The Healthy Participant Effect: insights and results from a population-based case-control study on breast cancer.

Agreement to participate in case-control studies has become low. Healthy participant bias resulting from differential response proportions in cases and controls can distort results; however, the magnitude of bias is difficult to assess. We investigated the effect in a large population-based case-control study on breast cancer, with a participation rate of 43.4% and 64.1% for controls and cases. We performed a mortality follow-up in 2020 for 3,813 cases and 7,335 controls recruited between 2002-2005. Standardized mortality ratios (SMR) for overall mortality and selected causes of death were estimated. The mean age at recruitment was 63.1 years. The overall mortality for controls was 0.66 times lower (95%CI 0.62-0.69) than for the reference population. For causes of death other than breast cancer, SMRs were similar in cases and controls (0.70 and 0.64). Higher education was associated with lower SMRs in both cases and controls. Options for adjusting the healthy participant bias are limited if the true risk factor distribution in the underlying population is unknown. However, a relevant bias in this particular case-control study is considered unlikely since a similar healthy participant effect was observed for both controls and cases.

The impact of cardiovascular disease on all-cause and cancer mortality: results from a 16-year follow-up of a German breast cancer case-control study.

BACKGROUND: Cardiovascular disease (CVD) is the leading cause of death worldwide. The aim of this study was to examine if CVD affects the mortality of women after a breast cancer diagnosis and population controls differently. METHODS: The analysis included a total of 3,555 women, diagnosed with primary stage 1-3 breast cancer or in situ carcinoma between 2002 and 2005 and 7,334 controls breast cancer-free at recruitment, all aged 50-74 years, who were followed-up in a German breast cancer case-control study until June, 30 2020. Kaplan-Meier and cumulative incidence function were calculated for all-cause mortality and mortality from any cancer, stratified for case-control status and CVD, separately for women aged < 65 and ≥ 65 years. Cox regression and Fine-Gray subdistribution hazard models were used to estimate hazard ratios (HR) and 95% confidence intervals (95% CI) for the association between case-control-status, CVD and mortality from all causes/any cancer. RESULTS: The median follow-up was 16.1 years. In total, 1,172 cases (33.0%) and 1,401 initial controls (19.1%) died. CVD prevalence at recruitment was 15.2% in cases and controls. Cases with CVD had the highest and controls without CVD the lowest mortality during the entire observation period in both age groups (< 65 and ≥ 65 years). CVD was identified as a risk factor for all-cause mortality in both cases and controls aged < 65 years (HR 1.22, 95%CI 0.96-1.55 and HR 1.79, 95%CI 1.43-2.24) as well as at ages of ≥ 65 years (HR 1.44, 95%CI 1.20-1.73 and HR 1.59, 95%CI 1.37-1.83). A significant association of CVD and cancer mortality was found only for cases aged ≥ 65 years. CONCLUSION: CVD was significantly associated with all-cause mortality of both cases and controls and CVD was identified as a risk factor for cancer mortality of cases aged ≥ 65 years at recruitment. Therefore, attention should be paid on monitoring and preventing CVD in breast cancer patients, especially in those diagnosed at older ages.

Cross-sectional survey on researchers' experience in using accelerometers in health-related studies.

Objectives: Accelerometers are widely applied in health studies, but lack of standardisation regarding device placement, sampling and data processing hampers comparability between studies. The objectives of this study were to assess how accelerometers are applied in health-related research and problems with accelerometer hardware and software encountered by researchers. Methods: Researchers applying accelerometry in a health context were invited to a cross-sectional web-based survey (August 2020-September 2020). The questionnaire included quantitative questions regarding the application of accelerometers and qualitative questions on encountered hardware and software problems. Descriptive statistics were calculated for quantitative data and content analysis was applied to qualitative data. Results: In total, 116 health researchers were included in the study (response: 13.7%). The most used brand was ActiGraph (67.2%). Independently of brand, the main reason for choosing a device was that it was the standard in the field (57.1%-83.3%). In children and adolescent populations, sampling frequency was higher (mean: 73.3 Hz ±29.9 Hz vs 47.6 Hz ±29.4 Hz) and epoch length (15.0s±15.6s vs 30.1s±25.9s) and non-wear time (42.9 min ±23.7 min vs 65.3 min ±35.4 min) were shorter compared with adult populations. Content analysis revealed eight categories of hardware problems (battery problems, compliance issues, data loss, mechanical problems, electronic problems, sensor problems, lacking waterproofness, other problems) and five categories of software problems (lack of user-friendliness, limited possibilities, bugs, high computational burden, black box character). Conclusions: The study confirms heterogeneity regarding accelerometer use in health-related research. Moreover, several hardware and software problems were documented. Both aspects must be tackled to increase validity, practicability and comparability of research.