METHODS: We reanalyzed the empirical data from the Health Insurance Plan trial in 1963 to the UK age trial in 1991 and their follow-up data published until 2015. We first performed Bayesian conjugated meta-analyses on the heterogeneity of attendance rate, sensitivity, and over-detection and their impacts on advanced stage breast cancer and death from breast cancer across trials using Bayesian Poisson fixed- and random-effect regression model. Bayesian meta-analysis of causal model was then developed to assess a cascade of causal relationships regarding the impact of both attendance and sensitivity on 2 main outcomes.
RESULTS: The causes of heterogeneity responsible for the disparities across the trials were clearly manifested in 3 components. The attendance rate ranged from 61.3% to 90.4%. The sensitivity estimates show substantial variation from 57.26% to 87.97% but improved with time from 64% in 1963 to 82% in 1980 when Bayesian conjugated meta-analysis was conducted in chronological order. The percentage of over-detection shows a wide range from 0% to 28%, adjusting for long lead-time. The impacts of the attendance rate and sensitivity on the 2 main outcomes were statistically significant. Causal inference made by linking these causal relationships with emphasis on the heterogeneity of the attendance rate and sensitivity accounted for the variation in the reduction of advanced breast cancer (none-30%) and of mortality (none-31%). We estimated a 33% (95% CI: 24-42%) and 13% (95% CI: 6-20%) breast cancer mortality reduction for the best scenario (90% attendance rate and 95% sensitivity) and the poor scenario (30% attendance rate and 55% sensitivity), respectively.
CONCLUSION: Elucidating the scenarios from high to low performance and learning from the experiences of these trials helps screening policy-makers contemplate on how to avoid errors made in ineffective studies and emulate the effective studies to save women lives.
DESIGN: This qualitative study employed an interpretive descriptive approach. Two trained researchers conducted in-depth interviews (IDIs) and focus group discussions (FGDs) using a semi-structured topic guide, which was developed based on literature review and behavioural theories. All IDIs and FGDs were audio-recorded and transcribed verbatim. Two researchers analysed the data independently using a thematic approach.
PARTICIPANTS AND SETTING: Men working in a banking institution in Kuala Lumpur were recruited to the study. They were purposively sampled according to their ethnicity, job position, age and screening status in order to achieve maximal variation.
RESULTS: Eight IDIs and five FGDs were conducted (n=31) and six themes emerged from the analysis. (1) Young men did not consider screening as part of prevention and had low risk perception. (2) The younger generation was more receptive to health screening due to their exposure to health information through the internet. (3) Health screening was not a priority in young men except for those who were married. (4) Young men had limited income and would rather invest in health insurance than screening. (5) Young men tended to follow doctors' advice when it comes to screening and preferred doctors of the same gender and ethnicity. (6) Medical overuse was also raised where young men wanted more screening tests while doctors tended to promote unnecessary screening tests to them.
CONCLUSIONS: This study identified important factors that influenced young men's screening behaviour. Health authorities should address young men's misperceptions, promote the importance of early detection and develop a reasonable health screening strategy for them. Appropriate measures must be put in place to reduce low value screening practices.