Evidence map›Paper›PMID 42876681›Full record

ArticleFrontiers in public health2026

Uncovering the mortality burden of lung cancer with documented sleep apnea in the United States: a 22-year population-based study.

Lan Lin, Ping Shi, Qingyuan Li, Tong Feng, Ran Duan, Pengcheng Zheng

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Article in Frontiers in public health, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

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2 · The registry

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

6 authors.

Lan Lin *Department of Nursing, The Second Affiliated Hospital of Chengdu Medical College (China National Nuclear Corporation 416 Hospital), Chengdu, China.
Ping Shi *Department of Respiratory and Critical Care, Guangyuan Central Hospital, Guangyuan, China.
Qingyuan Li *School of Clinical Medicine, Chengdu Medical College, Chengdu, China.
Tong FengDepartment of Respiratory and Critical Care Medicine, Deyang People's Hospital, Affiliated Hospital of Chengdu Medical College, Deyang, China.
Ran DuanSchool of Clinical Medicine, Chengdu Medical College, Chengdu, China.
Pengcheng ZhengSchool of Clinical Medicine, Chengdu Medical College, Chengdu, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Lung cancer remains the leading cause of cancer-related mortality worldwide, and sleep apnea may identify a clinically vulnerable subgroup of patients with lung cancer. However, population-level mortality patterns involving lung cancer with documented sleep apnea remain unclear. This study examined long-term trends, disparities, geographic variation, socioeconomic patterns, and future projections of related mortality in the United States. Methods: We conducted a retrospective population-based analysis using CDC WONDER Multiple Cause of Death data from 1999 to 2020. Deaths were included when lung cancer was recorded as the underlying cause of death and sleep apnea as a contributing cause. Age-adjusted mortality rates (AAMRs) were calculated per 100,000 population. Temporal trends were assessed using Joinpoint regression, historical AAMRs were projected with ARIMA models, out-of-sample performance was evaluated against final 2021-2024 CDC WONDER data, and state-level Sociodemographic Index and frontier analyses were performed. Results: A total of 4,339 deaths involving lung cancer with documented sleep apnea were identified. The overall AAMR was 0.05 per 100,000 population. Mortality was concentrated predominantly among adults aged 65 years and older and was higher among men, White and non-Hispanic individuals, residents of nonmetropolitan areas, and those living in the Midwest and West. The AAMR increased from 0.011 in 1999 to 0.112 in 2020, with a significant annual percent change of 9.398%. The ARIMA model projected an increase to 0.160 per 100,000 by 2030, but it consistently overestimated observed AAMRs during 2021-2024 (MAPE 9.71%); therefore, these forecasts were interpreted as conditional and exploratory projections. State-level analyses showed marked geographic heterogeneity not fully explained by socioeconomic development. Conclusion: Mortality involving lung cancer and documented sleep apnea increased substantially over 22 years and showed clear demographic and geographic disparities, with a disproportionate burden among older adults, particularly those aged 65 years and above. The historical trend and exploratory forecasting results support continued attention to sleep health assessment and integrated respiratory-oncology care.

Indexed as

Lung NeoplasmsSleep Apnea SyndromesAdultAgedAged, 80 and overCause of DeathFemaleHumansMaleMiddle AgedRetrospective StudiesUnited Statesage-adjusted mortality rateCDC WONDERJoinpoint regressionlung cancermortalitysleep apnea

Identifiers

PMID42876681
PMCPMC13661379

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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.