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  • 1
    In: Nature, Springer Science and Business Media LLC, Vol. 568, No. 7750 ( 2019-4), p. 112-116
    Type of Medium: Online Resource
    ISSN: 0028-0836 , 1476-4687
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    Language: English
    Publisher: Springer Science and Business Media LLC
    Publication Date: 2019
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  • 2
    In: Proceedings of the National Academy of Sciences, Proceedings of the National Academy of Sciences, Vol. 119, No. 6 ( 2022-02-08)
    Abstract: Metastatic osteosarcoma has a poor prognosis with a 2-y, event-free survival rate of ∼15 to 20%, highlighting the need for the advancement of efficacious therapeutics. Chimeric antigen receptor (CAR) T-cell therapy is a potent strategy for eliminating tumors by harnessing the immune system. However, clinical trials with CAR T cells in solid tumors have encountered significant challenges and have not yet demonstrated convincing evidence of efficacy for a large number of patients. A major bottleneck for the success of CAR T-cell therapy is our inability to monitor the accumulation of the CAR T cells in the tumor with clinical-imaging techniques. To address this, we developed a clinically translatable approach for labeling CAR T cells with iron oxide nanoparticles, which enabled the noninvasive detection of the iron-labeled T cells with magnetic resonance imaging (MRI), photoacoustic imaging (PAT), and magnetic particle imaging (MPI). Using a custom-made microfluidics device for T-cell labeling by mechanoporation, we achieved significant nanoparticle uptake in the CAR T cells, while preserving T-cell proliferation, viability, and function. Multimodal MRI, PAT, and MPI demonstrated homing of the T cells to osteosarcomas and off-target sites in animals administered with T cells labeled with the iron oxide nanoparticles, while T cells were not visualized in animals infused with unlabeled cells. This study details the successful labeling of CAR T cells with ferumoxytol, thereby paving the way for monitoring CAR T cells in solid tumors.
    Type of Medium: Online Resource
    ISSN: 0027-8424 , 1091-6490
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    Language: English
    Publisher: Proceedings of the National Academy of Sciences
    Publication Date: 2022
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  • 3
    Online Resource
    Online Resource
    SAGE Publications ; 2018
    In:  Statistical Methods in Medical Research Vol. 27, No. 11 ( 2018-11), p. 3447-3459
    In: Statistical Methods in Medical Research, SAGE Publications, Vol. 27, No. 11 ( 2018-11), p. 3447-3459
    Abstract: The primary goal of a phase I clinical trial in oncology is to evaluate the safety of a novel treatment and identify the maximum tolerated dose, defined as the maximum dose with a toxicity rate below some pre-specified threshold. Researchers are often interested in evaluating the performance of a novel treatment in multiple patient populations, which may require multiple phase I trials if the treatment is to be used with background standard-of-care that varies by population. An alternate approach is to run parallel trials but combine the data through a hierarchical model that allows for a different maximum tolerated dose in each population but shares information across populations to achieve a more accurate estimate of the maximum tolerated dose. In this manuscript, we discuss hierarchical extensions of three commonly used models for the dose–toxicity relationship in phase I oncology trials. We then propose three dose-finding guidelines for phase I oncology trials using hierarchical modeling. The proposed guidelines allow us to fully realize the benefits of hierarchical modeling while achieving a similar toxicity profile to standard phase I designs. Finally, we evaluate the operating characteristics of a phase I clinical trial using the proposed hierarchical models and dose-finding guidelines by simulation. Our simulation results suggest that incorporating hierarchical modeling in phase I dose-escalation studies will increase the probability of correctly identifying the maximum tolerated dose and the number of patients treated at the maximum tolerated dose, while decreasing the rate of dose-limiting toxicities and number of patients treated above the maximum tolerated dose, in most cases.
    Type of Medium: Online Resource
    ISSN: 0962-2802 , 1477-0334
    Language: English
    Publisher: SAGE Publications
    Publication Date: 2018
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  • 4
    In: Clinical Trials, SAGE Publications, Vol. 18, No. 3 ( 2021-06), p. 324-334
    Abstract: Clinical trials, conducted efficiently and with the utmost integrity, are a key component in identifying effective vaccines, therapies, and other interventions urgently needed to solve the COVID-19 crisis. Yet launching and implementing trials with the rigor necessary to produce convincing results is a complicated and time-consuming process. Balancing rigor and efficiency involves relying on designs that employ flexible features to respond to a fast-changing landscape, measuring valid endpoints that result in translational actions and disseminating findings in a timely manner. We describe the challenges involved in creating infrastructure with potential utility for shared learning. Methods: We have established a shared infrastructure that borrows strength across multiple trials. The infrastructure includes an endpoint registry to aid in selecting appropriate endpoints, a registry to facilitate establishing a Data & Safety Monitoring Board, common data collection instruments, a COVID-19 dedicated design and analysis team, and a pragmatic platform protocol, among other elements. Results: The authors have relied on the shared infrastructure for six clinical trials for which they serve as the Data Coordinating Center and have a design and analysis team comprising 15 members who are dedicated to COVID-19. The authors established a pragmatic platform to simultaneously investigate multiple treatments for the outpatient with adaptive features to add or drop treatment arms. Conclusion: The shared infrastructure provides appealing opportunities to evaluate disease in a more robust manner with fewer resources and is especially valued during a pandemic where efficiency in time and resources is crucial. The most important element of the shared infrastructure is the pragmatic platform. While it may be the most challenging of the elements to establish, it may provide the greatest benefit to both patients and researchers.
    Type of Medium: Online Resource
    ISSN: 1740-7745 , 1740-7753
    Language: English
    Publisher: SAGE Publications
    Publication Date: 2021
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  • 5
    Online Resource
    Online Resource
    Elsevier BV ; 2018
    In:  Contemporary Clinical Trials Vol. 71 ( 2018-08), p. 162-172
    In: Contemporary Clinical Trials, Elsevier BV, Vol. 71 ( 2018-08), p. 162-172
    Type of Medium: Online Resource
    ISSN: 1551-7144
    Language: English
    Publisher: Elsevier BV
    Publication Date: 2018
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  • 6
    In: Clinical Lung Cancer, Elsevier BV, Vol. 22, No. 3 ( 2021-05), p. 201-209
    Type of Medium: Online Resource
    ISSN: 1525-7304
    Language: English
    Publisher: Elsevier BV
    Publication Date: 2021
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  • 7
    Online Resource
    Online Resource
    Elsevier BV ; 2022
    In:  The American Journal of Clinical Nutrition Vol. 116, No. 4 ( 2022-10), p. 1184-1185
    In: The American Journal of Clinical Nutrition, Elsevier BV, Vol. 116, No. 4 ( 2022-10), p. 1184-1185
    Type of Medium: Online Resource
    ISSN: 0002-9165
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    Language: English
    Publisher: Elsevier BV
    Publication Date: 2022
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  • 8
    In: The Lancet, Elsevier BV, Vol. 404, No. 10450 ( 2024-07), p. 353-363
    Type of Medium: Online Resource
    ISSN: 0140-6736
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    Language: English
    Publisher: Elsevier BV
    Publication Date: 2024
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    SSG: 5,21
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  • 9
    Online Resource
    Online Resource
    Ovid Technologies (Wolters Kluwer Health) ; 2024
    In:  Circulation Vol. 149, No. Suppl_1 ( 2024-03-19)
    In: Circulation, Ovid Technologies (Wolters Kluwer Health), Vol. 149, No. Suppl_1 ( 2024-03-19)
    Abstract: Introduction: A healthy low fat (HLF) and healthy low carbohydrate (HLC) diet are common strategies for weight loss that vary in their effects on adiposity and metabolism. Visceral adipose tissue (VAT) is the major contributor to metabolism deregulation, beyond subcutaneous adipose tissue (SAT). Despite strong biological evidence that a HLC diet preferentially decreases VAT relative to SAT, the difficulty in measuring adipose sub-types has impeded its use in diet trials. To address this research gap, we measured VAT and SAT in a secondary analysis of the Diet Intervention Examining The Factors Interacting with Treatment Success (DIETFITS) weight loss trial to compare the effects of HLF and HLC diets and potential effect modification by sex and insulin resistance status. Hypothesis: We hypothesized that a HLC diet is associated with greater VAT loss compared with a HLF diet. Secondly, we hypothesized that men and those with greater baseline insulin secretion assigned to HLC diet would experience greater VAT loss. Methods: DIETFITS was a single-site, parallel-group, weight loss diet trial, randomizing 609 adults with overweight and obesity to a HLC or HLF diet for 12 months. Data collection occurred at baseline, 6 months, and 12 months. Insulin resistance status was proxy measured using insulin concentration 30 minutes after a glucose challenge (INS 30). In this secondary analysis, we measured VAT and SAT in the abdominal region by reanalyzing the dual-energy x-ray absorptiometry (DXA) scans. We fit a linear mixed model to evaluate the change in VAT after 6 and 12 months on HLF and HLC, with fixed effects: time, diet, and their interaction; and a random effect for repeated observations. We built separate models for each of the secondary hypotheses, with additional fixed effects INS 30 and sex, respectively. Results: We included 449 participants with baseline DXA (60% women; mean age 40 years). From baseline to 6-months, participants assigned to a HLC diet experienced a significant 10.6 cm 2 (95% CI: 5.1, 16.1) greater decrease in mean VAT compared to those assigned to a HLF diet. The 12-month difference in diets attenuated to 5.5 cm 2 (95% CI: -0.1, 11.1). Contrary to our hypothesis, INS 30 did not modify the diet-related changes in VAT. Among men, both diets resulted in a 12-month decrease in VAT. The HLC diet was associated with a 12.1 cm 2 (95% CI: 1.6, 22.7) greater loss of VAT compared to HLF. Among women, HLF but not HLC was associated with decreased VAT, and there was no difference in VAT loss between diets 1.8 cm 2 (95% CI: -4.1, 7.6). Models controlling for SAT indicated that VAT decreased independently of SAT. Conclusion: These findings contribute to the understanding of the nuanced impacts of HLF and HLC diets on adipose sub-types and underscore the relevance of considering sex in designing effective dietary interventions targeting VAT reduction and metabolic health.
    Type of Medium: Online Resource
    ISSN: 0009-7322 , 1524-4539
    Language: English
    Publisher: Ovid Technologies (Wolters Kluwer Health)
    Publication Date: 2024
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  • 10
    Online Resource
    Online Resource
    American Association for Cancer Research (AACR) ; 2016
    In:  Cancer Research Vol. 76, No. 14_Supplement ( 2016-07-15), p. CT118-CT118
    In: Cancer Research, American Association for Cancer Research (AACR), Vol. 76, No. 14_Supplement ( 2016-07-15), p. CT118-CT118
    Abstract: Background: Basket trials are used to study targeted treatments across a range of tumor sites. In these designs all patients have the same target altered and receive the same regimen but they are placed in baskets defined by the site of primary tumor. This design is particularly appealing since the prevalence of the target mutation is typically low in any given tumor site, and the drug sponsor is naturally interested in as broad an indication for use as possible. Given the multiple baskets, this design requires the investigation of whether the activity of the regimen applies uniformly to all baskets, i.e., homogeneity of treatment effect, and if not, which baskets show sufficient response. Many basket trial designs to date have resembled parallel phase II studies, using Simon's two-stage design separately for each basket. The inclusion of multiple baskets increases the overall false positive rate in the trial, an aspect that is commonly not taken into account in current designs. More importantly, the use of independent, parallel phase II trials fails to take advantage of the opportunity to combine baskets in the event that the interim results suggest common responsiveness across baskets, either common evidence of efficacy or common evidence of lack of efficacy. Methods: We develop a novel, adaptive study design that makes use of an interim assessment of the heterogeneity of treatment effect across baskets to determine the most appropriate statistical analysis, while controlling the overall false positive rate in the trial. Our proposed design allows for aggregation of baskets in stage 2 when evidence points to a common effect of the drug, while retaining the option to maintain selected individual baskets in stage 2, if the interim evidence supports this strategy. Similar to conventional designs, our proposed design allows for early termination of baskets for lack of responsiveness. Using simulations we demonstrate the potential reduction in the number of patients required compared with the traditional strategy based on parallel Simon two-stage designs, while maintaining similar levels of Type I and II errors. Citation Format: Kristen M. Cunanan, Alexia Iasonos, Ronglai Shen, David Hyman, Colin Begg, Mithat Gonen. Efficient basket trial designs. [abstract]. In: Proceedings of the 107th Annual Meeting of the American Association for Cancer Research; 2016 Apr 16-20; New Orleans, LA. Philadelphia (PA): AACR; Cancer Res 2016;76(14 Suppl):Abstract nr CT118.
    Type of Medium: Online Resource
    ISSN: 0008-5472 , 1538-7445
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    Language: English
    Publisher: American Association for Cancer Research (AACR)
    Publication Date: 2016
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