Citations

AbstractObjectivesTo analyze the economic impact of testing for activated protein C resistance (APC-R) due to factor V Leiden (FVL) mutation with APC-R with reflexive FVL genotyping (algorithmic approach) or genotyping alone.MethodsOptumLabs Data Warehouse (OLDW) data were used to assess testing approaches. Insurance claims for APC-R and FVL in 2013 were compared with the Mayo Clinic database. Centers for Medicare & Medicaid Services diagnostic fee schedules were used to assign costs.ResultsOf 19.3 million OLDW-covered individuals, 74,242 (0.385%) received 75,608 tests: APC-R, 2,265 (2.9%); FVL genotyping, 70,619 (90.1%); and both APC-R and FVL, 2,724 (7.0%). In total, 1,317 tests were performed at Mayo Clinic: APC-R with reflex FVL (1,256; 95.4%) and FVL alone (61; 4.6%). Costs per evaluated individual and per total population (person/year) in OLDW and algorithmic approach were $83.77 vs $36.38 and $0.32 vs $0.14, respectively.ConclusionsThe cost-optimized algorithmic approach reduces health care costs.

BACKGROUND. No laboratory test can predict the risk of nonrelapse mortality (NRM) or severe graft-versus-host disease (GVHD) after hematopoietic cellular transplantation (HCT) prior to the onset of GVHD symptoms. METHODS. Patient blood samples on day 7 after HCT were obtained from a multicenter set of 1,287 patients, and 620 samples were assigned to a training set. We measured the concentrations of 4 GVHD biomarkers (ST2, REG3α, TNFR1, and IL-2Rα) and used them to model 6-month NRM using rigorous cross-validation strategies to identify the best algorithm that defined 2 distinct risk groups. We then applied the final algorithm in an independent test set ( n = 309) and validation set ( n = 358). RESULTS. A 2-biomarker model using ST2 and REG3α concentrations identified patients with a cumulative incidence of 6-month NRM of 28% in the high-risk group and 7% in the low-risk group ( P < 0.001). The algorithm performed equally well in the test set (33% vs. 7%, P < 0.001) and the multicenter validation set (26% vs. 10%, P < 0.001). Sixteen percent, 17%, and 20% of patients were at high risk in the training, test, and validation sets, respectively. GVHD-related mortality was greater in high-risk patients (18% vs. 4%, P < 0.001), as was severe gastrointestinal GVHD (17% vs. 8%, P < 0.001). The same algorithm can be successfully adapted to define 3 distinct risk groups at GVHD onset. CONCLUSION. A biomarker algorithm based on a blood sample taken 7 days after HCT can consistently identify a group of patients at high risk for lethal GVHD and NRM. FUNDING. The National Cancer Institute, American Cancer Society, and the Doris Duke Charitable Foundation.

ABSTRACT Failure to eradicate Helicobacter pylori infection is often a result of antimicrobial resistance, which for clarithromycin is typically mediated by specific point mutations in the 23S rRNA gene. The purpose of this study was to define current patterns of antimicrobial susceptibility in H. pylori isolates derived primarily from the United States and to survey them for the presence of point mutations in the 23S rRNA gene and assess the ability of these mutations to predict phenotypic clarithromycin susceptibility. Antimicrobial susceptibility testing was performed using agar dilution on 413 H. pylori isolates submitted to Mayo Medical Laboratories for susceptibility testing. For a subset of these isolates, a 150-bp segment of the 23S rRNA gene was sequenced. A total of 1,970 MICs were reported over the 4-year study period. The rate of clarithromycin resistance was high (70.4%), and elevated MICs were frequently observed for metronidazole (82.4% of isolates had an MIC of >8 μg/ml) and ciprofloxacin (53.5% of isolates had an MIC of >1 μg/ml). A total of 111 archived H. pylori isolates underwent 23S rRNA gene sequencing; we found 95% concordance between genotypes and phenotypes ( P = 0.9802). Resistance to clarithromycin was most commonly due to an A2143G mutation (82%), followed by A2142G (14%) and A2142C (4%) mutations. Clinical H. pylori isolates derived primarily from the United States demonstrated a high rate of clarithromycin resistance and elevated metronidazole and ciprofloxacin MICs. The relative distribution of point mutations at positions 2143 and 2142 in the 23S rRNA gene in clarithromycin-resistant H. pylori was similar to that reported from other parts of the world; these mutations predict phenotypic resistance to clarithromycin.

Abstract Purpose: Recent progress in understanding the molecular biology of epithelial ovarian cancer has not yet translated into individualized treatment for these women or improvements in their disease outcome. Gene expression has been utilized to identify distinct molecular subtypes, but there have been no reports investigating whether or not molecular subtyping is predictive of response to bevacizumab in ovarian cancer. Experimental Design: DASL gene expression arrays were performed on FFPE tissue from patients enrolled on the ICON7 trial. Patients were stratified into four TCGA molecular subtypes. Associations between molecular subtype and the efficacy of randomly assigned therapy with bevacizumab were assessed. Results: Molecular subtypes were assigned as follows: 122 immunoreactive (34%), 96 proliferative (27%), 73 differentiated (20%), and 68 mesenchymal (19%). In univariate analysis patients with tumors of proliferative subtype obtained the greatest benefit from bevacizumab with a median PFS improvement of 10.1 months [HR, 0.55 (95% CI, 0.34–0.90), P = 0.016]. For the mesenchymal subtype, bevacizumab conferred a nonsignificant improvement in PFS of 8.2 months [HR 0.78 (95% CI, 0.44–1.40), P = 0.41]. Bevacizumab conferred modest improvements in PFS for patients with immunoreactive subtype (3.8 months; P = 0.08) or differentiated subtype (3.7 months; P = 0.61). Multivariate analysis demonstrated significant PFS improvement in proliferative subtype patients only [HR, 0.45 (95% CI, 0.27–0.74), P = 0.0015]. Conclusions: Ovarian carcinoma molecular subtypes with the poorest survival (proliferative and mesenchymal) derive a comparably greater benefit from treatment that includes bevacizumab. Validation of our findings in an independent cohort could enable the use of bevacizumab for those patients most likely to benefit, thereby reducing side effects and healthcare cost. Clin Cancer Res; 23(14); 3794–801. ©2017 AACR.