Focusing on COVID-19 deaths may underestimate the pandemic's effect on racial and ethnic disparities. This study estimated excess deaths related and unrelated to COVID-19 in the United States from ... Visual Racial and Ethnic Disparities in Excess Deaths During the COVID-19 Pandemic. Focusing on COVID-19 deaths may underestimate the pandemic's effect on racial and ethnic disparities. Th... Background: Although racial/ethnic disparities in U.S. COVID-19 death rates are striking, focusing on COVID-19 deaths alone may underestimate the true effect of the pandemic on disparities. Excess ...

Several optimality properties of Dorfman’s (1943) group testing procedure are derived for estimation of the prevalence of a rare disease whose status is classified with error. Exact ranges of disease prevalence are obtained for which group testing provides more efficient estimation when group size increases.

Background: To assess the feasibility and early toxicity of selective, IMRT-based dose escalation (simultaneous integrated boost) to biopsy proven dominant intra-prostatic lesions visible on MRI. Methods: Patients with localized prostate cancer and an abnormality within the prostate on endorectal coil MRI were eligible. All patients underwent a MRI-guided transrectal biopsy at the location of the MRI abnormality. Gold fiducial markers were also placed. Several days later patients underwent another MRI scan for fusion with the treatment planning CT scan. This fused MRI scan was used to delineate the region of the biopsy proven intra-prostatic lesion. A 3 mm expansion was performed on the intra-prostatic lesions, defined as a separate volume within the prostate. The lesion + 3 mm and the remainder of the prostate + 7 mm received 94.5/75.6 Gray (Gy) respectively in 42 fractions. Daily seed position was verified to be within 3 mm. Results: Three patients were treated. Follow-up was 18, 6, and 3 months respectively. Two patients had a single intra-prostatic lesion. One patient had 2 intra-prostatic lesions. All four intra-prostatic lesions, with margin, were successfully targeted and treated to 94.5 Gy. Two patients experienced acute RTOG grade 2 genitourinary (GU) toxicity. One had grade 1 gastrointestinal (GI) toxicity. All symptoms completely resolved by 3 months. One patient had no acute toxicity. Conclusion: These early results demonstrate the feasibility of using IMRT for simultaneous integrated boost to biopsy proven dominant intra-prostatic lesions visible on MRI. The treatment was well tolerated.

Objectives: To report on the ultrasound quality assurance program for the National Institute of Child Health and Human Development Fetal Growth Studies and describe both its advantages and generalizability.Methods: After training on an ultrasound system and software, research sonographers were expected to capture blank (unmeasured) images in triplicate for crown‐rump length, biparietal diameter, head circumference, abdominal circumference, and femur length. A primary expert sonographer was designated and validated. A 5% sample (n = 740 of 14,785 scans) was randomly selected in 3 distinct rounds from within strata of maternal body mass index (round 1 only), gestational age, and research site. Unmeasured images were extracted from selected scans and measured with the ultrasound software by an expert sonographer. Correlations and coefficients of variation (CVs) were calculated, and the within‐measurement standard deviation (ie, technical error of the measurement), was calculated.Results: The reliability between the site sonographers and the expert was high, with correlations exceeding 0.99 for all dimensions in all rounds. The CV % values showed low variability, with the percentage differences being less than 2%, except for abdominal circumference in rounds 2 and 3, in which it averaged about 3%. Correlations remained high (>0.90) with increasing fetal size; there was a monotonic increase in technical errors of the measurement but without a corresponding increase in the CV %.Conclusions: Using rigorous procedures for training sonographers, coupled with quality assurance oversight, we determined that the measurements acquired longitudinally for singletons are both accurate and reliable for establishment of an ultrasound standard for fetal growth.

Estimates of excess mortality during the coronavirus disease 2019 (COVID-19) pandemic provide an important metric for quantifying deaths due to COVID-19 as well as those indirectly caused by COVID-... Visual Impact of Population Growth and Aging on Excess U.S. Deaths During COVID-19 Estimates of excess mortality during the coronavirus disease 2019 (COVID-19) pandemic provide an importan... 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...

In many medical studies, patients are followed longitudinally and interest is on assessing the relationship between longitudinal measurements and time to an event. Recently, various authors have proposed joint modeling approaches for longitudinal and time-to-event data for a single longitudinal variable. These joint modeling approaches become intractable with even a few longitudinal variables. In this paper we propose a regression calibration approach for jointly modeling multiple longitudinal measurements and discrete time-to-event data. Ideally, a two-stage modeling approach could be applied in which the multiple longitudinal measurements are modeled in the first stage and the longitudinal model is related to the time-to-event data in the second stage. Biased parameter estimation due to informative dropout makes this direct two-stage modeling approach problematic. We propose a regression calibration approach which appropriately accounts for informative dropout. We approximate the conditional distribution of the multiple longitudinal measurements given the event time by modeling all pairwise combinations of the longitudinal measurements using a bivariate linear mixed model which conditions on the event time. Complete data are then simulated based on estimates from these pairwise conditional models, and regression calibration is used to estimate the relationship between longitudinal data and time-to-event data using the complete data. We show that this approach performs well in estimating the relationship between multivariate longitudinal measurements and the time-to-event data and in estimating the parameters of the multiple longitudinal process subject to informative dropout. We illustrate this methodology with simulations and with an analysis of primary biliary cirrhosis (PBC) data.