External Validation of the Briganti Nomogram to Predict Lymph Node Invasion in Prostate Cancer—Setting a New Threshold Value

Małkiewicz, Bartosz; Ptaszkowski, Kuba; Knecht, Klaudia; Gurwin, Adam; Wilk, Karol; Kiełb, Paweł; Dudek, Krzysztof; Zdrojowy, Romuald

doi:10.3390/life11060479

Cited by 5 publications

(4 citation statements)

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“…These results imply that our model has a low missing rate, and more LNI patients would be identified. This is consistent with the results of previous studies ( 44 ).…”

Section: Discussionsupporting

confidence: 94%

“…The significance of determining a cutoff value for a predictive model is to guide the physician during clinical decisions, but it also implies that a certain number of patients below that cutoff value may be missed. The current EAU guidelines suggest that the indication for ePLND is based on the risk of LN metastasis >5% using the Briganti nomogram ( 44 ). Using this cutoff, our model could spare about 50% (428/866) of ePLND and only 1.2% (5/428) of patients would be missed.…”

Section: Discussionmentioning

confidence: 99%

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Artificial Intelligence Combined With Big Data to Predict Lymph Node Involvement in Prostate Cancer: A Population-Based Study

et al. 2021

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BackgroundA more accurate preoperative prediction of lymph node involvement (LNI) in prostate cancer (PCa) would improve clinical treatment and follow-up strategies of this disease. We developed a predictive model based on machine learning (ML) combined with big data to achieve this.MethodsClinicopathological characteristics of 2,884 PCa patients who underwent extended pelvic lymph node dissection (ePLND) were collected from the U.S. National Cancer Institute’s Surveillance, Epidemiology, and End Results (SEER) database from 2010 to 2015. Eight variables were included to establish an ML model. Model performance was evaluated by the receiver operating characteristic (ROC) curves and calibration plots for predictive accuracy. Decision curve analysis (DCA) and cutoff values were obtained to estimate its clinical utility.ResultsThree hundred and forty-four (11.9%) patients were identified with LNI. The five most important factors were the Gleason score, T stage of disease, percentage of positive cores, tumor size, and prostate-specific antigen levels with 158, 137, 128, 113, and 88 points, respectively. The XGBoost (XGB) model showed the best predictive performance and had the highest net benefit when compared with the other algorithms, achieving an area under the curve of 0.883. With a 5%~20% cutoff value, the XGB model performed best in reducing omissions and avoiding overtreatment of patients when dealing with LNI. This model also had a lower false-negative rate and a higher percentage of ePLND was avoided. In addition, DCA showed it has the highest net benefit across the whole range of threshold probabilities.ConclusionsWe established an ML model based on big data for predicting LNI in PCa, and it could lead to a reduction of approximately 50% of ePLND cases. In addition, only ≤3% of patients were misdiagnosed with a cutoff value ranging from 5% to 20%. This promising study warrants further validation by using a larger prospective dataset.

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“…These results imply that our model has a low missing rate, and more LNI patients would be identified. This is consistent with the results of previous studies ( 44 ).…”

Section: Discussionsupporting

confidence: 94%

Section: Discussionmentioning

confidence: 99%

Artificial Intelligence Combined With Big Data to Predict Lymph Node Involvement in Prostate Cancer: A Population-Based Study

et al. 2021

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“…These findings imply that IL-17A and IL-17RA may play a significant role in the development of pre-metastatic niches, although further evidence is required to support this theory. These results could eventually assist in improving the accuracy of models such as Memorial Sloan Kettering Cancer Center (MSKCC), Partin, and Briganti nomograms, which are used to assess the likelihood of PCa nodal metastases [ 51 , 52 , 53 , 54 ]. The continuous improvement of methods to assess the risk of the presence of nodal metastases is very important because, despite the currently used tools, approximately 70% of patients undergo unnecessary extended lymphadenectomy, showing the absence of nodal metastases [ 55 ].…”

Section: Discussionmentioning

confidence: 99%

Role of IL-17A and IL-17RA in Prostate Cancer with Lymph Nodes Metastasis: Expression Patterns and Clinical Significance

Kiełb,

Kaczorowski,

Kowalczyk

et al. 2023

Cancers

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Prostate cancer (PCa) is the second most frequently diagnosed cancer among men. The use of IL-17A and its receptor IL-17RA as prognostic markers for PCa has shown promising results. We analyzed the clinical data of 77 patients with PCa after radical prostatectomy with lymphadenectomy and lymph node metastasis (LN+). We assessed the expression levels of IL-17A and IL-17RA in cancer cells in prostate and, for the first time, also in LN+. Prostate IL-17A expression positively correlated with BMI (p = 0.028). In LN+, the expression of IL-17A was positively correlated with the percentage of affected lymph nodes (p = 0.006) and EAU risk groups (p = 0.001). Additionally, in the group with high IL-17A expression in LN+, the extracapsular extension (ECE) of the prostate was significantly more frequent (p = 0.033). Also, significant correlations with the level of IL-17RA expression was found—expression was higher in prostate than in LN+ (p = 0.009); in LN+, expression positively correlated with the EAU risk group (p = 0.045), and in the group of high expression in LN+ ECE of lymph nodes was detected significantly more often (p = 0.009). Our findings support the potential role of IL-17A and IL-17RA as PCa markers; however, further studies are needed to determine their roles and potential clinical applications.

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“…In the future, this observation may also be helpful in improving the models used to determine the risk of nodal metastases of PCa, such as the Briganti nomogram. This issue is extremely important in the decision-making process regarding the determination of the indications for lymphadenectomy, which significantly increases the risk of surgery and potential complications (12,(35)(36)(37).…”

Section: Discussionmentioning

confidence: 99%

Comparative analysis of GOLPH3 expression in lymph node-positive prostate cancer: immunohistochemistry staining patterns and clinical significance

Kiełb,

Kaczorowski,

Kowalczyk

et al. 2023

Front. Oncol.

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IntroductionProstate cancer (PCa) is the second most commonly diagnosed cancer in men worldwide. Lymph node metastasis is a poor prognostic factor for PCa. Previous studies have found that Golgi phosphoprotein 3 (GOLPH3) is overexpressed in various cancers, including PCa. We examined GOLPH3 expression in PCa cells from primary tumor and, as the first, also in metastatic lymph nodes to assess its potential as a new risk factor for PCa progression.MethodsThe study included 78 patients diagnosed with lymph node-positive PCa confirmed in the postoperative material. All the patients underwent radical prostatectomy (RP) with extended lymphadenectomy. The clinical data of the patients were retrospectively analyzed, and their histopathological specimens were selected for further analysis. Immunohistochemistry (IHC) staining was performed and the expression of GOLPH3 was assessed by an experienced uropathologist using an immunoreactive scale (IRS). A correlational analysis of the obtained data with the clinicopathological data of patients was performed.ResultsA positive IHC reaction for GOLPH3 was observed in all samples. IRS score for GOLPH3 expression was higher in the metastatic lymph nodes than in the prostate (not statistically significant; p=0.056). Several significant correlations were identified in connection with GOLPH3 expression levels in the prostate and metastatic lymph node tissues. No significant correlations were found between GOLPH3 expression and patient characteristics (e.g. BMI, EAU risk group, or preoperative PSA level), pathological features, or postoperative outcomes. However, we found that lymphovascular invasion (LVI) tended to be more common in patients with a higher percentage of GOLPH3-positive cells (p=0.02). We also found a positive association between the intensity of GOLPH3 staining in metastatic lymph nodes and the EAU classification. Finally, we found a significant negative correlation between the GOLPH3 expression and the efficacy of RP – the higher the expression of GOLPH3, the lower the efficacy of RP was (p<0.05).ConclusionGOLPH3 is expressed in both prostate and metastatic lymph nodes, with higher expression in metastatic lymph nodes. High GOLPH3 expression was associated with the occurrence of LVI, higher-risk group in the EAU classification, and lower efficacy of the RP, but there was no significant correlation with other pathological features or postoperative outcomes.

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External Validation of the Briganti Nomogram to Predict Lymph Node Invasion in Prostate Cancer—Setting a New Threshold Value

Cited by 5 publications

References 46 publications

Artificial Intelligence Combined With Big Data to Predict Lymph Node Involvement in Prostate Cancer: A Population-Based Study

Artificial Intelligence Combined With Big Data to Predict Lymph Node Involvement in Prostate Cancer: A Population-Based Study

Role of IL-17A and IL-17RA in Prostate Cancer with Lymph Nodes Metastasis: Expression Patterns and Clinical Significance

Comparative analysis of GOLPH3 expression in lymph node-positive prostate cancer: immunohistochemistry staining patterns and clinical significance

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