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Analysis 1.1. Comparison 1 NI versus placebo for prophylaxis, Outcome 1 Influenza-like illness.. .. .. .. Analysis 1.2. Comparison 1 NI versus placebo for prophylaxis, Outcome 2 Influenza (symptomatic).. .. .. . Analysis 1.3. Comparison 1 NI versus placebo for prophylaxis, Outcome 3 Influenza (symptomatic and asymptomatic). Analysis 1.4. Comparison 1 NI versus placebo for prophylaxis, Outcome 4 Influenza (asymptomatic).. .. .. Analysis 1.5. Comparison 1 NI versus placebo for prophylaxis, Outcome 5 Adverse events-nausea.. .. .. . Analysis 1.6. Comparison 1 NI versus placebo for prophylaxis, Outcome 6 Adverse events-vomiting.. .. .. Analysis 1.7. Comparison 1 NI versus placebo for prophylaxis, Outcome 7 Adverse events-diarrhoea.. .. .. Analysis 1.8. Comparison 1 NI versus placebo for prophylaxis, Outcome 8 Adverse events-abdominal pain.. .. Analysis 1.9. Comparison 1 NI versus placebo for prophylaxis, Outcome 9 Adverse events-others.. .. .. .

On the 12th Day of Christmas, a Statistician Sent to Me . . . The BMJ's statistical editors relish a quiet Christmas, so make their wish come true and pay attention to the list of common statistical faux pas presented here by Riley and colleagues

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Background: Ovarian cancer (OC) is a diagnostic challenge, with the majority diagnosed at late stages. Existing systematic reviews of diagnostic models either use inappropriate meta-analytic methods or do not conduct statistical comparisons of models or stratify test performance by menopausal status. Methods: We searched CENTRAL, MEDLINE, EMBASE, CINAHL, CDSR, DARE, Health Technology Assessment Database and SCI Science Citation Index, trials registers, conference proceedings from 1991 to June 2019. Cochrane collaboration review methods included QUADAS-2 quality assessment and meta-analysis using hierarchical modelling. RMI, ROMA or ADNEX at any test positivity threshold were investigated. Histology or clinical follow-up was the reference standard. We excluded screening studies, studies restricted to pregnancy, recurrent or metastatic OC. 2 × 2 diagnostic tables were extracted separately for pre- and post-menopausal women. Results: We included 58 studies (30,121 patients, 9061 cases of ovarian cancer). Prevalence of OC ranged from 16 to 55% in studies. For premenopausal women, ROMA at a threshold of 13.1 (+/−2) and ADNEX at a threshold of 10% demonstrated significantly higher sensitivity compared to RMI I at 200 (p < 0.0001) 77.8 (72.5, 82.4), 94.9 (92.5, 96.6), and 57.1% (50.6 to 63.4) but lower specificity (p < 0.002), 92.5 (90.0, 94.4), 84.3 (81.3, 86.8), and 78.2 (75.8, 80.4). For postmenopausal women, ROMA at a threshold of 27.7 (+/−2) and AdNEX at a threshold of 10% demonstrated significantly higher sensitivity compared to RMI I at a threshold of 200 (p < 0.001) 90.4 (87.4, 92.7), 97.6 (96.2, 98.5), and 78.7 (74.3, 82.5), specificity of ROMA was comparable, whilst ADneX was lower, 85.5 (81.3, 88.9), 81.3 (76.9, 85.0) (p = 0.155), compared to RMI 55.2 (51.2, 59.1) (p < 0.001). Conclusions: In pre-menopausal women, ROMA and ADNEX offer significantly higher sensitivity but significantly decreased specificity. In post-menopausal women, ROMA demonstrates significantly higher sensitivity and comparable specificity to RMI I, ADNEX has the highest sensitivity of all models, but with significantly reduced specificity. RMI I has poor sensitivity compared to ROMA or ADNEX. Choice between ROMA and ADNEX as a replacement test will depend on cost effectiveness and resource implications.