Skip to content
New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

New Paper (Vaccine): Plausibility of Claimed Covid-19 Vaccine Efficacies by Age: A Simulation Study #1158

Open
2 of 32 tasks
agitter opened this issue Jun 21, 2022 · 0 comments

Comments

@agitter
Copy link
Collaborator

agitter commented Jun 21, 2022

Title: Plausibility of Claimed Covid-19 Vaccine Efficacies by Age: A Simulation Study

Please paste a link to the paper or a citation here:

Link: https://doi.org/10.1097/MJT.0000000000001528

What is the paper's Manubot-style citation?

Citation: doi:10.1097/MJT.0000000000001528

Please list some keywords (3-10) that help identify the relevance of this paper to COVID-19

  • Sputnik V vaccine
  • simulation

Please note the publication / review status

  • Pre-print
  • New Peer-Reviewed Paper
  • Peer-Reviewed Paper Pre-2020

Which areas of expertise are particularly relevant to the paper?

  • virology
  • epidemiology
  • biostatistics
  • immunology
  • pharmacology

Questions to answer about each paper:

Please provide 1-2 sentences introducing the study and its main findings

The distribution of alleged vaccine efficacies of the Sputnik vaccine by age in the phase-III trial is very unlikely to occur in genuine experimental data, even if the number of patients recruited, vaccine efficacy, and overall infection rate are true and there is no underlying difference in vaccine efficacy by age.

Study question(s) being investigated:

How many/what drugs/combinations are being considered?

What are the main hypotheses being tested?

Study population:

What is the model system (e.g., human study, animal model, cell line study)?

What is the sample size? If multiple groups are considered, give sample size for each group (including controls).

  • number treated with treatment A
  • number treated with treatment B

For human studies:

What countries/regions are considered?
What is the age range, gender, other relevant characteristics?
What is the setting of the study (random sample of school children, inpatient, outpatient, etc)?
What other specific inclusion-exclusion criteria are considered?

For example, do the investigators exclude patients with diagnosed neoplasms or patients over/under a certain age?

Treatment assignment:

How are treatments assigned?

For example, is it an interventional or an observational study?

Is the study randomized?

A study can be interventional but not randomized (e.g., a phase I or II clinical trial is interventional but often not randomized).

Provide other relevant details about the design.

This includes possible treatment stratification (e.g., within litters for animal studies, within hospitals for human studies), possible confounding variables (e.g., having a large age range of individuals), possible risks of bias and how they are addressed (e.g., is there masking in a clinical trial? how are individuals chosen in an observational study?).

Outcome Assessment:

Describe the outcome that is assessed and whether it is appropriate.

For example: Is the outcome assessed by a clinician or is it self-reported?
Is the outcome based on viral load or a functional measurement (e.g., respiratory function, discharge from hospital)?
What method is used to measure the outcome?
How long after a treatment is the outcome measured?

Are outcome measurements complete?

For example, are there individuals lost to follow up?

Are outcome measurements subject to various kinds of bias?

For example, a lack of masking in randomized clinical trials.

Statistical Methods Assessment:

What methods are used for inference?

For example, logistic regression, nonparametric methods.

Are the methods appropriate for the study?

For example, are clustered data treated independently or are clusters adjusted for, such as different hospitals or litters?

Are adjustments made for possible confounders?

For example, adjustment for age, sex, or comorbidities.

Results Summary:

What is the estimated association?

For example, is it an estimated odds ratio, a median difference in detected cases, etc?

What measures of confidence or statistical significance are provided?

For example, confidence intervals, p-values, and/or Bayes factors.

Interpretation of results for study population:

Can we make a causal interpretation for the individuals in the study of drug -> outcome, such as "taking drug A improves likelihood of survival twofold over taking drug B."

For example, with a well-performed animal study or randomized trial it is often possible to infer causality.
If is an observational study, does it match up with some of the Bradford Hill criteria? https://www.edwardtufte.com/tufte/hill https://en.wikipedia.org/wiki/Bradford_Hill_criteria

Are there identified side effects or interactions with other drugs?

For example, is the treatment known to cause liver damage or to not be prescribed for individuals with certain comorbities?

Are there specific subgroups with different findings?

For example, do individuals with a specific baseline seem to do particularly well? Be particularly cautious with respect to multiple testing here.

Extrapolation of conclusions to other groups of individuals not specifically included in the study:

If the study is an animal study, which animal and how relevant is that model?

Is the model system appropriate? Is there evidence from past use that it's highly-relevant to therapeutic design in this context?

If it is a human study, what characteristics of the study population may support/limit extrapolation?

  • Can results extrapolate easily to other similar groups? (e.g., same country, similar age groups)
  • What would happen if conditions are extended in terms of dose or duration?
  • Can results be extrapolated to other populations or in very different settings? (e.g., different age group, primary care setting vs emergency department etc)

Summary of reliability

1-2 sentences on concluding remarks, including summary of strengths, weaknesses, limitations.

Progress

Check off the components as they are completed. If the component is not applicable, check the box as well.

  • 1-2 sentences introducing the study and its main findings
  • Describe How many/what drugs/combinations are being considered
  • Describe the model system
  • What is the sample size?
  • What countries/regions are considered
  • What is the age range, gender, other relevant characteristics
  • Describe study setting
  • Describe other specific inclusion-exclusion criteria
  • Describe how treatments are assigned
  • Describe randomization (or not) and other relavent details about the design
  • Describe the outcome that is assessed and whether it is appropriate.
  • Describe whether the outcome measurements are complete
  • Are outcome measurements subject to various kinds of bias?
  • Describe methods used for inference
  • Describe whether the methods are appropriate for the study
  • Are adjustments made for possible confounders?
  • Describe the estimated association
  • What measures of confidence or statistical significance are provided?
  • Describe whether a causal interpretation can be made
  • Are there identified side effects or interactions with other drugs?
  • Are there specific subgroups with different findings?
  • If the study is an animal study, which animal and how relevant is that model?
  • If it is a human study, what characteristics of the study population may support/limit extrapolation?
  • Summary of reliability
Sign up for free to join this conversation on GitHub. Already have an account? Sign in to comment
Projects
None yet
Development

No branches or pull requests

1 participant