What ever happened to N-of-1 trials? Insiders' perspectives and a look to the future

Richard L Kravitz, Naihua Duan, Edmund J. Niedzinski, M. Cameron Hay, Saskia K. Subramanian, Thomas S. Weisner

Research output: Contribution to journalArticle

51 Citations (Scopus)

Abstract

Context: When feasible, randomized, blinded single-patient (n-of-1) trials are uniquely capable of establishing the best treatment in an individual patient. Despite early enthusiasm, by the turn of the twenty-first century, few academic centers were conducting n-of-1 trials on a regular basis. Methods: The authors reviewed the literature and conducted in-depth telephone interviews with leaders in the n-of-1 trial movement. Findings: N-of-1 trials can improve care by increasing therapeutic precision. However, they have not been widely adopted, in part because physicians do not sufficiently value the reduction in uncertainty they yield weighed against the inconvenience they impose. Limited evidence suggests that patients may be receptive to n-of-1 trials once they understand the benefits. Conclusions: N-of-1 trials offer a unique opportunity to individualize clinical care and enrich clinical research. While ongoing changes in drug discovery, manufacture, and marketing may ultimately spur pharmaceutical makers and health care payers to support n-of-1 trials, at present the most promising resuscitation strategy is stripping n-of-1 trials to their essentials and marketing them directly to patients. In order to optimize statistical inference from these trials, empirical Bayes methods can be used to combine individual patient data with aggregate data from comparable patients.

Original languageEnglish (US)
Pages (from-to)533-555
Number of pages23
JournalMilbank Quarterly
Volume86
Issue number4
DOIs
StatePublished - Dec 2008

Fingerprint

Marketing
Pharmaceutical Services
Drug Discovery
Resuscitation
Uncertainty
Interviews
Delivery of Health Care
Physicians
Therapeutics
Research

Keywords

  • Bayesian methods
  • Clinical effectiveness
  • N-of-1 trial
  • Personalized medicine
  • Research policy
  • Treatment effects heterogeneity

ASJC Scopus subject areas

  • Public Health, Environmental and Occupational Health
  • Health Policy

Cite this

What ever happened to N-of-1 trials? Insiders' perspectives and a look to the future. / Kravitz, Richard L; Duan, Naihua; Niedzinski, Edmund J.; Hay, M. Cameron; Subramanian, Saskia K.; Weisner, Thomas S.

In: Milbank Quarterly, Vol. 86, No. 4, 12.2008, p. 533-555.

Research output: Contribution to journalArticle

Kravitz, RL, Duan, N, Niedzinski, EJ, Hay, MC, Subramanian, SK & Weisner, TS 2008, 'What ever happened to N-of-1 trials? Insiders' perspectives and a look to the future', Milbank Quarterly, vol. 86, no. 4, pp. 533-555. https://doi.org/10.1111/j.1468-0009.2008.00533.x
Kravitz, Richard L ; Duan, Naihua ; Niedzinski, Edmund J. ; Hay, M. Cameron ; Subramanian, Saskia K. ; Weisner, Thomas S. / What ever happened to N-of-1 trials? Insiders' perspectives and a look to the future. In: Milbank Quarterly. 2008 ; Vol. 86, No. 4. pp. 533-555.
@article{20ba652ddaee48c0b2aea4e07c67a77b,
title = "What ever happened to N-of-1 trials? Insiders' perspectives and a look to the future",
abstract = "Context: When feasible, randomized, blinded single-patient (n-of-1) trials are uniquely capable of establishing the best treatment in an individual patient. Despite early enthusiasm, by the turn of the twenty-first century, few academic centers were conducting n-of-1 trials on a regular basis. Methods: The authors reviewed the literature and conducted in-depth telephone interviews with leaders in the n-of-1 trial movement. Findings: N-of-1 trials can improve care by increasing therapeutic precision. However, they have not been widely adopted, in part because physicians do not sufficiently value the reduction in uncertainty they yield weighed against the inconvenience they impose. Limited evidence suggests that patients may be receptive to n-of-1 trials once they understand the benefits. Conclusions: N-of-1 trials offer a unique opportunity to individualize clinical care and enrich clinical research. While ongoing changes in drug discovery, manufacture, and marketing may ultimately spur pharmaceutical makers and health care payers to support n-of-1 trials, at present the most promising resuscitation strategy is stripping n-of-1 trials to their essentials and marketing them directly to patients. In order to optimize statistical inference from these trials, empirical Bayes methods can be used to combine individual patient data with aggregate data from comparable patients.",
keywords = "Bayesian methods, Clinical effectiveness, N-of-1 trial, Personalized medicine, Research policy, Treatment effects heterogeneity",
author = "Kravitz, {Richard L} and Naihua Duan and Niedzinski, {Edmund J.} and Hay, {M. Cameron} and Subramanian, {Saskia K.} and Weisner, {Thomas S.}",
year = "2008",
month = "12",
doi = "10.1111/j.1468-0009.2008.00533.x",
language = "English (US)",
volume = "86",
pages = "533--555",
journal = "Milbank Quarterly",
issn = "0887-378X",
publisher = "Wiley-Blackwell",
number = "4",

}

TY - JOUR

T1 - What ever happened to N-of-1 trials? Insiders' perspectives and a look to the future

AU - Kravitz, Richard L

AU - Duan, Naihua

AU - Niedzinski, Edmund J.

AU - Hay, M. Cameron

AU - Subramanian, Saskia K.

AU - Weisner, Thomas S.

PY - 2008/12

Y1 - 2008/12

N2 - Context: When feasible, randomized, blinded single-patient (n-of-1) trials are uniquely capable of establishing the best treatment in an individual patient. Despite early enthusiasm, by the turn of the twenty-first century, few academic centers were conducting n-of-1 trials on a regular basis. Methods: The authors reviewed the literature and conducted in-depth telephone interviews with leaders in the n-of-1 trial movement. Findings: N-of-1 trials can improve care by increasing therapeutic precision. However, they have not been widely adopted, in part because physicians do not sufficiently value the reduction in uncertainty they yield weighed against the inconvenience they impose. Limited evidence suggests that patients may be receptive to n-of-1 trials once they understand the benefits. Conclusions: N-of-1 trials offer a unique opportunity to individualize clinical care and enrich clinical research. While ongoing changes in drug discovery, manufacture, and marketing may ultimately spur pharmaceutical makers and health care payers to support n-of-1 trials, at present the most promising resuscitation strategy is stripping n-of-1 trials to their essentials and marketing them directly to patients. In order to optimize statistical inference from these trials, empirical Bayes methods can be used to combine individual patient data with aggregate data from comparable patients.

AB - Context: When feasible, randomized, blinded single-patient (n-of-1) trials are uniquely capable of establishing the best treatment in an individual patient. Despite early enthusiasm, by the turn of the twenty-first century, few academic centers were conducting n-of-1 trials on a regular basis. Methods: The authors reviewed the literature and conducted in-depth telephone interviews with leaders in the n-of-1 trial movement. Findings: N-of-1 trials can improve care by increasing therapeutic precision. However, they have not been widely adopted, in part because physicians do not sufficiently value the reduction in uncertainty they yield weighed against the inconvenience they impose. Limited evidence suggests that patients may be receptive to n-of-1 trials once they understand the benefits. Conclusions: N-of-1 trials offer a unique opportunity to individualize clinical care and enrich clinical research. While ongoing changes in drug discovery, manufacture, and marketing may ultimately spur pharmaceutical makers and health care payers to support n-of-1 trials, at present the most promising resuscitation strategy is stripping n-of-1 trials to their essentials and marketing them directly to patients. In order to optimize statistical inference from these trials, empirical Bayes methods can be used to combine individual patient data with aggregate data from comparable patients.

KW - Bayesian methods

KW - Clinical effectiveness

KW - N-of-1 trial

KW - Personalized medicine

KW - Research policy

KW - Treatment effects heterogeneity

UR - http://www.scopus.com/inward/record.url?scp=56649123410&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=56649123410&partnerID=8YFLogxK

U2 - 10.1111/j.1468-0009.2008.00533.x

DO - 10.1111/j.1468-0009.2008.00533.x

M3 - Article

VL - 86

SP - 533

EP - 555

JO - Milbank Quarterly

JF - Milbank Quarterly

SN - 0887-378X

IS - 4

ER -