A pinboard by
Tyler Seibert

Resident Physician / Research Fellow, University of California, San Diego


Genetic information can be used to design a customized, optimal prostate cancer screening plan.

Note: the following abstract does not include new, still confidential results regarding remarkable prediction of risk of aggressive prostate cancer. I also plan to present a pending replication of these results in another large data set.

Background: Prostate-specific-antigen (PSA) screening resulted in reduced prostate cancer (PCa) mortality in a large clinical trial, but due to a high false-positive rate, among other concerns, many guidelines do not endorse universal screening and instead recommend an individualized decision based on each patient’s risk. Genetic risk may provide key information to guide the decisions of whether and at what age to screen an individual man for PCa. Methods: Genotype, PCa status, and age from 34,444 men of European ancestry from the PRACTICAL consortium database were analyzed to select single-nucleotide polymorphisms (SNPs) associated with prostate cancer diagnosis. These SNPs were then incorporated into a survival analysis to estimate their effects on age at PCa diagnosis. The resulting polygenic hazard score (PHS) is an assessment of individual genetic risk. The final model was validated in an independent dataset comprised of 6,417 men with screening PSA and genotype data. PHS was calculated for these men to test for prediction of PCa-free survival. PHS was also combined with age-specific PCa incidence data from the U.S. population to generate a PCa-Risk (PCaR) age that relates a given man’s risk to that of the population average. PHS and PCaR age were evaluated for prediction of positive predictive value (PPV) of PSA screening. Findings: PHS calculated from 54 SNPs was very highly predictive of age at PCa diagnosis for men in the validation set (p=10-53). PPV of PSA screening varied from 0·18 to 0·52 for men with low and high genetic risk, respectively. PHS modulates PCa-free survival curves by an estimated 20 years between men in the 1st or 99th percentiles of genetic risk. Interpretation: Polygenic hazard scores give personalized genetic risk estimates and can inform the decisions of whether and at what age to screen a man for PCa.


Monitoring Tumor Volume in Patients With Prostate Cancer Undergoing Active Surveillance: Is MRI Apparent Diffusion Coefficient Indicative of Tumor Growth?

Abstract: The purpose of this study was to measure longitudinal change in tumor volume of the dominant intraprostatic lesion and determine whether baseline apparent diffusion coefficient (ADC) and change in ADC are indicative of tumor growth in patients with prostate cancer undergoing active surveillance.The study group included 151 men (mean age, 68.1 ± 7.4 [SD] years; range, 50-83 years) undergoing active surveillance with 3D whole prostate, zonal, and tumor volumetric findings documented at endorectal MRI examinations performed at two time points (median interval, 1.9 years). Tumor (location confirmed at transrectal ultrasound or template biopsy) ADC was measured on the slice with the largest lesion. Twenty randomly selected patients had the measurements repeated by the same observer after a greater than 4-month interval, and the limits of agreement of measurements were calculated. Tumor volume increases greater than the upper limit of agreement were designated measurable growth, and their baseline ADCs and change in ADC were compared with those of tumors without measurable growth (independent-samples t test).Fifty-two (34.4%) tumors increased measurably in volume. Baseline ADC and tumor volume were negatively correlated (r = -0.42, p = 0.001). Baseline ADC values did not differ between those with and those without measurable growth (p = 0.06), but change in ADC was significantly different (-6.8% ± 12.3% for those with measurable growth vs 0.23% ± 10.1% for those without, p = 0.0005). Percentage change in tumor volume and percentage change in ADC were negatively correlated (r = -0.31, p = 0.0001). A 5.8% reduction in ADC indicated a measurable increase in tumor volume with 54.9% sensitivity and 77.0% specificity (AUC, 0.67).Tumor volume increased measurably in 34.4% of men after 2 years of active surveillance. Change in ADC may be used to identify tumors with measurable growth.

Pub.: 14 Jun '17, Pinned: 14 Jun '17

Prostate-specific membrane antigen PET/MRI validation of MR textural analysis for detection of transition zone prostate cancer.

Abstract: To validate MR textural analysis (MRTA) for detection of transition zone (TZ) prostate cancer through comparison with co-registered prostate-specific membrane antigen (PSMA) PET-MR.Retrospective analysis was performed for 30 men who underwent simultaneous PSMA PET-MR imaging for staging of prostate cancer. Thirty texture features were derived from each manually contoured T2-weighted, transaxial, prostatic TZ using texture analysis software that applies a spatial band-pass filter and quantifies texture through histogram analysis. Texture features of the TZ were compared to PSMA expression on the corresponding PET images. The Benjamini-Hochberg correction controlled the false discovery rate at <5%.Eighty-eight T2-weighted images in 18 patients demonstrated abnormal PSMA expression within the TZ on PET-MR. 123 images were PSMA negative. Based on the corrected p-value of 0.005, significant differences between PSMA positive and negative slices were found for 16 texture parameters: Standard deviation and mean of positive pixels for all spatial filters (p = <0.0001 for both at all spatial scaling factor (SSF) values) and mean intensity following filtration for SSF 3-6 mm (p = 0.0002-0.0018).Abnormal expression of PSMA within the TZ is associated with altered texture on T2-weighted MR, providing validation of MRTA for the detection of TZ prostate cancer.• Prostate transition zone (TZ) MR texture analysis may assist in prostate cancer detection. • Abnormal transition zone PSMA expression correlates with altered texture on T2-weighted MR. • TZ with abnormal PSMA expression demonstrates significantly reduced MI, SD and MPP.

Pub.: 14 Jun '17, Pinned: 14 Jun '17