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open access
14 September 2016
Dear Editor,
External
validation studies of prediction models are of utmost importance in
order to assess the performance of a prediction model in different
locations (Altman et al., 2009). We therefore read with interest the recent external validation study of the ADNEX model (Szubert et al., 2016)......
Ref: Szubert et al., 2016
- External validation of the IOTA ADNEX model performed by two independent gynecologic centers
- Gynecol. Oncol. (2016)
Highlights (abstract)
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- We performed external validation of IOTA ADNEX model in two European centers.
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- The study confirms high discrimination accuracy of the ADNEX model.
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- The prediction of specific tumor type had moderate performance.
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- The results were comparable to original IOTA report and similar between two centers.
References
- Altman et al., 2009
- Prognosis and prognostic research: validating a prognostic model
- BMJ, 338 (2009), p. b605
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- Collins et al., 2016
- Sample size considerations for the external validation of a multivariable prognostic model: a resampling study
- Stat. Med., 35 (2016), pp. 214–226
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- Moons et al., 2015
- Transparent Reporting of a multivariable prediction model for Individual Prognosis or Diagnosis (TRIPOD): explanation and elaboration
- Ann. Intern. Med., 162 (2015), pp. W1–73
- Riley et al., 2016
- External validation of clinical prediction models using big datasets from e-health records or IPD meta-analysis: opportunities and challenges
- BMJ, 353 (2016), p. i3140
- Steyerberg, 2009
- Clinical Prediction Models. A Practical Approach to Development, Validation, and Updating
- Springer-Verlag, New York (2009)
- Steyerberg et al., 1998
- Validity of predictions of residual retroperitoneal mass histology in nonseminomatous testicular cancer
- J. Clin. Oncol., 16 (1998), pp. 269–274
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- Szubert et al., 2016
- External validation of the IOTA ADNEX model performed by two independent gynecologic centers
- Gynecol. Oncol. (2016)
- Van Calster et al., 2012
- Assessing the discriminative ability of risk models for more than two outcome categories
- Eur. J. Epidemiol., 27 (2012), pp. 761–770
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- Van Calster et al., 2014
- Evaluating the risk of ovarian cancer before surgery using the ADNEX model to differentiate between benign, borderline, early and advanced stage invasive, and secondary metastatic tumours: prospective multicentre diagnostic study
- BMJ, 349 (2014), p. g5920
- Vergouwe et al., 2005
- Substantial effective sample sizes were required for external validation studies of predictive logistic regression models
- J. Clin. Epidemiol., 58 (2005), pp. 475–483
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- Corresponding author at: KU Leuven, Department of Development and Regeneration, Leuven, Belgium.
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- STRATOS initiative (STRengthening Analytical Thinking for Observational Studies), Topic Group 6 on evaluating diagnostic tests and prediction models.
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