Improved automated spot counting and modeling with bias correction.

A complete workflow was presented for estimating the concentration of microorganisms in biological samples by automatically counting spots that represent viral plaque forming units (PFU) bacterial colony forming units (CFU), or spot forming units (SFU) in images, and modeling the counts. The workflow was designed for processing images from dilution series but can also be applied to stand-alone images. The accuracy of the methods was greatly improved by adding a newly developed bias correction method. When the spots in images are densely populated, the probability of spot overlapping increases, leading to systematic undercounting. In this paper, this undercount issue was addressed in an empirical way. The proposed empirical bias correction method utilized synthetic images with known spot sizes and counts as a training set, enabling the development of an effective bias correction function using a thin-plate spline model. Its application focused on the bias correction for the automated spot counting algorithm LoST proposed by Lin et al. Simulation results demonstrated that the empirical bias correction significantly improved spot counts, reducing bias for both fixed and random spot sizes and counts.

Automated Spot Counting in Microbiology.

Biological samples are routinely analyzed for microbe concentration. The samples are diluted, loaded onto established host cell cultures, and incubated. If infectious agents are present in the samples, they form circular spots that do not contain the host cells. Each spot is assumed to be originated from a single microbial unit such as a bacterial colony forming unit or viral plaque forming unit. The undiluted sample concentration is estimated by counting the spots and back-calculating. Counting the number of spots by trained technicians is currently the gold standard but it is laborious, subjective, and hard to scale. This paper presents a new automated algorithm for spot counting, Localized and Sequential Thresholding (LoST). Validation studies showed that LoST performance was comparable with manual counting and outperformed several existing tools on images with overlapping spots. The LoST algorithm employs sequential thresholding through a two-stage segmentation and borrows information across all images from the same dilution series to fine-tune the count and identify right censoring. The algorithm increases the efficiency of the spot counting and the quality of the downstream analysis, especially when coupled with an appropriate statistical serial dilution model to enhance the undiluted sample concentration estimation procedure.

Hybrid continuous reassessment method with overdose control for safer dose escalation.

Phase 1 oncology studies focus on safety of novel treatments and identifying a dose associated with acceptable toxicity level. Various model-based designs have been proposed for guiding dose escalation and estimating maximum tolerated dose in dose-finding studies. However, these methods are either excessively conservative or imprudent by allowing overly toxic doses. Transparent and easy to implement model-assisted designs have also received increasing attention but require pre-set rules including perceived dose levels. Therefore, we propose a hybrid model-based design that has a high probability to select MTD with a good balance of overdose control by disentangling in two separate models, which is flexible and easy to implement. Extensive simulations show the model to have real promise.

The treatment of missing data in a large cardiovascular clinical outcomes study.

BACKGROUND: The potential impact of missing data on the results of clinical trials has received heightened attention recently. A National Research Council study provides recommendations for limiting missing data in clinical trial design and conduct, and principles for analysis, including the need for sensitivity analyses to assess robustness of findings to alternative assumptions about the missing data. A Food and Drug Administration advisory committee raised missing data as a serious concern in their review of results from the ATLAS ACS 2 TIMI 51 study, a large clinical trial that assessed rivaroxaban for its ability to reduce the risk of cardiovascular death, myocardial infarction or stroke in patients with acute coronary syndrome. This case study describes a variety of measures that were taken to address concerns about the missing data. METHODS: A range of analyses are described to assess the potential impact of missing data on conclusions. In particular, measures of the amount of missing data are discussed, and the fraction of missing information from multiple imputation is proposed as an alternative measure. The sensitivity analysis in the National Research Council study is modified in the context of survival analysis where some individuals are lost to follow-up. The impact of deviations from ignorable censoring is assessed by differentially increasing the hazard of the primary outcome in the treatment groups and multiply imputing events between dropout and the end of the study. Tipping-point analyses are described, where the deviation from ignorable censoring that results in a reversal of significance of the treatment effect is determined. A study to determine the vital status of participants lost to follow-up was also conducted, and the results of including this additional information are assessed. RESULTS: Sensitivity analyses suggest that findings of the ATLAS ACS 2 TIMI 51 study are robust to missing data; this robustness is reinforced by the follow-up study, since inclusion of data from this study had little impact on the study conclusions. CONCLUSION: Missing data are a serious problem in clinical trials. The methods presented here, namely, the sensitivity analyses, the follow-up study to determine survival of missing cases, and the proposed measurement of missing data via the fraction of missing information, have potential application in other studies involving survival analysis where missing data are a concern.

An alternative approach to confidence interval estimation for the win ratio statistic.

Pocock et al. (2012, European Heart Journal 33, 176-182) proposed a win ratio approach to analyzing composite endpoints comprised of outcomes with different clinical priorities. In this article, we establish a statistical framework for this approach. We derive the null hypothesis and propose a closed-form variance estimator for the win ratio statistic in all pairwise matching situation. Our simulation study shows that the proposed variance estimator performs well regardless of the magnitude of treatment effect size and the type of the joint distribution of the outcomes.

Outcomes of discontinuing rivaroxaban compared with warfarin in patients with nonvalvular atrial fibrillation: analysis from the ROCKET AF trial (Rivaroxaban Once-Daily, Oral, Direct Factor Xa Inhibition Compared With Vitamin K Antagonism for Prevention of Stroke and Embolism Trial in Atrial Fibrillation).

OBJECTIVES: The purpose of this study was to understand the possible risk of discontinuation in the context of clinical care. BACKGROUND: Rivaroxaban is noninferior to warfarin for preventing stroke in atrial fibrillation patients. Concerns exist regarding possible increased risk of stroke and non-central nervous system (CNS) thromboembolic events early after discontinuation of rivaroxaban. METHODS: We undertook a post-hoc analysis of data from the ROCKET AF (Rivaroxaban Once-Daily, Oral, Direct Factor Xa Inhibition Compared With Vitamin K Antagonism for Prevention of Stroke and Embolism Trial in Atrial Fibrillation, n = 14,624) for stroke or non-CNS embolism within 30 days after temporary interruptions of 3 days or more, early permanent study drug discontinuation, and end-of-study transition to open-label therapy. RESULTS: Stroke and non-CNS embolism occurred at similar rates after temporary interruptions (rivaroxaban: n = 9, warfarin: n = 8, 6.20 vs. 5.05/100 patient-years, hazard ratio [HR]: 1.28, 95% confidence interval [CI]: 0.49 to 3.31, p = 0.62) and after early permanent discontinuation (rivaroxaban: n = 42, warfarin: n = 36, 25.60 vs. 23.28/100 patient-years, HR: 1.10, 95% CI: 0.71 to 1.72, p = 0.66). Patients transitioning to open-label therapy at the end of the study had more strokes with rivaroxaban (n = 22) versus warfarin (n = 6, 6.42 vs. 1.73/100 patient-years, HR: 3.72, 95% CI: 1.51 to 9.16, p = 0.0044) and took longer to reach a therapeutic international normalized ratio with rivaroxaban versus warfarin. All thrombotic events within 30 days of any study drug cessation (including stroke, non-CNS embolism, myocardial infarction, and vascular death) were similar between groups (HR: 1.02, 95% CI: 0.83 to 1.26, p = 0.85). CONCLUSIONS: In atrial fibrillation patients who temporarily or permanently discontinued anticoagulation, the risk of stroke or non-CNS embolism was similar with rivaroxaban or warfarin. An increased risk of stroke and non-CNS embolism was observed in rivaroxaban-treated patients compared with warfarin-treated patients after the end of the study, underscoring the importance of therapeutic anticoagulation coverage during such a transition.

Pharmacokinetic-pharmacodynamic assessment of topiramate dosing regimens for children with epilepsy 2 to <10 years of age.

PURPOSE: To identify and validate the efficacious monotherapy dosing regimen for topiramate in children aged 2 to <10 years with newly diagnosed epilepsy using pharmacokinetic-pharmacodynamic (PK-PD) modeling and simulation bridging. METHODS: Several models were developed in pediatric and adult populations to relate steady-state trough plasma concentrations (C(min)) of topiramate to the magnitude of clinical effect in monotherapy and adjunctive settings. These models were integrated to derive and support the monotherapy dosing regimen for pediatric patients. KEY FINDINGS: A two-compartmental population PK model with first-order absorption described the time course of topiramate C(min) as a function of dosing regimen. Disposition of topiramate was related to age, body weight, and use of various concomitant antiepileptic drugs. The PK-PD model for monotherapy indicated that the hazard of time to first seizure decreased with increasing C(min) and time since randomization. Higher baseline seizure frequency increased risk for seizures. Age did not significantly influence hazard of time to first seizure after randomization to monotherapy. For adjunctive therapy, the distribution of drug and placebo responses was not significantly different among age groups. Based on the available PK-PD modeling data, the dosing regimen expected to achieve a 65-75% seizure freedom rate after 1 year for pediatric patients age 2-10 years is approximately 6-9 mg/kg per day. SIGNIFICANCE: This analysis indicated no difference in PK-PD of topiramate between adult and pediatric patients. Effects of indication and body weight on PK were adequately integrated into the model, and monotherapy dosing regimens were identified for children 2-10 years of age.

Telemedicine consultation and monitoring for pediatric liver transplant.

Telemedicine provides the opportunity to bring medical expertise to the bedside, even if the medical expert is not physically near the patient. Internet technology has facilitated telemedicine allowing for voice, video and other data to be exchanged between remote locations. To date, applications of telemedicine to anesthesia (Teleanesthesia) have been limited. Previous work by Cone et al., (Anesth Analg 2006;1463-7) demonstrated the ability to direct an anesthetic in a remote location using satellite communication. In this report, we describe the use of telemedicine to support two cases of elective living related pediatric liver transplants performed at the Narayana Hrudayalaya Institute of Medical Sciences in Bangalore, India with preoperative and intraoperative consultation provided by physicians at the Children's Hospital of Philadelphia.

Industry, government, and academic panel discussion on multiple comparisons in a "real" phase three clinical trial.

A Food and Drug Administration (FDA)/Industry/Academic Panel Discussion on multiplicity aspects of a real Phase III clinical trial was held at the Third International Conference on Multiple Comparisons, August 6, 2002, in Bethesda, Maryland. The goal was to develop some consensus among industry, government, and academic statisticians concerning requirements and methods for multiplicity management in typical clinical trials. The session was tape-recorded; this article mostly comes from an edited transcript.