Complete Covariate Information Research Articles

Compressed covariance sensing for blade tip timing measurement

Due to harsh working conditions, rotating blades are prone to failures. Thus, it is urgently needed to monitor blade health. Blade tip timing (BTT) is a promising non-contact vibration technique for rotating blades owing to its high efficiency and long service time. However, due to severe undersampling, traditional spectrum analysis methods are ineffective in identifying characteristic parameters and recovering the power spectrum of vibrations for condition monitoring. To address this issue, this paper proposes a compressed covariance sensing-based BTT (CCS-BTT) method for power spectrum estimation. Specifically, we build a compressed covariance sensing representation model for BTT signal, where the covariance representation can be non-underdetermined owing to the Hermitian Toeplitz structure of the covariance matrix. Then, a universal covariance sampling pattern (UCSP) is derived to ensure the complete covariance information can be efficiently recovered without sparsity constraint. By utilizing the inherent periodicity, the derived UCSP significantly improves the efficiency of BTT measurement. Moreover, for practicality, we present a series of optimized layouts based on UCSP that cover almost all possible cases of probe numbers in BTT measurement. Finally, extensive simulations and experiments validate the effectiveness and performance of CCS-BTT. By shifting the perspective from the signal itself to its covariance, CCS-BTT opens many avenues for the development of BTT signal processing. In addition, the proposed method is expected to be used in deterministic compressive sampling of wide-sense stationary signals.

O008 Refining the Hypoxic Burden Algorithm by Investigating different Methods for Calculating the SpO2 Baseline

Abstract Introduction Intermittent hypoxia is a key mechanism linking Obstructive Sleep Apnoea (OSA) to cardiovascular disease (CVD). Oximetry analysis could enhance understanding of which OSA phenotypes are associated with CVD risk. The hypoxic burden (HB) is a measure calculated from the oximetry signal that shows promise for predicting CVD mortality, but its calculation is complex. With a view to simplifying its calculation, we investigated three different baseline calculation methods and its impact on predicting CVD mortality for the HB algorithm. Methods Data from Sleep Heart Health Study (SHHS) with CVD mortality outcome and complete covariate information was used. We implemented the HB method of Azarbarzin et al 2018 ERJ. The three baseline methods included an event-based baseline (same as Azarbarzin et al 2018 ERJ), a record-based baseline, and a fixed baseline. The performance of each parameter in predicting CVD mortality was assessed using an adjusted Cox proportional hazard ratio (HR) analysis. Results The best performing method was the record-based baseline method which returned a fully adjusted model hazard ratio of 1.83 (95% CI: 1.03-3.27, p<0.05). The results for the event-based and record-based baseline methods were 1.60 (95% CI: 0.86-3.00, p=0.14) and 1.73 (95% CI: 0.93-3.22, p=0.08) respectively. Discussion HB with the record-based baseline was easier to calculate than the original event-based baseline method by Azarbarzin at al. and resulted in improved CVD mortality prediction performance. We believe that this method provides a step towards providing a novel parameter with easy calculation providing early risk stratification in cardiovascular patients.

Competing risks analysis for neutrophil to lymphocyte ratio as a predictor of diabetic retinopathy incidence in the Scottish population

BackgroundDiabetic retinopathy (DR) is a major sight-threatening microvascular complication in individuals with diabetes. Systemic inflammation combined with oxidative stress is thought to capture most of the complexities involved in the pathology of diabetic retinopathy. A high level of neutrophil–lymphocyte ratio (NLR) is an indicator of abnormal immune system activity. Current estimates of the association of NLR with diabetes and its complications are almost entirely derived from cross-sectional studies, suggesting that the nature of the reported association may be more diagnostic than prognostic. Therefore, in the present study, we examined the utility of NLR as a biomarker to predict the incidence of DR in the Scottish population.MethodsThe incidence of DR was defined as the time to the first diagnosis of R1 or above grade in the Scottish retinopathy grading scheme from type 2 diabetes diagnosis. The effect of NLR and its interactions were explored using a competing risks survival model adjusting for other risk factors and accounting for deaths. The Fine and Gray subdistribution hazard model (FGR) was used to predict the effect of NLR on the incidence of DR.ResultsWe analysed data from 23,531 individuals with complete covariate information. At 10 years, 8416 (35.8%) had developed DR and 2989 (12.7%) were lost to competing events (death) without developing DR and 12,126 individuals did not have DR. The median (interquartile range) level of NLR was 2.04 (1.5 to 2.7). The optimal NLR cut-off value to predict retinopathy incidence was 3.04. After accounting for competing risks at 10 years, the cumulative incidence of DR and deaths without DR were 50.7% and 21.9%, respectively. NLR was associated with incident DR in both Cause-specific hazard (CSH = 1.63; 95% CI: 1.28–2.07) and FGR models the subdistribution hazard (sHR = 2.24; 95% CI: 1.70–2.94). Both age and HbA1c were found to modulate the association between NLR and the risk of DR.ConclusionsThe current study suggests that NLR has a promising potential to predict DR incidence in the Scottish population, especially in individuals less than 65 years and in those with well-controlled glycaemic status.

A synthetic data integration framework to leverage external summary-level information from heterogeneous populations.

There is a growing need for flexible general frameworks that integrate individual-level data with external summary information for improved statistical inference. External information relevant for a risk prediction model may come in multiple forms, through regression coefficient estimates or predicted values of the outcome variable. Different external models may use different sets of predictors and the algorithm they used to predict the outcome Y given these predictors may or may not be known. The underlying populations corresponding to each external model may be different from each other and from the internal study population. Motivated by a prostate cancer risk prediction problem where novel biomarkers are measured only in the internal study, this paper proposes an imputation-based methodology, where the goal is to fit a target regression model with all available predictors in the internal study while utilizing summary information from external models that may have used only a subset of the predictors. The method allows for heterogeneity of covariate effects across the external populations. The proposed approach generates synthetic outcome data in each external population, uses stacked multiple imputation to create a long dataset with complete covariate information. The final analysis of the stacked imputed data is conducted by weighted regression. This flexible and unified approach can improve statistical efficiency of the estimated coefficients in the internal study, improve predictions by utilizing even partial information available from models that use a subset of the full set of covariates used in the internal study, and provide statistical inference for the external population with potentially different covariate effects from the internalpopulation.

Uncertainty-quantified phenomenological optical potentials for single-nucleon scattering

Optical-model potentials (OMPs) continue to play a key role in nuclear reaction calculations. However, the uncertainty of phenomenological OMPs in widespread use---inherent to any parametric model trained on data---has not been fully characterized, and its impact on downstream users of OMPs remains unclear. Here we assign well-calibrated uncertainties for two representative global OMPs, those of Koning-Delaroche and Chapel Hill '89, using Markov-chain Monte Carlo for parameter inference. By comparing the canonical versions of these OMPs against the experimental data originally used to constrain them, we show how a lack of outlier rejection and a systematic underestimation of experimental uncertainties contributes to bias of, and overconfidence in, best-fit parameter values. Our updated, uncertainty-quantified versions of these OMPs address these issues and yield complete covariance information for potential parameters. Scattering predictions generated from our ensembles show improved performance both against the original training corpora of experimental data and against a new ``test'' corpus comprising many of the experimental single-nucleon scattering data collected over the last twenty years. Finally, we apply our uncertainty-quantified OMPs to two case studies of application-relevant cross sections. We conclude that, for many common applications of OMPs, including OMP uncertainty should become standard practice. To facilitate their immediate use, digital versions of our updated OMPs and related tools for forward uncertainty propagation are included as Supplemental Material.

Race and Ethnicity, Stage-Specific Mortality, and Cancer Treatment in Esophageal and Gastric Cancers: Surveillance, Epidemiology, and End Results (2000–2018)

Race and Ethnicity, Stage-Specific Mortality, and Cancer Treatment in Esophageal and Gastric Cancers: Surveillance, Epidemiology, and End Results (2000–2018)

O073 Traditional Clinical and Novel Oximetry Measures as Predictors of Cardiovascular Events

Abstract Introduction Intermittent hypoxia is a key mechanism linking Obstructive Sleep Apnoea (OSA) to cardiovascular disease (CVD). Oximetry analysis could enhance understanding of which OSA phenotypes are associated with CVD risk. We investigated if traditional clinical and novel oximetry measures including hypoxic burden (HB) calculated from the polysomnogram SpO2 signal can predict CVD outcomes in all-comers and OSA subsample cohorts from the Sleep Heart Health Study (SHHS). Methods CVD mortality outcome and complete covariate information was used. We implemented 31 oximetry measures and assessed the performance of the parameters in predicting CVD outcomes (CVD death or incident CVD) in the all-comers and sleep apnoea subsamples. The performance of each measure was assessed using an adjusted Cox proportional hazard ratio (HR) analysis. Results In the general subsample, HB successfully predicted CVD death (HR>1.8, p<0.05) but did not predict incident CVD. In the sleep apnoea subsample (AHI>5) with no CVD at baseline, none of the SpO2 measures we considered predicted incident CVD. Discussion The ability of HB to predict CVD outcomes depends on the cohort and the CVD outcome. Our analysis of the selected SpO2 measures in an OSA subsample did not find strong links between any oximetry measures and incident CVD, and therefore no strong candidates for CVD risk phenotyping in the sleep clinic. Further work is needed to understand the complex relationship between OSA-related intermittent hypoxia patterns and development of CVD to further understanding of OSA phenotypes at risk of CVD consequences.

Relationship between Patient Experience Scores and Health Insurance.

(1) Background: the patient experience may be a performance indicator in value-based reimbursement. Accordingly, providers have an incentive to understand factors that affect their patients’ experiences. This study evaluated the relationship between health insurance type and patient experience ratings. (2) Methods: individual-level demographic, health/healthcare, and patient experience data were extracted from the Full-Year Consolidated Data File of the 2019 Medical Expenditure Panel Surveys. A logistic regression was used to evaluate whether how persons—included in this study’s analytic sample (aged 18 and over with complete covariate information)—rated the healthcare they received from all their providers was associated with their health insurance types controlling for covariates. (3) Results: relative to people 18−64 years of age with private health insurance, people 18−64 years of age without health insurance were less likely to rank their healthcare as a 9 or 10—where a 10 indicates the best possible care—(OR: 0.69; p = 0.015) while people aged 65 years or over with Medicare (OR: 1.34; p = 0.002) or with Medicare/private health insurance (OR: 1.48; p < 0.001) were more likely to rank their healthcare as a 9 or 10. (4) Conclusions: Select health insurance types were associated with how patients rate their healthcare. Stakeholders could use this information to create programs aimed to improve patient experience.

Associations between airborne crude oil chemicals and symptom-based asthma.

The 2010 Deepwater Horizon (DWH) oil spill response and cleanup (OSRC) workers were exposed to airborne total hydrocarbons (THC), benzene, toluene, ethylbenzene, o-, m-, and p-xylenes and n-hexane (BTEX-H) from crude oil and PM2.5 from burning/flaring oil and natural gas. Little is known about asthma risk among oil spill cleanup workers. We assessed the relationship between asthma and several oil spill-related exposures including job classes, THC, individual BTEX-H chemicals, the BTEX-H mixture, and PM2.5 using data from the Gulf Long-Term Follow-up (GuLF) Study, a prospective cohort of 24,937 cleanup workers and 7,671 nonworkers following the DWH disaster. Our analysis largely focused on the 19,018 workers without asthma before the spill who had complete exposure, outcome, and covariate information. We defined incident asthma 1-3years following exposure using both self-reported wheeze and self-reported physician diagnosis of asthma. THC and BTEX-H were assigned to participants based on measurement data and work histories, while PM2.5 used modeled estimates. We used modified Poisson regression to estimate risk ratios (RR) and 95% confidence intervals (CIs) for associations between spill-related exposures and asthma and a quantile-based g-computation approach to explore the joint effect of the BTEX-H mixture on asthma risk. OSRC workers had greater asthma risk than nonworkers (RR: 1.60, 95% CI: 1.38, 1.85). Higher estimated THC exposure levels were associated with increased risk in an exposure-dependent manner (linear trend test p<0.0001). Asthma risk also increased with increasing exposure to individual BTEX-H chemicals and the chemical mixture: A simultaneous quartile increase in the BTEX-H mixture was associated with an increased asthma risk of 1.45 (95% CI: 1.35,1.55). With fewer cases, associations were less apparent for physician-diagnosed asthma alone. THC and BTEX-H were associated with increased asthma risk defined using wheeze symptoms as well as a physician diagnosis.

A new approach to estimation of the proportional hazards model based on interval-censored data with missing covariates

This paper discusses the fitting of the proportional hazards model to interval-censored failure time data with missing covariates. Many authors have discussed the problem when complete covariate information is available or the missing is completely at random. In contrast to this, we will focus on the situation where the missing is at random. For the problem, a sieve maximum likelihood estimation approach is proposed with the use of I-spline functions to approximate the unknown cumulative baseline hazard function in the model. For the implementation of the proposed method, we develop an EM algorithm based on a two-stage data augmentation. Furthermore, we show that the proposed estimators of regression parameters are consistent and asymptotically normal. The proposed approach is then applied to a set of the data concerning Alzheimer Disease that motivated this study.

O036 Respiratory event related oxygen desaturation is predictive of cardiovascular mortality in sleep apnoea patients

Abstract Introduction Cardiovascular disease (CVD) is the leading cause of death globally. The mechanisms underpinning the development of CVD in OSA are multifaceted and include sympathetic overactivity, endothelial dysfunction, inflammation, and oxidative stress. Nocturnal hypoxaemic burden—the cumulative exposure to hypoxaemia experienced overnight—may contribute to the pathophysiology of CVD. We investigated if polysomnogram SpO2 parameters can predict CVD outcomes in OSA patients. Methods Data from the SpO2 signals from 4689 polysomnograms (PSGs) of the Sleep Heart Health Study with CVD mortality outcome and complete covariate information was used. Analysis of the average SpO2 responses to respiratory events revealed a transient response from the event start that extended for four event lengths. Based on the response we developed a respiratory event related oxygen desaturation (REROD) parameter for quantifying the desaturation associated with respiratory events that is readily calculated. The performance of the parameter in predicting CVD death was assessed using an adjusted Cox proportional hazard ratio (HR) analysis and compared to other methods including hypoxic burden, T90 and ODI3. Results The COX analysis was adjusted for known covariates of CVD. The HR results indicate a dose-response relationship with the highest quintile providing a HR=2.0(95% C.I. 1.3–3.2). Discussion Our REROD metric predicts CVD mortality independent of confounding covariates and provides prediction performance superior to other hypoxemia metrics. A big advantage of our metric is its computational simplicity and reproducibility. We believe the metric is an important enabling step towards clinical methods that provide CVD risk stratification from the PSG.

Co-Morbidity Patterns Identified Using Latent Class Analysis of Medications Predict All-Cause Mortality Independent of Other Known Risk Factors: The COPDGene® Study.

PurposeMedication patterns include all medications in an individual’s clinical profile. We aimed to identify chronic co-morbidity treatment patterns through medication use among COPDGene participants and determine whether these patterns were associated with mortality, acute exacerbations of chronic obstructive pulmonary disease (AECOPD) and quality of life.Materials and MethodsParticipants analyzed here completed Phase 1 (P1) and/or Phase 2 (P2) of COPDGene. Latent class analysis (LCA) was used to identify medication patterns and assign individuals into unobserved LCA classes. Mortality, AECOPD, and the St. George’s Respiratory Questionnaire (SGRQ) health status were compared in different LCA classes through survival analysis, logistic regression, and Kruskal–Wallis test, respectively.ResultsLCA identified 8 medication patterns from 32 classes of chronic comorbid medications. A total of 8110 out of 10,127 participants with complete covariate information were included. Survival analysis adjusted for covariates showed, compared to a low medication use class, mortality was highest in participants with hypertension+diabetes+statin+antiplatelet medication group. Participants in hypertension+SSRI+statin medication group had the highest odds of AECOPD and the highest SGRQ score at both P1 and P2.ConclusionMedication pattern can serve as a good indicator of an individual’s comorbidities profile and improves models predicting clinical outcomes.

Association of Sex or Race With the Effect of Weight Loss on Physical Function

Consideration of differential treatment effects among subgroups in clinical trial research is a topic of increasing interest. This is an especially salient issue for weight loss trials. To determine whether stratification by sex and race is associated with meaningful differences in physical function response to weight loss among older adults. This pooled analysis used individual-level data from 8 completed randomized clinical trials of weight loss conducted at Wake Forest University or Wake Forest School of Medicine, Winston-Salem, North Carolina. Data were housed within the Wake Forest Older Americans Independence Center data repository and provided complete exposure, outcome, and covariate information. Data were collected from November 1996 to March 30, 2017, and analyzed from August 15, 2019, to June 10, 2020. Treatment arms within each study were collapsed into caloric restriction (CR [n = 734]) and non-CR (n = 583) categories based on whether caloric restriction was specified in the original study protocol. Objectively measured 6-month change in weight, fast-paced gait speed (meters per second), and Short Physical Performance Battery (SPPB) score. A total of 1317 adults (mean [SD] age, 67.7 [5.4] years; 920 [69.9%] female; 275 [20.9%] Black) with overweight or obesity (mean [SD] body mass index [calculated as weight in kilograms divided by height in meters squared], 33.9 [4.4]) were included at baseline. Six-month weight change achieved among those randomized to CR was -7.7% (95% CI, -8.3% to -7.2%), with no difference noted by sex; however, White individuals lost more weight than Black individuals assigned to CR (-9.0% [95% CI, -9.6% to -8.4%] vs -6.0% [95% CI, -6.9% to 5.2%]; P < .001), and all CR groups lost a significantly greater amount from baseline compared with non-CR groups (Black participants in CR vs non-CR groups, -5.3% [95% CI, -6.4% to -4.1%; P < .001]; White participants in CR vs non-CR groups, -7.2% [95% CI, -7.8% to -6.6%; P < .001]). Women experienced greater weight loss-associated improvement in SPPB score (CR group, 0.35 [95% CI, 0.18-0.52]; non-CR group, 0.08 [95% CI, -0.11 to 0.27]) compared with men (CR group, 0.23 [95% CI, 0.00-0.46]; non-CR group, 0.34 [95% CI, 0.09-0.58]; P = .03). Black participants experienced greater weight loss-associated improvement in gait speed (CR group, 0.08 [95% CI, 0.05-0.10] m/s; non-CR group, 0.02 [95% CI, -0.01 to 0.05] m/s) compared with White participants (CR group, 0.07 [95% CI, 0.06-0.09] m/s; non-CR group, 0.06 [95% CI, 0.04-0.08] m/s; P = .02). The association of weight loss on physical function in older adults appears to differ by sex and race. These findings affirm the need to consider biological variables in clinical trial design.

1132: Association of interleukin-6 and obesity across pregnancy

There is evidence that obesity is associated with a state of chronic inflammation. Interleukin-6 (IL-6) is an inflammatory mediator that has been linked to adverse pregnancy outcomes. IL-6 levels are elevated in non-pregnant obese individuals. The association between IL-6 and obesity in pregnancy has not been well established. The objective of this study was to evaluate the association between obesity and IL-6 in pregnancy across gestation. A prospective cohort study of 744 pregnant women was conducted from 2013-2015 at four US sites. Participants were ≥ 18 years old with a singleton pregnancy, English speaking without fetal anomalies or steroid use. Women with recent infection, fever, or antibiotic treatment were excluded. Participants had two blood draws during pregnancy, first between 12w0d-20w6d gestation and second between 32w0d-35w6d gestation. Pre-pregnancy body mass index (BMI) was obtained by self-report. Linear regression was used to model associations between BMI category and percent change in serum IL-6 across study visits. Models were adjusted for maternal age, parity, race, education, time between study visits, gestational age at first study visit, smoking, and study site. Among the 744 participants, 72.8% (n=545) completed both blood draws and had complete covariate information. The mean log-transformed IL-6 levels at the initial study visit were 0.16±0.08, 0.20±0.08, and 0.25±0.09 among normal weight, overweight, and obese subjects, respectively (p< 0.01). IL-6 levels generally increased across gestation in all weight categories, however obese and overweight women had a significantly lower percent change across gestation (Table 1, Figure 1). IL-6 levels are elevated in obese and overweight pregnant women compared to their normal weight counterparts. However, across gestation women with normal pre-pregnancy BMIs experience greater percent change in IL-6 levels. Future work should evaluate how change in inflammation across pregnancy mediates the relationship between obesity and adverse outcomes.View Large Image Figure ViewerDownload Hi-res image Download (PPT)

The impact of the Luton social prescribing programme on energy expenditure: a quantitative before-and-after study

ObjectivesThe objective of this study was to assess the change in energy expenditure levels of service users after participation in the Luton social prescribing programme.DesignUncontrolled before-and-after study.SettingThis study was set...

Aspirin and nonsteroidal anti-inflammatory drug use and keratinocyte cancers: a large population-based cohort study of skin cancer in Australia.

Nonsteroidal anti-inflammatory drugs (NSAIDs) have been postulated as chemopreventive agents for basal cell carcinoma (BCC) and squamous cell carcinoma (SCC), but findings from observational studies have been inconsistent, and clinical trial data are scant. To examine the association between aspirin and NSAID (nonaspirin) use and the risk of BCC and SCC in a large cohort specifically designed for skin cancer outcomes. We used data from the QSkin Study, a prospective cohort of 43764 residents of Queensland, Australia (34630 were included in this study and 23581 were used in our primary analyses). We used Cox proportional hazards models to estimate the hazard ratios (HRs) between self-reported aspirin and NSAID use 1 year prior to study baseline and the first histologically confirmed BCC or SCC for high-risk (history of skin cancer excisions or more than five actinic lesions treated) and average-to-low-risk participants (no history of skin cancer excision and at most five actinic lesions treated). After a median of 3 years of follow-up, 3421 participants developed BCC and 1470 SCC (2288 BCC and 932 SCC with complete covariate information). Among the high-risk group (1826 BCC and 796 SCC), compared with never use, frequent (at least weekly) NSAID use was associated with reduced risk of BCC (HR 0·84, 95% confidence interval 0·71-0.99) but not SCC. Aspirin use was associated with reduced risk of SCC (HR 0·77, 95% confidence interval 0·64-0·93) only among infrequent (less than weekly) users and was not associated with BCC. We observed no association between NSAID or aspirin use and the risk of BCC or SCC among average-to-low-risk participants. While some weakly inverse associations were observed between prior use of aspirin or NSAIDs and skin cancer, the inconsistent patterns of associations do not provide convincing evidence that these medications reduce subsequent skin cancer risk. Further data on doses, duration and long-term follow-up may help us to comprehend the cumulative dose effect.

Gender differences in the association between life history of body silhouettes and asthma incidence: Results from the SAPALDIA cohort study

BackgroundThe association of obesity and asthma has been described in children and adults. However, whether a different life course of weight in men and women may explain gender differences in asthma incidence, has not been addressed. ObjectivesUsing data from the Swiss Cohort Study on Air Pollution and Lung and Heart Diseases in Adults, we investigated the role of overweight/obesity as measured by body silhouettes at different life stages in men and women for asthma incidence. MethodsOur analysis included 5417 subjects who were asthma free at age 8, followed up to 2011, and had complete covariate information. The main predictor of interest was self-reported body silhouettes at age 8, menarche, 30, 45, menopause, and 60, and additionally changes in body silhouette number across these different time points. Asthma incidence was defined as newly reported doctor-diagnosed asthma after the body silhouette time point. Asthma incidence and its association with body silhouettes was analysed using sex stratified logistic regression, adjusting for age, atopy, urbanity, smoking, parental asthma, education and study area. ResultsMen at age 60 had an increased risk of asthma incidence per unit increase in body silhouette number (OR 1.93, 95% CI 1.13–3.30). This association was stronger in women at age 60 (OR 2.78, 95% CI 1.49–5.18) and observed also at menopause (OR 1.35, 95% CI 1.03–1.78), as well as per unit change in body silhouette number between age 45 – menopause (OR 1.74, 95% CI 1.15–2.63). ConclusionIn this longitudinal study, the risk of incident asthma increased in men and women with a larger body silhouette in late adulthood. In women, this risk appeared present between age 45 and menopause. At age 60, both men and women were at higher risk of asthma incidence per unit increase in body silhouette, the risk being more pronounced in women. The age-related increase of obesity may underlie gender differences in asthma incidence at higher ages.

Predicting erectile function following external beam radiation therapy or brachytherapy for prostate cancer using EPIC-CP

87 Background: EPIC-CP (Expanded Prostate Cancer Index Composite for Clinical Practice) is a one page, 16-item questionnaire designed and validated to measure patient-reported health related quality of life in prostate cancer (PC) patients at the point of care in the clinical setting. We previously developed and externally validated models predictive of intact sexual function (i.e. achieving an erection firm enough for intercourse) at two years following external beam radiation (EBRT) or brachytherapy (BT) using EPIC-26, the parent tool from which EPIC-CP was derived. We aimed to enable the use of these models in clinical practice by recalibrating them for use with EPIC-CP. Methods: Using a previously described multicenter longitudinal cohort (PROST-QA), we identified 217 men treated with EBRT and 230 with BT with complete sexual domain and model covariate information. We used the established covariates predictive of functional erections in the EPIC-26-based models (baseline sexual score, neoadjuvant horm...

Chronic disease concordance within Indian households: A cross-sectional study.

BackgroundThe household is a potentially important but understudied unit of analysis and intervention in chronic disease research. We sought to estimate the association between living with someone with a chronic condition and one’s own chronic condition status.Methods and findingsWe conducted a cross-sectional analysis of population-based household- and individual-level data collected in 4 socioculturally and geographically diverse settings across rural and urban India in 2013 and 2014. Of 10,703 adults ages 18 years and older with coresiding household members surveyed, data from 7,522 adults (mean age 39 years) in 2,574 households with complete covariate information were analyzed. The main outcome measures were diabetes (fasting plasma glucose ≥ 126 mg/dL or taking medication), common mental disorder (General Health Questionnaire score ≥ 12), hypertension (blood pressure ≥ 140/90 mmHg or taking medication), obesity (body mass index ≥ 30 kg/m2), and high cholesterol (total blood cholesterol ≥ 240 mg/dL or taking medication). Logistic regression with generalized estimating equations was used to model associations with adjustment for a participant’s age, sex, education, marital status, religion, and study site. Inverse probability weighting was applied to account for missing data. We found that 44% of adults had 1 or more of the chronic conditions examined. Irrespective of familial relationship, adults who resided with another adult with any chronic condition had 29% higher adjusted relative odds of having 1 or more chronic conditions themselves (adjusted odds ratio [aOR] = 1.29; 95% confidence interval [95% CI] 1.10–1.50). We also observed positive statistically significant associations of diabetes, common mental disorder, and hypertension with any chronic condition (aORs ranging from 1.19 to 1.61) in the analysis of all coresiding household members. Associations, however, were stronger for concordance of certain chronic conditions among coresiding household members. Specifically, we observed positive statistically significant associations between living with another adult with diabetes (aOR = 1.60; 95% CI 1.23–2.07), common mental disorder (aOR = 2.69; 95% CI 2.12–3.42), or obesity (aOR = 1.82; 95% CI 1.33–2.50) and having the same condition. Among separate analyses of dyads of parents and their adult children and dyads of spouses, the concordance between the chronic disease status was striking. The associations between common mental disorder, hypertension, obesity, and high cholesterol in parents and those same conditions in their adult children were aOR = 2.20 (95% CI 1.28–3.77), 1.58 (95% CI 1.15–2.16), 4.99 (95% CI 2.71–9.20), and 2.57 (95% CI 1.15–5.73), respectively. The associations between diabetes and common mental disorder in husbands and those same conditions in their wives were aORs = 2.28 (95% CI 1.52–3.42) and 3.01 (95% CI 2.01–4.52), respectively. Relative odds were raised even across different chronic condition phenotypes; specifically, we observed positive statistically significant associations between hypertension and obesity in the total sample of all coresiding adults (aOR = 1.24; 95% CI 1.02–1.52), high cholesterol and diabetes in the adult-parent sample (aOR = 2.02; 95% CI 1.08–3.78), and hypertension and diabetes in the spousal sample (aOR = 1.51; 95% CI 1.05–2.17). Of all associations examined, only the relationship between hypertension and diabetes in the adult-parent dyads was statistically significantly negative (aOR = 0.62; 95% CI 0.40–0.94). Relatively small samples in the dyadic analysis and site-specific analysis call for caution in interpreting qualitative differences between associations among different dyad types and geographical locations. Because of the cross-sectional nature of the analysis, the findings do not provide information on the etiology of incident chronic conditions among household members.ConclusionsWe observed strong concordance of chronic conditions within coresiding adults across diverse settings in India. These data provide early evidence that a household-based approach to chronic disease research may advance public health strategies to prevent and control chronic conditions.Trial registrationClinical Trials Registry India CTRI/2013/10/004049; http://ctri.nic.in/Clinicaltrials/login.php

Early menarche and new onset of asthma: Results from the SAPALDIA cohort study

RationaleThe association between early menarche and new onset of asthma warrants further investigation in those aged >30 years. ObjectivesUsing data from the Swiss Cohort Study on Air Pollution and Lung and Heart Diseases in Adults (SAPALDIA), we investigated whether early menarche was associated with new onset of asthma in women aged 18–60 years at baseline. MethodsOur analysis included 2492 women with information on age at menarche and doctor-diagnosed asthma, who had been asthma free at the time of menarche and had complete covariate information. New onset of asthma was defined as newly reported doctor-diagnosed asthma which occurred at least one year after menarche. Asthma incidence and its association with early menarche was analysed using logistic regression, adjusting for age, atopy, smoking, BMI, parental asthma, urbanity, education and study area, and additionally stratifying by atopy and BMI. ResultsAfter adjustment of relevant confounders, women with early menarche did not have a significantly higher risk of onset of asthma than women without early menarche (OR 1.23, 95% CI 0.85–1.80). Young atopic women with early menarche appeared to have an increased risk of asthma compared with non-atopic women (OR 2.21, 95% CI 0.90–5.43); however, our results did not reach statistical significance. ConclusionWe could not substantiate an association of early menarche with new onset of asthma in this Swiss population-based cohort aged 18–60 years at baseline. Future studies may need to prospectively assess age of menarche to investigate the association with new onset of asthma in those aged >30 years.