ArticleAsian journal of andrology
A novel robust nomogram based on peripheral monocyte counts for predicting lymph node metastasis of prostate cancer.
Article in Asian journal of andrology. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
3 citing papers in PubMed, 5 citations in OpenAlex.
- Predictive model based on blood cell analysis and coagulation function indicators for neuroblastic tumors staging diagnosis.Frontiers in oncology · 2025Article
- The influence of extraprostatic extension grade on the detection of pelvic lymph node metastasis in prostate cancer.Frontiers in oncology · 2025Article
- Association of systemic inflammatory biomarkers with prostate cancer risk: a population-based (NHANES) and clinical validation study.Frontiers in endocrinology · 2025Article
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Authors and funding
16 authors at 6 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Accurate methods for identifying pelvic lymph node metastasis (LNM) of prostate cancer (PCa) prior to surgery are still lacking. We aimed to investigate the predictive value of peripheral monocyte count (PMC) for LNM of PCa in this study. Two hundred and ninety-eight patients from three centers were divided into a training set (n = 125) and a validation set (n = 173). In the training set, the independent predictors of LNM were analyzed using univariate and multivariate logistic regression analyses, and the optimal cutoff value was calculated by the receiver operating characteristic (ROC) curve. The sensitivity and specificity of the optimal cutoff were authenticated in the validation cohort. Finally, a nomogram based on the PMC was constructed for predicting LNM. Multivariate analyses of the training cohort demonstrated that clinical T stage, preoperative Gleason score, and PMC were independent risk factors for LNM. The subsequent ROC analysis showed that the optimal cutoff value of PMC for diagnosing LNM was 0.405 × 109 l
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