Volunteer effect and compromised randomization in the Mayo Project of screening for lung cancer

The role of randomized cluster crossover trials for comparative effectiveness testing in anesthesia: design of the Benzodiazepine-Free Cardiac Anesthesia for Reduction in Postoperative Delirium (B-Free) trial

Increasingly, clinicians and researchers recognize that studies of interventions need to evaluate not only their therapeutic efficacy (i.e., the effect on an outcome in ideal, controlled settings) but also their real-world effectiveness in broad, unselected patient groups. Effectiveness trials inform clinical practice by comparing variations in therapeutic approaches that fall within the standard of care. In this article, we discuss the need for studies of comparative effectiveness in anesthesia and the limitations of individual patient randomized-controlled trials in determining comparative effectiveness. We introduce the concept of randomized cluster crossover trials as a means of answering questions of comparative effectiveness in anesthesia, using the design of the Benzodiazepine-Free Cardiac Anesthesia for Reduction in Postoperative Delirium (B-Free) trial (Clinicaltrials.gov identifier NCT03053869).

The Rotterdam Study: 2014 objectives and design update

The Rotterdam Study is a prospective cohort study ongoing since 1990 in the city of Rotterdam in The Netherlands. The study targets cardiovascular, endocrine, hepatic, neurological, ophthalmic, psychiatric, dermatological, oncological, and respiratory diseases. As of 2008, 14,926 subjects aged 45 years or over comprise the Rotterdam Study cohort. The findings of the Rotterdam Study have been presented in over a 1,000 research articles and reports (see www.erasmus-epidemiology.nl/rotterdamstudy ). This article gives the rationale of the study and its design. It also presents a summary of the major findings and an update of the objectives and methods.

Screening for lung cancer

BACKGROUND

This is an updated version of the original review published in The Cochrane Library in 1999 and updated in 2004 and 2010. Population-based screening for lung cancer has not been adopted in the majority of countries. However it is not clear whether sputum examinations, chest radiography or newer methods such as computed tomography (CT) are effective in reducing mortality from lung cancer.

OBJECTIVES

To determine whether screening for lung cancer, using regular sputum examinations, chest radiography or CT scanning of the chest, reduces lung cancer mortality.

SEARCH METHODS

We searched electronic databases: the Cochrane Central Register of Controlled Trials (CENTRAL) (The Cochrane Library 2012, Issue 5), MEDLINE (1966 to 2012), PREMEDLINE and EMBASE (to 2012) and bibliographies. We handsearched the journal Lung Cancer (to 2000) and contacted experts in the field to identify published and unpublished trials.

SELECTION CRITERIA

Controlled trials of screening for lung cancer using sputum examinations, chest radiography or chest CT.

DATA COLLECTION AND ANALYSIS

We performed an intention-to-screen analysis. Where there was significant statistical heterogeneity, we reported risk ratios (RRs) using the random-effects model. For other outcomes we used the fixed-effect model.

MAIN RESULTS

We included nine trials in the review (eight randomised controlled studies and one controlled trial) with a total of 453,965 subjects. In one large study that included both smokers and non-smokers comparing annual chest x-ray screening with usual care there was no reduction in lung cancer mortality (RR 0.99, 95% CI 0.91 to 1.07). In a meta-analysis of studies comparing different frequencies of chest x-ray screening, frequent screening with chest x-rays was associated with an 11% relative increase in mortality from lung cancer compared with less frequent screening (RR 1.11, 95% CI 1.00 to 1.23); however several of the trials included in this meta-analysis had potential methodological weaknesses. We observed a non-statistically significant trend to reduced mortality from lung cancer when screening with chest x-ray and sputum cytology was compared with chest x-ray alone (RR 0.88, 95% CI 0.74 to 1.03). There was one large methodologically rigorous trial in high-risk smokers and ex-smokers (those aged 55 to 74 years with ≥ 30 pack-years of smoking and who quit ≤ 15 years prior to entry if ex-smokers) comparing annual low-dose CT screening with annual chest x-ray screening; in this study the relative risk of death from lung cancer was significantly reduced in the low-dose CT group (RR 0.80, 95% CI 0.70 to 0.92).

AUTHORS' CONCLUSIONS

The current evidence does not support screening for lung cancer with chest radiography or sputum cytology. Annual low-dose CT screening is associated with a reduction in lung cancer mortality in high-risk smokers but further data are required on the cost effectiveness of screening and the relative harms and benefits of screening across a range of different risk groups and settings.

Assessment of lung cancer mortality reduction after chest X-ray screening in smokers: a population-based cohort study in Varese, Italy

BACKGROUND

The effectiveness of screening for lung cancer (LC) in smokers on a population level, as distinct from the special circumstances that may apply in a randomized trial of selected volunteers, has not been thoroughly investigated. Here we evaluate by the standardized mortality ratio (SMR) indicator the impact of a chest X-ray (CXR) screening programme carried out at community level on LC mortality in smokers.

METHODS

All smokers of >10 pack-years, of both genders, ages 45-75 years, resident in 50 communities of the Province of Varese, Italy, screening-eligible, in 1997 were invited by their National Health Service (NHS) general practitioner physicians to a nonrandomized programme of five annual CXR screenings. The entire invitation-to-screen cohort (n=5815 subjects) received NHS usual care, with the addition of CXR exams in volunteer participants (21% of invitees), and was observed through December 2006. To overcome participants' selection bias of LC mortality assessment, for the entire invitation-to-screen cohort we estimated the LC-specific SMR, based on the local reference population receiving the NHS usual care.

RESULTS

Over the 8-year period 1999-2006, a total of 172 cumulative LC deaths were observed in the invitation-to-screen cohort; 210 were expected based on the reference population. Each year in the invited cohort the observed LC deaths were fewer than expected. The cumulative LC SMR was 0.82 (95% CI, 0.67-0.99; p=0.048), suggesting that LC mortality was reduced by 18% with CXR screening.

CONCLUSION

Implementation of a CXR screening programme at community level was associated with a significant reduction of LC mortality in smokers.

Exploring the uncertainties of early detection results: model-based interpretation of mayo lung project

BACKGROUND

The Mayo Lung Project (MLP), a randomized controlled clinical trial of lung cancer screening conducted between 1971 and 1986 among male smokers aged 45 or above, demonstrated an increase in lung cancer survival since the time of diagnosis, but no reduction in lung cancer mortality. Whether this result necessarily indicates a lack of mortality benefit for screening remains controversial. A number of hypotheses have been proposed to explain the observed outcome, including over-diagnosis, screening sensitivity, and population heterogeneity (initial difference in lung cancer risks between the two trial arms). This study is intended to provide model-based testing for some of these important arguments.

METHOD

Using a micro-simulation model, the MISCAN-lung model, we explore the possible influence of screening sensitivity, systematic error, over-diagnosis and population heterogeneity.

RESULTS

Calibrating screening sensitivity, systematic error, or over-diagnosis does not noticeably improve the fit of the model, whereas calibrating population heterogeneity helps the model predict lung cancer incidence better.

CONCLUSIONS

Our conclusion is that the hypothesized imperfection in screening sensitivity, systematic error, and over-diagnosis do not in themselves explain the observed trial results. Model fit improvement achieved by accounting for population heterogeneity suggests a higher risk of cancer incidence in the intervention group as compared with the control group.