Evidence map›Paper›PMID 36935107›Full record

ArticleAmerican journal of epidemiology2023

Using LASSO Regression to Estimate the Population-Level Impact of Pneumococcal Conjugate Vaccines.

Anabelle Wong, Sarah C Kramer, Marco Piccininni, Jessica L Rohmann, Tobias Kurth, Sylvie Escolano, Ulrike Grittner, Matthieu Domenech de Cellès

Open access · hybridAbstract read
In one paragraph

Article in American journal of epidemiology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.

0numbers the graph read from it
0cells of the map it votes in
14citing papers in PubMed
3.9field-weighted citation impact, top 6% 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

14 citing papers in PubMed, 18 citations in OpenAlex.

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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

8 authors at 3 institutions in 2 countries.

Anabelle Wong
Sarah C Kramer
Marco Piccininni
Jessica L Rohmann
Tobias Kurth
Sylvie Escolano
Ulrike Grittner
Matthieu Domenech de Cellès
Charité - Universitätsmedizin Berlin · DEBerlin Institute of Health at Charité - Universitätsmedizin Berlin · DEUniversité Paris-Sud · FR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Pneumococcal conjugate vaccines (PCVs) protect against diseases caused by Streptococcus pneumoniae, such as meningitis, bacteremia, and pneumonia. It is challenging to estimate their population-level impact due to the lack of a perfect control population and the subtleness of signals when the endpoint-such as all-cause pneumonia-is nonspecific. Here we present a new approach for estimating the impact of PCVs: using least absolute shrinkage and selection operator (LASSO) regression to select variables in a synthetic control model to predict the counterfactual outcome for vaccine impact inference. We first used a simulation study based on hospitalization data from Mexico (2000-2013) to test the performance of LASSO and established methods, including the synthetic control model with Bayesian variable selection (SC). We found that LASSO achieved accurate and precise estimation, even in complex simulation scenarios where the association between the outcome and all control variables was noncausal. We then applied LASSO to real-world hospitalization data from Chile (2001-2012), Ecuador (2001-2012), Mexico (2000-2013), and the United States (1996-2005), and found that it yielded estimates of vaccine impact similar to SC. The LASSO method is accurate and easily implementable and can be applied to study the impact of PCVs and other vaccines.

Indexed as

Pneumococcal InfectionsPneumoniaBayes TheoremHumansInfantPneumococcal VaccinesStreptococcus pneumoniaeUnited StatesVaccines, ConjugatePneumococcal VaccinesVaccines, Conjugatecounterfactual predictionepidemiologic methodsLASSO regressionleast absolute shrinkage and selection operatorpneumococcal conjugate vaccinesStreptococcus pneumoniaevaccine impact

Identifiers

PMID36935107
PMCPMC10326487
OpenAlexW4327858836

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

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.