-sample performances were calculated via using leave-one-out cross-validation, aiming to minimize potential model overfitting. A careful analysis of using the biomarker cancer antigen 125 for ovarian cancer early detection showed significantly improved discrimination performance of PMM as compared with SREM and ROCA, nevertheless all approaches were generally well calibrated. Robustness of all approaches was further investigated in extensive simulation studies. The improved performance of PMM relative to ROCA is in part due to the fact that the biomarker measurements were taken at a yearly interval, which is not frequent enough to reliably estimate the changepoint or the slope after changepoint in cases under ROCA.
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http://dx.doi.org/10.1002/sim.8731DOI Listing
December 2020

An imputation approach for fitting two-part mixed effects models for longitudinal semi-continuous data.

Stat Methods Med Res 2020 11 11;29(11):3351-3361. Epub 2020 Jun 11.

Biostatistics Branch, Division of Cancer Epidemiology and Genetics, 3421National Cancer Institute, MD, USA.

Two-part mixed effects models are often used for analyzing longitudinal data with many zeros. Typically, these models are formulated with binary and continuous components separately with random effects that are correlated between the two components. Researchers have developed maximum-likelihood and Bayesian approaches for fitting these models that often require using particular software packages or very specialized software. We propose an imputation approach that will allow practitioners to separately use standard linear and generalized linear mixed models to estimate the fixed effects for two-part mixed effects models with complex random effects structures. An approximation to the conditional distribution of positive measurements given an individual's pattern of non-zero measurements is proposed that can be easily estimated and then imputed from. We show that for a wide range of parameter values, the imputation approach results in nearly unbiased estimation and can be implemented with standard software. We illustrate the proposed imputation approach for the analysis of longitudinal clinical trial data with many zeros.
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http://dx.doi.org/10.1177/0962280220927720DOI Listing
November 2020

Dicamba use and cancer incidence in the agricultural health study: an updated analysis.

Int J Epidemiol 2020 08;49(4):1326-1337

Occupational and Environmental Epidemiology Branch, Division of Cancer Epidemiology and Genetics, National Cancer Institute, Rockville, MD, USA.

Background: The herbicide dicamba has been commonly used agriculturally and residentially. Recent approval of genetically engineered dicamba-resistant crops is expected to lead to increased dicamba use, and there has been growing interest in potential human health effects. A prior analysis in the Agricultural Health Study (AHS) suggested associations between dicamba and colon and lung cancer. We re-evaluated dicamba use in the AHS, including an additional 12 years and 2702 exposed cancers.

Methods: The AHS is a prospective cohort of pesticide applicators in Iowa and North Carolina. At enrollment (1993-1997) and follow-up (1999-2005), participants reported dicamba use. Exposure was characterized by cumulative intensity-weighted lifetime days, including exposure lags of up to 20 years. We estimated relative risks (RR) and 95% confidence intervals (CI) using multivariable Poisson regression for incident cancers diagnosed from enrollment through 2014/2015.

Results: Among 49 922 applicators, 26 412 (52.9%) used dicamba. Compared with applicators reporting no dicamba use, those in the highest quartile of exposure had elevated risk of liver and intrahepatic bile duct cancer (nexposed = 28, RRQ4 = 1.80, CI: 1.26-2.56, Ptrend < 0.001) and chronic lymphocytic leukaemia (CLL, nexposed = 93, RRQ4 = 1.20, CI: 0.96-1.50, Ptrend = 0.01) and decreased risk of myeloid leukaemia (nexposed = 55, RRQ4 = 0.73, CI: 0.51-1.03, Ptrend = 0.01). The associations for liver cancer and myeloid leukaemia remained after lagging exposure of up to 20 years.

Conclusions: With additional follow-up and exposure information, associations with lung and colon cancer were no longer apparent. In this first evaluation of liver and intrahepatic bile duct cancer, there was an association with increasing use of dicamba that persisted across lags of up to 20 years.
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http://dx.doi.org/10.1093/ije/dyaa066DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7660157PMC
August 2020

A hidden Markov modeling approach for identifying tumor subclones in next-generation sequencing studies.

Biostatistics 2020 Apr 13. Epub 2020 Apr 13.

Biostatistics Branch, Division of Cancer Epidemiology and Genetics, National Cancer Institute, 9609 Medical Center Dr, Rockville MD 20850 USA.

Allele-specific copy number alteration (ASCNA) analysis is for identifying copy number abnormalities in tumor cells. Unlike normal cells, tumor cells are heterogeneous as a combination of dominant and minor subclones with distinct copy number profiles. Estimating the clonal proportion and identifying mainclone and subclone genotypes across the genome are important for understanding tumor progression. Several ASCNA tools have recently been developed, but they have been limited to the identification of subclone regions, and not the genotype of subclones. In this article, we propose subHMM, a hidden Markov model-based approach that estimates both subclone region and region-specific subclone genotype and clonal proportion. We specify a hidden state variable representing the conglomeration of clonal genotype and subclone status. We propose a two-step algorithm for parameter estimation, where in the first step, a standard hidden Markov model with this conglomerated state variable is fit. Then, in the second step, region-specific estimates of the clonal proportions are obtained by maximizing region-specific pseudo-likelihoods. We apply subHMM to study renal cell carcinoma datasets in The Cancer Genome Atlas. In addition, we conduct simulation studies that show the good performance of the proposed approach. The R source code is available online at https://dceg.cancer.gov/tools/analysis/subhmm. Expectation-Maximization algorithm; Forward-backward algorithm; Somatic copy number alteration; Tumor subclones.
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http://dx.doi.org/10.1093/biostatistics/kxaa013DOI Listing
April 2020

Diesel Exhaust Exposure during Farming Activities: Statistical Modeling of Continuous Black Carbon Concentrations.

Ann Work Expo Health 2020 06;64(5):503-513

Occupational and Environmental Epidemiology Branch, Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, MD, USA.

Objectives: Daily driving of diesel-powered tractors has been linked to increased lung cancer risk in farmers, yet few studies have quantified exposure levels to diesel exhaust during tractor driving or during other farm activities. We expanded an earlier task-based descriptive investigation of factors associated with real-time exposure levels to black carbon (BC, a surrogate of diesel exhaust) in Iowa farmers by increasing the sample size, collecting repeated measurements, and applying statistical models adapted to continuous measurements.

Methods: The expanded study added 43 days of sampling, for a total of 63 sample days conducted in 2015 and 2016 on 31 Iowa farmers. Real-time, continuous monitoring (30-s intervals) of personal BC concentrations was performed using a MicroAeth AE51 microaethelometer affixed with a micro-cyclone. A field researcher recorded information on tasks, fuel type, farmer location, and proximity to burning biomass. We evaluated the influence of these variables on log-transformed BC concentrations using a linear mixed-effect model with random effects for farmer and day and a first-order autoregressive structure for within-day correlation.

Results: Proximity to diesel-powered equipment was observed for 42.5% of the overall sampling time and on 61 of the 63 sample days. Predicted geometric mean BC concentrations were highest during grain bin work, loading, and harvesting, and lower for soil preparation and planting. A 68% increase in BC concentrations was predicted for close proximity to a diesel-powered vehicle, relative to far proximity, while BC concentrations were 44% higher in diesel vehicles with open cabins compared with closed cabins. Task, farmer location, fuel type, and proximity to burning biomass explained 8% of within-day variance in BC concentrations, 2% of between-day variance, and no between-farmer variance.

Conclusion: Our findings showed that farmers worked frequently near diesel equipment and that BC concentrations varied between tasks and by fuel type, farmer location, and proximity to burning biomass. These results could support the development of exposure models applicable to investigations of health effects in farmers associated with exposure to diesel engine exhaust.
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http://dx.doi.org/10.1093/annweh/wxaa032DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7313260PMC
June 2020

Glycaemic status during pregnancy and longitudinal measures of fetal growth in a multi-racial US population: a prospective cohort study.

Lancet Diabetes Endocrinol 2020 04 2;8(4):292-300. Epub 2020 Mar 2.

Division of Intramural Population Health Research, Eunice Kennedy Shriver National Institute of Child Health and Human Development, National Institutes of Health, Bethesda, MD, USA. Electronic address:

Background: The timepoint at which fetal growth begins to differ by maternal glycaemic status is not well understood. To address this lack of data, we examined gestational diabetes, impaired glucose tolerance, and early pregnancy glucose concentrations in relation to fetal growth trajectories.

Methods: This cohort study included 2458 pregnant women from the NICHD Fetal Growth Studies-Singletons study, which took place between 2009 and 2013. Women were recruited from 12 clinical centres in the USA. Women aged 18-40 years without major chronic conditions when entering pregnancy were included and those with records of neither glucose screening test or glucose tolerance test were excluded from the study. Women were enrolled at gestational weeks 8-13 and randomly assigned to four ultrasonogram schedules (Group A; weeks 16, 24, 30, 34; Group B: weeks 18, 26, 31, 35, 39; Group C: weeks 20, 28, 32, 36; Group D: weeks 22, 29, 33, 37, 41) to capture weekly fetal growth. Gestational diabetes, impaired glucose tolerance, and normal glucose tolerance were defined by medical record review. Glucose was measured in a subsample of women at weeks 10-14. We modelled fetal growth trajectories using linear mixed models with cubic splines. This study is registered with ClinicalTrials.gov, NCT00912132.

Findings: Of the 2458 women included in this study, 107 (4·4%) had gestational diabetes, 118 (4·8%) had impaired glucose tolerance, and 2020 (82·2%) had NGT. 213 women were excluded from the main analysis. The cohort with gestational diabetes was associated with a larger estimated fetal weight that started at week 20 and was significant at week 28-40 (at week 37: 3061 g [95% CI 2967-3164] for women with gestational diabetes vs 2943 g [2924-2962] for women with normal glucose tolerance, adjusted p=0·02). In addition, glucose levels at weeks 10-14 were positively associated with estimated fetal weight starting at week 23 and the association became significant at week 27 (at week 37: 3073 g [2983-3167] in the highest tertile vs 2853 g [2755-2955] in the lowest tertile, adjusted p=0·0009.

Interpretation: Gestational diabetes was associated with a larger fetal size that started at week 20 and became significant at gestational week 28. Efforts to mitigate gestational diabetes-related fetal overgrowth should start before 24-28 gestational weeks, when gestational diabetes is typically screened for in the USA.

Funding: National Institutes of Health.
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http://dx.doi.org/10.1016/S2213-8587(20)30024-3DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7676113PMC
April 2020

Nonparametric estimation of distributions and diagnostic accuracy based on group-tested results with differential misclassification.

Biometrics 2020 12 5;76(4):1147-1156. Epub 2020 Mar 5.

Biostatistics Branch, Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, Maryland.

This article concerns the problem of estimating a continuous distribution in a diseased or nondiseased population when only group-based test results on the disease status are available. The problem is challenging in that individual disease statuses are not observed and testing results are often subject to misclassification, with further complication that the misclassification may be differential as the group size and the number of the diseased individuals in the group vary. We propose a method to construct nonparametric estimation of the distribution and obtain its asymptotic properties. The performance of the distribution estimator is evaluated under various design considerations concerning group sizes and classification errors. The method is exemplified with data from the National Health and Nutrition Examination Survey study to estimate the distribution and diagnostic accuracy of C-reactive protein in blood samples in predicting chlamydia incidence.
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http://dx.doi.org/10.1111/biom.13236DOI Listing
December 2020

Modeling repeated labor curves in consecutive pregnancies: Individualized prediction of labor progression from previous pregnancy data.

Stat Med 2020 04 14;39(8):1068-1083. Epub 2020 Jan 14.

Biostatistics Branch, Division of Cancer Epidemiology and Genetics, National Cancer Institute, NIH, Bethesda, Maryland.

The measurement of cervical dilation of a pregnant woman is used to monitor the progression of labor until 10 cm when pushing begins. There is anecdotal evidence that labor tracks across repeated pregnancies; moreover, no statistical methodology has been developed to address this important issue, which can help obstetricians make more informed clinical decisions about an individual woman's progression. Motivated by the NICHD Consecutive Pregnancies Study (CPS), we propose new methodology for analyzing labor curves across consecutive pregnancies. Our focus is both on studying the correlation between repeated labor curves on the same woman and on using the cervical dilation data from prior pregnancies to predict subsequent labor curves. We propose a hierarchical random effects model with a random change point that characterizes repeated labor curves within and between women to address these issues. We employ Bayesian methodology for parameter estimation and prediction. Model diagnostics to examine the appropriateness of the hierarchical random effects structure for characterizing the dependence structure across consecutive pregnancies are also proposed. The methodology was used in analyzing the CPS data and in developing a predictor for labor progression that can be used in clinical practice.
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http://dx.doi.org/10.1002/sim.8462DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7171572PMC
April 2020

Revisiting Nested Group Testing Procedures: New Results, Comparisons, and Robustness.

Am Stat 2019 4;73(2):117-125. Epub 2018 Jun 4.

Biostatistics Branch, Division of Cancer Epidemiology and Genetics National Cancer Institute, Rockville, MD.

Group testing has its origin in the identification of syphilis in the U.S. army during World War II. Much of the theoretical framework of group testing was developed starting in the late 1950s, with continued work into the 1990s. Recently, with the advent of new laboratory and genetic technologies, there has been an increasing interest in group testing designs for cost saving purposes. In this article, we compare different nested designs, including Dorfman, Sterrett and an optimal nested procedure obtained through dynamic programming. To elucidate these comparisons, we develop closed-form expressions for the optimal Sterrett procedure and provide a concise review of the prior literature for other commonly used procedures. We consider designs where the prevalence of disease is known as well as investigate the robustness of these procedures, when it is incorrectly assumed. This article provides a technical presentation that will be of interest to researchers as well as from a pedagogical perspective. Supplementary material for this article available online.
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http://dx.doi.org/10.1080/00031305.2017.1366367DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6896989PMC
June 2018

Incorporating retesting outcomes for estimation of disease prevalence.

Stat Med 2020 03 23;39(6):687-697. Epub 2019 Nov 23.

Biostatistics Branch, Division of Cancer Epidemiology and Genetics, National Institutes of Health, Rockville, Maryland.

Group testing has been widely used as a cost-effective strategy to screen for and estimate the prevalence of a rare disease. While it is well-recognized that retesting is necessary for identifying infected subjects, it is not required for estimating the prevalence. For a test without misclassification, gains in statistical efficiency are expected from incorporating retesting results in the estimation of the prevalence. However, when the test is subject to misclassification, it is not clear how much gain should be expected. There are a number of theoretical challenges in addressing this issue, including (1) enumerating the potential test results from retesting individual subjects in a group, (2) the dependence among these test results and the test result from testing at the group level, and (3) differential misclassification due to pooling of biospecimens. Overcoming some of these challenges, we show that retesting subjects in either positive or negative groups can substantially improve the efficiency of the estimation and that retesting positive groups yields higher efficiency than retesting a same number or proportion of negative groups.
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http://dx.doi.org/10.1002/sim.8439DOI Listing
March 2020

Association of Cardiovascular Disease With Premature Mortality in the United States.

JAMA Cardiol 2019 12;4(12):1230-1238

Division of Cancer Epidemiology and Genetics, National Cancer Institute, Rockville, Maryland.

Importance: Cardiovascular disease (CVD) is a leading cause of morbidity and mortality in the United States. Despite substantial declines in CVD mortality rates during past decades, progress against cardiovascular deaths in midlife has stagnated, with rates increased in some US racial/ethnic groups.

Objective: To examine the trends in premature (ages 25-64 years) mortality from CVD from 2000 to 2015 by demographics and county-level factors, including education, rurality, and the prevalence of smoking, obesity, and diabetes.

Design, Setting, And Participants: This descriptive study used US national mortality data from the Surveillance, Epidemiology, and End Results data set and included all CVD deaths among individuals ages 25 to 64 years from January 2000 to December 2015. The data analysis began in February 2018.

Exposures: Age, sex, race/ethnicity, and county-level factors.

Main Outcomes And Measures: Age-standardized mortality rates and average annual percent change (AAPC) in rates by age, sex, race/ethnicity, and county-level factors (in quintiles) and relative risks of CVD mortality across quintiles of each county-level factor.

Results: In 2000 to 2015, 2.3 million CVD deaths occurred among individuals age 25 to 64 years in the United States. There were significant declines in CVD mortality for black, Latinx, and Asian and Pacific Islander individuals (AAPC: range, -1.7 to -3.2%), although black people continued to have the highest CVD mortality rates. Mortality rates were second highest for American Indian/Alaskan Native individuals and increased significantly among those aged 25 to 49 years (AAPC: women, 2.1%; men, 1.3%). For white individuals, mortality rates plateaued among women age 25 to 49 years (AAPC, 0.05%). Declines in mortality rates were observed for most major CVD subtypes except for ischemic heart disease, which was stable in white women and increased in American Indian/Alaska Native women, hypertensive heart disease, for which significant increases in rates were observed in most racial/ethnic groups, and endocarditis, for which rates increased in white individuals and American Indian/Alaska Native men. Counties with the highest prevalence of diabetes (quintile 5 vs quintile 1: relative risk range 1.6-1.8 for white individuals and 1.4-1.6 for black individuals) had the most risk of CVD mortality.

Conclusions And Relevance: There have been substantial declines in premature CVD mortality in much of the US population. However, increases in CVD mortality before age 50 years among American Indian/Alaska Native individuals, flattening rates in white people, and overall increases in deaths from hypertensive disease suggest that targeted public health interventions are needed to prevent these premature deaths.
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http://dx.doi.org/10.1001/jamacardio.2019.3891DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6802055PMC
December 2019

Associations between estimated foetal weight discordance and clinical characteristics within dichorionic twins: The NICHD Fetal Growth Studies.

Paediatr Perinat Epidemiol 2019 09 3;33(5):332-342. Epub 2019 Sep 3.

Division of Intramural Population Health Research, Eunice Kennedy Shriver National Institute of Child Health and Human Development, National Institutes of Health, Bethesda, Maryland.

Background: Birthweight discordance is well studied, with less known about longitudinal inter-twin differences in foetal growth.

Objective: To examine inter-twin per cent differences in EFW (EFW ), head (HC ) and abdominal circumference (AC ), and femur length (FL ) across gestation in dichorionic twin gestations and explore associated characteristics.

Methods: Foetal biometrics were assessed by ultrasound and EFW calculated at ≤6 study visits among women with dichorionic twin pregnancies enrolled in the NICHD Fetal Growth Studies cohort (US, 2012-2013). Inter-twin per cent difference was defined: ([Size  - Size ]/Size  × 100). Linear mixed models evaluated per cent differences in foetal biometrics at 15 weeks and their change per week overall and by maternal/neonatal characteristics in unadjusted and adjusted models.

Results: In 140 pregnancies, inter-twin per cent differences increased across gestation for EFW (0.18%/week, 95% confidence interval [CI] 0.10, 0.27), HC (0.03%/week, 95% CI 0.00, 0.06), and AC (0.03%/week, 95%CI -0.01, 0.08) but decreased for FL (-0.03%/week, 95% CI -0.09, 0.02). After adjustment, change in EFW difference across gestation differed by pre-pregnancy body mass index (BMI [kg/m ]; underweight [<18.5]; normal weight [18.5-24.9]; overweight [25.0-29.9]; obese [≥30.0]; P  = .022); and conception method (in vitro fertilisation [IVF], intrauterine insemination, ovulation induction medication, donor egg/embryo, none; P  = .060). While EFW difference increased with normal pre-pregnancy BMI (0.24%/week, 95% CI 0.12, 0.37), little change was noted with pre-pregnancy obesity (0.01%/week, 95% CI -0.15, 0.17). EFW difference increased in conceptions without fertility treatments (0.23%/week, 95% CI 0.11, 0.34) but not IVF conceptions (-0.00%/week, 95% CI -0.16, 0.16). Similar patterns of differences across gestation were noted for HC by conception method (P  = .026) and AC by pre-pregnancy BMI (P  = .071); changes in HC differed by parity (nulliparous, multiparous; P  = .004).

Conclusions: EFW difference increased across gestation in dichorionic twins, but remained stable with pre-pregnancy obesity or IVF conception, patterns mirrored for HC and AC. Research is needed to understand pathologic versus physiologic differential twin growth trajectories.
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http://dx.doi.org/10.1111/ppe.12570DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7593826PMC
September 2019

Intrauterine growth discordance across gestation and birthweight discordance in dichorionic twins.

Am J Obstet Gynecol 2020 02 24;222(2):174.e1-174.e10. Epub 2019 Aug 24.

Division of Intramural Population Health Research, Eunice Kennedy Shriver National Institute of Child Health and Human Development, Bethesda, MD. Electronic address:

Background: Although intertwin size difference is an important measure of fetal growth, the appropriate cut point to define discordance is unclear. Few studies have assessed intertwin differences in estimated fetal weight longitudinally or in relation to size differences at birth.

Objectives: The objectives of the study were to estimate the magnitude of percentage differences in estimated fetal weight across gestation in dichorionic twins in relation to a fixed discordance cut point and compare classification of aberrant fetal growth by different measures (estimated fetal weight differences, birthweight discordance, small for gestational age).

Study Design: Women aged 18-45 years from 8 US centers with dichorionic twin pregnancies at 8 weeks 0 days to 13 weeks 6 days gestation planning to deliver in participating hospitals were recruited into the Eunice Kennedy Shriver National Institute of Child Health and Human Development Fetal Growth Studies-Dichorionic Twins study and followed through delivery (n = 140; 2012-2013). Ultrasounds were conducted at 6 targeted study visits to obtain fetal biometrics and calculate estimated fetal weight. Percent estimated fetal weight and birthweight differences were calculated: ([weight - weight]/weight)*100; discordance was defined as ≥18% for illustration. Birth sizes for gestational age (both, 1, or neither small for gestational age) were determined; twins were categorized into combined birthweight plus small for gestational age groups: birthweight discordance ≥18% (yes, no) with both, 1, or neither small for gestational age. Linear mixed-models estimated percentiles of estimated fetal weight percent differences across gestation and compared estimated fetal weight differences between combined birthweight discordance and small for gestational age groups. A Fisher exact test compared birthweight discordance and small for gestational age classifications.

Results: Median estimated fetal weight percentage difference increased across gestation (5.9% at 15.0, 8.4% at 38.0 weeks), with greater disparities at higher percentiles (eg, 90th percentile: 15.6% at 15.0, 26.3% at 38.0 weeks). As gestation advanced, an increasing percentage of pregnancies were classified as discordant using a fixed cut point: 10% at 27.0, 15% at 34.0, and 20% at 38.0 weeks. Birthweight discordance and small for gestational age classifications differed (P = .002); for birthweight discordance ≥18% vs <18%: 44% vs 71% had neither small for gestational age; 56% vs 18% had 1 small for gestational age; no cases (0%) vs 11% had both small for gestational age, respectively. Estimated fetal weight percent difference varied across gestation by birthweight discordance plus small for gestational age classification (P = .040). Estimated fetal weight percentage difference increased with birthweight discordance ≥18% (neither small for gestational age: 0.46%/week [95% confidence interval, 0.08-0.84]; 1 small for gestational age: 0.57%/week [95% confidence interval, 0.25-0.90]) but less so without birthweight discordance (neither small for gestational age: 0.17%/week [95% confidence interval, 0.06-0.28]; 1 small for gestational age: 0.03%/week [95% confidence interval, -0.17 to 0.24]); both small for gestational age: 0.10%/week [95% confidence interval, -0.15 to 0.36]).

Conclusion: The percentage of dichorionic pregnancies exceeding a fixed discordance cut point increased over gestation. A fixed cut point for defining twin discordance would identify an increasing percentage of twins as discordant as gestation advances. Small for gestational age and percentage weight differences assess distinct aspects of dichorionic twin growth. A percentile cut point may be more clinically useful for defining discordance, although further study is required to assess whether any specific percentile cut point correlates to adverse outcomes.
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http://dx.doi.org/10.1016/j.ajog.2019.08.027DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7535857PMC
February 2020

Validity of retrospective occupational exposure estimates of lead and manganese in a case-control study.

Occup Environ Med 2019 09 15;76(9):680-687. Epub 2019 Jul 15.

Occupational and Environmental Epidemiology Branch, Division of Cancer Epidemiology and Genetics, National Cancer Institute, Rockville, Maryland, USA.

Objectives: The validity of surrogate measures of retrospective occupational exposure in population-based epidemiological studies has rarely been evaluated. Using toenail samples as bioindicators of exposure, we assessed whether work tasks and expert assessments of occupational metal exposure obtained from personal interviews were associated with lead and manganese concentrations.

Methods: We selected 609 controls from a case-control study of bladder cancer in New England who had held a job for ≥1 year 8-24 months prior to toenail collection. We evaluated associations between toenail metal concentrations and five tasks extracted from occupational questionnaires (grinding, painting, soldering, welding, working near engines) using linear regression models. For 139 subjects, we also evaluated associations between the toenail concentrations and exposure estimates from three experts.

Results: We observed a 1.9-fold increase (95% CI 1.4 to 2.5) in toenail lead concentrations with painting and 1.4-fold increase (95% CI 1.1 to 1.7) in manganese concentrations with working around engines and handling fuel. We observed significant trends with increasing frequency of both activities. For lead, significant trends were observed with the ratings from all three experts. Their average ratings showed the strongest association, with subjects rated as possibly or probably exposed to lead having concentrations that were 2.0 and 2.5 times higher, respectively, than in unexposed subjects (p <0.001). Expert estimates were only weakly associated with manganese toenail concentrations.

Conclusions: Our findings support the ability of experts to identify broad contrasts in previous occupational exposure to lead. The stronger associations with task frequency and expert assessments support using refined exposure characterisation whenever possible.
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http://dx.doi.org/10.1136/oemed-2019-105744DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6767614PMC
September 2019

Fetal growth patterns in pregnancy-associated hypertensive disorders: NICHD Fetal Growth Studies.

Am J Obstet Gynecol 2019 12 19;221(6):635.e1-635.e16. Epub 2019 Jun 19.

Division of Intramural Population Health Research, Eunice Kennedy Shriver National Institute of Child Health and Human Development, National Institutes of Health, Bethesda, MD.

Background: Fetal growth patterns in pregnancy-associated hypertensive disorders is poorly understood because prospective longitudinal data are lacking.

Objective: The objective of the study was to compare longitudinal fetal growth trajectories between normotensive women and those with pregnancy-associated hypertensive disorders.

Study Design: This is a study based on data from a prospective longitudinal cohort study of fetal growth performed at 12 US sites (2009-2013). Project gestational age was confirmed by ultrasound between 8 weeks 0 days and 13 weels 6 days, and up to 6 ultrasounds were performed across gestation. Hypertensive disorders were diagnosed based on 2002 American College of Obstetricians and Gynecologists guidelines and grouped hierarchically as severe preeclampsia (including eclampsia or HELLP [hemolysis, elevated liver enzymes, and low platelet count] syndrome), mild preeclampsia, severe gestational hypertension, mild gestational hypertension, or unspecified hypertension. Women without any hypertensive disorder constituted the normotensive group. Growth curves for estimated fetal weight and individual biometric parameters including biparietal diameter, head circumference, abdominal circumference, and femur and humerus length were calculated for each group using linear mixed models with cubic splines. Global and weekly pairwise comparisons were performed between women with a hypertensive disorder compared with normotensive women to analyze differences while adjusting for confounding variables. Delivery gestational age and birthweights were compared among groups.

Results: Of 2462 women analyzed, 2296 (93.3%) were normotensive, 63 (2.6%) had mild gestational hypertension, 54 (2.2%) mild preeclampsia, 32 (1.3%) severe preeclampsia, and 17 (0.7%) unspecified hypertension. Compared with normotensive women, those with severe preeclampsia had estimated fetal weights that were reduced between 22 and 38 weeks (all weekly pairwise values of P < .008). Women with severe preeclampsia compared with those without hypertension also had significantly smaller fetal abdominal circumference between 23-31 and 33-37 weeks' gestation (weekly pairwise values of P < .04). Scattered weekly growth differences were noted on other biometric parameters between these 2 groups. The consistent differences in estimated fetal weight and abdominal circumference were not observed between women with other hypertensive disorders and those who were normotensive. Women with severe preeclampsia delivered significantly earlier (mean gestational age 35.9 ± 3.2 weeks) than the other groups (global P < .0001). Birthweights in the severe preeclampsia group were also significantly lower (mean -949.5 g [95% confidence interval, -1117.7 to -781.2 g]; P < .0001) than in the normotensive group.

Conclusion: Among women with pregnancy-associated hypertensive disorders, only those destined to develop severe preeclampsia demonstrated a significant and consistent difference in fetal growth (ie, smaller estimated fetal weight and abdominal circumference) when compared with normotensive women.
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http://dx.doi.org/10.1016/j.ajog.2019.06.028DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6888945PMC
December 2019

Maternal Serum Lipid Trajectories and Association with Pregnancy Loss and Length of Gestation.

Am J Perinatol 2020 07 2;37(9):914-923. Epub 2019 Jun 2.

Biostatistics and Bioinformatics Branch, Division of Intramural Population Health Research, Eunice Kennedy Shriver National Institute of Child Health and Human Development, National Institutes of Health, Bethesda, Maryland.

Objective: We characterized lipid trajectories and investigated lipids and rate of pregnancy lipid change with the risk of pregnancy loss or preterm delivery <37 weeks.

Study Design: In a secondary analysis of 337 women with one to two prior losses assigned to placebo in a randomized controlled trial at four centers (2007-2012), cholesterol, low- and high-density lipoprotein cholesterol (HDL-C), and triglycerides were measured up to 6 months prepregnancy (time 0) and pregnancy up to 7 visits. Trajectories were created using linear mixed models. Multivariable logistic regression with adjustment for maternal characteristics and cholesterol was performed.

Results: Lipids decreased from prepregnancy to 4 to 5 weeks, followed by an increase, and were biphasic or triphasic depending on the lipid component. Between 4 and 8 weeks, for every 1-unit increase in HDL-C, there was a 22% decreased odds of loss <14 weeks (odds ratio: 0.78; 95% confidence interval: 0.60, 0.99) and 24% decreased odds of loss or preterm delivery 14 to <37 weeks (odds ratio: 0.76; 95% confidence interval: 0.60, 0.96).

Conclusion: There were no associations with other lipid components or other time points. An impaired rise of HDL-C early in pregnancy may signal maladaptation to pregnancy that is associated with pregnancy loss or preterm delivery.
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http://dx.doi.org/10.1055/s-0039-1689000DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7558414PMC
July 2020
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