Related Experiment Video
Updated: Oct 12, 2025
An R-Based Landscape Validation of a Competing Risk Model
Published on: September 16, 2022
[Retrospective validation of a model to predict the outcome of pregnancies of unknown location]
M Dap1, M Chaillot2, J Rouche2
1Pôle de gynécologie obstétrique, maternité universitaire, CHRU de Nancy, Nancy, France; Laboratoire de pathologies fœtale et placentaire, maternité universitaire, CHRU de Nancy, Nancy, France.
Objective:
The prediction model M6 classifies pregnancy of unknown location (PUL) into a low-risk or a high-risk group in developing ectopic pregnancy (EP). The aim of this study was to validate the two-step M6 model's ability to classify PUL in French women.
Material And Methods:
All women with a diagnosis of PUL over a year were included in this single center retrospective study. Patients with a diagnosis of EP at the first consultation of with incomplete data were excluded. For each patient, the M6 model calculator was used to classified them into "high risk of EP" and "low risk of EP" group. The reference standard was the final diagnostic: failed PUL (FPUL), intrauterine pregnancy (IUP) of EP. The statistical measures of the test's performance were calculated.
Results:
Over the period, 255 women's consulted for a PUL, 197 has been included in the study. Final diagnosis were: 94 FPUL (94/197; 47.7%), 74 IUP (74/197; 37.6%) et 29 EP (29/197; 14.7%). The first step of the M6 model classified 16 women in the FPUL group of which 15 (15/16; 93.7%) correctly. The second step of the M6 model classified 181 women: 90 (90/181; 49.7%) in the "high risk of EP" group of which 63 (63/90; 70%) were FPUL/IUP and 27 (27/90; 30%) were EP. 91 (91/181; 50.3%) was classified in the "low risk of EP" group of which 90 (90/91; 98.9%) were FPUL/IUP and 1 (1/91; 1.1%) were EP. EP were correctly classified with sensitivity of 96.4%, negative predictive value of 98.9%, specificity of 58.8% and positive predictive value of 30.0%.
Conclusions:
The prediction model of PUL M6 classified EP in "high risk of EP group" with a sensitivity of 96.4%. It classified 50.3% of PUL in a "low risk of EP" group with a negative predictive value of 98.9%.
Related Concept Videos
01:52Regression Toward the Mean
01:11Residuals and Least-Squares Property
If the observed data point lies above the line, the residual is positive, and the line underestimates the actual data value for y. If the observed data point lies below the line, the residual is negative, and the line overestimates the actual data value for y.
The process of fitting the best-fit...
01:03Prediction Intervals
However, the point estimate is most likely not the exact value of the population parameter, but close to it. After calculating point estimates, we construct interval estimates, called confidence intervals or prediction intervals. This prediction interval comprises a range of values unlike the point estimate and is a better predictor of the observed sample value, y.