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Risk Model-Based Lung Cancer Screening and Racial and Ethnic Disparities in the US.
Choi, Eunji; Ding, Victoria Y; Luo, Sophia J; Ten Haaf, Kevin; Wu, Julie T; Aredo, Jacqueline V; Wilkens, Lynne R; Freedman, Neal D; Backhus, Leah M; Leung, Ann N; Meza, Rafael; Lui, Natalie S; Haiman, Christopher A; Park, Sung-Shim Lani; Le Marchand, Loïc; Neal, Joel W; Cheng, Iona; Wakelee, Heather A; Tammemägi, Martin C; Han, Summer S.
Afiliação
  • Choi E; Quantitative Sciences Unit, Stanford University School of Medicine, Stanford, California.
  • Ding VY; Department of Neurosurgery, Stanford University School of Medicine, Stanford, California.
  • Luo SJ; Quantitative Sciences Unit, Stanford University School of Medicine, Stanford, California.
  • Ten Haaf K; Quantitative Sciences Unit, Stanford University School of Medicine, Stanford, California.
  • Wu JT; Department of Public Health, Erasmus Medical Center, Rotterdam, the Netherlands.
  • Aredo JV; Stanford University School of Medicine, Stanford, California.
  • Wilkens LR; Department of Medicine, University of California, San Francisco.
  • Freedman ND; Cancer Epidemiology Program, University of Hawaii Cancer Center, Honolulu, Hawaii.
  • Backhus LM; Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, Maryland.
  • Leung AN; Department of Cardiothoracic Surgery, Stanford University School of Medicine, Stanford, California.
  • Meza R; Department of Radiology, Stanford University School of Medicine, Stanford, California.
  • Lui NS; Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor.
  • Haiman CA; Department of Cardiothoracic Surgery, Stanford University School of Medicine, Stanford, California.
  • Park SL; Center for Genetic Epidemiology, Department of Population and Public Health Sciences, Keck School of Medicine, University of Southern California, Los Angeles.
  • Le Marchand L; Cancer Epidemiology Program, University of Hawaii Cancer Center, Honolulu, Hawaii.
  • Neal JW; Cancer Epidemiology Program, University of Hawaii Cancer Center, Honolulu, Hawaii.
  • Cheng I; Division of Oncology, Department of Medicine, Stanford University School of Medicine, Stanford, California.
  • Wakelee HA; Stanford Cancer Institute, Stanford University School of Medicine, Stanford, California.
  • Tammemägi MC; Department of Epidemiology and Biostatistics, University of California, San Francisco.
  • Han SS; Division of Oncology, Department of Medicine, Stanford University School of Medicine, Stanford, California.
JAMA Oncol ; 9(12): 1640-1648, 2023 Dec 01.
Article em En | MEDLINE | ID: mdl-37883107
ABSTRACT
Importance The revised 2021 US Preventive Services Task Force (USPSTF) guidelines for lung cancer screening have been shown to reduce disparities in screening eligibility and performance between African American and White individuals vs the 2013 guidelines. However, potential disparities across other racial and ethnic groups in the US remain unknown. Risk model-based screening may reduce racial and ethnic disparities and improve screening performance, but neither validation of key risk prediction models nor their screening performance has been examined by race and ethnicity.

Objective:

To validate and recalibrate the Prostate, Lung, Colorectal, and Ovarian Cancer Screening Trial 2012 (PLCOm2012) model-a well-established risk prediction model based on a predominantly White population-across races and ethnicities in the US and evaluate racial and ethnic disparities and screening performance through risk-based screening using PLCOm2012 vs the USPSTF 2021 criteria. Design, Setting, and

Participants:

In a population-based cohort design, the Multiethnic Cohort Study enrolled participants in 1993-1996, followed up through December 31, 2018. Data analysis was conducted from April 1, 2022, to May 19. 2023. A total of 105 261 adults with a smoking history were included. Exposures The 6-year lung cancer risk was calculated through recalibrated PLCOm2012 (ie, PLCOm2012-Update) and screening eligibility based on a 6-year risk threshold greater than or equal to 1.3%, yielding similar eligibility as the USPSTF 2021 guidelines.

Outcomes:

Predictive accuracy, screening eligibility-incidence (E-I) ratio (ie, ratio of the number of eligible to incident cases), and screening performance (sensitivity, specificity, and number needed to screen to detect 1 lung cancer).

Results:

Of 105 261 participants (60 011 [57.0%] men; mean [SD] age, 59.8 [8.7] years), consisting of 19 258 (18.3%) African American, 27 227 (25.9%) Japanese American, 21 383 (20.3%) Latino, 8368 (7.9%) Native Hawaiian/Other Pacific Islander, and 29 025 (27.6%) White individuals, 1464 (1.4%) developed lung cancer within 6 years from enrollment. The PLCOm2012-Update showed good predictive accuracy across races and ethnicities (area under the curve, 0.72-0.82). The USPSTF 2021 criteria yielded a large disparity among African American individuals, whose E-I ratio was 53% lower vs White individuals (E-I ratio 9.5 vs 20.3; P < .001). Under the risk-based screening (PLCOm2012-Update 6-year risk ≥1.3%), the disparity between African American and White individuals was substantially reduced (E-I ratio 15.9 vs 18.4; P < .001), with minimal disparities observed in persons of other minoritized groups, including Japanese American, Latino, and Native Hawaiian/Other Pacific Islander. Risk-based screening yielded superior overall and race and ethnicity-specific performance to the USPSTF 2021 criteria, with higher overall sensitivity (67.2% vs 57.7%) and lower number needed to screen (26 vs 30) at similar specificity (76.6%).

Conclusions:

The findings of this cohort study suggest that risk-based lung cancer screening can reduce racial and ethnic disparities and improve screening performance across races and ethnicities vs the USPSTF 2021 criteria.
Assuntos

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Detecção Precoce de Câncer / Neoplasias Pulmonares Limite: Adult / Female / Humans / Male / Middle aged Idioma: En Ano de publicação: 2023 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Detecção Precoce de Câncer / Neoplasias Pulmonares Limite: Adult / Female / Humans / Male / Middle aged Idioma: En Ano de publicação: 2023 Tipo de documento: Article