rando2
commented
4 years ago Please provide 1-2 sentences introducing the study and its main findings
This study administered Standard of Care with or without HCQ to 150 patients (75 per group) at several hospitals in China. They did not find a difference between the two groups in negative viral status achieved by day 28. However, they did find that CRP levels of patients treated with HCQ were more likely to return to normal within the 28 day period. Additionally, patients who were administered HCQ in the absence of antivirals showed a reduction in symptoms during the 28 day period.
Study question(s) being investigated:
- Does administration of HCQ in addition to SOC to COVID-19 patients correlate with:
- Primary Endpoint: Viral clearance at day 28
- Secondary Endpoints:
- Viral clearance at days 4, 7, 10, 14, 21 as assessed with RT-PCR
- Normalization of clinical symptoms over 28 day hospitalization period, defined as 1) fever; 2) peripheral capillary oxygen saturation (spO2); 3) respiratory symptoms such as cough, sore throat, sputum production, shortness of breath
- Normalization of laboratory measurements at 28 days, including C-reactive protein, erythrocyte sedimentation rate, IL-6, TNF-α, complete blood cells count with differential, blood chemistry, coagulation panel, pulse oximetry, and respiratory symptoms.
- Additionally, adverse outcomes such as death (from any cause), days of mechanical ventilation, oxygen supplementation, and disease progression were also evaluated
How many/what drugs/combinations are being considered?
- HCQ vs no HCQ was what they were examining, but Standard of Care can include a range of other drugs, including antivirals
What are the main hypotheses being tested?
- Patients administered HCQ will be more likely to receive negative RT-PCR results (viral clearance) at day 28, or alternatively at intermediate endpoints.
- Alternatively:
- Patients administered HCQ will show improved clinical symptoms at day 28;
- Patients administered HCQ will show improved normalization of laboratory metrics at day 28
Study population:
- Adult patients (18+) in 3 Chinese provinces hospitalized for COVID-19 at hospitals capable of providing SOC according to certain guidelines.
- SARS-CoV-2 infection was confirmed with RT-PCR.
- Patients underwent chest CT scan to determine disease severity, which was used to balance assignment to the treatment and control groups.
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).
- 75 SOC (but one was accidentally given HCQ)
- 75 SOC + HCQ (but 6 were non-compliant)
For human studies:
What countries/regions are considered?
- China, 3 provinces: Hubei, Henan and Anhui
What is the age range, gender, other relevant characteristics?
- Mean age 46.1 years, standard deviation of 14.7. In HCQ group, mean = 48.0, sd = 14.1; in SOC only, mean = 44.1, sd = 15.0
- 54.7% male overall, 42/75 in SOC+HCQ and 40/75 in SOC-only
- Only two patients rated as having severe COVID-19 infections (assigned one to each group)
What is the setting of the study (random sample of school children, inpatient, outpatient, etc)?
- inpatient
What other specific inclusion-exclusion criteria are considered?
- Confirmed COVID-19 based on RT-PCR
- Patients were excluded if they were allergic to HCQ or had conditions that it could exacerbate (e.g., renal or liver disease)
- Pregnant and cognitively impaired individuals were excluded.
- All adults 18+
- 41 patients were evaluated and excluded
Treatment assignment:
How are treatments assigned?
- Patients were stratified according to disease severity (mild/moderate vs severe) and were then randomly assigned to treatment conditions. They printed off cards and put them in envelopes that were numbered sequentially. The corresponding envelope was opened each time a patient was recruited.
- I believe this study qualifies as interventional
- On average, randomization occurred at 16.6 days since infection
Is the study randomized?
- Yes, patient assignment to the conditions was randomized within disease severity categories (mild/moderate vs severe)
Provide other relevant details about the design.
- For HCQ, "loading dose of 1,200 mg daily for three days, followed by a maintained dose of 800 mg daily for remaining days (total treatment duration: 2 weeks or 3 weeks for mild/moderate or severe patients, respectively)"
- Multi-center study -- hospitals that were capable of meeting the SOC were invited to take part. I cannot find: a) whether ALL hospitals capable of meeting SOC were invited, b) how many hospitals accepted invitation, or c) the number of hospitals involved in the study. They were split across 3 provinces in China
- Age distribution (avg 46, sd 14) suggests population in study overlapped multiple age-related risk categories
- No masking and no placebo
- Most patients were administered drugs outside of the scope of the study, and post hoc analysis revealed that antivirals may well have confounding effects.
- 6 patients assigned to the SOC+HCQ condition did not receive HCQ due to either withdrawing or refusing the medication. One patient in the SOC condition received HCQ erroneously. These patients were reclassified for safety analysis but appear to have been left in their original assigned condition for other analyses.
Outcome Assessment:
Describe the outcome that is assessed and whether it is appropriate.
- 28 days seems like a reasonable benchmark for assessing viral clearance, but there isn't enough evidence to be sure. Another study reported the average duration of viral shedding was reported to be 20 days and the max observed to be 37 days since disease onset
- The study was originally designed to enroll 360 subjects (180 per condition) to provide adequate power, and this analysis is meant to present interim results at 7 days of treatment. However, they report that the "median duration of follow-up" was 20 vs 21 days in HCQ vs SOC-only, respectively, but it isn't clear if that means since they became sick, or since they enrolled in the study and began receiving treatment. It also seems that in terms of laboratory results, only CRP and blood lymphocyte count were analyzed here
- This appears to be a midpoint analysis using only preliminary data
- Disease progression was observed in two SOC patients and no HCQ+SOC patients during the study period
- I am concerned that t-tests for only two laboratory measures are reported, and the values are not reported for the assessments. Did they really only do these two tests, or are these just the two that look the best? The other concern is that they represent p=0.547 (for lymphocyte counts across the two groups) as a marginal p-value.
Are outcome measurements complete?
- 6 individuals in the HCQ+SOC group did not take HCQ and were reclassified for the safety analysis
- 1 individual in the SOC group received HCQ and was reclassified for the safety analysis
- They note that retinal damage as an adverse outcome may be under-identified in the present study
- They were not able to collect CT data for all of the patients by the deadline to assess changes after the treatment (SOC or SOC+HCQ)
Are outcome measurements subject to various kinds of bias?
- No placebo was given and the drug was unmasked.
- However, this study certainly has fewer biases than other COVID-19 HCQ studies available due to the use of randomization
Statistical Methods Assessment:
What methods are used for inference?
- Kaplan-Meier method on intention-to-treat population used to assess negative conversion rate
- Also analyzed with hazard ratio between the two groups, estimated with "Cox model"
- This was also used to assess secondary endpoints
- Two-sample t-test for comparing CRP levels & blood lymphocyte counts between groups
Are the methods appropriate for the study?
- I don't feel qualified to assess statistical methodology decisions related to survival analysis.
Are adjustments made for possible confounders?
- They performed post hoc analyses within subgroups to determine whether the following factors influenced outcomes: age, BMI, presence/absence of pre-existing conditions, days between disease onset and randomization time (defined as < or >= 7 days), baseline CPR level (defined as below/above upper threshold for normal), baseline lymphocyte count (below/above upper threshold for normal), with/without administration of antivirals during study period
Results Summary:
What is the estimated association?
- No difference in viral clearance at day 28 based on:
- Kaplan-Meier method
- SOC+HCQ: 85.4% with 95% CI 73.8% to 93.8%
- SOC: 81.3% with 95% CI 71.2% to 89.6%
- Hazard ratio not significant for viral clearance
- 0.846; 95%CI 0.580 to 1.234; P=0.341
- Median negative conversion time not significantly different
- 7 vs 8 days for SOC+HCQ vs SOC
- Kaplan-Meier method
- Secondary assessment of symptom alleviation also found no significant difference between groups
- Kaplan-Meier:
- SOC+HCQ: 59.9%, 95%CI, 45.0% to 75.3%
- SOC: 66.6%, 95%CI, 39.5% to 90.9%
- Median time to alleviation of clinical symptoms similar across groups
- SOC+HCQ: 19 days
- SOC: 21 days
- Kaplan-Meier:
- However, report that association seems to be increasing in second week of treatment
- Did not report statistics
- Additionally, report that controlling for antivirals post hoc reveals association between symptom alleviation and treatment
- Hazard ratio, 8.83 (95%CI: 1.09 to 71.3)
- No other subgroups associated with differences in post hoc analyses
- Report earlier recovery of CRP and blood lymphocyte count in HCQ group
- CRP: 6.986 versus 2.723 milligram/liter, P=0.045
- Blood Lymphocyte Count: 0.062 versus 0.008 ×109/liter, P=0.547
- Please note p-value reported for Blood Lymphocyte count, they indicate on the figure that it is not significant but imply in text that this is a real difference
- Other laboratory variables were not analyzed "due to very limited data of these parameters on pre-specified visiting date [sic]"
What measures of confidence or statistical significance are provided?
- Please see above
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."
- No. There is a suggestion in post hoc analysis that HCQ may help alleviate symptoms in mild/moderate cases, but this needs further investigation.
- They did find that CRP was reduced in HCQ group. I think cautiously this can be interpreted as causal (there may be other variables that should have been treated as confounds that I am also not considering)
Are there identified side effects or interactions with other drugs?
- HCQ is already known to carry risks. The study excluded individuals with liver or renal disease, but there are other concerns (e.g., retinopathy, heart problems-- e.g., see #160 )
- In the present study, they found that adverse effects were significantly more common in the SOC+HCQ group than SOC (30% vs 8.8%, p=0.001).
- Diarrhea was the most common averse effect (10% in SOC+HCQ versus 0% in SOC, P=0.004).
- Two patients had significant enough effects to stop treatment or change dosage (blurred vision & thirst, respectively)
Are there specific subgroups with different findings?
- HCQ may alleviate symptoms in patients who did not receive antivirals
Extrapolation of conclusions to other groups of individuals not specifically included in the study:
- These results are preliminary and warrant follow-up.
- Additionally, this study considers patients in three adjacent provinces in eastern China. Because HCQ's mechanism involves MHC and certain MHC alleles are more common in various geographic regions, I don't feel confident speculating whether geographic variation could influence HCQ response. I would need to look further into the mechanism.
If the study is an animal study, which animal and how relevant is that model?
- N/A
If it is a human study, what characteristics of the study population may support/limit extrapolation?
- Statistical association for alleviation of symptoms was not very strong, so hard to make conclusions about extrapolation
- Effect of HCQ on CRP should be tested in other populations (or someone who knows more about MHC variability and immune response can weigh in!)
- They did not test different doses. It sounds like they may be preparing a second report with more subjects over a longer time period.
- That they mostly focused on mild/moderate cases whereas other studies have emphasized more severe cases. Seems that this might be worth consideration in future studies.
- Most (but not all) samples for viral testing were taken from the upper respiratory tract, not broncheoalveolar lavage fluid, and the relative accuracy of these sampling methods was not known.
Summary of reliability
In contrast to the non-randomized Gauteret et al. (2020) study, this randomized (still no placebo and unmasked) investigation found no evidence that HCQ administration results in quicker viral clearance*. They did find some preliminary evidence that in the absence of other antivirals, HCQ was associated with quicker alleviation of symptoms, and that C-reactive protein normalized more quickly in patients in the HCQ+SOC group.
*As a note, only two patients in this study were administered azithromycin.
Title: Hydroxychloroquine in patients with COVID-19: an open-label, randomized, controlled trial
Please paste a link to the paper or a citation here:
Link: https://doi.org/10.1101/2020.04.10.20060558
What is the paper's Manubot-style citation?
Citation: doi:10.1101/2020.04.10.20060558
Please list some keywords (3-10) that help identify the relevance of this paper to COVID-19
Which areas of expertise are particularly relevant to the paper?
Questions to answer about each paper:
Please provide 1-2 sentences introducing the study and its main findings
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).
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?
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.