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ORIGINAL RESEARCH

External Validation of the International IgA Nephropathy Prediction Tool in Older Adult Patients

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Pages 911-922 | Received 15 Dec 2023, Accepted 30 Apr 2024, Published online: 21 May 2024

Figures & data

Figure 1 Flowchart of patients screened, recruited, and included in the final analysis.

Figure 1 Flowchart of patients screened, recruited, and included in the final analysis.

Table 1 Characteristics of Participants in the Older Adults Validation Cohort, the Original Derivation Cohort, and the Original Validation Cohort

Table 2 Concordance Statistics, Calibration Slopes, Net Reclassification Improvements, and Integrated Discrimination Improvements of Full Models in the Older Adults External Validation Cohort

Table 3 Associations of the Risk Groups with the Composite Outcome of 50% Decline in Estimated Glomerular Filtration Rate or Kidney Failure in Patients with Over 5-Year Follow-Up (n=165)

Figure 2 The Time-dependent receiver operating characteristic (ROC) curves and the Kaplan-Meier curves confirmed the excellent distinguishing ability of both full models.

Notes: (a and b) show the receiver operating curve analysis at 3 years and 5 years for both full models, respectively. (c and d) respectively show the Kaplan-Meier curves of the primary outcome in 4 risk groups distinguished by the Full model with race and the full model without race: the well-separated curves indicate good discriminant ability of both the models. The 4 risk groups were defined as <16th (low risk), 16th −50th (intermediate risk), 50th −84th (higher risk), and >84th (the highest risk) percentiles of the linear predictor from the full model without and with race, respectively.
Abbreviations: AUC, the area under the receiver operating characteristic (ROC) curve.
Figure 2 The Time-dependent receiver operating characteristic (ROC) curves and the Kaplan-Meier curves confirmed the excellent distinguishing ability of both full models.

Figure 3 The full model without race more accurately prognoses the risk associated with primary outcomes in the older adult cohort.

Notes: (a) Comparison of observed and predicted risks of the primary outcome during the follow-up period. Predicted risks are mean predicted risk curves (blue and pink solid lines), observed risks were estimated by the Kaplan–Meier method (black solid line), and the grey dashed lines represent 95% confidence intervals of the observed risks. (b and c) Comparison of observed and predicted risks of the primary outcome throughout follow-up. The full prediction models with and without race were analyzed by subgroups based on the percentile of the linear predictor (<16th in yellow, 16th-50th in blue, 50th-84th in green, and >84th in pink) in the older adult cohorts. Predicted risks are mean predicted survival curves (dotted lines), and observed risks are Kaplan-Meier curves (solid lines).
Figure 3 The full model without race more accurately prognoses the risk associated with primary outcomes in the older adult cohort.

Figure 4 Calibration plots at 3 years for (a and b) the full model with race and (c and d) the full model without race, and at 5 years for (e and f) the full model with race and (g and h) the full model without race.

Notes: Plots by risk groups are (a, c, e, and g, and by fifths of predicted risk are b, d, f, and h). The dashed lines indicate perfect calibration, in which predicted risks are the same as the observed risks. Vertical lines in observed groups represent 95% confidence intervals. Risk groups were based on percentiles of the linear predictor (group 1(low risk);<16th, group 2 (intermediate risk); 16th-50th, group 3 (higher risk); 50th-84th, group 4(highest risk: >84th)).
Figure 4 Calibration plots at 3 years for (a and b) the full model with race and (c and d) the full model without race, and at 5 years for (e and f) the full model with race and (g and h) the full model without race.

Data Sharing Statement

The raw data supporting the conclusions of this article will be made available by the authors without undue reservation. Correspondence and requests for materials should be addressed to Guang-yan Cai.