New Paper (Therapeutic): Research Article JAK inhibition reduces SARS-CoV-2 liver infectivity and modulates inflammatory responses to reduce morbidity and mortality

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Title:

Research Article JAK inhibition reduces SARS-CoV-2 liver infectivity and modulates inflammatory responses to reduce morbidity and mortality

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

Link: https://advances.sciencemag.org/content/early/2020/11/13/sciadv.abe4724

What is the paper's Manubot-style citation?

Citation: doi:10.1126/sciadv.abe4724

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

• bariticinib
• jak inhibitor
• rheumatoid arthritis

Please note the publication / review status

• [ ] Pre-print
• [x] New Peer-Reviewed Paper
• [ ] Peer-Reviewed Paper Pre-2020

Which areas of expertise are particularly relevant to the paper?

• [ ] virology
• [ ] epidemiology
• [ ] biostatistics
• [ ] immunology
• [x] pharmacology

Questions to answer about each paper:

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

Bariticinib was found to reduce 71% (95% CI 0.15-0.58) mortality for 83 patients with moderate-severe SARS-CoV-2 pneumonia with few drug-induced adverse events, including a large elderly cohort (median age 81 years).

Study question(s) being investigated:

How many/what drugs/combinations are being considered?

1

What are the main hypotheses being tested?

Bariticinib as a therapeutic reducing mortality rate.

Study population:

601 patients were enrolled at the University of Pisa (n=179) and Albacete Hospital (n=422) cohorts

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

human study

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

After PS-matching procedure that reduce confounding, the remaining group involves:

• 74 patients at Pisa, with 37 treated with Bericitinib
• 92 patients at Albacete, with 46 treated with Bericitinib

In total, 83 cases and 83 controls.

For human studies:

What countries/regions are considered?

Italy, Spain

What is the age range, gender, other relevant characteristics?

Age: 66.0 (48.0-84.0)† cases, 65 (40-90) controls,

What is the setting of the study (random sample of school children, inpatient, outpatient, etc)?

What other specific inclusion-exclusion criteria are considered?

PS-matching

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?

no

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.

mortality

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.

• [x] 1-2 sentences introducing the study and its main findings
• [x] Describe How many/what drugs/combinations are being considered
• [ ] Describe the model system
• [x] What is the sample size?
• [x] What countries/regions are considered
• [x] 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