The primary outcome was “time to clinical improvement within 28 days after randomization.” Clinical improvement was defined using a 6-point ordinal scale:
6 = death
5 = hospital admission for ECMO or mechanical ventilation
4 = hospital admission for non-invasive ventilation or high-flow oxygen
3 = hospital admission for regular oxygen therapy
2 = hospital admission but not requiring oxygen
1 = discharged or having reached discharge criteria
The statistical analysis, briefly, was as follows:
“The primary efficacy analysis was done on an intention-to-treat (ITT) basis with all randomly assigned patients. Time to clinical improvement was assessed after all patients had reached day 28; no clinical improvement at day 28 or death before day 28 were considered as right censored at day 28. Time to clinical improvement was portrayed by Kaplan-Meier plot and compared with a log-rank test. The HR and 95% CI for clinical improvement and HR with 95% CI for clinical deterioration were calculated by Cox proportional hazards model.”
Question: (Edited)
I am trying to understand why the outcomes appear to shift for the worse at Day 7, and then for the better at Day 14.
Is this just normal “noise” that we see in data early on in a trial?
Is it possible chance handed Remdesivir a slightly sicker group of patients at baseline?
Does Cox proportional hazards model take into account baseline differences?
Does this violate the proportional odds assumption?
Does this effect the optimal choice for a statistical model?
Is it possible the choice of outcome scale flawed?
My initial assumption is that this is just expected noise/variation in data at the early point of the study. But I thought I would ask others so they could offer expertise on how to best interpret & learn form this example.
worth noting clinical improvement defined as: “a decline of two levels on a six-point ordinal scale of clinical status (from 1=discharged to 6=death) or discharged alive from hospital, whichever came first”, also phrased as: "a two-point reduction in patients’ admission status on a six-point ordinal scale, or live discharge from the hospital, whichever came first. "
i guess they mean 2 levels or more, although im not sure what decline of 2 levels means on the scale you give above
One imbalance in risk factors from table 1 suggesting to me that sicker patients were in the placebo arm:
Hospitalized, needing invasive ventilation or ECMO.
-Remdesivir 125 (23%) | Placebo 147 (28%)
My understanding is that this risk factor is more substantially associated with death than any other.
Highlighting the source that prompts my concern for persons requiring mechanical ventilation: “Of those receiving mechanical ventilation, 17% (276/1658) were discharged alive, 37% (618/1658) died, and 46% (764/1658) remained in hospital.”
Features of 20 133 UK patients in hospital with covid-19 using the ISARIC WHO Clinical Characterisation Protocol: prospective observational cohort study https://www.bmj.com/content/369/bmj.m1985
Results The median age of patients admitted to hospital with covid-19, or with a diagnosis of covid-19 made in hospital, was 73 years (interquartile range 58-82, range 0-104). More men were admitted than women (men 60%, n=12 068; women 40%, n=8065). The median duration of symptoms before admission was 4 days (interquartile range 1-8). The commonest comorbidities were chronic cardiac disease (31%, 5469/17 702), uncomplicated diabetes (21%, 3650/17 599), non-asthmatic chronic pulmonary disease (18%, 3128/17 634), and chronic kidney disease (16%, 2830/17 506); 23% (4161/18 525) had no reported major comorbidity.
Overall, 41% (8199/20 133) of patients were discharged alive, 26% (5165/20 133) died, and 34% (6769/20 133) continued to receive care at the reporting date.
17% (3001/18 183) required admission to high dependency or intensive care units; of these, 28% (826/3001) were discharged alive, 32% (958/3001) died, and 41% (1217/3001) continued to receive care at the reporting date.
Of those receiving mechanical ventilation, 17% (276/1658) were discharged alive, 37% (618/1658) died, and 46% (764/1658) remained in hospital.
I had a question regarding the clinical interpretation of the common odds ratio. This is a segment of Table 3, with the results of the ordinal scale at day 28:
I realize that the CI for the common odds ratio is very wide, but let’s just assume the point estimate is valid for argument purposes. I think I would interpret it as follows:
If a patient started treatment requiring supplemental oxygen (3 on the scale), he has a 1.15x higher odds of being at a 2 on the scale 28 days later (being hospitalized, but not requiring supplemental oxygen).
How would the common OR change if I wanted to estimate the odds of a patient improving by > 1 point on the scale? Taking the example above, what are the odds the patient goes from a 3 to a 1 (discharged from the hospital)?
Also, @f2harrell mentioned how there is a major problem with the primary endpoint of clinical improvement.
This seems to be the main problem with ACTT-1 study as well right? The difference being that the common odds ratio in that study showed a significant benefit in favor of remdesivir.
As an aside note that only using the 28d result results in a power loss.
The OR doesn’t have to do with within-patient changes. If the OR is not covariate adjusted for initial ordinal state, then the interpretation is the ratio of odds for treatment B : A of being in outcome category y or worse, for any y other than the first. If it is covariate adjusted, then the OR responses the same ratio of odds but for a subject on treatment B with initial state x being compared to a subject on treatment A who is in the same initial state x.
