Determinants of (non-)attendance at the Dutch cancer screening programmes: A systematic review.

OBJECTIVE: The Netherlands host three population-based cancer screening programmes: for cervical, breast, and colorectal cancer. For screening programmes to be effective, high participation rates are essential, but participation in the Netherlands' programmes is starting to fall below the minimal effective rate. We aimed to produce a systematic overview of the current known determinants of (non-)attendance at the Dutch cancer screening programmes. METHODS: A literature search was conducted in the electronic databases Academic Search Premier, Cochrane Library, Embase, EMCare, PubMed, PsycINFO, Web of Science, and also in grey literature, including all articles published before February 2018. The I-Change model was used to categorize the identified determinants of cancer screening attendance. RESULTS: In total, 19/1232 identified studies and 6 grey literature reports were included. Fifteen studies reported on predisposing factors. Characteristics such as social economic status, country of birth, and residency were most often reported, and correlate with cancer screening attendance. Thirteen studies addressed information factors. Factors on awareness, motivation, ability, and barriers were less often studied. CONCLUSION: Current studies tend to describe the general characteristics of (non-)attendance and (non-)attenders, but rarely provide in depth information on other factors of (non-)participation. The I-Change model proved to be a useful tool in mapping current knowledge on cancer screening attendance and revealed knowledge gaps regarding determinants of (non-)participation in the screening programmes. More research is needed to fully understand determinants of participation, in order to influence and optimize attendance rates over the long term.

Post-study therapy as a source of confounding in survival analysis of first-line studies in patients with advanced non-small-cell lung cancer.

Clinical trials exploring the long-term effects of first-line therapy in patients with advanced non-small-cell lung cancer generally disregard subsequent treatment although most patients receive second and third-line therapies. The choice of further therapy depends on critical intermediate events such as disease progression and it is usually left at the physician's discretion. Time-dependent confounding may then arise with standard survival analyses producing biased effect estimates, even in randomized trials. Herein we describe the concept of time-dependent confounding in detail and discuss whether the response to first-line treatment may be a potential time-dependent confounding factor for survival in the context of subsequent therapy. A prospective observational study of 406 patients with advanced non-small-cell lung cancer served as an example base. There is evidence that time-dependent confounding may occur in multivariate survival analysis after first-line therapy when disregarding subsequent treatment. In the light of this important but underestimated aspect some of the large and meaningful recent clinical first-line lung cancer studies are discussed, focussing on subsequent treatment and its potential impact on the survival of the study patients. No recently performed lung cancer trial applied adequate statistical analyses despite the frequent use of subsequent therapies. In conclusion, effect estimates from standard survival analysis may be biased even in randomized controlled trials because of time-dependent confounding. To adequately assess treatment effects on long-term outcomes appropriate statistical analyses need to take subsequent treatment into account.