Open Access. Powered by Scholars. Published by Universities.®
Physical Sciences and Mathematics Commons™
Open Access. Powered by Scholars. Published by Universities.®
- Keyword
-
- Cross-validation (3)
- Colon cancer (2)
- Dependence (2)
- Functional genomics (2)
- Linear regression (2)
-
- Model selection (2)
- Multivariate distribution (2)
- Non-neoplastic mucosa (2)
- Prognosis prediction (2)
- Screening (2)
- Sensitivity (2)
- Transformation model (2)
- Alzheimer's disease (1)
- B-splines; Cox regression; Generalized cross validation; Marker events; Nonparametric regression; Survival Analysis; Time-dependent covariates (1)
- Basket trials (1)
- Bayesian method; Case-control; Etiology; Latent class; Measurement error; Pneumonia (1)
- Bayesian methods (1)
- Binding site (1)
- Biomarkers (1)
- Bivariate survival (1)
- Bootstrap (1)
- Breast cancer screening (1)
- Cancer staging (1)
- Case-control studies (1)
- Causal inference; End stage renal disease; Instrumental variables; Unmeasured confounding; Weak instruments (1)
- ChIP-Chip data (1)
- Chromatin immunoprecipitation (1)
- Classification (1)
- Clayton model (1)
- Clinical breast examination (1)
- Publication Year
- Publication
-
- The University of Michigan Department of Biostatistics Working Paper Series (7)
- Johns Hopkins University, Dept. of Biostatistics Working Papers (4)
- Memorial Sloan-Kettering Cancer Center, Dept. of Epidemiology & Biostatistics Working Paper Series (4)
- UW Biostatistics Working Paper Series (4)
- U.C. Berkeley Division of Biostatistics Working Paper Series (3)
Articles 1 - 23 of 23
Full-Text Articles in Physical Sciences and Mathematics
A Modular Framework For Early-Phase Seamless Oncology Trials, Philip S. Boonstra, Thomas M. Braun, Elizabeth C. Chase
A Modular Framework For Early-Phase Seamless Oncology Trials, Philip S. Boonstra, Thomas M. Braun, Elizabeth C. Chase
The University of Michigan Department of Biostatistics Working Paper Series
Background: As our understanding of the etiology and mechanisms of cancer becomes more sophisticated and the number of therapeutic options increases, phase I oncology trials today have multiple primary objectives. Many such designs are now 'seamless', meaning that the trial estimates both the maximum tolerated dose and the efficacy at this dose level. Sponsors often proceed with further study only with this additional efficacy evidence. However, with this increasing complexity in trial design, it becomes challenging to articulate fundamental operating characteristics of these trials, such as (i) what is the probability that the design will identify an acceptable, i.e. safe …
Estimating The Probability Of Clonal Relatedness Of Pairs Of Tumors In Cancer Patients, Audrey Mauguen, Venkatraman E. Seshan, Irina Ostrovnaya, Colin B. Begg
Estimating The Probability Of Clonal Relatedness Of Pairs Of Tumors In Cancer Patients, Audrey Mauguen, Venkatraman E. Seshan, Irina Ostrovnaya, Colin B. Begg
Memorial Sloan-Kettering Cancer Center, Dept. of Epidemiology & Biostatistics Working Paper Series
Next generation sequencing panels are being used increasingly in cancer research to study tumor evolution. A specific statistical challenge is to compare the mutational profiles in different tumors from a patient to determine the strength of evidence that the tumors are clonally related, i.e. derived from a single, founder clonal cell. The presence of identical mutations in each tumor provides evidence of clonal relatedness, although the strength of evidence from a match is related to how commonly the mutation is seen in the tumor type under investigation. This evidence must be weighed against the evidence in favor of independent tumors …
Strengthening Instrumental Variables Through Weighting, Douglas Lehmann, Yun Li, Rajiv Saran, Yi Li
Strengthening Instrumental Variables Through Weighting, Douglas Lehmann, Yun Li, Rajiv Saran, Yi Li
The University of Michigan Department of Biostatistics Working Paper Series
Instrumental variable (IV) methods are widely used to deal with the issue of unmeasured confounding and are becoming popular in health and medical research. IV models are able to obtain consistent estimates in the presence of unmeasured confounding, but rely on assumptions that are hard to verify and often criticized. An instrument is a variable that influences or encourages individuals toward a particular treatment without directly affecting the outcome. Estimates obtained using instruments with a weak influence over the treatment are known to have larger small-sample bias and to be less robust to the critical IV assumption that the instrument …
Models For Hsv Shedding Must Account For Two Levels Of Overdispersion, Amalia Magaret
Models For Hsv Shedding Must Account For Two Levels Of Overdispersion, Amalia Magaret
UW Biostatistics Working Paper Series
We have frequently implemented crossover studies to evaluate new therapeutic interventions for genital herpes simplex virus infection. The outcome measured to assess the efficacy of interventions on herpes disease severity is the viral shedding rate, defined as the frequency of detection of HSV on the genital skin and mucosa. We performed a simulation study to ascertain whether our standard model, which we have used previously, was appropriately considering all the necessary features of the shedding data to provide correct inference. We simulated shedding data under our standard, validated assumptions and assessed the ability of 5 different models to reproduce the …
An Efficient Basket Trial Design, Kristen Cunanan, Alexia Iasonos, Ronglai Shen, Colin B. Begg, Mithat Gonen
An Efficient Basket Trial Design, Kristen Cunanan, Alexia Iasonos, Ronglai Shen, Colin B. Begg, Mithat Gonen
Memorial Sloan-Kettering Cancer Center, Dept. of Epidemiology & Biostatistics Working Paper Series
The landscape for early phase cancer clinical trials is changing dramatically due to the advent of targeted therapy. Increasingly, new drugs are designed to work against a target such as the presence of a specific tumor mutation. Since typically only a small proportion of cancer patients will possess the mutational target, but the mutation is present in many different cancers, a new class of basket trials is emerging, whereby the drug is tested simultaneously in different baskets, i.e., sub-groups of different tumor types. Investigators not only desire to test whether the drug works, but also to determine which types of …
Nested Partially-Latent, Class Models For Dependent Binary Data, Estimating Disease Etiology, Zhenke Wu, Maria Deloria-Knoll, Scott L. Zeger
Nested Partially-Latent, Class Models For Dependent Binary Data, Estimating Disease Etiology, Zhenke Wu, Maria Deloria-Knoll, Scott L. Zeger
Johns Hopkins University, Dept. of Biostatistics Working Papers
The Pneumonia Etiology Research for Child Health (PERCH) study seeks to use modern measurement technology to infer the causes of pneumonia for which gold-standard evidence is unavailable. The paper describes a latent variable model designed to infer from case-control data the etiology distribution for the population of cases, and for an individual case given his or her measurements. We assume each observation is drawn from a mixture model for which each component represents one cause or disease class. The model addresses a major limitation of the traditional latent class approach by taking account of residual dependence among multivariate binary outcome …
Partially-Latent Class Models (Plcm) For Case-Control Studies Of Childhood Pneumonia Etiology, Zhenke Wu, Maria Deloria-Knoll, Laura L. Hammitt, Scott L. Zeger
Partially-Latent Class Models (Plcm) For Case-Control Studies Of Childhood Pneumonia Etiology, Zhenke Wu, Maria Deloria-Knoll, Laura L. Hammitt, Scott L. Zeger
Johns Hopkins University, Dept. of Biostatistics Working Papers
In population studies on the etiology of disease, one goal is the estimation of the fraction of cases attributable to each of several causes. For example, pneumonia is a clinical diagnosis of lung infection that may be caused by viral, bacterial, fungal, or other pathogens. The study of pneumonia etiology is challenging because directly sampling from the lung to identify the etiologic pathogen is not standard clinical practice in most settings. Instead, measurements from multiple peripheral specimens are made. This paper considers the problem of estimating the population etiology distribution and the individual etiology probabilities. We formulate the scientific …
Dose Expansion Cohorts In Phase I Trials, Alexia Iasonos, John O'Quigley
Dose Expansion Cohorts In Phase I Trials, Alexia Iasonos, John O'Quigley
Memorial Sloan-Kettering Cancer Center, Dept. of Epidemiology & Biostatistics Working Paper Series
A rapidly increasing number of Phase I dose-finding studies, and in particular those based on the standard 3+3 design, frequently prolong the study and include dose expansion cohorts (DEC) with the goal to better characterize the toxicity profiles of experimental agents and to study disease specific cohorts. These trials consist of two phases: the usual dose escalation phase that aims to establish the maximum tolerated dose (MTD) and the dose expansion phase that accrues additional patients, often with different eligibility criteria, and where additional information is being collected. Current protocols typically do not specify whether the MTD will be updated …
A Systematic Selection Method For The Development Of Cancer Staging Systems, Yunzhi Lin, Richard Chappell, Mithat Gonen
A Systematic Selection Method For The Development Of Cancer Staging Systems, Yunzhi Lin, Richard Chappell, Mithat Gonen
Memorial Sloan-Kettering Cancer Center, Dept. of Epidemiology & Biostatistics Working Paper Series
The tumor-node-metastasis (TNM) staging system has been the anchor of cancer diagnosis, treatment, and prognosis for many years. For meaningful clinical use, an orderly, progressive condensation of the T and N categories into an overall staging system needs to be defined, usually with respect to a time-to-event outcome. This can be considered as a cutpoint selection problem for a censored response partitioned with respect to two ordered categorical covariates and their interaction. The aim is to select the best grouping of the TN categories. A novel bootstrap cutpoint/model selection method is proposed for this task by maximizing bootstrap estimates of …
Group Comparison Of Eigenvalues And Eigenvectors Of Diffusion Tensors, Armin Schwartzman, Robert F. Dougherty, Jonathan E. Taylor
Group Comparison Of Eigenvalues And Eigenvectors Of Diffusion Tensors, Armin Schwartzman, Robert F. Dougherty, Jonathan E. Taylor
Harvard University Biostatistics Working Paper Series
No abstract provided.
Prognosis Of Stage Ii Colon Cancer By Non-Neoplastic Mucosa Gene Expresssion Profiling, Alain Barrier, Sandrine Dudoit, Et Al.
Prognosis Of Stage Ii Colon Cancer By Non-Neoplastic Mucosa Gene Expresssion Profiling, Alain Barrier, Sandrine Dudoit, Et Al.
U.C. Berkeley Division of Biostatistics Working Paper Series
Aims. This study assessed the possibility to build a prognosis predictor, based on non-neoplastic mucosa microarray gene expression measures, in stage II colon cancer patients. Materials and Methods. Non-neoplastic colonic mucosa mRNA samples from 24 patients (10 with a metachronous metastasis, 14 with no recurrence) were profiled using the Affymetrix HGU133A GeneChip. The k-nearest neighbor method was used for prognosis prediction using microarray gene expression measures. Leave-one-out cross-validation was used to select the number of neighbors and number of informative genes to include in the predictor. Based on this information, a prognosis predictor was proposed and its accuracy estimated by …
Colon Cancer Prognosis Prediction By Gene Expression Profiling, Alain Barrier, Sandrine Dudoit, Et Al.
Colon Cancer Prognosis Prediction By Gene Expression Profiling, Alain Barrier, Sandrine Dudoit, Et Al.
U.C. Berkeley Division of Biostatistics Working Paper Series
Aims. This study assessed the possibility to build a prognosis predictor, based on microarray gene expression measures, in stage II and III colon cancer patients. Materials and Methods. Tumour (T) and non-neoplastic mucosa (NM) mRNA samples from 18 patients (9 with a recurrence, 9 with no recurrence) were profiled using the Affymetrix HGU133A GeneChip. The k-nearest neighbour method was used for prognosis prediction using T and NM gene expression measures. Six-fold cross-validation was applied to select the number of neighbours and the number of informative genes to include in the predictors. Based on this information, one T-based and one NM-based …
Semiparametric Methods For The Binormal Model With Multiple Biomarkers, Debashis Ghosh
Semiparametric Methods For The Binormal Model With Multiple Biomarkers, Debashis Ghosh
The University of Michigan Department of Biostatistics Working Paper Series
Abstract: In diagnostic medicine, there is great interest in developing strategies for combining biomarkers in order to optimize classification accuracy. A popular model that has been used when one biomarker is available is the binormal model. Extension of the model to accommodate multiple biomarkers has not been considered in this literature. Here, we consider a multivariate binormal framework for combining biomarkers using copula functions that leads to a natural multivariate extension of the binormal model. Estimation in this model will be done using rank-based procedures. We also discuss adjustment for covariates in this class of models and provide a simple …
Multiple Testing Methods For Chip-Chip High Density Oligonucleotide Array Data, Sunduz Keles, Mark J. Van Der Laan, Sandrine Dudoit, Simon E. Cawley
Multiple Testing Methods For Chip-Chip High Density Oligonucleotide Array Data, Sunduz Keles, Mark J. Van Der Laan, Sandrine Dudoit, Simon E. Cawley
U.C. Berkeley Division of Biostatistics Working Paper Series
Cawley et al. (2004) have recently mapped the locations of binding sites for three transcription factors along human chromosomes 21 and 22 using ChIP-Chip experiments. ChIP-Chip experiments are a new approach to the genome-wide identification of transcription factor binding sites and consist of chromatin (Ch) immunoprecipitation (IP) of transcription factor-bound genomic DNA followed by high density oligonucleotide hybridization (Chip) of the IP-enriched DNA. We investigate the ChIP-Chip data structure and propose methods for inferring the location of transcription factor binding sites from these data. The proposed methods involve testing for each probe whether it is part of a bound sequence …
Semiparametic Models And Estimation Procedures For Binormal Roc Curves With Multiple Biomarkers, Debashis Ghosh
Semiparametic Models And Estimation Procedures For Binormal Roc Curves With Multiple Biomarkers, Debashis Ghosh
The University of Michigan Department of Biostatistics Working Paper Series
In diagnostic medicine, there is great interest in developing strategies for combining biomarkers in order to optimize classification accuracy. A popular model that has been used for receiver operating characteristic (ROC) curve modelling when one biomarker is available is the binormal model. Extension of the model to accommodate multiple biomarkers has not been considered in this literature. Here, we consider a multivariate binormal framework for combining biomarkers using copula functions that leads to a natural multivariate extension of the binormal model. Estimation in this model will be done using rank-based procedures. We show that the Van der Waerden rank score …
Binary Isotonic Regression Procedures, With Application To Cancer Biomarkers, Debashis Ghosh, Moulinath Banerjee, Pinaki Biswas
Binary Isotonic Regression Procedures, With Application To Cancer Biomarkers, Debashis Ghosh, Moulinath Banerjee, Pinaki Biswas
The University of Michigan Department of Biostatistics Working Paper Series
There is a lot of interest in the development and characterization of new biomarkers for screening large populations for disease. In much of the literature on diagnostic testing, increased levels of a biomarker correlate with increased disease risk. However, parametric forms are typically used to associate these quantities. In this article, we specify a monotonic relationship between biomarker levels with disease risk. This leads to consideration of a nonparametric regression model for a single biomarker. Estimation results using isotonic regression-type estimators and asymptotic results are given. We also discuss confidence set estimation in this setting and propose three procedures for …
Evaluating Markers For Selecting A Patient's Treatment, Xiao Song, Margaret S. Pepe
Evaluating Markers For Selecting A Patient's Treatment, Xiao Song, Margaret S. Pepe
UW Biostatistics Working Paper Series
Selecting the best treatment for a patient's disease may be facilitated by evaluating clinical characteristics or biomarker measurements at diagnosis. We consider how to evaluate the potential of such measurements to impact on treatment selection algorithms. For example, magnetic resonance neurographic imaging is potentially useful for deciding whether a patient should be treated surgically for carpal tunnel syndrome or if he/she should receive less invasive conservative therapy. We propose a graphical display, the selection impact (SI) curve, that shows the population response rate as a function of treatment selection criteria based on the marker. The curve can be useful for …
Piecewise Constant Cross-Ratio Estimation For Association In Bivariate Survival Data With Application To Studying Markers Of Menopausal Transition, Bin Nan, Xihong Lin, Lynda D. Lisabet, Sioban Harlow
Piecewise Constant Cross-Ratio Estimation For Association In Bivariate Survival Data With Application To Studying Markers Of Menopausal Transition, Bin Nan, Xihong Lin, Lynda D. Lisabet, Sioban Harlow
The University of Michigan Department of Biostatistics Working Paper Series
A question of significant interest in female reproductive aging is to identify bleeding criteria for the menopausal transition. Although various bleeding criteria, or markers, have been proposed for the menopausal transition, their validity has not been adequately examined. The Tremin Trust data are collected from a long-term cohort study that followed a group of women throughout their whole reproductive life, and provide a unique opportunity for assessing the association between age at onset of a bleeding marker and age onset of menopause. Formal statistical analysis of this dependence is challenging give the fact that both the marker event and menopause …
Uncertainty And The Value Of Diagnostic Information With Application To Axillary Lymph Node Dissection In Breast Cancer, Giovanni Parmigiani
Uncertainty And The Value Of Diagnostic Information With Application To Axillary Lymph Node Dissection In Breast Cancer, Giovanni Parmigiani
Johns Hopkins University, Dept. of Biostatistics Working Papers
In clinical decision making, it is common to ask whether, and how much, a diagnostic procedure is contributing to subsequent treatment decisions. Statistically, quantification of the value of the information provided by a diagnostic procedure can be carried out using decision trees with multiple decision points, representing both the diagnostic test and the subsequent treatments that may depend on the test's results. This article investigates probabilistic sensitivity analysis approaches for exploring and communicating parameter uncertainty in such decision trees. Complexities arise because uncertainty about a model's inputs determines uncertainty about optimal decisions at all decision nodes of a tree. We …
Optimization Of Breast Cancer Screening Modalities, Yu Shen, Giovanni Parmigiani
Optimization Of Breast Cancer Screening Modalities, Yu Shen, Giovanni Parmigiani
Johns Hopkins University, Dept. of Biostatistics Working Papers
Mathematical models and decision analyses based on microsimulations have been shown to be useful in evaluating relative merits of various screening strategies in terms of cost and mortality reduction. Most investigations regarding the balance between mortality reduction and costs have focused on a single modality, mammography. A systematic evaluation of the relative expenses and projected benefit of combining clinical breast examination and mammography is not at present available. The purpose of this report is to provide methodologic details including assumptions and data used in the process of modeling for complex decision analyses, when searching for optimal breast cancer screening strategies …
A Varying-Coefficient Cox Model For The Effect Of Age At A Marker Event On Age At Menopause, Bin Nan, Xihong Lin, Lynda D. Lisabeth, Sioban D. Harlow
A Varying-Coefficient Cox Model For The Effect Of Age At A Marker Event On Age At Menopause, Bin Nan, Xihong Lin, Lynda D. Lisabeth, Sioban D. Harlow
The University of Michigan Department of Biostatistics Working Paper Series
. It is of recent interest in reproductive health research to investigate the validity of a marker event for the onset of menopausal transition and to estimate age at menopause using age at the marker event. We propose a varying coefficient Cox model to investigate the association between age at a marker event, denned as a specific bleeding pattern change, and age at menopause, where both events are subject to censoring and their association varies with age at the marker event. Estimation proceeds using the regression spline method. The proposed method is applied to the Tremin Trust Data to evaluate …
Adjusting For Non-Ignorable Verification Bias In Clinical Studies For Alzheimer’S Disease, Xiao-Hua Zhou, Pete Castelluccio
Adjusting For Non-Ignorable Verification Bias In Clinical Studies For Alzheimer’S Disease, Xiao-Hua Zhou, Pete Castelluccio
UW Biostatistics Working Paper Series
A common problem for comparing the relative accuracy of two screening tests for Alzheimer’s disease (D) in a two-stage design study is verification bias. If the verification bias can be assumed to be ignorable, Zhou and Higgs (2000) have proposed a maximum likelihood approach to compare the relative accuracy of screening tests in a two-stage design study. However, if the verification mechanism also depends on the unobserved disease status, the ignorable assumption does not hold. In this paper, we discuss how to use a profile likelihood approach to compare the relative accuracy of two screening tests for AD without assuming …
Semiparametric Receiver Operating Characteristic Analysis To Evaluate Biomarkers For Disease, Tianxi Cai, Margaret S. Pepe
Semiparametric Receiver Operating Characteristic Analysis To Evaluate Biomarkers For Disease, Tianxi Cai, Margaret S. Pepe
UW Biostatistics Working Paper Series
The receiver operating characteristic (ROC) curve is a popular method for characterizing the accuracy of diagnostic tests when test results are not binary. Various methodologies for estimating and comparing ROC curves have been developed. One approach, due to Pepe, uses a parametric regression model with the baseline function specified up to a finite-dimensional parameter. In this article we extend the regression models by allowing arbitrary nonparametric baseline functions. We also provide asymptotic distribution theory and procedures for making statistical inference. We illustrate our approach with dataset from a prostate cancer biomarker study. Simulation studies suggest that the extra flexibility inherent …