Page 52 - The diagnostic work-up of women with postmenopausal bleeding

Chapter 3
Methods
Study identification
We performed a computerized MEDLINE and EMBASE search to identify all studies on prediction models in women with postmenopausal bleeding published from inception to June 2011. The search was limited to human studies, no restrictions were held concerning publication year or language.We included articles reporting on multivariable models predicting endometrial cancer in women with PMB. We checked references cited in the selected articles for further relevant prediction models not identified by the electronic searches.We used all known synonyms for the terms ‘postmenopausal bleeding’ and ‘endometrial cancer’ and we used a search- filter for prediction models.22 The search strategy can be found in Appendix 1.
Study selection
This review focused on articles that report on a prediction model for endometrial cancer in women with PMB. In this review, a prediction model was defined as a multivariable model that expresses the chance of endometrial cancer as a function of two or more predictor variables. PMB was defined as vaginal bleeding after more than one year of amenorrhea after the age of 40 or persistent (>3 months) unscheduled bleeding on hormone replacement therapy (HRT). Two independently working reviewers (NvH and MB) selected the articles, by assessing titles and abstracts. If there were any doubts about eligibility after reading title and abstract, we read the full text version to make sure no articles were missed. In case of disagreement the article was included for full text reading and assessed by a third reviewer (AT).
Study quality assessment
A framework for quality assessment was developed based on the recommendations of Hayden et al23 and on a quality assessment framework for prediction models in subfertile women to predict the chance of pregnancy.24 The framework was divided into four sections: study participation, predictor variables, outcome measurement and analysis. Each item in the different sections was scored with ‘yes’, ‘no’ or ‘unclear’.
Predictor variables
All predictor variables were collected for each prediction model.The predictor variables are the potential predictors, which were tested, both during model development and in the final model.The original articles selected multiple variables or risk factors,
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