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Exploiting Clinical Decision-making Thresholds to Recover Causal Effects From Observational Data

Exploiting Clinical Decision-making Thresholds to Recover Causal Effects From Observational Data Clinical Decision-making Thresholds for Recovering Effects From Observational Data Invited Commentary Invited Commentary Exploiting Clinical Decision-making Thresholds to Recover Causal Effects From Observational Data Randomization Without Trials Vinay Guduguntla, MD; J. Michael McWilliams, MD, PhD Randomized clinical trials (RCTs) are the gold standard of study minimizing the need to measure and control for confound- design because randomization ensures that differences in ers. Despite rapidly growing use of quasi-experimental meth- outcomes between a treatment and control group reflect the ods in other fields, adoption in clinical research has been slow. causal effect of treatment. Although RCTs greatly benefit In this issue of JAMA Internal Medicine, Goulden et al science and society for this reason, they often cannot be con- (a multidisciplinary team of clinicians and economists) use ducted because of logistical, ethical, or resource constraints. a regression discontinuity design to estimate the effect of Researchers are thus confronted with many questions left intravenous (IV) contrast on kidney function. They exploit a unanswered. D-dimer threshold commonly used to guide use of computed To answer those questions, clinical investigators have tra- tomographic pulmonary angiography (CTPA). Because pa- ditionally turned to straightforward observational compari- tients with D-dimer values just above vs below the http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png JAMA Internal Medicine American Medical Association

Exploiting Clinical Decision-making Thresholds to Recover Causal Effects From Observational Data

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Exploiting Clinical Decision-making Thresholds to Recover Causal Effects From Observational Data

Abstract

Clinical Decision-making Thresholds for Recovering Effects From Observational Data Invited Commentary Invited Commentary Exploiting Clinical Decision-making Thresholds to Recover Causal Effects From Observational Data Randomization Without Trials Vinay Guduguntla, MD; J. Michael McWilliams, MD, PhD Randomized clinical trials (RCTs) are the gold standard of study minimizing the need to measure and control for confound- design because randomization ensures that differences in ers. Despite...
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Publisher
American Medical Association
Copyright
Copyright 2021 American Medical Association. All Rights Reserved.
ISSN
2168-6106
eISSN
2168-6114
DOI
10.1001/jamainternmed.2021.0923
Publisher site
See Article on Publisher Site

Abstract

Clinical Decision-making Thresholds for Recovering Effects From Observational Data Invited Commentary Invited Commentary Exploiting Clinical Decision-making Thresholds to Recover Causal Effects From Observational Data Randomization Without Trials Vinay Guduguntla, MD; J. Michael McWilliams, MD, PhD Randomized clinical trials (RCTs) are the gold standard of study minimizing the need to measure and control for confound- design because randomization ensures that differences in ers. Despite rapidly growing use of quasi-experimental meth- outcomes between a treatment and control group reflect the ods in other fields, adoption in clinical research has been slow. causal effect of treatment. Although RCTs greatly benefit In this issue of JAMA Internal Medicine, Goulden et al science and society for this reason, they often cannot be con- (a multidisciplinary team of clinicians and economists) use ducted because of logistical, ethical, or resource constraints. a regression discontinuity design to estimate the effect of Researchers are thus confronted with many questions left intravenous (IV) contrast on kidney function. They exploit a unanswered. D-dimer threshold commonly used to guide use of computed To answer those questions, clinical investigators have tra- tomographic pulmonary angiography (CTPA). Because pa- ditionally turned to straightforward observational compari- tients with D-dimer values just above vs below the

Journal

JAMA Internal Medicine – American Medical Association

Published: Jun 5, 2021

References

  • Regression discontinuity designs are underutilized in medicine, epidemiology, and public health: a review of current and best practice
    Moscoe, E; Bor, J; Bärnighausen, T
  • Association of intravenous radiocontrast with kidney function:a quasi-experimental study using regression discontinuity
    Goulden, R; Rowe, BH; Abrahamowicz, M; Strumpf, E; Tamblyn, R
  • Regression discontinuity design
    Maciejewski, ML; Basu, A
  • Efficacy of prostate-specific antigen screening: use of regression discontinuity in the PLCO cancer screening trial
    Shoag, J; Halpern, J; Eisner, B
  • Association of the National Health Guidance Intervention for Obesity and cardiovascular risks with health outcomes among Japanese men
    Fukuma, S; Iizuka, T; Ikenoue, T; Tsugawa, Y
  • What difference does a diagnosis make? evidence from marginal patients
    Alalouf, M; Miller, S; Wherry, L

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