These tools will no longer be maintained as of December 31, 2024. Archived website can be found here. PubMed4Hh GitHub repository can be found here. Contact NLM Customer Service if you have questions.


BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

155 related articles for article (PubMed ID: 33350439)

  • 1. Invited Commentary: The Prevalent New-User Design in Pharmacoepidemiology-Challenges and Opportunities.
    Filion KB; Yu YH
    Am J Epidemiol; 2021 Jul; 190(7):1349-1352. PubMed ID: 33350439
    [TBL] [Abstract][Full Text] [Related]  

  • 2. Initiator Types and the Causal Question of the Prevalent New-User Design: A Simulation Study.
    Webster-Clark M; Ross RK; Lund JL
    Am J Epidemiol; 2021 Jul; 190(7):1341-1348. PubMed ID: 33350433
    [TBL] [Abstract][Full Text] [Related]  

  • 3. New-user and prevalent-user designs and the definition of study time origin in pharmacoepidemiology: A review of reporting practices.
    Luijken K; Spekreijse JJ; van Smeden M; Gardarsdottir H; Groenwold RHH
    Pharmacoepidemiol Drug Saf; 2021 Jul; 30(7):960-974. PubMed ID: 33899305
    [TBL] [Abstract][Full Text] [Related]  

  • 4. Core concepts in pharmacoepidemiology: Key biases arising in pharmacoepidemiologic studies.
    Acton EK; Willis AW; Hennessy S
    Pharmacoepidemiol Drug Saf; 2023 Jan; 32(1):9-18. PubMed ID: 36216785
    [TBL] [Abstract][Full Text] [Related]  

  • 5. 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]  

  • 6. The active comparator, new user study design in pharmacoepidemiology: historical foundations and contemporary application.
    Lund JL; Richardson DB; Stürmer T
    Curr Epidemiol Rep; 2015 Dec; 2(4):221-228. PubMed ID: 26954351
    [TBL] [Abstract][Full Text] [Related]  

  • 7. Prevalent new-user cohort designs for comparative drug effect studies by time-conditional propensity scores.
    Suissa S; Moodie EE; Dell'Aniello S
    Pharmacoepidemiol Drug Saf; 2017 Apr; 26(4):459-468. PubMed ID: 27610604
    [TBL] [Abstract][Full Text] [Related]  

  • 8. Importance of feasibility assessments before implementing non-interventional pharmacoepidemiologic studies of vaccines: lessons learned and recommendations for future studies.
    Willame C; Baril L; van den Bosch J; Ferreira GL; Williams R; Rosillon D; Cohet C
    Pharmacoepidemiol Drug Saf; 2016 Dec; 25(12):1397-1406. PubMed ID: 27601179
    [TBL] [Abstract][Full Text] [Related]  

  • 9. Evaluating medication effects outside of clinical trials: new-user designs.
    Ray WA
    Am J Epidemiol; 2003 Nov; 158(9):915-20. PubMed ID: 14585769
    [TBL] [Abstract][Full Text] [Related]  

  • 10. Invited Commentary: Go BIG and Go Global-Executing Large-Scale, Multisite Pharmacoepidemiologic Studies Using Real-World Data.
    Maro JC; Toh S
    Am J Epidemiol; 2022 Jul; 191(8):1368-1371. PubMed ID: 35597819
    [TBL] [Abstract][Full Text] [Related]  

  • 11. Counterpoint: the treatment decision design.
    Brookhart MA
    Am J Epidemiol; 2015 Nov; 182(10):840-5. PubMed ID: 26507307
    [TBL] [Abstract][Full Text] [Related]  

  • 12. The effectiveness of internet-based e-learning on clinician behavior and patient outcomes: a systematic review protocol.
    Sinclair P; Kable A; Levett-Jones T
    JBI Database System Rev Implement Rep; 2015 Jan; 13(1):52-64. PubMed ID: 26447007
    [TBL] [Abstract][Full Text] [Related]  

  • 13. Disease latency and new-user versus prevalent-user cohort designs: Implications for pharmacoepidemiology in dementia.
    Wu CY; Swardfager W
    J Am Geriatr Soc; 2024 Mar; 72(3):953-955. PubMed ID: 38147492
    [No Abstract]   [Full Text] [Related]  

  • 14. Reply to: Disease latency and new-user versus prevalent-user cohort designs: Implications for pharmacoepidemiology in dementia.
    Lee AK; Lee SJ; Dublin S
    J Am Geriatr Soc; 2024 Mar; 72(3):956-957. PubMed ID: 38147504
    [No Abstract]   [Full Text] [Related]  

  • 15. 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]  

  • 16. Invited Commentary: Cross-Sectional Studies and Causal Inference-It's Complicated.
    Barnett TA; Koushik A; Schuster T
    Am J Epidemiol; 2023 Apr; 192(4):517-519. PubMed ID: 36722176
    [TBL] [Abstract][Full Text] [Related]  

  • 17. The importance and implications of comparator selection in pharmacoepidemiologic research.
    D'Arcy M; Stürmer T; Lund JL
    Curr Epidemiol Rep; 2018 Sep; 5(3):272-283. PubMed ID: 30666285
    [TBL] [Abstract][Full Text] [Related]  

  • 18. Causality in Pharmacoepidemiology and Pharmacovigilance: a theoretical excursion.
    Mota DM; Kuchenbecker RS
    Rev Bras Epidemiol; 2017; 20(3):475-486. PubMed ID: 29160439
    [TBL] [Abstract][Full Text] [Related]  

  • 19. Invited Commentary: Treatment Drop-in-Making the Case for Causal Prediction.
    Sperrin M; Diaz-Ordaz K; Pajouheshnia R
    Am J Epidemiol; 2021 Oct; 190(10):2015-2018. PubMed ID: 33595073
    [TBL] [Abstract][Full Text] [Related]  

  • 20. Pharmacoepidemiology for nephrologists (part 2): potential biases and how to overcome them.
    Fu EL; van Diepen M; Xu Y; Trevisan M; Dekker FW; Zoccali C; Jager K; Carrero JJ
    Clin Kidney J; 2021 May; 14(5):1317-1326. PubMed ID: 33959262
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 8.