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Comparison between treatment effects in a randomised controlled trial and an observational study using propensity scores in primary care

Comparison between treatment effects in a randomised controlled trial and an observational study using propensity scores in primary care
Comparison between treatment effects in a randomised controlled trial and an observational study using propensity scores in primary care

Background Although randomized controlled trials(RCT) are considered “gold standard” evidence, they are not always feasible or appropriate and may represent a select population. Observational studies provide a useful alternative to enhance applicability, but results can be biased due to confounding.

Aim To explore the utility of propensity scores for causal inference in an observational study

Design and Setting Comparison of the effect of amoxicillin on key outcomes in an international trial and observational study of lower respiratory tract infections.

Method Propensity scores were calculated and applied as probability weights in the analyses. The adjusted results were compared to the effects reported in the RCT.

Results Groups were well balanced in the RCT but significantly imbalanced in the observational study, with evidence of confounding by indication; patients receiving antibiotics tended to be older and more unwell at baseline consultation. In the trial duration of symptoms (hazard ratio 1.06, 95% CI 0.96 - 1.18) and symptoms severity (-0.07) 95% CI -0.15, 0.007) did not differ between groups. Weighting by propensity score in the observational study resulted in very similar estimates of effect: hazard ratios for duration of symptoms (1.06 95% CI 0.80-1.40) and difference for symptom severity -0.07 (95% CI -0.34- 0.20).

Conclusion The observational study, after conditioning on propensity score, echoed the trial results. Provided that detailed information is available on potential sources of confounding, effects of interventions can probably be assessed reasonably well in observational data sets, allowing them to be more directly compared with the results of RCTs.

0960-1643
e643-e649
Stuart, Beth L.
626862fc-892b-4f6d-9cbb-7a8d7172b209
Grebel, Louise E.N.
310c1a76-e5b2-475a-9bdd-b348d2efe8c6
Butler, Christopher C.
736f78ad-3e18-4c63-900f-c2249577b645
Hood, Kerenza
62906d76-4931-4b12-9a64-0c867c7b84c1
Verheij, Theo
772e019f-486f-4a64-9260-bac6446a85d2
Little, Paul
1bf2d1f7-200c-47a5-ab16-fe5a8756a777
Stuart, Beth L.
626862fc-892b-4f6d-9cbb-7a8d7172b209
Grebel, Louise E.N.
310c1a76-e5b2-475a-9bdd-b348d2efe8c6
Butler, Christopher C.
736f78ad-3e18-4c63-900f-c2249577b645
Hood, Kerenza
62906d76-4931-4b12-9a64-0c867c7b84c1
Verheij, Theo
772e019f-486f-4a64-9260-bac6446a85d2
Little, Paul
1bf2d1f7-200c-47a5-ab16-fe5a8756a777

Stuart, Beth L., Grebel, Louise E.N., Butler, Christopher C., Hood, Kerenza, Verheij, Theo and Little, Paul (2017) Comparison between treatment effects in a randomised controlled trial and an observational study using propensity scores in primary care. British Journal of General Practice, 67 (662), e643-e649. (doi:10.3399/bjgp17X692153).

Record type: Article

Abstract

Background Although randomized controlled trials(RCT) are considered “gold standard” evidence, they are not always feasible or appropriate and may represent a select population. Observational studies provide a useful alternative to enhance applicability, but results can be biased due to confounding.

Aim To explore the utility of propensity scores for causal inference in an observational study

Design and Setting Comparison of the effect of amoxicillin on key outcomes in an international trial and observational study of lower respiratory tract infections.

Method Propensity scores were calculated and applied as probability weights in the analyses. The adjusted results were compared to the effects reported in the RCT.

Results Groups were well balanced in the RCT but significantly imbalanced in the observational study, with evidence of confounding by indication; patients receiving antibiotics tended to be older and more unwell at baseline consultation. In the trial duration of symptoms (hazard ratio 1.06, 95% CI 0.96 - 1.18) and symptoms severity (-0.07) 95% CI -0.15, 0.007) did not differ between groups. Weighting by propensity score in the observational study resulted in very similar estimates of effect: hazard ratios for duration of symptoms (1.06 95% CI 0.80-1.40) and difference for symptom severity -0.07 (95% CI -0.34- 0.20).

Conclusion The observational study, after conditioning on propensity score, echoed the trial results. Provided that detailed information is available on potential sources of confounding, effects of interventions can probably be assessed reasonably well in observational data sets, allowing them to be more directly compared with the results of RCTs.

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BJGP-2016-0590R1 - Accepted Manuscript
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More information

Accepted/In Press date: 23 February 2017
e-pub ahead of print date: 31 August 2017
Organisations: Primary Care & Population Sciences

Identifiers

Local EPrints ID: 407621
URI: http://eprints.soton.ac.uk/id/eprint/407621
ISSN: 0960-1643
PURE UUID: df295c3e-3aed-4c7e-a189-ec8e4707ce33
ORCID for Beth L. Stuart: ORCID iD orcid.org/0000-0001-5432-7437
ORCID for Paul Little: ORCID iD orcid.org/0000-0003-3664-1873

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Date deposited: 16 Apr 2017 17:05
Last modified: 12 Jul 2024 04:08

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Contributors

Author: Beth L. Stuart ORCID iD
Author: Louise E.N. Grebel
Author: Christopher C. Butler
Author: Kerenza Hood
Author: Theo Verheij
Author: Paul Little ORCID iD

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