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Lung cancer diagnosis and mortality beyond 15 years since quit in individuals with a 20+ pack-year history: A systematic review.

Karli K KondoBasmah RahmanChelsea K AyersRose RelevoJessica C GriffinMichael T Halpern
Published in: CA: a cancer journal for clinicians (2023)
Current US lung cancer screening recommendations limit eligibility to adults with a pack-year (PY) history of ≥20 years and the first 15 years since quit (YSQ). The authors conducted a systematic review to better understand lung cancer incidence, risk and mortality among otherwise eligible individuals in this population beyond 15 YSQ. The PubMed and Scopus databases were searched through February 14, 2023, and relevant articles were searched by hand. Included studies examined the relationship between adults with both a ≥20-PY history and ≥15 YSQ and lung cancer diagnosis, mortality, and screening ineligibility. One investigator abstracted data and a second confirmed. Two investigators independently assessed study quality and certainty of evidence (COE) and resolved discordance through consensus. From 2636 titles, 22 studies in 26 articles were included. Three studies provided low COE of elevated lung cancer incidence beyond 15 YSQ, as compared with people who never smoked, and six studies provided moderate COE that the risk of a lung cancer diagnosis after 15 YSQ declines gradually, but with no clinically significant difference just before and after 15 YSQ. Studies examining lung cancer-related disparities suggest that outcomes after 15 YSQ were similar between African American/Black and White participants; increasing YSQ would expand eligibility for African American/Black individuals, but for a significantly larger proportion of White individuals. The authors observed that the risk of lung cancer not only persists beyond 15 YSQ but that, compared with individuals who never smoked, the risk may remain significantly elevated for 2 or 3 decades. Future research of nationally representative samples with consistent reporting across studies is needed, as are better data from which to examine the effects on health disparities across different populations.
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