Holly Janes

Summary

Affiliation: Fred Hutchinson Cancer Research Center
Country: USA

Publications

  1. pmc On quantifying the magnitude of confounding
    Holly Janes
    Vaccine and Infectious Disease Institute and Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, 1100 Fairview Avenue North M2 C200, Seattle, WA 98109, USA
    Biostatistics 11:572-82. 2010
  2. pmc Adjusting for covariate effects on classification accuracy using the covariate-adjusted receiver operating characteristic curve
    Holly Janes
    Division of Public Health Sciences, Fred Hutchinson Cancer, Research Center, 1100 Fairview Avenue North, Seattle, Washington 98109, U S A
    Biometrika 96:371-382. 2009
  3. doi request reprint Statistical analysis of air pollution panel studies: an illustration
    Holly Janes
    Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, University of Washington, Seattle, USA
    Ann Epidemiol 18:792-802. 2008
  4. pmc Assessing the value of risk predictions by using risk stratification tables
    Holly Janes
    Fred Hutchinson Cancer Research Center, Seattle, Washington 98109, USA
    Ann Intern Med 149:751-60. 2008
  5. doi request reprint Adjusting for covariates in studies of diagnostic, screening, or prognostic markers: an old concept in a new setting
    Holly Janes
    Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, WA 98109, USA
    Am J Epidemiol 168:89-97. 2008
  6. pmc Net risk reclassification p values: valid or misleading?
    Margaret S Pepe
    Affiliations of authors Public Health Sciences Division, Fred Hutchinson Cancer Research Center, Seattle, WA MSP, HJ, CIL Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Research Center, Seattle, WA HJ
    J Natl Cancer Inst 106:dju041. 2014
  7. ncbi request reprint Case-crossover analyses of air pollution exposure data: referent selection strategies and their implications for bias
    Holly Janes
    Department of Biostatistics, University of Washington, Seattle, Washington 98195, USA
    Epidemiology 16:717-26. 2005
  8. ncbi request reprint Identifying target populations for screening or not screening using logic regression
    Holly Janes
    Department of Biostatistics, University of Washington, Seattle, WA 98195, USA
    Stat Med 24:1321-38. 2005
  9. ncbi request reprint Overlap bias in the case-crossover design, with application to air pollution exposures
    Holly Janes
    Department of Biostatistics, University of Washington, Seattle, WA 98195, USA
    Stat Med 24:285-300. 2005
  10. pmc Pivotal evaluation of the accuracy of a biomarker used for classification or prediction: standards for study design
    Margaret S Pepe
    Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, WA 98109 1024, USA
    J Natl Cancer Inst 100:1432-8. 2008

Detail Information

Publications36

  1. pmc On quantifying the magnitude of confounding
    Holly Janes
    Vaccine and Infectious Disease Institute and Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, 1100 Fairview Avenue North M2 C200, Seattle, WA 98109, USA
    Biostatistics 11:572-82. 2010
    ..In settings with a sizable nonlinearity effect, the corrected estimate of confounding has improved performance...
  2. pmc Adjusting for covariate effects on classification accuracy using the covariate-adjusted receiver operating characteristic curve
    Holly Janes
    Division of Public Health Sciences, Fred Hutchinson Cancer, Research Center, 1100 Fairview Avenue North, Seattle, Washington 98109, U S A
    Biometrika 96:371-382. 2009
    ..For illustration we characterize the age-adjusted discriminatory accuracy of prostate-specific antigen as a biomarker for prostate cancer...
  3. doi request reprint Statistical analysis of air pollution panel studies: an illustration
    Holly Janes
    Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, University of Washington, Seattle, USA
    Ann Epidemiol 18:792-802. 2008
    ..Standard statistical methods are available for analyzing longitudinal data, but the literature reveals that these methods are poorly understood by practitioners...
  4. pmc Assessing the value of risk predictions by using risk stratification tables
    Holly Janes
    Fred Hutchinson Cancer Research Center, Seattle, Washington 98109, USA
    Ann Intern Med 149:751-60. 2008
    ....
  5. doi request reprint Adjusting for covariates in studies of diagnostic, screening, or prognostic markers: an old concept in a new setting
    Holly Janes
    Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, WA 98109, USA
    Am J Epidemiol 168:89-97. 2008
    ..They draw analogies and contrasts throughout with studies of association...
  6. pmc Net risk reclassification p values: valid or misleading?
    Margaret S Pepe
    Affiliations of authors Public Health Sciences Division, Fred Hutchinson Cancer Research Center, Seattle, WA MSP, HJ, CIL Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Research Center, Seattle, WA HJ
    J Natl Cancer Inst 106:dju041. 2014
    ..Although proposed only 5 years ago, the NRI has gained enormous traction in the risk prediction literature. Concerns have recently been raised about the statistical validity of the NRI...
  7. ncbi request reprint Case-crossover analyses of air pollution exposure data: referent selection strategies and their implications for bias
    Holly Janes
    Department of Biostatistics, University of Washington, Seattle, Washington 98195, USA
    Epidemiology 16:717-26. 2005
    ....
  8. ncbi request reprint Identifying target populations for screening or not screening using logic regression
    Holly Janes
    Department of Biostatistics, University of Washington, Seattle, WA 98195, USA
    Stat Med 24:1321-38. 2005
    ..However, we believe that our novel statistical approach could be useful in settings where risk factors do discriminate between cases and controls, and illustrate this with a simulated data set...
  9. ncbi request reprint Overlap bias in the case-crossover design, with application to air pollution exposures
    Holly Janes
    Department of Biostatistics, University of Washington, Seattle, WA 98195, USA
    Stat Med 24:285-300. 2005
    ..We give a derivation of overlap bias, explore its magnitude, and consider how the bias depends on properties of the exposure series. We conclude that the bias is usually small, though highly unpredictable, and easily avoided...
  10. pmc Pivotal evaluation of the accuracy of a biomarker used for classification or prediction: standards for study design
    Margaret S Pepe
    Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, WA 98109 1024, USA
    J Natl Cancer Inst 100:1432-8. 2008
    ..Common biases that pervade the biomarker research literature would be eliminated if these rigorous standards were followed...
  11. pmc Effect of rAd5-Vector HIV-1 Preventive Vaccines on HIV-1 Acquisition: A Participant-Level Meta-Analysis of Randomized Trials
    Yunda Huang
    Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Research Center, Seattle, Washington, United States of America
    PLoS ONE 10:e0136626. 2015
    ..Rigorous meta-analysis can provide crucial information to advise the future utility of rAd5-vector vaccines...
  12. pmc Selection of HIV vaccine candidates for concurrent testing in an efficacy trial
    Ying Huang
    Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Research Center, Seattle, WA, United States Electronic address
    Curr Opin Virol 17:57-65. 2016
    ..We illustrate the selection approaches using data from HIV-1 vaccine trials. ..
  13. pmc Net reclassification indices for evaluating risk prediction instruments: a critical review
    Kathleen F Kerr
    From the aDepartment of Biostatistics, University of Washington, Seattle, WA bFred Hutchinson Cancer Research Center, University of Washington, Seattle, WA and cCardiovascular Health Research Unit, Departments of Medicine, Epidemiology, and Health Services, University of Washington, Group Health Research Institute, Group Health Cooperative, Seattle, WA
    Epidemiology 25:114-21. 2014
    ..The preferred single-number summary of the prediction increment is the improvement in net benefit. ..
  14. pmc In pursuit of an HIV vaccine: designing efficacy trials in the context of partially effective nonvaccine prevention modalities
    Holly Janes
    1 Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Research Center, Seattle, Washington
    AIDS Res Hum Retroviruses 29:1513-23. 2013
    ....
  15. pmc New clinical trial designs for HIV vaccine evaluation
    Zoe Moodie
    Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Research Center, University of Washington, Seattle, WA 98109, USA
    Curr Opin HIV AIDS 8:437-42. 2013
    ....
  16. pmc Measuring the performance of markers for guiding treatment decisions
    Holly Janes
    Fred Hutchinson Cancer Research Center, Seattle, Washington 98109, USA
    Ann Intern Med 154:253-9. 2011
    ..Randomized therapeutic clinical trials, in which entry criteria and treatment regimens are not restricted by the marker, are also proposed as the basis for constructing the curves and evaluating and comparing markers...
  17. ncbi request reprint Limitations of the odds ratio in gauging the performance of a diagnostic, prognostic, or screening marker
    Margaret Sullivan Pepe
    Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, WA, USA
    Am J Epidemiol 159:882-90. 2004
    ..In addition, the serious pitfalls of using more traditional methods based on parameters in logistic regression models are illustrated...
  18. pmc Estimation and Comparison of Receiver Operating Characteristic Curves
    Margaret Pepe
    Fred Hutchinson Cancer Research Center, Seattle, Washington, USA
    Stata J 9:1. 2009
    ..We use a unified framework by representing the ROC curve as the distribution of the marker in cases after standardizing it to the control reference distribution...
  19. pmc Assessing the Clinical Impact of Risk Prediction Models With Decision Curves: Guidance for Correct Interpretation and Appropriate Use
    Kathleen F Kerr
    Kathleen F Kerr and Kehao Zhu, University of Washington and Marshall D Brown and Holly Janes, Fred Hutchinson Cancer Research Center, Seattle, WA
    J Clin Oncol 34:2534-40. 2016
    ..As a companion to this article, we released an R software package called DecisionCurve for making decision curves and related graphics. ..
  20. ncbi request reprint Statistical methods for down-selection of treatment regimens based on multiple endpoints, with application to HIV vaccine trials
    Ying Huang
    Biostatistics, Bioinformatics, and Epidemiology Program, Vaccine and Infectious Diseases Division, Fred Hutchinson Cancer Research Center, 1100 Fairview Ave N, Seattle, WA 98109, USA and Department of Biostatistics, University of Washington, 1705 NE Pacific Street, Seattle, WA 98195, USA
    Biostatistics . 2016
    ..We demonstrate the application of the proposed methods through the comparison of immune responses between several HIV vaccine regimens. The methods are applicable to general down-selection applications in clinical trials...
  21. pmc HIV-1 infections with multiple founders are associated with higher viral loads than infections with single founders
    Holly Janes
    Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Research Center, Seattle, Washington, USA
    Nat Med 21:1139-41. 2015
    ....
  22. pmc Use of placebos in Phase 1 preventive HIV vaccine clinical trials
    Yunda Huang
    Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Research Center, Seattle, WA, USA Public Health Sciences Division, Fred Hutchinson Cancer Research Center, Seattle, WA, USA Electronic address
    Vaccine 33:749-52. 2015
    ..In some settings, however, placebo recipients are less important because other data sources and tools are available to achieve the study objectives. ..
  23. pmc A framework for evaluating markers used to select patient treatment
    Holly Janes
    Divisions of Vaccine and Infectious Disease and Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, WA HJ, MSP, yh
    Med Decis Making 34:159-67. 2014
    ..In doing so, we review the existing approaches, clarify their underlying assumptions, and facilitate the evaluation of markers under less restrictive assumptions. ..
  24. pmc Assessing treatment-selection markers using a potential outcomes framework
    Ying Huang
    Fred Hutchinson Cancer Research Center, Seattle, Washington, 98109, USA
    Biometrics 68:687-96. 2012
    ..Finally, we illustrate the methods using an HIV vaccine trial where we explore the value of the level of preexisting immunity to adenovirus serotype 5 for predicting a vaccine-induced increase in the risk of HIV acquisition...
  25. ncbi request reprint Insights into latent class analysis of diagnostic test performance
    Margaret Sullivan Pepe
    Department of Biostatistics, University of Washington and Fred Hutchinson Cancer Research Center, Seattle, WA 98109, USA
    Biostatistics 8:474-84. 2007
    ..Such justification must be based in part on a clear clinical definition of disease and biological knowledge about mechanisms giving rise to test results...
  26. pmc The Fundamental Difficulty With Evaluating the Accuracy of Biomarkers for Guiding Treatment
    Holly Janes
    Divisions of Vaccine and Infectious Disease and Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, Washington HJ, MSP Department of Biostatistics, University of Washington, Seattle, Washington HJ, MSP, PJH Biometric Research Branch, Division of Cancer Treatment and Diagnosis, National Cancer Institute, National Institutes of Health, Rockville, Maryland LMM Department of Health Science Research, Mayo Clinic, Rochester, Minnesota DJS
    J Natl Cancer Inst 107:. 2015
    ..Ideally these entities are estimated from a randomized trial comparing the experimental intervention with standard of care. ..
  27. pmc Designing a study to evaluate the benefit of a biomarker for selecting patient treatment
    Holly Janes
    Fred Hutchinson Cancer Research Center, Seattle, Washington, U S A
    Stat Med 34:3503-15. 2015
    ..We also find that retrospectively selecting a case-control subset of subjects for marker evaluation can lead to large efficiency gains, especially if cases and controls are matched on treatment assignment...
  28. pmc Combining biomarkers to optimize patient treatment recommendations
    Chaeryon Kang
    Vaccine and Infectious Disease Division and Public Health Sciences Division, Fred Hutchinson Cancer Research Center, Seattle, Washington 98109, U S A
    Biometrics 70:695-707. 2014
    ..Application of the boosting approach to the breast cancer data, using scaled versions of the original markers, produces marker combinations that may have improved performance for treatment selection...
  29. pmc Characterizing expected benefits of biomarkers in treatment selection
    Ying Huang
    Fred Hutchinson Cancer Research Center, 1100 Fairview Avenue N, Seattle WA, 98109, USA
    Biostatistics 16:383-99. 2015
    ..We illustrate our methods using the Diabetes Control and Complications Trial where we evaluate the expected benefit of baseline hemoglobin A1C in selecting diabetes treatment. ..
  30. ncbi request reprint Trends in air pollution and mortality: an approach to the assessment of unmeasured confounding
    Holly Janes
    Department of Biostatistics, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland 21205, USA
    Epidemiology 18:416-23. 2007
    ..5 and mortality at the local scale. If the association at the national scale is set aside, there is little evidence of an association between 12-month exposure to PM2.5 and mortality...
  31. pmc Cox models for ecologic time-series data?
    Thomas Lumley
    Environ Health Perspect 114:A690-1; author reply A691. 2006
  32. ncbi request reprint Matching in studies of classification accuracy: implications for analysis, efficiency, and assessment of incremental value
    Holly Janes
    Department of Biostatistics, Johns Hopkins Bloomberg School of Public Health, 615 N Wolfe St, Baltimore, MD 21205, USA
    Biometrics 64:1-9. 2008
    ..However, we also show that matching greatly complicates estimation of the incremental value of the marker. We recommend that matching be carefully considered in the context of these findings...
  33. ncbi request reprint The optimal ratio of cases to controls for estimating the classification accuracy of a biomarker
    Holly Janes
    Department of Biostatistics, Johns Hopkins Bloomberg School of Public Health, 615 North Wolfe Street, Baltimore, MD 21205, USA
    Biostatistics 7:456-68. 2006
    ..Our methods are applied to a study of a new marker for adenocarcinoma in patients with Barrett's esophagus...
  34. ncbi request reprint Do subject characteristics modify the effects of particulate air pollution on daily mortality among the elderly?
    Holly Janes
    J Occup Environ Med 47:543; author reply 543-5. 2005
  35. doi request reprint Fine particulate matter and mortality: a comparison of the six cities and American Cancer Society cohorts with a medicare cohort
    Sorina E Eftim
    Department of Biostatistics, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD 21205, USA
    Epidemiology 19:209-16. 2008
    ..5) on mortality. Using Medicare data, we assessed the association of PM2.5 with mortality for the same locations included in these studies...
  36. ncbi request reprint Letter by Pepe et al regarding article, "Use and misuse of the receiver operating characteristic curve in risk prediction"
    Margaret S Pepe
    Circulation 116:e132; author reply e134. 2007