Objective: To improve the calibration of logistic regression (LR) estimates using local information.
Background: Individualized risk assessment tools are increasingly being utilized. External validation of these tools often reveals poor model calibration.
Methods: We combine a clustering algorithm with an LR model to produce probability estimates that are close to the true probabilities for a particular case. The new method is compared to a standard LR model in terms of calibration, as measured by the sum of absolute differences (SAD) between model estimates and true probabilities, and discrimination, as measured by area under the ROC curve (AUC).
Results: We evaluate the new method on two synthetic data sets. SADs are significantly lower (p < 0.0001) in both data sets, and AUCs are significantly higher in one data set (p < 0.01).
Conclusion: The results suggest that the proposed method may be useful to improve the calibration of LR models.
Download full-text PDF |
Source |
|---|---|
| http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2656048 | PMC |
Publication Analysis
Top Keywords
Similar Publications
A new prediction model for sustained ventricular tachycardia in arrhythmogenic cardiomyopathy.
Front Cardiovasc Med
December 2024
Department of Cardiology, Shanghai East Hospital, Tongji University School of Medicine, Shanghai, China.
Background: Arrhythmogenic cardiomyopathy (ACM) is an inherited cardiomyopathy characterized by high risks of sustained ventricular tachycardia (sVT) and sudden cardiac death. Identifying patients with high risk of sVT is crucial for the management of ACM.
Methods: A total of 147 ACM patients were retrospectively enrolled in the observational study and divided into training and validation groups.
Construction and validation of a nomogram model for predicting diabetic peripheral neuropathy.
Front Endocrinol (Lausanne)
December 2024
Department of Endocrinology, Taizhou Central Hospital (Taizhou University Hospital), Taizhou, China.
Objective: Diabetic peripheral neuropathy (DPN) is a chronic complication of diabetes that can potentially escalate into ulceration, amputation and other severe consequences. The aim of this study was to construct and validate a predictive nomogram model for assessing the risk of DPN development among diabetic patients, thereby facilitating the early identification of high-risk DPN individuals and mitigating the incidence of severe outcomes.
Methods: 1185 patients were included in this study from June 2020 to June 2023.
Comparison of models to predict incident chronic liver disease: a systematic review and external validation in Chinese adults.
BMC Med
December 2024
Department of Epidemiology & Biostatistics, School of Public Health, Peking University, 38 Xueyuan Road, Beijing, 100191, China.
Background: Risk prediction models can identify individuals at high risk of chronic liver disease (CLD), but there is limited evidence on the performance of various models in diverse populations. We aimed to systematically review CLD prediction models, meta-analyze their performance, and externally validate them in 0.5 million Chinese adults in the China Kadoorie Biobank (CKB).
View Article and Find Full Text PDFClinical assessment of urinary prostate cancer antigen 3 in Chinese population: a large-scale, prospective and multicenter study.
World J Surg Oncol
December 2024
Department of Urology, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China.
Background: To assess the clinical utility of PCA3 in the diagnostic accuracy, the correlation between PCA3 and biopsy or pathological characteristics and the performance of PCA3 to reduce the unnecessary biopsies in Chinese population.
Methods: A prospective study including patients with indication of prostate biopsies from 4 centers was conducted. All patients underwent PCA3 urine tests and prostate biopsies.
Want AI Summaries of new PubMed Abstracts delivered to your In-box?
Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!