Trial reportBioMed research international2023
A Novel Nomogram Combined the Aggregate Index of Systemic Inflammation and PIRADS Score to Predict the Risk of Clinically Significant Prostate Cancer.
Trial report in BioMed research international, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.
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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
17 citing papers in PubMed.
- Risk stratification in colorectal cancer: A retrospective cohort study of nomograms based on inflammatory and immunohematological biomarkers.The Journal of international medical research · 2026Article
- Article
- Prospective Evaluation of Postoperative SIRS and Serum Inflammatory Indices in Percutaneous Nephrolithotomy Patients.Therapeutics and clinical risk management · 2026Article
- Association between the aggregate index of systemic inflammation and 28- or 365-day mortality in acute myocardial infarction patients: insights from the MIMIC-IV database.BMC cardiovascular disorders · 2025Article
- Can the systemic immune-inflammation index be used to differentiate benign and malignant pathologies before transrectal ultrasound-guided prostate biopsy?BMC urology · 2025Article
- Inflammation Beyond the Prostate: The Role of Systemic Inflammatory Disorders in Prostate Carcinogenesis.Cureus · 2025Review
- Association of the aggregate index of systemic inflammation in cancer survivors with all-cause, cardiovascular, and cancer-related mortality.Translational cancer research · 2025Article
- The aggregate index of systemic inflammation is positively correlated with the risk of all-cause mortality in sepsis-associated acute kidney injury.Scientific reports · 2025Article
- Relationship between aggregate index of systemic inflammation and mortality from CCD and malignant neoplasms in diabetic patients.Scientific reports · 2025Article
- Association between the aggregate index of systemic inflammation and CKD: evidence from NHANES 1999-2018.Frontiers in medicine · 2025Article
- Identification of prognostic hub genes and functional role of BAIAP2L2 in prostate cancer progression: a transcriptomic and experimental study.Frontiers in immunology · 2025Article
- Low Aggregate Index of Systemic Inflammation Values Correlate with Favorable Prognosis and High Abundance ofJournal of hepatocellular carcinoma · 2025Article
- Optimizing prostate biopsy decision-making for patients with Prostate Imaging-Reporting and Data System (PI-RADS) ≥3 lesions: novel magnetic resonance imaging (MRI)-based nomograms.Quantitative imaging in medicine and surgery · 2024Article
- Association between monocyte-to-lymphocyte ratio and prostate cancer in the U.S. population: a population-based study.Frontiers in cell and developmental biology · 2024Article
- The association between the aggregate index of systemic inflammation and risk of rheumatoid arthritis: retrospective analysis of NHANES 1999-2018.Frontiers in medicine · 2024Article
- Association Between the Aggregate Index of Systemic Inflammation and Clinical Outcomes in Patients with Acute Myocardial Infarction: A Retrospective Study.Journal of inflammation research · 2024Article
- Association between a four-parameter inflammatory index and all-cause mortality in critical ill patients with non-traumatic subarachnoid hemorrhage: a retrospective analysis of the MIMIC-IV database (2012-2019).Frontiers in immunology · 2023Article
Corrections and comments
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Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: This study is aimed at constructing a nomogram to predict the risk of clinically significant prostate cancer (csPCa) based on the aggregate index of systemic inflammation (AISI) and prostate imaging-reporting and data system version (PIRADS) score. Methods: Clinical data on patients who had undergone initial prostate biopsy from January 2019 to December 2021 were collected. Patients were randomized in a 7 : 3 ratio to the training cohort and the validation cohort. Potential risk factors for csPCa were identified by univariable and multivariate logistic regression. Nomogram was conducted with these independent risk factors, and calibration curves, the receiver operating characteristic (ROC), and decision curve analysis (DCA) were employed to assess the nomogram's ability for prediction. Results: A total of 1219 patients were enrolled in this study. Multivariate logistic regression identified that age, AISI, total prostatic specific-antigen (tPSA), free to total PSA (f/tPSA), prostate volume (PV), and PIRADS score were potential risk predictors of csPCa, and the nomogram was developed based on these factors. The area under the curve (AUC) of the training cohort and validation cohort was 0.884 (95% CI: 0.862-0.906) and 0.899 (95% CI: 0.867-0.931). The calibration curves showed that the apparent curves were closer to the ideal curves. The DCA results revealed that the nomogram model seemed to have clinical application value per DCA. Conclusion: The nomogram model can efficiently predict the risk of csPCa and may assist clinicians in determining if a prostate biopsy is necessary.
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