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. 2023 Nov:87:S1047-2797(23)00171-0.
doi: 10.1016/j.annepidem.2023.09.005. Epub 2023 Sep 22.

Impact of subgroup-specific heterogeneities and dynamic changes in mortality rates on forecasted population size, deaths, and age distribution of persons receiving antiretroviral treatment in the United States: a computer simulation study

Parastu Kasaie  1 , Cameron Stewart  2 , Elizabeth Humes  2 , Lucas Gerace  2 , Emily P Hyle  3 , Lauren C Zalla  2 , Peter F Rebeiro  4 , Michael J Silverberg  5 , Anna A Rubtsova  6 , Ashleigh J Rich  7 , Kelly Gebo  8 , Catherine R Lesko  2 , Anthony T Fojo  8 , Raynell Lang  9 , Jessie K Edwards  10 , Keri N Althoff  2
Affiliations

Impact of subgroup-specific heterogeneities and dynamic changes in mortality rates on forecasted population size, deaths, and age distribution of persons receiving antiretroviral treatment in the United States: a computer simulation study

Parastu Kasaie et al. Ann Epidemiol. 2023 Nov.

Abstract

Purpose: Model-based forecasts of population size, deaths, and age distribution of people with HIV (PWH) are helpful for public health and clinical services planning but are influenced by subgroup-specific heterogeneities and changes in mortality rates.

Methods: Using an agent-based simulation of PWH in the United States, we examined the impact of distinct approaches to parametrizing mortality rates on forecasted epidemiology of PWH on antiretroviral treatment (ART). We first estimated mortality rates among (1) all PWH, (2) sex-specific, (3) sex-and-race/ethnicity-specific, and (4) sex-race/ethnicity-and-HIV-acquisition-risk-specific subgroups. We then assessed each scenario by (1) allowing unrestricted reductions in age-specific mortality rates over time and (2) restricting the mortality rates among PWH to subgroup-specific mortality thresholds from the general population.

Results: Among the eight scenarios examined, those lacking subgroup-specific heterogeneities and those allowing unrestricted reductions in future mortality rates forecasted the lowest number of deaths among all PWH and 9 of the 15 subgroups through 2030. The forecasted overall number and age distribution of people with a history of injection drug use were sensitive to inclusion of subgroup-specific mortality rates.

Conclusions: Our results underscore the potential risk of underestimating future deaths by models lacking subgroup-specific heterogeneities in mortality rates, and those allowing unrestricted reductions in future mortality rates.

Keywords: Aging; Computer simulation; HIV; Hispanic ethnicity; Mortality; People who inject drugs; Racial disparities.

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Conflict of interest statement

Declaration of Competing Interest The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: Parastu Kasaie reports financial support was provided by National Institutes of Health. Keri Althof reports financial support was provided by National Institutes of Health. Emily Hyle reports financial support was provided by National Institutes of Health. Lauren Zalla reports financial support was provided by National Institutes of Health. Anthony Fojo reports financial support was provided by National Institutes of Health. Emily Hyle reports financial support was provided by Massachusetts General Hospital. Keri Althoff reports a relationship with TrioHealth that includes: board membership. KNA reports serving on the Scientific Advisory Board for TrioHealth Inc. and as a consultant to the All of Us Study (National Institutes of Health). PFR reports serving as a consultant for Gilead and Janssen Pharmaceuticals. Kelly Gebo is a consultant for Teach for America and the Aspen Institute and was an unpaid representative to a scientific Advisory Board for Pfizer. LCZ reports serving as a consultant for Carelon. None of these have direct relation to, or impact on, the findings presented here. All other authors declare no conflicts of interest.

Figures

Figure 1:
Figure 1:. Comparing forecasted mortality rates among PWH on ART across alternative scenarios (2010–2030).
Panel A compares median forecasted mortality rate (per 1,000 persons) among all PWH on ART across eight scenarios with varying subgroup-specific mortality rates and the use of general-population mortality rate thresholds. Restricted and unrestricted scenarios (according to Table 1) are shown via solid and dashed lines respectively. Panel B compares median forecasted mortality rates (per 1,000 persons) in restricted scenarios among 15 subgroups of PWH; unrestricted scenarios are presented in the Supplement S7. * Seven subgroups (including a. White, Hispanic and Black/AA WWID, b. White and Hispanic HET men, and c. White and Hispanic HET women) share a similar subgroups-specific mortality rate function (and were originally collapsed together to ensure a minimum of 100 deaths in NA-ACCORD). As such, our forecasts may overrepresent similarities in future mortality rates among these subgroups. Abbreviations: ART=antiretroviral therapy; PWH=people with HIV; HET=heterosexual; MSM=men who have sex with men; WWID= women who have ever injected drugs; MWID= men who have ever injected drugs
Figure 2:
Figure 2:. Comparing forecasted total deaths among PWH on ART (2010 – 2030) in the US across alternative scenarios.
Panel A compares forecasted total deaths (thousands) among PWH on ART across eight scenarios with varying subgroup-specific mortality rates and the use of general-population mortality rate thresholds. Panel B compares forecasted total deaths (thousands) in restricted scenarios among 15 subgroups of PWH; unrestricted scenarios are presented in the Supplement S7. Boxes represent the interquartile range and whiskers mark the 95% uncertainty range. * Seven subgroups (including a. White, Hispanic and Black/AA WWID, b. White and Hispanic HET men, and c. White and Hispanic HET women) share a similar subgroups-specific mortality rate function (and were originally collapsed together to ensure a minimum of 100 deaths in NA-ACCORD). As such, our forecasts may overrepresent similarities in future mortality rates among these subgroups. Abbreviations: ART=antiretroviral therapy; PWH=people living with HIV; HET=heterosexual; MSM=men who have sex with men; WWID= women who have ever injected drugs; MWID= men who have ever injected drugs
Figure 3:
Figure 3:. Forecasted trends in age-specific mortality rates among PWH on ART.
Black dots and gray shading represent observed age-specific mortality rate (per 1,000 person) and 95% confidence intervals, respectively, among PWH on ART in NA-ACCORD between 2009 to 2015. The dashed green line represents the 5-year age-specific death rate in the US general population in 2018 form CDC WONDER. The orange line represents the PEARL-forecasted mortality rates in each subgroup under the “sex-, race/ethnicity-, HIV acquisition risk-specific & restricted” scenario (applying a general-population mortality threshold) and the purple line represents the “sex-, race/ethnicity-, HIV acquisition risk-specific & unrestricted” model (allowing unrestricted reductions in age-specific mortality). The solid line represents the median value, and the shaded area marks the 95% uncertainty range. Other scenarios are presented in Supplement S8. Abbreviations: ART=antiretroviral therapy; CDC=Centers for Disease Control and Prevention; PWH=people with HIV
Figure 4:
Figure 4:. Comparing the forecasted age distributions of PWH on ART in 2030 under alternative mortality rate scenarios.
Panel A compares forecasts from restricted scenarios (applying general-population mortality rate thresholds) to assess the impact of subgroup-specific mortality rates on the overall age distribution of PWH in 2030 in the US. Panel B compares forecasts by the “sex-, race/ethnicity-, HIV acquisition risk-specific & restricted” scenario (solid line) vs “sex-, race/ethnicity-, HIV acquisition risk-specific & unrestricted” scenario (dashed line) in year 2030 to assess the impact of the general-population mortality rate thresholds on the overall age distribution of PWH in 2030 in the US. Panel C compares forecasts from scenarios “overall & restricted” and “sex-, race/ethnicity-, HIV acquisition risk-specific & restricted” among 15 subgroups of PWH to assess the heterogeneity in impact of subgroup-specific mortality rates on the age distribution in 2030. Values shown on each panel represent population size of PWH on ART (n) and the percentage over 65 years old. Abbreviations: ART=antiretroviral therapy; CDC=Centers for Disease Control and Prevention; PWH=people living with HIV; HET=heterosexual; MSM=men who have sex with men; WWID= women who have ever injected drugs; MWID= men who have ever injected drugs
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