Skip to main content

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

  • Review Article
  • Published:

Kidney disease trials for the 21st century: innovations in design and conduct

Nature Reviews Nephrology volume 16, pages 173–185 (2020)Cite this article

Subjects

Abstract

Compared to other specialties, nephrology has reported relatively few clinical trials, and most of these are too small to detect moderate treatment effects. Consequently, interventions that are commonly used by nephrologists have not been adequately tested and some may be ineffective or harmful. More randomized trials are urgently needed to address important clinical questions in patients with kidney disease. The use of robust surrogate markers may accelerate early-phase drug development. However, scientific innovations in trial conduct developed by other specialties should also be adopted to improve trial quality and enable more, larger trials in kidney disease to be completed in the current era of burdensome regulation and escalating research costs. Examples of such innovations include utilizing routinely collected health-care data and disease-specific registries to identify and invite potential trial participants, and for long-term follow-up; use of prescreening to facilitate rapid recruitment of participants; use of pre-randomization run-in periods to improve participant adherence and assess responses to study interventions prior to randomization; and appropriate use of statistics to monitor studies and analyse their results. Nephrology is well positioned to harness such innovations due to its advanced use of electronic health-care records and the development of disease-specific registries. Adopting a population approach and efficient trial conduct along with challenging unscientific regulation may increase the number of definitive clinical trials in nephrology and improve the care of current and future patients.

Key points

  • Nephrology has the potential to benefit from large streamlined trials similar to those that have led to advances in cardiology and diabetology.

  • As effective interventions are developed and population-level risks fall, larger trial sample sizes are often needed to ensure sufficient statistical power to demonstrate the effects of new therapies.

  • When moderate effect sizes are anticipated, real-world evidence from association studies cannot provide a reliable estimate of the effect of an intervention; only ‘randomization’ guarantees the elimination of moderate biases.

  • Potential surrogate outcomes in renal trials include change in albuminuria and estimated glomerular filtration rate slopes; however, no surrogate exists for safety, and large trials with sufficiently long follow-up remain necessary.

  • Precision medicine approaches have the potential to reduce trial sample sizes but might exclude at-risk groups who could potentially benefit from an intervention and can lead to time-consuming and costly recruitment procedures.

  • In this era of complex research governance and burdensome regulation, innovations in trial conduct to enable large-scale invitation, better adherence and low-cost follow-up may be more important than innovations in trial design.

This is a preview of subscription content, access via your institution

Access options

Buy this article

  • Purchase on Springer Link
  • Instant access to full article PDF
Buy now

Prices may be subject to local taxes which are calculated during checkout

Fig. 1: Avoiding bias in responder analyses.
Fig. 2: Parallel-group randomized trial designs.
Fig. 3: Cluster randomized trial designs.
Fig. 4: Master protocol trial designs.

Similar content being viewed by others

References

  1. Collins, R. Back to the future: the urgent need to re-introduce streamlined trials. Eur. Heart J. Suppl. 20, C14–C17 (2018).

    Article  Google Scholar 

  2. European Society of Cardiology. Clinical Practice Guidelines https://www.escardio.org/Guidelines/Clinical-Practice-Guidelines (2019).

  3. Nabel, E. G. & Braunwald, E. A tale of coronary artery disease and myocardial infarction. N. Engl. J. Med. 366, 54–63 (2012).

    Article  CAS  PubMed  Google Scholar 

  4. Herrington, W., Lacey, B., Sherliker, P., Armitage, J. & Lewington, S. Epidemiology of atherosclerosis and the potential to reduce the global burden of atherothrombotic disease. Circ. Res. 118, 535–546 (2016).

    Article  CAS  PubMed  Google Scholar 

  5. Wanner, C. et al. Empagliflozin and progression of kidney disease in type 2 diabetes. N. Engl. J. Med. 375, 323–334 (2016).

    Article  CAS  PubMed  Google Scholar 

  6. Perkovic, V. et al. Canagliflozin and renal outcomes in type 2 diabetes: results from the CANVAS program randomised clinical trials. Lancet Diabetes Endocrinol. 6, 691–704 (2018).

    Article  CAS  PubMed  Google Scholar 

  7. Zelniker, T. A. et al. Comparison of the effects of glucagon-like peptide receptor agonists and sodium-glucose co-transporter 2 inhibitors for prevention of major adverse cardiovascular and renal outcomes in type 2 diabetes mellitus. Circulation 139, 2022–2031 (2019).

    Article  CAS  PubMed  Google Scholar 

  8. Strippoli, G. F., Craig, J. C. & Schena, F. P. The number, quality, and coverage of randomized controlled trials in nephrology. J. Am. Soc. Nephrol. 15, 411–419 (2004).

    Article  PubMed  Google Scholar 

  9. Inrig, J. K. et al. The landscape of clinical trials in nephrology: a systematic review of Clinicaltrials.gov. Am. J. Kidney Dis. 63, 771–780 (2014).

    Article  PubMed  Google Scholar 

  10. Tonelli, M. et al. Comparison of the complexity of patients seen by different medical subspecialists in a universal health care system. JAMA Netw. Open 1, e184852 (2018).

    Article  PubMed  PubMed Central  Google Scholar 

  11. Kerr, M., Bray, B., Medcalf, J., O'Donoghue, D. J. & Matthews, B. Estimating the financial cost of chronic kidney disease to the NHS in England. Nephrol. Dial Transpl. 27, iii73–iii80 (2012).

    Article  Google Scholar 

  12. Deeks, J. J. et al. Evaluating non-randomised intervention studies. Health Technol. Assess. 7, 1–179 (2003).

    Article  Google Scholar 

  13. Gerstein, H. C., McMurray, J. & Holman, R. R. Real-world studies no substitute for RCTs in establishing efficacy. Lancet 393, 210–211 (2019).

    Article  PubMed  Google Scholar 

  14. Grady, D. et al. Hormone therapy to prevent disease and prolong life in postmenopausal women. Ann. Intern. Med. 117, 1016–1037 (1992).

    Article  CAS  PubMed  Google Scholar 

  15. Rossouw, J. E. et al. Risks and benefits of estrogen plus progestin in healthy postmenopausal women: principal results from the women's health initiative randomized controlled trial. JAMA 288, 321–333 (2002).

    Article  CAS  PubMed  Google Scholar 

  16. Collins, R. et al. Interpretation of the evidence for the efficacy and safety of statin therapy. Lancet 388, 2532–2561 (2016).

    Article  CAS  PubMed  Google Scholar 

  17. Bennett, D. A. & Holmes, M. V. Mendelian randomisation in cardiovascular research: an introduction for clinicians. Heart 103, 1400–1407 (2017).

    Article  CAS  PubMed  Google Scholar 

  18. Sun, L. et al. Causal associations of blood lipids with risk of ischemic stroke and intracerebral hemorrhage in Chinese adults. Nat. Med. 25, 569–574 (2019).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  19. Holmes, M. V. Human genetics and drug development. N. Engl. J. Med. 380, 1076–1079 (2019).

    Article  PubMed  Google Scholar 

  20. Collins, R. & MacMahon, S. Reliable assessment of the effects of treatment on mortality and major morbidity. I: Clinical trials. Lancet 357, 373–380 (2001).

    Article  CAS  PubMed  Google Scholar 

  21. Pitt, B. et al. The effect of spironolactone on morbidity and mortality in patients with severe heart failure. Randomized Aldactone Evaluation Study Investigators. N. Engl. J. Med. 341, 709–717 (1999).

    Article  CAS  PubMed  Google Scholar 

  22. Perkovic, V. et al. Canagliflozin and renal outcomes in type 2 diabetes and nephropathy. N. Engl. J. Med. 380, 2295–2306 (2019).

    Article  CAS  PubMed  Google Scholar 

  23. Ettehad, D. et al. Blood pressure lowering for prevention of cardiovascular disease and death: a systematic review and meta-analysis. Lancet 387, 957–967 (2016).

    Article  PubMed  Google Scholar 

  24. Xie, X. et al. Effects of intensive blood pressure lowering on cardiovascular and renal outcomes: updated systematic review and meta-analysis. Lancet 387, 435–443 (2016).

    Article  PubMed  Google Scholar 

  25. Herrington, W. et al. How are the effects of reducing LDL cholesterol with a statin-based regime influenced by renal function? Meta-analysis of individual data from 28 randomised trials. Lancet Diabetes Endocrinol. 4, 829–839 (2016).

    Article  PubMed  Google Scholar 

  26. Jafar, T. H. et al. Angiotensin-converting enzyme inhibitors and progression of nondiabetic renal disease. A meta-analysis of patient-level data. Ann. Intern. Med. 135, 73–87 (2001).

    Article  CAS  PubMed  Google Scholar 

  27. Webster, A. C., Playford, E. G., Higgins, G., Chapman, J. R. & Craig, J. C. Interleukin 2 receptor antagonists for renal transplant recipients: a meta-analysis of randomized trials. Transplantation 77, 166–176 (2004).

    Article  CAS  PubMed  Google Scholar 

  28. Egger, M. & Smith, G. D. Misleading meta-analysis. BMJ 310, 752–754 (1995).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  29. Chertow, G. M. et al. Effect of cinacalcet on cardiovascular disease in patients undergoing dialysis. N. Engl. J. Med. 367, 2482–2494 (2012).

    Article  CAS  PubMed  Google Scholar 

  30. Parfrey, P. S. et al. Lessons learned from EVOLVE for planning of future randomized trials in patients on dialysis. Clin J. Am. Soc. Nephrol. 11, 539–546 (2016).

    Article  PubMed  Google Scholar 

  31. Haynes, R., Landray, M. J., Herrington, W. G. & Baigent, C. in Oxford Textbook of Clinical Nephrology 4th edn (eds Turner, N. et al.) 161–170 (Oxford Uni. Press, 2015).

  32. Baigent, C. et al. Challenges in conducting clinical trials in nephrology: conclusions from a kidney disease-improving global outcomes (KDIGO) controversies conference. Kidney Int. 92, 297–305 (2017).

    Article  PubMed  PubMed Central  Google Scholar 

  33. Pfeffer, M. A. et al. A trial of darbepoetin alfa in type 2 diabetes and chronic kidney disease. N. Engl. J. Med. 361, 2019–2032 (2009).

    Article  PubMed  Google Scholar 

  34. Phrommintikul, A., Haas, S. J., Elsik, M. & Krum, H. Mortality and target haemoglobin concentrations in anaemic patients with chronic kidney disease treated with erythropoietin: a meta-analysis. Lancet 369, 381–388 (2007).

    Article  CAS  PubMed  Google Scholar 

  35. European Renal Association − European Dialysis and Transplant Association. ERA−EDTA registry annual report 2016 (ERA, 2016).

  36. UK Renal Registry. The National Registry of Rare Kidney Disease (RaDaR) https://www.renalreg.org/projects/the-national-registry-of-rare-kidney-disease-radar/ (2019).

  37. Moxey-Mims, M. M. et al. Glomerular diseases: registries and clinical trials. Clin J. Am. Soc. Nephrol. 11, 2234–2243 (2016).

    Article  PubMed  PubMed Central  Google Scholar 

  38. Miner, J. H. et al. The 2014 International workshop on Alport syndrome. Kidney Int. 86, 679–684 (2014).

    Article  PubMed  PubMed Central  Google Scholar 

  39. Bowman, L. et al. ASCEND: a study of cardiovascular events in diabetes: characteristics of a randomized trial of aspirin and of omega-3 fatty acid supplementation in 15,480 people with diabetes. Am. Heart J. 198, 135–144 (2018).

    Article  PubMed  PubMed Central  Google Scholar 

  40. Group, A. S. C. et al. Effects of aspirin for primary prevention in persons with diabetes mellitus. N. Engl. J. Med. 379, 1529–1539 (2018).

    Article  Google Scholar 

  41. Haynes, R. et al. Effects of sacubitril/valsartan versus irbesartan in patients with chronic kidney disease. Circulation 138, 1505–1514 (2018).

    Article  CAS  PubMed  Google Scholar 

  42. Sharp Collaborative Group. Study of Heart and Renal Protection (SHARP): randomized trial to assess the effects of lowering low-density lipoprotein cholesterol among 9,438 patients with chronic kidney disease. Am. Heart J. 160, 785–794.e710 (2010).

    Article  CAS  PubMed  Google Scholar 

  43. Lang, J. M., Buring, J. E., Rosner, B., Cook, N. & Hennekens, C. H. Estimating the effect of the run-in on the power of the Physicians' Health Study. Stat. Med. 10, 1585–1593 (1991).

    Article  CAS  PubMed  Google Scholar 

  44. Landray, M. J. et al. Effects of extended-release niacin with laropiprant in high-risk patients. N. Engl. J. Med. 371, 203–212 (2014).

    Article  PubMed  CAS  Google Scholar 

  45. Heerspink, H. J. L. et al. Atrasentan and renal events in patients with type 2 diabetes and chronic kidney disease (SONAR): a double-blind, randomised, placebo-controlled trial. Lancet 393, 1937–1947 (2019).

    Article  CAS  PubMed  Google Scholar 

  46. Symplicity, H. T. N. I. et al. Renal sympathetic denervation in patients with treatment-resistant hypertension (The Symplicity HTN-2 Trial): a randomised controlled trial. Lancet 376, 1903–1909 (2010).

    Article  Google Scholar 

  47. Bhatt, D. L. et al. A controlled trial of renal denervation for resistant hypertension. N. Engl. J. Med. 370, 1393–1401 (2014).

    Article  CAS  PubMed  Google Scholar 

  48. Howard, J. P. et al. Quantifying the 3 biases that lead to unintentional overestimation of the blood pressure-lowering effect of renal denervation. Circ. Cardiovasc. Qual. Outcomes 9, 14–22 (2016).

    Article  PubMed  Google Scholar 

  49. Meeker-O'Connell, A. et al. Enhancing clinical evidence by proactively building quality into clinical trials. Clin. Trials 13, 439–444 (2016).

    Article  PubMed  PubMed Central  Google Scholar 

  50. Pogue, J. M., Devereaux, P. J., Thorlund, K. & Yusuf, S. Central statistical monitoring: detecting fraud in clinical trials. Clin. Trials 10, 225–235 (2013).

    Article  PubMed  Google Scholar 

  51. 3C Study Collaborative Group. Campath, calcineurin inhibitor reduction, and chronic allograft nephropathy (the 3C Study) — results of a randomized controlled clinical trial. Am. J. Transpl. 18, 1424–1434 (2018).

    Article  CAS  Google Scholar 

  52. Ndounga Diakou, L. A. et al. Comparison of central adjudication of outcomes and onsite outcome assessment on treatment effect estimates. Cochrane Database Syst. Rev. 3, MR000043 (2016).

    PubMed  Google Scholar 

  53. Hlatky, M. A. et al. Use of Medicare data to identify coronary heart disease outcomes in the Women's Health Initiative. Circ. Cardiovasc. Qual. Outcomes 7, 157–162 (2014).

    Article  PubMed  PubMed Central  Google Scholar 

  54. Frobert, O. et al. Thrombus aspiration during ST-segment elevation myocardial infarction. N. Engl. J. Med. 369, 1587–1597 (2013).

    Article  CAS  PubMed  Google Scholar 

  55. Prentice, R. L. Surrogate endpoints in clinical trials: definition and operational criteria. Stat. Med. 8, 431–440 (1989).

    Article  CAS  PubMed  Google Scholar 

  56. Levey, A. S. et al. GFR decline as an end point for clinical trials in CKD: a scientific workshop sponsored by the National Kidney Foundation and the US food and drug administration. Am. J. Kidney Dis. 64, 821–835 (2014).

    Article  PubMed  Google Scholar 

  57. Fried, L. F. & Lewis, J. Albuminuria is not an appropriate therapeutic target in patients with CKD: the con view. Clin. J. Am. Soc. Nephrol. 10, 1089–1093 (2015).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  58. Lambers Heerspink, H. J. & Gansevoort, R. T. Albuminuria is an appropriate therapeutic target in patients with CKD: the pro view. Clin. J. Am. Soc. Nephrol. 10, 1079–1088 (2015).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  59. Heerspink, H. J. L. et al. Change in albuminuria as a surrogate endpoint for progression of kidney disease: a meta-analysis of treatment effects in randomised clinical trials. Lancet Diabetes Endocrinol. 7, 128–139 (2019).

    Article  CAS  PubMed  Google Scholar 

  60. Smith, M. et al. Change in albuminuria and risk of renal and cardiovascular outcomes: natural variation should be taken into account. Kidney Int. Rep. 3, 939–949 (2018).

    Article  PubMed  PubMed Central  Google Scholar 

  61. Thompson, A. et al. Proteinuria reduction as a surrogate end point in trials of IgA nephropathy. Clin. J. Am. Soc. Nephrol. 14, 469–481 (2019).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  62. Schluchter, M. D., Greene, T. & Beck, G. J. Analysis of change in the presence of informative censoring: application to a longitudinal clinical trial of progressive renal disease. Stat. Med. 20, 989–1007 (2001).

    Article  CAS  PubMed  Google Scholar 

  63. Vonesh, E. F., Greene, T. & Schluchter, M. D. Shared parameter models for the joint analysis of longitudinal data and event times. Stat. Med. 25, 143–163 (2006).

    Article  PubMed  Google Scholar 

  64. Kular, D. & Macdougall, I. C. HIF stabilizers in the management of renal anemia: from bench to bedside to pediatrics. Pediatr. Nephrol. 34, 365–378 (2019).

    Article  PubMed  Google Scholar 

  65. McMurray, J. J. et al. Angiotensin-neprilysin inhibition versus enalapril in heart failure. N. Engl. J. Med. 371, 993–1004 (2014).

    Article  PubMed  CAS  Google Scholar 

  66. Deo, A., Schmid, C. H., Earley, A., Lau, J. & Uhlig, K. Loss to analysis in randomized controlled trials in CKD. Am. J. Kidney Dis. 58, 349–355 (2011).

    Article  PubMed  Google Scholar 

  67. Coronary Drug Project Research Group. Influence of adherence to treatment and response of cholesterol on mortality in the coronary drug project. N. Engl. J. Med. 303, 1038–1041 (1980).

    Article  Google Scholar 

  68. Eijkelkamp, W. B. et al. Albuminuria is a target for renoprotective therapy independent from blood pressure in patients with type 2 diabetic nephropathy: post hoc analysis from the Reduction of Endpoints in NIDDM with the Angiotensin II Antagonist Losartan (RENAAL) trial. J. Am. Soc. Nephrol. 18, 1540–1546 (2007).

    Article  CAS  PubMed  Google Scholar 

  69. Heart Protection Study Collaborative Group. MRC/BHF Heart Protection Study of cholesterol lowering with simvastatin in 20,536 high-risk individuals: a randomised placebo-controlled trial. Lancet 360, 7–22 (2002).

    Article  Google Scholar 

  70. Schmidt, M. et al. Serum creatinine elevation after renin-angiotensin system blockade and long term cardiorenal risks: cohort study. BMJ 356, j791 (2017).

    Article  PubMed  PubMed Central  Google Scholar 

  71. Ohkuma, T. et al. Acute increases in serum creatinine after starting angiotensin-converting enzyme inhibitor-based therapy and effects of its continuation on major clinical outcomes in type 2 diabetes mellitus. Hypertension 73, 84–91 (2019).

    Article  CAS  PubMed  Google Scholar 

  72. Vickers, A. J. & Altman, D. G. Statistics notes: analysing controlled trials with baseline and follow up measurements. BMJ 323, 1123–1124 (2001).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  73. Dember, L. M. et al. Pragmatic trials in maintenance dialysis: perspectives from the kidney health initiative. J. Am. Soc. Nephrol. 27, 2955–2963 (2016).

    Article  PubMed  PubMed Central  Google Scholar 

  74. Hemming, K., Eldridge, S., Forbes, G., Weijer, C. & Taljaard, M. How to design efficient cluster randomised trials. BMJ 358, j3064 (2017).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  75. Torgerson, D. J. Contamination in trials: is cluster randomisation the answer? BMJ 322, 355–357 (2001).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  76. Eldridge, S., Kerry, S. & Torgerson, D. J. Bias in identifying and recruiting participants in cluster randomised trials: what can be done? BMJ 339, b4006 (2009).

    Article  PubMed  Google Scholar 

  77. Dember, L. M. et al. The time trial: a fully embedded, cluster-randomized, pragmatic trial of hemodialysis session duration. J. Am. Soc. Nephrol. 30, 890–903 (2019).

    Article  PubMed  PubMed Central  Google Scholar 

  78. Hemming, K., Haines, T. P., Chilton, P. J., Girling, A. J. & Lilford, R. J. The stepped wedge cluster randomised trial: rationale, design, analysis, and reporting. BMJ 350, h391 (2015).

    Article  CAS  PubMed  Google Scholar 

  79. Selby, N. M. et al. An organizational-level program of intervention for aki: a pragmatic stepped wedge cluster randomized trial. J. Am. Soc. Nephrol. 30, 505–515 (2019).

    Article  PubMed  PubMed Central  Google Scholar 

  80. Feldman, A. M. et al. Precision medicine for heart failure: lessons from oncology. Circ. Heart Fail. 10, e004202 (2017).

    Article  PubMed  PubMed Central  Google Scholar 

  81. Baigent, C. et al. Efficacy and safety of more intensive lowering of LDL cholesterol: a meta-analysis of data from 170,000 participants in 26 randomised trials. Lancet 376, 1670–1681 (2010).

    Article  CAS  PubMed  Google Scholar 

  82. Ruggenenti, P., Bettinaglio, P., Pinares, F. & Remuzzi, G. Angiotensin converting enzyme insertion/deletion polymorphism and renoprotection in diabetic and nondiabetic nephropathies. Clin. J. Am. Soc. Nephrol. 3, 1511–1525 (2008).

    Article  PubMed  PubMed Central  Google Scholar 

  83. de Zeeuw, D., Heerspink, H. J. L., Jardine, M. & Perkovic, V. Renal trials in diabetes need a platform: time for a global approach? Lancet Diabetes Endocrinol. 6, 356–358 (2018).

    Article  PubMed  Google Scholar 

  84. Heerspink, H. J. L. et al. Rationale and protocol of the Study of diabetic Nephropathy with Atrasentan (SONAR) trial: a clinical trial design novel to diabetic nephropathy. Diabetes Obes. Metab. 20, 1369–1376 (2018).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  85. Park, J. J., Thorlund, K. & Mills, E. J. Critical concepts in adaptive clinical trials. Clin. Epidemiol. 10, 343–351 (2018).

    Article  PubMed  PubMed Central  Google Scholar 

  86. Thorlund, K., Haggstrom, J., Park, J. J. & Mills, E. J. Key design considerations for adaptive clinical trials: a primer for clinicians. BMJ 360, k698 (2018).

    Article  PubMed  PubMed Central  Google Scholar 

  87. Mann, J. F. et al. Avosentan for overt diabetic nephropathy. J. Am. Soc. Nephrol. 21, 527–535 (2010).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  88. Hirakawa, A., Asano, J., Sato, H. & Teramukai, S. Master protocol trials in oncology: review and new trial designs. Contemp. Clin. Trials Commun. 12, 1–8 (2018).

    Article  PubMed  PubMed Central  Google Scholar 

  89. Renfro, L. A. & Sargent, D. J. Statistical controversies in clinical research: basket trials, umbrella trials, and other master protocols: a review and examples. Ann. Oncol. 28, 34–43 (2017).

    Article  CAS  PubMed  Google Scholar 

  90. Saville, B. R. & Berry, S. M. Efficiencies of platform clinical trials: a vision of the future. Clin. Trials 13, 358–366 (2016).

    Article  PubMed  Google Scholar 

  91. Heerspink, H. J. L. & Perkovic, V. Trial design innovations to accelerate therapeutic advances in chronic kidney disease: moving from single trials to an ongoing platform. Clin. J. Am. Soc. Nephrol. 13, 946–948 (2018).

    Article  PubMed  PubMed Central  Google Scholar 

  92. Butler, C. C. et al. A trial like ALIC(4)E: why design a platform, response-adaptive, open, randomised controlled trial of antivirals for influenza-like illness? ERJ Open Res. 4, 00046-2018 (2018).

    Article  PubMed  PubMed Central  Google Scholar 

  93. Landray, M. Improving public health by improving clinical trial guidelines and their application. Eur. Heart J. 38, 1632–1637 (2017).

    Article  PubMed  PubMed Central  Google Scholar 

  94. Sprosen, T. Major funders establish initiative to develop new trial guidelines. MoreTrials https://moretrials.net/major-funders-establish-initiative-develop-new-trial-guidelines/ (2019).

  95. Clinical Trials Transformation Initiative. Who We Are https://www.ctti-clinicaltrials.org/who-we-are (2019).

  96. Linde, P. G. et al. Overcoming barriers in kidney health-forging a platform for innovation. J. Am. Soc. Nephrol. 27, 1902–1910 (2016).

    Article  PubMed  PubMed Central  Google Scholar 

Download references

Acknowledgements

The Medical Research Council Population Health Research Unit at the University of Oxford is funded by the UK Medical Research Council. W.G.H. is funded by a Medical Research Council-Kidney Research UK Professor David Kerr Clinician Scientist Award.

Reviewer information

Nature Reviews Nephrology thanks M. Takeuchi and the other, anonymous, reviewer(s) for their contribution to the peer review of this work.

Author information

Authors and Affiliations

  1. Medical Research Council Population Health Research Unit at the University of Oxford, Clinical Trial Service Unit and Epidemiological Studies Unit (CTSU), Nuffield Department of Population Health, Oxford, UK

    William G. Herrington, Natalie Staplin & Richard Haynes

  2. Oxford Kidney Unit, Oxford University Hospitals NHS Foundation Trust, Oxford, UK

    William G. Herrington & Richard Haynes

Authors
  1. William G. Herrington
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Natalie Staplin
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Richard Haynes
    View author publications

    You can also search for this author in PubMed Google Scholar

Contributions

All authors researched the data for the article, contributed to discussions of the content, wrote the text and reviewed or edited the manuscript before submission.

Corresponding author

Correspondence to Richard Haynes.

Ethics declarations

Competing interests

W.G.H., R.H. and N.S. report grants to the Renal Studies Group at the University of Oxford from Novartis, Boehringer Ingelheim, and Pfizer. CTSU has a staff policy of not accepting honoraria or other payments from the pharmaceutical industry, except for the reimbursement of costs to participate in scientific meetings (www.ctsu.ox.ac.uk).

Additional information

Publisher’s note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Related links

Standardised Outcomes in Nephrology (SONG): http://songinitiative.org

Glossary

Propensity-score matching

A statistical matching technique employed in observational studies to reduce the potential for bias by factors that predict use of an intervention rather than the effect of the intervention. Elimination of such biases can only be ensured by randomization in a trial.

Mendelian randomization

(MR). A method of analysing observational study data in which allele variation in genes encoding risk factors or biomarkers are used to infer whether a risk factor may be a cause of disease. Such design requires assumptions but may control for biases (for example, reverse causation or confounding) that are inherent in classic observational studies.

Statistical tests for heterogeneity

In trials, this term refers to a statistical test of whether effects in a particular subgroup of participants differ significantly from the overall effect (for example, a chi-squared test).

Linear mixed models

Extension of simple linear models to include random effects (for example, patient-specific intercepts and/or slopes) to account for dependence between data points (such as multiple estimated glomerular filtration rate measurements from the same patient).

Shared parameter models

Statistical method that jointly models longitudinal data (using linear mixed models) and a censoring event (using a survival model) to enable unbiased estimation of a longitudinal outcome (for example, rate of decline in estimated glomerular filtration rate) in the presence of a non-ignorable dropout mechanism (in other words, patients are dropped from analyses for reasons related to their decline, such as end-stage renal disease or death).

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Herrington, W.G., Staplin, N. & Haynes, R. Kidney disease trials for the 21st century: innovations in design and conduct. Nat Rev Nephrol 16, 173–185 (2020). https://doi.org/10.1038/s41581-019-0212-x

Download citation

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1038/s41581-019-0212-x

This article is cited by

Search

Advanced search

Quick links

Nature Briefing

Sign up for the Nature Briefing newsletter — what matters in science, free to your inbox daily.

Get the most important science stories of the day, free in your inbox. Sign up for Nature Briefing