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Med Decis Making. 2012 Jan-Feb;32(1):83-92. doi: 10.1177/0272989X11416512. Epub 2011 Aug 21.

Efficacy of phototherapy for newborns with hyperbilirubinemia: a cautionary example of an instrumental variable analysis.

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  • 1Department of Epidemiology and Biostatistics, Division of Clinical Epidemiology, University of California, San Francisco, CA 94143, USA.



Use of instrumental variables is gaining popularity as a method of controlling for confounding by indication in observational studies of treatments.


To illustrate how unmeasured instrument-level treatment substitution can distort effect size estimates using as an example an instrumental variable analysis of phototherapy for neonatal jaundice.


Retrospective cohort study.


Northern California Kaiser Permanente Hospitals.


The authors studied 20,731 newborns ≥ 2000 g and ≥ 35 weeks' gestation born 1995-2004 with a "qualifying" total serum bilirubin (TSB) level within 3 mg/dL of the 2004 American Academy of Pediatrics (AAP) phototherapy threshold who did not have a positive direct antiglobulin test.


The intervention was inpatient phototherapy within 8 hours of the qualifying TSB. The outcome was a TSB level exceeding the AAP exchange transfusion threshold <48 hours from the qualifying TSB. The instrumental variable was a measure of the frequency of phototherapy use at the newborn's birth hospital. The unmeasured substituted treatment was supplementation with infant formula, assessed by chart review in a sample from the same cohort.


In total, 128 infants (0.62%) exceeded the exchange transfusion threshold. Logistic and propensity analyses yielded crude odds ratios of ~0.5 for phototherapy efficacy, decreasing to ~0.2 with control for confounding by indication. Instrumental variable analyses suggested much greater phototherapy efficacy (e.g., odds ratios of 0.02-0.05). However, chart reviews revealed greater use of infant formula (which also lowers bilirubin levels) in hospitals that used more phototherapy (r = 0.56; P = 0.02), an association not present at the individual level (r = 0.13).


Instrumental variable analyses may provide biased estimates of treatment efficacy if there are cointerventions or confounders associated with treatment at the level of the instrument, although even when these associations may not exist in individuals.

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