Contextual factors in shared decision making: a randomised controlled trial in women with a strong suspicion of breast cancer

Decision aids in North American breast cancer outpatients have been shown to assist with treatment decision making and reduce decisional conflict. To date, appropriate delivery formats to effectively increase patient participation in newly diagnosed breast cancer inpatients have not been investigated in the context of German health care provision. The impact of a decision aid intervention was studied in patients (n=111) with a strong suspicion of breast cancer in a randomised controlled trial. The primary outcome variable was decisional conflict. Participants were followed up 1 week post-intervention with a retention rate of 92%. Analyses revealed that the intervention group felt better informed (ηp2=0.06) but did not experience an overall reduction in decisional conflict as compared with the control group. The intervention had no effect on uptake rates of treatment options, length of consultation with the surgeon, time point of treatment decision making, perceived involvement in decision making, neither decision related nor general patient satisfaction. Patients who received the decision aid intervention experienced a small benefit with regards to how informed they felt about advantages and disadvantages of relevant treatment options. Results are discussed in terms of contextual factors and individual differences as moderators of treatment decision aid effectiveness

Erratum to: Methods for evaluating medical tests and biomarkers

[This corrects the article DOI: 10.1186/s41512-016-0001-y.]

Erratum to: Methods for evaluating medical tests and biomarkers

[This corrects the article DOI: 10.1186/s41512-016-0001-y.]

Evidence synthesis to inform model-based cost-effectiveness evaluations of diagnostic tests: a methodological systematic review of health technology assessments

Background: Evaluations of diagnostic tests are challenging because of the indirect nature of their impact on patient outcomes. Model-based health economic evaluations of tests allow different types of evidence from various sources to be incorporated and enable cost-effectiveness estimates to be made beyond the duration of available study data. To parameterize a health-economic model fully, all the ways a test impacts on patient health must be quantified, including but not limited to diagnostic test accuracy. Methods: We assessed all UK NIHR HTA reports published May 2009-July 2015. Reports were included if they evaluated a diagnostic test, included a model-based health economic evaluation and included a systematic review and meta-analysis of test accuracy. From each eligible report we extracted information on the following topics: 1) what evidence aside from test accuracy was searched for and synthesised, 2) which methods were used to synthesise test accuracy evidence and how did the results inform the economic model, 3) how/whether threshold effects were explored, 4) how the potential dependency between multiple tests in a pathway was accounted for, and 5) for evaluations of tests targeted at the primary care setting, how evidence from differing healthcare settings was incorporated. Results: The bivariate or HSROC model was implemented in 20/22 reports that met all inclusion criteria. Test accuracy data for health economic modelling was obtained from meta-analyses completely in four reports, partially in fourteen reports and not at all in four reports. Only 2/7 reports that used a quantitative test gave clear threshold recommendations. All 22 reports explored the effect of uncertainty in accuracy parameters but most of those that used multiple tests did not allow for dependence between test results. 7/22 tests were potentially suitable for primary care but the majority found limited evidence on test accuracy in primary care settings. Conclusions: The uptake of appropriate meta-analysis methods for synthesising evidence on diagnostic test accuracy in UK NIHR HTAs has improved in recent years. Future research should focus on other evidence requirements for cost-effectiveness assessment, threshold effects for quantitative tests and the impact of multiple diagnostic tests