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Secondly, in a separate modeling analysis we reorganized the model development set into two groups divided by age (≤50 years versus ≥61 years), irrespective of disease status.
The validation plots were chosen randomly from the dataset with the restriction that all plots in the three least well represented regions were retained in the model development set.
Firstly, we used a strategy in which the average age of cases and controls were very similar in the model development set.
Indeed, in later work (unpublished) in which we built classification models using later disease stages for the model development set, we did identify patterns strongly predictive of ovarian cancer.
While our strategy involved several steps and training data were used repetitively to refine the set of the most informative assays it is critical to appreciate that only the model development set, composed of the stage I data and an equal number of non-ovarian cancer data, were used repetitively.
All samples in the model development set had technical replicates.
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Before analysis, patients were allocated to a model-development set (n=304; March 2009 August 2011) and a validation set (n=189; September 2011 December 2012) based on surgery dates.
These data were divided into two sets, a model development data set of 94 courses and a validation data set of 93 courses.
Of these, 2,937 sample plots containing 23,813 measurements aged between 3 and 61 years old, were used as a model development data set, and a further 702 plots containing 5,699 measurements were used as a validation data set.
First, a different, proprietary algorithm was implemented, and second, all stage I samples analyzed across both rounds one and two were used to increase the size of the model development data set (Figure 1).
With this model, the prediction obtained was: development set with discrimination ROC=0.89 and calibration goodness-of-fit C = 1.68 and validation set with ROC = 0.84 and goodness-of-fit C = 7.72.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com