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Table 2 Two examples of differences in conclusions with regard to how patient-level characteristics modify treatment effect

From: A systematic review of individual patient data meta-analyses on surgical interventions

Example Description
Effectiveness of coronary artery bypass grafting vs. percutaneous coronary interventions for multivessel disease. A two-step meta-analysis of individual patient data from 7,812 patients included in 10 randomized trials comparing coronary artery bypass grafting (CABG) and percutaneous coronary intervention (PCI) in patients with multivessel coronary artery disease, showed a similar overall treatment effect on long-term mortality after CABG and PCI [20]. However, in diabetic patients mortality was substantially lower in the CABG group than in the PCI group (HR 0.70, 95% CI 0.56-0.87). Mortality was similar between groups in patients without diabetes (HR 0.98, 95% CI 0.86-1.12; P=0.01 for interaction). Patient age modified the effect of treatment on mortality with hazard ratios of 1.25 (95% CI 0.94-1.66) in patients aged <55 years, 0.90 (95% CI 0.75-1.09) in patients aged 55–64 years, and 0.82 (95% CI 0.70-0.97) in patients aged ≥65 years (P=0.002 for interaction). Treatment effect was not modified by other subgroups. CABG might be a better option for patients aged ≥65 years and patients with diabetes since mortality was found to be lower in these subgroups. These results have been implemented in clinical guidelines [41].
Effectiveness of routine vs. selective invasive strategy in patients with non-ST-segment elevation acute coronary syndrome. An individual patient data meta-analysis of three randomized trials of routine versus selective invasive strategies in patients with non-ST-segment elevation acute coronary syndrome showed that a routine invasive strategy resulted in significantly less cardiovascular deaths (CV deaths) or non-fatal myocardial infarctions (MIs) compared to selective invasive strategies [30]. The authors used patient’s baseline characteristics to develop a multivariable risk prediction model. A simplified integer risk score was derived from the risk prediction model to predict a patient’s 5-year probability of CV death or MI, and the patients were categorized into three risk groups (low, intermediate, and high risk).
The treatment effect was similar between groups in patients with low-risk (HR 0.80 (95% CI 0.63-1.02)) and intermediate-risk (HR 0.81 (95% CI 0.66-1.01)) scores. In patients with high-risk scores treatment favored routine over selective invasive strategies (HR 0.68 (95% CI 0.53-0.86)). There were 2.0% (95% CI −4.1-0.1%) and 3.8% (95% CI −7.4- -0.1%) absolute risk reductions in CV death or MI in the low- and intermediate-risk groups and an 11.1% (95% CI −18.4- -3.8%) absolute risk reduction in the highest-risk patients. The multivariable risk prediction model has not yet been implemented in clinical guidelines.