An under-used yet easily understood statistic: the number needed to treat (NNT)

Effect of alirocumab and evolocumab on all-cause mortality and major cardiovascular events: A meta-analysis focusing on the number needed to treat

AIMS

The efficacy of anti-proprotein convertase subtilisin/Kexin type 9 (PCSK9) monoclonal antibodies in patients with atherosclerotic cardiovascular disease (ASCVD) remains unclear. Therefore, this study aims to assess the effect of PCSK9 inhibitors (alirocumab and evolocumab) on ASCVD patients considering the number needed to treat (NNT).

METHODS

We reviewed randomized controlled trials (RCTs) which compared the effects of alirocumab or evolocumab and placebo or standards of care. All articles were published in English up to May 2022. Using random effect models, we estimated risk ratios (RRs), NNT, and 95% confidence intervals (CI).

RESULTS

We incorporated 12 RCTs with 53 486 patients total, of which 27 674 received PCSK9 inhibitors and 25 812 received placebos. The mean follow-up duration was 1.56 years. The effect of PCSK9 inhibitors on major adverse cardiovascular events (MACE) was statistically significant, and the corresponding mean NNT was 36. Alirocumab reduced the risk of MACE, stroke, and coronary revascularization; the corresponding mean NNT were 37, 319, and 107, respectively. Evolocumab positively affected MACE, myocardial infarction, stroke, and coronary revascularization; the corresponding mean NNT were 32, 78, 267, and 65, respectively. The effects of alirocumab or evolocumab on all-cause mortality and cardiovascular mortality were not statistically significant.

CONCLUSION

This study suggests that preventing one patient from MACE needed to treat 36 patients with ASCVD with PCSK9 inhibitors for 1.56 years. Both alirocumab and evolocumab reduced MACE, stroke, and coronary revascularization. Evolocumab had a positive effect on myocardial infarction, but no effects were noted for alirocumab. In addition, alirocumab may not be as effective as evolocumab. NNT visualizes the magnitude of efficacy to assist in clinical decisions.

SYSTEMATIC REVIEW REGISTRATION

[https://www.crd.york.ac.uk/PROSPERO/display_record.php?RecordID=344908], identifier [CRD42022344908].

Predictive validity performance indicators in violence risk assessment: a methodological primer

The predictive validity of violence risk assessments can be divided into two components: calibration and discrimination. The most common performance indicator used to measure the predictive validity of structured risk assessments, the area under the receiver operating characteristic curve (AUC), measures the latter component but not the former. As it does not capture how well a risk assessment tool's predictions of risk agree with actual observed risk, the AUC provides an incomplete portrayal of predictive validity. This primer provides an overview of calibration and discrimination performance indicators that measure global performance, performance in identifying higher-risk groups, and performance in identifying lower-risk groups. It is recommended that future research into the predictive validity of violence risk assessment tools includes a number of performance indicators that measure different facets of predictive validity and that the limitations of reported indicators be routinely explicated.

Using alternative statistical formats for presenting risks and risk reductions

BACKGROUND

The success of evidence-based practice depends on the clear and effective communication of statistical information.

OBJECTIVES

To evaluate the effects of using alternative statistical presentations of the same risks and risk reductions on understanding, perception, persuasiveness and behaviour of health professionals, policy makers, and consumers.

SEARCH STRATEGY

We searched Ovid MEDLINE (1966 to October 2007), EMBASE (1980 to October 2007), PsycLIT (1887 to October 2007), and the Cochrane Central Register of Controlled Trials (The Cochrane Library, 2007, Issue 3). We reviewed the reference lists of relevant articles, and contacted experts in the field.

SELECTION CRITERIA

We included randomized and non-randomized controlled parallel and cross-over studies. We focused on four comparisons: a comparison of statistical presentations of a risk (eg frequencies versus probabilities) and three comparisons of statistical presentation of risk reduction: relative risk reduction (RRR) versus absolute risk reduction (ARR), RRR versus number needed to treat (NNT), and ARR versus NNT.

DATA COLLECTION AND ANALYSIS

Two authors independently selected studies for inclusion, extracted data, and assessed risk of bias. We contacted investigators to obtain missing information. We graded the quality of evidence for each outcome using the GRADE approach. We standardized the outcome effects using adjusted standardized mean difference (SMD).

MAIN RESULTS

We included 35 studies reporting 83 comparisons. None of the studies involved policy makers. Participants (health professionals and consumers) understood natural frequencies better than probabilities (SMD 0.69 (95% confidence interval (CI) 0.45 to 0.93)). Compared with ARR, RRR had little or no difference in understanding (SMD 0.02 (95% CI -0.39 to 0.43)) but was perceived to be larger (SMD 0.41 (95% CI 0.03 to 0.79)) and more persuasive (SMD 0.66 (95% CI 0.51 to 0.81)). Compared with NNT, RRR was better understood (SMD 0.73 (95% CI 0.43 to 1.04)), was perceived to be larger (SMD 1.15 (95% CI 0.80 to 1.50)) and was more persuasive (SMD 0.65 (95% CI 0.51 to 0.80)). Compared with NNT, ARR was better understood (SMD 0.42 (95% CI 0.12 to 0.71)), was perceived to be larger (SMD 0.79 (95% CI 0.43 to 1.15)).There was little or no difference for persuasiveness (SMD 0.05 (95% CI -0.04 to 0.15)). The sensitivity analyses including only high quality comparisons showed consistent results for persuasiveness for all three comparisons. Overall there were no differences between health professionals and consumers. The overall quality of evidence was rated down to moderate because of the use of surrogate outcomes and/or heterogeneity. None of the comparisons assessed behaviourbehaviour.

AUTHORS' CONCLUSIONS

Natural frequencies are probably better understood than probabilities. Relative risk reduction (RRR), compared with absolute risk reduction (ARR) and number needed to treat (NNT), may be perceived to be larger and is more likely to be persuasive. However, it is uncertain whether presenting RRR is likely to help people make decisions most consistent with their own values and, in fact, it could lead to misinterpretation. More research is needed to further explore this question.