Skip to main content
SpringerLink
Log in

Quantitative Aspects of Clinical Reasoning: Measuring Endpoints and Performance

  • Chapter
  • First Online:
Kidney and Pancreas Transplantation

Part of the book series: Current Clinical Urology ((CCU))

  • 1669 Accesses

Abstract

Appropriate metrics are critical in evaluating the quality of care and performance in the field of transplantation. The proper interpretation and implications of research often depend upon the reliability of data sources and the use of appropriate statistical methodology. This chapter provides an overview of the data sources and key metrics that are utilized in the analysis of performance of transplant programs.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 189.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 249.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 249.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  1. Juni P, Witschi A, Bloch R et al. The hazards of scoring the quality of clinical trials for meta-analysis. JAMA 1999;282:1054–1060.

    Article  CAS  PubMed  Google Scholar 

  2. Moher D, Schulz KF, Altman DG. The CONSORT statement: revised recommendations for improving the quality of reports of parallel-group randomised trials. Lancet 2001;357:1191–1194.

    Article  CAS  PubMed  Google Scholar 

  3. Moher D, Jones A, Lepage L. Use of the CONSORT statement and quality of reports of randomized trials: a comparative before-and-after evaluation. JAMA 2001;285:1992–1995.

    Article  CAS  PubMed  Google Scholar 

  4. Wang R, Lagakos SW, Ware JH, et al. Statistics in medicine – reporting of subgroup analyses in clinical trials. NEJM 2007;357:2189–2194.

    Article  CAS  PubMed  Google Scholar 

  5. Wiens BL. Choosing an equivalence limit for noninferiority or equivalence studies. Control Clin Trials 2002;23:2–14.

    Article  PubMed  Google Scholar 

  6. Freemantle N, Calvert M, Wood J, et al. Composite outcomes in randomized trials: greater precision but with greater uncertainty? JAMA 2003;289:2554–2559.

    Article  PubMed  Google Scholar 

  7. Dickinson DM, Dykstra DM, Levine GN, et al. Transplant data: sources, collection and research considerations, 2004. Am J Transplant 2005;5:850–861.

    Article  PubMed  Google Scholar 

  8. Kaplan B, Schold J, Meier-Kriesche HU. Overview of large database analysis in renal transplantation. Am J Transplant 2003;3:1052–1056.

    Article  PubMed  Google Scholar 

  9. Meier-Kriesche HU, Schold JD, Srinivas TR, et al. Lack of improvement in renal allograft survival despite a marked decrease in acute rejection rates over the most recent era. Am J Transplant 2004;4:378–383.

    Article  PubMed  Google Scholar 

  10. Fleiner F, Fritsche L, Glander P, et al. Reporting of rejection after renal transplantation in large immunosuppressive trials: biopsy-proven, clinical, presumed, or treated rejection? Transplantation 2006;81:655–659.

    Article  PubMed  Google Scholar 

  11. Wu O, Levy AR, Briggs A, et al. Acute rejection and chronic nephropathy: a systematic review of the literature. Transplantation 2009;87:1330–1339.

    Article  PubMed  Google Scholar 

  12. Nett PC, Heisey DM, Shames BD, et al. Influence of kidney function to the impact of acute rejection on long-term kidney transplant survival. Transpl Int 2005;18:385–389.

    Article  PubMed  Google Scholar 

  13. Sijpkens YW, Doxiadis II, Mallat MJ, et al. Early versus late acute rejection episodes in renal transplantation. Transplantation 2003;75:204–208.

    Article  PubMed  Google Scholar 

  14. Irish WD, McCollum DA, Tesi RJ, et al. Nomogram for predicting the likelihood of delayed graft function in adult cadaveric renal transplant recipients. J Am Soc Nephrol 2003;14:2967–2974.

    Article  PubMed  Google Scholar 

  15. Schold JD, Kaplan B, Howard RJ, et al. Are we frozen in time? Analysis of the utilization and efficacy of pulsatile perfusion in renal transplantation. Am J Transplant 2005;5:1681–1688.

    Article  PubMed  Google Scholar 

  16. Shoskes DA, Halloran PF. Delayed graft function in renal transplantation: etiology, management and long-term significance. J Urol 1996;155:1831–1840.

    Article  CAS  PubMed  Google Scholar 

  17. Louvar DW, Li N, Snyder J, et al. “Nature versus nurture” study of deceased-donor pairs in kidney transplantation. J Am Soc Nephrol 2009;20:1351–1358.

    Article  PubMed  Google Scholar 

  18. Burroughs TE, Swindle J, Takemoto S, et al. Diabetic complications associated with new-onset diabetes mellitus in renal transplant recipients. Transplantation 2007;83:1027–1034.

    Article  PubMed  Google Scholar 

  19. Flechner SM, Avery RK, Fisher R, et al. A randomized prospective controlled trial of oral acyclovir versus oral ganciclovir for cytomegalovirus prophylaxis in high-risk kidney transplant recipients. Transplantation 1998;66:1682–1688.

    Article  CAS  PubMed  Google Scholar 

  20. Meier-Kriesche HU, Ojo AO, Hanson JA, et al. Exponentially increased risk of infectious death in older renal transplant recipients. Kidney Int 2001;59:1539–1543.

    Article  CAS  PubMed  Google Scholar 

  21. Snyder JJ, Israni AK, Peng Y et al. Rates of first infection following kidney transplant in the United States. Kidney Int 2009;75:317–326.

    Article  PubMed  Google Scholar 

  22. Abbott KC, Duran M, Hypolite I, et al. Hospitalizations for bacterial endocarditis after renal transplantation in the United States. J Nephrol 2001;14:353–360.

    CAS  PubMed  Google Scholar 

  23. Abbott KC, Hypolite I, Poropatich RK, et al. Hospitalizations for fungal infections after renal transplantation in the United States. Transpl Infect Dis 2001;3:203–211.

    Article  CAS  PubMed  Google Scholar 

  24. Cosio FG, Nuovo M, Delgado L, et al. EBV kidney allograft infection: possible relationship with a peri-graft localization of PTLD. Am J Transplant 2004;4:116–123.

    Article  PubMed  Google Scholar 

  25. Jevnikar AM, Mannon RB. Late kidney allograft loss: what we know about it, and what we can do about it. Clin J Am Soc Nephrol 2008;3(Suppl 2):S56–S67.

    Article  PubMed  Google Scholar 

  26. Hariharan S, Kasiske B, Matas A, et al. Surrogate markers for long-term renal allograft survival. Am J Transplant 2004;4:1179–1183.

    Article  PubMed  Google Scholar 

  27. Kasiske BL, Massy ZA, Guijarro C, et al. Chronic renal allograft rejection and clinical trial design. Kidney Int Suppl 1995;52:S116–S119.

    CAS  PubMed  Google Scholar 

  28. Schold JD, Kaplan B. Design and analysis of clinical trials in transplantation: principles and pitfalls. Am J Transplant 2008;8:1779–1785.

    Article  CAS  PubMed  Google Scholar 

  29. Howard RJ, Reed AI, Hemming AW, et al. Graft loss and death: changing causes after kidney transplantation. Transplant Proc 2001;33:3416.

    Article  CAS  PubMed  Google Scholar 

  30. Kaplan B, Meier-Kriesche HU. Death after graft loss: an important late study endpoint in kidney transplantation. Am J Transplant 2002;2:970–974.

    Article  PubMed  Google Scholar 

  31. Hariharan S, McBride MA, Cherikh WS, et al. Post-transplant renal function in the first year predicts long-term kidney transplant survival. Kidney Int 2002;62:311–318.

    Article  PubMed  Google Scholar 

  32. Meier-Kriesche HU, Baliga R, Kaplan B. Decreased renal function is a strong risk factor for cardiovascular death after renal transplantation. Transplantation 2003;75:1291–1295.

    Article  PubMed  Google Scholar 

  33. Levey AS, Stevens LA, Schmid CH, et al. A new equation to estimate glomerular filtration rate. Ann Intern Med 2009;150:604–612.

    PubMed  Google Scholar 

  34. Pascual J, Marcen R, Zamora J, et al. Very early serum creatinine as a surrogate marker for graft survival beyond 10 years. J Nephrol 2009;22:90–98.

    CAS  PubMed  Google Scholar 

  35. Kaplan B, Schold J, Meier-Kriesche HU. Poor predictive value of serum creatinine for renal allograft loss. Am J Transplant 2003;3:1560–1565.

    Article  CAS  PubMed  Google Scholar 

  36. Whiting JF, Woodward RS, Zavala EY, et al. Economic cost of expanded criteria donors in cadaveric renal transplantation: analysis of Medicare payments. Transplantation 2000;70:755–760.

    Article  CAS  PubMed  Google Scholar 

  37. Abecassis MM, Seifeldin R, Riordan ME. Patient outcomes and economics of once-daily tacrolimus in renal transplant patients: results of a modeling analysis. Transplant Proc 2008;40:1443–1445.

    Article  CAS  PubMed  Google Scholar 

  38. Kutinova A, Woodward RS, Ricci JF, et al. The incidence and costs of sepsis and pneumonia before and after renal transplantation in the United States. Am J Transplant 2006;6:129–139.

    Article  CAS  PubMed  Google Scholar 

  39. Woodward RS, Schnitzler MA, Lowell JA, et al. Effect of extended coverage of immunosuppressive medications by medicare on the survival of cadaveric renal transplants. Am J Transplant 2001;1:69–73.

    Article  CAS  PubMed  Google Scholar 

  40. Hornberger JC, Best JH, Garrison LP Jr. Cost-effectiveness of repeat medical procedures: kidney transplantation as an example. Med Decis Making 1997;17:363–372.

    Article  CAS  PubMed  Google Scholar 

  41. Meier-Kriesche HU, Schold JD, Gaston RS, et al. Kidneys from deceased donors: maximizing the value of a scarce resource. Am J Transplant 2005;5:1725–1730.

    Article  PubMed  Google Scholar 

  42. Wolfe RA, McCullough KP, Schaubel DE, et al. Calculating life years from transplant (LYFT): methods for kidney and kidney-pancreas candidates. Am J Transplant 2008;8:997–1011.

    Article  CAS  PubMed  Google Scholar 

  43. Dickinson DM, Shearon TH, O’Keefe J, et al. SRTR center-specific reporting tools: posttransplant outcomes. Am J Transplant 2006;6:1198–1211.

    Article  CAS  PubMed  Google Scholar 

  44. New Medicare Hospital Conditions of Participation for Transplant Centers. Centers for Medicare and Medicaid Services 12/23/09. https://www.cms.gov/CertificationandComplianc/Downloads/Transplantfinal.pdf

  45. Dobbels F, De BL, De GS, et al. Quality of life after kidney transplantation: the bright side of life? Adv Chronic Kidney Dis 2007;14:370–378.

    Article  PubMed  Google Scholar 

  46. Tanriverdi N, Ozcurumez G, Colak T, et al. Quality of life and mood in renal transplantation recipients, donors, and controls: preliminary report. Transplant Proc 2004;36:117–119.

    Article  CAS  PubMed  Google Scholar 

  47. Schold JD, Howard RJ. Prediction models assessing transplant center performance: can a little knowledge be a dangerous thing? Am J Transplant 2006;6:245–246.

    Article  CAS  PubMed  Google Scholar 

  48. Schold JD, Srinivas TR, Howard RJ, et al. The association of candidate mortality rates with kidney transplant outcomes and center performance evaluations. Transplantation 2008;85:1–6.

    Article  PubMed  Google Scholar 

  49. Weinhandl ED, Snyder JJ, Israni AK, et al. Effect of comorbidity adjustment on CMS criteria for kidney transplant center performance. Am J Transplant 2009;9:506–516.

    Article  CAS  PubMed  Google Scholar 

  50. Stern JM, Simes RJ. Publication bias: evidence of delayed publication in a cohort study of clinical research projects. BMJ 1997;315:640–645.

    Article  CAS  PubMed  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Department of Quantitative Health Sciences, Cleveland Clinic, 9500 Euclid Avenue, Cleveland, OH, 44195, USA

    Jesse D. Schold

Authors
  1. Jesse D. Schold
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Jesse D. Schold .

Editor information

Editors and Affiliations

  1. Glickman Urological & Kidney Institute, Children's Hospital of Cleveland Clinic, Euclid Ave. 9500, Cleveland, 44195, Ohio, USA

    T. R. Srinivas

  2. Glickman Urological & Kidney Institute, Cleveland Clinic, 9500 Euclid Avenue 9500, Cleveland, 44195, Ohio, USA

    Daniel A. Shoskes

Rights and permissions

Reprints and permissions

Copyright information

© 2011 Springer Science+Business Media, LLC

About this chapter

Cite this chapter

Schold, J.D. (2011). Quantitative Aspects of Clinical Reasoning: Measuring Endpoints and Performance. In: Srinivas, T., Shoskes, D. (eds) Kidney and Pancreas Transplantation. Current Clinical Urology. Humana Press, Totowa, NJ. https://doi.org/10.1007/978-1-60761-642-9_24

Download citation

  • DOI: https://doi.org/10.1007/978-1-60761-642-9_24

  • Published:

  • Publisher Name: Humana Press, Totowa, NJ

  • Print ISBN: 978-1-60761-641-2

  • Online ISBN: 978-1-60761-642-9

  • eBook Packages: MedicineMedicine (R0)

Publish with us

Policies and ethics

Search

Navigation