Estimating the number of people with hepatitis C virus who have ever injected drugs and have yet to be diagnosed: an evidence synthesis approach for Scotland.

AIMS: To estimate the number of people who have ever injected drugs (defined here as PWID) living in Scotland in 2009 who have been infected with the hepatitis C virus (HCV) and to quantify and characterize the population remaining undiagnosed. METHODS: Information from routine surveillance (n=22616) and survey data (n=2511) was combined using a multiparameter evidence synthesis approach to estimate the size of the PWID population, HCV antibody prevalence and the proportion of HCV antibody prevalent cases who have been diagnosed, in subgroups defined by recency of injecting (in the last year or not), age (15-34 and 35-64 years), gender and region of residence (Greater Glasgow and Clyde and the rest of Scotland). RESULTS: HCV antibody-prevalence among PWID in Scotland during 2009 was estimated to be 57% [95% CI=52-61%], corresponding to 46657 [95% credible interval (CI)=33812-66803] prevalent cases. Of these, 27434 (95% CI=14636-47564) were undiagnosed, representing 59% [95% CI=43-71%] of prevalent cases. Among the undiagnosed, 83% (95% CI=75-89%) were PWID who had not injected in the last year and 71% (95% CI=58-85%) were aged 35-64 years. CONCLUSIONS: The number of undiagnosed hepatitis C virus-infected cases in Scotland appears to be particularly high among those who have injected drugs more than 1 year ago and are more than 35 years old.

Prospective estimation of rates of change in mammographic parenchymal patterns: influence of age and of hormone replacement therapy.

The objective of this study was to assess the effect of age, breast size and use of hormone replacement therapy (HRT) on the rate of change of mammographic parenchymal patterns, and the effect of age on the probability of misclassification between patterns. It was designed as a longitudinal study of the members of the treatment arm of a non-randomized screening trial in which subjects were assigned to screening or not by year of birth. The subjects were women in the Kotka district of Finland, each of whom attended for four or five mammographic screens. Participants were all women living in the district who were born in the relevant years and accepted an invitation to screening. A model was fitted to the longitudinal data comprising the observed Wolfe patterns on each woman, with age and breast size as predictors of breast density at first screen, age and HRT use as predictors of change in density at future screens, and age as a predictor of misclassification of true density between favourable (non-dense) and unfavourable (dense) patterns (according to the Wolfe classification). Relevant posterior probability estimates (with 95% credible intervals) were as follows. The probability that a woman of age 43.5 is truly in the favourable state ranged from 0.35 (0.34-0.37) for smallest breast size to 0.74 (0.72-0.76) for the largest. The probability that a woman is truly in the favourable state at first screen increased from 0.37 (0.36-0.38) at age 40 to 0.59 (0.58-0.60) at age 47. The probability that a woman having a later screen who had truly been in the unfavourable state at her previous screen changed to the favourable state increased from 0.12 (0.11-0.13) at age 42 to 0.48 (0.46-0.50) at age 55 for a woman not taking HRT, and from 0.10 (0.09-0.11) to 0.43 (0.40-0.45) at the same ages for a woman taking HRT. The probability that a woman would have changed from being truly in the favourable state to the unfavourable state was 0.003 (0.001-0.003) for any age and HRT use. The probability that a woman truly in a favourable state would be correctly classified rose from 0.87 (0.85-0.89) at age 40 to 0.998 (0.997-0.998) at age 55. The probability that a woman truly in the unfavourable state would be correctly classified decreased from 0.96 (0.95-0.97) to 0.93 (0.91-0.94) between the same ages. The probability of being in a non-dense, favourable state increases with age, as does the rate of change from dense to non-dense patterns. These are consistent with previous work. The probability of non-dense patterns and the rate of change to non-dense patterns are reduced with HRT use. Errors of classification are relatively rare, but are dependent on the age of the subject.

Misclassification in a matched case-control study with variable matching ratio: application to a study of c-erbB-2 overexpression and breast cancer.

We provide a simple analytic correction for risk factor misclassification in a matched case-control study with variable numbers of controls per case. The method is an extension of existing methodology, and involves estimating the corrected proportions of controls and cases in risk factor categories within each matched set. These estimates are then used to calculate the Mantel-Haenszel odds ratio estimate corrected for misclassification. A simulation-based interval estimate is developed. An example is given from a study of risk factors for progression of benign breast disease to breast cancer, in which the risk factor is a biological marker measured with poor sensitivity.