Statistics are used to evaluate diagnostic tests or predictive models, but often from these calculations, we do not understand whether the model or test could be useful or harmful in clinical practice.

Net benefit is a type of decision making analysis, with benefits and harms put on the same scale so that they can be compared directly1. More specifically, the European Federation of Pharmaceutical Industries and Associations (EFPIA) defined Net Clinical Benefit as “a quantitative framework that compares the time-course overall change in the benefits and risks of a drug over a comparator. Net Clinical Benefit is the sum of the change in expected benefits minus the change in expected risks as a result of treatment. The benefits and risks must be placed on a common scale, such as using the health-state related utilities. The expected benefit is calculated by multiplying the benefit, assuming it is realised by the patient, by the probability of its being realised, with a similar calculation for expected risks”2.

The Net Clinical Benefit framework is composed by different steps:

  • Definition of problem and data sources: clinicians have to focus on issues related to the benefit-risk assessment, including the purpose and context of the assessment. Moreover, data sources and evidences must be identified for the benefit-risk assessment analysis2.
  • Estimate the Net Clinical Benefit: data are evaluated, quantifying the magnitude of benefits and risks. Different methodologies for analysis include metric indices which provide numerical representations of benefits and risks (Number Needed to Treat (NNT) / Number Needed to Harm (NNH), Impact numbers), quantitative frameworks which model benefit-risk trade-off and balance benefits and risks (Multi-Criteria Decision Analysis (MCDA), Stochastic Multi-criteria Acceptability Analysis (SMAA)), and utility survey techniques which elicit stakeholders’ preference information (Discrete Choice Experiment (DCE))2.
    Data analyses are then visualized with line graph and distribution plot to evaluate whether clinical use of prediction models or diagnostic tests are useful or harmful in clinical practice.
  • Conclusion: on the base of the benefit-risk assessment results, a decision-making conclusion is reached.

Net Clinical Benefit is a useful evaluating tool for risk-benefit analysis that could be applied to accept or reject a hypothesis that support the use of an intervention in specific circumstances. However, more studies of the are needed to understand how benefit-risk assessment can lead to better health care decision strategies.

In vascular patients, arterial (i.e. peripheral arterial disease, PAD, and critical limb ischemia, CLI) and venous (i.e. venous thromboembolism, VTE) Net Clinical Benefit has become in recent years a common risk-benefit analysis tool for drug therapy decision making in time-course treatment. In details, ischemic/thrombotic events (major adverse cardiovascular events, MACE, major adverse limb events, MALE; VTE) prevention benefits and bleeding (major bleeding, MB/clinically relevant non-major bleeding, CRNMB) harms are taken in account for clinical decision. It is noteworthy how Net Clinical Benefit changes in vascular patients during time-course antithrombotic therapy due to Case Fatality Rate (CFR) sharp drop in recurrent deep vein thrombosis (DVT) events in comparison with constant CRF in major bleedings3, 4.

That’s why COMPASS therapeutic option (low dosage direct oral anticoagulants + acetylsalicylic acid) in severe PAD patients and SURVET option (sulodexide) in high bleeding risk VTE patients are becoming therapeutic route of choice5.

References

  1. Vickers AJ, Van Calster B, Steyerberg EW. Net benefit approaches to the evaluation of prediction models, molecular markers, and diagnostic tests. BMJ. 2016;352:i6. doi:10.1136/bmj.i6
  2. PROTECT Benefit-Risk. Accessed August 30, 2021. https://protectbenefitrisk.eu/netclinicalbenefit.html
  3. Lecumberri R, Alfonso A, Jiménez D, et al. Dynamics of case-fatalilty rates of recurrent thromboembolism and major bleeding in patients treated for venous thromboembolism. Thromb Haemost. 2013;110(4):834-843. doi:10.1160/TH13-02-0132
  4. Tomkowski W, Kuca P, Urbanek T, et al. Żylna choroba zakrzepowo-zatorowa — wytyczne profilaktyki, diagnostyki i terapii Konsensus Polski 2017. Acta Angiologica. 2017;23(2):73-113.
  5. Steffel J, Eikelboom JW, Anand SS, Shestakovska O, Yusuf S, Fox KAA. The COMPASS Trial: Net Clinical Benefit of Low-Dose Rivaroxaban Plus Aspirin as Compared With Aspirin in Patients With Chronic Vascular Disease. Circulation. 2020;142(1):40-48. doi:10.1161/CIRCULATIONAHA.120.046048