ArticleInternational urology and nephrology2022
Evaluation of prostate health index in predicting bone metastasis of prostate cancer before bone scanning.
Article in International urology and nephrology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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1 citing paper in PubMed, 1 citations in OpenAlex.
- An online clustering algorithm predicting model for prostate cancer based on PHI-related variables and PI-RADS in different PSA populations.Cancer cell international · 2025Article
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6 authors at 2 institutions in 1 country.
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Abstract
purposeIn patients undergoing bone scanning, the positive rate of bone metastasis (BM) of prostate cancer (PCa) is quite low. The main purpose of this study was to explore the application of %p2PSA and prostate health index (phi) in predicting BM of PCa before bone scanning to reduce unnecessary bone scanning.
methodsA total of 279 PCa patients were enrolled in our study. The area under the ROC curve was used to evaluate the prediction accuracy of the variables. Binary logistic regression analysis was performed to establish a prediction model. A multivariate regression model was established to evaluate the predictive value of the variables. The nomogram model was established by R software. The patients were stratified into an intermediate-risk subgroup (T2b-T2c, Gleason score = 6-7) and a high-risk subgroup (cT3-4, Gleason score = 8-10). In the overall cohort and subgroups, McNemar's test was used for comparison of different predictive variables.
resultsOf the 279 patients included in the study, 43 patients were identified as having BM by bone scanning. Univariate logistic regression analysis showed that age (p = 0.043), tPSA (p = 0.001), Ki-67 (p = 0.003), Gleason score (p = 0.001), clinical T stage (p < 0.001) and phi (p < 0.001) were significantly different in BM patients. In multivariate regression analysis, the model with phi showed significant diagnostic ability for predicting BM (AUC = 0.854). In the subgroup analysis, phi was significantly superior to tPSA in terms of the positive predictive value at sensitivities of 84.62% and 61.54% in the overall cohort (p < 0.001) and intermediate-risk subgroup (p < 0.001), respectively. Moreover, %p2PSA showed no significant advantage over tPSA (p > 0.05).
conclusionThe level of phi was significantly related to the positive rate of BM in initially diagnosed PCa. In PCa patients with clinical stage T2b-T2c and Gleason score = 6-7, phi can be used as a surrogate indicator of tPSA for screening BM.
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