Joseph DiStefano

Prof. Dr. Joseph DiStefano


Research Focus & Metrics

Academic Career Length

23Years (2004-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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1 November 2005 in Annals of Biomedical Engineering
Verified
Journal Article
Closed access
PDF file
GFGregory Z. Ferl
Gregory Z. Ferl
AWAnna M. Wu
Anna M. Wu
JDJoseph DiStefano
Joseph DiStefano

15 November 2019 in Frontiers in Endocrinology
Verified
Journal Article
Open access
PDF file
JDJoseph DiStefano
Joseph DiStefano
JJJacqueline Jonklaas
Jacqueline Jonklaas
Objective: To gain insight into the mixed results of reported combination therapy studies conducted with levothyroxine (LT4) and liothyronine (LT3) between 1999 and 2016. Methods: We defined trial success as improved clinical outcome measures and/or patient preference for added LT3. We hypothesized that success depends strongly on residual thyroid function (RTF) as well as the LT3 added to sufficient LT4 dosing to normalize serum T4 and TSH, all rendering T3 levels to at least middle-normal range. The THYROSIM app was used to simulate “what-if” experiments in patients and study designs corresponding to the study trials. The app graphically provided serum total (T4) and free (FT4) thyroxine, total (T3) and free (FT3) triiodothyronine, and TSH responses over time, to different simulated LT4 and combination LT4 + LT3 dosage inputs in patients with primary hypothyroidism. We compared simulation results with available study response data, computed RTF values that matched the data, classified and compared them with trial success measures, and also generated nomograms for optimizing dosages based on RTF estimates. Results: Simulation results generated three categories of patients with different RTFs and T3 and T4 levels at trial endpoints. Four trial groups had >20%, four <10%, and five 10–20% RTF. Four trials were predicted to achieve high, seven medium, and two low T3 levels. From these attributes, we were able to correctly predict 12 of 13 trials deemed successful or not. We generated an algorithm for optimizing dosage combinations suitable for different RTF categories, with the goal of achieving mid-range normal T4, T3 and TSH levels. RTF is estimated from TSH, T4 or T3 measurements prior to any hormone therapy treatment, using three new nonlinear nomograms for computing RTFs from these measurements. Recommended once-daily starting doses are: 100 μg LT4 + 10–12.5 μg LT3; 100 μg LT4 + 7.5–10 μg LT3; and 87.5 μg LT4 + 7.5 μg LT3; for 20% RTF, respectively. Conclusion: Unmeasured and variable RTF is a complicating factor in assessing effectiveness of combination LT4 + T3 therapy. We have estimated and partially validated RTFs for most existing trial data, using THYROSIM, and provided an algorithm for estimating RTF from accessible data, and optimizing patient dosing of LT4 + LT3 combinations for future combination therapy trials.

1 January 2004 in Journal of Cancer Research and Clinical Oncology
Verified
Journal Article
Closed access
PDF file
DTDaniel Tee
Daniel Tee
JDJoseph DiStefano
Joseph DiStefano

1 April 2016 in Thyroid®
Verified
Journal Article
Closed access
SHSimon X. Han
Simon X. Han
MEMarisa Eisenberg
Marisa Eisenberg
PLP. Reed Larsen
P. Reed Larsen
JDJoseph DiStefano
Joseph DiStefano
Background: Computer simulation tools for education and research are making increasingly effective use of the Internet and personal devices. To facilitate these activities in endocrinology and metabolism, a mechanistically based simulator of human thyroid hormone and thyrotropin (TSH) regulation dynamics was developed and further validated, and it was implemented as a facile and freely accessible web-based and personal device application: the THYROSIM app. This study elucidates and demonstrates its utility in a research context by exploring key physiological effects of over-the-counter thyroid supplements. Methods: THYROSIM has a simple and intuitive user interface for teaching and conducting simulated “what-if” experiments. User-selectable “experimental” test-input dosages (oral, intravenous pulses, intravenous infusions) are represented by animated graphical icons integrated with a cartoon of the hypothalamic–pituitary–thyroid axis. Simulations of familiar triiodothyronine (T3), thyroxine (T4), and TSH temporal dynamic responses to these exogenous stimuli are reported graphically, along with normal ranges on the same single interface page; and multiple sets of simulated experimental results are superimposable to facilitate comparative analyses. Results and Conclusions: This study shows that THYROSIM accurately reproduces a wide range of published clinical study data reporting hormonal kinetic responses to large and small oral hormone challenges. Simulation examples of partial thyroidectomies and malabsorption illustrate typical usage by optionally changing thyroid gland secretion and/or gut absorption rates—expressed as percentages of normal—as well as additions of oral hormone dosing, all directly on the interface, and visualizing the kinetic responses to these challenges. Classroom and patient education usage—with public health implications—is illustrated by predictive simulated responses to nonprescription thyroid health supplements analyzed previously for T3 and T4 content. Notably, it was found that T3 in supplements has potentially more serious pathophysiological effects than does T4—concomitant with low-normal TSH levels. Some preparations contain enough T3 to generate thyrotoxic conditions, with supernormal serum T3-spiking and subnormal serum T4 and TSH levels and, in some cases, with normal or low-normal range TSH levels due to thyroidal axis negative feedback. These results suggest that appropriate regulation of these products is needed.

14 July 2022 in Frontiers in Endocrinology
Verified
Journal Article
Open access
MCMauricio Cruz-Loya
Mauricio Cruz-Loya
BCBenjamin B. Chu
Benjamin B. Chu
JJJacqueline Jonklaas
Jacqueline Jonklaas
DSDavid F. Schneider
David F. Schneider
JDJoseph DiStefano
Joseph DiStefano
Objective: A personalized simulation tool, p-THYROSIM, was developed (1) to better optimize replacement LT4 and LT4+LT3 dosing for hypothyroid patients, based on individual hormone levels, BMIs, and gender; and (2) to better understand how gender and BMI impact thyroid dynamical regulation over time in these patients.Methods: p-THYROSIM was developed by (1) modifying and refining THYROSIM, an established physiologically based mechanistic model of the system regulating serum T3, T4, and TSH level dynamics; (2) incorporating sex and BMI of individual patients into the model; and (3) quantifying it with 3 experimental datasets and validating it with a fourth containing data from distinct male and female patients across a wide range of BMIs. For validation, we compared our optimized predictions with previously published results on optimized LT4 monotherapies. We also optimized combination T3+T4 dosing and computed unmeasured residual thyroid function (RTF) across a wide range of BMIs from male and female patient data.Results: Compared with 3 other dosing methods, the accuracy of p-THYROSIM optimized dosages for LT4 monotherapy was better overall (53% vs. 44%, 43%, and 38%) and for extreme BMI patients (63% vs. ~51% low BMI, 48% vs. ~36% and 22% for high BMI). Optimal dosing for combination LT4+LT3 therapy and unmeasured RTFs was predictively computed with p-THYROSIM for male and female patients in low, normal, and high BMI ranges, yielding daily T3 doses of 5 to 7.5 μg of LT3 combined with 62.5–100 μg of LT4 for women or 75–125 μg of LT4 for men. Also, graphs of steady-state serum T3, T4, and TSH concentrations vs. RTF (range 0%–50%) for untreated patients showed that neither BMI nor gender had any effect on RTF predictions for our patient cohort data. Notably, the graphs provide a means for estimating unmeasurable RTFs for individual patients from their hormone measurements before treatment.Conclusions: p-THYROSIM can provide accurate monotherapies for male and female hypothyroid patients, personalized with their BMIs. Where combination therapy is warranted, our results predict that not much LT3 is needed in addition to LT4 to restore euthyroid levels, suggesting opportunities for further research exploring combination therapy with lower T3 doses and slow-releasing T3 formulations.

1 January 2004 in Discrete and Continuous Dynamical Systems-Series B
Verified
Journal Article
Open access
PDF file
Pep CharusantiPep Charusanti
Pep Charusanti
XHXiao Hu
Xiao Hu
LCLuonan Chen
Luonan Chen
DNDaniel Neuhauser
Daniel Neuhauser
JDJoseph DiStefano
Joseph DiStefano
A mathematical model is presented that describes several signaling events that occur in cells from patients with chronic myeloid leukemia, i.e. autophosphorylation of the Bcr-Abl oncoprotein and subsequent signaling through the Crkl pathway. Dynamical effects of the drug STI-571 (Gleevec) on these events are examined, and a minimal concentration for drug effectiveness is predicted by simulation. Most importantly, the model suggests that, for cells in blast crisis, cellular drug clearance mechanisms such as drug efflux pumps dramatically reduce the effectiveness of Gleevec. This is a new prediction regarding the efficacy of Gleevec. In addition, it is speculated that these resistance mechanisms might be present from the onset of disease.