BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

291 related articles for article (PubMed ID: 26028416)

  • 1. [Bias and confounding: pharmacoepidemiological study using administrative database].
    Nojiri S
    Yakugaku Zasshi; 2015; 135(6):793-808. PubMed ID: 26028416
    [TBL] [Abstract][Full Text] [Related]  

  • 2. Administrative database research has unique characteristics that can risk biased results.
    van Walraven C; Austin P
    J Clin Epidemiol; 2012 Feb; 65(2):126-31. PubMed ID: 22075111
    [TBL] [Abstract][Full Text] [Related]  

  • 3. [Application of disease-risk score in pharmacoepidemiologic studies].
    Zhao HY; Zhan SY
    Zhonghua Liu Xing Bing Xue Za Zhi; 2017 Feb; 38(2):261-266. PubMed ID: 28231678
    [TBL] [Abstract][Full Text] [Related]  

  • 4. Bias in pharmacoepidemiologic studies using secondary health care databases: a scoping review.
    Prada-Ramallal G; Takkouche B; Figueiras A
    BMC Med Res Methodol; 2019 Mar; 19(1):53. PubMed ID: 30871502
    [TBL] [Abstract][Full Text] [Related]  

  • 5. The value of a health insurance database to conduct pharmacoepidemiological studies in oncology.
    Conte C; Vaysse C; Bosco P; Noize P; Fourrier-Reglat A; Despas F; Lapeyre-Mestre M
    Therapie; 2019 Apr; 74(2):279-288. PubMed ID: 30824175
    [TBL] [Abstract][Full Text] [Related]  

  • 6. Supplementary data collection with case-cohort analysis to address potential confounding in a cohort study of thromboembolism in oral contraceptive initiators matched on claims-based propensity scores.
    Eng PM; Seeger JD; Loughlin J; Clifford CR; Mentor S; Walker AM
    Pharmacoepidemiol Drug Saf; 2008 Mar; 17(3):297-305. PubMed ID: 18215000
    [TBL] [Abstract][Full Text] [Related]  

  • 7. Why do covariates defined by International Classification of Diseases codes fail to remove confounding in pharmacoepidemiologic studies among seniors?
    Jackson ML; Nelson JC; Jackson LA
    Pharmacoepidemiol Drug Saf; 2011 Aug; 20(8):858-65. PubMed ID: 21671442
    [TBL] [Abstract][Full Text] [Related]  

  • 8. A comparison of estimators from self-controlled case series, case-crossover design, and sequence symmetry analysis for pharmacoepidemiological studies.
    Takeuchi Y; Shinozaki T; Matsuyama Y
    BMC Med Res Methodol; 2018 Jan; 18(1):4. PubMed ID: 29310575
    [TBL] [Abstract][Full Text] [Related]  

  • 9. Good research practices for comparative effectiveness research: approaches to mitigate bias and confounding in the design of nonrandomized studies of treatment effects using secondary data sources: the International Society for Pharmacoeconomics and Outcomes Research Good Research Practices for Retrospective Database Analysis Task Force Report--Part II.
    Cox E; Martin BC; Van Staa T; Garbe E; Siebert U; Johnson ML
    Value Health; 2009; 12(8):1053-61. PubMed ID: 19744292
    [TBL] [Abstract][Full Text] [Related]  

  • 10. Measuring frailty using claims data for pharmacoepidemiologic studies of mortality in older adults: evidence and recommendations.
    Kim DH; Schneeweiss S
    Pharmacoepidemiol Drug Saf; 2014 Sep; 23(9):891-901. PubMed ID: 24962929
    [TBL] [Abstract][Full Text] [Related]  

  • 11. Challenges and opportunities for pharmacoepidemiology in drug-therapy decision making.
    Etminan M; Gill S; Fitzgerald M; Samii A
    J Clin Pharmacol; 2006 Jan; 46(1):6-9. PubMed ID: 16397278
    [TBL] [Abstract][Full Text] [Related]  

  • 12. Pre-study feasibility and identifying sensitivity analyses for protocol pre-specification in comparative effectiveness research.
    Girman CJ; Faries D; Ryan P; Rotelli M; Belger M; Binkowitz B; O'Neill R;
    J Comp Eff Res; 2014 May; 3(3):259-70. PubMed ID: 24969153
    [TBL] [Abstract][Full Text] [Related]  

  • 13. The missing cause approach to unmeasured confounding in pharmacoepidemiology.
    Abrahamowicz M; Bjerre LM; Beauchamp ME; LeLorier J; Burne R
    Stat Med; 2016 Mar; 35(7):1001-16. PubMed ID: 26932124
    [TBL] [Abstract][Full Text] [Related]  

  • 14. Inventory of real-world data sources in Japan: Annual survey conducted by the Japanese Society for Pharmacoepidemiology Task Force.
    Kumamaru H; Togo K; Kimura T; Koide D; Iihara N; Tokumasu H; Imai S
    Pharmacoepidemiol Drug Saf; 2024 Jan; 33(1):e5680. PubMed ID: 37650434
    [TBL] [Abstract][Full Text] [Related]  

  • 15. Methods to adjust for bias and confounding in critical care health services research involving observational data.
    Wunsch H; Linde-Zwirble WT; Angus DC
    J Crit Care; 2006 Mar; 21(1):1-7. PubMed ID: 16616616
    [TBL] [Abstract][Full Text] [Related]  

  • 16. Core concepts in pharmacoepidemiology: Measurement of medication exposure in routinely collected healthcare data for causal inference studies in pharmacoepidemiology.
    Thai TN; Winterstein AG
    Pharmacoepidemiol Drug Saf; 2024 Mar; 33(3):e5683. PubMed ID: 37752827
    [TBL] [Abstract][Full Text] [Related]  

  • 17. [Secondary Data for Pharmacoepidemiological Research - Making the Best of It!].
    Pigeot I; Kollhorst B; Didelez V
    Gesundheitswesen; 2021 Nov; 83(S 02):S69-S76. PubMed ID: 34695869
    [TBL] [Abstract][Full Text] [Related]  

  • 18. Martingale residual-based method to control for confounders measured only in a validation sample in time-to-event analysis.
    Burne RM; Abrahamowicz M
    Stat Med; 2016 Nov; 35(25):4588-4606. PubMed ID: 27306611
    [TBL] [Abstract][Full Text] [Related]  

  • 19. Addressing unmeasured confounding in comparative observational research.
    Zhang X; Faries DE; Li H; Stamey JD; Imbens GW
    Pharmacoepidemiol Drug Saf; 2018 Apr; 27(4):373-382. PubMed ID: 29383840
    [TBL] [Abstract][Full Text] [Related]  

  • 20. Bias: considerations for research practice.
    Gerhard T
    Am J Health Syst Pharm; 2008 Nov; 65(22):2159-68. PubMed ID: 18997149
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 15.