Population Data to Measure Mortality Reductions Produced by Organized Cancer Screening: Analyze with Care

• Activity Number: 76
• Type: Contributed
• Date/Time: Sunday, August 9, 2015 : 4:00 PM to 5:50 PM
• Sponsor: Section on Statistics in Epidemiology
• Author(s): James A. Hanley* and Harald Weedon-Fekjaer and Ailish Hannigan and Olli Saarela
• Companies: McGill University and University of Oslo and University of Limerick and University of Toronto
• Keywords: underestimation ; target of screening ; delayed impact ; non-proportional hazards ; conditional ; matching

Abstract

Although many of the trials were carried out decades ago, and did not necessarily produce valid or precise estimates of the reductions that might be expected from a sustained screening program, data from randomized cancer screening trials are still relied on by many task forces.

Increasingly, the focus is on non-experimental evidence, i.e. data from populations where organized screening programs have been introduced.

In the evaluation of the impact of such programs, before-after comparisons of cancer mortality rates need to take account of concomitant improvements in cancer care over these same decades. Time-, age- and place-matched comparisons, and attention to which deaths could/could not be averted by the screening program, are essential for valid estimates of benefit.

Using organized population-based programs of mammography screening for breast cancer as an example, we show that by ignoring these issues, many of the prevailing statistical approaches to the analysis of such population-based data underestimate the mortality reductions produced by these programs. Statistical approaches that can deal with these 'dilutions' will be described.