Forecast of myocardial infarction incidence, events and prevalence in England to 2035 using a microsimulation model with endogenous disease outcomes.
<h4>Background</h4>Models that forecast non-communicable disease rates are poorly designed to predict future changes in trend because they are based on exogenous measures of disease rates. We introduce microPRIME, which forecasts myocardial infarction (MI) incidence, events and prevalenc...
Saved in:
| Main Authors: | , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Public Library of Science (PLoS)
2022-01-01
|
| Series: | PLoS ONE |
| Online Access: | https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0270189&type=printable |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1849337249433387008 |
|---|---|
| author | Peter Scarborough Asha Kaur Linda J Cobiac |
| author_facet | Peter Scarborough Asha Kaur Linda J Cobiac |
| author_sort | Peter Scarborough |
| collection | DOAJ |
| description | <h4>Background</h4>Models that forecast non-communicable disease rates are poorly designed to predict future changes in trend because they are based on exogenous measures of disease rates. We introduce microPRIME, which forecasts myocardial infarction (MI) incidence, events and prevalence in England to 2035. microPRIME can forecast changes in trend as all MI rates emerge from competing trends in risk factors and treatment.<h4>Materials and methods</h4>microPRIME is a microsimulation of MI events within a sample of 114,000 agents representative of England. We simulate 37 annual time points from 1998 to 2035, where agents can have an MI event, die from an MI, or die from an unrelated cause. The probability of each event is a function of age, sex, BMI, blood pressure, cholesterol, smoking, diabetes and previous MI. This function does not change over time. Instead population-level changes in MI rates are due to competing trends in risk factors and treatment. Uncertainty estimates are based on 450 model runs that use parameters calibrated against external measures of MI rates between 1999 and 2011.<h4>Findings</h4>Forecasted MI incidence rates fall for men and women of different age groups before plateauing in the mid 2020s. Age-standardised event rates show a similar pattern, with a non-significant upturn by 2035, larger for men than women. Prevalence in men decreases for the oldest age groups, with peaks of prevalence rates in 2019 for 85 and older at 25.8% (23.3-28.3). For women, prevalence rates are more stable. Prevalence in over 85s is estimated as 14.5% (12.6-16.5) in 2019, and then plateaus thereafter.<h4>Conclusion</h4>We may see an increase in event rates from MI in England for men before 2035 but increases for women are unlikely. Prevalence rates may fall in older men, and are likely to remain stable in women over the next decade and a half. |
| format | Article |
| id | doaj-art-0b9721e624d7444ea9f3e2937ffdf487 |
| institution | Kabale University |
| issn | 1932-6203 |
| language | English |
| publishDate | 2022-01-01 |
| publisher | Public Library of Science (PLoS) |
| record_format | Article |
| series | PLoS ONE |
| spelling | doaj-art-0b9721e624d7444ea9f3e2937ffdf4872025-08-20T03:44:46ZengPublic Library of Science (PLoS)PLoS ONE1932-62032022-01-01176e027018910.1371/journal.pone.0270189Forecast of myocardial infarction incidence, events and prevalence in England to 2035 using a microsimulation model with endogenous disease outcomes.Peter ScarboroughAsha KaurLinda J Cobiac<h4>Background</h4>Models that forecast non-communicable disease rates are poorly designed to predict future changes in trend because they are based on exogenous measures of disease rates. We introduce microPRIME, which forecasts myocardial infarction (MI) incidence, events and prevalence in England to 2035. microPRIME can forecast changes in trend as all MI rates emerge from competing trends in risk factors and treatment.<h4>Materials and methods</h4>microPRIME is a microsimulation of MI events within a sample of 114,000 agents representative of England. We simulate 37 annual time points from 1998 to 2035, where agents can have an MI event, die from an MI, or die from an unrelated cause. The probability of each event is a function of age, sex, BMI, blood pressure, cholesterol, smoking, diabetes and previous MI. This function does not change over time. Instead population-level changes in MI rates are due to competing trends in risk factors and treatment. Uncertainty estimates are based on 450 model runs that use parameters calibrated against external measures of MI rates between 1999 and 2011.<h4>Findings</h4>Forecasted MI incidence rates fall for men and women of different age groups before plateauing in the mid 2020s. Age-standardised event rates show a similar pattern, with a non-significant upturn by 2035, larger for men than women. Prevalence in men decreases for the oldest age groups, with peaks of prevalence rates in 2019 for 85 and older at 25.8% (23.3-28.3). For women, prevalence rates are more stable. Prevalence in over 85s is estimated as 14.5% (12.6-16.5) in 2019, and then plateaus thereafter.<h4>Conclusion</h4>We may see an increase in event rates from MI in England for men before 2035 but increases for women are unlikely. Prevalence rates may fall in older men, and are likely to remain stable in women over the next decade and a half.https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0270189&type=printable |
| spellingShingle | Peter Scarborough Asha Kaur Linda J Cobiac Forecast of myocardial infarction incidence, events and prevalence in England to 2035 using a microsimulation model with endogenous disease outcomes. PLoS ONE |
| title | Forecast of myocardial infarction incidence, events and prevalence in England to 2035 using a microsimulation model with endogenous disease outcomes. |
| title_full | Forecast of myocardial infarction incidence, events and prevalence in England to 2035 using a microsimulation model with endogenous disease outcomes. |
| title_fullStr | Forecast of myocardial infarction incidence, events and prevalence in England to 2035 using a microsimulation model with endogenous disease outcomes. |
| title_full_unstemmed | Forecast of myocardial infarction incidence, events and prevalence in England to 2035 using a microsimulation model with endogenous disease outcomes. |
| title_short | Forecast of myocardial infarction incidence, events and prevalence in England to 2035 using a microsimulation model with endogenous disease outcomes. |
| title_sort | forecast of myocardial infarction incidence events and prevalence in england to 2035 using a microsimulation model with endogenous disease outcomes |
| url | https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0270189&type=printable |
| work_keys_str_mv | AT peterscarborough forecastofmyocardialinfarctionincidenceeventsandprevalenceinenglandto2035usingamicrosimulationmodelwithendogenousdiseaseoutcomes AT ashakaur forecastofmyocardialinfarctionincidenceeventsandprevalenceinenglandto2035usingamicrosimulationmodelwithendogenousdiseaseoutcomes AT lindajcobiac forecastofmyocardialinfarctionincidenceeventsandprevalenceinenglandto2035usingamicrosimulationmodelwithendogenousdiseaseoutcomes |