The case‐cohort design for longitudinal data consists of a subcohort sampled at the beginning of the study that is followed repeatedly over time, and a case sample that is ascertained through the ...course of the study. Although some members in the subcohort may experience events over the study period, we refer to it as the “control‐cohort.” The case sample is a random sample of subjects not in the control‐cohort, who have experienced at least one event during the study period. Different correlations among repeated observations on the same individual are accommodated by a two‐level random‐effects model. This design allows consistent estimation of all parameters estimable in a cohort design and is a cost‐effective way to study the effects of covariates on repeated observations of relatively rare binary outcomes when exposure assessment is expensive. It is an extension of the case‐cohort design (Prentice, 1986, Biometrika73, 1–11) and the bidirectional case‐crossover design (Navidi, 1998, Biometrics54, 596–605). A simulation study compares the efficiency of the longitudinal case‐cohort design to a full cohort analysis, and we find that in certain situations up to 90% efficiency can be obtained with half the sample size required for a full cohort analysis. A bootstrap method is presented that permits testing for intra‐subject homogeneity in the presence of unidentifiable nuisance parameters in the two‐level random‐effects model. As an illustration we apply the design to data from an ongoing study of childhood asthma.
Family studies to identify disease‐related genes often collect families with multiple cases. If environmental exposures or other measured covariates are also important, they should be incorporated ...into these genetic analyses to control for confounding and increase statistical power. We propose a two‐level mixed effects model that allows us to estimate environmental effects while accounting for varying genetic correlations among family members and adjusting for ascertainment by conditioning on the number of cases in the family. We describe a conditional maximum likelihood analysis based on this model. When genetic effects are negligible, this conditional likelihood reduces to standard conditional logistic regression. We show that the simpler conditional logistic regression typically yields biased estimators of exposure effects, and we describe conditions under which the conditional logistic approach has little or no bias.
Methods for efficiently identifying subjects with constantly acidic pH in epidemiological and clinical studies have not been assessed. We recruited 30 volunteers to estimate the minimum number of ...urine pH measurements using pH strips needed to identify subjects with “constantly acidic urine pH” Spearman's correlation coefficients between urine pH measured with a pH meter and with the four pH strips ranged from 0.94 to 0.95 (p < 0.001 for all four strips). Overall agreement within ±0.5 pH units between the four strips and the pH meter ranged from 62.2% to 74.4%. When using a spot urine sample from a single morning to classify participants with respect to their urine pH, 80% of individuals fell into the acidic urine pH (pH equal to or lower than 6.0) group. When we required subjects to have urine pH equal to or lower than 6.0 in six consecutive AM spot urine samples and seven spot PM urine samples, only 20% of participants fulfilled this criterion. Measuring urine pH twice a day (early in the morning and early in the evening) during four consecutive days classified individuals in the same way as two daily measurements for one week. A single pH measurement from a spot urine sample is not reliable to identify individuals with constantly acidic pH. Morning and evening urine pH measurements with pH strips during four consecutive days identify individuals with constantly acidic urine pH individuals as well as one week of measurements, and thus might be useful to identify subjects with constantly acidic urine pH in epidemiological and clinical studies.
Lesser degrees of terminal duct lobular unit (TDLU) involution, as reflected by higher numbers of TDLUs and acini/TDLU, are associated with elevated breast cancer risk. In rodent models, the ...insulin-like growth factor (IGF) system regulates involution of the mammary gland. We examined associations of circulating IGF measures with TDLU involution in normal breast tissues among women without precancerous lesions. Among 715 Caucasian and 283 African American (AA) women who donated normal breast tissue samples to the Komen Tissue Bank between 2009 to 2012 (75% premenopausal), serum concentrations of IGF-I and binding protein (IGFBP)-3 were quantified using enzyme-linked immunosorbent assay. Hematoxilyn & eosin-stained tissue sections were assessed for numbers of TDLUs (“TDLU count”). Zero-inflated Poisson regression models with a robust variance estimator were used to estimate relative risks (RRs) for association of IGF measures (tertiles) with TDLU count by race and menopausal status, adjusting for potential confounders. AA (vs. Caucasian) women had higher age-adjusted mean levels of serum IGF-I (137 vs. 131 ng/mL, p=0.07) and lower levels of IGFBP-3 (4165 vs. 4684 ng/mL, p<0.0001). Postmenopausal IGFBP-3 was inversely associated with TDLU count among AA (RR
T3vs.T1
=0.49, 95% CI=0.28-0.84, p-trend=0.04) and Caucasian (RR
T3vs.T1
=0.64, 95% CI=0.42-0.98, p-trend=0.04) women. In premenopausal women, higher IGF-I:IGFBP-3 ratios were associated with higher TDLU count in Caucasian (RR
T3vs.T1
=1.33, 95% CI=1.02-1.75, p-trend=0.04), but not in AA (RR
T3vs.T1
=0.65, 95% CI=0.42-1.00, p-trend=0.05), women. Our data suggest a role of the IGF system, particularly IGFBP-3, in TDLU involution of the normal breast, a breast cancer risk factor, among Caucasian and AA women.
Welzel et al. discuss the impact of classification of hilar cholangiocarcinoma on rates of intra- and extrahepatic cholangiocarcinomas. A consistent global classification of hilar cholangiocarcinoma ...is required to compare trends around the world.
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