Case-cohort Study Design Research Articles

Case-cohort design as an efficient approach to evaluating COVID-19 vaccine effectiveness, waning, heterologous immune effect and optimal dosing interval

Though widely applied in other epidemiological fields, the case-cohort study design has seen little application in the field of vaccinology. Case-cohort studies use probabilistic sampling and reweighting to draw inferences about effects (in this case vaccine efficacy) at the population level in an efficient manner. The SARS-CoV-2 pandemic was met with high vaccine uptake, and high rates of population testing prior to the emergence of Omicron variants of concern, in Ontario, Canada, providing an ideal environment for application of case-cohort methodology. We combined a population-based case line list and vaccination database for the province of Ontario between December 2020 and October 2021. Risk of infection after vaccination was evaluated in all laboratory-confirmed vaccinated SARS-CoV-2 cases, and a 2 % sample of vaccinated controls, evaluated using survival analytic methods, including construction of Cox proportional hazards models. Vaccination status was treated as a time-varying covariate. First and second doses of SARS-CoV-2 vaccine markedly reduced risk of infection (first dose efficacy 68 %, 95 % CI 67 %–69 %; second dose efficacy 88 %, 95 % CI 87–88 %). In multivariable models, extended dosing intervals were associated with lowest risk of breakthrough infection (HR for redosing 0.64 (95 % CI 0.61–0.67) at 6–8 weeks). Heterologous vaccine schedules that mixed viral vector vaccine first doses with mRNA second doses were significantly more effective than mRNA only vaccines. Risk of infection largely vanished during the time period 4–6 months after the second vaccine dose, but rose markedly thereafter. We conclude that a case-cohort design provided an efficient means to identify strong protective effects associated with SARS-CoV-2 vaccination in real time, and also served to quantify the timing and magnitude of infection breakthrough risk in the same cohort. Heterologous vaccination and extended dosing intervals improved the durability of immune response.

Efficient estimation for left-truncated competing risks regression for case-cohort studies.

The case-cohort study design provides a cost-effective study design for a large cohort study with competing risk outcomes. The proportional subdistribution hazards model is widely used to estimate direct covariate effects on the cumulative incidence function for competing risk data. In biomedical studies, left truncation often occurs and brings extra challenges to the analysis. Existing inverse probability weighting methods for case-cohort studies with competing risk data not only have not addressed left truncation, but also are inefficient in regression parameter estimation for fully observed covariates. We propose an augmented inverse probability-weighted estimating equationfor left-truncated competing risk data to address these limitations of the current literature. We further propose a more efficient estimator when extra information from the other causes is available. The proposed estimators are consistent and asymptotically normally distributed. Simulation studies show that the proposed estimator is unbiased and leads to estimation efficiency gain in the regression parameter estimation. We analyze the Atherosclerosis Risk in Communities study data using the proposed methods.

Abstract B065: Percent mammographic density and breast cancer risk among U.S. Black women

Abstract Background: High mammographic density is a well-established risk factor for breast cancer. A few studies have suggested a difference in mammographic density by race wherein Black women – who have a high risk of aggressive breast cancer subtypes – are more likely to have dense breasts compared to women of other racial/ethnic groups. It is unknown whether mammographic density may contribute to differences in breast cancer risk by tumor hormone subtype across race and ethnicity. Methods: We used a case-cohort study design to examine the association between percent mammographic density (PMD) and breast cancer risk among Black women in the United States using data from the Black Women’s Health Study (BWHS). Our study consisted of 5,904 women with digital screening (i.e., pre-diagnostic) mammograms of which 363 (6.15%) were women with breast cancer (cases) and 5,541 (93.85%) were women without breast cancer (non-cases). We used Cumulus to assess PMD. Quartiles for PMD were determined based on the distribution in the non-cases. We used logistic regression, adjusted for age and body mass index (BMI) at mammography, to estimate relative risks (RRs) and 95% confidence intervals (CIs) for the association of PMD with breast cancer overall and by estrogen receptor (ER) status. Fully adjusted models additionally included other established breast cancer risk factors. We also stratified analyses by age at mammography (<55 vs. ≥ 55 years). Results: The mean age at mammography was 56 years for both cases and non-cases and approximately 70% of participants were postmenopausal. Cases had a lower mean BMI at age 18 years (20.9 kg/m2) compared to non-cases (21.4 kg/m2), while there was no difference in mean BMI at mammography between cases and non-cases. As expected, cases were more likely than non-cases to have a family history of breast cancer (25% vs. 19%). Additionally, cases had a higher mean PMD than did non-cases (26.3% vs. 24.5%). Overall, women in the highest quartile of PMD had a 58% higher risk of breast cancer compared to those in the lowest quartile (RRQ4vsQ1 1.58; 95% CI: 1.14, 2.18). Corresponding RRs were 1.46 (95% CI: 0.99, 2.14) for ER+ cancer and 1.57 (95% CI: 0.79, 3.14) for ER– cancer. Among women under 55 years of age, the RR for the highest quartile of PMD relative to the lowest quartile was 1.35, 95% CI: 0.83, 2.19). Among the older women, the comparable RR was 1.75, 95% CI: 1.13, 2.69). Associations were largely unchanged in multivariable models. Conclusion: In the largest study of mammographic density in U.S. Black women to date, we confirmed that higher PMD is associated with both ER+ and ER– breast cancer risk in this population. Associations were statistically significant among women ≥55 years of age. Findings from this study reinforce the importance of breast density as a risk factor for breast cancer across racial/ethnic groups. Citation Format: Etienne X. Holder, Zahna Bigham, Kerrie P. Nelson, Julie R. Palmer, Kimberly A. Bertrand. Percent mammographic density and breast cancer risk among U.S. Black women [abstract]. In: Proceedings of the 16th AACR Conference on the Science of Cancer Health Disparities in Racial/Ethnic Minorities and the Medically Underserved; 2023 Sep 29-Oct 2;Orlando, FL. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2023;32(12 Suppl):Abstract nr B065.

Abstract 5241: Association of polygenic risk scores with breast cancer risk among women with benign breast disease

Abstract Over one million biopsies are performed annually in the U.S. to evaluate suspicious breast lesions. Most biopsies lead to a diagnosis of benign breast disease (BBD) and these women have a 1.5- to fourfold increase in subsequent breast cancer (BC) risk compared with the general population. A polygenic risk score (PRS) including 313 common variants was developed to predict BC risk in the general population and has improved performance when added to existing BC prediction models. However, the value of PRS in risk prediction models among women with BBD has not been evaluated. To evaluate the role of the established PRS, BBD, and BC risk, we pooled data from 15,194 white women (6,706 BC cases and 8,488 controls) participating in five Breast Cancer Association Consortium case-control studies. BC risk associations were evaluated by self-reported BBD history and combinations of PRS expressed in tertiles using odds ratios (OR), considering the lowest category of PRS among women without BBD as the referent. Associations were also assessed in an independent case-cohort study (831 BC cases and 1,845 controls) using hazard ratios (HR). Among the case-control studies, the PRS was strongly associated with BC risk (OR=2.50 per standard deviation increase), and associations were similar in women with (OR=2.60) and without a history of BBD (OR=2.44, p-interaction=0.23). Women with BBD have a higher risk of BC than those without BBD within each level of PRS. Compared to women without BBD and in the lowest PRS category, those with BBD and PRS in the highest tertile had 5-fold increased odds of BC (OR = 5.38; 95% CI 4.73-6.13). Associations were similar in an independent case-cohort study. These findings indicate that BBD history and PRS are independent contributors to BC risk, and consideration of both simultaneously could improve breast cancer risk prediction. Future studies are needed to integrate PRS with other risk measures to refine absolute BC risk prediction among BBD patients. Associations of BC risk with combinations of PRS (tertiles) and history of BBD in five case-control studies and a case-cohort study from the Breast Cancer Association Consortium. Case-control studies Case-cohort study PRS score range History of BBD n BC cases n controls OR (95% CI)1 n BC cases n controls HR (95% CI)2 Tertile 1 (≤ -0.57) No 1009 2692 1.00 (Ref) 117 584 1.00 (Ref) Yes 508 902 1.54 (1.35-1.76) 69 163 2.05 (1.45-2.89) Tertile 2 (-0.58, -0.03) No 1469 2001 1.97 (1.78-2.17) 181 475 1.93 (1.48-2.51) Yes 760 798 2.65 (2.34-3.01) 108 170 2.99 (2.18-4.09) Tertile 3 (≥ -0.02) No 1910 1551 3.32 (3.01-3.67) 214 336 3.28 (2.52-4.26) Yes 1050 544 5.38 (4.73-6.13) 142 117 4.83 4.25-8.02) 1.Logistic regression analysis, adjusted for study site/genomic platform and age at enrollment. OR, odds ratio; CI, confidence interval.2.Cox proportional hazards regression analysis, accounting for the case-cohort study design and adjusted for age at enrollment. HR, hazard ratio; CI, confidence interval. Citation Format: Stacey J. Winham, Mark Sherman, Robert Vierkant, Bryan McCauley, Christopher Scott, Mia Gaudet, Melissa Troester, Sandhya Pruthi, Derek Radisky, Amy Degnim, Kristan Aronson, Rachel Murphy, Pascal Guenel, Therese Truong, Jenny Chang-Claude, Heiko Becher, Montserrat Garcia-Closas, Stephen Chanock, Thomas Ahearn, Xiaohong Yang, Doug Easton, Manjeet Bolla, Celine Vachon, Breast Cancer Association Consortium. Association of polygenic risk scores with breast cancer risk among women with benign breast disease. [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 5241.

Lipolysis and gestational diabetes mellitus onset: a case-cohort genome-wide association study in Chinese

BackgroundGenetic knowledge of gestational diabetes mellitus (GDM) in Chinese women is quite limited. This study aimed to identify the risk factors and mechanism of GDM at the genetic level in a Chinese population.MethodsWe conducted a genome-wide association study (GWAS) based on single nucleotide polymorphism (SNP) array genotyping (ASA-CHIA Bead chip, Illumina) and a case-cohort study design. Variants including SNPs, copy number variants (CNVs), and insertions-deletions (InDels) were called from genotyping data. A total of 2232 pregnant women were enrolled in their first/second trimester between February 2018 and December 2020 from Anqing Municipal Hospital in Anhui Province, China. The GWAS included 193 GDM patients and 819 subjects without a diabetes diagnosis, and risk ratios (RRs) and their 95% confidence intervals (CIs) were estimated by a regression-based method conditional on the population structure. The calling and quality control of genotyping data were performed following published guidelines. CNVs were merged into CNV regions (CNVR) to simplify analyses. To interpret the GWAS results, gene mapping and overexpression analyses (ORAs) were further performed to prioritize the candidate genes and related biological mechanisms.ResultsWe identified 14 CNVRs (false discovery rate corrected P values < 0.05) and two suggestively significant SNPs (P value < 0.00001) associated with GDM, and a total of 19 candidate genes were mapped. Ten genes were significantly enriched in gene sets related to lipase (triglyceride lipase and lipoprotein lipase) activity (LIPF, LIPK, LIPN, and LIPJ genes), oxidoreductase activity (TPH1 and TPH2 genes), and cellular components beta-catenin destruction complex (APC and GSK3B genes), Wnt signalosome (APC and GSK3B genes), and lateral element in the Gene Ontology resource (BRCA1 and SYCP2 genes) by two ORA methods (adjusted P values < 0.05).ConclusionsGenes related to lipolysis, redox reaction, and proliferation of islet β-cells are associated with GDM in Chinese women. Energy metabolism, particularly lipolysis, may play an important role in GDM aetiology and pathology, which needs further molecular studies to verify.

Additive subdistribution hazards regression for competing risks data in case-cohort studies.

In survival data analysis, a competing risk is an event whose occurrence precludes or alters the chance of the occurrence of the primary event of interest. In large cohort studies with long-term follow-up, there are often competing risks. Further, if the event of interest is rare in such large studies, the case-cohort study design is widely used to reduce the cost and achieve the same efficiency as a cohort study. The conventional additive hazards modeling for competing risks data in case-cohort studies involves the cause-specific hazard function, under which direct assessment of covariate effects on the cumulative incidence function, or the subdistribution, is not possible. In this paper, we consider an additive hazard model for the subdistribution of a competing risk in case-cohort studies. We propose estimating equationsbased on inverse probability weighting methods for the estimation of the model parameters. Consistency and asymptotic normality of the proposed estimators are established. The performance of the proposed methods in finite samples is examined through simulation studies and the proposed approach is applied to a case-cohort dataset from the SisterStudy.

How many crashes does cellphone use contribute to? Population attributable risk of cellphone use while driving

Background: Cellphone distraction is a major contributing factor for traffic crashes, a leading cause of death worldwide. The novel naturalistic driving study (NDS) study with continuously collected in situ driving videos provides an opportunity to accurately estimate the safety impact of cellphone distraction. Methods: We apply a case-cohort study design to the Second Strategic Highway Research Program NDS, the largest NDS up-to-date with more than 3400 participants. The data include with 842 level 1–3 crashes and 19,338 randomly selected control driving segments. We propose a partial Population Attributable Risk (PAR) estimator that provides consistent and stable estimation over time and across different driving behaviors. Results: The US population-adjusted PAR show that 8% of crashes (PAR = 0.08, 95 %CI: [0.06, 0.19]) can be reduced if cellphone distraction were switched to sober, alert, and attentive driving behavior. Young adults (age 20–29 years) and middle-aged drivers (age 30–64 years) each contribute 39% of the population level PAR. Within each age group, the PARs vary substantially from 18% for young adult drivers to 5% for middle-aged drivers. The contribution of cellphone visual-manual tasks to crashes is more than 4 times larger than cellphone talking and accounts for 87.5% of cellphone-related crashes (PAR = 0.07). Conclusions: Cellphone distraction contributes to a considerable part of crashes. Young drivers are more susceptible to the influence of cellphone distraction and visual-manual distraction accounts for the majority of cellphone-related crashes.

Statistical methods for relative risk estimation and applications in case-cohort study

Objective: To systematically introduce the design of case-cohort study and the statistical methods of relative risk estimation and their application in the design. Methods: First, we introduced the basic principles of case-cohort study design. Secondly, Prentice's method, Self-Prentice method and Barlow method were described in the weighted Cox proportional hazard regression models in detail, finally, the data from the Shanghai Women's Health Study were used as an example to analyze the association between obesity and liver cancer incidence in the full cohort and case-cohort sample, and the results of parameters from each method were compared. Results: Significant association was observed between obesity and risk for liver cancer incidence in women in both the full cohort and the case-cohort sample. In the Cox proportional hazard regression model, the partial regression coefficients of the full cohort and the case-cohort sample fluctuated with the adjustment of confounding factors, but the hazard ratio estimates of them were close. There was a difference in the standard error of the partial regression coefficient between the full cohort and the case-cohort sample. The standard error of the partial regression coefficient of the case-cohort sample was larger than that of the full cohort, resulting in a wider 95% confidence interval of the relative risk. In the weighted Cox proportional hazard regression model, the standard error of the partial regression coefficient of Prentice's method was closer to the parameter estimates from full cohort than Self-Prentice method and Barlow method, and the 95% confidence interval of hazard ratio was closer to that of the full cohort. Conclusions: Case-cohort design could yield parameter results closer to the full cohort by collecting and analyzing data from sub-cohort members and patients with the disease, and reduce sample size and improve research efficiency. The results suggested that Prentice's method would be preferred in case-cohort design.

Gestational Phthalate Exposure and Preschool Attention Deficit Hyperactivity Disorder in Norway.

Prenatal phthalate exposure has been linked to altered neurobehavioral development in both animal models and epidemiologic studies, but whether or not these associations translate to increased risk of neurodevelopmental disorders is unclear. We used a nested case-cohort study design to assess whether maternal urinary concentrations of 12 phthalate metabolites at 17 weeks gestation were associated with criteria for Attention Deficit Hyperactivity Disorder (ADHD) classified among 3-year-old children in the Norwegian Mother, Father and Child Cohort Study (MoBa). Between 2007 and 2011, 260 children in this substudy were classified with ADHD using a standardized, on-site clinical assessment; they were compared with 549 population-based controls. We modeled phthalate levels both linearly and by quintiles in logistic regression models adjusted for relevant covariates and tested for interaction by child sex. Children of mothers in the highest quintile of di-iso-nonyl phthalate (∑DiNP) metabolite levels had 1.70 times the odds of being classified with ADHD compared with those in the lowest quintile (95% confidence interval [CI] = 1.03 to 2.82). In linear models, there was a trend with the sum of di-2-ethylhexyl phthalate metabolites (∑DEHP); each natural log-unit increase in concentration was associated with 1.22 times the odds of ADHD (95% CI = 0.99 to 1.52). In boys, but not girls, mono-n-butyl phthalate exposure was associated with increased odds of ADHD (odds ratio [OR] 1.42; 95% CI = 1.07 to 1.88). Additional adjustment for correlated phthalate metabolites attenuated estimates. These results suggest gestational phthalate exposure may impact the behavior of children as young as 3 years.

Literature Review: The relationship of the physical quality of the environment in the dwelling to the incidence of Acute Respiratory Infection (ARI)

Background: Acute Respiratory Infection (ARI) is a disease transmitted by viruses. This health problem persists from year to year, starting from developing countries to developed countries there are still morbidity and mortality rates due to ARI. One of the factors that can affect human health is environmental factors which include occupancy density, ventilation area, natural lighting, humidity, temperature, conditions and types of walls, and floors.Purpose: This literature study aims to analyze the relationship between the physical quality of the occupancy and the occurrence of acute respiratory infections (ARI).Reviews: The results of the journal search were found as many as 17 journals that met the inclusion criteria set by the researcher. Most of the research found used a cross sectional study design, but some studies also used case control and cohort study designs. Several different results were found for each study, but still showed similarities, namely the incidence of ARI in each study.Conclusion: The journal review that has been conducted can conclude that there is a relationship between the area of ventilation, humidity, temperature, natural lighting, occupancy density, conditions and types of walls, as well as conditions and types of floors. There are differences from each of the research results, but there are still similarities which state that there is a relationship between the physical quality of the environment at home and the incidence of ARI.

Brominated flame retardants and organochlorine pesticides and incidence of uterine leiomyomata: A prospective ultrasound study.

The Study of Environmental, Lifestyle, and Fibroids is a Detroit-area prospective cohort of 1693 Black women 23-35 years of age. At baseline and approximately every 20 months for 5 years, women completed questionnaires and underwent transvaginal ultrasounds. Using a case-cohort study design, we selected 729 UL-free participants at baseline and analyzed baseline plasma samples for polybrominated diphenyl ethers (PBDEs), a polybrominated biphenyl ether (PBB-153), and OCPs. We used Cox proportional hazard models to estimate hazard ratios (HRs) and 95% confidence intervals (CIs). Compared with total PBDE plasma concentrations <50th percentile, adjusted HRs for the 50th-74th, 75th-89th, and ≥90th percentiles were 1.00 (95% CI = 0.68, 1.47), 1.04 (95% CI = 0.63, 1.68), and 0.85 (95% CI = 0.48, 1.50), respectively. HRs for PBB-153 plasma concentrations were generally similar to total PBDE plasma concentrations. Compared with total OCP plasma concentrations <50th percentile, HRs for the 50th-74th, 75th-89th, and ≥90th percentiles were 0.86 (95% CI = 0.57, 1.29), 0.73 (95% CI = 0.43, 1.22), and 0.58 (95% CI = 0.32, 1.04), respectively. HRs for individual PBDEs and OCPs were similar to their respective totals. We found little support for an association between brominated flame retardant plasma concentrations and UL incidence, and some evidence of lower UL incidence with the highest OCP plasma concentrations.

A Prospective Ultrasound Study of Plasma Polychlorinated Biphenyl Concentrations and Incidence of Uterine Leiomyomata.

Uterine leiomyomata, or fibroids, are hormone-dependent neoplasms of the myometrium that can cause severe gynecologic morbidity. In previous studies, incidence of these lesions has been positively associated with exposure to polychlorinated biphenyls (PCBs), a class of persistent endocrine-disrupting chemicals. However, previous studies have been retrospective in design and none has used ultrasound to reduce disease misclassification. The Study of Environment, Lifestyle, and Fibroids is a prospective cohort of 1,693 reproductive-aged Black women residing in Detroit, Michigan (enrolled during 2010-2012). At baseline and every 20 months for 5 years, women completed questionnaires, provided blood samples, and underwent transvaginal ultrasound to detect incident fibroids. We analyzed 754 baseline plasma samples for concentrations of 24 PCB congeners using a case-cohort study design. We used multivariable Cox proportional hazards regression to estimate hazard ratios (HRs) and 95% confidence intervals for the association between plasma PCB concentrations and ultrasound-detected fibroid incidence over a 5-year period. We observed little association between PCB congener concentrations and fibroid incidence. The HR for a one-standard deviation increase in log-transformed total PCBs was 0.94 (95% CI = 0.78, 1.1). The PCB congener with the largest effect estimate was PCB 187 (HR for a one-standard deviation increase in log-transformed exposure = 0.88, 95% CI = 0.73, 1.1). Associations did not seem to vary strongly across PCB groupings based on hormonal activity. In this cohort of reproductive-aged Black women, plasma PCB concentrations typical of the contemporary general population were not appreciably associated with higher risk of fibroids.

Proportional Subdistribution Hazards Model for Competing Risks in Case-Cohort Studies

Competing risks refer to the situation where there are multiple causes of failure and the occurrence of one type of event prohibits the occurrence of the other types of event or alters the chance to observe them. In large cohort studies with long-term follow-up, there are often competing risks. When the failure events are rare, or the information on certain risk factors is difficult or costly to measure for the full cohort, a case-cohort study design can be a desirable approach. In this paper, we consider a semiparametric proportional subdistribution hazards model in the presence of competing risks in case-cohort studies. The subdistribution hazards function, unlike the cause-specific hazards function, gives the advantage of outlining the marginal probability of a particular type of event. We propose estimating equations based on inverse probability weighting techniques for the estimation of the model parameters. In the estimation methods, we considered a weighted availability indicator to properly account for the case-cohort sampling scheme. We also proposed a Breslow-type estimator for the cumulative baseline subdistribution hazard function. The resulting estimators are shown, using empirical processes and martingale properties, to be consistent and asymptotically normally distributed. The performance of the proposed methods in finite samples are examined through simulation studies by considering different levels of censoring and event of interest percentages. The simulation results from the different scenarios suggest that the parameter estimates are reasonably close to the true values of the respective parameters in the model. Finally, the proposed estimation methods are applied to a case-cohort sample from the Sister Study, in which we illustrated the proposed methods by studying the association between selected CpGs and invasive breast cancer in the presence of ductal carcinoma in situ as competing risk.

Change in Cardiac Biomarkers and Risk of Incident Heart Failure and Atrial Fibrillation in CKD: The Chronic Renal Insufficiency Cohort (CRIC) Study

Circulating cardiac biomarkers may signal potential mechanistic pathways involved in heart failure (HF) and atrial fibrillation (AF). Single measures of circulating cardiac biomarkers are strongly associated with incident HF and AF in chronic kidney disease (CKD). We tested the associations of longitudinal changes in the N-terminal fragment of the prohormone brain natriuretic peptide (NT-proBNP), high-sensitivity troponin T (hsTnT), galectin-3, growth differentiation factor 15 (GDF-15), and soluble ST-2 (sST-2) with incident HF and AF in patients with CKD. Observational, case-cohort study design. Adults with CKD enrolled in the Chronic Renal Insufficiency Cohort study. Biomarkers were measured at baseline and 2 years later among those without kidney failure. We created 3 categories of absolute change in each biomarker: the lowest quartile, the middle 2 quartiles, and the top quartile. The primary outcomes were incident HF and AF. Cox proportional hazards regression models were used to test the associations of the change categories of each cardiac biomarker with each outcome (with the middle 2 quartiles of change as the referent group), adjusting for potential confounders and baseline concentrations of each biomarker. The incident HF analysis included 789 participants (which included 138 incident HF cases), and the incident AF analysis included 774 participants (123 incident AF cases). In multivariable models, the top quartile of NT-proBNP change (>232pg/mL over 2years) was associated with increased risk of incident HF (HR, 1.79 [95% CI, 1.06-3.04]) and AF (HR, 2.32 [95% CI, 1.37-3.93]) compared with the referent group. Participants in the top quartile of sST2 change (>3.37ng/mL over 2years) had significantly greater risk of incident HF (HR, 1.89 [95% CI, 1.13-3.16]), whereas those in the bottom quartile (≤-3.78ng/mL over 2years) had greater risk of incident AF (HR, 2.43 [95% CI, 1.39-4.22]) compared with the 2 middle quartiles. There was no association of changes in hsTnT, galectin-3, or GDF-15 with incident HF or AF. Observational study. In CKD, increases in NT-proBNPwere significantly associated with greater risk of incident HF and AF, and increases in sST2 were associated with HF. Further studies should investigate whether these markers of subclinical cardiovascular disease can be modified to reduce the risk of cardiovascular disease in CKD.

Brand-specific rates of pertussis disease among Wisconsin children given 1–4 doses of pertussis Vaccine, 2010–2014

BackgroundAcellular pertussis vaccines were initially licensed based on placebo-controlled efficacy trials, but such trials are no longer ethical. The effectiveness of current pertussis vaccines among properly vaccinated children <5 years is so high that a randomized trial is infeasible. Fluctuations in pertussis incidence and characteristics of the US vaccine marketplace make selection of suitable controls for a case-control study problematic. To satisfy an FDA requirement to evaluate rates of pertussis following licensure of Pentacel® vaccine, we used a case-cohort study design with a novel method for characterizing the cohort population. MethodsThis prospective, observational study was conducted in Wisconsin from 2010 to 2014 among Wisconsin residents <60 months of age who received ≤four doses of pertussis vaccine (surveillance population). Cases were identified by the Wisconsin Division of Public Health. Characteristics and pertussis vaccinations of the surveillance population were estimated by ongoing random telephonic survey. The primary objective was to determine rates of pertussis disease among those who received only Pentacel vaccine (Group 1) vs those who received a single brand of vaccine other than Pentacel vaccine (Group 2). Results1195 pertussis cases were identified. It was estimated that the surveillance population accrued a total of 1,133,403 person-years (Group 1, 39%; Group 2, 41%; Group 3 [those not in Group 1 or Group 2], 20%). Pertussis rates were similar in Group 1 (98.9/100,000) and Group 2 (96.2/100,000); rate ratios were 1.03 (unadjusted; 90% CI, 0.92–1.15) and 0.99 (adjusted; 90% CI, 0.89–1.12). Persons with one or more delayed vaccinations had a 66% higher risk of pertussis (90% CI, 39–96%). DiscussionPertussis protection was not found to differ for recipients of the newly licensed vs other available pertussis vaccines. Delayed vaccination substantially increased risk of pertussis. Sample survey methodology was able to characterize the study cohort and enable an otherwise-infeasible study.Clinical Trial Registry number: ClinicalTrials.gov, NCT01129362.

Vitamin D Metabolic Ratio and Risks of Death and CKD Progression

IntroductionAssessment of impaired vitamin D metabolism is limited by lack of functional measures. CYP24A1-mediated vitamin D clearance, calculated as the ratio of serum 24,25-dihydroxyvitamin D3 to 25-hydroxyvitamin D3 (the vitamin D metabolic ratio, VDMR), is induced by 1,25-dihydroxyvitamin D and may assess tissue-level activity. We tested associations of the VDMR with risks of death and progression to end-stage renal disease (ESRD) in patients with chronic kidney disease (CKD).MethodsWe studied participants from the Chronic Renal Insufficiency Cohort (CRIC), which included a random subset of 1080 CRIC participants plus additional participants who experienced ESRD or died (case cohort study design). Serum 24,25-dihydroxyvitamin D3 and 25-hydroxyvitamin D3 was measured 1 year after enrollment. The primary outcomes included death and progression to ESRD. Using inverse probability weighting, we tested associations of VDMR (24,25[OH]2D3/25[OH]D3) with risks of death and ESRD, adjusting for demographics, comorbidity, and kidney function (estimated glomerular filtration rate [eGFR] and urine protein-to-creatinine ratio [PCR]).ResultsThere were a total of 708 ESRD events and 650 deaths events over mean (SD) follow-up periods of 4.9 (2.9) years and 6.5 (2.5) years, respectively. Lower VDMR was associated with increased risk of ESRD prior to adjusting for kidney function (hazard ratio [HR], 1.80 per 20 pg/ng lower VDMR; 95% confidence interval [CI], 1.56–2.08), but not with adjustment for kidney function (HR, 0.94 per 20 pg/ng; 95% CI, 0.81–1.10). Lower VDMR was associated with modestly increased mortality risk, including adjustment for kidney function (HR, 1.18 per 20 pg/ng; 95% CI, 1.02–1.36).ConclusionLower VDMR, a measure of CYP24A1-mediated vitamin D clearance, was significantly associated with all-cause mortality but not with progression to ESRD in patients with CKD.

Statistical Methods for Naturalistic Driving Studies

The naturalistic driving study (NDS) is an innovative research method characterized by the continuous recording of driving information using advanced instrumentation under real-world driving conditions. NDSs provide opportunities to assess driving risks that are difficult to evaluate using traditional crash database or experimental methods. NDS findings have profound impacts on driving safety research, safety countermeasures development, and public policy. NDSs also come with attendant challenges to statistical analysis, however, due to the sheer volume of data collected, complex structure, and high cost associated with information extraction. This article reviews statistical and analytical methods for working with NDS data. Topics include the characteristics of NDSs; NDS data components; and epidemiological approaches for video-based risk modeling, including case-cohort and case-crossover study designs, logistic models, Poisson models, and recurrent event models. The article also discusses several key issues related to NDS analysis, such as crash surrogates and alternative reference exposure levels.

Early labor force exit subsequent to permanently impairing occupational injury or illness among workers 50-64 years of age.

Severity of workplace injury tends to increase with age. Whether older workers who experience a workplace injury or illness exit the labor force sooner than comparable peers is not established. A case-cohort study design and complementary log-log model were used to identify factors associated with average time to early substantial labor force exit among workers' compensation claimants 50-64 years of age with permanent impairment from an occupational injury or illness. Analysis was based on Ontario's workers' compensation claimant data from 1998 to 2006 linked with Canadian tax files. Workers with permanent impairment left the labor force earlier, on average, than peers without claims. Early retirement was associated with older age in the injury/illness year, greater impairment, lower pre-claim income, physically demanding jobs, and soft-tissue injuries. Policies aiming to extend older adults' working lives should account for the potentially disparate impacts on older workers of occupational injury and illness.

Regression analysis for secondary response variable in a case-cohort study.

Case-cohort study design has been widely used for its cost-effectiveness. In any real study, there are always other important outcomes of interest beside the failure time that the original case-cohort study is based on. How to utilize the available case-cohort data to study the relationship of a secondary outcome with the primary exposure obtained through the case-cohort study is not well studied. In this article, we propose a non-parametric estimated likelihood approach for analyzing a secondary outcome in a case-cohort study. The estimation is based on maximizing a semiparametric likelihood function that is built jointly on both time-to-failure outcome and the secondary outcome. The proposed estimator is shown to be consistent, efficient, and asymptotically normal. Finite sample performance is evaluated via simulation studies. Data from the Sister Study is analyzed to illustrate our method.

Neonatal vitamin D status from archived dried blood spots and future risk of fractures in childhood: results from the D-tect study, a population-based case-cohort study

Background: Whether antenatal and neonatal vitamin D status have clinical relevance in fracture prevention has not been examined extensively, although observational studies indicate that fetal life may be a sensitive period in relation to bone growth and mineralization during childhood.Objective: We examined whether 25-hydroxyvitamin D3 [25(OH)D3] concentrations in stored neonatal dried blood spot (DBS) samples are associated with pediatric fracture risk. We hypothesized that in particular, low neonatal vitamin D status may be a risk factor for fracture incidence among children.Design: In a register-based case-cohort study design, the case group was composed of 1039 individuals who were randomly selected from a total of 82,154 individuals who were born during 1989-1999 and admitted to a Danish hospital with a fracture of the forearm, wrist, scaphoid bone, clavicle, or ankle at age 6-13 y. The subcohort was composed of 1600 individuals randomly selected from all Danish children born during 1989-1999. The neonatal 25(OH)D3 concentrations in DBS samples were assessed by using highly sensitive chromatography-tandem mass spectrometry.Results: The mean ± SD 25(OH)D3 concentration for all subjects was 27.7 ± 18.9 nmol/L [median (IQR): 23.5 nmol/L (13.3, 37.3 nmol/L)] and showed significant monthly variation (P < 0.0001) with the highest values in July and August. Individuals in the middle quintile of neonatal 25(OH)D3 had lower odds of sustaining a fracture than did those in the lowest quintile (adjusted OR: 0.75; 95% CI: 0.58, 0.96), but a global test did not show any significant overall association (adjusted P = 0.13).Conclusions: This study suggested that neonatal vitamin D status does not influence subsequent fracture risk in childhood. This is in accordance with studies that report no association between antenatal maternal vitamin D status and childhood fractures. Further studies are needed to examine fracture risk in relation to prenatal vitamin D status in a randomized controlled setting.