Rapid and accurate Bayesian diagnosis of heparin-induced thrombocytopenia.

Prompt diagnostic evaluation of suspected heparin-induced thrombocytopenia (HIT) is critical for guiding initial patient management. We assessed the performance of 3 immunoassays detecting anti-platelet factor 4 (PF4)/heparin antibodies, derived a diagnostic algorithm with a short analytical turnaround time (TAT), and prospectively validated the algorithm. Plasma samples were analyzed by Zymutest-HIA-IgG, HemosIL-AcuStar-HIT-IgG, and ID-H/PF4-PaGIA in retrospective (n = 221) and prospective (n = 305) derivation cohorts. We calculated likelihood ratios of result intervals and cutoff values with 100% negative (NPV) and positive (PPV) predictive values for a positive gold standard functional assay (heparin-induced platelet activation [HIPA]). A diagnostic algorithm was established based on the Bayesian combination of pretest probability and likelihood ratios of first- and second-line immunoassays. Cutoffs with 100% PPV for positive HIPA were >3.0 U/mL (HemosIL-AcuStar-HIT-IgG) and titer ≥16 (ID-H/PF4-PaGIA); cutoffs with 100% NPV were <0.13 U/mL and ≤1, respectively. During the prospective validation of the derived algorithm (n = 687), HemosIL-AcuStar-HIT-IgG was used as unique testing in 566 (82.4%) of 687 cases (analytical TAT, 30 minutes). In 121 (17.6%) of 687 unresolved cases, ID-H/PF4-PaGIA was used as second-line testing (additional TAT, 30 minutes). The algorithm accurately predicted HIT in 51 (7.4%) of 687 patients and excluded it in 604 (87.9%) of 687 patients, leaving only 20 (2.9%) cases unresolved. We also identified 12 (1.7%) of 687 positive predictions not confirmed by HIPA: 10 patients with probable HIT despite negative HIPA and 2 possible false-positive algorithm predictions. The combination of pretest probability with first- and second-line immunoassays for anti-PF4/heparin antibodies is accurate for ruling in or out HIT in ≥95% of cases within 60 minutes. This diagnostic approach improves initial management of patients with suspected HIT.

African-American Prostate Normal and Cancer Cells for Health Disparities Research.

Prostate cancer is the most frequently diagnosed solid malignancy in men. Epidemiological studies have shown African-American men to be at higher risk for developing prostate cancer and experience higher death as compared to other ethnic groups. Establishment of prostate cancer cell lines paired with normal cells derived from the same patient is a fundamental breakthrough in cell culture technology and provides a resource to improve our understanding of cancer development and pertinent molecular events. Previous studies have demonstrated that conditional reprogramming (CR) allows the establishment and propagation of patient-derived normal and tumor epithelial cell cultures from a variety of tissue types. Here, we report a new AA prostate cell model, paired normal and cancer epithelial cells from the same patient. "Tumor" cell culture AA-103A was derived from malignant prostate tissues, and "normal" cell culture AA-103B was derived from non-malignant prostate tissues from the prostatectomy specimen of an African-American male. These paired cell cultures have been propagated under CRC conditions to permit direct comparison of the molecular and genetic profiles of the normal epithelium and adenocarcinoma cells for comparison of biomarkers, enabling patient-specific pathological analysis, and molecular and cellular characterization. STR confirmed human origin albeit no karyotypic abnormalities in the two cell lines. Further quantitative PCR analyses demonstrated characteristic markers, including the high level of basal cell marker, the keratin 5 (KRT5) in normal cells and of luminal marker, the androgen receptor (AR) as well as the programmed death-ligand 1 (PD-L1) in tumor cells. Although 3-D sphere formation was observed, the AA-103A of tumor cells did not generate tumors in vivo. We report these paired primary epithelial cultures under CRC growth as a potentially useful tool for studies to understand molecular mechanisms underlying health disparities in prostate cancer.