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Machine Learning for Prediction and Risk Stratification of Lupus Nephritis Renal Flare
- Source :
- American Journal of Nephrology. 52:152-160
- Publication Year :
- 2021
- Publisher :
- S. Karger AG, 2021.
-
Abstract
- Background: Renal flare of lupus nephritis (LN) is strongly associated with poor kidney outcomes, and predicting renal flare and stratifying its risk are important for clinical decision-making and individualized management to reduce LN flare. Methods: We randomly divided 1,694 patients with biopsy-proven LN, who had achieved remission after treatment, into a derivation cohort (n = 1,186) and an internal validation cohort (n = 508), at a ratio of 7:3. The risk of renal flare 5 years after remission was predicted using an eXtreme Gradient Boosting (XGBoost) method model, developed from 59 variables, including demographic, clinical, immunological, pathological, and therapeutic characteristics. A simplified risk score prediction model (SRSPM) was developed from important variables selected by XGBoost model using stepwise Cox regression for practical convenience. Results: The 5-year relapse rates were 39.5% and 38.2% in the derivation and internal validation cohorts, respectively. Both the XGBoost model and the SRSPM had good predictive performance, with a C-index of 0.819 (95% confidence interval [CI]: 0.774–0.857) and 0.746 (95% CI: 0.697–0.795), respectively, in the validation cohort. The SRSPM comprised 6 variables, including partial remission and endocapillary hypercellularity at baseline, age, serum Alb, anti-dsDNA, and serum complement C3 at the point of remission. Using Kaplan-Meier analysis, the SRSPM identified significant risk stratification for renal flares (p < 0.001). Conclusions: Renal flare of LN can be readily predicted using the XGBoost model and the SRSPM, and the SRSPM can also stratify flare risk. Both models are useful for clinical decision-making and individualized management in LN.
- Subjects :
- Adult
Male
medicine.medical_specialty
Clinical Decision-Making
Lupus nephritis
Kaplan-Meier Estimate
Risk Assessment
Machine Learning
Young Adult
Recurrence
Risk Factors
Internal medicine
medicine
Humans
Derivation
Pathological
Serum Albumin
Proportional Hazards Models
Kidney
Models, Statistical
Framingham Risk Score
business.industry
Proportional hazards model
Age Factors
Complement C3
Symptom Flare Up
medicine.disease
Lupus Nephritis
Confidence interval
Capillaries
medicine.anatomical_structure
Nephrology
Antibodies, Antinuclear
Cohort
Female
business
Subjects
Details
- ISSN :
- 14219670 and 02508095
- Volume :
- 52
- Database :
- OpenAIRE
- Journal :
- American Journal of Nephrology
- Accession number :
- edsair.doi.dedup.....785af5dc352cb16c896e765a2887f06f