The University of Massachusetts Amherst

Cancers- Global

Project title: Decision-analytic tool for early detection of cancer in low and middle income countries

  1. Funding
  2. Student open positions
  3. Journal publications
  4. Policy impact
  5. Model Access
  6. Collaborators 
  7. Description 

Funding

World Health Organization, January 2015 - January 2016;
and January 2018 - December 2018
Principal Investigator: Chaitra Gopalappa

Student open positions:

Graduate student open positions? NO 
Undergraduate student open positions? YES
(contact Prof Gopalappa at chaitrag@umass.edu).
Suitable candidates: BS students at UMass- Amherst interested in doing an independent 
study, or Honors thesis in topics related to this project. 
Contact: Send an email to Prof Gopalappa at chaitrag@umass.edu with your CV 
and one paragraph statement of interest.

Journal publications

  • Shifali Bansal*, BS, Vijeta Deshpande*, MS, Xinmeng Zhao, BS, Jeremy A. Lauer, PhD, Filip  Meheus, PhD, André Ilbawi, MD, Chaitra Gopalappa1, PhD, Analysis of mammography screening schedules under varying resource constraints for planning breast cancer control programs in low- and middle- income countries: a mathematical study, Medical Decision Making, (In Print, Feb 2020) PDF
  • Gopalappa, C., Guo*, J., Meckoni*, P., Munkhbat*, B., Pretorius, C., Lauer, J., Ilbawi, A., Bertram, M., A two-step Markov processes approach for parameterization of cancer state-transition models for low- and middle- income countries, Medical Decision Making, PDF technical-suppl LINK
  • Ambinintsoa H. Ralaidovy, Chaitra  Gopalappa, André  Ilbawi, Carel  Pretorius and Jeremy A. Lauer, Cost-effective interventions for breast cancer, cervical cancer, and colorectal cancer: new results from WHO-CHOICE, Cost Effectiveness and Resource Allocation, 18 (38), 2018 LINK LINK

Policy impact: Used by the WHO to inform guidelines related to cancers of the breast, colorectal, and cervical for the Appendix 3 of the Global Action Plan for Non-Communicable Diseases, for the World Health Assembly.

Model Access

 Part of the non communicable disease (NCD) module in the Spectrum software a desktop application software (Work in Progress). Please contact Prof. Gopalappa at chaitrag@umass.edu for any questions related to the models.

Collaborators 

World Health Organization, International Agency for research on Cancer, Avenir Health, Pan-American Health Organization

Background

    •  Implementation of organized cancer screening and prevention programmes in high-income countries (HICs) has considerably decreased cancer related incidence and mortality. In low- and middle-income countries (LMICs), screening and early diagnosis programmes are generally unavailable, and a majority of cancers are diagnosed in late stages when survival is very low. Analyzing cost-effectiveness of alternative cancer control programmes and estimating resource needs will help health planner prioritize interventions in LMICs. However, mathematical models of natural cancer onset and progression, for conducting the economic analyses, are predominantly based on populations in HICs because the longitudinal data on screening and diagnoses required for parameterization are unavailable in LMICs. Models currently used for LMICs mostly concentrate on directly calculating the shift in distribution of cancer diagnosis as an evaluation measure of screening.

Work at UMass

    • At UMass Amherst we are developing new methodologies based for parameterization of natural cancer onset and progression, specifically for LMICs that do not have longitudinal data on screening and diagnoses.

Purpose

    •  Health planners can use the model to conduct economic analyses, i.e., compare costs and impact of alternative intervention options based on region-specific resource availabilities and disease burden, to prioritize program implementation. Alternative intervention options that health planners encounter could include (i) different types of screening modalities such as colonoscopy versus faecal immunochemical test for colorectal cancer; (ii) different screening intervals such as mammography every 1 year versus every 2 years to test for breast cancer; or (iii) combinations of interventions such as frequency of PapSmear to screen for cervical cancer in addition to HPV (human papillomavirus) vaccination to prevent cervical cancer.

Methods

    •  stochastic processes, non-linear simulation-based optimization, dynamic programming, and population-level simulation;

Software

    •  MATLAB