dc.contributor.author | Schierenberg, Alwin | |
dc.contributor.author | Minnaard, Margaretha C. | |
dc.contributor.author | Hopstaken, Rogier M. | |
dc.contributor.author | Van De Pol, Alma C. | |
dc.contributor.author | Broekhuizen, Berna D.L. | |
dc.contributor.author | De Wit, Niek J. | |
dc.contributor.author | Reitsma, Johannes B. | |
dc.contributor.author | Van Vugt, Saskia F. | |
dc.contributor.author | Graffelman, Aleida W. | |
dc.contributor.author | Melbye, Hasse | |
dc.contributor.author | Rainer, Timothy H. | |
dc.contributor.author | Steurer, Johann | |
dc.contributor.author | Holm, Anette | |
dc.contributor.author | Gonzales, Ralph | |
dc.contributor.author | Dinant, Geert-Jan | |
dc.contributor.author | De Groot, Joris A.H. | |
dc.contributor.author | Verheij, Theo J.M. | |
dc.date.accessioned | 2017-02-22T14:40:49Z | |
dc.date.available | 2017-02-22T14:40:49Z | |
dc.date.issued | 2016-02-26 | |
dc.description.abstract | Background:<br>
Pneumonia remains difficult to diagnose in primary care. Prediction models based on signs
and symptoms (S&S) serve to minimize the diagnostic uncertainty. External validation of
these models is essential before implementation into routine practice. In this study all published
S&S models for prediction of pneumonia in primary care were externally validated in
the individual patient data (IPD) of previously performed diagnostic studies.<br>
Methods and Findings:<br>
S&S models for diagnosing pneumonia in adults presenting to primary care with lower respiratory
tract infection and IPD for validation were identified through a systematical search.
Six prediction models and IPD of eight diagnostic studies (N total = 5308, prevalence pneumonia
12%) were included. Models were assessed on discrimination and calibration. Discrimination
was measured using the pooled Area Under the Curve (AUC) and delta AUC,
representing the performance of an individual model relative to the average dataset performance.
Prediction models by van Vugt et al. and Heckerling et al. demonstrated the highest
pooled AUC of 0.79 (95% CI 0.74–0.85) and 0.72 (0.68–0.76), respectively. Other models
by Diehr et al., Singal et al., Melbye et al., and Hopstaken et al. demonstrated pooled AUCs
of 0.65 (0.61–0.68), 0.64 (0.61–0.67), 0.56 (0.49–0.63) and 0.53 (0.5–0.56), respectively. A
similar ranking was present based on the delta AUCs of the models. Calibration demonstrated
close agreement of observed and predicted probabilities in the models by van Vugt
et al. and Singal et al., other models lacked such correspondence. The absence of predictors
in the IPD on dataset level hampered a systematical comparison of model performance
and could be a limitation to the study.<br>
Conclusions:<br>
The model by van Vugt et al. demonstrated the highest discriminative accuracy coupled
with reasonable to good calibration across the IPD of different study populations. This
model is therefore the main candidate for primary care use. | en_US |
dc.description | Source: <a href=http://dx.doi.org/10.1371/journal.pone.0149895>doi: 10.1371/journal.pone.0149895</a> | en_US |
dc.identifier.citation | Schierenberg A, Minnaard MC, Hopstaken RM, van de Pol AC, Broekhuizen BDL, de Wit NJ, et al. (2016) External Validation of Prediction Models for Pneumonia in Primary Care Patients with Lower Respiratory Tract Infection: An Individual Patient Data Meta-Analysis. PLoS ONE 11(2): e0149895. doi:10.1371/journal.pone.0149895 | en_US |
dc.identifier.cristinID | FRIDAID 1418820 | |
dc.identifier.doi | 10.1371/journal.pone.0149895 | |
dc.identifier.issn | 1932-6203 | |
dc.identifier.uri | https://hdl.handle.net/10037/10343 | |
dc.language.iso | eng | en_US |
dc.publisher | Public Library of Science | en_US |
dc.relation.journal | PLoS ONE | |
dc.rights.accessRights | openAccess | en_US |
dc.subject | VDP::Medisinske Fag: 700::Helsefag: 800::Samfunnsmedisin, sosialmedisin: 801 | en_US |
dc.subject | VDP::Medical disciplines: 700::Health sciences: 800::Community medicine, Social medicine: 801 | en_US |
dc.title | External validation of prediction models for pneumonia in primary care patients with lower respiratory tract infection: An individual patient data meta-analysis | en_US |
dc.type | Journal article | en_US |
dc.type | Tidsskriftartikkel | en_US |
dc.type | Peer reviewed | en_US |