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Ross L. Prentice

Bio: Ross L. Prentice is an academic researcher from Fred Hutchinson Cancer Research Center. The author has contributed to research in topics: Breast cancer & Women's Health Initiative. The author has an hindex of 94, co-authored 407 publications receiving 33619 citations. Previous affiliations of Ross L. Prentice include Argonne National Laboratory & Radiation Effects Research Foundation.


Papers
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Journal ArticleDOI
Garnet L. Anderson1, S. Cummings1, L. S. Freedman1, C. Furberg1, Maureen M. Henderson1, Susan R. Johnson1, L. Kuller1, JoAnn E. Manson1, A. Oberman1, Ross L. Prentice1, Jacques E. Rossouw1, L. Finnegan1, R. Hiatt1, L. Pottern1, J. McGowan1, C. Clifford1, B. Caan1, V. Kipnis1, B. Ettinger1, S. Sidney1, G. Bailey1, Andrea Z. LaCroix1, Anne McTiernan1, Deborah J. Bowen1, C. Chen1, Barbara B. Cochrane1, Julie R. Hunt1, Alan R. Kristal1, Brian J. Lund1, Ruth E. Patterson1, Jeffrey L. Probstfield1, Lesley F. Tinker1, Nicole Urban1, Ching Yun Wang1, Emily White1, J. M. Kotchen1, S. Shumaker1, P. Rautaharju1, F. Rautaharju1, E. Stein1, P. Laskarzewski1, P. Steiner1, K. Sagar1, M. Nevitt1, M. Dockrell1, T. Fuerst1, John H. Himes1, M. Stevens1, F. Cammarata1, S. Lindenfelser1, Bruce M. Psaty1, D. Siscovick1, W. Longstreth1, S. Heckbert1, S. Wassertheil-Smoller1, W. Frishman1, Judy Wylie-Rosett1, D. Barad1, R. Freeman1, S. Miller1, Jennifer Hays1, R. Young1, C. Crowley1, M. A. DePoe1, G. Burke1, E. Paskett1, L. Wagenknecht1, R. Crouse1, L. Parsons1, T. Kotchen1, E. Braunwald1, J. Buring1, C. Hennekens1, J. M. Gaziano1, Annlouise R. Assaf1, R. C. Carleton1, M. Miller1, C. Wheeler1, A. Hume1, M. Pedersen1, O. Strickland1, M. Huber1, V. Porter1, Shirley A.A. Beresford1, V. Taylor1, N. Woods1, J. Hsia1, V. Barnabei1, M. Bovun1, Rowan T. Chlebowski1, R. Detrano1, A. Nelson1, J. Heiner1, S. Pushkin1, B. Valanis1, V. Stevens1, E. Whitlock1, N. Karanja1, A. Clark1 
TL;DR: The rationale for the interventions being studied in each of the CT components and for the inclusion of the OS component is described, including a brief description of the scientific and logistic complexity of the WHI.

2,310 citations

Journal ArticleDOI
TL;DR: LDpred is introduced, a method that infers the posterior mean effect size of each marker by using a prior on effect sizes and LD information from an external reference panel, and outperforms the approach of pruning followed by thresholding, particularly at large sample sizes.
Abstract: Polygenic risk scores have shown great promise in predicting complex disease risk and will become more accurate as training sample sizes increase. The standard approach for calculating risk scores involves linkage disequilibrium (LD)-based marker pruning and applying a p value threshold to association statistics, but this discards information and can reduce predictive accuracy. We introduce LDpred, a method that infers the posterior mean effect size of each marker by using a prior on effect sizes and LD information from an external reference panel. Theory and simulations show that LDpred outperforms the approach of pruning followed by thresholding, particularly at large sample sizes. Accordingly, predicted R(2) increased from 20.1% to 25.3% in a large schizophrenia dataset and from 9.8% to 12.0% in a large multiple sclerosis dataset. A similar relative improvement in accuracy was observed for three additional large disease datasets and for non-European schizophrenia samples. The advantage of LDpred over existing methods will grow as sample sizes increase.

1,088 citations

Journal ArticleDOI
TL;DR: In this article, Andersen and Gill (hereafter AG) present a stimulating development of asymptotic distribution theory for the Cox regression model with time-dependent covariates, which involves such conditions as $\sigma$-algebra right continuity and predictable, locally bounded, covariate processes.
Abstract: In this issue Andersen and Gill (hereafter AG) present a stimulating development of asymptotic distribution theory for the Cox regression model with time-dependent covariates. They use a counting process formulation for the failure time data and martingale covergence results. This approach involves such conditions as $\sigma$-algebra right continuity and predictable, locally bounded, covariate processes. In this commentary we consider the implications of such assumptions for likelihood factorization and covariate modeling. In particular, it is noted that the partial likelihood function modeled by AG cannot, in general, involve covariate measurements at the random failure times. Some related work by the authors on a partial likelihood function that may involve covariate values at the random failure times is briefly discussed. Assumptions under which the intensity process modeled by AG has a standard "hazard" function interpretation are described and some generalizations of the AG results are mentioned.

1,031 citations

Journal ArticleDOI
02 Nov 2017-Nature
TL;DR: A genome-wide association study of breast cancer in 122,977 cases and 105,974 controls of European ancestry and 14,068 cases and 13,104 controls of East Asian ancestry finds that heritability of Breast cancer due to all single-nucleotide polymorphisms in regulatory features was 2–5-fold enriched relative to the genome- wide average.
Abstract: Breast cancer risk is influenced by rare coding variants in susceptibility genes, such as BRCA1, and many common, mostly non-coding variants. However, much of the genetic contribution to breast cancer risk remains unknown. Here we report the results of a genome-wide association study of breast cancer in 122,977 cases and 105,974 controls of European ancestry and 14,068 cases and 13,104 controls of East Asian ancestry. We identified 65 new loci that are associated with overall breast cancer risk at P < 5 × 10-8. The majority of credible risk single-nucleotide polymorphisms in these loci fall in distal regulatory elements, and by integrating in silico data to predict target genes in breast cells at each locus, we demonstrate a strong overlap between candidate target genes and somatic driver genes in breast tumours. We also find that heritability of breast cancer due to all single-nucleotide polymorphisms in regulatory features was 2-5-fold enriched relative to the genome-wide average, with strong enrichment for particular transcription factor binding sites. These results provide further insight into genetic susceptibility to breast cancer and will improve the use of genetic risk scores for individualized screening and prevention.

1,014 citations

Journal ArticleDOI
TL;DR: It is argued that binary response models that condition on some or all binary responses in a given "block" are useful for studying certain types of dependencies, but not for the estimation of marginal response probabilities or pairwise correlations.
Abstract: Regression methods are considered for the analysis of correlated binary data when each binary observation may have its own covariates. It is argued that binary response models that condition on some or all binary responses in a given "block" are useful for studying certain types of dependencies, but not for the estimation of marginal response probabilities or pairwise correlations. Fully parametric approaches to these latter problems appear to be unduly complicated except in such special cases as the analysis of paired binary data. Hence, a generalized estimating equation approach is advocated for inference on response probabilities and correlations. Illustrations involving both small and large block sizes are provided.

852 citations


Cited by
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TL;DR: A substantial portion of cancer cases and deaths could be prevented by broadly applying effective prevention measures, such as tobacco control, vaccination, and the use of early detection tests.
Abstract: Cancer constitutes an enormous burden on society in more and less economically developed countries alike. The occurrence of cancer is increasing because of the growth and aging of the population, as well as an increasing prevalence of established risk factors such as smoking, overweight, physical inactivity, and changing reproductive patterns associated with urbanization and economic development. Based on GLOBOCAN estimates, about 14.1 million new cancer cases and 8.2 million deaths occurred in 2012 worldwide. Over the years, the burden has shifted to less developed countries, which currently account for about 57% of cases and 65% of cancer deaths worldwide. Lung cancer is the leading cause of cancer death among males in both more and less developed countries, and has surpassed breast cancer as the leading cause of cancer death among females in more developed countries; breast cancer remains the leading cause of cancer death among females in less developed countries. Other leading causes of cancer death in more developed countries include colorectal cancer among males and females and prostate cancer among males. In less developed countries, liver and stomach cancer among males and cervical cancer among females are also leading causes of cancer death. Although incidence rates for all cancers combined are nearly twice as high in more developed than in less developed countries in both males and females, mortality rates are only 8% to 15% higher in more developed countries. This disparity reflects regional differences in the mix of cancers, which is affected by risk factors and detection practices, and/or the availability of treatment. Risk factors associated with the leading causes of cancer death include tobacco use (lung, colorectal, stomach, and liver cancer), overweight/obesity and physical inactivity (breast and colorectal cancer), and infection (liver, stomach, and cervical cancer). A substantial portion of cancer cases and deaths could be prevented by broadly applying effective prevention measures, such as tobacco control, vaccination, and the use of early detection tests.

23,203 citations

Journal ArticleDOI
TL;DR: In this article, an extension of generalized linear models to the analysis of longitudinal data is proposed, which gives consistent estimates of the regression parameters and of their variance under mild assumptions about the time dependence.
Abstract: SUMMARY This paper proposes an extension of generalized linear models to the analysis of longitudinal data. We introduce a class of estimating equations that give consistent estimates of the regression parameters and of their variance under mild assumptions about the time dependence. The estimating equations are derived without specifying the joint distribution of a subject's observations yet they reduce to the score equations for multivariate Gaussian outcomes. Asymptotic theory is presented for the general class of estimators. Specific cases in which we assume independence, m-dependence and exchangeable correlation structures from each subject are discussed. Efficiency of the proposed estimators in two simple situations is considered. The approach is closely related to quasi-likelih ood. Some key ironh: Estimating equation; Generalized linear model; Longitudinal data; Quasi-likelihood; Repeated measures.

17,111 citations

Journal ArticleDOI
TL;DR: Overall cancer incidence trends are stable in women, but declining by 3.1% per year in men, much of which is because of recent rapid declines in prostate cancer diagnoses, and brain cancer has surpassed leukemia as the leading cause of cancer death among children and adolescents.
Abstract: Each year, the American Cancer Society estimates the numbers of new cancer cases and deaths that will occur in the United States in the current year and compiles the most recent data on cancer incidence, mortality, and survival. Incidence data were collected by the National Cancer Institute (Surveillance, Epidemiology, and End Results [SEER] Program), the Centers for Disease Control and Prevention (National Program of Cancer Registries), and the North American Association of Central Cancer Registries. Mortality data were collected by the National Center for Health Statistics. In 2016, 1,685,210 new cancer cases and 595,690 cancer deaths are projected to occur in the United States. Overall cancer incidence trends (13 oldest SEER registries) are stable in women, but declining by 3.1% per year in men (from 2009-2012), much of which is because of recent rapid declines in prostate cancer diagnoses. The cancer death rate has dropped by 23% since 1991, translating to more than 1.7 million deaths averted through 2012. Despite this progress, death rates are increasing for cancers of the liver, pancreas, and uterine corpus, and cancer is now the leading cause of death in 21 states, primarily due to exceptionally large reductions in death from heart disease. Among children and adolescents (aged birth-19 years), brain cancer has surpassed leukemia as the leading cause of cancer death because of the dramatic therapeutic advances against leukemia. Accelerating progress against cancer requires both increased national investment in cancer research and the application of existing cancer control knowledge across all segments of the population.

14,664 citations

Journal ArticleDOI
17 Jul 2002-JAMA
TL;DR: Overall health risks exceeded benefits from use of combined estrogen plus progestin for an average 5.2-year follow-up among healthy postmenopausal US women, and the results indicate that this regimen should not be initiated or continued for primary prevention of CHD.
Abstract: Context Despite decades of accumulated observational evidence, the balance of risks and benefits for hormone use in healthy postmenopausal women remains uncertain Objective To assess the major health benefits and risks of the most commonly used combined hormone preparation in the United States Design Estrogen plus progestin component of the Women's Health Initiative, a randomized controlled primary prevention trial (planned duration, 85 years) in which 16608 postmenopausal women aged 50-79 years with an intact uterus at baseline were recruited by 40 US clinical centers in 1993-1998 Interventions Participants received conjugated equine estrogens, 0625 mg/d, plus medroxyprogesterone acetate, 25 mg/d, in 1 tablet (n = 8506) or placebo (n = 8102) Main outcomes measures The primary outcome was coronary heart disease (CHD) (nonfatal myocardial infarction and CHD death), with invasive breast cancer as the primary adverse outcome A global index summarizing the balance of risks and benefits included the 2 primary outcomes plus stroke, pulmonary embolism (PE), endometrial cancer, colorectal cancer, hip fracture, and death due to other causes Results On May 31, 2002, after a mean of 52 years of follow-up, the data and safety monitoring board recommended stopping the trial of estrogen plus progestin vs placebo because the test statistic for invasive breast cancer exceeded the stopping boundary for this adverse effect and the global index statistic supported risks exceeding benefits This report includes data on the major clinical outcomes through April 30, 2002 Estimated hazard ratios (HRs) (nominal 95% confidence intervals [CIs]) were as follows: CHD, 129 (102-163) with 286 cases; breast cancer, 126 (100-159) with 290 cases; stroke, 141 (107-185) with 212 cases; PE, 213 (139-325) with 101 cases; colorectal cancer, 063 (043-092) with 112 cases; endometrial cancer, 083 (047-147) with 47 cases; hip fracture, 066 (045-098) with 106 cases; and death due to other causes, 092 (074-114) with 331 cases Corresponding HRs (nominal 95% CIs) for composite outcomes were 122 (109-136) for total cardiovascular disease (arterial and venous disease), 103 (090-117) for total cancer, 076 (069-085) for combined fractures, 098 (082-118) for total mortality, and 115 (103-128) for the global index Absolute excess risks per 10 000 person-years attributable to estrogen plus progestin were 7 more CHD events, 8 more strokes, 8 more PEs, and 8 more invasive breast cancers, while absolute risk reductions per 10 000 person-years were 6 fewer colorectal cancers and 5 fewer hip fractures The absolute excess risk of events included in the global index was 19 per 10 000 person-years Conclusions Overall health risks exceeded benefits from use of combined estrogen plus progestin for an average 52-year follow-up among healthy postmenopausal US women All-cause mortality was not affected during the trial The risk-benefit profile found in this trial is not consistent with the requirements for a viable intervention for primary prevention of chronic diseases, and the results indicate that this regimen should not be initiated or continued for primary prevention of CHD

14,646 citations

Journal ArticleDOI
08 Oct 2009-Nature
TL;DR: This paper examined potential sources of missing heritability and proposed research strategies, including and extending beyond current genome-wide association approaches, to illuminate the genetics of complex diseases and enhance its potential to enable effective disease prevention or treatment.
Abstract: Genome-wide association studies have identified hundreds of genetic variants associated with complex human diseases and traits, and have provided valuable insights into their genetic architecture. Most variants identified so far confer relatively small increments in risk, and explain only a small proportion of familial clustering, leading many to question how the remaining, 'missing' heritability can be explained. Here we examine potential sources of missing heritability and propose research strategies, including and extending beyond current genome-wide association approaches, to illuminate the genetics of complex diseases and enhance its potential to enable effective disease prevention or treatment.

7,797 citations