Evidence map›Paper›PMID 38737675›Full record

ArticleTranslational cancer research2024

Safety net hospital risk model demonstrates stronger, population-specific applicability in characterizing lung cancer risk.

Adriana A Rodriguez Alvarez, Benjamin Crosby, Sarah Singh, Janice Weinberg, Nicole Byrne, Aniket Vazirani, Kei Suzuki

Abstract read
In one paragraph

Article in Translational cancer research, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed, 1 pooled it
–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

2 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Article
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.

Adriana A Rodriguez AlvarezDepartment of Clinical Research, Boston University Chobanian and Avedisian School of Medicine, Boston, MA, USA.ORCID https://orcid.org/0000-0002-5394-3323
Benjamin CrosbyDepartment of Clinical Research, Boston University Chobanian and Avedisian School of Medicine, Boston, MA, USA.
Sarah SinghDepartment of Surgery, University of California Davis, Sacramento, CA, USA.
Janice WeinbergDepartment of Biostatistics, Boston University School of Public Health, Boston, MA, USA.
Nicole ByrneDepartment of Clinical Research, Boston University Chobanian and Avedisian School of Medicine, Boston, MA, USA.
Aniket VaziraniDepartment of Surgery, Boston Medical Center, Boston, MA, USA.
Kei SuzukiDepartment of Thoracic Surgery, Inova Fairfax Medical Campus, Falls Church, VA, USA.ORCID https://orcid.org/0000-0002-2316-3158

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Determining lung cancer (LC) risk using personalized risk stratification may improve screening effectiveness. While the Prostate, Lung, Colorectal, and Ovarian Cancer Screening Trial (PLCO) is a well-established stratification model for LC screening, it was derived from a predominantly Caucasian population and its effectiveness in a safety net hospital (SNH) population is unknown. We have developed a model more tailored to the SNH population and compared its performance to the PLCO model in a SNH setting. Methods: Retrospective dataset was compiled from patients screened for LC at SNH from 2015 to 2019. Descriptive statistics were calculated using the following variables: age, sex, race, education, body mass index (BMI), smoking history, personal cancer history, family LC history, chronic obstructive pulmonary disease (COPD), and emphysema. Variables distribution was compared using Results: Of 896 individuals, 38 were diagnosed with LC. Data reflected the SNH patient demographics, which predominantly were African American (53.5%), current smokers (69.9%), and with emphysema (70.1%). Among the non-LC cohort, SNH model most frequently categorized patients as low risk, while PLCO model most frequently classified patients as moderate risk. Among the LC cohort, there was no significant difference between mean scores or risk stratification. SNH model showed 92.1% sensitivity and 96.8% specificity while PLCO model showed 89.4% sensitivity and 26.1% specificity. Emphysema demonstrated a strong association in SNH model (P<0.001) while race showed no relation. Conclusions: SNH model demonstrated greater specificity for characterizing LC risk in a SNH population. The results demonstrated the importance of study sample representation when identifying risk factors in a stratification model.

Indexed as

Diversity populationemphysemalow-dose computed tomography (LDCT)Prostate, Lung, Colorectal, and Ovarian Cancer Screening Trial model (PLCO model)safety net hospital model (SNH model)

Identifiers

PMID38737675
PMCPMC11082666

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Registered trials

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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.