Evidence map›Paper›PMID 32404384›Full record

ArticleBMJ open2020

Novel microsimulation model of tobacco use behaviours and outcomes: calibration and validation in a US population.

Krishna P Reddy, Alexander J B Bulteel, Douglas E Levy, Pamela Torola, Emily P Hyle, Taige Hou, Benjamin Osher, Liyang Yu, Fatma M Shebl, A David Paltiel and 4 more

Abstract readComparative Study
In one paragraph

Article in BMJ open, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.

0numbers the graph read from it
0cells of the map it votes in
13citing papers in PubMed
–field-weighted citation impact
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

13 citing papers in PubMed.

  1. Review
  2. Article
  3. Article
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  5. Article
  6. Article
  7. Article
  8. Observational
  9. Calibration and Validation of the Colorectal Cancer and Adenoma Incidence and Mortality (CRC-AIM) Microsimulation Model Using Deep Neural Networks.Medical decision making : an international journal of the Society for Medical Decision Making · 2023
    Article
  10. 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

14 authors.

Krishna P ReddyMedical Practice Evaluation Center, Massachusetts General Hospital, Boston, Massachusetts, USA kpreddy@mgh.harvard.edu.ORCID 0000-0002-1832-2193
Alexander J B BulteelMedical Practice Evaluation Center, Massachusetts General Hospital, Boston, Massachusetts, USA.
Douglas E LevyTobacco Research and Treatment Center, Massachusetts General Hospital, Boston, Massachusetts, USA.
Pamela TorolaMedical Practice Evaluation Center, Massachusetts General Hospital, Boston, Massachusetts, USA.
Emily P HyleMedical Practice Evaluation Center, Massachusetts General Hospital, Boston, Massachusetts, USA.
Taige HouMedical Practice Evaluation Center, Massachusetts General Hospital, Boston, Massachusetts, USA.
Benjamin OsherMedical Practice Evaluation Center, Massachusetts General Hospital, Boston, Massachusetts, USA.
Liyang YuMedical Practice Evaluation Center, Massachusetts General Hospital, Boston, Massachusetts, USA.
Fatma M SheblMedical Practice Evaluation Center, Massachusetts General Hospital, Boston, Massachusetts, USA.
A David PaltielYale School of Public Health, New Haven, Connecticut, USA.
Kenneth A FreedbergMedical Practice Evaluation Center, Massachusetts General Hospital, Boston, Massachusetts, USA.
Milton C WeinsteinHarvard Medical School, Boston, Massachusetts, USA.
Nancy A RigottiTobacco Research and Treatment Center, Massachusetts General Hospital, Boston, Massachusetts, USA.
Rochelle P WalenskyMedical Practice Evaluation Center, Massachusetts General Hospital, Boston, Massachusetts, USA.

Funding

Clinical and Economic Outcomes of HIV, Cigarette Smoking, and Smoking Cessation InterventionsK01DA042687 · NIDA · MASSACHUSETTS GENERAL HOSPITAL · PI REDDY, KRISHNA P · 2016 to 2020
$929k
Cardiovascular Disease in South African HIV Patients: Value of PreventionK01HL123349 · NHLBI · MASSACHUSETTS GENERAL HOSPITAL · PI HYLE, EMILY PARKER · 2016 to 2020
$896k
NHLBI NIH HHS K01 HL123349NIDA NIH HHS K01 DA042687
6 · The paper itself

Abstract

BACKGROUND AND

objectiveSimulation models can project effects of tobacco use and cessation and inform tobacco control policies. Most existing tobacco models do not explicitly include relapse, a key component of the natural history of tobacco use. Our objective was to develop, calibrate and validate a novel individual-level microsimulation model that would explicitly include smoking relapse and project cigarette smoking behaviours and associated mortality risks.

methodsWe developed the Simulation of Tobacco and Nicotine Outcomes and Policy (STOP) model, in which individuals transition monthly between tobacco use states (current/former/never) depending on rates of initiation, cessation and relapse. Simulated individuals face tobacco use-stratified mortality risks. For US women and men, we conducted cross-validation with a Cancer Intervention and Surveillance Modeling Network (CISNET) model. We then incorporated smoking relapse and calibrated cessation rates to reflect the difference between a transient quit attempt and sustained abstinence. We performed external validation with the National Health Interview Survey (NHIS) and the linked National Death Index. Comparisons were based on root-mean-square error (RMSE).

resultsIn cross-validation, STOP-generated projections of current/former/never smoking prevalence fit CISNET-projected data well (coefficient of variation (CV)-RMSE≤15%). After incorporating smoking relapse, multiplying the CISNET-reported cessation rates for women/men by 7.75/7.25, to reflect the ratio of quit attempts to sustained abstinence, resulted in the best approximation to CISNET-reported smoking prevalence (CV-RMSE 2%/3%). In external validation using these new multipliers, STOP-generated cumulative mortality curves for 20-year-old current smokers and never smokers each had CV-RMSE ≤1% compared with NHIS. In simulating those surveyed by NHIS in 1997, the STOP-projected prevalence of current/former/never smokers annually (1998-2009) was similar to that reported by NHIS (CV-RMSE 12%).

conclusionsThe STOP model, with relapse included, performed well when validated to US smoking prevalence and mortality. STOP provides a flexible framework for policy-relevant analysis of tobacco and nicotine product use.

Indexed as

AdultAgedAged, 80 and overCalibrationCigarette SmokingComputer SimulationFemaleHumansMaleMiddle AgedNicotineOutcome Assessment, Health CarePrevalenceRecurrenceResearch DesignSmokingNicotinecalibrationmodelnicotinerelapsetobaccovalidation

Identifiers

PMID32404384
PMCPMC7228509

What OpenQuestion holds

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LicenceCC BY-NC
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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.