Literature DB >> 28268936

Assessing the population representativeness of colorectal cancer treatment clinical trials.

Thomas J George, Gloria Lipori.   

Abstract

The generalizability (external validity) of clinical trials has long been a concern for both clinical research community as well as the general public. Results of trials that do not represent the target population may not be applicable to the broader patient population. In this study, we used a previously published metric Generalizability Index for Study Traits (GIST) to assess the population representativeness of colorectal cancer (CRC) treatment trials. Our analysis showed that the quantitative eligibility criteria of CRC trials are in general not restrictive. However, the qualitative eligibility criteria in these trials are with moderate or strict restrictions, which may impact their population representativeness of the real-world patient population.

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Year:  2016        PMID: 28268936      PMCID: PMC5727892          DOI: 10.1109/EMBC.2016.7591353

Source DB:  PubMed          Journal:  Conf Proc IEEE Eng Med Biol Soc        ISSN: 1557-170X


  14 in total

1.  The Unified Medical Language System (UMLS): integrating biomedical terminology.

Authors:  Olivier Bodenreider
Journal:  Nucleic Acids Res       Date:  2004-01-01       Impact factor: 16.971

2.  External validity of randomised controlled trials: "to whom do the results of this trial apply?".

Authors:  Peter M Rothwell
Journal:  Lancet       Date:  2005 Jan 1-7       Impact factor: 79.321

3.  A distribution-based method for assessing the differences between clinical trial target populations and patient populations in electronic health records.

Authors:  C Weng; Y Li; P Ryan; Y Zhang; F Liu; J Gao; J T Bigger; G Hripcsak
Journal:  Appl Clin Inform       Date:  2014-05-07       Impact factor: 2.342

4.  Visual aggregate analysis of eligibility features of clinical trials.

Authors:  Zhe He; Simona Carini; Ida Sim; Chunhua Weng
Journal:  J Biomed Inform       Date:  2015-01-20       Impact factor: 6.317

5.  Underrepresentation of patients 65 years of age or older in cancer-treatment trials.

Authors:  L F Hutchins; J M Unger; J J Crowley; C A Coltman; K S Albain
Journal:  N Engl J Med       Date:  1999-12-30       Impact factor: 91.245

6.  Simulation-based Evaluation of the Generalizability Index for Study Traits.

Authors:  Zhe He; Praveen Chandar; Patrick Ryan; Chunhua Weng
Journal:  AMIA Annu Symp Proc       Date:  2015-11-05

7.  Representation of elderly persons and women in published randomized trials of acute coronary syndromes.

Authors:  P Y Lee; K P Alexander; B G Hammill; S K Pasquali; E D Peterson
Journal:  JAMA       Date:  2001-08-08       Impact factor: 56.272

8.  Participation of patients 65 years of age or older in cancer clinical trials.

Authors:  Joy H Lewis; Meredith L Kilgore; Dana P Goldman; Edward L Trimble; Richard Kaplan; Michael J Montello; Michael G Housman; José J Escarce
Journal:  J Clin Oncol       Date:  2003-04-01       Impact factor: 44.544

9.  Examination of external validity in randomized controlled trials for adjuvant treatment of pancreatic adenocarcinoma.

Authors:  Carolin Sorg; Jan Schmidt; Markus W Büchler; Lutz Edler; Angela Märten
Journal:  Pancreas       Date:  2009-07       Impact factor: 3.327

10.  Multivariate analysis of the population representativeness of related clinical studies.

Authors:  Zhe He; Patrick Ryan; Julia Hoxha; Shuang Wang; Simona Carini; Ida Sim; Chunhua Weng
Journal:  J Biomed Inform       Date:  2016-01-25       Impact factor: 6.317

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  3 in total

1.  Analysis of Temporal Constraints in Qualitative Eligibility Criteria of Cancer Clinical Studies.

Authors:  Zhe He; Zhiwei Chen; Jiang Bian
Journal:  Proceedings (IEEE Int Conf Bioinformatics Biomed)       Date:  2017-01-19

Review 2.  A 10-year review of survival among patients with metastatic gastrointestinal cancers: a population-based study.

Authors:  Omar Abdel-Rahman
Journal:  Int J Colorectal Dis       Date:  2020-03-17       Impact factor: 2.571

3.  Semantic categorization of Chinese eligibility criteria in clinical trials using machine learning methods.

Authors:  Hui Zong; Jinxuan Yang; Zeyu Zhang; Zuofeng Li; Xiaoyan Zhang
Journal:  BMC Med Inform Decis Mak       Date:  2021-04-15       Impact factor: 2.796

  3 in total

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