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Estimating Sensitivity and Sojourn Time in Screening for Colorectal Cancer A Comparison of Statistical Approaches

TLDR
Various analytic strategies for fitting exponential models to data from a screening program for colorectal cancer conducted in Calvados, France, between 1991 and 1994 are considered, yielding estimates of mean sojourn time and sensitivity.
Abstract
The effectiveness of cancer screening depends crucially on two elements: the sojourn time (that is, the duration of the preclinical screen-detectable period) and the sensitivity of the screening test. Previous literature on methods of estimating mean sojourn time and sensitivity has largely concentrated on breast cancer screening. Screening for colorectal cancer has been shown to be effective in randomized trials, but there is little literature on the estimation of sojourn time and sensitivity. It would be interesting to demonstrate whether methods commonly used in breast cancer screening could be used in colorectal cancer screening. In this paper, the authors consider various analytic strategies for fitting exponential models to data from a screening program for colorectal cancer conducted in Calvados, France, between 1991 and 1994. The models yielded estimates of mean sojourn time of approximately 2 years for 45- to 54-year-olds, 3 years for 55- to 64-year-olds, and 6 years for 65- to 74-year-olds. Estimates of sensitivity were approximately 75%, 50%, and 40% for persons aged 45-54, 55-64, and 65-74 years, respectively. There is room for improvement in all models in terms of goodness of fit, particularly for the first year after screening, but results from randomized trials indicate that the sensitivity estimates are roughly correct. Am J Epidemiol 1998;148:609-19.

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Sojourn Time of Preclinical Colorectal Cancer by Sex and Age: Estimates From the German National Screening Colonoscopy Database

TL;DR: This study provides, for the first time, precise estimates of sojourn time by age and sex, and it suggests thatSojourn times are remarkably consistent across age groups and in both sexes.
Journal ArticleDOI

Measuring interval cancers in population‐based screening using different assays of fecal occult blood testing: The district of Florence experience

TL;DR: It is confirmed that RPHA is more sensitive than the guaiac test, and the assumption that FOBT screening for CRC has to be based on a guaiAC test should be reconsidered, and RPHA should be recommended as the standard FOBTs for screening purposes.
Journal ArticleDOI

Effectiveness of interventions to improve follow-up after abnormal cervical cancer screening.

TL;DR: Cognitive strategies led to the greatest improvement in compliance with follow-up of abnormal Pap smear screening tests, and evaluation of the cost-effectiveness of these strategies are important priorities for future research.
Journal ArticleDOI

The relationship between endogenous testosterone and lipid profile in middle-aged and elderly Chinese men

TL;DR: There was a significant linear trend toward lower total cholesterol, lower triglycerides, and higher HDL-C with increasing serum TT with increasing TT, which remained significant after adjusting for age, BMI, fasting blood glucose, systolic blood pressure, free triiodothyronine, free thyroxine, and TSH.
References
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Journal ArticleDOI

Inference from Iterative Simulation Using Multiple Sequences

TL;DR: The focus is on applied inference for Bayesian posterior distributions in real problems, which often tend toward normal- ity after transformations and marginalization, and the results are derived as normal-theory approximations to exact Bayesian inference, conditional on the observed simulations.
Journal ArticleDOI

Sampling-Based Approaches to Calculating Marginal Densities

TL;DR: In this paper, three sampling-based approaches, namely stochastic substitution, the Gibbs sampler, and the sampling-importance-resampling algorithm, are compared and contrasted in relation to various joint probability structures frequently encountered in applications.
Journal Article

Sampling-based approaches to calculating marginal densities

TL;DR: Stochastic substitution, the Gibbs sampler, and the sampling-importance-resampling algorithm can be viewed as three alternative sampling- (or Monte Carlo-) based approaches to the calculation of numerical estimates of marginal probability distributions.
Book

The Mathematica Book

TL;DR: Mathematica has defined the state of the art in technical computing for over a decade, and has become a standard in many of the world's leading companies and universities as discussed by the authors.

The Mathematica book

TL;DR: From the Publisher: Mathematica has defined the state of the art in technical computing for over a decade, and has become a standard in many of the world's leading companies and universities.
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