Literature DB >> 28760739

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

Beth L Stuart1, Louise En Grebel2, Christopher C Butler3, Kerenza Hood4, Theo J M Verheij2, Paul Little1.   

Abstract

BACKGROUND: Although randomised controlled trials (RCTs) 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 RCT 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 with 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 to 1.18) and symptom severity (-0.07, 95% CI = -0.15 to 0.007) did not differ between groups. Weighting by propensity score in the observational study resulted in very similar estimates of effect: duration of symptoms (hazard ratio 1.06, 95% CI = 0.80 to 1.40) and difference for symptom severity (-0.07, 95% CI = -0.34 to 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 datasets, allowing them to be more directly compared with the results of RCTs. © British Journal of General Practice 2017.

Entities:  

Keywords:  antibiotics; observational study; primary health care; propensity score; randomised controlled trial; respiratory tract infection

Mesh:

Substances:

Year:  2017        PMID: 28760739      PMCID: PMC5569744          DOI: 10.3399/bjgp17X692153

Source DB:  PubMed          Journal:  Br J Gen Pract        ISSN: 0960-1643            Impact factor:   5.386


  24 in total

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Authors:  S T Normand; M B Landrum; E Guadagnoli; J Z Ayanian; T J Ryan; P D Cleary; B J McNeil
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Review 2.  Principles for modeling propensity scores in medical research: a systematic literature review.

Authors:  Sherry Weitzen; Kate L Lapane; Alicia Y Toledano; Anne L Hume; Vincent Mor
Journal:  Pharmacoepidemiol Drug Saf       Date:  2004-12       Impact factor: 2.890

Review 3.  Methods to assess intended effects of drug treatment in observational studies are reviewed.

Authors:  Olaf H Klungel; Edwin P Martens; Bruce M Psaty; Diederik E Grobbee; Sean D Sullivan; Bruno H Ch Stricker; Hubert G M Leufkens; A de Boer
Journal:  J Clin Epidemiol       Date:  2004-12       Impact factor: 6.437

4.  Bayesian propensity score analysis for observational data.

Authors:  Lawrence C McCandless; Paul Gustafson; Peter C Austin
Journal:  Stat Med       Date:  2009-01-15       Impact factor: 2.373

5.  Observational studies are complementary to randomized controlled trials.

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6.  Propensity score methods for bias reduction in the comparison of a treatment to a non-randomized control group.

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Review 7.  Medication use in European primary care patients with lower respiratory tract infection: an observational study.

Authors:  Marleen Hamoen; Berna D L Broekhuizen; Paul Little; Hasse Melbye; Samuel Coenen; Herman Goossens; Chris C Butler; Nick A Francis; Theo J M Verheij
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8.  Randomised controlled trials: balance in baseline characteristics.

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Journal:  BMJ       Date:  2014-09-19

9.  Antibiotics for acute cough: an international observational study of patient adherence in primary care.

Authors:  Nick A Francis; David Gillespie; Jacqueline Nuttall; Kerenza Hood; Paul Little; Theo Verheij; Samuel Coenen; Jochen W Cals; Herman Goossens; Christopher C Butler
Journal:  Br J Gen Pract       Date:  2012-06       Impact factor: 5.386

10.  Propensity score techniques and the assessment of measured covariate balance to test causal associations in psychological research.

Authors:  Valerie S Harder; Elizabeth A Stuart; James C Anthony
Journal:  Psychol Methods       Date:  2010-09
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3.  Impact of antibiotics for children presenting to general practice with cough on adverse outcomes: secondary analysis from a multicentre prospective cohort study.

Authors:  Niamh M Redmond; Sophie Turnbull; Beth Stuart; Hannah V Thornton; Hannah Christensen; Peter S Blair; Brendan C Delaney; Matthew Thompson; Tim J Peters; Alastair D Hay; Paul Little
Journal:  Br J Gen Pract       Date:  2018-09-10       Impact factor: 5.386

4.  The premature closure of ROMPA clinical trial: mortality reduction in septic shock by plasma adsorption.

Authors:  Carola Giménez-Esparza; Cristina Portillo-Requena; Francisco Colomina-Climent; José Manuel Allegue-Gallego; María Galindo-Martínez; Cristina Mollà-Jiménez; José Luis Antón-Pascual; Enrique Mármol-Peis; Cristina Dólera-Moreno; Manuel Rodríguez-Serra; José Luis Martín-Ruíz; Pablo Juan Fernández-Arroyo; Eugenia María Blasco-Císcar; José Cánovas-Robles; Enrique González-Hernández; Fernando Sánchez-Morán; Manuel Solera-Suárez; Jesús Torres-Tortajada; Antonio Palazón-Bru; Vicente F Gil-Guillen
Journal:  BMJ Open       Date:  2019-12-03       Impact factor: 2.692

  4 in total

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