Improved mortality analysis in early-phase dose-ranging clinical trials for emergency medical diseases using Bayesian time-to-event models with active comparators.

Emergency medical diseases (EMDs) are the leading cause of death worldwide. A time-to-death analysis is needed to accurately identify the risks and describe the pattern of an EMD because the mortality rate can peak early and then decline. Dose-ranging Phase II clinical trials are essential for developing new therapies for EMDs. However, most dose-finding trials do not analyze mortality as a time-to-event endpoint. We propose three Bayesian dose-response time-to-event models for a secondary mortality analysis of a clinical trial: a two-group (active treatment vs control) model, a three-parameter sigmoid EMAX model, and a hierarchical EMAX model. The study also incorporates one specific active treatment as an active comparator in constructing three new models. We evaluated the performance of these six models and a very popular independent model using simulated data motivated by a randomized Phase II clinical trial focused on identifying the most effective hyperbaric oxygen dose to achieve favorable functional outcomes in patients with severe traumatic brain injury. The results show that the three-group, EMAX, and EMAX model with an active comparator produce the smallest averaged mean squared errors and smallest mean absolute biases. We provide a new approach for time-to-event analysis in early-phase dose-ranging clinical trials for EMDs. The EMAX model with an active comparator can provide valuable insights into the mortality analysis of new EMDs or other conditions that have changing risks over time. The restricted mean survival time, a function of the model's hazards, is recommended for displaying treatment effects for EMD research.

Assessing the incidence and severity of drug adverse events: a Bayesian hierarchical cumulative logit model.

Detection of safety signals based on multiple comparisons of adverse events (AEs) between two treatments in a clinical trial involves evaluations requiring multiplicity adjustment. A Bayesian hierarchical mixture model is a good solution to this problem as it borrows information across AEs within the same System Organ Class (SOC) and modulates extremes due merely to chance. However, the hierarchical model compares only the incidence rates of AEs, regardless of severity. In this article, we propose a three-level Bayesian hierarchical non-proportional odds cumulative logit model. Our model allows for testing the equality of incidence rate and severity for AEs between the control arm and the treatment arm while addressing multiplicities. We conduct simulation study to investigate the operating characteristics of the proposed hierarchical model. The simulation study demonstrates that the proposed method could be implemented as an extension of the Bayesian hierarchical mixture model in detecting AEs with elevated incidence rate and/or elevated severity. To illustrate, we apply our proposed method using the safety data from a phase III, two-arm randomized trial.

Racial differences in serum chemokines in prostate cancer patients.

BACKGROUND: This study aimed to understand the differential levels of inflammatory chemokines in association with higher prostate cancer incidence and mortality in African American (AA) men than in Caucasians (CA). METHODS: The authors used a chemokine assay to simultaneously measure 40 chemokines and cytokines levels in the serum of preoperative prostate cancer patients and healthy controls of AA and CA races. Selected chemokines (CXCL2, CXCL5, and CCL23) serum level was validated in 211 serum samples from prostate cancer patients and healthy controls. Differential expression of CXCL5 and CCL23 was analyzed using immunohistochemistry in a representative cohort of prostate tumor tissues of AA and CA races. RESULTS: Race-specific comparisons from 211 serum samples showed significantly higher levels of CXCL2 (control: 3104.0 pg/mL vs. cancer: 2451.0 pg/mL) and CXCL5 (control: 5189.0 pg/mL vs. cancer: 5459.0 pg/mL) in AA men than in CAs (CXCL2; control: 1155.0 pg/mL vs. cancer: 889.3 pg/mL, and CXCL5; control: 1183.0 pg/mL vs. cancer: 977.5 pg/mL). CCL23 differed significantly within and between the races with a lower level in AA cancer cases (454.5 vs. 966.6 pg/mL) than healthy controls (740.5 vs. 1263.0 pg/mL). Patient age, prostate-specific antigen, or Gleason scores were not significantly associated with these chemokines. Immunostaining for CXCL5 and CCL23 in a representative cohort of archival prostate tissues displayed significantly higher CXCL5 in prostate tumors than in adjacent benign tissues, whereas CCL23 was nondetectable in most of the analyzed tumor tissues. CONCLUSION: Lower levels of CCL23 in AA prostate cancer patient sera and tumor tissues and high CXCL2 and CXCL5 may contribute to aggressive prostate cancer, as often seen in AA men. The disproportionate levels of serum chemokines associated with race warrant further exploration to improve equitability in precision oncology to benefit prostate cancer patients.

Women Physicians and Promotion in Academic Medicine.

BACKGROUND: In 2000, a landmark study showed that women who graduated from U.S. medical schools from 1979 through 1997 were less likely than their male counterparts to be promoted to upper faculty ranks in academic medical centers. It is unclear whether these differences persist. METHODS: We merged data from the Association of American Medical Colleges on all medical school graduates from 1979 through 2013 with faculty data through 2018, and we compared the percentages of women who would be expected to be promoted on the basis of the proportion of women in the graduating class with the actual percentages of women who were promoted. We calculated Kaplan-Meier curves and used adjusted Cox proportional-hazards models to examine the differences between the early cohorts (1979-1997) and the late cohorts (1998-2013). RESULTS: The sample included 559,098 graduates from 134 U.S. medical schools. In most of the cohorts, fewer women than expected were promoted to the rank of associate or full professor or appointed to the post of department chair. Findings were similar across basic science and clinical departments. In analyses that included all the cohorts, after adjustment for graduation year, race or ethnic group, and department type, women assistant professors were less likely than their male counterparts to be promoted to associate professor (hazard ratio, 0.76; 95% confidence interval [CI], 0.74 to 0.78). Similar sex disparities existed in promotions to full professor (hazard ratio, 0.77; 95% CI, 0.74 to 0.81) and appointments to department chair (hazard ratio, 0.46; 95% CI, 0.39 to 0.54). These sex differences in promotions and appointments did not diminish over time and were not smaller in the later cohorts than in the earlier cohorts. The sex differences were even larger in the later cohorts with respect to promotion to full professor. CONCLUSIONS: Over a 35-year period, women physicians in academic medical centers were less likely than men to be promoted to the rank of associate or full professor or to be appointed to department chair, and there was no apparent narrowing in the gap over time. (Funded by the University of Kansas Medical Center Joy McCann Professorship for Women in Medicine and the American Association of University Women.).

The effect of type 2 diabetes and diabetic peripheral neuropathy on predictive grip force control.

This study investigated the impact of type 2 diabetes and diabetic peripheral neuropathy on grip force control during object manipulation. The study included three age-matched groups: type 2 diabetes alone (n = 11), type 2 diabetes with neuropathy (n = 13), and healthy controls (n = 12). Grip force control variables derived from lifting and holding an experimental cup were the ratio between grip force and load forces during lifting (GFR), latency 1 and latency 2, which represented the time between the object's grip and its lift-off from the table, and the period between object's lift-off and the grip force peak, respectively; time lag, which denoted the time difference between the grip and load force peaks during the lifting phase, and finally static force, which was the grip force average during the holding phase. Grip force control variables were compared between groups using one-way ANOVA and Kruskal-Wallis test. Post-hoc analysis was used to compare differences between groups. GFR and latency 1 showed significant differences between groups; the type 2 diabetes with neuropathy group showed larger GFR than the type 2 diabetes alone and healthy control groups. The latency 1was longer for the group with neuropathy in comparison with the health control group. There were no significant differences between groups for latency 2, time lag, and static force. Our results showed impaired GFR and latency 1 in participants with type 2 diabetes with neuropathy while the time lag was preserved. People with type 2 diabetes alone might not have any deficits in grip force control. Higher grip forces might expose people with type 2 diabetes and diabetic peripheral neuropathy to the risk of fatigue and injuring their hands. Future studies should investigate strategies to help people with type 2 diabetes with neuropathy adjust grip forces during object manipulation.

Unifying the analysis of continuous and categorical measures of weight loss and incorporating group effect: a secondary re-analysis of a large cluster randomized clinical trial using Bayesian approach.

BACKGROUND: Although frequentist paradigm has been the predominant approach to clinical studies for decades, some limitations associated with the frequentist null hypothesis significance testing have been recognized. Bayesian approaches can provide additional insights into data interpretation and inference by deriving posterior distributions of model parameters reflecting the clinical interest. In this article, we sought to demonstrate how Bayesian approaches can improve the data interpretation by reanalyzing the Rural Engagement in Primary Care for Optimizing Weight Reduction (REPOWER). METHODS: REPOWER is a cluster randomized clinical trial comparing three care delivery models: in-clinic individual visits, in-clinic group visits, and phone-based group visits. The primary endpoint was weight loss at 24 months and the secondary endpoints included the proportions of achieving 5 and 10% weight loss at 24 months. We reanalyzed the data using a three-level Bayesian hierarchical model. The posterior distributions of weight loss at 24 months for each arm were obtained using Hamiltonian Monte Carlo. We then estimated the probability of having a higher weight loss and the probability of having greater proportion achieving 5 and 10% weight loss between groups. Additionally, a four-level hierarchical model was used to assess the partially nested intervention group effect which was not investigated in the original REPOWER analyses. RESULTS: The Bayesian analyses estimated 99.5% probability that in-clinic group visits, compared with in-clinic individual visits, resulted in a higher percent weight loss (posterior mean difference: 1.8%[95% CrI: 0.5,3.2%]), a greater probability of achieving 5% threshold (posterior mean difference: 9.2% [95% CrI: 2.4, 16.0%]) and 10% threshold (posterior mean difference: 6.6% [95% CrI: 1.7, 11.5%]). The phone-based group visits had similar result. We also concluded that including intervention group did not impact model fit significantly. CONCLUSIONS: We unified the analyses of continuous (the primary endpoint) and categorical measures (the secondary endpoints) of weight loss with one single Bayesian hierarchical model. This approach gained statistical power for the dichotomized endpoints by leveraging the information in the continuous data. Furthermore, the Bayesian analysis enabled additional insights into data interpretation and inference by providing posterior distributions for parameters of interest and posterior probabilities of different hypotheses that were not available with the frequentist approach. TRIAL REGISTRATION: ClinicalTrials.gov Identifier NCT02456636 ; date of registry: May 28, 2015.

A prenatal group based phone counseling intervention to improve breastfeeding rates and complementary feeding: a randomized, controlled pilot and feasibility trial.

BACKGROUND: Despite numerous benefits for both mom and baby, few infants are exclusively breastfed for the recommended first six months. Additionally, infants are given solids too early. Prenatal education increases rates of breastfeeding initiation and we hypothesize it can also improve exclusive breastfeeding rates and prevent the early introduction of solids. We conducted a randomized controlled pilot and feasibility trial to understand the feasibility and maternal acceptance of a prenatal behavioral lifestyle intervention (PBLI) delivered via group based phone counseling (GBPC) and its effectiveness on rates of exclusive breastfeeding up to six months postpartum. Secondary aims included rates of any breastfeeding up to six months, rates of early introduction of solids, and infant feeding progression. METHODS: Forty-one pregnant women were recruited from a Kansas City Metropolitan Obstetrics and Gynecology office and randomly assigned to a usual care group or a PBLI. Women in the PBLI participated in six GBPC sessions where they learned about breastfeeding and introducing solids. Feeding questionnaires to assess breastfeeding and introduction of solids were sent at two weeks, two months, four months, and six months postpartum. Structured interviews were also conducted after the intervention and at six months postpartum to assess maternal acceptance and intervention feasibility. RESULTS: Participants overwhelmingly found the intervention acceptable and beneficial. Rates of exclusive breastfeeding and any breastfeeding did not differ between groups at any time point. No between group differences were found for early introduction of solids or infant feeding progression. CONCLUSIONS: Mothers discontinue breastfeeding earlier than recommended despite high rates of initiation. A PBLI delivered via GBP is feasible, acceptable to participants, and showed positive impacts such as maternal empowerment for both breastfeeding and introducing solids. Future interventions should incorporate both prenatal and postpartum components. TRIAL REGISTRATION: Study protocols were approved by the University of Kansas Medical Center's Human Subjects Committee (STUDY00140506) and registered at ClinicalTrials.gov on 02/22/2018 ( NCT03442517 , retrospectively registered). All participants gave written informed consent prior to data collection.

Designing and analyzing clinical trials for personalized medicine via Bayesian models.

Patients with different characteristics (e.g., biomarkers, risk factors) may have different responses to the same medicine. Personalized medicine clinical studies that are designed to identify patient subgroup treatment efficacies can benefit patients and save medical resources. However, subgroup treatment effect identification complicates the study design in consideration of desired operating characteristics. We investigate three Bayesian adaptive models for subgroup treatment effect identification: pairwise independent, hierarchical, and cluster hierarchical achieved via Dirichlet Process (DP). The impact of interim analysis and longitudinal data modeling on the personalized medicine study design is also explored. Interim analysis is considered since they can accelerate personalized medicine studies in cases where early stopping rules for success or futility are met. We apply integrated two-component prediction method (ITP) for longitudinal data simulation, and simple linear regression for longitudinal data imputation to optimize the study design. The designs' performance in terms of power for the subgroup treatment effects and overall treatment effect, sample size, and study duration are investigated via simulation. We found the hierarchical model is an optimal approach to identifying subgroup treatment effects, and the cluster hierarchical model is an excellent alternative approach in cases where sufficient information is not available for specifying the priors. The interim analysis introduction to the study design lead to the trade-off between power and expected sample size via the adjustment of the early stopping criteria. The introduction of the longitudinal modeling slightly improves the power. These findings can be applied to future personalized medicine studies with discrete or time-to-event endpoints.

Two-stage Bayesian hierarchical modeling for blinded and unblinded safety monitoring in randomized clinical trials.

BACKGROUND: Monitoring and reporting of drug safety during a clinical trial is essential to its success. More recent attention to drug safety has encouraged statistical methods development for monitoring and detecting potential safety signals. This paper investigates the potential impact of the process of the blinded investigator identifying a potential safety signal, which should be further investigated by the Data and Safety Monitoring Board with an unblinded safety data analysis. METHODS: In this paper, two-stage Bayesian hierarchical models are proposed for safety signal detection following a pre-specified set of interim analyses that are applied to efficacy. At stage 1, a hierarchical blinded model uses blinded safety data to detect a potential safety signal and at stage 2, a hierarchical logistic model is applied to confirm the signal with unblinded safety data. RESULTS: Any interim safety monitoring analysis is usually scheduled via negotiation between the trial sponsor and the Data and Safety Monitoring Board. The proposed safety monitoring process starts once 53 subjects have been enrolled into an eight-arm phase II clinical trial for the first interim analysis. Operating characteristics describing the performance of this proposed workflow are investigated using simulations based on the different scenarios. CONCLUSIONS: The two-stage Bayesian safety procedure in this paper provides a statistical view to monitor safety during the clinical trials. The proposed two-stage monitoring model has an excellent accuracy of detecting and flagging a potential safety signal at stage 1, and with the most important feature that further action at stage 2 could confirm the safety issue.

Correction to: Two-stage Bayesian hierarchical modeling for blinded and unblinded safety monitoring in randomized clinical trials.

An amendment to this paper has been published and can be accessed via the original article.

Bayesian accrual modeling and prediction in multicenter clinical trials with varying center activation times.

Investigators who manage multicenter clinical trials need to pay careful attention to patterns of subject accrual, and the prediction of activation time for pending centers is potentially crucial for subject accrual prediction. We propose a Bayesian hierarchical model to predict subject accrual for multicenter clinical trials in which center activation times vary. We define center activation time as the time at which a center can begin enrolling patients in the trial. The difference in activation times between centers is assumed to follow an exponential distribution, and the model of subject accrual integrates prior information for the study with actual enrollment progress. We apply our proposed Bayesian multicenter accrual model to two multicenter clinical studies. The first is the PAIN-CONTRoLS study, a multicenter clinical trial with a goal of activating 40 centers and enrolling 400 patients within 104 weeks. The second is the HOBIT trial, a multicenter clinical trial with a goal of activating 14 centers and enrolling 200 subjects within 36 months. In summary, the Bayesian multicenter accrual model provides a prediction of subject accrual while accounting for both center- and individual patient-level variation.

Utilization of Technology to Improve Efficiency in Investigational Drug Management Processes.

Background: Background: An investigational pharmacy is responsible for all tasks related to receiving, storing, and dispensing of any investigational drugs. Traditional methods of inventory and protocol tracking on paper binders are very tedious and could be error-prone. Objective: To evaluate the utilization of the IDS to efficiently manage the inventory within an investigational Pharmacy. We hypothesize that the IDS will reduce the drug processing time. Methods: Our pharmacy tracked the drug processing time before and after using the IDS including the receiving, dispensing, and inventory. As part of the receiving the study drug pharmacists tracked the time it took a pharmacist to complete the tasks of logging the study drug before and after the implementation of the IDS system. In addition, the pharmacy also timed the process for drug dispensing and a full investigational drug inventory check. Wilcoxon signed-rank test was used to compare the difference in the meantime of total processing before and after the IDS. Results: Utilization of the IDS system showed significant reduction in processing time, and improvement of efficiency in inventory management. Additionally, the usability survey of the IDS demonstrated that the IDS system helped pharmacists capture data consistently across every clinical trial. Conclusion: Our results demonstrates how technology helps pharmacists to focus on their actual day to day medication-related tasks rather than worrying about other operational aspects. Informatics team continues to further enhance the features such as monitor portal, and features related to finance - generation of invoices, billing reconciliation, etc.

T-cell trafficking plays an essential role in tumor immunity.

Distinct populations of effector memory T cells use different homing receptors to traffic to the skin and gut. Whether tissue-selective T cells are needed for early rejection of a neoplasm growing in these tissues remains an open question. We chose to study an allogeneic tumor model because growth of such a fully mismatched tumor would signify a profound immune deficit. We implanted allogeneic tumor cells in the skin or gut of mice deficient in either α(1,3) fucosyltransferases IV and VII, enzymes critical for generating E-selectin ligands on skin-homing T cells, or ß7 integrin, a component of the α4ß7 integrin ligand for the mucosal adressin MAdCAM. During the first 9 days after tumor implantation, FucTVII-/- mice showed a profoundly impaired capacity to reject tumors growing in the skin, but readily rejected tumors implanted in the gut. Rejection of tumors in the skin was even more impaired in mice deficient in both FucTIV and FucTVII. This impairment was corrected by infusion of T cells from normal mice. By contrast, ß7 integrin-/- mice showed profoundly impaired rejection of tumors in the gut, but no defect in the skin tumor rejection. These differences were unrelated to antigen recognition or effector function of T cells, since all strains of mice were capable of generating tumor-specific CTLs in vitro against the tumor cell line used in vivo. These results demonstrate that T-cell homing defects in vivo impair immune surveillance of peripheral epithelial tissues in a specific and selective fashion.

The impact of diabetic peripheral neuropathy on pinch proprioception.

This study aims to investigate the impact of type 2 diabetes (T2D) and diabetic peripheral neuropathy (DPN) on pinch proprioception and to establish the correlations with sensory impairments. We collected data from a total of 36 participants (healthy, n = 12; T2D without DPN, n = 11; and T2D + DPN, n = 13), all matched for age, 60 ± 6 years. Pinch proprioception was determined through 3 trials of attempts to actively reproduce 15° of pinch position without visual feedback. Target accuracy and precision was compared between groups using Kruskal-Wallis test. Sensation was tested through the two-point discrimination and Semmes-Weinstein monofilaments applied on the fingers. Sensory measures were correlated with pinch proprioception measures via Spearman's rank test. The T2D + DPN group showed significant decrements in accuracy and precision as compared to the T2D-only (p = 0.003 and p = 0.006, respectively) and the healthy groups (both p = 0.002); no significant differences were found between T2D-only and healthy. Spearman's rank showed moderate (r = 0.45-0.66, p < 0.001) correlations between pinch proprioception and sensory measures. Our results showed pinch proprioception disruption in people with T2D + DPN, but not in people with T2D-only. The awareness of pinch proprioceptive deficits is paramount for the safety of individuals with T2D and DPN. Moderate correlations between sensory impairments and pinch proprioceptive deficits suggest that not only superficial/discriminative sensation is implicated in proprioceptive decrements. Other mechanisms such as damage to muscle spindles or central nervous system associated with T2D + DPN warrant further investigations.

Accrual Prediction Program: A web-based clinical trials tool for monitoring and predicting accrual for early-phase cancer studies.

BACKGROUND: Monitoring subject recruitment is key to the success of a clinical trial. Accordingly, researchers have developed accrual-monitoring tools to support the design and conduct of trials. At an institutional level, delays in identifying studies with high risk of accrual failure can lead to inefficient and costly trials with little chances of meeting study objectives. Comprehensive accrual monitoring is necessary to the success of the research enterprise. METHODS: This article describes the design and implementation of the University of Kansas Cancer Center Accrual Prediction Program, a web-based platform was developed to support comprehensive accrual monitoring and prediction for all active clinical trials. The Accrual Prediction Program provides information on accrual, including the predicted completion date, predicted number of accrued subjects during the pre-specified accrual period, and the probability of achieving accrual targets. It relies on a Bayesian accrual prediction model to combine protocol information with real-time trial enrollment data and disseminates results via web application. RESULTS: First released in 2016, the Accrual Prediction Program summarizes enrollment information for active studies categorized by various trial attributes. The web application supports real-time evidence-based decision making for strategic resource allocation and study management of over 120 ongoing clinical trials at the University of Kansas Cancer Center. CONCLUSION: The Accrual Prediction Program makes accessing comprehensive accrual information manageable at an institutional level. Cancer centers or even entire institutions can reproduce the Accrual Prediction Program to achieve real-time comprehensive monitoring and prediction of subject accrual to aid investigators and administrators in the design, conduct, and management of clinical trials.

Supplemental Screening With Automated Breast Ultrasound in Women With Dense Breasts: Comparing Notification Methods and Screening Behaviors.

OBJECTIVE: Supplemental screening with ultrasound has been shown to detect additional breast malignancies in women with dense breast tissue and normal mammogram findings. The frequency of supplemental screening with automated breast ultrasound and the effect and type of breast tissue density notification on automated screening breast ultrasound utilization rates are unknown. MATERIALS AND METHODS: We examined normal mammogram results letters for patients with heterogeneously or extremely dense breast tissue between July 1, 2013, and June 30, 2014, by type of results letter, notification method, and sociodemographic characteristics. Logistic regression was used to examine the association between type of results letter and subsequent automated screening breast ultrasound. RESULTS: Among 3012 women with dense breast tissue and normal mammogram findings, 15% returned for supplemental automated screening breast ultrasound within 18 months of results letter notification. Compared with a similarly sized control group of women who did not undergo automated ultrasound, a significantly greater proportion of patients (86.9%) returned for breast ultrasound if they received a results letter indicating breast density in combination with a courtesy phone call (p < 0.001). Patients who received results letters with breast density notification including a statement that they may benefit from additional screening with automated breast ultrasound examination were 9.91 times (95% CI, 6.08-16.16) more likely to return for the examination than patients who did not receive breast density notification or mention of supplemental screening. CONCLUSION: Patient breast density notification and radiologists' recommendations for supplemental screening with breast ultrasound increase patient utilization of automated screening breast ultrasound examinations.

Bayesian design for two-arm randomized Phase II clinical trials with endpoints from the exponential family using multiple constraints.

Frequentist design for two-arm randomized Phase II clinical trials with outcomes from the exponential dispersion family was proposed previously, where the total sample sizes are minimized under multiple constraints on the standard errors of the estimated group means and their difference. This design was generalized from an approach specific for dichotomous outcomes. The two previous approaches measure the central tendency of each group and treatment effect based on mean and difference in means. Other measures such as median or hazard ratio are more appropriate under certain situations. In addition, the frequentist approaches assume that unknown parameters are fixed values. This does not reflect the reality that uncertainty always exists for unknowns. Compared to the frequentist methods, the Bayesian approach offers a flexible way to measure central tendency and treatment effect, and incorporate uncertainty in parameters of interest into considerations. In this article, we generalize a Bayesian design for Phase II clinical trials with endpoints in the exponential family from the two previously developed frequentist approaches. The proposed design minimizes the total sample sizes under pre-specified constraints on the expected length of posterior credible intervals for measures of treatment effect and central tendency in each group. The design is applicable for trials with fixed or optimal randomization allocation ratio and can be applied under adaptive procedure. Examples of method implementations are provided for different types of endpoints from the exponential family in both fixed and adaptive settings.

A novel evaluation of optimality for randomized controlled trials.

Balanced two-arm designs are more powerful than unbalanced designs and, consequently, Bayesian adaptive designs (BADs) are less powerful. However, when considering other subject- or community-focused design characteristics, fixed two-arm designs can be suboptimal. We use a novel approach to identify the best two-arm study design, taking into consideration both the statistical perspective and the community's perception. Data envelopment analysis (DEA) was used to estimate the relative performance of competing designs in the presence of multiple optimality criteria. The two-arm fixed design has enough deficiencies in subject- and community-specific benefit to make it the least favorable study design.

Reducing radiation exposure with iterative reconstruction: an inter- and intra-scanner analysis.

Our purpose in this study was to compare delivered radiation exposure via computed tomography dose index volume (CTDIvol) and dose length production (DLP) measurements from computed tomography (CT) examinations performed on scanners with and without image-quality enhancing iterative reconstruction (IR) software. A retrospective analysis was conducted on randomly selected chest, abdomen, and/or pelvis CT examinations from three different scanners from 1 January 2013 to 31 December 2013. CTDIvol and DLP measurements were obtained from two CT scanners with and one CT scanner without IR software. To evaluate inter-scanner variability, we compared measurements from the same model CT scanners, one with and one without IR software. To evaluate intra-scanner variability, we compared measurements between two scanners with IR software from different manufacturers. CT scanners with IR software aided in the overall reduction in radiation exposure, measured as CTDIvol by 30% and DLP by 39% when compared to a scanner without IR. There was no significant difference in CTDlvol or DLP measurements across different manufacturers with IR software. As a result, IR software significantly decreased the radiation exposure to patients, but there were no differences in radiation measurements across CT manufacturers with IR software.