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SMART Designs in Observational Studies of Opioid Therapy Duration

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References

  1. Institute of Medicine (US). Committee on Advancing Pain Research Care and Education. Relieving pain in America : a blueprint for transforming prevention, care, education, and research. Washington, DC: National Academies Press; 2011. xvii, 364 p. p.

  2. Sullivan MD, Howe CQ. Opioid therapy for chronic pain in the United States: promises and perils. Pain. 2013. doi:10.1016/j.pain.2013.09.009. PubMed PMID: 24036286.

    Google Scholar 

  3. IMS Institute for Healthcare Informatics. The Use of Medicines in the United States: Review of 2011. Parsippany, NJ: IMS Institute for Healthcare Informatics; 2012.

    Google Scholar 

  4. Scherrer JF, Svrakic DM, Freedland KE, Chrusciel T, Balasubramanian S, Bucholz KK, et al. Prescription opioid analgesics increase the risk of depression. J Gen Intern Med. 2013. doi:10.1007/s11606-013-2648-1. PubMed PMID: 24165926.

    PubMed  Google Scholar 

  5. Rosenbaum P. Delimnas and Craftsmanship. Design of Observational Studies. New York, NY: Springer; 2010:3–13.

    Google Scholar 

  6. Almirall D, Compton SN, Rynn MA, Walkup JT, Murphy SA. SMARTer discontinuation trial designs for developing an adaptive treatment strategy. J Child Adolesc Psychopharmacol. 2012;22(5):364–74.

    Article  PubMed Central  PubMed  Google Scholar 

  7. Rush AJ, First MB, Blacker D, American Psychiatric Association. Task Force for the Handbook of Psychiatric Measures. Handbook of psychiatric measures, vol. xxxvi. 2nd ed. Washington, DC: American Psychiatric Pub; 2008. 828 p. p.

    Google Scholar 

  8. Robins JM, Hernan MA. Estimation of the causal effects of time-varying exposures. In: Fitzmaurice GM, editor. Longitudinal data analysis. Chapman & Hall/CRC handbooks of modern statistical methods. Boca Raton: CRC Press; 2009:p. xiv, 618 p.

  9. Robins JM, Hernan MA, Brumback B. Marginal structural models and causal inference in epidemiology. Epidemiology (Cambridge, Mass). 2000;11(5):550–60.

    Article  CAS  Google Scholar 

  10. Joffe MM. Administrative and artificial censoring in censored regression models. Stat Med. 2001;20(15):2287–304.

    Article  CAS  PubMed  Google Scholar 

  11. Cole SR, Hernan MA. Constructing inverse probability weights for marginal structural models. Am J Epidemiol. 2008;168(6):656–64.

    Article  PubMed Central  PubMed  Google Scholar 

  12. Townsend L, Walkup JT, Crystal S, Olfson M. A systematic review of validated methods for identifying depression using administrative data. Pharmacoepidemiol Drug Saf. 2012;21(Suppl 1):163–73.

    Article  PubMed  Google Scholar 

  13. Braden JB, Sullivan MD, Ray GT, Saunders K, Merrill J, Silverberg MJ, et al. Trends in long-term opioid therapy for noncancer pain among persons with a history of depression. Gen Hosp Psychiatry. 2009;31(6):564–70.

    Article  PubMed Central  PubMed  Google Scholar 

  14. Hennessy S, Freeman CP, Cunningham F. US Government Claims Databases. Pharmacoepidemiology. 5th ed. Chichester, West Sussex, UK: Wiley-Blackwell; 2012:p. p.

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Correspondence to Joshua J. Gagne PharmD, ScD.

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Jackson, J.W., Gagne, J.J. SMART Designs in Observational Studies of Opioid Therapy Duration. J GEN INTERN MED 29, 429–431 (2014). https://doi.org/10.1007/s11606-013-2725-5

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