Peter F. Thall’s Personal Website
Here is a picture of me being a professional biostatistician. It requires computers and dogged determination.
Hobbies
Swimming; walking;
trading stock options; nonverbal canine communication; intergalactic
exploration; searching for movies worth the time to watch; gourmet cooking;
giving terribly useful advice to people who seem to need it; staying in hotels
in cities I probably wouldn’t visit if I weren’t attending a conference;
collecting not-too-expensive artwork.
Curriculum Vitae
For
a copy of my CV, click here.
Book on Dose
Finding Designs
Bayesian
Designs for Phase I-II Clinical Trials. Y. Yuan, H. Nguyen, and PF Thall. Chapman & Hall/CRC
Biostatistics Series, 2016.
Book on How to Avoid Making Dumb Mistakes
Statistical
Remedies for Medical Researchers. PF Thall, Springer Series in Biopharmaceutical Statistics,
2020.
This book is for anyone interested in medical research, including
biostatisticians, physicians, research nurses, people in the pharmaceutical
industry, and employees of federal regulatory agencies. It contains numerous
examples of common statistical practices that are deeply flawed. Many have become
conventions that, tragically, often are used in the medical literature. For each
example, the book provides an alternative approach, which most often is
Bayesian. Be sure to buy several copies of this timeless masterpiece to give as
Xmas and birthday presents. Your family dog also might like a copy to chew on.
A review of the book by Peter Mueller can be found at this link https://doi.org/10.1111/biom.13350
New Book
Bayesian
Precision Medicine.
PF Thall, 2024, Chapman and Hall/CRC Press.
After over four years of labor, under the guidance of Almighty God, I have published my third book. It is about methods that use Bayesian methods to identify personalized treatments. Here is a review of the book by Brad Carlin:
“With this latest book, Dr. Thall adds to his reputation as one of the most innovative thinkers in the field of adaptive clinical trial design. This book offers a wide variety of cutting-edge methods in Bayesian precision medicine, all explicated in the context of utility-driven designs that can simultaneously evaluate and trade off treatment safety and efficacy. The book’s unification of standard tools for causal inference with Bayesian methods is very welcome, as is its generous collection of case studies, most drawn from the author’s own extensive statistical consulting portfolio. It is a must-read for students and practitioners in biopharmaceutical statistics who want to see the current frontier of individualized complex innovative trial design.”
Bradley P. Carlin, Cencora-PharmaLex, USA
Publications
Some
of my publications are given in the links below. All of them are about
statistics, probability, medicine, or clinical trials. If you like one of the
papers, be sure to tell your friends and relatives about it.
Random Measures With
Aftereffects, Annals of Probability, 1978
A theorem on regular infinitely divisible
Cox processes. Stochastic Processes and Their Applications 16: 205-210, 1983
Two-stage selection and
testing designs for comparative clinical trials, Biometrika, 1988
Analysis of recurrent
events: nonparametric methods for random interval count data. JASA 83: 339-347,
1988
Poisson
likelihood regression models for longitudinal interval count data. Biometrics
44: 197-209, 1988
Some covariance
models for longitudinal count data with overdispersion. Biometrics 46: 657-671,
1990.
Test-based variable selection via
cross-validation. J Computational and Graphical Stat 1: 41-61, 1992
Practical Bayesian
guidelines for phase IIB clinical trials. Biometrics 50: 337-349, 1994
Bayesian sequential
monitoring designs for single-arm clinical trials with multiple outcomes. Stat
in Med 14:357-379, 1995
Estimating genomic
category probabilities from fluorescent in situ hybridization counts with
misclassification. JRSS-C (Applied Statistics) 45:431-446, 1996
Variable selection in regression via repeated
data splitting. J Comp and Graphical Stat, 6:416-434, 1997
Parametric likelihoods for
multiple non-fatal competing risks and death. Stat in Med, 17:999-1016, 1998
Some extensions and applications of a
Bayesian strategy for monitoring multiple outcomes in clinical trials. Stat in
Med, 17:1563-1580, 1998.
A strategy for dose finding
and safety monitoring based on efficacy and adverse outcomes in phase I/II
clinical trials. Biometrics 54:251-264, 1998.
Treatment
Comparisons Based on Two-Dimensional Safety and Efficacy Alternatives in
Oncology Trials, Biometrics 1999
Decision
Theoretic Designs for Phase II Clinical Trials with Multiple Outcomes,
Biometrics 1999
Accrual strategies for phase I trials with
delayed patient outcome, Statistics in Medicine, 1999
Decision
Theoretic Designs for Phase II Clinical Trials with Multiple Outcomes,
Biometrics 1999
Evaluating multiple treatment
courses in clinical trials. Stat in Med, 19: 1011-1028, 2000
Approximate Bayesian
Evaluation of Multiple Treatment Effects, Biometrics 56: 213-219, 2000
Decision-Theoretic
Designs for Pre-Phase II Screening Trials in Oncology, Biometrics 2001
Dose-Finding Based on
Feasibility and Toxicity in T-cell Infusion Trials, Biometrics 2001
Selecting therapeutic
strategies based on efficacy and death in multi-course clinical trials. JASA,
97:29-39, 2002
Ethical issues in oncology biostatistics.
Stat Meth in Medical Res, 11:429-448, 2002
Seamlessly Expanding a
Randomized Phase II Trial to Phase III, Biometrics, 2002
Adaptive Decision Making in
a Lymphocyte Infusion Trial, Biometrics, 2002
Monitoring the Rates of
Composite Events with Censored Data in Phase II Clinical Trials, Biometrics,
2002
Busulfan systemic exposure relative to
regimen-related toxicity and acute graft vs. host disease; defining a
therapeutic window for IVBuCy2 in chronic myelogenous leukemia. Biology of
Blood and Marrow Transplantation, 8:477-485, 2002
Hierarchical Bayesian
approaches to phase II trials in diseases with multiple subtypes. Statistics in
Medicine, 22: 763-780, 2003
Dose-finding with two
agents in phase I oncology trials. Biometrics, 59:487-496, 2003
Comparison of 100-day mortality
rates associated with IV busulfan and cyclophosphamide versus other preparative
regimens in allogeneic bone marrow transplant for chronic myelogenous leukemia:
Bayesian sensitivity analyses of confounded treatment and center effects. Bone
Marrow Transplantation, 33: 1191-1199, 2004.
Dose-finding based on multiple
toxicities in a soft tissue sarcoma trial. JASA, 99:26-35, 2004
Dose-finding based on
efficacy-toxicity trade-offs. Biometrics, 60:684-693, 2004.
Determining a Maximum-Tolerated
Schedule of a Cytotoxic Agent, Biometrics 61, 335–343, 2005
Monitoring event times in early
phase clinical trials: some practical issues. Clinical Trials. 2:467-478, 2005
Adaptive dose selection using
efficacy-toxicity trade-offs: illustrations and practical considerations. J
Biopharm Stat 16:623-638, 2006
A Geometric Approach to
Comparing Treatments for Rapidly Fatal Diseases, Biometrics 2006
Continuous Bayesian adaptive
randomization based on event times with covariates. Stat in Med, 25:55-70, 2006
Simultaneously optimizing
dose and schedule of a new cytotoxic agent. Clinical Trials, 4:113-124, 2007
Bayesian and frequentist two-stage
treatment strategies based on sequential failure times subject to interval censoring.
Stat in Med 26:4687-4702, 2007.
Adaptive Therapy for
Androgen-Independent Prostate Cancer: A Randomized Selection Trial of Four
Regimens, JNCI, 99:1613-1622, 2007
Phase I/II study of
gemtuzumab ozogamicin added to fludarabine, melphalan and allogeneic
hematopoietic stem cell transplantation for high-risk CD33 positive myeloid
leukemias and myelodysplastic syndrome. Leukemia. 22:258-264, 2008
Once
daily IV busulfan and fludarabine (IV Bu-Flu) compares favorably with IV
busulfan and cyclophosphamide (IV BuCy2) as pretransplant conditioning therapy
in AML/MDS. Biology of Blood and Marrow Transplantation. 14:672-684, 2008
A review of phase 2-3 clinical
trial designs. Lifetime Data Analysis. 14:37-53, 2008
Determining the effective sample size
of a parametric prior. Biometrics. 64:595-602, 2008.
Accounting for patient heterogeneity
in phase II clinical trials. Stat in Med 27:2802-2815, 2008
Monitoring late onset
toxicities in phase I trials using predicted risks. Biostatistics. 9:442-457,
2008
Patient-Specific Dose
Finding Based on Bivariate Outcomes and Covariates, Biometrics, 2008
Bayesian adaptive model selection for
optimizing group sequential clinical trials. Stat in Med, 27:5586-5604, 2008.
Bayesian hierarchical mixture model for
platelet derived growth factor receptor phosphorylation to improve estimation
of progression-free survival in prostate cancer. JRSS-C, 59:19-34, 2010.
Utility-based optimization of
combination therapy using ordinal toxicity and efficacy in phase I/II trials.
Biometrics. 66:532-540, 2010
Evaluating the impact of prior
assumptions in Bayesian biostatistics. Statistics in Biosciences. 2:1-17, 2010
Bayesian models and decision algorithms for
complex early phase clinical trials. Statistical Science. 25:227-244, 2010
Defining and ranking effects of individual
agents based on survival times of cancer patients treated with combination
chemotherapies. Stat in Med, 30:1777-1794, 2011
Optimizing the concentration and
bolus of a drug delivered by continuous infusion. Biometrics. 67:1638-1646,
2011
A hybrid geometric phase
II-III clinical trial design based on treatment failure time and toxicity. J
Stat Planning and Inf. 142:944-955, 2012
Estimating progression-free survival
in pediatric brain tumor patients when some progression statuses are unknown.
JRSS-C, 61:135-149, 2012
Evaluation of viable
dynamic treatment regimes in a sequentially randomized trial of advanced
prostate cancer (with discussion). JASA. 107:493-508, (with discussion, pages
509-517; rejoinder, pages 518-520), 2012
Adaptive randomization to improve
utility-based dose-finding with bivariate ordinal outcomes. J Biopharmaceutical
Stat. 22:785-801, 2012.
Prior effective sample
size in conditionally independent hierarchical models. Bayesian Analysis. 7:591-614,
2012.
Bayesian adaptive dose-finding
based on efficacy and toxicity. J. Statistical Research. 14:187-202, 2012.
Evaluating joint effects of
induction-salvage treatment regimes on overall survival in acute leukemia.
JRSS-C. 62:67-83, 2013.
Using joint utilities of
the times to response and toxicity to adaptively optimize schedule-dose
regimes. Biometrics 69:673-682, 2013.
Using data augmentation to
facilitate conduct of phase I/II clinical trials with delayed outcomes. J
American Statistical Assoc. 109:525-536, 2014.
Optimizing sedative dose in
preterm infants undergoing treatment for respiratory distress syndrome. J
American Statistical Assoc. 109:931-943, 2014.
Using effective sample size for
prior calibration in Bayesian phase I-II dose-finding. Clinical Trials.
11:657-666, 2014.
A modified adaptive Lasso
for identifying interactions in the Cox model with the heredity constraint.
Statistics and Probability Letters. 93:126-133, 2014.
Optimization of multi-stage
dynamic treatment regimes utilizing accumulated data. Statistics in Medicine,
34:3424-3443, 2015
SMART design,
conduct, and analysis in oncology. In Dynamic Treatment Regimes in Practice:
Planning Trials and Analyzing Data for Personalized Medicine. E Moodie and M.
Kosorok (eds), SIAM. In press.
Some caveats for
outcome adaptive randomization in clinical trials. In Modern Adaptive
Randomized Clinical Trials: Statistical, Operational, and Regulatory Aspects.
A. Sverdlov (ed). Taylor & Francis. 2015.
Bayesian dose-finding in
two treatment cycles based on the joint utility of efficacy and toxicity. J
American Statistical Assoc. 110:711-722, 2015.
Bayesian
nonparametric estimation of targeted agent effects on biomarker change to
predict clinical outcome. Biometrics. 71:188-197, 2015.
Comparing radiation modalities for
esophageal cancer based on total toxicity burden and disease-free survival. J
Royal Statistical Society, Series C (Applied Statistics) 65:273-297, 2016.
A Decision Theoretic Phase
I-II Design for Ordinal Outcomes in Two Cycles. Biostatistics 17:304-319, 2016.
Bayesian nonparametric estimation
for dynamic treatment regimes with sequential transition times J. American
Statistical Assoc. with discussion) 111:921-950, 2016.
Utility-based designs for randomized
comparative trials with discrete outcomes. Statistics in Medicine.
35:4285-4305, 2016.
Robust treatment comparison based on
utilities of semi-competing risks in non-small-cell lung cancer. J American
Statistical Assoc. 112:11-23, 2017.
A decision-theoretic
comparison of treatments to resolve air leaks after lung surgery based on
nonparametric modeling. Bayesian Analysis. 12(3):639-652, 2017.
Parametric dose
standardization for two-agent combinations in a phase I-II trial with ordinal
outcomes. J Royal Statistical Society, Series C (Applied Statistics).
66:201-224, 2017.
A simulation study of methods for
selecting subgroup-specific doses in phase I trials. Pharmaceutical
Statistics. 16:143-156, 2017.
Bayesian variable
selection for a semi-competing risks model with three hazard functions. Computational
Statistics and Data Analysis. 112:170-185, 2017.
Clinical trial design as a
decision problem. Applied Stochastic Models in Business and Industry.
(Invited, special issue in honor of Kathryn Chaloner) 33:296-301, 2017.
A simulation study of
outcome adaptive randomization in multi-arm clinical trials. Clinical Trials.
14:432-440, 2017.
Bayesian nonparametric
statistics: A new toolkit for discovery in cancer research. Pharmaceutical
Statistics. 16:414-423, 2017.
A Bayesian machine learning method for
optimizing dynamic treatment regimes. J American Statistical Assoc 113:523,
1255-1267, 2018.
Subgroup-specific dose finding in
phase I clinical trials based on time to toxicity allowing adaptive subgroup
combination. Pharmaceutical Statistics. 17:734-749, 2018.
A utility-based
design for randomized comparative trials with ordinal outcomes and prognostic
subgroups. Biometrics. 74:1095-1103, 2018.
Bayesian treatment comparison using
parametric mixture priors computed from elicited histograms Statistical
Methods in Medical Research. 28:404-418, 2019.
Optimizing natural killer
cell doses for heterogeneous cancer patients based on multiple event times. J
Royal Statistical Society, Series C (Applied Statistics). 68:461-474, 2019.
Bayesian nonparametric survival
regression for optimizing precision dosing of intravenous busulfan in
allogeneic stem cell transplantation. J Royal Statistical Society, Series C.
68:809-828, 2019.
Bayesian variable selection based
on clinical relevance weights in small sample studies - Application to colon
cancer. Statistics in Medicine. 38:2228-2247, 2019
A hybrid phase I-II/III
clinical trial design allowing dose re-optimization in phase III. Biometrics
(with discussion). Biometrics 75:371-381, discussion and rejoinder
382-391, 2019.
Bayesian
semiparametric joint regression analysis of recurrent adverse events and
survival in esophageal cancer patients. Annals of Applied Statistics.
13:221-247, 2019
An adaptive trial design to
optimize dose--schedule regimes with delayed outcomes. Biometrics.
76:304-315, 2020.
A phase I-II design based on periodic and
continuous monitoring of ordinal disease severity and the times to toxicity and
death. Statistics in Medicine. 39:2035–2050, 2020.
Integration of elicited expert
information via a power prior in Bayesian variable selection: application to
colon cancer data. Statistical Methods in Medical Research. 29:541-567,
2020
Comparing Bayesian early stopping
boundaries for phase II clinical trials. Pharmaceutical Statistics.
19:928–939, 2020.
A phase I-II basket
trial design to optimize dose-schedule regimes based on delayed outcomes. Bayesian
Analysis. 16:179-202, 2021.
Adaptive
enrichment designs in clinical trials. Annual Review of Statistics and Its
Application. (Invited) 8:393–411, 2021.
BAGS: A Bayesian adaptive group sequential
trial design with subgroup-specific survival comparisons. (Invited) J
American Statistical Association. 116:322-334, 2021.
Murray TA, Thall PF,
Schortgen F, Zohar S, Asfar P, Katsahian S. Robust adaptive incorporation of
historical control data in design of a randomized controlled trial to evaluate
external cooling in treatment of septic shock. Bayesian Analysis 16:825-844,
2021.
Lee J, Thall PF, Msaouel P.
Precision Bayesian phase I-II dose-finding based on utilities tailored to
prognostic subgroups. Stat in Medicine. 40:5199-5217, 2021.
Park Y, Liu S, Thall PF, Yuan
Y. Group sequential enrichment designs based on adaptive regression of response
and survival time on baseline biomarkers. Biometrics 78:60–71, 2022.
Lin R, Shi H, Yin G, Thall PF,
Yuan Y, Flowers CR. Bayesian hierarchical random-effects meta-analysis and
design of phase I clinical trials. Ann Applied Statistics 16:2481-2504, 2022.
Lee J, Thall PF, Lim
B, Msaouel P. Utility based Bayesian personalized treatment selection for
advanced breast cancer. J Royal Statistical Soc, C. 71:1605–1622, 2022.
Lee J, Thall PF, Msaouel P.
Bayesian treatment screening and selection using subgroup-specific utilities of
response and toxicity. Biometrics. 79:2458–2473, 2023..
Qing Y, Thall PF, Yuan Y.
A Bayesian piecewise exponential phase II design for monitoring a time-to-event
endpoint. Pharmaceutical Statistics. 22:34–44, 2023.
Msaouel P, Lee J, Thall PF. Making
patient-specific treatment decisions using prognostic variables and utilities
of clinical outcomes. Cancers. 2021, 13, 2741. https: //doi.org/ 10.3390/
cancers13112741
Msaouel P, Lee J, Karam JA, Thall PF.
A causal framework for making individualized treatment decisions in oncology.
Cancers. 14, 3923, 2022. https://doi.org/10.3390/cancers14163923
Msaouel P, Lee J, Thall PF. Interpreting
randomized controlled trials. Cancers. 15, 4674, 2023.
https://doi.org/10.3390/cancers15194674
Lui A, Lee J, Thall PF, Daher M,
Rezvani K, Barar R. A Bayesian feature allocation model for identification of
cell subpopulations using CYTOF data. J Royal Statistical Soc, C. 72:718-738,
2023.
Thall PF, Zang Y, Yuan Y. Generalized
phase I-II designs to increase long term therapeutic success rate.
Pharmaceutical Statistics. 22:692–706, 2023.
Jiang L, Thall PF, Yan F, Kopetz
S, Yuan Y. BASIC: A Bayesian adaptive synthetic control design for phase II
clinical trials. Clinical Trials. 20:486-496, 2023.
Thall PF, Zang Y, Chapple A, Yuan Y, Lin R,
Marin D, Msaouel P. Novel clinical trial designs that optimize dose to improve
long-term outcomes. Clinical Cancer Research. 29:4549-4554,2023.
Msaouel P, Lee J,
Thall PF. Risk-benefit trade-offs and precision utilities in phase I-II clinical
trials. Clinical Trials. 21(3):287–297, 2024.
Thall, et al.. Current issues in dose-finding designs: A response to the US Food and Drug Adminstrations’s Oncology Center of Excellence Project Optimus. Clinical Trials. 21(3):267–272, 2024.
Zang Y, Thall P, Yuan Y. A generalized phase 1-2-3 design
integrating dose optimization with confirmatory treatment comparison. Biometrics. 80(1) ujad022, 2024.
Yang Y, Cheng Y, Thall PF, Wahed A. GO-SMART: Generalized outcome-adaptive sequential multiple assignment randomized trial. Biometrics. 80(1) ujad022, 2024.