We develop a probability model for evaluating long-term outcomes due to regular screening that in... more We develop a probability model for evaluating long-term outcomes due to regular screening that incorporates the effects of prior screening examinations. Previous models assume that individuals have no prior screening examinations at their current ages. Due to current widespread medical emphasis on screening, the consideration of screening histories is essential, particularly in assessing the benefit of future screening examinations given a certain number of previous negative screens. Screening participants are categorized into four mutually exclusive groups: symptom-free-life, no-early-detection, true-early-detection, and overdiagnosis. For each case, we develop models that incorporate a person's current age, screening history, expected future screening frequency, screening test sensitivity, and other factors, and derive the probabilities of occurrence for the four groups. The probability of overdiagnosis among screen-detected cases is derived and estimated. The model applies to screening for any disease or condition; for concreteness, we focus on female breast cancer and use data from the study conducted by the Health Insurance Plan of Greater New York (HIP) to estimate these probabilities and corresponding credible intervals. The model can provide policy makers with important information regarding ranges of expected lives saved and percentages of true-early-detection and overdiagnosis among the screen-detected cases.
Based on recent reports from the National Lung Screening Trial (NLST), smokers who were screened ... more Based on recent reports from the National Lung Screening Trial (NLST), smokers who were screened by low-dose computer tomography (LDCT) had a 20% lower chance of dying from lung cancer than those screened by chest X-rays. However, due to the complexities of lead time bias and over diagnosis, no formal test has been shown to reduce lung cancer mortality. To correctly evaluate survival benefit due to early detection, it is critical to estimate lead time, the length of time that detection of a disease is advanced by screening. We applied a recently developed probability method to estimate lead time, using the LDCT data from NLST, where human lifetime was treated as random and derived from the actuarial life table of the US Social Security Administration. Using Bayesian posterior samples of key parameters extracted from the NLST-LDCT data, simulations on lead time were carried out on 16 hypothetical cohorts with four initial ages (55, 60, 65, and 70) and four future screening intervals (12, 18, 24, and 30 months). For each scenario, the estimated lead time for both screendetected and interval cases is reported. Results show that the probability of no-earlydetection (interval cases) increases monotonically when the screening interval increases for both genders. A male heavy smoker with an initial screening age at 60 has 11.65% (female 6.76%) chance of no-early-detection with annual screenings. This probability increases to 36.35% (female 28.26%) if the screenings were biennial. The mean lead time appears longer for women than for men. The mean lead time decreases when the screening interval increases, but it appears stable across different initial age groups.
Using a Bayesian approach to clinical trial design is becoming more common. For example, at the M... more Using a Bayesian approach to clinical trial design is becoming more common. For example, at the MD Anderson Cancer Center, Bayesian techniques are routinely employed in the design and analysis of Phase I and II trials. It is important that the operating characteristics of these procedures be determined as part of the process when establishing a stopping rule for a clinical trial. This study determines the power function for some common fixed-sample procedures in hypothesis testing, namely the one and two-sample tests involving the binomial and normal distributions. Also considered is a Bayesian test for multi-response (response and toxicity) in a Phase II trial, where the power function is determined.
The implementation of a Bayesian approach to wavelet regression that corresponds to the human vis... more The implementation of a Bayesian approach to wavelet regression that corresponds to the human visual system is examined. Most existing research in this area assumes non-informative priors, that is, a prior with mean zero. A new way is offered to implement prior information that mimics a visual inspection of noisy data, to obtain a first impression about the shape of the function that results in a prior with non-zero mean. This visually adaptive Bayesian (VAB) prior has a simple structure, intuitive interpretation, and is easy to implement. Skorohod topology is suggested as a more appropriate measure in signal recovering than the commonly used mean-squared error.
Normalization is an essential step with considerable impact on high-throughput RNA sequencing (RN... more Normalization is an essential step with considerable impact on high-throughput RNA sequencing (RNA-seq) data analysis. Although there are numerous methods for read count normalization, it remains a challenge to choose an optimal method due to multiple factors contributing to read count variability that affects the overall sensitivity and specificity. In order to properly determine the most appropriate normalization methods, it is critical to compare the performance and shortcomings of a representative set of normalization routines based on different dataset characteristics. Therefore, we set out to evaluate the performance of the commonly used methods (DESeq, TMM-edgeR, FPKM-CuffDiff, TC, Med UQ and FQ) and two new methods we propose: Med-pgQ2 and UQ-pgQ2 (per-gene normalization after per-sample median or upper-quartile global scaling). Our per-gene normalization approach allows for comparisons between conditions based on similar count levels. Using the benchmark Microarray Quality ...
A nonlinear mixed-effects approach is developed for disease progression models that incorporate v... more A nonlinear mixed-effects approach is developed for disease progression models that incorporate variation in age in a Bayesian framework. We further generalize the probability model for sensitivity to depend on age at diagnosis, time spent in the preclinical state and sojourn time. The developed models are then applied to the Johns Hopkins Lung Project data and the Health Insurance Plan for Greater New York data using Bayesian Markov chain Monte Carlo and are compared with the estimation method that does not consider random-effects from age. Using the developed models, we obtain not only age-specific individual-level distributions, but also population-level distributions of sensitivity, sojourn time and transition probability.
Generally, novices are taught fiberoptic intubation on patients by attending anesthesiologists; h... more Generally, novices are taught fiberoptic intubation on patients by attending anesthesiologists; however, this approach raises patient safety concerns. Patient safety should improve if novice learners are trained for basic skills on simulators. In this educational study, we assessed the time and number of attempts required to train novices in fiberoptic bronchoscopy and fiberoptic intubation on simulators. Because decay in skills is inevitable, we also assessed fiberoptic bronchoscopy and fiberoptic intubation skill decay and the amount of effort required to regain fiberoptic bronchoscopy skill. First, we established attempt- and duration-based quantitative norms for reaching skill proficiency for fiberoptic bronchoscopy and fiberoptic intubation by experienced anesthesiologists (n = 8) and prepared an 11-step checklist and a 5-point global rating scale for assessment. Novice learners (n = 15) were trained to reach the established skill proficiency in a Virtual Reality simulator for ...
I would like to thank all the people who made this work possible. First, I would like to thank my... more I would like to thank all the people who made this work possible. First, I would like to thank my principle advisor, Dr. Seongho Kim, for his guidance and patience that he gave me throughout this research project. I would not have accomplished this project without his help and support. I would also like to thank Dr. Xiang Zhang for giving me an opportunity to work on this project. I appreciate his moral and financial support during this eight months. Also many thanks to Dr. Dongfeng Wu, for being my thesis committee member and assisting and supporting me during my Master's study at University of Louisville.
Journal of modern applied statistical methods : JMASM, 2005
A general simulation procedure is described to validate model fitting algorithms for complex like... more A general simulation procedure is described to validate model fitting algorithms for complex likelihood functions that are utilized in periodic cancer screening trials. Although screening programs have existed for a few decades, there are still many unsolved problems, such as how age or hormone affects the screening sensitivity, the sojourn time in the preclinical state, and the transition probability from disease-free state to the preclinical state. Simulations are needed to check reliability or validity of the likelihood function combined with the associated effect functions. One bottleneck in the simulation procedure is the very time consuming calculations of the maximum likelihood estimates (MLE) from generated data. A practical procedure is presented, along with results for when both sensitivity and transition probability into the preclinical state are age-dependent. The procedure is also suitable for other applications.
ABSTRACT We develop a probability model for evaluating long-term effects due to regular screening... more ABSTRACT We develop a probability model for evaluating long-term effects due to regular screening. People who take part in cancer screening are divided into four mutually exclusive groups: True-early-detection, No-early-detection, Overdiagnosis, and Symptom-free-life. For each case, we derive the probability formula. Simulation studies using the HIP (Health Insurance Plan for Greater New York) breast cancer study data provide estimates for these probabilities and the corresponding credible intervals. These probabilities change with a person’s age at study entry, screening frequency, screening sensitivity, and other parameters. We also allow the human life time to be subject to a competing risk of death from other causes. The model can provide policy makers with important information regarding the distribution of individuals participating in a screening program who eventually fall into one of the four groups.
Lung cancer screening using X-rays has been controversial for many years. A major concern is whet... more Lung cancer screening using X-rays has been controversial for many years. A major concern is whether lung cancer screening really brings any survival benefits, which depends on effective treatment after early detection. The problem was analyzed from a different point of view and estimates were presented of the projected lead time for participants in a lung cancer screening program using the Johns Hopkins Lung Project (JHLP) data. The newly developed method of lead time estimation was applied where the lifetime T was treated as a random variable rather than a fixed value, resulting in the number of future screenings for a given individual is a random variable. Using the actuarial life table available from the United States Social Security Administration, the lifetime distribution was first obtained, then the lead time distribution was projected using the JHLP data. The data analysis with the JHLP data shows that, for a male heavy smoker with initial screening ages at 50, 60, and 70, ...
We estimated the effects on the lead time for women participating in a long-term breast cancer sc... more We estimated the effects on the lead time for women participating in a long-term breast cancer screening program when the screening sensitivities and disease progression are independent of age. The lead time, or time by which a diagnosis is advanced by screening, is one of the major concerns of any cancer screening program, which we consider to include both a mammogram and physical examination. Using estimates of test sensitivities and mean sojourn times previously calculated by other authors from observed data, we estimated properties of the lead time. We utilized the model for the lead time derived by other authors and ran simulations for different screening program designs, concentrating on screening interval lengths of 0.5 years, 1 year, 1.5 years, and 2 years. These estimates were based on a long-term screening program from age 50 to 80. For each six-month decrease in screening interval length, we estimated the percent increase in mean lead time, as well as the percent increase in the proportion of clinical patients who will have their cancer detected at a screening exam.
Background: The importance of fiberoptic bronchoscopy (FOB) and intubation (FOI) is well establis... more Background: The importance of fiberoptic bronchoscopy (FOB) and intubation (FOI) is well established to reduce anesthesia-related morbidity and mortality during airway management in clinical practice. We conducted a trial to determine whether simulation-based training of novices can increase FOB and FOI skills to an expert level. Methods: Eight anesthesiologists as experts and 15 fourth-year medical students as novices were enrolled. The computerized AccuTouch ® Bronchoscopy Simulator (ATBS, Immersion Medical, Gaithersburg, MD) and the Human Airway Anatomy Simulator (HAAS, Medical Plastics Inc, Gatesville, TX) were used for FOB and FOI training and testing, respectively. Data included three discrete variables: the numbers of airway collisions, oral passes, and nasal passes. Experts were tested, while novices were tested, trained, and retested. Twelve novices returned after 2 months and were again tested, retrained, and retested. Data were analyzed by a newly proposed likelihood ratio test based on the assumption that the data follow a Poisson distribution. A testing procedure was derived to compare performance between experts, novices pre-and post-training, and novices after the 2-month lag period. Results: As expected, experts outperformed pre-trained novices on all variables (P , 0.0001). Post-training, novices' skills improved (P , 0.0001) to the point that there were no significant differences between experts and novices post-training (P = 0.1709, 0.9857, and 0.5014 for collisions, and oral and nasal passes, respectively). After 2 months there was a significant decay in FOB skills among novices compared to the prior level achieved (P , 0.0001), but brief retraining brought their performance back to the expert level (P = 0.2207). Conclusion: Due to the small sample size, normal approximation is not applicable; therefore many existing tests are not appropriate. Our novel likelihood ratio test provided a powerful tool in analyzing the small samples of discrete training data. Simulation can be used to train novices in fiberoptic airway skills to an expert level in a relatively short period of time.
The objective of this study was to investigate the moisture absorption process for wood-based com... more The objective of this study was to investigate the moisture absorption process for wood-based composites subjected to over-saturated moisture conditions. Two stages are comprised in the moisture transfer process at the oversaturated moisture conditions, an initial stage which is the moisture transfer process mainly under fiber saturation point (FSP), and a second stage which is the moisture transfer process beyond the FSP. A model was developed based on two-part equations to describe the process, from which three coefficients (k 1 , k 21 , and k 22) can be used to quantitatively describe the moisture transfer process under the conditions. Two different wood-based composites, wood fiberboard and wood fiber/polymer composites (polymer content: 30%), were used to test the model at four different ambient temperatures (30, 45, 62, and 80°C). It was shown that the two-part equation can accurately describe the moisture absorption process under over-saturated moisture conditions. The moisture absorption rate in the initial stage was about 30-60% greater than that in the second stage for most of the cases evaluated in this study. The higher the temperature, the greater moisture absorption parameters were obtained. At both moisture absorption stages (below FSP and above FSP), the calculated activation energy for the moisture
We investigate screening sensitivity, transition probability and sojourn time in lung cancer scre... more We investigate screening sensitivity, transition probability and sojourn time in lung cancer screening for male heavy smokers using the Mayo Lung Project data. We also estimate the lead time distribution, its property, and the projected effect of taking regular chest X-rays for lung cancer detection. We apply the statistical method developed by Wu et al. [1] using the Mayo Lung Project (MLP) data, to make Bayesian inference for the screening test sensitivity, the age-dependent transition probability from disease-free to preclinical state, and the sojourn time distribution, for male heavy smokers in a periodic screening program. We then apply the statistical method developed by Wu et al. [2] using the Bayesian posterior samples from the MLP data to make inference for the lead time, the time of diagnosis advanced by screening for male heavy smokers. The lead time is distributed as a mixture of a point mass at zero and a piecewise continuous distribution, which corresponds to the probability of no-early-detection, and the probability distribution of the early diagnosis time. We present estimates of these two measures for male heavy smokers by simulations. The posterior sensitivity is almost symmetric, with posterior mean 0.89, and posterior median 0.91; the 95% highest posterior density (HPD) interval is (0.72, 0.98). The posterior mean sojourn time is 2.24 years, with a posterior median of 2.20 years for male heavy smokers. The 95% HPD interval for the mean sojourn time is (1.57, 3.35) years. The age-dependent transition probability is not a monotone function of age; it has a single maximum at age 68. The mean lead time increases as the screening time interval decreases. The standard error of the lead time also increases as the screening time interval decreases. Although the mean sojourn time for male heavy smokers is longer than expected, the predictive estimation of the lead time is much shorter. This may provide policy makers important information on the effectiveness of the chest X-rays and sputum cytology in lung cancer early detection.
We develop a probability model for evaluating long-term outcomes due to regular screening that in... more We develop a probability model for evaluating long-term outcomes due to regular screening that incorporates the effects of prior screening examinations. Previous models assume that individuals have no prior screening examinations at their current ages. Due to current widespread medical emphasis on screening, the consideration of screening histories is essential, particularly in assessing the benefit of future screening examinations given a certain number of previous negative screens. Screening participants are categorized into four mutually exclusive groups: symptom-free-life, no-early-detection, true-early-detection, and overdiagnosis. For each case, we develop models that incorporate a person's current age, screening history, expected future screening frequency, screening test sensitivity, and other factors, and derive the probabilities of occurrence for the four groups. The probability of overdiagnosis among screen-detected cases is derived and estimated. The model applies to screening for any disease or condition; for concreteness, we focus on female breast cancer and use data from the study conducted by the Health Insurance Plan of Greater New York (HIP) to estimate these probabilities and corresponding credible intervals. The model can provide policy makers with important information regarding ranges of expected lives saved and percentages of true-early-detection and overdiagnosis among the screen-detected cases.
Based on recent reports from the National Lung Screening Trial (NLST), smokers who were screened ... more Based on recent reports from the National Lung Screening Trial (NLST), smokers who were screened by low-dose computer tomography (LDCT) had a 20% lower chance of dying from lung cancer than those screened by chest X-rays. However, due to the complexities of lead time bias and over diagnosis, no formal test has been shown to reduce lung cancer mortality. To correctly evaluate survival benefit due to early detection, it is critical to estimate lead time, the length of time that detection of a disease is advanced by screening. We applied a recently developed probability method to estimate lead time, using the LDCT data from NLST, where human lifetime was treated as random and derived from the actuarial life table of the US Social Security Administration. Using Bayesian posterior samples of key parameters extracted from the NLST-LDCT data, simulations on lead time were carried out on 16 hypothetical cohorts with four initial ages (55, 60, 65, and 70) and four future screening intervals (12, 18, 24, and 30 months). For each scenario, the estimated lead time for both screendetected and interval cases is reported. Results show that the probability of no-earlydetection (interval cases) increases monotonically when the screening interval increases for both genders. A male heavy smoker with an initial screening age at 60 has 11.65% (female 6.76%) chance of no-early-detection with annual screenings. This probability increases to 36.35% (female 28.26%) if the screenings were biennial. The mean lead time appears longer for women than for men. The mean lead time decreases when the screening interval increases, but it appears stable across different initial age groups.
Using a Bayesian approach to clinical trial design is becoming more common. For example, at the M... more Using a Bayesian approach to clinical trial design is becoming more common. For example, at the MD Anderson Cancer Center, Bayesian techniques are routinely employed in the design and analysis of Phase I and II trials. It is important that the operating characteristics of these procedures be determined as part of the process when establishing a stopping rule for a clinical trial. This study determines the power function for some common fixed-sample procedures in hypothesis testing, namely the one and two-sample tests involving the binomial and normal distributions. Also considered is a Bayesian test for multi-response (response and toxicity) in a Phase II trial, where the power function is determined.
The implementation of a Bayesian approach to wavelet regression that corresponds to the human vis... more The implementation of a Bayesian approach to wavelet regression that corresponds to the human visual system is examined. Most existing research in this area assumes non-informative priors, that is, a prior with mean zero. A new way is offered to implement prior information that mimics a visual inspection of noisy data, to obtain a first impression about the shape of the function that results in a prior with non-zero mean. This visually adaptive Bayesian (VAB) prior has a simple structure, intuitive interpretation, and is easy to implement. Skorohod topology is suggested as a more appropriate measure in signal recovering than the commonly used mean-squared error.
Normalization is an essential step with considerable impact on high-throughput RNA sequencing (RN... more Normalization is an essential step with considerable impact on high-throughput RNA sequencing (RNA-seq) data analysis. Although there are numerous methods for read count normalization, it remains a challenge to choose an optimal method due to multiple factors contributing to read count variability that affects the overall sensitivity and specificity. In order to properly determine the most appropriate normalization methods, it is critical to compare the performance and shortcomings of a representative set of normalization routines based on different dataset characteristics. Therefore, we set out to evaluate the performance of the commonly used methods (DESeq, TMM-edgeR, FPKM-CuffDiff, TC, Med UQ and FQ) and two new methods we propose: Med-pgQ2 and UQ-pgQ2 (per-gene normalization after per-sample median or upper-quartile global scaling). Our per-gene normalization approach allows for comparisons between conditions based on similar count levels. Using the benchmark Microarray Quality ...
A nonlinear mixed-effects approach is developed for disease progression models that incorporate v... more A nonlinear mixed-effects approach is developed for disease progression models that incorporate variation in age in a Bayesian framework. We further generalize the probability model for sensitivity to depend on age at diagnosis, time spent in the preclinical state and sojourn time. The developed models are then applied to the Johns Hopkins Lung Project data and the Health Insurance Plan for Greater New York data using Bayesian Markov chain Monte Carlo and are compared with the estimation method that does not consider random-effects from age. Using the developed models, we obtain not only age-specific individual-level distributions, but also population-level distributions of sensitivity, sojourn time and transition probability.
Generally, novices are taught fiberoptic intubation on patients by attending anesthesiologists; h... more Generally, novices are taught fiberoptic intubation on patients by attending anesthesiologists; however, this approach raises patient safety concerns. Patient safety should improve if novice learners are trained for basic skills on simulators. In this educational study, we assessed the time and number of attempts required to train novices in fiberoptic bronchoscopy and fiberoptic intubation on simulators. Because decay in skills is inevitable, we also assessed fiberoptic bronchoscopy and fiberoptic intubation skill decay and the amount of effort required to regain fiberoptic bronchoscopy skill. First, we established attempt- and duration-based quantitative norms for reaching skill proficiency for fiberoptic bronchoscopy and fiberoptic intubation by experienced anesthesiologists (n = 8) and prepared an 11-step checklist and a 5-point global rating scale for assessment. Novice learners (n = 15) were trained to reach the established skill proficiency in a Virtual Reality simulator for ...
I would like to thank all the people who made this work possible. First, I would like to thank my... more I would like to thank all the people who made this work possible. First, I would like to thank my principle advisor, Dr. Seongho Kim, for his guidance and patience that he gave me throughout this research project. I would not have accomplished this project without his help and support. I would also like to thank Dr. Xiang Zhang for giving me an opportunity to work on this project. I appreciate his moral and financial support during this eight months. Also many thanks to Dr. Dongfeng Wu, for being my thesis committee member and assisting and supporting me during my Master's study at University of Louisville.
Journal of modern applied statistical methods : JMASM, 2005
A general simulation procedure is described to validate model fitting algorithms for complex like... more A general simulation procedure is described to validate model fitting algorithms for complex likelihood functions that are utilized in periodic cancer screening trials. Although screening programs have existed for a few decades, there are still many unsolved problems, such as how age or hormone affects the screening sensitivity, the sojourn time in the preclinical state, and the transition probability from disease-free state to the preclinical state. Simulations are needed to check reliability or validity of the likelihood function combined with the associated effect functions. One bottleneck in the simulation procedure is the very time consuming calculations of the maximum likelihood estimates (MLE) from generated data. A practical procedure is presented, along with results for when both sensitivity and transition probability into the preclinical state are age-dependent. The procedure is also suitable for other applications.
ABSTRACT We develop a probability model for evaluating long-term effects due to regular screening... more ABSTRACT We develop a probability model for evaluating long-term effects due to regular screening. People who take part in cancer screening are divided into four mutually exclusive groups: True-early-detection, No-early-detection, Overdiagnosis, and Symptom-free-life. For each case, we derive the probability formula. Simulation studies using the HIP (Health Insurance Plan for Greater New York) breast cancer study data provide estimates for these probabilities and the corresponding credible intervals. These probabilities change with a person’s age at study entry, screening frequency, screening sensitivity, and other parameters. We also allow the human life time to be subject to a competing risk of death from other causes. The model can provide policy makers with important information regarding the distribution of individuals participating in a screening program who eventually fall into one of the four groups.
Lung cancer screening using X-rays has been controversial for many years. A major concern is whet... more Lung cancer screening using X-rays has been controversial for many years. A major concern is whether lung cancer screening really brings any survival benefits, which depends on effective treatment after early detection. The problem was analyzed from a different point of view and estimates were presented of the projected lead time for participants in a lung cancer screening program using the Johns Hopkins Lung Project (JHLP) data. The newly developed method of lead time estimation was applied where the lifetime T was treated as a random variable rather than a fixed value, resulting in the number of future screenings for a given individual is a random variable. Using the actuarial life table available from the United States Social Security Administration, the lifetime distribution was first obtained, then the lead time distribution was projected using the JHLP data. The data analysis with the JHLP data shows that, for a male heavy smoker with initial screening ages at 50, 60, and 70, ...
We estimated the effects on the lead time for women participating in a long-term breast cancer sc... more We estimated the effects on the lead time for women participating in a long-term breast cancer screening program when the screening sensitivities and disease progression are independent of age. The lead time, or time by which a diagnosis is advanced by screening, is one of the major concerns of any cancer screening program, which we consider to include both a mammogram and physical examination. Using estimates of test sensitivities and mean sojourn times previously calculated by other authors from observed data, we estimated properties of the lead time. We utilized the model for the lead time derived by other authors and ran simulations for different screening program designs, concentrating on screening interval lengths of 0.5 years, 1 year, 1.5 years, and 2 years. These estimates were based on a long-term screening program from age 50 to 80. For each six-month decrease in screening interval length, we estimated the percent increase in mean lead time, as well as the percent increase in the proportion of clinical patients who will have their cancer detected at a screening exam.
Background: The importance of fiberoptic bronchoscopy (FOB) and intubation (FOI) is well establis... more Background: The importance of fiberoptic bronchoscopy (FOB) and intubation (FOI) is well established to reduce anesthesia-related morbidity and mortality during airway management in clinical practice. We conducted a trial to determine whether simulation-based training of novices can increase FOB and FOI skills to an expert level. Methods: Eight anesthesiologists as experts and 15 fourth-year medical students as novices were enrolled. The computerized AccuTouch ® Bronchoscopy Simulator (ATBS, Immersion Medical, Gaithersburg, MD) and the Human Airway Anatomy Simulator (HAAS, Medical Plastics Inc, Gatesville, TX) were used for FOB and FOI training and testing, respectively. Data included three discrete variables: the numbers of airway collisions, oral passes, and nasal passes. Experts were tested, while novices were tested, trained, and retested. Twelve novices returned after 2 months and were again tested, retrained, and retested. Data were analyzed by a newly proposed likelihood ratio test based on the assumption that the data follow a Poisson distribution. A testing procedure was derived to compare performance between experts, novices pre-and post-training, and novices after the 2-month lag period. Results: As expected, experts outperformed pre-trained novices on all variables (P , 0.0001). Post-training, novices' skills improved (P , 0.0001) to the point that there were no significant differences between experts and novices post-training (P = 0.1709, 0.9857, and 0.5014 for collisions, and oral and nasal passes, respectively). After 2 months there was a significant decay in FOB skills among novices compared to the prior level achieved (P , 0.0001), but brief retraining brought their performance back to the expert level (P = 0.2207). Conclusion: Due to the small sample size, normal approximation is not applicable; therefore many existing tests are not appropriate. Our novel likelihood ratio test provided a powerful tool in analyzing the small samples of discrete training data. Simulation can be used to train novices in fiberoptic airway skills to an expert level in a relatively short period of time.
The objective of this study was to investigate the moisture absorption process for wood-based com... more The objective of this study was to investigate the moisture absorption process for wood-based composites subjected to over-saturated moisture conditions. Two stages are comprised in the moisture transfer process at the oversaturated moisture conditions, an initial stage which is the moisture transfer process mainly under fiber saturation point (FSP), and a second stage which is the moisture transfer process beyond the FSP. A model was developed based on two-part equations to describe the process, from which three coefficients (k 1 , k 21 , and k 22) can be used to quantitatively describe the moisture transfer process under the conditions. Two different wood-based composites, wood fiberboard and wood fiber/polymer composites (polymer content: 30%), were used to test the model at four different ambient temperatures (30, 45, 62, and 80°C). It was shown that the two-part equation can accurately describe the moisture absorption process under over-saturated moisture conditions. The moisture absorption rate in the initial stage was about 30-60% greater than that in the second stage for most of the cases evaluated in this study. The higher the temperature, the greater moisture absorption parameters were obtained. At both moisture absorption stages (below FSP and above FSP), the calculated activation energy for the moisture
We investigate screening sensitivity, transition probability and sojourn time in lung cancer scre... more We investigate screening sensitivity, transition probability and sojourn time in lung cancer screening for male heavy smokers using the Mayo Lung Project data. We also estimate the lead time distribution, its property, and the projected effect of taking regular chest X-rays for lung cancer detection. We apply the statistical method developed by Wu et al. [1] using the Mayo Lung Project (MLP) data, to make Bayesian inference for the screening test sensitivity, the age-dependent transition probability from disease-free to preclinical state, and the sojourn time distribution, for male heavy smokers in a periodic screening program. We then apply the statistical method developed by Wu et al. [2] using the Bayesian posterior samples from the MLP data to make inference for the lead time, the time of diagnosis advanced by screening for male heavy smokers. The lead time is distributed as a mixture of a point mass at zero and a piecewise continuous distribution, which corresponds to the probability of no-early-detection, and the probability distribution of the early diagnosis time. We present estimates of these two measures for male heavy smokers by simulations. The posterior sensitivity is almost symmetric, with posterior mean 0.89, and posterior median 0.91; the 95% highest posterior density (HPD) interval is (0.72, 0.98). The posterior mean sojourn time is 2.24 years, with a posterior median of 2.20 years for male heavy smokers. The 95% HPD interval for the mean sojourn time is (1.57, 3.35) years. The age-dependent transition probability is not a monotone function of age; it has a single maximum at age 68. The mean lead time increases as the screening time interval decreases. The standard error of the lead time also increases as the screening time interval decreases. Although the mean sojourn time for male heavy smokers is longer than expected, the predictive estimation of the lead time is much shorter. This may provide policy makers important information on the effectiveness of the chest X-rays and sputum cytology in lung cancer early detection.
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Papers by Dongfeng Wu