# Systematic review and meta-analysis on the impact of lung cancer screening by low-dose computed tomography

Alexandre Sadate, Bob Ocean, Jean-Paul Beregi, Aymeric Hamard, Takieddine Addala, Hélène de Forges, Pascale Fabbro-Peray, Julien Frandon

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## To cite this version:

Alexandre Sadate, Bob Ocean, Jean-Paul Beregi, Aymeric Hamard, Takieddine Addala, et al. Systematic review and meta-analysis on the impact of lung cancer screening by low-dose computed tomography. European Journal of Cancer, 2020, 134, pp.107-114. 10.1016/j.ejca.2020.04.035. hal-03345675

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# Systematic review and meta-analysis on the impact of lung cancer screening by low-dose computed tomography

Alexandre Sadate (1), Bob V. Ocean (2), Jean-Paul Beregi (1), Aymeric Hamard (1), Takieddine

Addala (1), Hélène de Forges (1), Pascale Fabbro-Peray (2), Julien Frandon (1)

1 Department of Radiology and Medical Imaging, CHU Nîmes, Univ. Montpellier, EA2415, Nîmes, France

2 Department of Biostatistics, Epidemiology, Public Health and Innovation in Methodology (BESPIM), CHU Nîmes, Univ. Montpellier, Nîmes, France

Correspondance to:

Dr Alexandre Sadate, Département d'Imagerie Médicale, CHU Nîmes, 4 rue du Professeur-Robert-Debré, 30029 Nîmes cedex 9, France.

Mail : alexandre.sadate@chu-nimes.fr
# ABSTRACT

**Introduction.** Lung cancer (LC) has the highest cancer mortality worldwide with poor prognosis. Screening with low-dose computed tomography (LDCT) in populations highly exposed to tobacco has been proposed to improve LC prognosis. Our objective was to perform a systematic review and meta-analysis to evaluate the efficacy of screening by LDCT compared to any other intervention in populations who reported tobacco consumption for more than 15 years on LC and overall mortality.

**Methods.** We searched randomized controlled trials (RCTs) studying screening by LDCT compared with any other intervention in a population who reported an average smoking history greater than 15 pack-years from inception until the 19th February 2018 using Medline and Cochrane Library databases. Publication selection and data extraction were made independently by two double-blind reviewers.

**Results.** Seven RCTs were included in the meta-analysis which corresponds to 84558 participants. A significant relative reduction of LC-specific mortality of 17% (RR= 0.83, 95% CI: 0.76-0.91) and a relative reduction of overall mortality of 4% (RR= 0.96, 95% CI: 0.92-1.00) was observed in the screening group compared with the control group.

**Conclusion.** In populations highly exposed to tobacco, screening by LDCT reduces lung cancer mortality.
Keywords

Lung cancer; screening; low-dose computed tomography; meta-analysis

List of abbreviations

CI: Confidence Interval

CXR: Chest X-ray

LC: Lung Cancer

HAS: National Authority for Health

LDCT: Low-Dose Computed Tomography

NLST: National Lung Screening Trial

OR: Odds Ratio

PLCO: Prostate, Lung, Colorectal and Ovarian Cancer Screening Trial

p-yrs: person years

RCT: Randomized Controlled Trial

RR: Risk Ratio

Yrs: years
Introduction

Lung cancer shows the highest cancer mortality worldwide and a poor prognosis with a 5-year survival rate of 16% in the United States (1). It is the fourth most common cancer in France; around 30 000 lung cancer specific deaths in 2012 for around 40 000 diagnosed diseases (2). The incidence rates have been stable among men whilst they are rising rapidly in women in France and Europe. One cause may be that the main risk factor of lung cancer is tobacco consumption, that increases in women yet decreases in men (3,4). This confirms the promotion of smoking cessation is the most effective strategy to reduce LC mortality. One major issue is early detection, as nearly half of patients are diagnosed at an advanced stage, with various prognosis depending on cancer stage at diagnosis (5).

Two main trials have evaluated the benefits of chest radiography with or without sputum cytology, the PLCO Cancer Screening Trial and the Mayo Lung Project, with no efficacy in reduction of cancer-specific mortality (6,7). Several years later, a Japanese trial showed that low-dose computed tomography (LDCT) was superior to chest radiograph for the detection of peripheral lung cancer in a population highly exposed to tobacco (8). The Early Lung Cancer Action Project (ELCAP) program then showed that LDCT not only detected more lung cancers than chest radiography but also at an earlier and more resectable stage, which could potentially reduce cancer-specific mortality (9).

Radiation risk is one of the main obstacles preventing a more wide-spread lung cancer screening in populations highly exposed to tobacco. However, LDCT allows dose reduction without altering image quality (10), thanks to tube voltage and current reduction and iterative reconstructions.

Based on these results, several randomized controlled trials (RCT) were launched to evaluate the efficacy and cost effectiveness of a potential lung cancer screening in high-risk populations.

Following the results of a large randomized American trial, the National Lung Screening Trial (NLST) (11), which demonstrated a significant relative reduction in all-cause and lung cancer-specific mortality, the US Preventive Services Task Force recommended screening with LDCT all adults between 55 and 80 years with a 30 pack-year smoking history (12). Other international guidelines have also published recommendations supporting lung cancer screening in various eligible populations (13).
The objective of our systematic review and meta-analysis was to evaluate the efficacy of lung cancer screening by LDCT in populations highly exposed to tobacco on cancer specific- and overall mortality.

## Materials and methods

The systematic review protocol was registered with PROSPERO on March 27th, 2018 (CRD42018091720). Results are reported here following the PRISMA Equator Network guidelines (14).

## Search strategy

The search was made using the Medline and Cochrane Library databases. The research terms were covering lung cancer, screening by LDCT compared with any other intervention, randomized controlled trials (RCT) and their synonyms, from inception until the February 19th, 2018, as follows: ((("Lung Neoplasms"[Mesh] OR lung neoplasm*[TIAB] OR pulmonary neoplasm*[TIAB] OR bronchopulmonary neoplasm*[TIAB] OR broncho-pulmonary neoplasm*[TIAB] OR bronchial neoplasm*[TIAB] OR lung cancer*[TIAB] OR pulmonary cancer*[TIAB] OR bronchopulmonary cancer*[TIAB] OR broncho-pulmonary cancer*[TIAB] OR bronchial cancer*[TIAB] OR lung carcinoma*[TIAB] OR pulmonary carcinoma*[TIAB] OR bronchopulmonary carcinoma*[TIAB] OR broncho-pulmonary carcinoma*[TIAB] OR bronchial carcinoma*[TIAB] OR bronchogenic carcinoma*[TIAB] OR lung blastoma*[TIAB] OR pulmonary blastoma*[TIAB] OR bronchopulmonary blastoma*[TIAB] OR broncho-pulmonary blastoma*[TIAB] OR bronchial blastoma*[TIAB] OR lung tumor*[TIAB] OR pulmonary tumor*[TIAB] OR bronchopulmonary tumor*[TIAB] OR broncho-pulmonary tumor*[TIAB] OR bronchial tumor*[TIAB])) AND ("Mass Screening"[Mesh] OR "Early Detection of Cancer"[Mesh] OR screen*[TIAB] OR test[TI] OR testing[TI] OR detection*[TI])) AND (random*[TI] OR randomly[TIAB] OR randomized[TIAB] OR placebo[TIAB] OR Random
Allocation[MH] OR Double-Blind Method[MH] OR Single-Blind Method[MH] OR Cross-Over
Studies[MH] OR randomized controlled trial[PT] OR controlled clinical trial[PT]))))

It was completed by a Medline search with the names of the trials identified, the reference list of the eligible articles, a clinicaltrials.gov database search, a free-text Internet search and a regular update Medline search. The search was limited to articles published in English and French. The initial search was updated on February 12th, 2020.

## Study selection criteria

Inclusion criteria for the systematic review and meta-analysis were topics about lung cancer screening, RCT study design, LDCT compared to any other intervention, population who reported an average smoking history over 15 pack-years (corresponding to the lowest criteria of the European RCTs on lung cancer screening) and the report of data on all-cause mortality or lung cancer-specific mortality.

Two double-blind reviewers (AS, QD) selected the publications by screening the titles and abstracts first, and then on the full-text articles. Discrepancies were resolved by consensus between the two readers. If a consensus was not made, an epidemiologic expert (PFP), it was consulted.

## Quality assessment and data extraction

The critical appraisal of each eligible RCT was made by two reviewers (AS, JF) using a CONSORT checklist including random assignment, complete diagnostic work-up planned, respect of inclusion criteria, valid measurement of mortality and blinded outcomes assessment. The contents of the checklist and the inclusion or exclusion of each study for the meta-analysis were then discussed with two epidemiologic experts (PFP, BO). Data were collected and managed using REDCap electronic data capture tools.

The extraction of the data for the meta-analysis was made independently by two double-blind reviewers (AS, JF), and the differences were resolved by an epidemiologic expert (PFP). When several articles were available for a single study, data from the most recent publication were used, unless unique data was found in a previous publication. The following data were extracted: title of the article, sample size,
participants, characteristics (age, sex, smoking history), type of intervention in the control arm, median follow-up, number of screening rounds, time between rounds, number of any-cause and lung cancer-associated deaths.

## Statistical analysis

Results on all-causes and lung cancer-specific mortality of the studies included were combined for meta-analysis. In the collection of studies considered the effect size and the true effect size were estimated. A general model was then specified by both standard and random effects models to incorporate the between-study variance (15). The inverse variance weighting method was used for pooling, on the hypothesis of common "effect size" normality and weights assigned to individual studies. This method allows maximizing the accuracy of the estimate of the common effect, minimizing the variance of the pooled result. The binary outcome data as mortality rate was extracted in a 2X2 table for all selected studies. A relative risk and 95% confidence interval (95% CI) were used as summary statistics. The heterogeneity between trials was taken into account using chi-square tests. I² statistic was used to estimate the percentage of total variation across studies arising from heterogeneity rather than chance. I² values of 25%, 50%, and 75% represented a low, moderate or substantial heterogeneity (16). The reasons for substantial heterogeneity were explored and subgroup analyses were performed to consider possible variations across studies. Supplementary analyses excluding studies with heterogeneity and low contribution to the overall effect, then including only those with the highest weighting, were performed. A subgroup analysis was performed to take into account variability across studies during follow-up. Possible publication biases were explored through visual analysis of funnel plots. Statistical analysis was performed using General Package for Meta-Analysis "meta" v4.9-1 with R software v3.5.1.
# Results

## Study selection

Of the 891 publications identified with the search strategy in the Medline and Cochrane Library databases, 799 were excluded on titles and abstracts because of topic or study design: 449 were not related to lung cancer screening, 142 reported results of lung cancer screening without using LDCT, 40 were not RCTs and 168 were systematic review or general considerations. The additional search identified 22 other publications which were added to the 92 studies. Reading the full-text of these 114 publications, 107 studies were excluded: 11 were pilot study, 31 did not report mortality data in the control group, 59 did not assess mortality as primary endpoint, and 6 presented intermediate results. A total of 7 RCTs were finally included, including a total of 84,558 patients (Figure 1) (17–23).

## Study characteristics and quality assessment

The characteristics of the 7 RCTs included are detailed in Table 1. For all studies included in the meta-analysis, randomization was performed at inclusion. The intervention in the control arm was chest X-ray (CXR) at inclusion followed by annual clinical examination in the DANTE study, annual CXR in the NLST study, primary prevention for smoking cessation in four RCTs (NELSON, LUSI, ITALUNG, MILD) and annual clinical examination for the Danish Randomized Lung Cancer CT Screening Trial (DLCST). Five studies included both men and women; the DANTE and NELSON studies only included men.

All 7 trials presented a complete diagnostic work-up planned in the protocol with well-described and respected inclusion criteria. Validity of mortality measurement was checked in all studies. Quality assessment results of all 7 RCTs are shown in Table 2.

## Overall and lung cancer-specific mortality

Two trials reported statistically significant results on mortality data. The NLST trial showed a relative reduction of lung cancer-specific mortality of 20% (95% CI: 6.8-26.7; *p*=0.004) and a relative
reduction of overall mortality of 6.7% (95% CI: 1.2-13.6) in the LDCT group compared to the control annual CXR group. The NELSON study reported a relative reduction of lung-cancer-specific mortality of 24% (95% CI: 6-39; *p*=0.01) compared with standard primary prevention; there was no difference of overall mortality in the two groups.

The final results of the ITALILUNG, DANTE, MILD and LUSI trials did not find any difference for both overall and lung cancer-specific mortality in the LDCT groups compared to the control groups.

## Publication biases

The risk of publication bias was evaluated using a funnel plot (Figure 2). The symmetric distribution of the relative risk across the global effect paired with the standard deviation of the screening effect confirmed the studies included did not present major biases.

## Results of the meta-analysis

A total of 84,558 participants were included in the meta-analysis. There was no heterogeneity in the data (I²=0%, tau²=0, *p*=0.67). A relative reduction of overall mortality of 4% was observed in the experimental screening group *versus* control group (RR=0.96, 95% CI: 0.92-1.00) (Figure 3). Concerning lung cancer-specific mortality, a significant relative reduction of 17% was observed in the experimental screening group (RR=0.83, 95% CI: 0.76-0.91) (Figure 4). To prevent one lung-cancer related death, 294 patients needed to be screened.
Discussion

Our meta-analysis on the impact of lung cancer screening using LDCT is, to our knowledge, the first meta-analysis including the final mortality results of the recently published NELSON, DLCST, ITALUNG, MILD and LUSI studies (18–20,22,23). Our results show a significant relative reduction of lung cancer-specific mortality of 17% in the screening group compared to the control group, but no significant difference in the mortality of all causes.

A previous meta-analysis (24) based on the pooled analysis of four RCTs (DANTE, MILD, NLST and the intermediate results of DLCST) showed a significant decrease of lung cancer-specific mortality in the control group (OR=0.84 [0.78, 0.96]); no difference was reported for overall mortality between the two groups (OR=1.04 [0.72, 1.51]). However, this pooled analysis included RCTs with both short (intermediate results of MILD with a 4.4-year follow-up) or long follow-up (DANTE: 8.3-year follow-up), one reason of the heterogeneity of the study (Q test *p*-value = 0.13). In our meta-analysis, we have included more studies as recent RCTs have been published since, including the final results of the MILD study, *i.e.* we included only final results for the RCTs included, and thus mostly long follow-up studies.

One major issue regarding lung cancer risk and screening is defining target populations at risk. Among studies included in the meta-analysis, only the NLST study included older participants with higher smoking history. Subgroups analyses divided the population into quintiles according to the risk of lung-cancer associated death (25). Lung-cancer specific mortality increased significantly with each quintile and the proportion of false positive results decreased significantly. Overall, 88% of the prevented lung cancer-associated deaths in the LDCT group corresponded to the 60% of participants within the highest risk subgroups, whereas 1% of the prevented lung cancer deaths accounted for 20% of participants in the lowest risk subgroups. Furthermore, the number of screened patients required to prevent one death from lung cancer decreased from 5276 in the lowest risk subgroup to 161 in the highest risk subgroup of patients. Another study with post-hoc analysis of the targeted population was published on the DLCST cohort (24). In the highest risk subgroup (patients with chronic obstructive pulmonary disease and a smoking history of more than 35 pack-years), there was a non-significant a 20% decrease
in the hazard ratio for LC mortality in the LDCT group was reported although it did not reach significance (26). The recent NELSON study included patients with relatively small smoking history (less than 36 packs.years) as compared with other studies and especially the NLST study (23). Overall, these results suggest the screening program may be restricted to patients with the highest risk, *i.e.* patients with a significant smoking history.

Our meta-analysis included the eagerly awaited recent NELSON study (23). This well-designed study, the biggest European study, reported results after a long follow-up (10 years). The results were significant regarding the specific overall mortality, but did not show any difference between the two groups for the all-causes mortality. This was explained by the authors by the study design, as the study included around 13,000 patients, a number, although consequent, which was not sufficient to show a difference. Also, a strength of the NELSON study was the very low number of false-positive (1.2% only). This may be due to the study design and the fact that the positive screening tests were assessed by nodule volume and not size as many other studies.

One strength of our meta-analysis is the design and quality of our study; we conducted a systematic review following the PRISMA guidelines with two double-blind independent reviewers to avoid missing publications. Quality assessment of each eligible trial and data extraction were also made by two double-blind independent readers to prevent data errors. Other strengths included inclusion in our meta-analysis of only controlled randomized studies with precise inclusion and exclusion criteria. Also, the studies included had long-term follow-up and we only included final analyses results (no intermediate or preliminary results). The symmetric distribution of the relative risk in the funnel plot confirms the minimal publication bias among the studies included. Last, our meta-analysis included a large final total number of patients (n=84,558).

Limitations of our study include the partial heterogeneity of the protocols studied, in particular the interventions in the control arm, either prevention or clinical examination in all the studies except the NLST (annual CXR), and DANTE (CXR at inclusion) studies. Also, heterogeneity among studies concerned the smoking history of patients included, much higher in the NLST study than in other RCTs included.
## Conclusions

Our meta-analysis is the first systematic review to include all recent RCTs including the recent NELSON study. Our results confirm that of the NELSON study, showing an impact of lung cancer screening on lung cancer-specific mortality, reduced in the LDCT group. No impact of such screening on all-cause mortality was reported.

## Acknowledgements

We would like to thank Sarah Kabani for valuable editorial assistance and Quentin Durand for the study selection. This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors.

## Conflict of Interest statement

None declared

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**Figure and Table legends**

Table 1: Details of the 7 Randomized Clinical Trials included

Table 2: Quality assessment results

Figure 1: PRISMA flowdiagram of the meta-analysis

Figure 2: Funnel plot reporting relative risk for overall mortality

Figure 3: Forrest plot of relative risk for overall mortality

Figure 4: Forrest plot of relative risk for lung cancer specific mortality
Included

Eligibility

Screening

Identification

<figure><img src="image_3.png" /></figure>

Records identified through
database searching
(n=891)

Additional records identified
through other sources
(n=22)
<figure><img src="image_4.png" /><figcaption>Standard Error</figcaption></figure>

Risk Ratio
<table><thead><tr><th rowspan="2">Study</th><th colspan="2">Experimental</th><th colspan="2">Control</th><th colspan="2">Risk Ratio</th></tr><tr><th>Events</th><th>Total</th><th>Events</th><th>Total</th><th>Weight</th><th>IV, Fixed, 95% CI</th></tr></thead><tbody><tr><td>NLST - 2013</td><td>1912</td><td>26722</td><td>2039</td><td>26730</td><td>53.5%</td><td>0.94 [0.88-1.00]</td></tr><tr><td>DANTE - 2015</td><td>180</td><td>1264</td><td>176</td><td>1186</td><td>5.2%</td><td>0.96 [0.79-1.16]</td></tr><tr><td>DLCST - 2015</td><td>165</td><td>2052</td><td>163</td><td>2052</td><td>4.5%</td><td>1.01 [0.82-1.25]</td></tr><tr><td>ITALILUNG - 2017</td><td>154</td><td>1613</td><td>181</td><td>1593</td><td>4.7%</td><td>0.84 [0.69-1.03]</td></tr><tr><td>MILD - 2019</td><td>137</td><td>2376</td><td>106</td><td>1723</td><td>3.2%</td><td>0.94 [0.73-1.20]</td></tr><tr><td>LUSI - 2019</td><td>148</td><td>2029</td><td>150</td><td>2023</td><td>4.0%</td><td>0.98 [0.79-1.22]</td></tr><tr><td>NELSON - 2020</td><td>868</td><td>6583</td><td>860</td><td>6612</td><td>24.9%</td><td>1.01 [0.93-1.11]</td></tr></tbody><tfoot><tr><td>Total (95% CI)</td><td colspan="2">42639</td><td colspan="2">41919</td><td>100.0%</td><td>0.96 [0.92-1.00]</td></tr></tfoot></table>

Heterogeneity: Tau² = 0; Chi² = 4.02, df = 6 (P = 0.67); I² = 0%

<figure><img src="image_5.png" /></figure>

<==Favours Experimental group Favours Control group==>
<table><thead><tr><th rowspan="2">Study</th><th colspan="2">Experimental</th><th colspan="2">Control</th><th colspan="2">Risk Ratio</th></tr><tr><th>Events</th><th>Total</th><th>Events</th><th>Total</th><th>Weight</th><th>IV, Fixed, 95% CI</th></tr></thead><tbody><tr><td>NLST - 2013</td><td>469</td><td>26722</td><td>552</td><td>26730</td><td>55.6%</td><td>0.85 [0.75-0.96]</td></tr><tr><td>DANTE - 2015</td><td>59</td><td>1264</td><td>55</td><td>1186</td><td>6.4%</td><td>1.01 [0.70-1.44]</td></tr><tr><td>DLCST - 2015</td><td>39</td><td>2052</td><td>38</td><td>2052</td><td>4.2%</td><td>1.03 [0.66-1.60]</td></tr><tr><td>ITALILUNG - 2017</td><td>43</td><td>1613</td><td>60</td><td>1593</td><td>5.6%</td><td>0.71 [0.48-1.04]</td></tr><tr><td>MILD - 2019</td><td>40</td><td>2376</td><td>40</td><td>1723</td><td>4.4%</td><td>0.73 [0.47-1.12]</td></tr><tr><td>LUSI - 2019</td><td>29</td><td>2029</td><td>40</td><td>2023</td><td>3.7%</td><td>0.72 [0.45-1.16]</td></tr><tr><td>NELSON - 2020</td><td>160</td><td>6583</td><td>210</td><td>6612</td><td>20.1%</td><td>0.77 [0.62-0.94]</td></tr><tr><td>Total (95% CI)</td><td colspan="2">42639</td><td colspan="2">41919</td><td>100.0%</td><td>0.83 [0.76-0.91]</td></tr></tbody></table>

Heterogeneity: Tau² = 0; Chi² = 4.11, df = 6 (P = 0.66); I² = 0%

<figure><img src="image_6.png" /></figure>

<==Favours Experimental group Favours Control group==>
<table><caption>Table 1 Randomized Controlled Trials included in the meta-analysis</caption><thead><tr><th>Characteristics</th><th>DANTE<br>2015<br>(1)</th><th>DLSCT<br>2015<br>(24, 29)</th><th>ITALILUNG<br>2017<br>(4)</th><th>MILD<br>2019<br>(5)</th><th>LUSI<br>2019<br>(6,7)</th><th>NLST<br>2013<br>(8-10)</th><th>NELSON<br>2020<br>(11)</th></tr></thead><tbody><tr><td>Country</td><td>Italy</td><td>Denmark</td><td>Italy</td><td>Italy</td><td>Germany</td><td>USA</td><td>Belgium / Netherland</td></tr><tr><td>Control arm</td><td>CXR at inclusion</td><td>Annual clinical examination</td><td>Primary prevention for smoking cessation</td><td>Primary prevention for smoking cessation</td><td>Primary prevention for smoking cessation</td><td>Annual CXR</td><td>Primary prevention for smoking cessation</td></tr><tr><td>Total sample size</td><td>2450</td><td>4104</td><td>3206</td><td>4099</td><td>4052</td><td>53452</td><td>13195</td></tr><tr><td>LDCT arm</td><td>1264</td><td>2052</td><td>1613</td><td>2376</td><td>2029</td><td>26722</td><td>6583</td></tr><tr><td>Control arm</td><td>1186</td><td>2052</td><td>1593</td><td>1723</td><td>2023</td><td>26730</td><td>6612</td></tr><tr><td>Age, yrs</td><td>60-74</td><td>50-70</td><td>55-69</td><td>≥49</td><td>50-69</td><td>55-74</td><td>50-74</td></tr><tr><td>Men, %</td><td>100</td><td>55</td><td>65</td><td>66</td><td>65</td><td>59</td><td>100</td></tr><tr><td>Median follow-up, yrs</td><td>8.35</td><td>Intermediate: 4.8<br>Final: 9.8</td><td>9.3</td><td>4.4</td><td>3</td><td>6.5</td><td>10</td></tr><tr><td>Screening, p/yr</td><td>10875</td><td>19439</td><td>14658</td><td>6449.5</td><td>/</td><td>144103</td><td>/</td></tr><tr><td>Control, p/yr</td><td>10104</td><td>19547</td><td>14247</td><td>5556.7</td><td>/</td><td>143368</td><td>/</td></tr><tr><td>Smoking history</td><td>Mean [95% CI]:<br>Mean [95% CI]:<br>Mean: 40</td><td>Mean [95% CI]:<br>Mean [95% CI]:<br>Mean: 39</td><td>Mean: 40</td><td>Median: 39</td><td>NR</td><td>Mean: 56.04</td><td>Mean: 38.0 [29.7-49.5]</td></tr><tr><td>LDCT, pack-yrs</td><td>47.3 [45.7-49]</td><td>36.4 [23-49.8]</td><td>40</td><td>39</td><td>NR</td><td>56.04</td><td>38.0 [29.7-49.5]</td></tr><tr><td>Controls, pack-yrs</td><td>47.2 [45.5-49]</td><td>35.9 [22.5-49.3]</td><td>38</td><td>38</td><td>NR</td><td>55.93</td><td>38.0 [29.7-49.5]</td></tr><tr><td>Current smoker, n (%)</td><td>1395 (57%)</td><td>3124 (76%)</td><td>2077 (65%)</td><td>3176 (77%)</td><td>2506 (62%)</td><td>25779 (48%)</td><td>7254 (55%)</td></tr><tr><td>Former Smoker, n (%)</td><td>1055 (43%)</td><td>980 (24%)</td><td>1129 (35%)</td><td>923 (23%)</td><td>1545 (38%)</td><td>27677 (52%)</td><td>5941 (45%)</td></tr><tr><td>Screening rounds, n</td><td>5</td><td>5</td><td>4</td><td>5 or 3<sup>1</sup></td><td>5</td><td>3</td><td>4</td></tr><tr><td>Time between rounds, yrs</td><td>1</td><td>1</td><td>1</td><td>1 or 2</td><td>1</td><td>1</td><td>1-2-2.5</td></tr><tr><td>Definition of positive screening test</td><td>Nodule ≥ 10 mm</td><td>Nodule ≥ 5 mm</td><td>Nodule ≥ 5 mm</td><td>Nodule volume ≥60mm<sup>3</sup></td><td>Nodule ≥ 5 mm</td><td>Nodule ≥ 4mm</td><td>Nodule volume ≥50mm<sup>3</sup></td></tr></tbody></table>

CXR: Chest X-ray / 95% CI: 95% confidence interval / NR: not reported

¹⁵ for the annual arm and 3 for the biennial arm; p-yr: person years; yrs: years
<table><caption>Table 2: Quality assessment (CONSORT Check List) of the seven randomized controlled trials included in the meta-analysis.</caption><thead><tr><th>Quality criteria</th><th>DANTE</th><th>DLSCT</th><th>ITALILUNG</th><th>MILD</th><th>LUSI</th><th>NLST</th><th>NELSON</th></tr></thead><tbody><tr><td>Recruitment Strategies well defined</td><td>Yes</td><td>Yes</td><td>Yes</td><td>Yes</td><td>Yes</td><td>Yes</td><td>Yes</td></tr><tr><td>Complete diagnostic work-up planned</td><td>Yes</td><td>Yes</td><td>Yes</td><td>Yes</td><td>Yes</td><td>Yes</td><td>Yes</td></tr><tr><td>Random assignment</td><td>Yes</td><td>Yes</td><td>Yes</td><td>Yes</td><td>Yes</td><td>Yes</td><td>Yes</td></tr><tr><td>Inclusion criteria described and respected</td><td>Yes</td><td>Yes</td><td>Yes</td><td>Yes</td><td>Yes</td><td>Yes</td><td>Yes</td></tr><tr><td>Measure of all-cause mortality</td><td>Yes</td><td>Yes</td><td>Yes</td><td>Yes</td><td>Yes</td><td>Yes</td><td>Yes</td></tr><tr><td>Measure of specific mortality</td><td>Yes</td><td>Yes</td><td>Yes</td><td>Yes</td><td>No</td><td>Yes</td><td>Yes</td></tr><tr><td>Valid measurement of mortality</td><td>Yes</td><td>Yes</td><td>Yes</td><td>Yes</td><td>Yes</td><td>Yes</td><td>Yes</td></tr><tr><td>Blinded of outcome Assessment</td><td>Yes</td><td>NR</td><td>Yes</td><td>Yes</td><td>NR</td><td>Yes</td><td>Yes</td></tr><tr><td>Long enough follow-up</td><td>Yes</td><td>Yes</td><td>Yes</td><td>No</td><td>Yes</td><td>Yes</td><td>Yes</td></tr></tbody></table>

NR: not reported