A nomogram based on hematological parameters for prediction of spontaneous abortion risk in pregnancies

Abstract

Background: Pregnancy loss significantly affects physical and mental health. A nomogram for predicting spontaneous abortion risk was developed to improve pregnancy outcomes.

Methods: A total of 1346 pregnant women were enrolled from The Third Affiliated Hospital of Wenzhou Medical University (May 2020 - May 2022). The training set included 941 participants, and the validation set had 405. Feature selection was optimized using a random forest model, and a predictive model was constructed via multivariable logistic regression. The nomogram's performance was assessed with receiver operator characteristic (ROC), Hosmer-Lemeshow test, calibration curve, and clinical impact curve (CIC). Discrimination and clinical utility were compared between the nomogram and its individual variables.

Results: Antithrombin III (AT-III), homocysteine (Hcy), complement component 3 (C3), protein C (PC), and anti-β2 glycoprotein I antibody (anti-β2GP1) were identified as risk factors. The nomogram demonstrated satisfactory discrimination (Training AUC: 0.813, 95% CI: 0.790-0.842; Validation AUC: 0.792, 95% CI: 0.741-0.838). The Hosmer-Lemeshow test (P = 0.331) indicated a good fit, and the CIC showed clinical net benefit. The nomogram outperformed individual variables in discrimination (AUC: 0.804, 95% CI: 0.779-0.829).

Conclusion: The developed nomogram, incorporating AT-III, Hcy, C3, PC, and anti-β2GP1, aids clinicians in identifying pregnant women at high risk for spontaneous abortion.

Keywords: Abortion; Hematological parameters; Nomogram; Receiver operator characteristic.

Fig. 1

The flow chart of the study population’s inclusion and exclusion criteria and the research process diagram. The research process diagram describes the steps and procedures of the study, such as the data collection, analysis, and reporting methods. AT-III: antithrombin III; Hcy: homocysteine; C3: Complement protein 3; PC: protein C; anti-β2GP1: anti-beta 2 glycoprotein 1 antibody

Fig. 2

Top 30 important variables in the random forest model and the AUC of the 70 laboratory tests in the training and validation sets. Feature importance derived from the random forest model. The plot shows the relative importance of the variables in the random forest model (a). The AUC, or area under the curve, of the 70 laboratory tests in the training set (b) and the validation set (c) shows that the test performs well on new data and has good generalizability

Fig. 3

A nomogram for predicting the risk of spontaneous abortion in pregnancies. Covariates were assessed for the pregnancies and given a point in the nomogram. A higher total number of points indicated a higher likelihood of spontaneous abortion. AT-III: antithrombin III; Hcy: homocysteine; C3: Complement protein 3; PC: protein C; anti-β2GP1: anti-β2 glycoprotein 1 antibody

Fig. 4

Discrimination and calibration of the nomogram for predicting spontaneous abortion risk in the pregnancies and clinical impact curve depicting the clinical net benefit of the nomogram. Receiver operator characteristic curve of the nomogram in the training set (a) and validation set (b). Calibration curve of the nomogram in the training set (c) and validation set (d). Clinical impact curve for the nomogram in the training set (e) and validation set (f). For the calibration curve, the y-axis represents the actual observed spontaneous abortion probabilities, and the x‐axis represents nomogram‐predicted probabilities. The calibration curve shows how well the predicted probabilities agree with the observed probabilities. The diagonal blue dashed line represents a perfect prediction by an ideal model, and the green solid line reflects the performance of the nomogram; a closer fit to the diagonal dashed line indicates a better prediction. Clinical impact curve to predict the improved number for a population size of 1000. The red solid curve shows the predicted number of spontaneous abortions at different threshold probabilities, and the blue dashed curve represents the actual number of spontaneous abortions in the pregnancies. AUC: area under the curve

Fig. 5

Models comparison in the whole study cohort. (a) Receiver operator characteristic curves of the models are presented to compare their discriminatory accuracy for predicting spontaneous abortion. P values show the difference between the AUC for the nomogram and the AUCs for other variables incorporated in the nomogram alone. (b) Decision curve analyses comparing the net benefit of the nomogram and the other variables incorporated in the nomogram alone are shown. AUC: area under the curve; CI: confidence interval; AT-III: antithrombin III; Hcy: homocysteine; C3: Complement protein 3; PC: protein C; anti-β2GP1: anti-β2 glycoprotein 1antibody