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raw data of " Risk score model to automatically detect prostate cancer patients by integrating diagnostic parameters" doi 10.3389/fonc.2024.1323247
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Age- and multivariable-adjusted odds ratios and 95% confidence intervals for high aggressive prostate cancer by tertiles of plasma 25(OH)D3.
aAdjusted for age, African ancestry, BMI, total energy intake, alcohol intake, physical activity, smoking status, educational status, PSA screening history, study site, NSAIDs use, and season of blood
Figshare2015-12-03 更新30
Logistic regression analysis of associations between mTOR genotypes and prostate cancer risk in Eastern Chinese men.
OR, odds ratio; CI, confidence interval.aHard-Wenberg equilibrium test for controls.bTwo-sided Chi-square tests were used to calculate differences in the frequency distribution of genotypes between ca
Figshare2015-12-02 更新20
Baseline patient characteristics and microbiome reads of samples obtained from our study.
Baseline patient characteristics and microbiome reads of samples obtained from our study.
NIAID Data Ecosystem20
How to Pick Out the “Unreal” Gleason 3 + 3 Patients: A Nomogram for More Precise Active Surveillance Protocol in Low-Risk Prostate Cancer in a Chinese Population
To develop a nomogram for selecting the “unreal” Gleason score (GS) 3 + 3 patients in biopsy GS 3 + 3 prostate cancer (PCa) patients. Patients who were newly diagnosed with PCa by biopsy and underwent
Taylor & Francis Group2024-03-01 更新30
Probability of positive prostate biopsy in high and low risk patients grouped by the genetic risk model at various cutoffs.
aPercentile of population above the cut-off odds ratio in all the samples in the present study. bPercentile of population below the cutoff odds ratio. CProbability of positive prostate biopsy assuming
NIAID Data Ecosystem20
