Approaches to Developing De Novo Cancer Population Models to Examine Questions about Cancer and Race in Bladder, Gastric, and Endometrial Cancer and Multiple Myeloma: The CISNET Incubator Program

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Sereda Y, Alarid-Escudero F, Bickell NA, Chang SH, Colditz GA, Hur C, Jalal H, Myers ER, Layne TM, Wang SY, Yeh JM, Trikalinos TA. Approaches to Developing De Novo Cancer Population Models to Examine Questions about Cancer and Race in Bladder, Gastric, and Endometrial Cancer and Multiple Myeloma: The CISNET Incubator Program. Journal of the National Cancer Institute Monographs, 2023 (In Press).

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@article{sereda2023approaches,
  title={Approaches to developing de novo cancer population models to examine questions about cancer and race in bladder, gastric, and endometrial cancer and multiple myeloma: the Cancer Intervention and Surveillance Modeling Network incubator program},
  author={Sereda, Yuliia and Alarid-Escudero, Fernando and Bickell, Nina A and Chang, Su-Hsin and Colditz, Graham A and Hur, Chin and Jalal, Hawre and Myers, Evan R and Layne, Tracy M and Wang, Shi-Yi and others},
  journal={JNCI Monographs},
  volume={2023},
  number={62},
  pages={219--230},
  year={2023},
  publisher={Oxford University Press}
}

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EndNote

%0 Journal Article
%T Approaches to developing de novo cancer population models to examine questions about cancer and race in bladder, gastric, and endometrial cancer and multiple myeloma: the Cancer Intervention and Surveillance Modeling Network incubator program
%A Sereda, Yuliia
%A Alarid-Escudero, Fernando
%A Bickell, Nina A
%A Chang, Su-Hsin
%A Colditz, Graham A
%A Hur, Chin
%A Jalal, Hawre
%A Myers, Evan R
%A Layne, Tracy M
%A Wang, Shi-Yi
%J JNCI Monographs
%V 2023
%N 62
%P 219-230
%@ 1052-6773
%D 2023
%I Oxford University Press

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RefMan

TY  - JOUR
T1  - Approaches to developing de novo cancer population models to examine questions about cancer and race in bladder, gastric, and endometrial cancer and multiple myeloma: the Cancer Intervention and Surveillance Modeling Network incubator program
A1  - Sereda, Yuliia
A1  - Alarid-Escudero, Fernando
A1  - Bickell, Nina A
A1  - Chang, Su-Hsin
A1  - Colditz, Graham A
A1  - Hur, Chin
A1  - Jalal, Hawre
A1  - Myers, Evan R
A1  - Layne, Tracy M
A1  - Wang, Shi-Yi
JO  - JNCI Monographs
VL  - 2023
IS  - 62
SP  - 219
EP  - 230
SN  - 1052-6773
Y1  - 2023
PB  - Oxford University Press
ER  - 

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Abstract

 

Background

We are developing 10 de novo population-level mathematical models in 4 malignancies (multiple myeloma and bladder, gastric, and uterine cancers). Each of these sites has documented disparities in outcome that are believed to be downstream effects of systemic racism.

Methods

Ten models are being independently developed as part of the Cancer Intervention and Surveillance Modeling Network incubator program. These models simulate trends in cancer incidence, early diagnosis, treatment, and mortality for the general population and are stratified by racial subgroup. Model inputs are based on large population datasets, clinical trials, and observational studies. Some core parameters are shared, and other parameters are model specific. All models are microsimulation models that use self-reported race to stratify model inputs. They can simulate the distribution of relevant risk factors (eg, smoking, obesity) and insurance status (for multiple myeloma and uterine cancer) in US birth cohorts and population.

Results

The models aim to refine approaches in prevention, detection, and management of 4 cancers given uncertainties and constraints. They will help explore whether the observed racial disparities are explainable by inequities, assess the effects of existing and potential cancer prevention and control policies on health equity and disparities, and identify policies that balance efficiency and fairness in decreasing cancer mortality.