[Psychometric validation of Convergence criteria PP]
V Quistrebert-Davanne1, J-B Hardouin2, T Riant3
1Centre fédératif de pelvipérinéologie et clinique urologique, CHU de Nantes, Nantes, France.
Context:
The PP Convergences criteria group together 10 of the most significant clinical criteria for sensitization in the context of chronic pelvic pain. They are the result of a consensus of experts and represent to date the only clinical evaluation guide to identify patients with pelvic perineal pain in whom a pelvic sensitization component can be evoked.
Objective:
This work concerns the psychometric validation of these criteria. The aim is to answer 3 questions: 1) is the instrument reliable (i.e., sensitive, specific and accurate)?; 2) can we define a screening score for pelvic-perineal pain by sensitization from the CPP criteria?; 3) can combinations of criteria be defined to predict pelvic-perineal sensitization from the CPP criteria?
Methodology And Subjects:
In total, 308 patients with pelviperineal pain were recruited during their medical consultation.
Procedure:
Fifteen expert physicians were asked to judge the presence or absence of the 10 CPP criteria and to make a diagnosis of the presence or absence of pelviperineal sensitization in their patient.
Results:
ROC curve analysis indicated that a score of 5 was the closest to a perfect score with a sensitivity of 95% and a specificity of 87%. They also indicate that the CPP criteria have a very good sensitivity (97%) and specificity (91%) and present globally a good reproducibility on all the criteria (Kappa>0.6). Finally, the statistical analyses reveal that the most discriminating criterion for predicting sensitization is Q8 (pain persisting after sexual activity).
Conclusion:
The CPP criteria represent a very good screening tool for pelvic sensitization. The score of 5 corresponds to the score at which the patient has sufficient clinical criteria to be classified as sensitized.
Level Of Evidence:
4.
Related Concept Videos
Reliability and Validity
Kendall's Coefficient of Concordance
Data Validation
Key parameters for method validation include:
Expected Frequencies in Goodness-of-Fit Tests
Goodness-of-Fit Test
Calibration Curves: Correlation Coefficient


