External validation of genomic classifier-based risk-stratification tool to identify candidates for adjuvant radiation therapy in patients with prostate cancer.

World J Urol

VUI Center for Outcomes Research Analytics and Evaluation, Senior staff, Vattikuti Urology Institute (VUI), Henry Ford Hospital, 2799 W Grand Blvd, Detroit, MI, 48202-2689, USA.

Published: September 2021

Objective: To externally validate a Genomic Classifier (GC) based risk-stratification nomogram identifying candidates who would benefit from adjuvant radiation (aRT) therapy after radical prostatectomy (RP).

Methods: We identified 350 patients who underwent RP, between 2013 and 2018, and had adverse pathological features (positive margin, and/or pT3a or higher) on final pathology. Genomic profile was available for all these men. The clinical recurrence-free survival was estimated using the Kaplan-Meier method. The external validity of the nomogram was tested using the concordance index (c-index), calibration plot, and decision curve analysis.

Results: The median follow-up of the cohort was 26.5 months. Overall, 14% of the patients received aRT. During the follow-up period, 3.4% of the patients developed metastasis. Overall 3-year metastasis-free survival was 95% (95% CI 0.92-0.98). The c-index of the nomogram was 0.84. The calibration of the model was favorable. Decision-curve analysis showed a positive net benefit for probabilities ranging between 0.01 and 0.09, with the highest difference at threshold probability around 0.05. At that threshold, the net benefit is 0.06 for the model and 0 for treating all the patients.

Conclusion: Our report is the first to confirm the validity of this genomic-based risk-stratification tool in identifying men who might benefit from aRT after RP. As such, it can be a useful instrument to be incorporated in shared decision making on whether administration of aRT will lead to a clinically meaningful benefit. Such a model can also be useful for patients' classification in future clinical trials.

Download full-text PDF

Source
http://dx.doi.org/10.1007/s00345-020-03540-1DOI Listing

Publication Analysis

Top Keywords

risk-stratification tool
8
adjuvant radiation
8
net benefit
8
benefit
5
external validation
4
validation genomic
4
genomic classifier-based
4
classifier-based risk-stratification
4
tool identify
4
identify candidates
4

Similar Publications

Background: Multidrug-resistant Klebsiella pneumoniae (MDR-KP) infections pose a significant global healthcare challenge, particularly due to the high mortality risk associated with septic shock. This study aimed to develop and validate a machine learning-based model to predict the risk of MDR-KP-associated septic shock, enabling early risk stratification and targeted interventions.

Methods: A retrospective analysis was conducted on 1,385 patients with MDR-KP infections admitted between January 2019 and June 2024.

View Article and Find Full Text PDF

Background: Prognosis assessments for transcatheter aortic valve implantation (TAVI) patients remain challenging, particularly as the indications for TAVI expand to lower-risk patients. This study assessed the prognostic value of the tricuspid regurgitation impact on outcomes (TRIO) score in patients after TAVI.

Methods: This single-center study included 530 consecutive patients who underwent TAVI.

View Article and Find Full Text PDF

Breast arterial calcification (BAC) is a common benign finding on a screening mammogram. Additionally, BAC is a type of medial calcification known as Mönckeberg medial calcific sclerosis, which differs from the intimal calcification seen in patients with coronary artery disease (CAD). Recently, BAC has appeared as a new cardiovascular risk stratification method.

View Article and Find Full Text PDF

Background: Clinical determination of patients at high risk of poor surgical outcomes is complex and may be supported by clinical tools to summarize the patient's own personalized electronic health record (EHR) history and vitals data through predictive risk models. Since prior models were not readily available for EHR-integration, our objective was to develop and validate a risk stratification tool, named the Assessment of Geriatric Emergency Surgery (AGES) score, predicting risk of 30-day major postoperative complications in geriatric patients under consideration for urgent and emergency surgery using pre-surgical existing electronic health record (EHR) data.

Methods: Patients 65-years and older undergoing urgent or emergency non-cardiac surgery within 21 hospitals 2017-2021 were used to develop the model (randomly split: 80% training, 20% test).

View Article and Find Full Text PDF

Introduction: The Rutherford Classification for chronic limb-threatening ischemia (CLTI) is used to categorize peripheral artery disease severity through history and physical examination. This study investigated whether higher Rutherford Classification correlates with worse clinical outcomes and could serve as a predictive tool.

Methods: In this prospective single-center study , 252 patients undergoing lower extremity revascularization were followed for three years (2020-2023).

View Article and Find Full Text PDF

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!