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ORIGINAL RESEARCH

Risk Factors for Granulomatous Mastitis and Establishment and Validation of a Clinical Prediction Model (Nomogram)

, , , , , , , , , & show all
Pages 2209-2222 | Received 18 Jul 2023, Accepted 13 Oct 2023, Published online: 20 Oct 2023

Figures & data

Figure 1 Flow chart of the study.

Figure 1 Flow chart of the study.

Table 1 Comparison of Basic Information Between the Two Groups

Table 2 Clinical Characteristics of the Case Group

Table 3 Comparison of Factors Relevant to Lactation Between Two Groups

Table 4 Comparison of Other Factors Between the Two Groups

Table 5 Multivariate Logistic Analysis of Risk Factors for Granulomatous Mastitis

Figure 2 The clinical prediction model (Nomogram) for predicting the risk of granulomatous mastitis (*Indicates P<0.05; ***Indicates P<0.001).

Figure 2 The clinical prediction model (Nomogram) for predicting the risk of granulomatous mastitis (*Indicates P<0.05; ***Indicates P<0.001).

Table 6 Comparison of Important Variables Between the Modeling and Validation Groups

Figure 3 The calibration curves of the prediction model in modeling group (A) and validation group (B), indicating its uniformity.

Figure 3 The calibration curves of the prediction model in modeling group (A) and validation group (B), indicating its uniformity.

Figure 4 The receiver operating characteristic curve of the prediction model in the modeling group (A) and validation group (B), indicating its discrimination.

Figure 4 The receiver operating characteristic curve of the prediction model in the modeling group (A) and validation group (B), indicating its discrimination.

Figure 5 The decision curve analysis (DCA) of the prediction model in the modeling group (A) and validation group (B), indicating good clinical practicability of the model. The red DCA represents the established curve of the prediction model, and the blue DCA is the curve of the simple clinical model.

Figure 5 The decision curve analysis (DCA) of the prediction model in the modeling group (A) and validation group (B), indicating good clinical practicability of the model. The red DCA represents the established curve of the prediction model, and the blue DCA is the curve of the simple clinical model.

Figure 6 The clinical impact curves (CIC) of the prediction model in the modeling group (A) and validation group (B). The red curve (number of high risks) indicates the number of people classified as positive (high risk) by the Nomogram for each threshold probability. The blue curve (number of high risks with the outcome) represents the number of true positives under each threshold probability.

Figure 6 The clinical impact curves (CIC) of the prediction model in the modeling group (A) and validation group (B). The red curve (number of high risks) indicates the number of people classified as positive (high risk) by the Nomogram for each threshold probability. The blue curve (number of high risks with the outcome) represents the number of true positives under each threshold probability.