Annals of the American Thoracic Society

Rationale: In 2020, lung cancer was the leading cause of cancer deaths and the most common cancer in men. Although obstructive sleep apnea (OSA) has been postulated to be carcinogenic, epidemiological studies are inconclusive.

Objectives: To investigate the associations between OSA and the incidence and mortality of lung cancer.

Methods: Four electronic databases (PubMed, Embase, Cochrane Library, and Scopus) were searched from inception until 6 June 2021 for randomized controlled trials and observational studies examining the association between sleep apnea and incident lung cancer. Two reviewers selected studies, extracted data, graded the risk of bias using the Newcastle-Ottawa scale and the quality of evidence using the Grading of Recommendations Assessment, Development, and Evaluation system. Random-effects models were used to meta-analyze the maximally covariate-adjusted associations.

Results: Seven studies were included in our systematic review, among which four were suitable for meta-analysis, comprising a combined cohort of 4,885,518 patients. Risk of bias was low to moderate. OSA was associated with a higher incidence of lung cancer (hazard ratio, 1.25; 95% confidence interval, 1.02–1.53), with substantial heterogeneity (I2 = 97%). Heterogeneity was eliminated, with a stable pooled effect size, when including the three studies with at least 5 years of median follow-up (hazard ratio, 1.32; 95% confidence interval, 1.27–1.37; I2 = 0%).

Conclusions: In this meta-analysis of 4,885,518 patients from four observational studies, patients with OSA had an approximately 30% higher risk of lung cancer compared with those without OSA. We suggest more clinical studies with longer follow-up as well as biological models of lung cancer be performed to further elucidate this relationship.

Cancer is one of the leading causes of death worldwide, with lung cancers being the leading cause of cancer deaths with an estimated 1.8 million deaths (1). In 2020, 11.4% of new cancers diagnosed were lung cancers, placing it as the second most common site of incident cancers and the most common cancer in men (1). Hence, it is important to identify potential modifiable risk and prognostic factors to aid early diagnosis and intervention.

Close to 1 billion adults among the global population have been estimated to suffer from obstructive sleep apnea (OSA) (2). New studies have also raised concern that there appears to be a higher overall cancer incidence among people suffering from OSA. This has been postulated to be due to phases of repetitive hypoxia and reoxygenation in OSA patients because of repetitive upper airway obstruction during sleep (3). These episodes of intermittent hypoxia enhance angiogenesis, immune evasion, and metastasis through various mechanisms. Adrenergic signaling is one such mechanism responsible for multiple steps in cancer progression as well as expression of inflammatory and chemotactic cytokines, which have been shown to enhance tumor invasion and metastasis (4); macrophage recruitment and activity in chronic hypoxic states also contribute to accelerated tumor progression (5). Another proposed mechanism is intercellular crosstalk via extracellular exosomes; in animal models, exosomes from cells exposed to hypoxic environments have been shown to be proangiogenic and increase the malignancy of tumor cells (3, 6).

For lung cancer in particular, some of these mechanisms include a heightened inflammatory state because of poor sleep (712) as well as intermittent hypoxia, stimulating hypoxia-inducible factors (HIFs) (1316). These changes in the body encourage tumorigenesis and cancer progression. From an observational perspective, studies have shown a high prevalence of lung cancer among people with OSA (17, 18) as well as a high prevalence of OSA among patients with lung cancer (19, 20). These reflect the close association between OSA and lung cancer.

However, current evidence is inconclusive regarding the association between these two diseases. Although some studies, such as one by Huang and colleagues (18), appear to suggest a positive association, there are others, like Gozal and colleagues (21), that suggest a negative association instead.

We believe it is important to clarify this association because it has significant clinical implications for early detection and surveillance of lung cancer. Hence, we conducted this systematic review and meta-analysis to investigate the association of OSA with lung cancer.

This review is reported in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines (22). The Preferred Reporting Items for Systematic Reviews and Meta-Analyses checklist is included in Table E1 in the online supplement. This review is part of an a priori systematic review protocol registered on the International Prospective Register of Systematic Reviews (PROSPERO) (CRD42021220836).

Search Strategy

Our initial search was based on four databases (PubMed, Embase, Scopus, and Cochrane Library) from inception until 6 June 2021. Our free text search strategy was as follows: (sleep apnea OR nocturnal hypoxia OR nocturnal hypoxemia) AND cancer AND (incidence OR incident OR mortality). Our initial search strategy was intentionally not limited to lung cancers because some papers had an overall cohort study of many cancer types, including the incidence and mortality of lung cancers. Thus, we assessed all potentially relevant full-text articles for reported lung cancer statistics. We also manually searched the bibliographies of included articles and relevant reviews, journals, and electronic sources.

Study Selection

Two authors independently selected potentially eligible studies using the data management software Rayyan QCRI (http://rayyan.qcri.org) (23). Our initial screening process was based on titles and abstracts, whereas full texts were subsequently used for final inclusion. We included randomized controlled trials and observational studies of adults 18 years and older that reported on any association between sleep apnea and lung cancer incidence or mortality in comparison with controls without sleep apnea or nocturnal hypoxemia or with less severe forms of these conditions. The presence and severity of OSA were measured by the apnea–hypopnea index (AHI), respiratory disturbance index, or clinical diagnoses of OSA (e.g., International Classification of Diseases [ICD] diagnostic codes). Conference abstracts, academic dissertations, and other gray literature were accepted if they fulfilled the above criteria. Case reports, reviews, letters, and non-English publications were excluded.

Data Extraction

Two authors extracted the following data from each article into a standardized extraction spreadsheet template: first author, year published, study design, setting, country, sample size, percentage male, mean/median age, body mass index, intervention/exposure, outcomes, covariates, statistical methods, and key findings.

Risk of Bias

Because all included studies were observational, we used the Newcastle-Ottawa scale to evaluate the risk of bias at the study level (Table E2) (24). One author had a high risk of bias (<5 stars), whereas the rest had a moderate (5–7 stars) or low risk of bias (⩾8 stars).

Statistical Analysis

We meta-analyzed the longitudinal association between baseline OSA and the incidence of lung cancers. We used the generic inverse variance method and favored maximally covariate-adjusted estimates where available. Random-effects models were used to account for heterogeneity in the observational estimates (25), and between-study heterogeneity was assessed with the I2 value we obtained (26). We considered an I2 of less than 30% as indicative of low heterogeneity between studies, 30–60% indicative of moderate heterogeneity, and more than 60% indicative of substantial heterogeneity. We performed prespecified subgroup analyses of follow-up duration. There were insufficient studies to perform subgroup analyses or assess publication bias via visual inspection of funnel plot asymmetry, Egger’s bias, or trim-and-fill (2729) We used RevMan (version 5.4) by Cochrane RevMan for our analysis, in accordance with statistical approaches from the Cochrane Handbook, and considered a two-sided P value of less than 0.05 statistically significant.

The study selection process is summarized in Figure E1. Our systematic search retrieved 1,895 results, and a manual search identified two additional studies. A total of 197 duplicates were removed. Title and abstract screening excluded a further 1,654 articles. Full text screening excluded 232 articles. Seven articles were included in the review. Four studies were identified for the meta-analysis.

Baseline Characteristics

The seven studies comprised a combined cohort of 4,939,391 patients. All studies reported OSA, except for Sillah and colleagues (30), who reported sleep apnea. Diagnoses of OSA or sleep apnea were made using the ICD diagnostic codes in Sillah and colleagues (30), Gozal and colleagues (21), and Jara and colleagues (31). In Huang and colleagues (18), the initial screening for patient selection involved self-reporting any clinically diagnosed OSA. This was validated using polysomnography in a subsample (N = 108) and found that the self-reported diagnosis was 92% accurate. Kendzerska and colleagues (32) diagnosed patients using polysomnography (AHI severity scores), and Singh and colleagues (33) used polysomnography to determine the time (T90) and percentage (P90) of the study at an oxygen saturation of less than 90%. Prasad and colleagues (34) reported objectively testing patients for sleep apnea, although the method was unspecified.

In Kendzerska and colleagues (32), other than OSA diagnosis via AHI scoring, various other parameters, such as mean arterial oxygen saturation (SaO2) as well as the percentage of sleep time spent with SaO2 less than 90% were analyzed for their respective associations with lung cancer incidence. The other three studies (18, 21, 31) only compared lung cancer incidence between patients with no OSA against patients with OSA diagnosed with various indices (ICD, AHI, polysomnography, etc.).

The participant characteristics of the included studies are shown in Table 1. Across the 7 studies, 6 were retrospective, and 1 was a prospective study. Five studies were conducted in the United States, 1 was conducted in Australia, and 1 was conducted in Canada. Median follow-up duration of the studies ranged from 1.87 to 11.9 years.

Table 1. Characteristics of the included studies

First Author and Year PublishedStudy DesignSample SizeTotal Incident Lung Cancer (Non-OSA)OSA DiagnosisSetting/CountryMedian AgeMale (%)CovariatesMedian Follow-Up Duration (Yr)Newcastle-Ottawa Scale (Maximum 9)
Gozal 2016Retrospective matched cohort3,408,90611,744ICDUnited States50–59 (range)50.2Age, sex, morbid obesity, hypertension, type 2 diabetes, ischemic heart disease, coronary heart failure, stroke, cardiac arrhythmias, and depression1.87, 3.75, and 3.91 for the different subgroups8
Huang 2021Prospective cohort65,330492Self-reported clinical diagnosis of OSA, validated by polysomnography in a subsampleUnited States730Age, race/ethnicity, family history of cancer, body mass index (BMI), height, pack-years of smoking, alcohol drinking, physical activity, sleep duration, duration of hormonal therapy use by type, history of type 2 diabetes, aspirin use, and recent physical examination85
Jara 2020Retrospective matched cohort1,377,28510,595ICDUnited States55.294Age, sex, year of cohort entry, smoking status, alcohol use, obesity, and comorbidity7.47
Kendzerska 2021Retrospective cohort33,997241Polysomnography (AHI severity scoring)Canada5058Exposure, year of study, sleep clinic site, age, sex, alcohol use disorder, prior CHF, COPD, hypertension, diabetes, OSA treatment as time-varying covariate77
Sillah 2018Retrospective cohort34,402290ICDUnited States51.657.4Age, sex5.36
Singh 2019Retrospective cohort19,327NAT90, P90AustraliaNRNRAge, sex, blood pressure, and socioeconomic status11.97
Prasad 2019Retrospective cohort144NRNRUnited States67.298Age, race, pack-year tobacco use, (FEV1)/(FVC), duration of lung cancer, and PAP compliance54

Definition of abbreviations: AHI = apnea–hypopnea index; BMI = body mass index; CHF = congestive heart failure; COPD = chronic obstructive pulmonary disease; FEV1 = forced expiratory volume in 1 second; FVC = forced vital capacity; ICD = Internal Classification of Diseases; NA = not applicable; NR = not reported; OSA = obstructive sleep apnea; P90 = percentage of cumulative time with oxygen saturation below 90% in total sleep time; PAP = positive airway pressure; T90 = cumulative time with oxygen saturation below 90%.

The total incidence of lung cancer in each study is also included in Table 1. Because most studies, except for Jara and colleagues (31) and Sillah and colleagues (30), did not report the incidence of lung cancer in OSA and non-OSA groups separately, the total incidence in both groups was tabulated instead. In Jara and colleagues (31), lung cancer incidence in the OSA group (sample size, 726,008) was 6,813, and lung cancer incidence in the non-OSA group (sample size, 651,277) was 3,782. Sillah and colleagues (30) studied a cohort of patients with known OSA (sample size, 34,402), and lung cancer incidence was 115. This was compared with their standardized cancer incidence ratios based on expected population estimates over a comparable study period (expected lung cancer incidence of 175).

The sex composition of the included studies in the meta-analysis were varied. Of note, Jara and colleagues (31) and Prasad and colleagues (34) studied a predominantly male population (94% male and 98% male, respectively), and Huang and colleagues (18) studied an all-female population. Subgroup analysis by sex was not performed because the data were not reported by the studies.

Lung Cancer Incidence

Four studies were included in our meta-analysis (Gozal and colleagues [21], Kendzerska and colleagues [32], Jara and colleagues [31], and Huang and colleagues [18]), all of which had a low or moderate risk of bias. Adjustments were made for age, sex, and a range of comorbidities, including chronic obstructive pulmonary disorder, hypertension, diabetes, heart failure, obesity, and a history of smoking and alcohol use (Table 1). The total population size of our meta-analysis was 4,885,518. Except for Gozal and colleagues (21), who had follow-up durations ranging from 1.87 years to 3.91 years in the various subgroups, the studies included in our meta-analysis had median follow-up durations of 7 years or longer. Three other studies were excluded from meta-analysis for various reasons: Sillah and colleagues (30), because it adjusted only for age and sex but did not adjust for other comorbidities, making it clinically heterogenous from the other studies, and Singh and colleagues (33) and Prasad and colleagues (34) because they did not report any hazard ratios for cancer incidence.

The pooled incidence outcomes are presented in Figure 1. In the overall analysis, incident lung cancer was positively associated with OSA (hazard ratio, 1.25; 95% confidence interval, 1.02–1.53; I2 = 97%). Further sensitivity analysis, including the three studies with 5 years or longer median follow-up demonstrated that patients with OSA had significantly higher pooled hazards of incident cancer (hazard ratio, 1.32; 95% confidence interval, 1.27–1.37; I2 = 0%) compared with patients without OSA. Notably, the heterogeneity decreased to 0% (low heterogeneity).

Cancer Mortality

Gozal and colleagues (21) and Prasad and colleagues (34) examined the association between OSA and lung cancer mortality. Gozal and colleagues (21) reported that the OSA cohort had significantly lower mortality rates; five cancer types had no significant difference in mortality rates. Prasad and colleagues (34) also reported that the diagnosis, severity, and treatment of OSA had no significant difference on lung cancer mortality rates.

Certainty of Evidence

The quality of pooled evidence was assessed with the Grading of Recommendations Assessment, Development, and Evaluation system (Table E3). The quality of evidence was low for the primary outcome of lung cancer incidence; it was downgraded by two levels because there was significant statistical heterogeneity and by one level because of the small number of included studies. However, the quality of evidence is high for our subgroup of studies with at least 5 years of median follow-up duration.

In this meta-analysis of a combined cohort of 4,885,518 patients, we found that patients with OSA had a 25% higher incidence of lung cancer compared with those without. In studies with more than 5 years of follow-up, patients with OSA had a 32% higher incidence of lung cancer. Included studies adjusted for important confounders such as age, sex, obesity, and various patient comorbidities, but not all adjusted for smoking. This aligns with our hypothesis.

In our subgroup analysis of studies with more than 5 years of follow-up, patients with OSA had a nominally larger risk of lung cancer compared with our main analysis. Gozal and colleagues (21) had the shortest follow-up period of around 3 years among its different subgroups, whereas the next-lowest follow-up duration is 7 years, more than double that of Gozal and colleagues (21). We suggest that the short follow-up duration in the study by Gozal and colleagues (21) may affect our ability to evaluate lung cancer incidence; by excluding the study by Gozal and colleagues (21) from our subgroup analysis, the heterogeneity was reduced to 0%. This suggests the importance of long-term follow-up in studies aiming to pick up incidence of lung cancer. This is even more relevant considering the time required for lung cancers to manifest and subsequently be detected. For instance, squamous cell lung carcinoma takes approximately 8 years to reach a size of 30 mm, which is the size at which it is most commonly diagnosed (35). At the same time, we acknowledge that the heterogeneity of the main analysis may also be due to other factors, such as differences in the studies’ adjustment for confounders or in their population characteristics. Therefore, although this subgroup analysis may be more representative of the association between OSA and lung cancer incidence, further studies are required to confirm this.

Kendzerska and colleagues (32) stratified their study population using the AHI, grouping them as mild, moderate, or severe OSA; a dose–response relationship between OSA severity and incident cancer controlling for confounders was identified, but not for lung cancer specifically. The other studies included in our meta-analysis did not stratify the study populations by OSA severity. The potential finding of a dose–response relationship between OSA severity and lung cancer incidence, if shown, would strengthen the case for an association between the two. More studies will be useful to characterize the relationship between the two diseases.

We acknowledge that some of the included studies were not focused on lung cancer specifically, and thus the covariates that were adjusted were inadequate. Gozal and colleagues (21) and Kendzerska and colleagues (32) did not adjust for smoking status in their primary analyses, which may have contributed to the observed association of OSA with incident lung cancer in these two studies. Although Kendzerska and colleagues (32) did perform subsequent sensitivity analyses that accounted for smoking status, they noted that smoking status was only collected for a small proportion of their study population. After adjustment for smoking status, the association between OSA and incident smoking-related cancers was attenuated but remained significant for those with severe nocturnal hypoxemia. Exact data for incident lung cancer after adjustment for smoking status was not reported. Jara and colleagues (31) adjusted for smoking status by classifying veterans as current, former, or non-smokers; we suggest that a better way to adjust for residual confounding would be to adjust for cigarette pack-years, as performed by Huang and colleagues (18), rather than smoking status alone.

There have been different theories regarding the association between OSA and lung cancer pathogenesis. One possibility is that OSA results in sleep fragmentation. Sleep fragmentation increases sympathetic activation, systemic inflammation, and immune dysregulation (3638), driving carcinogenesis. Inflammatory states, such as raised c-reactive protein, have been demonstrated to be associated with increased incidences of different types of cancer, including lung cancers (79). Specific to the lungs, the inflammatory state may interact with other factors, such as smoking, to increase overall lung cancer risk (1012). The implication of this may be that this relationship is not unique to those suffering from OSA but even applies to those who are sleep-deprived by virtue of their lifestyle. In turn, promoting healthy sleep duration may be important in reducing lung cancer incidence, especially those with other predispositions for lung cancer, such as smokers. Future studies can base their assessments of nocturnal hypoxemia on oxygen saturation as measured by pulse oximetry nadir and area-under-curve analyses of a patient’s oxygen saturation as measured by pulse oximetry instead, which may be better markers than those used for OSA detection and severity.

An alternative theory is that HIFs are responsible for stimulating tumor progression. Cellular and murine models have demonstrated that intermittent hypoxia upregulate HIFs, which consequently promotes tumor proliferation and invasion. One such factor, HIF-2a, was found to be associated with poor prognosis in non-small cell lung cancer, promoting tumorigenesis, angiogenesis, metastasis, and cancer progression (16). β-Catenin is an important target protein for this pathway, having been shown to promote non-small cell lung cancer through the Wnt signaling pathways (13, 14). However, even within lung cancers, different subtypes may respond differently to hypoxia. In fact, HIF-2a expression is suppressed in small cell lung cancer cells (15). Further studies should investigate the risk of specific types of lung cancer in patients with OSA.

Only two studies, Gozal and colleagues (21) and Prasad and colleagues (34), examined the association between OSA and lung cancer mortality. Gozal and colleagues (21) found that lung cancer patients with OSA had significantly lowered metastasis and mortality rates compared with those without OSA. We suggest that the short duration of follow-up by Gozal and colleagues (21) may partially explain their observations, but their findings also imply that more studies could be performed to elucidate whether OSA truly has a protective effect against lung cancer metastasis and mortality. Prasad and colleagues (34) found no significant difference in lung cancer mortality between OSA and non-OSA groups, but they had a small sample size of 144 lung cancer patients who were predominantly male. Overall, evidence for the relationship between lung cancer prognosis and OSA is weak, and more studies with sufficiently large sample size and longer duration of follow-up should be performed before stronger conclusions can be made.

Our findings in this meta-analysis demonstrated increased lung cancer incidence in patients with OSA, and this was statistically significant among studies with long-term follow-up of 5 years or longer. We acknowledge that these findings are exploratory, given the small number of studies performed at present. This topic is of relevance because many cases of OSA are undiagnosed and untreated (2), and lung cancer is the one of the most common incident sites of cancer. Therefore, we recommend that more studies with sufficient follow-up duration be performed; further studies could study the association between duration of OSA and lung cancer risk, which could provide further insights into the difference in the associations by length of follow-up observed in our meta-analysis. Furthermore, many aspects of the association between OSA and lung cancer are still unexplored; for instance, future studies could examine the associations between OSA and specific histologic subtypes of lung cancer, which may elucidate the effect of OSA on the pathogenesis of different lung cancer subtypes. Future research should also explore the possibility of additional population-based OSA screening to increase surveillance and early detection of lung cancer.

Strengths and Limitations

The strengths of this study lie in the large number of participants and methodological decisions, such as an adequate follow-up duration. Six of our seven included studies also achieved a Newcastle-Ottawa scale score of at least five, indicating moderate to low risk of bias. Nonetheless, our findings should be interpreted with due consideration of the limitations.

There was significant heterogeneity in our overall findings, although the heterogeneity was eliminated (97–0%) in the sensitivity analysis of 5 years or longer of follow-up. Apart from having less than 5 years of follow-up, Gozal et al. was also based on administrative records, which can be useful for general evaluations but not for the study of specific relationships that focus on a specific topic. Second, the total number of included studies was limited. Further studies, ideally with ⩾5 years of follow-up and adequate adjustment for comorbidities, would contribute to more definitive epidemiological conclusions on the association of OSA with lung cancer.

Not all studies adjusted for smoking status, which is an important confounder contributing to lung cancer incidence—Gozal and colleagues (21) and Kendzerska and colleagues (32) did not adjust for smoking status in their primary analyses. Kendzerska and colleagues (32) performed subsequent sensitivity analyses accounting for smoking status, but these were limited by the lack of data on participants’ smoking.

The study by Jara and colleagues (31) involved mostly male participants (94%), whereas Huang and colleagues (18) analyzed data from the Nurses’ Health Study comprising only females. In the absence of sex-stratified analyses in the primary studies, we are limited in our ability to provide sex-stratified data in our meta-analysis. However, it appears from the studies by Jara and colleagues (31) and Huang and colleagues (18) that this association can be observed in males and females, although further studies with sex-stratified analyses are required to draw firm conclusions. Last, the majority of the studies in our meta-analysis were performed in the United States; future studies of different study populations may yield differing levels of association, given that cancer incidence among different geographical locations also differs.

Conclusion

In this meta-analysis of observational studies, OSA was associated with higher lung cancer risk among studies with at least 5 years of median follow-up. However, the certainty of current evidence is low, mainly because of the observational nature of included studies and the small number of studies performed so far. Thus, we suggest more clinical studies with longer follow-up as well as biological models of lung cancer be performed to further elucidate this relationship.

1. Sung H, Ferlay J, Siegel RL, Laversanne M, Soerjomataram I, Jemal A, et al. Global cancer statistics 2020: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries. CA Cancer J Clin 2021;71:209249.
2. Benjafield AV, Ayas NT, Eastwood PR, Heinzer R, Ip MSM, Morrell MJ, et al. Estimation of the global prevalence and burden of obstructive sleep apnoea: a literature-based analysis. Lancet Respir Med 2019;7:687698.
3. Gozal D, Farré R, Nieto FJ. Putative links between sleep apnea and cancer: from hypotheses to evolving evidence. Chest 2015;148: 11401147.
4. Gozal D, Farré R, Nieto FJ. Obstructive sleep apnea and cancer: epidemiologic links and theoretical biological constructs. Sleep Med Rev 2016;27:4355.
5. Almendros I, Gileles-Hillel A, Khalyfa A, Wang Y, Zhang SX, Carreras A, et al. Adipose tissue macrophage polarization by intermittent hypoxia in a mouse model of OSA: effect of tumor microenvironment. Cancer Lett 2015;361:233239.
6. Almendros I, Khalyfa A, Trzepizur W, Gileles-Hillel A, Huang L, Akbarpour M, et al. Tumor cell malignant properties are enhanced by circulating exosomes in sleep apnea. Chest 2016;150:10301041.
7. Irwin MR. Why sleep is important for health: a psychoneuroimmunology perspective. Annu Rev Psychol 2015;66:143172.
8. Meier-Ewert HK, Ridker PM, Rifai N, Regan MM, Price NJ, Dinges DF, et al. Effect of sleep loss on C-reactive protein, an inflammatory marker of cardiovascular risk. J Am Coll Cardiol 2004;43:678683.
9. Mullington JM, Simpson NS, Meier-Ewert HK, Haack M. Sleep loss and inflammation. Best Pract Res Clin Endocrinol Metab 2010;24:775784.
10. O’Callaghan DS, O’Donnell D, O’Connell F, O’Byrne KJ. The role of inflammation in the pathogenesis of non-small cell lung cancer. J Thorac Oncol 2010;5:20242036.
11. Shiels MS, Pfeiffer RM, Hildesheim A, Engels EA, Kemp TJ, Park JH, et al. Circulating inflammation markers and prospective risk for lung cancer. J Natl Cancer Inst 2013;105:18711880.
12. Siemes C, Visser LE, Coebergh JW, Splinter TA, Witteman JC, Uitterlinden AG, et al. C-reactive protein levels, variation in the C-reactive protein gene, and cancer risk: the Rotterdam Study. J Clin Oncol 2006;24:52165222.
13. Hong CF, Chen WY, Wu CW. Upregulation of Wnt signaling under hypoxia promotes lung cancer progression. Oncol Rep 2017;38:17061714.
14. Kong X, Zhao Y, Li X, Tao Z, Hou M, Ma H. Overexpression of HIF-2α-dependent NEAT1 promotes the progression of non-small cell lung cancer through miR-101-3p/SOX9/Wnt/β-catenin signal pathway. Cell Physiol Biochem 2019;52:368381.
15. Munksgaard Persson M, Johansson ME, Monsef N, Planck M, Beckman S, Seckl MJ, et al. HIF-2α expression is suppressed in SCLC cells, which survive in moderate and severe hypoxia when HIF-1α is repressed. Am J Pathol 2012;180:494504.
16. Wang WJ, Ouyang C, Yu B, Chen C, Xu XF, Ye XQ. Role of hypoxia-inducible factor-2α in lung cancer (review). Oncol Rep 2021;45:57.
17. Huang HY, Lin SW, Chuang LP, Wang CL, Sun MH, Li HY, et al. Severe OSA associated with higher risk of mortality in stage III and IV lung cancer. J Clin Sleep Med 2020;16:10911098.
18. Huang T, Lin BM, Stampfer MJ, Schernhammer ES, Saxena R, Tworoger SS, et al. Associations of self-reported obstructive sleep apnea with total and site-specific cancer risk in older women: a prospective study. Sleep (Basel) 2021;44:zsaa198.
19. Cabezas E, Pérez-Warnisher MT, Troncoso MF, Gómez T, Melchor R, Pinillos EJ, et al. Sleep disordered breathing is highly prevalent in patients with lung cancer: results of the Sleep Apnea in Lung Cancer study. Respiration 2019;97:119124.
20. Dreher M, Krüger S, Schulze-Olden S, Keszei A, Storre JH, Woehrle H, et al. Sleep-disordered breathing in patients with newly diagnosed lung cancer. BMC Pulm Med 2018;18:72.
21. Gozal D, Ham SA, Mokhlesi B. Sleep apnea and cancer: analysis of a nationwide population sample. Sleep (Basel) 2016;39: 14931500.
22. Moher D, Liberati A, Tetzlaff J, Altman DG; PRISMA Group. Preferred reporting items for systematic reviews and meta-analyses: the PRISMA statement. BMJ 2009;339:b2535.
23. Ouzzani M, Hammady H, Fedorowicz Z, Elmagarmid A. Rayyan: a web and mobile app for systematic reviews. Syst Rev 2016;5:210.
24. Wells GA, Shea B, O’Connell D, Peterson J, Welch V, Losos M, et al. The Newcastle-Ottawa Scale (NOS) for assessing the quality of nonrandomised studies in meta-analyses. The Ottawa Hospital Research Institute; 2012 [accessed 2019 Apr 24]. Available from: http://www.ohri.ca/programs/clinical_epidemiology/oxford.asp.
25. DerSimonian R, Laird N. Meta-analysis in clinical trials. Control Clin Trials 1986;7:177188.
26. Higgins JPT, Thompson SG. Quantifying heterogeneity in a meta-analysis. Stat Med 2002;21:15391558.
27. Begg CB, Mazumdar M. Operating characteristics of a rank correlation test for publication bias. Biometrics 1994;50:10881101.
28. Egger M, Davey Smith G, Schneider M, Minder C. Bias in meta-analysis detected by a simple, graphical test. BMJ 1997;315:629634.
29. Duval S, Tweedie R. Trim and fill: A simple funnel-plot-based method of testing and adjusting for publication bias in meta-analysis. Biometrics 2000;56:455463.
30. Sillah A, Watson NF, Schwartz SM, Gozal D, Phipps AI. Sleep apnea and subsequent cancer incidence. Cancer Causes Control 2018;29:987994.
31. Jara SM, Phipps AI, Maynard C, Weaver EM. The association of sleep apnea and cancer in veterans. Otolaryngol Head Neck Surg 2020;162:581588.
32. Kendzerska T, Povitz M, Leung RS, Boulos MI, McIsaac DI, Murray BJ, et al. Obstructive sleep apnea and incident cancer: a large retrospective multicenter clinical cohort study. Cancer Epidemiol Biomarkers Prev 2021;30:295304.
33. Singh B, McArdle N, Marriott R, Darcey E, Bond-Smith E, King S, et al. Association between hypoxemia in OSA and cancer incidence in a large sleep clinic cohort. J Sleep Res 2019;28:60.
34. Prasad B, Imayama I, Ahmed K, Malik MM, Mohindra NA, Rubinstein I. Obstructive sleep apnea and positive airway pressure therapy use are not associated with mortality in veterans with lung cancer. Am J Respir Crit Care Med 2019;199:A2279.
35. Birring SS, Peake MD. Symptoms and the early diagnosis of lung cancer. Thorax 2005;60:268269.
36. Chouchou F, Pichot V, Pepin JL, Tamisier R, Celle S, Maudoux D, et al. Sympathetic overactivity due to sleep fragmentation is associated with elevated diurnal systolic blood pressure in healthy elderly subjects: the PROOF-SYNAPSE study. Eur Heart J 2013;34:21222131, 2131a.
37. Peled N, Greenberg A, Pillar G, Zinder O, Levi N, Lavie P. Contributions of hypoxia and respiratory disturbance index to sympathetic activation and blood pressure in obstructive sleep apnea syndrome. Am J Hypertens 1998;11:12841289.
38. Smagula SF, Stone KL, Redline S, Ancoli-Israel S, Barrett-Connor E, Lane NE, et al.; Osteoporotic Fractures in Men (MrOS) Research Group. Actigraphy- and polysomnography-measured sleep disturbances, inflammation, and mortality among older men. Psychosom Med 2016;78:686696.
Correspondence and requests for reprints should be addressed to Song Tar Toh, M.D., Department of Otorhinolaryngology–Head & Neck Surgery, Singapore General Hospital, Outram Road, Singapore 169608, Singapore. E-mail: .

*These authors contributed equally to this work.

Supported by the SingHealth Medical Student Talent Development Award (A.J.Y.C.) and a Singapore Government Public Service Commission medicine scholarship (B.K.J.T.).

Author Contributions: A.J.Y.C., B.K.J.T., Y.H.T., N.K.W.T., D.W.T.Y., C.-H.S., T.H.O., L.C.L., A.S., and S.T.T. designed the study and developed the study protocol and tools. N.K.W.T. and D.W.T.Y. were responsible for data collection. A.J.Y.C., B.K.J.T., Y.H.T., C.-H.S., T.H.O., L.C.L., A.S., and S.T.T. analyzed data and wrote the manuscript. All authors contributed to conceptualization of the research questions, interpretation of the results, and manuscript writing. All authors read and approved the final manuscript.

This article has an online supplement, which is accessible from this issue’s table of contents at www.atsjournals.org.

Author disclosures are available with the text of this article at www.atsjournals.org.

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Annals of the American Thoracic Society
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