Dataset Information

Lung cancer screening with low-dose spiral computed tomography: evidence from a pooled analysis of two Italian randomized trials.

ABSTRACT: The benefits and harms of lung cancer (LC) screening with low-dose computed tomography (LDCT) are debatable. Positive results from the US National Lung Screening Trial were not evident in the European trials, possibly due to their smaller sample sizes. To address this issue, we conducted a patient-level pooled analysis of two Italian randomized controlled trials. Data from DANTE and MILD trials were combined for a total of 3640 individuals in the LDCT arm and 2909 in the control arm. LC and overall mortality were analyzed using multivariate hazard ratios (HRs) and log-rank tests stratified by study. The median follow-up was 8.2 years, with a total of 30?480 person-years in the LDCT arm and 22?157 in the control arm. A total of 192 patients developed LC in the LDCT arm and 105 in the control arm. Half of the LC cases in the LDCT arm had stage IA or IB cancer, as compared with 21% in the control arm. Overall mortality rates/100?000 person-years were 925 in the LDCT arm and 1074 in the control arm, and LC mortality rates were 299 and 357, respectively. The multivariate pooled overall mortality HR was 0.89 (95% confidence interval: 0.74-1.06) and the LC mortality HR was 0.83 (95% confidence interval: 0.61-1.12) for the LDCT arm as compared with the control arm. The present pooled analysis shows a nonsignificant 11% reduction in overall mortality in individuals undergoing LDCT screening as compared with the control arm. A pooled analysis of all European trials would be a useful contribution to assess the real benefit of LDCT screening.

SUBMITTER: Infante M

PROVIDER: S-EPMC6861837 | biostudies-literature | 2017 Jul

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Lung cancer screening with low-dose spiral computed tomography: evidence from a pooled analysis of two Italian randomized trials.

Infante Maurizio M Sestini Stefano S Galeone Carlotta C Marchianò Alfonso A Lutman Fabio R FR Angeli Enzo E Calareso Giuseppina G Pelosi Giuseppe G Sozzi Gabriella G Silva Mario M Sverzellati Nicola N Cavuto Silvio S La Vecchia Carlo C Santoro Armando A Alloisio Marco M Pastorino Ugo U

European journal of cancer prevention : the official journal of the European Cancer Prevention Organisation (ECP) 20170701 4

The benefits and harms of lung cancer (LC) screening with low-dose computed tomography (LDCT) are debatable. Positive results from the US National Lung Screening Trial were not evident in the European trials, possibly due to their smaller sample sizes. To address this issue, we conducted a patient-level pooled analysis of two Italian randomized controlled trials. Data from DANTE and MILD trials were combined for a total of 3640 individuals in the LDCT arm and 2909 in the control arm. LC and over ...[more]

PMID: 27222939

Similar Datasets

Project description:ImportanceScreening for lung cancer has the potential to reduce mortality, but in addition to detecting aggressive tumors, screening will also detect indolent tumors that otherwise may not cause clinical symptoms. These overdiagnosis cases represent an important potential harm of screening because they incur additional cost, anxiety, and morbidity associated with cancer treatment.ObjectiveTo estimate overdiagnosis in the National Lung Screening Trial (NLST).Design, setting, and participantsWe used data from the NLST, a randomized trial comparing screening using low-dose computed tomography (LDCT) vs chest radiography (CXR) among 53 452 persons at high risk for lung cancer observed for 6.4 years, to estimate the excess number of lung cancers in the LDCT arm of the NLST compared with the CXR arm.Main outcomes and measuresWe calculated 2 measures of overdiagnosis: the probability that a lung cancer detected by screening with LDCT is an overdiagnosis (PS), defined as the excess lung cancers detected by LDCT divided by all lung cancers detected by screening in the LDCT arm; and the number of cases that were considered overdiagnosis relative to the number of persons needed to screen to prevent 1 death from lung cancer.ResultsDuring follow-up, 1089 lung cancers were reported in the LDCT arm and 969 in the CXR arm of the NLST. The probability is 18.5% (95% CI, 5.4%-30.6%) that any lung cancer detected by screening with LDCT was an overdiagnosis, 22.5% (95% CI, 9.7%-34.3%) that a non-small cell lung cancer detected by LDCT was an overdiagnosis, and 78.9% (95% CI, 62.2%-93.5%) that a bronchioalveolar lung cancer detected by LDCT was an overdiagnosis. The number of cases of overdiagnosis found among the 320 participants who would need to be screened in the NLST to prevent 1 death from lung cancer was 1.38.Conclusions and relevanceMore than 18% of all lung cancers detected by LDCT in the NLST seem to be indolent, and overdiagnosis should be considered when describing the risks of LDCT screening for lung cancer.

Project description:ImportanceDespite the recommendations of lung cancer screening guidelines and the evidence supporting the effectiveness of population-based lung screening, a common barrier to effective lung cancer screening is that the participation rates of low-dose computed tomography (LDCT) screening among individuals with the highest risk are not large. There are limited data from clinical practice regarding whether opportunistic LDCT screening is associated with reduced lung-cancer mortality.ObjectiveTo evaluate whether opportunistic LDCT screening is associated with improved prognosis among adults with lung cancer in mainland China.Design, setting, and participantsThis cohort study included patients diagnosed with lung cancer at Weihai Municipal Hospital Healthcare Group, Weihai City, China, from 2016 to 2021. Data were analyzed from January 2022 to February 2023.ExposuresData collected included demographic indicators, tumor characteristics, comorbidities, blood indexes, and treatment information. Patients were classified into screened and nonscreened groups on the basis of whether or not their lung cancer diagnosis occurred through opportunistic screening.Main outcomes and measuresFollow-up outcome indicators included lung cancer-specific mortality and all-cause mortality. Propensity score matching (PSM) was adopted to account for potential imbalanced factors between groups. The associations between LDCT screening and outcomes were analyzed using Cox regression models based on the matched data. Propensity score regression adjustment and inverse probability treatment weighting were used for sensitivity analysis.ResultsA total of 5234 patients (mean [SD] baseline age, 61.8 [9.8] years; 2518 [48.1%] female) with complete opportunistic screening information were included in the analytical sample, with 2251 patients (42.91%) receiving their lung cancer diagnosis through opportunistic screening. After 1:1 PSM, 2788 patients (1394 in each group) were finally included. The baseline characteristics of the matched patients were balanced between groups. Opportunistic screening with LDCT was associated with a 49% lower risk of lung cancer death (HR, 0.51; 95% CI, 0.42-0.62) and 46% lower risk of all-cause death (HR, 0.54; 95% CI, 0.45-0.64).Conclusions and relevanceIn this cohort study of patients with lung cancer, opportunistic lung cancer screening with LDCT was associated with lower lung cancer mortality and all-cause mortality. These findings suggest that opportunistic screening is an important supplement to population screening to improve prognosis of adults with lung cancer.

Project description:ImportanceLung cancer screening has been widely implemented in Europe and the US. However, there is little evidence on participation and diagnostic yields in population-based lung cancer screening in China.ObjectiveTo assess the participation rate and detection rate of lung cancer in a population-based screening program and the factors associated with participation.Design, setting, and participantsThis cross-sectional study used data from the Cancer Screening Program in Urban China from October 2013 to October 2019, with follow-up until March 10, 2020. The program is conducted at centers in 8 cities in Henan Province, China. Eligible participants were aged 40 to 74 and were evaluated for a high risk for lung cancer using an established risk score system.Main outcomes and measuresOverall and group-specific participation rates by common factors, such as age, sex, and educational level, were calculated. Differences in participation rates between those groups were compared. The diagnostic yield of both screening and nonscreening groups was calculated.ResultsThe study recruited 282 377 eligible participants and included 55 428 with high risk for lung cancer; the mean (SD) age was 55.3 (8.1) years, and 34 966 participants (63.1%) were men. A total of 22 260 participants underwent LDCT (participation rate, 40.16%; 95% CI, 39.82%-40.50%). The multivariable logistic regression model showed that female sex (odds ratio [OR], 1.64; 95% CI, 1.52-1.78), former smoking (OR, 1.26; 95% CI, 1.13-1.41), lack of physical activity (OR, 1.19; 95% CI, 1.14-1.24), family history of lung cancer (OR, 1.73; 95% CI, 1.66-1.79), and 7 other factors were associated with increased participation of LDCT screening. Overall, at 6-year follow-up, 78 participants in the screening group (0.35%; 95% CI, 0.29%-0.42%) and 125 in the nonscreening group (0.38%; 95% CI, 0.33%-0.44%) had lung cancer detected, which resulted in an odds ratio of 0.93 (95% CI, 0.70-1.23; P = .61).Conclusions and relevanceThe low participations rate in the program studied suggests that an improved strategy is needed. These findings may provide useful information for designing effective population-based lung cancer screening strategies in the future.

Dataset Information

Lung cancer screening with low-dose spiral computed tomography: evidence from a pooled analysis of two Italian randomized trials.

Publications

Lung cancer screening with low-dose spiral computed tomography: evidence from a pooled analysis of two Italian randomized trials.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets