|Grant Number:||2P01CA134294-06 Interpret this number|
|Primary Investigator:||Lin, Xihong|
|Organization:||Harvard School Of Public Health|
|Project Title:||Statistical Informatics for Cancer Research|
This renewal application proposes to carry out a Program Project of statistical methods research to address gaps and barriers arising in the analysis of large and complex data from observational studies in cancer research. The ultimate goal of the Program is to use rich data sources to develop effective strategies for reducing cancer burden in the U.S. and improving longevity and quality of life. This Program Project comprises three research projects and two cores. The three integrated projects jointly address the statistical needs for three research priority areas identified by the Division of Cancer Contro and Population Science of National Cancer Institute: Health Disparities; Comparative Effectiveness Research; and Public Health Genomics. In Project 1, we will develop statistical methods to overcome common data limitations for the investigation of social and racial disparities spanning the cancer continuum. We will analyze data from the SEER database that is linked with data from the National Longitudinal Mortality Survey (NLMS). In Project 2, we will develop methods for comparative effectiveness research (CER) in cancer using large observational data. We will use the SEER-Medicare data and the CaPSURE cohort to emulate complex randomized trials to compare the effectiveness of personalized strategies for cancer diagnosis and dynamic strategies for cancer treatment. In Project 3, we will develop statistical methods for analysis of next generation sequencing data in genetic cancer epidemiological studies. The proposed research in Project 3 is motivated by and applied to the Harvard lung cancer and breast cancer exome and targeted sequencing studies as well as the affiliated Genome-Wide Association Studies. The Administrative Core will coordinate the overall scientific direction and programmatic activities of the Program, which will include regular P01 meetings, seminars, the annual retreat, the external advisory committee meeting, short courses, a visitor program, dissemination of research results. The Statistical Computing Core will allow access to Harvard largest high performance computing cluster, perform data management, and ensure the development and dissemination of open access, high quality software. The Program PIs, Professors Xihong Lin and Francesca Dominici, are renowned biostatisticians with strong track records of methodological and collaborative research and academic administration.
Bayesian Semi-parametric Analysis of Semi-competing Risks Data: Investigating Hospital Readmission after a Pancreatic Cancer Diagnosis.
Authors: Lee KH, Haneuse S, Schrag D, Dominici F
Source: J R Stat Soc Ser C Appl Stat, 2015 Feb 1;64(2), p. 253-273.
Accounting for uncertainty in confounder and effect modifier selection when estimating average causal effects in generalized linear models.
Authors: Wang C, Dominici F, Parmigiani G, Zigler CM
Source: Biometrics, 2015 Apr 20;null, p. null.
EPub date: 2015 Apr 20.
Immediate versus deferred initiation of androgen deprivation therapy in prostate cancer patients with PSA-only relapse. An observational follow-up study.
Authors: Garcia-Albeniz X, Chan JM, Paciorek A, Logan RW, Kenfield SA, Cooperberg MR, Carroll PR, Hernán MA
Source: Eur J Cancer, 2015 May;51(7), p. 817-24.
EPub date: 2015 Mar 17.
Reproductive justice and the pace of change: socioeconomic trends in US infant death rates by legal status of abortion, 1960-1980.
Authors: Krieger N, Gruskin S, Singh N, Kiang MV, Chen JT, Waterman PD, Gottlieb J, Beckfield J, Coull BA
Source: Am J Public Health, 2015 Apr;105(4), p. 680-2.
EPub date: 2015 Feb 25.
Alternative decompositions for attributing effects to interactions.
Authors: VanderWeele TJ, Tchetgen Tchetgen EJ
Source: Epidemiology, 2015 May;26(3), p. e32-4.
SAS macro for causal mediation analysis with survival data.
Authors: Valeri L, VanderWeele TJ
Source: Epidemiology, 2015 Mar;26(2), p. e23-4.
Think globally, act globally: An epidemiologist's perspective on instrumental variable estimation.
Authors: Swanson SA, Hernán MA
Source: Stat Sci, 2014 Aug;29(3), p. 371-374.
Associations between long-term exposure to chemical constituents of fine particulate matter (PM2.5) and mortality in Medicare enrollees in the eastern United States.
Authors: Chung Y, Dominici F, Wang Y, Coull BA, Bell ML
Source: Environ Health Perspect, 2015 May;123(5), p. 467-74.
EPub date: 2015 Jan 6.
Cause-specific risk of hospital admission related to extreme heat in older adults.
Authors: Bobb JF, Obermeyer Z, Wang Y, Dominici F
Source: JAMA, 2014 Dec 24-31;312(24), p. 2659-67.
Short-term airborne particulate matter exposure alters the epigenetic landscape of human genes associated with the mitogen-activated protein kinase network: a cross-sectional study.
Authors: Carmona JJ, Sofer T, Hutchinson J, Cantone L, Coull B, Maity A, Vokonas P, Lin X, Schwartz J, Baccarelli AA
Source: Environ Health, 2014 Nov 13;13, p. 94.
EPub date: 2014 Nov 13.
Association between the Medicare hospice benefit and health care utilization and costs for patients with poor-prognosis cancer.
Authors: Obermeyer Z, Makar M, Abujaber S, Dominici F, Block S, Cutler DM
Source: JAMA, 2014 Nov 12;312(18), p. 1888-96.
Why post-progression survival and post-relapse survival are not appropriate measures of efficacy in cancer randomized clinical trials.
Authors: García-Albéniz X, Maurel J, Hernán MA
Source: Int J Cancer, 2015 May 15;136(10), p. 2444-7.
EPub date: 2014 Nov 3.
Learning how to improve healthcare delivery: the Swedish Quality Registers.
Authors: Adami HO, Hernán MA
Source: J Intern Med, 2015 Jan;277(1), p. 87-9.
EPub date: 2014 Nov 24.
On the analysis of hybrid designs that combine group- and individual-level data.
Authors: Smoot E, Haneuse S
Source: Biometrics, 2015 Mar;71(1), p. 227-36.
EPub date: 2014 Sep 22.
Evaluation of the duplication of staging CT scans for localized colon cancer in a Medicare population.
Authors: García-Albéniz X, Logan RW, Schrag D, Hernán MA
Source: Med Care, 2014 Nov;52(11), p. 963-8.
Mediation analysis when a continuous mediator is measured with error and the outcome follows a generalized linear model.
Authors: Valeri L, Lin X, VanderWeele TJ
Source: Stat Med, 2014 Dec 10;33(28), p. 4875-90.
EPub date: 2014 Sep 14.
Sparse kernel machine regression for ordinal outcomes.
Authors: Shen Y, Liao KP, Cai T
Source: Biometrics, 2015 Mar;71(1), p. 63-70.
EPub date: 2014 Sep 5.
Effect of flexible sigmoidoscopy screening on colorectal cancer incidence and mortality: a randomized clinical trial.
Authors: Holme Ř, Lřberg M, Kalager M, Bretthauer M, Hernán MA, Aas E, Eide TJ, Skovlund E, Schneede J, Tveit KM, Hoff G
Source: JAMA, 2014 Aug 13;312(6), p. 606-15.
Improving the power of genetic association tests with imperfect phenotype derived from electronic medical records.
Authors: Sinnott JA, Dai W, Liao KP, Shaw SY, Ananthakrishnan AN, Gainer VS, Karlson EW, Churchill S, Szolovits P, Murphy S, Kohane I, Plenge R, Cai T
Source: Hum Genet, 2014 Nov;133(11), p. 1369-82.
EPub date: 2014 Jul 26.
Attributing effects to interactions.
Authors: VanderWeele TJ, Tchetgen Tchetgen EJ
Source: Epidemiology, 2014 Sep;25(5), p. 711-22.
A unification of mediation and interaction: a 4-way decomposition.
Authors: VanderWeele TJ
Source: Epidemiology, 2014 Sep;25(5), p. 749-61.
Rare-variant association analysis: study designs and statistical tests.
Authors: Lee S, Abecasis GR, Boehnke M, Lin X
Source: Am J Hum Genet, 2014 Jul 3;95(1), p. 5-23.