Student or educator? Sign up with your school email and get 6 months of Pro free.
Cited by 727

The DOI matches its Crossref record; 7 of the 7 references it cites were found in a registry or an index.

Sensitivity analysis and external adjustment for unmeasured confounders in epidemiologic database studies of therapeutics

Schneeweiss, Sebastian·2006·Pharmacoepidemiology and Drug Safety

Abstract

Background: Large health care utilization databases are frequently used to analyze unintended effects of prescription drugs and biologics. Confounders that require detailed information on clinical parameters, lifestyle, or over‐the‐counter medications are often not measured in such datasets, causing residual confounding bias. Objective: This paper provides a systematic approach to sensitivity analyses to investigate the impact of residual confounding in pharmacoepidemiologic studies that use health care utilization databases. Methods: Four basic approaches to sensitivity analysis were identified: (1) sensitivity analyses based on an array of informed assumptions; (2) analyses to identify the strength of residual confounding that would be necessary to explain an observed drug‐outcome association; (3) external adjustment of a drug‐outcome association given additional information on single binary confounders from survey data using algebraic solutions; (4) external adjustment considering the joint distribution of multiple confounders of any distribution from external sources of information using propensity score calibration. Conclusion: Sensitivity analyses and external adjustments can improve our understanding of the effects of drugs and biologics in epidemiologic database studies. With the availability of easy‐to‐apply techniques, sensitivity analyses should be used more frequently, substituting qualitative discussions of residual confounding. Copyright © 2006 John Wiley & Sons, Ltd.

Overview

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.1002/pds.1200

Cites

7 of 7 references verified0 citation errors · 0 not checkable

Statistics

Verification

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Citations

Cites

Show all 7 references

Research works printed but not linked: 48

  1. 10.1097/00001648-200101000-00019 · DOI
  2. 10.1016/S0140-6736(00)04017-4 · DOI
  3. 10.1016/j.jclinepi.2004.10.012 · DOI · Paper page
  4. Walker AM, 1996, Confounding by indication, Epidemiology, 7, 335
  5. West SL, 2000, Pharmacoepidemiology, 668
  6. 10.1007/BF00386579 · DOI
  7. Schlesselman JJ, 1978, Assessing effects of confounding variables, Am J Epidemiol, 108, 3
  8. 10.1016/S0010-7824(98)00014-6 · DOI
  9. 10.1111/j.1532-5415.2001.49280.x · DOI · Paper page
  10. 10.1111/j.1532-5415.1999.tb01603.x · DOI · Paper page
  11. 10.1002/ajim.4700130108 · DOI
  12. 10.1016/j.jclinepi.2004.06.002 · DOI
  13. 10.1002/sim.4780100409 · DOI
  14. 10.1136/gut.52.9.1265 · DOI
  15. 10.1056/NEJM200011233432103 · DOI · Paper page
  16. 10.1001/jama.284.10.1247 · DOI · Paper page
  17. 10.2165/00002018-200427060-00005 · DOI · Paper page
  18. 10.1093/aje/154.6.557 · DOI
  19. Wolfe F, 2002, Increase in lifetime adverse drug reactions, service utilization, and disease severity among patients who will start COX‐2 specific inhibitors: quantitative assessment of channeling bias and confounding by indication in 6689 patients with rheumatoid arthritis and osteoarthritis, J Rheumatol, 29, 1015
  20. 10.1016/0021-9681(66)90062-2 · DOI · Paper page
  21. 10.1097/01.EDE.0000071419.41011.cf · DOI · Paper page
  22. 10.1111/j.0006-341X.1999.1316_1.x · DOI
  23. Walker AM, 1991, Observation an Inference, 120
  24. 10.1001/jama.1995.03530080036038 · DOI · Paper page
  25. 10.7326/0003-4819-123-11-199512010-00015 · DOI
  26. 10.1177/096228029500400403 · DOI
  27. 10.1097/01.ede.0000147164.11879.b5 · DOI
  28. 10.1093/gerona/55.12.M750 · DOI
  29. Eppig FJ, 1997, Matching MCBS and medicare data: the best of both worlds, Health Care Financ Rev, 18, 211
  30. 10.1097/01.jcp.0000145344.76288.39 · DOI
  31. 10.1111/j.1532-5415.2005.53303.x · DOI
  32. 10.1161/01.CIR.0000127578.21885.3E · DOI · Paper page
  33. Adler GS, 1994, A profile of the Medicare Current Beneficiary Survey, Health Care Financ Rev, 15, 153
  34. Adler GS, 1995, Medicare beneficiaries rate their medical care, Health Care Financ Rev, 16, 175
  35. 10.1093/aje/kwi192 · DOI
  36. 10.1093/oxfordjournals.aje.a115715 · DOI · Paper page
  37. Sturmer T, 2005, Performance of propensity score calibration (PSC), Am J Epidemiol, 161, S75, 10.1093/aje/161.Supplement_1.S75a · doi:10.1093/aje/161.supplement_1.s75a
  38. 10.2307/2529883 · DOI
  39. 10.1093/oxfordjournals.aje.a115074 · DOI
  40. 10.1002/sim.4780100509 · DOI
  41. 10.1002/sim.4780100410 · DOI · Paper page
  42. Strom BL, 2000, Pharmacoepidemiology, 10.1002/0470842555 · DOI
  43. 10.1093/aje/kwh211 · DOI · Paper page
  44. 10.1097/00001648-200009000-00010 · DOI
  45. 10.1097/01.ede.0000072106.65262.ae · DOI · Paper page
  46. 10.1002/art.20311 · DOI · Paper page
  47. 10.1136/ard.2004.030528 · DOI · Paper page
  48. 10.1136/bmj.317.7152.180 · DOI · Paper page

Cited by

See all 727

Metadata

Authors
Schneeweiss, S.
Venue
Pharmacoepidemiology and Drug Safety
Publisher
Wiley
Published
2006-01-31
Volume
15
Issue
5
Pages
291-303
ISSN
  • 1053-8569 (ISSN-L)
  • 1099-1557
OpenAlex
W2082081076
Cited by
727
References
7
FWCI
18.30
Type
journal article
Language
en
Open access
closed

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review

How to cite

Cite CoChat for the checks on this page, and the paper for its own findings.

This page
CoChat. (2026). Citation check: Sensitivity analysis and external adjustment for unmeasured confounders in epidemiologic database studies of therapeutics. https://app.cochat.ai/papers/10.1002/pds.1200
The paper
Schneeweiss, S. (2006). Sensitivity analysis and external adjustment for unmeasured confounders in epidemiologic database studies of therapeutics. Pharmacoepidemiology and Drug Safety. https://doi.org/10.1002/pds.1200

Data sources

Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.