Matthew J. Schipper, PhD
- Research Professor, Biostatistics
- Research Associate Professor, Radiation Oncology
- Center Cancer Biostatistics
- 1415 Washington Heights
- Ann Arbor, 48109-2029
Matthew Schipper is a Research Professor in the Departments of Radiation Oncology and Biostatistics. He received his PhD in Biostatistics from the University of Michigan in 2006. Prior to joining the Radiation Oncology department he was a Research Investigator in the Department of Radiology at the University of Michigan and a consulting statistician at Innovative Analytics.
- PhD, Biostatistics, University of Michigan, 2006
- M.S., Statistics, Western Michigan University, 2001
- B.S., Statistics, Western Michigan University, 2000
- Use of Biomarkers to Individualize Treatment - Selection of dose for cancer patients treated with Radiation Therapy (RT) must balance the increased efficacy with the increased toxicity associated with higher dose. Historically, a single dose has been selected for a population of patients (e.g. all stage III NSC lung cancer). However, the availability of new biologic markers for toxicity and efficacy allow the possibility of selecting a more personalized dose. I am interested in using statistical models for toxicity and efficacy as a function of RT dose and biomarkers to select an optimal dose for an individual patient. We are studying quantitative methods based on utilities to make this efficacy/toxicity tradeoff explicit and quantitative when biomarkers for one or multiple outcomes are available. We have proposed a simulation based method for studying the likely effects of any model or marker based dose selection on both toxicity and efficacy outcomes for a population of patients. In related projects, we are studying the role of correlation between the sensitivity of a patient' tumor and normal tissues to radiation. We are also studying how to utilize these techniques in combination with baseline and/or mid-treatment adaptive image guided RT.
- Early Phase Oncology Study Design – An increasingly common feature of phase I designs is the inclusion of 1 or more dose expansion cohorts (DECs) in which the MTD is first estimated using a 3+3 or other Phase I design and then a fixed number (often 10-20 in 1-10 cohorts) of patients are treated at the dose initially estimated to be the MTD. Such an approach has not been studied statistically or compared to alternative designs. We have shown that a CRM design, in which the dose-assignment mechanism is kept active for all patients, more accurately identifies the MTD and protects the safety of trial patients than a similarly sized DEC trial. It also meets the objective of treating 15 or more patients at the final estimated MTD. A follow-up paper evaluating the role of DECs with a focus on efficacy estimation is in press at Annals of Oncology.
- Boonstra PS, Braun TM, Taylor JMG, Kidwell K, Zhao L, Daignault SD, Griffith KA, Lawrence TS, Kalemkerian GP and Schipper MJ: Statistical Controversies In Cancer Research: Building the bridge to phase II: Efficacy estimation in dose-expansion cohorts. Ann Oncol (Accepted): 2017. (In Press)
- Dess R, Sun Y, ... Schipper MJ, Jolly S: Cardiac Events and Dose Escalated Radiotherapy: Combined Analysis of Prospective
Multicenter Trials for Locally Advanced Non-Small Cell Lung Cancer J Clin Oncol
(accepted for publication): 2017. (In Press)
- Wahl DR, Stenmark MH, Tao Y, Pollom EL, Caoili EM, Lawrence TS, Schipper MJ, Feng M: Outcomes After Stereotactic Body Radiotherapy or Radiofrequency Ablation for Hepatocellular Carcinoma. J Clin Oncol 34(5): 452-9, 2016. PM26628466/PMC4872011
- Boonstra PS, Shen J, Taylor JM, Braun TM, Griffith KA, Daignault S, Kalemkerian GP, Lawrence TS, Schipper MJ: A statistical evaluation of dose expansion cohorts in phase I clinical trials. J Natl Cancer Inst 107(3): pii: dju429, 2015. PM25710960
- Schipper MJ, Taylor JMG, TenHaken R, Matuzak M, Kong F and Lawrence TS.: Personalized dose selection in Radiation Therapy using statistical models for toxicity and efficacy with dose and biomarkers as covariates. Stat Med 33(30): 5330-9, 2014.
- Schipper M*, Vainshtein J*, Zalupski MM, Lawrence T, Abrams R, Francis IR, Khan G, Leslie W and Ben-Josef E. (). Prognostic Significance of CA 19-9 in Unresectable Locally Advanced Pancreatic Cancer Treated with Dose-Escalated Intensity Modulated Radiation Therapy and Concurrent Full Dose Gemcitabine: Analysis of a Prospective Phase I/II Dose Escalation Study Int J Radiation Oncology Biology Physics (Accepted). *Contributed equally to this work.
- Hunter K, Schipper M, Feng FY, Lyden T, Haxer M, Murdoch-Kinch C, Cornwall B, Lee C, Chepeha D, Eisbruch A. (). Toxicities affecting Quality of Life After Chemo-IMRT of Oropharyngeal Cancer: Prospective Study of Patient-Reported, Observer-Rated, and Objective Outcomes. Int J Radiation Oncology. Biology Physics (Accepted).
- Schipper MJ, Avram A., Kaminski MS and Dewaraja YK. I-131 (2012). Radioimmunotherapy: Prediction of tumor level therapy absorbed dose from the tracer study via a mixed model fit of time-activity. Cancer Biotherapy403-411.
- Sistare F, Goodsaid F, Schipper MJ [29/34], Yu Y. (2010). Towards Establishing Consensus Practices for Qualifying New Safety Biomarkers in Early Drug Development and Regulatory Decision-Making. Nature Biotechnology 446-54..
- Deiterle F, Sistare F, Goodsaid F, Schipper MJ [9/63] (2010). Mattes W. Renal Biomarker Qualification Submission: A dialog between the FDA/EMEA and PSTC. Nature Biotechnology 455-62.
- Schipper MJ, Taylor JM and Lin X. (2008). Generalized monotonic functional mixed models with application to modeling normal tissue complications. Journal of Royal Statistical Society 57(2): 1-15.
- Schipper MJ, Taylor JM and Lin X. (2007). Bayesian generalized monotonic functional mixed models for the effects of radiation dose histograms on normal tissue complications Statistics in Medicine 4643-56.
- American Statistical Association
- International Biometric Society