[Show abstract][Hide abstract] ABSTRACT: The traditional concept of a P-value comparing an observed binomial probability to a prescribed value is extended to the ordered trinomial case in which target proportions have been specified for 'excellent', 'acceptable' and 'unacceptable' quality. The resulting trinomial probabilities are summarised by calculating two aggregate probabilities, relating to outcomes unequivocally better than, and unequivocally worse than, that actually observed, based on these assumed target proportions. Accumulations of exactly calculated tail probabilities on a mid-P basis are recommended.
Statistical Methods in Medical Research 04/2008; 17(609). · 4.47 Impact Factor
[Show abstract][Hide abstract] ABSTRACT: Urinary biomarkers for the detection of bladder cancer have been developed, but no similar markers exist for prediction of clinical outcomes after receiving chemotherapy. Here we evaluate an approach that combines genomic, proteomic, and therapeutic outcome datasets to identify novel putative urinary biomarkers of clinical outcome after neoadjuvant methotrexate, vinblastine, doxorubicin, and cisplatin (MVAC). Using this method, we identified gamma-glutamyl hydrolase (GGH), emmprin, survivin, and diazepam-binding inhibitor (DBI). Interestingly, GGH is a protein associated with methotrexate resistance, whereas emmprin, survivin, and DBI had been previously identified as predictors of outcome after platinum-containing chemotherapeutic regimens when assessed on tumor tissue. Using disease-free survival as a marker for clinical outcome, we evaluated the ability of GGH, emmprin, survivin, and DBI expression in tumor tissue to stratify 27 patients treated with neoadjuvant MVAC. DBI (P = 0.046) but not GGH (P = 0.190), emmprin (P = 0.066), or survivin (P = 0.393) successfully stratified patients. When GGH was used with DBI the significance of stratification improved (P = 0.024), whereas the addition of survivin or emmprin to this latter two-gene model reduced its significance (P = 0.036 and P = 0.040, respectively). Although these predictive results were obtained on tumor tissues, the presence of GGH and DBI in urine serves as a rationale for developing them as urinary markers of clinical outcomes for patients treated with neoadjuvant MVAC.
American Journal Of Pathology 10/2009; 175(5):1824-30. DOI:10.2353/ajpath.2009.090155 · 4.59 Impact Factor
[Show abstract][Hide abstract] ABSTRACT: Confidence intervals for a binomial parameter or for the ratio of Poisson means are commonly desired in high energy physics (HEP) applications such as measuring a detection efficiency or branching ratio. Due to the discreteness of the data, in both of these problems the frequentist coverage probability unfortunately depends on the unknown parameter. Trade-offs among desiderata have led to numerous sets of intervals in the statistics literature, while in HEP one typically encounters only the classic intervals of Clopper–Pearson (central intervals with no undercoverage but substantial over-coverage) or a few approximate methods which perform rather poorly. If strict coverage is relaxed, some sort of averaging is needed to compare intervals. In most of the statistics literature, this averaging is over different values of the unknown parameter, which is conceptually problematic from the frequentist point of view in which the unknown parameter is typically fixed. In contrast, we perform an (unconditional) average over observed data in the ratio-of-Poisson-means problem. If strict conditional coverage is desired, we recommend Clopper–Pearson intervals and intervals from inverting the likelihood ratio test (for central and non-central intervals, respectively). Lancaster's mid-P modification to either provides excellent unconditional average coverage in the ratio-of-Poisson-means problem.
Nuclear Instruments and Methods in Physics Research Section A Accelerators Spectrometers Detectors and Associated Equipment 01/2010; 612(2-612):388-398. DOI:10.1016/j.nima.2009.10.156 · 1.22 Impact Factor
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