The association between emphysema detected on computed tomography and increased risk of lung cancer: a systematic review and meta-analysis

Introduction

Lung cancer is among the most commonly diagnosed cancers globally and is the leading cause of cancer-related mortality, with approximately 2 million new cases and 1.76 million deaths reported each year (1). Chronic obstructive pulmonary disease (COPD) is characterized by diffuse chronic inflammation within the lung tissue, oxidative stress, and lung destruction. Emphysema, recognized as one of the COPD phenotypes, can also arise from increased cell death in the alveolar walls and/or failure in alveolar wall maintenance (2,3). Lung cancer, COPD, and emphysema share common pathophysiological mechanisms (4), raising interest in the potential link between these conditions.

Chest computed tomography (CT) is a crucial tool for evaluating emphysema with high sensitivity; radiology indicates that pulmonary nodules often present as early signs of lung cancer (5-8). Some previous studies have included emphysema as a risk factor for lung cancer (9-11). Numerous research efforts have explored the relationship between the evaluation of emphysema via chest CT scans and lung cancer, employing both visual assessment and quantitative CT analysis techniques (10-12); nonetheless, the findings have been inconsistent. A 2012 meta-analysis demonstrated that visually assessed emphysema on chest CT scans was independently linked to lung cancer (10), whereas quantitative analysis failed to establish a similar correlation. A 2021 meta-analysis thoroughly examined the relationship between CT-defined emphysema and lung cancer; however, some data were derived from the same study cohort. Additionally, these studies did not consider the confounding factor of COPD, such as performing a stratified analysis based on the Global Initiative for Chronic Obstructive Lung Disease (GOLD) stages. Revising and integrating information from both current and novel research is crucial. Therefore, we aimed to conduct a systematic review and meta-analysis to evaluate the connection among CT-identified emphysema, the severity of COPD, and the likelihood of developing lung cancer. We present this article in accordance with the PRISMA reporting checklist (13) (available at https://qims.amegroups.com/article/view/10.21037/qims-24-1879/rc).

Methods

This systematic review was registered in the International Prospective Register of Systematic Reviews, or PROSPERO (No. CRD42024511856).

Search strategy

A comprehensive search was conducted on 6 June 2024 in the databases of PubMed, Embase, Web of Science, and Cochrane Library. The objective was to identify studies that assessed emphysema severity using chest CT, while also taking COPD status into account. The primary purpose was to investigate the association between these factors and the risk of developing lung malignancies. The reference list of included articles and relevant literature was also manually screened to ensure thoroughness. The search terms used included COPD, emphysema, solitary pulmonary nodule, and lung neoplasm (detailed search terms are provided in Appendix 1).

Definitions of emphysema and COPD

Visual emphysema was characterized by altered lung vasculature and parenchyma presenting with low attenuation in any region of the lungs on a chest CT scan, as assessed by radiologists according to the criteria established by the National Emphysema Treatment Trial (i.e., NETT) or Fleischer Society (14,15). Quantitative assessment was defined as the percentage of low attenuation area (LAA%), representing the proportion of total lung volume below a specified threshold of −950 Hounsfield units (HU) during full inspiration (16). Emphysema severity was classified according to the percentage of lung involvement, categorized as mild (0–25%), moderate (26–50%), and severe (≥51%) (17). Emphysema was also analyzed as a dichotomized variable, classified as normal or abnormal, with abnormal defined as having more than 3% LAA in quantitative analysis or at least a mild grading in visual assessment (17,18).

A postbronchodilator forced expiratory volume in one second to forced vital capacity (FEV1-FVC) ratio of less than 0.70 is required to diagnose COPD. According to the GOLD, the FEV1 percentage is the main indicator of disease severity, which was classified as GOLD I stage (FEV1 ≥80% of predicted), GOLD II (FEV1 of 50–79% of predicted), GOLD III (FEV1 of 30–49% of predicted), or GOLD IV (FEV1 <30% of predicted) (19,20).

Study selection

The data to be extracted included the following: (I) individuals diagnosed with lung cancer through histopathological evaluation, regardless of the histological type. (II) CT-defined emphysema (assessed by using quantitative CT or visual assessment). (III) COPD GOLD score or emphysema severity would be included if they were reported in articles. The exclusion criteria for our study were as follows: (I) review articles, case studies, letters, editorials, and conference abstracts; (II) non-English-language papers; (III) studies that are not relevant to the topic; (IV) studies on the same cohort; (V) studies lacking assessment of emphysema; and (VI) studies without adjusted effect size.

Data extraction

Two researchers independently performed all data extraction. Conflicts were resolved through consensus or by consulting an external reviewer. In each manuscript, the documented information encompasses a range of factors, organized as follows: authorship, country of origin, and year of publication; smoking status and familial predisposition to lung cancer; the number of individuals examined; the presence of emphysema, COPD, lung nodules, and lung cancer; the distribution of lung cancer histology; assessment of emphysema; severity of emphysema and COPD GOLD grades; outcome indicators, including odds ratios (ORs), risk ratios (RRs), and hazard ratios (HRs), together with their associated 95% confidence intervals (CIs); and variables that were either adjusted for or paired.

Quality assessment

The Quality Assessment of Diagnostic Accuracy Studies (QUADAS-2) was utilized to assess the methodological quality of every study. QUADAS-2 was structured so that four key domains (patient selection, index tests, reference standard and flow and timing, and applicability) were rated regarding the risk of bias and the concern regarding applicability to the research question (21). Any differences in ratings were settled through consensus.

Statistical analysis

The research was divided into groups based on visual assessment or quantitative evaluation. The principal outcome that was measured was the confirmed diagnosis of lung cancer. In cases where emphysema was observed, the adjusted OR served as the key outcome. RR and HR were treated as OR due to the low occurrence rate of lung cancer (22). If stratified ORs were reported in a study, a combined OR was estimated utilizing a random-effects model. Subgroup analyses were also conducted based on the severity of the emphysema and GOLD score.

The I² statistic was employed to estimate heterogeneity, which was categorized as low, moderate, substantial, or considerable (0–25%, 26–50%, 51–75%, and 76–100%, respectively) (23). Potential sources of variability were investigated through stratified analyses that considered region, sources of participants, and the design of the studies. Funnel plots served to assess any potential publication bias. Both visual inspection and the Egger’s test were utilized to evaluate asymmetry, which may signify publication bias. Subsequently, the trim-and-fill technique was employed to adjust for publication bias and to evaluate the stability of our findings. Additionally, we assessed the robustness of the estimates using a leave-one-out sensitivity analysis, in which each study was removed one at a time, followed by a recalculation of the OR. Finally, a significance level of P<0.05 was used to determine statistical significance. Statistical analysis was performed using Stata Standard Edition, version 18 (StataCorp., College Station, TX, USA).

Results

Literature search

As depicted in Figure 1, 6,114 studies underwent initial screening based on their abstracts and titles. After this screening, 5,658 studies were excluded from further consideration. Upon conducting a full-text screening, one study was excluded due to the repetition of data sources (3). Ultimately, 12 articles met all inclusion criteria for this meta-analysis.

Figure 1 Flowchart of study selection.

Study characteristics

The total number of samples across 12 studies was 22,190, including 1,649 patients with lung cancer and 827 lung nodules (Table 1). The research encompassed participants from diverse geographical locations, spanning the Americas (six from the USA), Europe (one from Germany, two from Norway, one from Spain), and Asia (two from Japan), with the majority hailing from the USA. There were six prospective studies and six retrospective studies. Sources of participants were derived from either hospitals (five out of 12 studies) or the general population (seven out of 12), with detailed source information provided in Table S1.

Quantitative CT was used in nine studies (24,26-32,35), and visual assessment was used in five (25,26,29,33,34). Emphysema was found in 37% of studies. Two studies featured visual and quantitative assessment (26,29). The definitions of emphysema employed for both visual and quantitative evaluations differed among the studies (Tables 2,3). In terms of quantitative CT evaluation, the HU threshold indicating low attenuation areas ranged between −880 and −950 HU, whereas the cutoffs for LAA% to identify the presence of emphysema spanned from 1% to 10%. Emphysema was categorized as a dichotomized threshold value in 11 studies and a continuous variable in three studies. Two studies allowed for converting a constant emphysema variable to a dichotomous variable (29,31). Moreover, eight studies used the GOLD score to assess COPD severity (24-30,33) (Table 3).

Data synthesis and meta-analysis

The aggregated total estimate for the relationship between lung cancer and emphysema was 2.45 (95% CI: 2.01–2.99) (Figure 2), with consistent results observed in the leave-one-out sensitivity analysis (Figure S1). Low heterogeneity was noted across the studies (I²=24.2%; P=0.213). A reasonable degree of symmetry was evident upon visually inspecting the funnel plot (Figure S2), and Egger’s test did not reveal significant publication bias (Egger’s test: t=1.26; P=0.241) (Figure S3).

Figure 2 The forest plot derived from the random-effects model illustrates the relationship between emphysema, evaluated both visually and quantitatively (as a dichotomous variable) through CT imaging, and lung cancer. The pooled OR (11 studies) was calculated to be 2.45 (95% CI: 2.01–2.99; I²=24.2%; P=0.213). In cases where emphysema was assessed using multiple methods, only the odds ratios from the main method were included in the overall estimates. CI, confidence interval; CT, computed tomography; DL, DerSimonian and Laird; OR, odds ratio.

Emphysema for lung cancer

The combined OR for lung cancer was 2.37 (95% CI: 1.93–2.80) in research employing visual evaluation, and 2.38 (95% CI: 1.85–3.05) in those utilizing quantitative evaluation. Research utilizing visual assessment exhibited substantial heterogeneity (I²=56.4%; P=0.057), whereas studies that applied quantitative assessment demonstrated showed low heterogeneity (I²=3.8%; P=0.397) (Figure 3).

Figure 3 Forest plot illustrating the random-effects model regarding the relationship between lung cancer and emphysema, categorized based on the method used to assess emphysema. The pooled ORs for lung cancer given quantitative and visual emphysema (dichotomous variable) assessment were 2.38 (95% CI: 1.85–3.05; I²=3.8%; P=0.397) and 2.37 (95% CI: 1.78–3.16; I²=56.4%; P=0.057) respectively. Studies denoted with ‘*’ assessed emphysema both visually and quantitively. CI, confidence intervals; DL, DerSimonian, and Laird; OR, odds ratio.

Emphysema severity for lung cancer

Emphysema severity was associated with lung cancer as a risk factor, with the overall pooled ORs for lung cancer showing a gradual increase (3.66 for mild and 4.6 for moderate to severe) corresponding to the escalating severity of emphysema. Moderate heterogeneity was noted in research that suggested mild emphysema (I²=39.7%) compared with moderate to severe cases (I²=0%) (Figure 4).

Figure 4 The forest plot illustrating the random-effects model demonstrates the relationship between the severity of emphysema and the incidence of lung cancer. The overall pooled ORs of mild, and moderate to severe emphysema for lung cancer were 3.66 (95% CI: 2.16–6.20; I²=39.7%; P=0.156) and 4.66 (95% CI: 3.30–6.60; I²=0.0%; P=0.509). DL, DerSimonian and Laird; CI, confidence interval; OR, odds ratio.

COPD severity for lung cancer

COPD severity was also associated with lung cancer as a risk factor. The overall pooled ORs for lung cancer gradually increased (1.56, 1.64, 2.02) as the COPD severity increased (GOLD I, GOLD II, GOLD III–IV), respectively. Low heterogeneity was observed for studies that reported GOLD I stage (I²=23.3%; P=0.266) compared with GOLD II stage (I²=0.0%; P=0.729) and GOLD III–IV stage (I²=27.6%; P=0.237) (Figure 5).

Figure 5 Forest plot illustrating the random-effects model regarding the relationship between the severity of COPD and lung cancer, categorized according to GOLD stage. The overall pooled OR was 1.75 (95% CI: 1.55–1.97; I²=3.6%; P=0.412). The pooled ORs for GOLD I stage to GOLD III–IV stage were 1.56 (95% CI: 1.11–2.19; I²=23.3%; P=0.266), 2.02 (95% CI: 1.57–2.60; I²=27.6%; P=0.237). CI, confidence interval; COPD, chronic obstructive pulmonary disease; DL, DerSimonian and Laird; GOLD, Global Initiative for Chronic Obstructive Lung Disease; OR, odds ratio.

Lung cancer confirmed by pathology

All studies confirmed lung cancer through histologic examination, with four studies providing specific histologic distributions (26,29,32,33). Adenocarcinoma was the most prevalent type, accounting for 288 of 613 cases. Two studies reported a total of 827 pulmonary nodules, of which 334 (40%) were confirmed as lung cancer through pathology (31,35).

Sources of heterogeneity

In the supplementary stratified analyses, we examined the possible sources of heterogeneity. The combined ORs were similar between case-control studies (2.54; 95% CI: 1.84–3.51; I²=45.7%; P=0.101) and cohort studies (2.21; 95% CI: 1.78–2.75; I²=0%; P=0.532). Likewise, the combined ORs were found to be similar for both retrospective (2.13; 95% CI: 1.75–2.59; I²=4.5%; P=0.381) and prospective studies (3.10; 95% CI: 2.31–4.17; I²=0.0%; P=0.481). Studies based on population showed a moderate degree of heterogeneity (I²=41.8%). The pooled OR was 2.74 (95% CI: 2.01–3.73; P=0.127), which is similar to that found in studies conducted in hospital settings (2.24; 95% CI: 1.69–2.97; I²=9.8%; P=0.351). Regarding regional differences, the pooled ORs were 2.21 (95% CI: 1.82–2.69; I²=10.2%; P=0.351) for America, 2.39 (95% CI: 1.51–3.79; I²=0%; P=0.495) for Asia, and 4.10 (95% CI: 2.51–6.71; I²=0%; P=0.42) for Europe. As for CT scan parameters, we observed the substantial heterogeneity (I²=61.4%) in monophasic CT scan (inspiratory scan only), which had a pooled OR 2.43 (95% CI: 1.57–3.77; P=0.035) comparable to that of dual-phase CT scans (2.72; 95% CI: 1.86–2.97; I²=0.0%; P=0.605). As for radiation dose differences, the pooled ORs were 2.21 (95% CI: 1.72–3.59; I²=63.4%; P=0.027) for low-dose CT and 2.39 (95% CI: 1.58–3.63; I²=0.0%; P=0.792) for standard-dose CT. Additionally, a pooled OR of 2.43 (95% CI: 1.87–3.14; I²=24.1%; P=0.253) was observed based on thin CT sections (Appendix 1).

Risk of bias assessment

According to the QUADAS-2 tool, Figure S4 provides a summary of the assessment of this study. Regarding patient selection, the risk of bias was low at 6 (50%) and high at 6 (50%). The risk of bias for the reference standard test was low in nine studies (75%), high in one study (8%), and unclear in two studies (17%). The risk of bias for the index test was low in eight studies (75%) and unclear in four studies (25%). Regarding the flow and timing, the risk of bias was the same as the reference standard.

Discussion

Our systematic review of the literature identified 12 studies that explored the association between COPD and lung cancer. In our meta-analysis, we noted that the population sources in Labaki et al.’s study were identical to those utilized in the study by Yong et al. (3,34), both of which were derived from the National Lung Screening Trial (NLST). In accordance with the PRISMA statement (13), we selected the study by Yong et al. due to its larger sample size of 16,624 participants, compared to 7,262 participants in the study by Labaki et al.

This article examined the relationship between emphysema and lung cancer, revealing an overall pooled OR of 2.45 (95% CI: 2.01–2.99). The pooled OR for lung cancer was 2.37 (95% CI: 1.93–2.80) in studies using visual assessment and 2.38 (95% CI: 1.85–3.05) in those using quantitative assessment. The combined ORs for lung cancer progressively rose (3.66 to 4.6) with the escalation of emphysema severity, moving from mild to moderate and then to severe stages. Meanwhile, the overall pooled ORs for lung cancer gradually increased (1.56, 1.64, 2.02) as the COPD severity increased (GOLD I, GOLD II, GOLD III–IV), respectively.

Quantitative CT assessment was discovered to correlate with an increased risk of lung cancer, with a pooled odds ratio of 2.38 (95% CI: 1.85–3.05). Meanwhile, the visual evaluation had higher heterogeneity (I²=56.4%), which favors previous studies by Yang et al. (11). It is important to note that each emphysema assessment method has its limitations. Although the visual assessment method was well-developed with standardized criteria (14,17), significant variation was observed both between and within observers. Conversely, when uniform equipment and protocols are employed, the quantitative evaluation is objective, swift, and exceptionally reproducible (17,36,37).

Inconsistent CT scanning parameters across different institutions, such as slice thickness, HU threshold, and LAA% cut-off values also influenced the variability in quantitative CT assessments (36). Conversely, we noted that the definitions of dichotomous emphysema employed for both visual and quantitative evaluations vary among different studies. There is a lack of uniformity in the HU thresholds and the LAA% cutoffs employed to determine the severity of emphysema. Moreover, the current study does not offer standardized guidelines or recommendations for LAA staging classification. These discrepancies may contribute to significant variations in the reported incidence of emphysema. Therefore, it is essential to standardize CT scanning parameters and establish reliable LAA% staging guidelines to ensure the accuracy and consistency of quantitative CT assessments (17,18,36).

Pulmonary function serves as a crucial foundation for GOLD classification. The risk assessment stratification by GOLD also underscores the correlation between airway obstruction and the potential for lung cancer, marking a distinctive aspect of innovation in our article. We found that COPD severity was positively associated with lung malignancy, particularly from the GOLD II to the GOLD III–IV stage. We combined GOLD III and IV classifications due to limited data in some studies. According to the GOLD guideline, GOLD III–IV indicates a predicted FEV1 <50%. Some studies suggest that the disease risk does not increase when the ratio exceeds this threshold (38,39). Meanwhile, the main basis of GOLD grade is spirometry, including FEV1pred% (predicted FEV1). The GOLD grade reflects the airway obstruction status of patients. From GOLD II to GOLD III–IV, there was a 1.6-fold and 2.0-fold increased odds of lung cancer, respectively. Other studies have also reported that the risk of lung cancer increases with the severity of COPD (40).

The interplay among emphysema, COPD, and lung cancer risk is intricate. It is well established that chronic bronchitis, which leads to airway thickening, accounts for the incomplete correlation between emphysema and airflow obstruction. Some studies have evaluated airway thickening using dedicated software, indicating that this metric plays a significant role in the diagnosis of COPD and lung cancer screening. Mets et al. demonstrated that the quantitative evaluation of CT imaging related to emphysema, air trapping, and bronchial wall thickness offers distinct diagnostic insights for COPD. Moreover, inspiratory CT biomarkers alone may suffice to identify patients with COPD in the context of lung cancer screening (41). Additionally, Schreuder et al. developed risk models to predict lung cancer incidence, cardiovascular disease, and COPD mortality, revealing that the utilization of quantitative measures of COPD [including mean lung density, emphysema score, and the square root of wall area of a hypothetical airway with internal perimeter of 10 mm (Pi10)] enhances the prediction accuracy of lung cancer incidence (42). Therefore, integrating these quantitative indicators in future research is essential, as this comprehensive approach may illuminate the complex relationships between emphysema, COPD, and lung cancer.

Although this study performed a meta-analysis of emphysema severity and five studies stratified the severity of emphysema, only one study provided the OR values of trace emphysema. In one study, Nishio et al., only classified emphysema as mild or severe (31). However, several studies have also reported that the risk of lung cancer increases with the severity of emphysema. For example, Yang et al. conducted six emphysema severity studies with 2,730 patients. Comparatively, this research included five studies (1,267 patients) for meta-analysis, with varying degrees of emphysema (11). Inadequate sample size may explain any inconsistencies across different studies. Therefore, the resulting pooled OR values were inadequate to support the meta-analysis due to different evaluation criteria.

Several limitations in this study warrant attention. Firstly, the data incorporated into this meta-analysis lacks sufficient evidence to conclusively establish whether CT-defined emphysema holds a higher independent predictive value than recognized risk factors for emphysema and lung cancer. Secondly, the constrained sample size hindered our ability to conduct a meta-analysis on the severity of emphysema (only one study reported trace emphysema for lung cancer). Thirdly, our evaluation of the risk associated with COPD was incomplete due to some articles lacking adjustments for COPD.

Conclusions

In summary, the diagnosis of emphysema through CT scans was linked to an elevated risk of developing lung cancer. The relationship between CT-defined emphysema and increased lung cancer risk, along with the correlation between the severity of COPD and malignancy, suggests the utility of CT imaging in flagging at-risk individuals. Although emphysema is incurable, CT scanning can be utilized to screen for and monitor early lung cancer, allowing for timely intervention. These strategies increase the window for early intervention in at-risk populations, ultimately allowing for better patient outcomes (Figure 6).

Figure 6 Schematic representation of the risk of lung cancer associated with emphysema by quantitative analysis of chest CT. CT, computed tomography; COPD, chronic obstructive pulmonary disease.

Acknowledgments

None.

Footnote

Reporting Checklist: The authors have completed the PRISMA reporting checklist. Available at https://qims.amegroups.com/article/view/10.21037/qims-24-1879/rc

Funding: This study was supported by “Pioneer” and “Leading Goose” R&D Program of Zhejiang (grant No. 2022C03046), National Natural Science Foundation of China (grant No. 82102128), Zhejiang Provincial Natural Science Foundation of China (grant Nos. LTGY24H180006 and LTGY23H180001), Medical and Health Science and Technology Project of Zhejiang Province (grant Nos. 2024KY129, 2024KY132, and 2022KY230), and Research Project of Zhejiang Chinese Medical University (grant No. 2022JKJNTZ19).

Conflicts of Interest: All authors have completed the ICMJE uniform disclosure form (available at https://qims.amegroups.com/article/view/10.21037/qims-24-1879/coif). The authors have no conflicts of interest to declare.

Ethical Statement: The authors are accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved.

Open Access Statement: This is an Open Access article distributed in accordance with the Creative Commons Attribution-NonCommercial-NoDerivs 4.0 International License (CC BY-NC-ND 4.0), which permits the non-commercial replication and distribution of the article with the strict proviso that no changes or edits are made and the original work is properly cited (including links to both the formal publication through the relevant DOI and the license). See: https://creativecommons.org/licenses/by-nc-nd/4.0/.

References

1. Thai AA, Solomon BJ, Sequist LV, Gainor JF, Heist RS. Lung cancer. Lancet 2021;398:535-54. [Crossref] [PubMed]
2. Christenson SA, Smith BM, Bafadhel M, Putcha N. Chronic obstructive pulmonary disease. Lancet 2022;399:2227-42. [Crossref] [PubMed]
3. Labaki WW, Xia M, Murray S, Hatt CR, Al-Abcha A, Ferrera MC, Meldrum CA, Keith LA, Galbán CJ, Arenberg DA, Curtis JL, Martinez FJ, Kazerooni EA, Han MK. Quantitative Emphysema on Low-Dose CT Imaging of the Chest and Risk of Lung Cancer and Airflow Obstruction: An Analysis of the National Lung Screening Trial. Chest 2021;159:1812-20. [Crossref] [PubMed]
4. Durham AL, Adcock IM. The relationship between COPD and lung cancer. Lung Cancer 2015;90:121-7. [Crossref] [PubMed]
5. Zou PL, Ma CH, Li X, Luo TY, Lv FJ, Li Q. Early Lung Adenocarcinoma Manifesting as Irregular Subsolid Nodules: Clinical and CT Characteristics. Acad Radiol 2024;S1076-6332(24)00958-9. Epub ahead of print. [Crossref]
6. Zolfaghari EJ, Kuehne AM, Antonoff MB. Silent Signals: Advancing Incidental Lung Nodule Screening Through Artificial Intelligence Innovation. Ann Thorac Surg 2024;S0003-4975(24)01106-8. Epub ahead of print. [Crossref]
7. Walter JE, Heuvelmans MA, de Jong PA, Vliegenthart R, van Ooijen PMA, Peters RB, Ten Haaf K, Yousaf-Khan U, van der Aalst CM, de Bock GH, Mali W, Groen HJM, de Koning HJ, Oudkerk M. Occurrence and lung cancer probability of new solid nodules at incidence screening with low-dose CT: analysis of data from the randomised, controlled NELSON trial. Lancet Oncol 2016;17:907-16. [Crossref] [PubMed]
8. Hohberger LA, Schroeder DR, Bartholmai BJ, Yang P, Wendt CH, Bitterman PB, Larsson O, Limper AH. Correlation of regional emphysema and lung cancer: a lung tissue research consortium-based study. J Thorac Oncol 2014;9:639-45. [Crossref] [PubMed]
9. de Torres JP, Bastarrika G, Wisnivesky JP, Alcaide AB, Campo A, Seijo LM, Pueyo JC, Villanueva A, Lozano MD, Montes U, Montuenga L, Zulueta JJ. Assessing the relationship between lung cancer risk and emphysema detected on low-dose CT of the chest. Chest 2007;132:1932-8. [Crossref] [PubMed]
10. Smith BM, Pinto L, Ezer N, Sverzellati N, Muro S, Schwartzman K. Emphysema detected on computed tomography and risk of lung cancer: a systematic review and meta-analysis. Lung Cancer 2012;77:58-63. [Crossref] [PubMed]
11. Yang X, Wisselink HJ, Vliegenthart R, Heuvelmans MA, Groen HJM, Vonder M, Dorrius MD, de Bock GH. Association between Chest CT-defined Emphysema and Lung Cancer: A Systematic Review and Meta-Analysis. Radiology 2022;304:322-30. [Crossref] [PubMed]
12. Mouronte-Roibás C, Leiro-Fernández V, Fernández-Villar A, Botana-Rial M, Ramos-Hernández C, Ruano-Ravina A. COPD, emphysema and the onset of lung cancer. A systematic review. Cancer Lett 2016;382:240-4. [Crossref] [PubMed]
13. Page MJ, McKenzie JE, Bossuyt PM, Boutron I, Hoffmann TC, Mulrow CD, et al. The PRISMA 2020 statement: an updated guideline for reporting systematic reviews. BMJ 2021;372: [Crossref] [PubMed]
14. Lynch DA, Austin JH, Hogg JC, Grenier PA, Kauczor HU, Bankier AA, Barr RG, Colby TV, Galvin JR, Gevenois PA, Coxson HO, Hoffman EA, Newell JD Jr, Pistolesi M, Silverman EK, Crapo JD. CT-Definable Subtypes of Chronic Obstructive Pulmonary Disease: A Statement of the Fleischner Society. Radiology 2015;277:192-205. [Crossref] [PubMed]
15. Fishman A, Fessler H, Martinez F, McKenna RJ Jr, Naunheim K, Piantadosi S, Weinmann G, Wise R. Patients at high risk of death after lung-volume-reduction surgery. N Engl J Med 2001;345:1075-83. [Crossref] [PubMed]
16. Kerber B, Ensle F, Kroschke J, Strappa C, Larici AR, Frauenfelder T, Jungblut L. Assessment of Emphysema on X-ray Equivalent Dose Photon-Counting Detector CT: Evaluation of Visual Scoring and Automated Quantification Algorithms. Invest Radiol 2024; Epub ahead of print. [Crossref]
17. Leader JK, Zheng B, Rogers RM, Sciurba FC, Perez A, Chapman BE, Patel S, Fuhrman CR, Gur D. Automated lung segmentation in X-ray computed tomography: development and evaluation of a heuristic threshold-based scheme. Acad Radiol 2003;10:1224-36. [Crossref] [PubMed]
18. Johannessen A, Skorge TD, Bottai M, Grydeland TB, Nilsen RM, Coxson H, Dirksen A, Omenaas E, Gulsvik A, Bakke P. Mortality by level of emphysema and airway wall thickness. Am J Respir Crit Care Med 2013;187:602-8. [Crossref] [PubMed]
19. Agustí A, Celli BR, Criner GJ, Halpin D, Anzueto A, Barnes P, et al. Global Initiative for Chronic Obstructive Lung Disease 2023 Report: GOLD Executive Summary. Eur Respir J 2023;61:2300239. [Crossref] [PubMed]
20. Lareau SC, Fahy B, Meek P, Wang A. Chronic Obstructive Pulmonary Disease (COPD). Am J Respir Crit Care Med 2019;199:1-2. [Crossref] [PubMed]
21. Whiting PF, Rutjes AW, Westwood ME, Mallett S, Deeks JJ, Reitsma JB, Leeflang MM, Sterne JA, Bossuyt PM. QUADAS-2 Group. QUADAS-2: a revised tool for the quality assessment of diagnostic accuracy studies. Ann Intern Med 2011;155:529-36. [Crossref] [PubMed]
22. Kuiper JS, Zuidersma M, Zuidema SU, Burgerhof JG, Stolk RP, Oude Voshaar RC, Smidt N. Social relationships and cognitive decline: a systematic review and meta-analysis of longitudinal cohort studies. Int J Epidemiol 2016;45:1169-206. [Crossref] [PubMed]
23. Higgins JP, Thompson SG, Deeks JJ, Altman DG. Measuring inconsistency in meta-analyses. BMJ 2003;327:557-60. [Crossref] [PubMed]
24. Kishi K, Gurney JW, Schroeder DR, Scanlon PD, Swensen SJ, Jett JR. The correlation of emphysema or airway obstruction with the risk of lung cancer: a matched case-controlled study. Eur Respir J 2002;19:1093-8. [Crossref] [PubMed]
25. Wilson DO, Leader JK, Fuhrman CR, Reilly JJ, Sciurba FC, Weissfeld JL. Quantitative computed tomography analysis, airflow obstruction, and lung cancer in the pittsburgh lung screening study. J Thorac Oncol 2011;6:1200-5. [Crossref] [PubMed]
26. Schwartz AG, Lusk CM, Wenzlaff AS, Watza D, Pandolfi S, Mantha L, Cote ML, Soubani AO, Walworth G, Wozniak A, Neslund-Dudas C, Ardisana AA, Flynn MJ, Song T, Spizarny DL, Kvale PA, Chapman RA, Gadgeel SM. Risk of Lung Cancer Associated with COPD Phenotype Based on Quantitative Image Analysis. Cancer Epidemiol Biomarkers Prev 2016;25:1341-7. [Crossref] [PubMed]
27. Chubachi S, Takahashi S, Tsutsumi A, Kameyama N, Sasaki M, Naoki K, Soejima K, Nakamura H, Asano K, Betsuyaku T. Radiologic features of precancerous areas of the lungs in chronic obstructive pulmonary disease. Int J Chron Obstruct Pulmon Dis 2017;12:1613-24. [Crossref] [PubMed]
28. Aamli Gagnat A, Gjerdevik M, Gallefoss F, Coxson HO, Gulsvik A, Bakke P. Incidence of non-pulmonary cancer and lung cancer by amount of emphysema and airway wall thickness: a community-based cohort. Eur Respir J 2017;49:1601162. [Crossref] [PubMed]
29. Carr LL, Jacobson S, Lynch DA, Foreman MG, Flenaugh EL, Hersh CP, Sciurba FC, Wilson DO, Sieren JC, Mulhall P, Kim V, Kinsey CM, Bowler RP. Features of COPD as Predictors of Lung Cancer. Chest 2018;153:1326-35. [Crossref] [PubMed]
30. Mouronte-Roibás C, Fernández-Villar A, Ruano-Raviña A, Ramos-Hernández C, Tilve-Gómez A, Rodríguez-Fernández P, Díaz ACC, Vázquez-Noguerol MG, Fernández-García S, Leiro-Fernández V. Influence of the type of emphysema in the relationship between COPD and lung cancer. Int J Chron Obstruct Pulmon Dis 2018;13:3563-70. [Crossref] [PubMed]
31. Nishio M, Kubo T, Togashi K. Estimation of lung cancer risk using homology-based emphysema quantification in patients with lung nodules. PLoS One 2019;14:e0210720. [Crossref] [PubMed]
32. Husebø GR, Nielsen R, Hardie J, Bakke PS, Lerner L, D'Alessandro-Gabazza C, Gyuris J, Gabazza E, Aukrust P, Eagan T. Risk factors for lung cancer in COPD - results from the Bergen COPD cohort study. Respir Med 2019;152:81-8. [Crossref] [PubMed]
33. González J, Henschke CI, Yankelevitz DF, Seijo LM, Reeves AP, Yip R, Xie Y, Chung M, Sánchez-Salcedo P, Alcaide AB, Campo A, Bertó J, Del Mar Ocón M, Pueyo J, Bastarrika G, de-Torres JP, Zulueta JJ. Emphysema phenotypes and lung cancer risk. PLoS One 2019;14:e0219187. [Crossref] [PubMed]
34. Yong PC, Sigel K, de-Torres JP, Mhango G, Kale M, Kong CY, Zulueta JJ, Wilson D, Brown SW, Slatore C, Wisnivesky J. The effect of radiographic emphysema in assessing lung cancer risk. Thorax 2019;74:858-64. [Crossref] [PubMed]
35. Peters AA, Weinheimer O, von Stackelberg O, Kroschke J, Piskorski L, Debic M, Schlamp K, Welzel L, Pohl M, Christe A, Ebner L, Kauczor HU, Heußel CP, Wielpütz MO. Quantitative CT analysis of lung parenchyma to improve malignancy risk estimation in incidental pulmonary nodules. Eur Radiol 2023;33:3908-17. [Crossref] [PubMed]
36. Hagiwara A, Fujita S, Ohno Y, Aoki S. Variability and Standardization of Quantitative Imaging: Monoparametric to Multiparametric Quantification, Radiomics, and Artificial Intelligence. Invest Radiol 2020;55:601-16. [Crossref] [PubMed]
37. Baraghoshi D, Strand M, Humphries SM, San José Estépar R, Vegas Sanchez-Ferrero G, Charbonnier JP, Latisenko R, Silverman EK, Crapo JD, Lynch DA, Quantitative CT. Evaluation of Emphysema Progression over 10 Years in the COPDGene Study. Radiology 2023;307:e222786. [Crossref] [PubMed]
38. Young RP, Hopkins RJ. Chronic obstructive pulmonary disease (COPD) and lung cancer screening. Transl Lung Cancer Res 2018;7:347-60. [Crossref] [PubMed]
39. Tisi S, Dickson JL, Horst C, Quaife SL, Hall H, Verghese P, Gyertson K, Bowyer V, Levermore C, Mullin AM, Teague J, Farrelly L, Nair A, Devaraj A, Hackshaw A, Hurst JR, Janes SM. Detection of COPD in the SUMMIT Study lung cancer screening cohort using symptoms and spirometry. Eur Respir J 2022;60:2200795. [Crossref] [PubMed]
40. de-Torres JP, Alcaide AB, Campo A, Zulueta JJ, Bastarrika G, Ezponda A, Mesa M, Murillo D, Rodriguez M, Del Mar Ocón M, Felgueroso C, Pueyo J, Lozano MD, Montuenga LM, Berto J, Perez-Warnisher MT, Di-Frisco IM, Seijo LM. Lung Cancer Screening in People With COPD: The Pamplona-IELCAP Experience. Arch Bronconeumol 2024;60:95-100. [Crossref] [PubMed]
41. Mets OM, Schmidt M, Buckens CF, Gondrie MJ, Isgum I, Oudkerk M, Vliegenthart R, de Koning HJ, van der Aalst CM, Prokop M, Lammers JW, Zanen P, Mohamed Hoesein FA, Mali WP, van Ginneken B, van Rikxoort EM, de Jong PA. Diagnosis of chronic obstructive pulmonary disease in lung cancer screening Computed Tomography scans: independent contribution of emphysema, air trapping and bronchial wall thickening. Respir Res 2013;14:59. [Crossref] [PubMed]
42. Schreuder A, Jacobs C, Lessmann N, Broeders MJM, Silva M, Išgum I, de Jong PA, Sverzellati N, Prokop M, Pastorino U, Schaefer-Prokop CM, van Ginneken B. Combining pulmonary and cardiac computed tomography biomarkers for disease-specific risk modelling in lung cancer screening. Eur Respir J 2021;58:2003386. [Crossref] [PubMed]