Giovanni Parmigiani

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Biography

Models and software for predicting who is at risk of carrying genetic variants that confer susceptibility to cancer. Application to breast, ovarian, colorectal, pancreatic and skin cancer.

Statistical methods for the analysis of high throughput genomic data: analysis of cancer genome sequencing projects; integration of genomic information across technologies; cross-study validation of genomics results.

Statistical methods for comparative effectiveness research: comprehensive models for lifetime history of chronic disease outcomes; Bayesian meta-analysis; Bayesian causal inference; decision analysis.

Bayesian modeling and computation: multilevel models; decision theoretic approaches to inference; sequential experimental design and their application to adaptive and multistage studies in clinical and epidemiological research.

Publications

• MSGene: a multistate model using genetic risk and the electronic health record applied to lifetime risk of coronary artery disease.

  Urbut SM, Yeung MW, Khurshid S, Cho SMJ, Schuermans A, German J, Taraszka K, Paruchuri K, Fahed AC, Ellinor PT, Trinquart L, Parmigiani G, Gusev A, Natarajan P, Urbut SM, Yeung MW, Khurshid S, Cho SMJ, Schuermans A, German J, Taraszka K, Paruchuri K, Fahed AC, Ellinor PT, Trinquart L, Parmigiani G, Gusev A, Natarajan P, Urbut SM, Yeung MW, Khurshid S, Cho SMJ, Schuermans A, German J, Taraszka K, Paruchuri K, Fahed AC, Ellinor PT, Trinquart L, Parmigiani G, Gusev A, Natarajan P. Nat Commun 2024 Jun 07

• Benefits and Harms of Interception and Early Detection of Cancer.

  Parmigiani G. Hematol Oncol Clin North Am 2024 08

• Bone marrow stromal cells induce chromatin remodeling in multiple myeloma cells leading to transcriptional changes.

  Binder M, Szalat RE, Talluri S, Fulciniti M, Avet-Loiseau H, Parmigiani G, Samur MK, Munshi NC. Nat Commun 2024 May 16

• Meta-analysis of breast cancer risk for individuals with PALB2 pathogenic variants.

  Ruberu TLM, Braun D, Parmigiani G, Biswas S. Genet Epidemiol 2024 Apr 23

• The Pancreatic Cancer Early Detection (PRECEDE) Study is a Global Effort to Drive Early Detection: Baseline Imaging Findings in High-Risk Individuals.

  Zogopoulos G, Haimi I, Sanoba SA, Everett JN, Wang Y, Katona BW, Farrell JJ, Grossberg AJ, Paiella S, Klute KA, Bi Y, Wallace MB, Kwon RS, Stoffel EM, Wadlow RC, Sussman DA, Merchant NB, Permuth JB, Golan T, Raitses-Gurevich M, Lowy AM, Liau J, Jeter JM, Lindberg JM, Chung DC, Earl J, Brentnall TA, Schrader KA, Kaul V, Huang C, Chandarana H, Smerdon C, Graff JJ, Kastrinos F, Kupfer SS, Lucas AL, Sears RC, Brand RE, Parmigiani G, Simeone DM. J Natl Compr Canc Netw 2024 04