Hyune Ju Kim

Permutation tests for joinpoint regression with applications to cancer rates

The identification of changes in the recent trend is an important issue in the analysis of cancer mortality and incidence data. We apply a joinpoint regression model to describe such continuous changes and use the grid-search method to fit the regression function with unknown joinpoints assuming constant variance and uncorrelated errors. We find the number of significant joinpoints by performing several permutation tests, each of which has a correct significance level asymptotically. Each p-value is found using Monte Carlo methods, and the overall asymptotic significance level is maintained through a Bonferroni correction. These tests are extended to the situation with non-constant variance to handle rates with Poisson variation and possibly autocorrelated errors. The performance of these tests are studied via simulations and the tests are applied to U.S. prostate cancer incidence and mortality rates.

Use of recombinant human soluble TNF receptor in anorectic tumor-bearing rats

With progression of tumor growth, rats demonstrate anorexia and reduced food intake, a function of meal number and meal size. Tumor necrosis factor-alpha (TNF-alpha), a recognized anorectic agent, reacts with two different receptors (type I: 55 kDa; type II: 75 kDa). We used a dimeric, pegylated 55-kDa TNF receptor construct to test its effects on food intake, meal number, and meal size, which were continuously measured with a rat eater meter in 16 Fischer 344 male rats injected with 10(6) viable methylcholanthrene cells. When anorexia developed, rats received a subcutaneous injection of either 0.25 mg/kg body wt of soluble TNF receptor construct (study) or vehicle (tumor-bearing control). Before TNF inhibitor injection, no differences were observed in food intake, meal number, or meal size between the two groups. After the TNF inhibitor injection, study vs. control rats significantly improved food intake as a result of an increase in meal number and meal size. Rats also showed a significant improvement in body weight. These data suggest that TNF-alpha, in addition to other cytokines, contributes to the anorexia of tumor growth, probably mediated via the hypothalamus.With progression of tumor growth, rats demonstrate anorexia and reduced food intake, a function of meal number and meal size. Tumor necrosis factor-α (TNF-α), a recognized anorectic agent, reacts with two different receptors (type I: 55 kDa; type II: 75 kDa). We used a dimeric, pegylated 55-kDa TNF receptor construct to test its effects on food intake, meal number, and meal size, which were continuously measured with a rat eater meter in 16 Fischer 344 male rats injected with 106 viable methylcholanthrene cells. When anorexia developed, rats received a subcutaneous injection of either 0.25 mg/kg body wt of soluble TNF receptor construct (study) or vehicle (tumor-bearing control). Before TNF inhibitor injection, no differences were observed in food intake, meal number, or meal size between the two groups. After the TNF inhibitor injection, study vs. control rats significantly improved food intake as a result of an increase in meal number and meal size. Rats also showed a significant improvement in body weight. These data suggest that TNF-α, in addition to other cytokines, contributes to the anorexia of tumor growth, probably mediated via the hypothalamus.

Nicotine alters the usual reciprocity between meal size and meal number in female rat

Tobacco smoking reduces appetite and body weight (BW). Cessation of smoking leads to hyperphagia and weight gain. Daily food intake (FI) is a function of meal number (MN) and meal size (MZ), i.e., FI=MNxMZ. Under normal conditions, the female Fischer rat has a periodic reciprocal fluctuation between MZ and MN corresponding to phase of estrous cycle. Wide fluctuations between MZ and MN compensate each other to keep FI constant. Nicotine (5 mg/kg BW/day) was infused via osmotic minipump for 7 days. Controls received saline. FI, MZ, and MN were measured by an Automated Computerized Rat Eater Meter. Nicotine significantly decreased BW and FI via a decrease in MZ without compensatory increase of MN. Nicotine cessation led to hyperphagia, normalizing BW loss via an increase in MZ, which exceeded a compensatory decrease in MN. Nicotine significantly prolonged the estrous cycle by an extension of proestrous phase. Nicotine significantly lengthened the intermeal interval (IMI), delaying the start of the next meal and simultaneously decreasing subsequent MZ. Stopping nicotine led to normalization of IMI and MZ. Data show that nicotine alters the usual reciprocal regulation between MZ and MN and leads to a prolongation of the estrous cycle.

Predicting US- and state-level cancer counts for the current calendar year: Part II: Evaluation of spatiotemporal projection methods for incidence

The current study was undertaken to evaluate the spatiotemporal projection models applied by the American Cancer Society to predict the number of new cancer cases.

Estimating joinpoints in continuous time scale for multiple change-point models

Joinpoint models have been applied to the cancer incidence and mortality data with continuous change points. The current estimation method [Lerman, P.M., 1980. Fitting segmented regression models by grid search. Appl. Statist. 29, 77-84] assumes that the joinpoints only occur at discrete grid points. However, it is more realistic that the joinpoints take any value within the observed data range. Hudson [1966. Fitting segmented curves whose join points have to be estimated. J. Amer. Statist. Soc. 61, 1097-1129] provides an algorithm to find the weighted least square estimates of the joinpoint on the continuous scale. Hudson described the estimation procedure in detail for a model with only one joinpoint, but its extension to a multiple joinpoint model is not straightforward. In this article, we describe in detail Hudsons method for the multiple joinpoint model and discuss issues in the implementation. We compare the computational efficiencies of the LGS method and Hudsons method. The comparisons between the proposed estimation method and several alternative approaches, especially the Bayesian joinpoint models, are discussed. Hudsons method is implemented by C++ and applied to the colorectal cancer incidence data for men under age 65 from SEER nine registries.

Predicting US and State-Level Cancer Counts for the Current Calendar Year: Part I – Evaluation of Temporal Projection Methods for Mortality

A study was undertaken to evaluate the temporal projection methods that are applied by the American Cancer Society to predict 4‐year‐ahead projections.

On Using Truncated Sequential Probability Ratio Test Boundaries for Monte Carlo Implementation of Hypothesis Tests

When designing programs or software for the implementation of Monte Carlo (MC) hypothesis tests, we can save computation time by using sequential stopping boundaries. Such boundaries imply stopping resampling after relatively few replications if the early replications indicate a very large or a very small p value. We study a truncated sequential probability ratio test (SPRT) boundary and provide a tractable algorithm to implement it. We review two properties desired of any MC p value, the validity of the p value and a small resampling risk, where resampling risk is the probability that the accept/reject decision will be different than the decision from complete enumeration. We show how the algorithm can be used to calculate a valid p value and confidence intervals for any truncated SPRT boundary. We show that a class of SPRT boundaries is minimax with respect to resampling risk and recommend a truncated version of boundaries in that class by comparing their resampling risk (RR) to the RR of fixed boundaries with the same maximum resample size. We study the lack of validity of some simple estimators of p values and offer a new, simple valid p value for the recommended truncated SPRT boundary. We explore the use of these methods in a practical example and provide the MChtest R package to perform the methods.

Inference in segmented line regression: a simulation study

A segmented line regression model has been used to describe changes in cancer incidence and mortality trends [Kim, H.-J., Fay, M.P., Feuer, E.J. and Midthune, D.N., 2000, Permutation tests for joinpoint regression with applications to cancer rates. Statistics in Medicine, 19, 335–351. Kim, H.-J., Fay, M.P., Yu, B., Barrett., M.J. and Feuer, E.J., 2004, Comparability of segmented line regression models. Biometrics, 60, 1005–1014.]. The least squares fit can be obtained by using either the grid search method proposed by Lerman [Lerman, P.M., 1980, Fitting segmented regression models by grid search. Applied Statistics, 29, 77–84.] which is implemented in Joinpoint 3.0 available at http://srab.cancer.gov/joinpoint/index.html, or by using the continuous fitting algorithm proposed by Hudson [Hudson, D.J., 1966, Fitting segmented curves whose join points have to be estimated. Journal of the American Statistical Association, 61, 1097–1129.] which will be implemented in the next version of Joinpoint software. Following the least squares fitting of the model, inference on the parameters can be pursued by using the asymptotic results of Hinkley [Hinkley, D.V., 1971, Inference in two-phase regression. Journal of the American Statistical Association, 66, 736–743.] and Feder [Feder, P.I., 1975a, On asymptotic distribution theory in segmented regression Problems-Identified Case. The Annals of Statistics, 3, 49–83.] Feder [Feder, P.I., 1975b, The log likelihood ratio in segmented regression. The Annals of Statistics, 3, 84–97.] Via simulations, this paper empirically examines small sample behavior of these asymptotic results, studies how the two fitting methods, the grid search and the Hudsons algorithm affect these inferential procedures, and also assesses the robustness of the asymptotic inferential procedures.

vmn Hypothalamic Dopamine And Serotonin In Anorectic Septic Rats

ABSTRACT During sepsis, catabolism of proteins and associated changes in plasma amino acids occur. Tryptophan and tyrosine, and their derivatives serotonin (5‐HT) and dopamine (DA), influence hypothalamic feeding‐related areas and are associated with the onset of anorexia. We hypothesized that anorexia of sepsis is associated with changes in serotonin and dopamine in the ventromedial nucleus (VMN) of the hypothalamus. The aim of this study was to test our hypothesis by measuring intra‐VMN changes of these two neurotransmitters at the onset of anorexia during sepsis. Fischer 344 male rats had an intracerebral guide cannula stereotaxically implanted into the VMN. Ten days later, in awake, overnight‐food‐deprived rats, a microdialysis probe was inserted through the in situ VMN cannula. Two hours thereafter, serial baseline serotonin and dopamine concentrations were measured. Then cecal ligation and puncture to induce sepsis or a control laparotomy was performed under isoflurane anesthesia. VMN microdialysis samples were serially collected every 30 min for 8 h after the surgical procedure to determine 5‐HT and DA changes in response to sepsis. During the hypermetabolic response to sepsis, a strong association occurred between anorexia and a significant reduction of VMN dopamine concentration (P < 0.05; constant rate of dopamine decrease in the Study group of 0.99 pg per 2 h); no changes occurred in 5‐HT in association with anorexia of sepsis. Six hours after operation, a single meal was offered for 20 min to assess the response of neurotransmitters to food ingestion. Food intake was minimal in anorectic septic rats (mean size of the after food‐deprived meal in the Septic group was 0.03 ± 0.01 g, that of the Control group was 1.27 ± 0.14 g; P = 0.0001), while Control rats demonstrated anticipated changes in neurotransmitters in response to eating. We conclude that the onset of anorexia in septic rats is associated with a reduction in VMN dopamine.

AEWS: an integrated knowledge-based system with neural networks for reliability prediction

Abstract The ability of accurately predicting reliability for products is an invaluable asset for any manufacturing company. The United Technologies Carrier developed such a system based on Weibull distribution. However, predicting accurate reliability requires experienced persons special knowledge. Two expert systems were developed to capture such knowledge. The use of Weibull plots was critical in interpreting the results of failure rates. This interpretation process was imitated by employing multi-layer feed-forward neural networks. The expert systems and neural networks are integrated with the already existing Early Warning System (EWS) and databases. The resulting system, Automatic Early Warning System (AEWS), is currently deployed in United Technologies Carrier and has led to a significant boost in productivity by at least 8 times in terms of process time.