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Published on: June 21, 2024
Simple adaptations to the Templeton model for IVF outcome prediction make it current and clinically useful
P Arvis1, P Lehert, A Guivarc'h-Levêque
1Clinique la Sagesse, Place St Guénolé, Rennes 35000, France. philippe.lehert@gmail.com
Study Question:
What is the validity of the Templeton model (TM) in predicting live birth (LB) for a couple starting an IVF/ICSI cycle?
Summary Answer:
A centre-specific model based on the original predictors of the TM may reach a sufficient level of accuracy to be used in every day practice, with a few simple adaptations.
What Is Known And What This Paper Adds:
The TM seems the best predictive model of LB in IVF. However, previous validations of the TM suggest a lack of discrimination and calibration which means that it is not used in regular practice. We confirm this finding, and argue that such results are predictable, and essentially due to a strong centre effect. We provide evidence that the TM constitutes a useful reference reflecting a high proportion of the patient-mix effect since the parameters of the model remain invariant among centres, but also across various cultures, countries and types of hospitals. The only difference was the intercept value, interpreted as the measurement of the global performance of one centre, in particular, for a population of reference.
Study Design:
The validity of the TM was tested by a retrospective analysis all IVF/ICSI cycles (n = 12 901) in our centre since 2000.
Participants, Setting And Methods:
All IVF/ICSI cycles were included in the analysis. The model discrimination was evaluated by C-statistics, calculated as the area under the curve of an ROC curve. The TM was then adjusted for our data and additional variables were assessed.
Main Results And The Role Of Chance:
Poor calibration and discrimination (C = 0.64) was observed in conformity with previous external validations. Fitting the TM to our centre constituted the first substantial improvement in prediction accuracy of discrimination (C = 0.69) and calibration. We identified an important linear time trend effect and the added value of three other predictors (FSH, smoking habits and BMI) that significantly improved the model (C = 0.71).
Bias, Confounding And Other Reasons For Caution:
Bias due to missing data handling was assessed through sensitivity analyses.
Generalizability To Other Populations:
Neither the TM nor any other models based on some centres are directly applicable to other centres. However, the TM constitutes a useful basis to build an accurate centre-specific model.
Study Funding/Competing Interest(S):
There were no commercial relationships (i.e. consultancies, patent-licensing agreements) that might pose a conflict of interest in connection with the submitted manuscript. The objective of this research was not directed toward any treatment effects.
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