Literature DB >> 23462919

Cultivating cohort studies for observational translational research.

David F Ransohoff1.   

Abstract

BACKGROUND: "Discovery" research about molecular markers for diagnosis, prognosis, or prediction of response to therapy has frequently produced results that were not reproducible in subsequent studies. What are the reasons, and can observational cohorts be cultivated to provide strong and reliable answers to those questions? Experimental
METHODS: Selected examples are used to illustrate: (i) what features of research design provide strength and reliability in observational studies about markers of diagnosis, prognosis, and response to therapy? (ii) How can those design features be cultivated in existing observational cohorts, for example, within randomized controlled clinical trial (RCT), other existing observational research studies, or practice settings like health maintenance organization (HMOs)?
RESULTS: Examples include a study of RNA expression profiles of tumor tissue to predict prognosis of breast cancer, a study of serum proteomics profiles to diagnose ovarian cancer, and a study of stool-based DNA assays to screen for colon cancer. Strengths and weaknesses of observational study design features are discussed, along with lessons about how features that help assure strength might be "cultivated" in the future. CONCLUSIONS AND IMPACT: By considering these examples and others, it may be possible to develop a process of "cultivating cohorts" in ongoing RCTs, observational cohort studies, and practice settings like HMOs that have strong features of study design. Such an effort could produce sources of data and specimens to reliably answer questions about the use of molecular markers in diagnosis, prognosis, and response to therapy.

Entities:  

Mesh:

Year:  2013        PMID: 23462919      PMCID: PMC4378958          DOI: 10.1158/1055-9965.EPI-13-0140

Source DB:  PubMed          Journal:  Cancer Epidemiol Biomarkers Prev        ISSN: 1055-9965            Impact factor:   4.254


  13 in total

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Authors:  John P A Ioannidis; Muin J Khoury
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2.  Lessons from controversy: ovarian cancer screening and serum proteomics.

Authors:  David F Ransohoff
Journal:  J Natl Cancer Inst       Date:  2005-02-16       Impact factor: 13.506

3.  Fecal DNA versus fecal occult blood for colorectal-cancer screening in an average-risk population.

Authors:  Thomas F Imperiale; David F Ransohoff; Steven H Itzkowitz; Barry A Turnbull; Michael E Ross
Journal:  N Engl J Med       Date:  2004-12-23       Impact factor: 91.245

Review 4.  How to improve reliability and efficiency of research about molecular markers: roles of phases, guidelines, and study design.

Authors:  David F Ransohoff
Journal:  J Clin Epidemiol       Date:  2007-09-24       Impact factor: 6.437

5.  Signal in noise: evaluating reported reproducibility of serum proteomic tests for ovarian cancer.

Authors:  Keith A Baggerly; Jeffrey S Morris; Sarah R Edmonson; Kevin R Coombes
Journal:  J Natl Cancer Inst       Date:  2005-02-16       Impact factor: 13.506

6.  A multigene assay to predict recurrence of tamoxifen-treated, node-negative breast cancer.

Authors:  Soonmyung Paik; Steven Shak; Gong Tang; Chungyeul Kim; Joffre Baker; Maureen Cronin; Frederick L Baehner; Michael G Walker; Drew Watson; Taesung Park; William Hiller; Edwin R Fisher; D Lawrence Wickerham; John Bryant; Norman Wolmark
Journal:  N Engl J Med       Date:  2004-12-10       Impact factor: 91.245

7.  A framework for evaluating biomarkers for early detection: validation of biomarker panels for ovarian cancer.

Authors:  Claire S Zhu; Paul F Pinsky; Daniel W Cramer; David F Ransohoff; Patricia Hartge; Ruth M Pfeiffer; Nicole Urban; Gil Mor; Robert C Bast; Lee E Moore; Anna E Lokshin; Martin W McIntosh; Steven J Skates; Allison Vitonis; Zhen Zhang; David C Ward; James T Symanowski; Aleksey Lomakin; Eric T Fung; Patrick M Sluss; Nathalie Scholler; Karen H Lu; Adele M Marrangoni; Christos Patriotis; Sudhir Srivastava; Saundra S Buys; Christine D Berg
Journal:  Cancer Prev Res (Phila)       Date:  2011-03

8.  Use of proteomic patterns in serum to identify ovarian cancer.

Authors:  Emanuel F Petricoin; Ali M Ardekani; Ben A Hitt; Peter J Levine; Vincent A Fusaro; Seth M Steinberg; Gordon B Mills; Charles Simone; David A Fishman; Elise C Kohn; Lance A Liotta
Journal:  Lancet       Date:  2002-02-16       Impact factor: 79.321

9.  Transforming epidemiology for 21st century medicine and public health.

Authors:  Muin J Khoury; Tram Kim Lam; John P A Ioannidis; Patricia Hartge; Margaret R Spitz; Julie E Buring; Stephen J Chanock; Robert T Croyle; Katrina A Goddard; Geoffrey S Ginsburg; Zdenko Herceg; Robert A Hiatt; Robert N Hoover; David J Hunter; Barnet S Kramer; Michael S Lauer; Jeffrey A Meyerhardt; Olufunmilayo I Olopade; Julie R Palmer; Thomas A Sellers; Daniela Seminara; David F Ransohoff; Timothy R Rebbeck; Georgia Tourassi; Deborah M Winn; Ann Zauber; Sheri D Schully
Journal:  Cancer Epidemiol Biomarkers Prev       Date:  2013-03-05       Impact factor: 4.254

10.  Sources of bias in specimens for research about molecular markers for cancer.

Authors:  David F Ransohoff; Margaret L Gourlay
Journal:  J Clin Oncol       Date:  2009-12-28       Impact factor: 44.544

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3.  Transforming epidemiology for 21st century medicine and public health.

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Journal:  Cancer Epidemiol Biomarkers Prev       Date:  2013-03-05       Impact factor: 4.254

4.  A processual model for functional analyses of carcinogenesis in the prospective cohort design.

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Authors:  Nigel T Brockton; Stephanie J Gill; Stephanie L Laborge; Alexander H G Paterson; Linda S Cook; Hans J Vogel; Carrie S Shemanko; David A Hanley; Anthony M Magliocco; Christine M Friedenreich
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