Literature DB >> 30652561

Computational Model of Progression to Multiple Myeloma Identifies Optimum Screening Strategies.

Philipp M Altrock1, Jeremy Ferlic1, Tobias Galla1, Michael H Tomasson1, Franziska Michor1.   

Abstract

PURPOSE: Recent advances have uncovered therapeutic interventions that might reduce the risk of progression of premalignant diagnoses, such as monoclonal gammopathy of undetermined significance (MGUS) to multiple myeloma (MM). It remains unclear how to best screen populations at risk and how to evaluate the ability of these interventions to reduce disease prevalence and mortality at the population level. To address these questions, we developed a computational modeling framework.
MATERIALS AND METHODS: We used individual-based computational modeling of MGUS incidence and progression across a population of diverse individuals to determine best screening strategies in terms of screening start, intervals, and risk-group specificity. Inputs were life tables, MGUS incidence, and baseline MM survival. We measured MM-specific mortality and MM prevalence after MGUS detection from simulations and mathematic modeling predictions.
RESULTS: Our framework is applicable to a wide spectrum of screening and intervention scenarios, including variation of the baseline MGUS to MM progression rate and evolving MGUS, in which progression increases over time. Given the currently available point estimate of progression risk reduction to 61% risk, starting screening at age 55 years and performing follow-up screening every 6 years reduced total MM prevalence by 19%. The same reduction could be achieved with starting screening at age 65 years and performing follow-up screening every 2 years. A 40% progression risk reduction per patient with MGUS per year would reduce MM-specific mortality by 40%. Specifically, screening onset age and screening frequency can change disease prevalence, and progression risk reduction changes both prevalence and disease-specific mortality. Screening would generally be favorable in high-risk individuals.
CONCLUSION: Screening efforts should focus on specifically identified groups with high lifetime risk of MGUS, for which screening benefits can be significant. Screening low-risk individuals with MGUS would require improved preventions.

Entities:  

Mesh:

Year:  2018        PMID: 30652561      PMCID: PMC6873949          DOI: 10.1200/CCI.17.00131

Source DB:  PubMed          Journal:  JCO Clin Cancer Inform        ISSN: 2473-4276


  36 in total

1.  Risk of monoclonal gammopathy of undetermined significance (MGUS) and subsequent multiple myeloma among African American and white veterans in the United States.

Authors:  Ola Landgren; Gloria Gridley; Ingemar Turesson; Neil E Caporaso; Lynn R Goldin; Dalsu Baris; Thomas R Fears; Robert N Hoover; Martha S Linet
Journal:  Blood       Date:  2005-10-06       Impact factor: 22.113

Review 2.  Monoclonal gammopathy of undetermined significance (MGUS) and smoldering multiple myeloma (SMM): novel biological insights and development of early treatment strategies.

Authors:  Neha Korde; Sigurdur Y Kristinsson; Ola Landgren
Journal:  Blood       Date:  2011-03-25       Impact factor: 22.113

3.  Racial disparities in the prevalence of monoclonal gammopathies: a population-based study of 12,482 persons from the National Health and Nutritional Examination Survey.

Authors:  O Landgren; B I Graubard; J A Katzmann; R A Kyle; I Ahmadizadeh; R Clark; S K Kumar; A Dispenzieri; A J Greenberg; T M Therneau; L J Melton; N Caporaso; N Korde; M Roschewski; R Costello; G M McQuillan; S V Rajkumar
Journal:  Leukemia       Date:  2014-01-20       Impact factor: 11.528

Review 4.  Pathogenesis of monoclonal gammopathy of undetermined significance and progression to multiple myeloma.

Authors:  Adriana Zingone; W Michael Kuehl
Journal:  Semin Hematol       Date:  2011-01       Impact factor: 3.851

5.  Prevalence of monoclonal gammopathy of undetermined significance.

Authors:  Robert A Kyle; Terry M Therneau; S Vincent Rajkumar; Dirk R Larson; Matthew F Plevak; Janice R Offord; Angela Dispenzieri; Jerry A Katzmann; L Joseph Melton
Journal:  N Engl J Med       Date:  2006-03-30       Impact factor: 91.245

Review 6.  Body mass index and risk of multiple myeloma: a meta-analysis of prospective studies.

Authors:  Alice Wallin; Susanna C Larsson
Journal:  Eur J Cancer       Date:  2011-02-25       Impact factor: 9.162

7.  Monoclonal gammopathy of undetermined significance (MGUS) consistently precedes multiple myeloma: a prospective study.

Authors:  Ola Landgren; Robert A Kyle; Ruth M Pfeiffer; Jerry A Katzmann; Neil E Caporaso; Richard B Hayes; Angela Dispenzieri; Shaji Kumar; Raynell J Clark; Dalsu Baris; Robert Hoover; S Vincent Rajkumar
Journal:  Blood       Date:  2009-01-29       Impact factor: 22.113

8.  Improved survival in multiple myeloma and the impact of novel therapies.

Authors:  Shaji K Kumar; S Vincent Rajkumar; Angela Dispenzieri; Martha Q Lacy; Suzanne R Hayman; Francis K Buadi; Steven R Zeldenrust; David Dingli; Stephen J Russell; John A Lust; Philip R Greipp; Robert A Kyle; Morie A Gertz
Journal:  Blood       Date:  2007-11-01       Impact factor: 22.113

Review 9.  The skinny on obesity and plasma cell myeloma: a review of the literature.

Authors:  K R Carson; M L Bates; M H Tomasson
Journal:  Bone Marrow Transplant       Date:  2014-05-12       Impact factor: 5.483

10.  Monoclonal gammopathy of undetermined significance: predictors of malignant transformation and recognition of an evolving type characterized by a progressive increase in M protein size.

Authors:  Laura Rosiñol; M Teresa Cibeira; Silvia Montoto; María Rozman; Jordi Esteve; Xavier Filella; Joan Bladé
Journal:  Mayo Clin Proc       Date:  2007-04       Impact factor: 7.616

View more
  3 in total

1.  Designing optimal allocations for cancer screening using queuing network models.

Authors:  Justin Dean; Evan Goldberg; Franziska Michor
Journal:  PLoS Comput Biol       Date:  2022-05-27       Impact factor: 4.779

Review 2.  The 2019 mathematical oncology roadmap.

Authors:  Russell C Rockne; Andrea Hawkins-Daarud; Kristin R Swanson; James P Sluka; James A Glazier; Paul Macklin; David A Hormuth; Angela M Jarrett; Ernesto A B F Lima; J Tinsley Oden; George Biros; Thomas E Yankeelov; Kit Curtius; Ibrahim Al Bakir; Dominik Wodarz; Natalia Komarova; Luis Aparicio; Mykola Bordyuh; Raul Rabadan; Stacey D Finley; Heiko Enderling; Jimmy Caudell; Eduardo G Moros; Alexander R A Anderson; Robert A Gatenby; Artem Kaznatcheev; Peter Jeavons; Nikhil Krishnan; Julia Pelesko; Raoul R Wadhwa; Nara Yoon; Daniel Nichol; Andriy Marusyk; Michael Hinczewski; Jacob G Scott
Journal:  Phys Biol       Date:  2019-06-19       Impact factor: 2.959

Review 3.  System-based approaches as prognostic tools for glioblastoma.

Authors:  Manuela Salvucci; Zaitun Zakaria; Steven Carberry; Amanda Tivnan; Volker Seifert; Donat Kögel; Brona M Murphy; Jochen H M Prehn
Journal:  BMC Cancer       Date:  2019-11-12       Impact factor: 4.430

  3 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.