Evidence map›Paper›PMID 32526280›Full record

ArticleJournal of biomedical informatics2020

A novel method to estimate the indirect community benefit of HIV interventions using a microsimulation model of HIV disease.

Pooyan Kazemian, Sydney Costantini, Anne M Neilan, Stephen C Resch, Rochelle P Walensky, Milton C Weinstein, Kenneth A Freedberg

Open access · greenAbstract read
In one paragraph

Article in Journal of biomedical informatics, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed, 1 pooled it
0.4field-weighted citation impact, top 26% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

6 citing papers in PubMed, 1 synthesis or guideline pooled it, 18 citations in OpenAlex.

  1. Pooled it
  2. Review
  3. Daily Oral HIV Pre-exposure Prophylaxis Among Young Men Who Have Sex With Men in the United States: Cost-saving at Generic Drug Price.Clinical infectious diseases : an official publication of the Infectious Diseases Society of America · 2024
    Article
  4. Article
  5. Article
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors at 2 institutions in 1 country.

Pooyan KazemianMedical Practice Evaluation Center, Massachusetts General Hospital, Boston, MA, USA; Division of General Internal Medicine, Massachusetts General Hospital, Boston, MA, USA; Department of Medicine, Harvard Medical School, Boston, MA, USA. Electronic address: pooyan.kazemian@mgh.harvard.edu.
Sydney CostantiniMedical Practice Evaluation Center, Massachusetts General Hospital, Boston, MA, USA.
Anne M NeilanMedical Practice Evaluation Center, Massachusetts General Hospital, Boston, MA, USA; Department of Medicine, Harvard Medical School, Boston, MA, USA; Division of Infectious Diseases, Massachusetts General Hospital, Boston, MA, USA; Division of General Academic Pediatrics, Department of Pediatrics, Massachusetts General Hospital, Boston, USA.
Stephen C ReschDepartment of Health Policy and Management, Harvard T.H. Chan School of Public Health, Boston, MA, USA.
Rochelle P WalenskyMedical Practice Evaluation Center, Massachusetts General Hospital, Boston, MA, USA; Division of General Internal Medicine, Massachusetts General Hospital, Boston, MA, USA; Department of Medicine, Harvard Medical School, Boston, MA, USA; Division of Infectious Diseases, Massachusetts General Hospital, Boston, MA, USA.
Milton C WeinsteinDepartment of Health Policy and Management, Harvard T.H. Chan School of Public Health, Boston, MA, USA.
Kenneth A FreedbergMedical Practice Evaluation Center, Massachusetts General Hospital, Boston, MA, USA; Division of General Internal Medicine, Massachusetts General Hospital, Boston, MA, USA; Department of Medicine, Harvard Medical School, Boston, MA, USA; Department of Health Policy and Management, Harvard T.H. Chan School of Public Health, Boston, MA, USA; Division of Infectious Diseases, Massachusetts General Hospital, Boston, MA, USA.
Harvard University · USMassachusetts General Hospital · US

Funding

Optimizing HIV Care in Less Developed CountriesR01AI058736 · NIAID · MASSACHUSETTS GENERAL HOSPITAL · PI Kenneth Alan Freedberg, Emily Parker Hyle · 2004 to 2026
$21.5M
Optimizing HIV Care in Less Developed CountriesR37AI058736 · NIAID · MASSACHUSETTS GENERAL HOSPITAL · PI FREEDBERG, KENNETH ALAN · 2018 to 2024
$6.6M
Diagnosing and preventing HIV infection in adolescents and young adults in the US: clinical impact and cost-effectivenessK08HD094638 · NICHD · MASSACHUSETTS GENERAL HOSPITAL · PI NEILAN, ANNE · 2018 to 2023
$936k
NIAID NIH HHS R01 AI058736NIAID NIH HHS R37 AI058736NICHD NIH HHS K08 HD094638
6 · The paper itself

Abstract

backgroundMicrosimulation models of human immunodeficiency virus (HIV) disease that simulate individual patients one at a time and assess clinical and economic outcomes of HIV interventions often provide key details regarding direct individual clinical benefits ("individual benefit"), but they may lack detail on transmissions, and thus may underestimate an intervention's indirect benefits ("community benefit"). Dynamic transmission models can be used to simulate HIV transmissions, but they may do so at the expense of the clinical detail of microsimulations. We sought to develop, validate, and demonstrate a practical, novel method that can be integrated into existing HIV microsimulation models to capture this community benefit, integrating the effects of reduced transmission while keeping the clinical detail of microsimulations.

methodsWe developed a new method to capture the community benefit of HIV interventions by estimating HIV transmissions from the primary cohort of interest. The method captures the benefit of averting infections within the cohort of interest by estimating a corresponding gradual decline in incidence within the cohort. For infections averted outside the cohort of interest, our method estimates transmissions averted based on reductions in HIV viral load within the cohort, and the benefit (life-years gained and cost savings) of averting those infections based on the time they were averted. To assess the validity of our method, we paired it with the Cost-effectiveness of Preventing AIDS Complications (CEPAC) Model - a validated and widely-published microsimulation model of HIV disease. We then compared the consistency of model-estimated outcomes against outcomes of a widely-validated dynamic compartmental transmission model of HIV disease, the HIV Optimization and Prevention Economics (HOPE) model, using the intraclass correlation coefficient (ICC) with a two-way mixed effects model. Replicating an analysis done with HOPE, validation endpoints were number of HIV transmissions averted by offering pre-exposure prophylaxis (PrEP) to men who have sex with men (MSM) and people who inject drugs (PWID) in the US at various uptake and efficacy levels. Finally, we demonstrated an application of our method in a different setting by evaluating the clinical and economic outcomes of a PrEP program for MSM in India, a country currently considering PrEP rollout for this high-risk group.

resultsThe new method paired with CEPAC demonstrated excellent consistency with the HOPE model (ICC = 0.98 for MSM and 0.99 for PWID). With only the individual benefit of the intervention incorporated, a PrEP program for MSM in India averted 43,000 transmissions over a 5-year period and resulted in a lifetime incremental cost-effectiveness ratio (ICER) of US$2,300/year-of-life saved (YLS) compared to the status quo. After applying both the direct (individual) and indirect (community) benefits, PrEP averted 86,000 transmissions over the same period and resulted in an ICER of US$600/YLS.

conclusionsOur method enables HIV microsimulation models that evaluate clinical and economic outcomes of HIV interventions to estimate the community benefit of these interventions (in terms of survival gains and cost savings) efficiently and without sacrificing clinical detail. This method addresses an important methodological gap in health economics microsimulation modeling and allows decision scientists to make more accurate policy recommendations.

Indexed as

Anti-HIV AgentsHIV InfectionsPre-Exposure ProphylaxisSexual and Gender MinoritiesCost-Benefit AnalysisHomosexuality, MaleHumansMaleAnti-HIV AgentsCommunity BenefitHIVMSMPrEPSimulationTransmission

Identifiers

PMID32526280
PMCPMC7374016
OpenAlexW3034370126

What OpenQuestion holds

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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.