Literature DB >> 34027506

COVID-19 vaccines: effectiveness and number needed to treat.

Luis C L Correia1, Denise Matias1.   

Abstract

Entities:  

Mesh:

Substances:

Year:  2021        PMID: 34027506      PMCID: PMC8121500          DOI: 10.1016/S2666-5247(21)00119-1

Source DB:  PubMed          Journal:  Lancet Microbe        ISSN: 2666-5247


× No keyword cloud information.
In a Lancet Microbe Comment, Piero Olliaro and colleagues suggest that reporting relative risk reduction (RRR) for vaccination does not reflect entirely its therapeutic performance and consider the solw use of RRR a reporting bias. In addition, they propose that absolute risk reduction (ARR) should be reported as a measure of the vaccine's effectiveness. The authors end up comparing the numbers needed to vaccinate to prevent one case of COVID-19 among the vaccines, which derives from the absolute reductions. However, this suggestion might have a paradoxical effect in misleading perception of treatment performance. This approach disregards three epidemiological facts. First, number needed to treat (NNT) is not an intrinsic property of a treatment, it is rather a property of the population that receives a treatment: for a constant relative risk reduction, populations of different baseline risks will have different absolute reductions. Therefore, NNT comparison of different treatments across studies should be avoided, because sample populations will always have baseline risk variations. Indeed, this approach is the actual reporting bias. Second, the authors raise a concern that different levels of background risk might change relative risk reduction of studies. This statement disregards the constant property of relative risk repeatedly demonstrated by subgroup analysis of clinical trials and meta-scientific evaluations of a treatment across studies of different baseline risks. For example, statins,3, 4 anti-hypertensive therapy, and aspirin have the same relative risk reduction across the baseline risks of primary or secondary prevention. Finally, effectiveness—a real-world property—is about clinical decision making, and not to be derived from efficacy studies (randomised controlled studies). As a clinician or an epidemiologist, one should multiply the RRR (intrinsic property of a treatment) by the baseline risk of a given population or patient, individualising the ARR and NNT. They are not scientific concepts, they are circumstantial information. We declare no competing interests.
  6 in total

1.  Can we individualize the 'number needed to treat'? An empirical study of summary effect measures in meta-analyses.

Authors:  Toshiaki A Furukawa; Gordon H Guyatt; Lauren E Griffith
Journal:  Int J Epidemiol       Date:  2002-02       Impact factor: 7.196

2.  Impact of Cardiovascular Risk on the Relative Benefit and Harm of Intensive Treatment of Hypertension.

Authors:  Robert A Phillips; Jiaqiong Xu; Leif E Peterson; Ryan M Arnold; Joseph A Diamond; Adam E Schussheim
Journal:  J Am Coll Cardiol       Date:  2018-03-07       Impact factor: 24.094

3.  Cholesterol Lowering in Intermediate-Risk Persons without Cardiovascular Disease.

Authors:  Salim Yusuf; Jackie Bosch; Gilles Dagenais; Jun Zhu; Denis Xavier; Lisheng Liu; Prem Pais; Patricio López-Jaramillo; Lawrence A Leiter; Antonio Dans; Alvaro Avezum; Leopoldo S Piegas; Alexander Parkhomenko; Katalin Keltai; Matyas Keltai; Karen Sliwa; Ron J G Peters; Claes Held; Irina Chazova; Khalid Yusoff; Basil S Lewis; Petr Jansky; Kamlesh Khunti; William D Toff; Christopher M Reid; John Varigos; Gregorio Sanchez-Vallejo; Robert McKelvie; Janice Pogue; Hyejung Jung; Peggy Gao; Rafael Diaz; Eva Lonn
Journal:  N Engl J Med       Date:  2016-04-02       Impact factor: 91.245

4.  COVID-19 vaccine efficacy and effectiveness-the elephant (not) in the room.

Authors:  Piero Olliaro; Els Torreele; Michel Vaillant
Journal:  Lancet Microbe       Date:  2021-04-20

5.  Aspirin in the primary and secondary prevention of vascular disease: collaborative meta-analysis of individual participant data from randomised trials.

Authors:  Colin Baigent; Lisa Blackwell; Rory Collins; Jonathan Emberson; Jon Godwin; Richard Peto; Julie Buring; Charles Hennekens; Patricia Kearney; Tom Meade; Carlo Patrono; Maria Carla Roncaglioni; Alberto Zanchetti
Journal:  Lancet       Date:  2009-05-30       Impact factor: 79.321

6.  MRC/BHF Heart Protection Study of cholesterol lowering with simvastatin in 20,536 high-risk individuals: a randomised placebo-controlled trial.

Authors: 
Journal:  Lancet       Date:  2002-07-06       Impact factor: 79.321

  6 in total
  2 in total

1.  COVID-19 vaccines: effectiveness and number needed to treat - Authors' reply.

Authors:  Piero Olliaro; Els Torreele; Michel Vaillant
Journal:  Lancet Microbe       Date:  2021-05-14

Review 2.  Updated Recommendations on Cardiovascular Prevention in 2022: An Executive Document of the Italian Society of Cardiovascular Prevention.

Authors:  Massimo Volpe; Giovanna Gallo; Maria Grazia Modena; Claudio Ferri; Giovambattista Desideri; Giuliano Tocci
Journal:  High Blood Press Cardiovasc Prev       Date:  2022-01-13
  2 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.