Search

PurposeDiscovery of SNPs that predict a patient's risk of docetaxel-induced neuropathy would enable treatment individualization to maximize efficacy and avoid unnecessary toxicity. The objectives of this analysis were to discover SNPs associated with docetaxel-induced neuropathy and mechanistically validate these associations in preclinical models of drug-induced neuropathy.Experimental designA genome-wide association study was conducted in metastatic castrate-resistant prostate cancer patients treated with docetaxel, prednisone and randomized to bevacizumab or placebo on CALGB 90401. SNPs were genotyped on the Illumina HumanHap610-Quad platform followed by rigorous quality control. The inference was conducted on the cumulative dose at occurrence of grade 3+ sensory neuropathy using a cause-specific hazard model that accounted for early treatment discontinuation. Genes with SNPs significantly associated with neuropathy were knocked down in cellular and mouse models of drug-induced neuropathy.ResultsA total of 498,081 SNPs were analyzed in 623 Caucasian patients, 50 (8%) of whom experienced grade 3+ neuropathy. The 1,000 SNPs most associated with neuropathy clustered in relevant pathways including neuropathic pain and axonal guidance. An SNP in VAC14 (rs875858) surpassed genome-wide significance (P = 2.12 × 10-8, adjusted P = 5.88 × 10-7). siRNA knockdown of VAC14 in stem cell-derived peripheral neuronal cells increased docetaxel sensitivity as measured by decreased neurite processes (P = 0.0015) and branches (P < 0.0001). Prior to docetaxel treatment, VAC14 heterozygous mice had greater nociceptive sensitivity than wild-type litter mate controls (P = 0.001).ConclusionsVAC14 should be prioritized for further validation of its potential role as a predictor of docetaxel-induced neuropathy and biomarker for treatment individualization. Clin Cancer Res; 22(19); 4890-900. ©2016 AACR.

BackgroundPreliminary data suggest a potential decreased benefit of docetaxel in patients with metastatic, castration-resistant prostate cancer (mCRPC) who previously received abiraterone acetate, a novel androgen synthesis inhibitor (ASI). Cancer and Leukemia Group B (CALGB) trial 90401 (Alliance), a phase 3 trial in patients with mCRPC who received docetaxel-based chemotherapy, offered the opportunity to evaluate effect of prior ketoconazole, an earlier generation ASI, on clinical outcomes after docetaxel.MethodsIn CALGB trial 90401, 1050 men with chemotherapy-naive mCRPC were randomized to receive treatment with docetaxel and prednisone that included either bevacizumab or placebo. In total, 1005 men (96%) had data available regarding prior ketoconazole therapy. The observed effects of prior ketoconazole on overall survival (OS), progression-free survival (PFS), prostate-specific antigen (PSA) decline, and the objective response rate (ORR) were assessed using proportional hazards and Poisson regression methods adjusted for validated prognostic factors and treatment arm.ResultsBaseline characteristics between patients who did (N=277) and did not (N=728) receive prior ketoconazole therapy were similar. There were no statistically significant differences between patients who did and those who did not receive prior ketoconazole therapy with respect to OS (median OS, 21.1 months vs 22.3 months, respectively; stratified log-rank P=.635), PFS (median PFS, 8.1 months vs 8.6 months, respectively; stratified log-rank P=.342), the proportion achieving a decline ≥ 50% in PSA (61% vs 66%, respectively; relative risk, 1.09; adjusted P=.129), or ORR (39% vs 43%, respectively; relative risk, 1.11; adjusted P=.366).ConclusionsAs measured by OS, PFS, PSA, and the ORR, there was no evidence that prior treatment with ketoconazole had an impact on the clinical outcomes of patients with mCRPC who received subsequent docetaxel-based therapy. The current results highlight the need for prospective studies to assess for potential cross-resistance with novel ASIs and to define the optimal sequence of therapy in mCRPC.

Approaches that use a simulated patient case to study and assess diagnostic reasoning usually use the correct diagnosis of the case as a measure of success and as an anchor for other measures. Commonly, the correctness of a diagnosis is determined by the judgment of one or more experts. In this study, the consistency of experts' judgments of the correctness of a diagnosis, and the structure of knowledge supporting their judgments, were explored using a card sorting task. Seven expert pediatricians were asked to sort into piles the diagnoses proposed by 119 individuals who had worked through a simulated patient case of "Haemophilus influenzae" Type B (HIB) meningitis. The 119 individuals had varying experience levels. The expert pediatricians were asked to sort the proposed diagnoses by similarity of content, and then to order the piles based on correctness, relative to the known correct diagnosis (HIB meningitis). Finally, the experts were asked to judge which piles contained correct or incorrect diagnoses. We found that, contrary to previous studies, experts shared a common conceptual framework of the diagnostic domain being considered and were consistent in how they categorized the diagnoses. However, similar to previous studies, the experts differed greatly in their judgment of which diagnoses were correct. This study has important implications for understanding expert knowledge, for scoring performance on simulated or real patient cases, for providing feedback to learners in the clinical setting, and for establishing criteria that define what is correct in studies of diagnostic error and diagnostic reasoning.

Benjamin Banneker, a self-taught mathematician, surveyor and astronomer published annual almanacs containing his astronomical observations and predictions. Banneker who also used logarithms to apply the Law of Sines believed that the method used to solve a mathematical problem depends on the tools available.

The presidential election that frequently features the results of political polling is presented. These polls attempt to estimate the popular vote that each candidate would receive as they could predict who would win the elections.