seanong.bsky.social
Sean Ong
@seanong.bsky.social
1K followers 170 following 86 posts
ID doc and joint PhD candidate at University of Toronto + University of Melbourne. Talk to me about clinical trial design and methodology, bloodstream infections, S. aureus, and Gram negatives 🦠 🇸🇬🇨🇦🇦🇺
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seanong.bsky.social
Sean Ong @seanong.bsky.social · 10d
"Addressing these challenges requires rethinking funding models, fostering equitable collaborations, and strengthening LMIC research leadership, trial capacity and infrastructure —not just as a matter of justice and equity, but as a necessity for global health security."
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seanong.bsky.social
Sean Ong @seanong.bsky.social · 10d
"Reduction in funding is likely to lead to reduced trial capacity, weakened surveillance, and delayed access to vaccines and therapeutics, and ultimately poorer global health outcomes."
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seanong.bsky.social
Sean Ong @seanong.bsky.social · 10d
High-income countries fund a large majority of clinical trials in ID, with the NIH in particular funding 20% of trials in our review. Current changes in funding (especially the de-prioritisation of global health amongst some funders) has major implications on ID clinical trials worldwide.
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seanong.bsky.social
Sean Ong @seanong.bsky.social · 10d
Our new paper in @cmijournal.bsky.social led by the brilliant Hadrien Moffroid, a junior colleague in Melbourne. We examined international funding flows in ID RCTs published in selected high-impact journals over a 10-year period.

doi.org/10.1016/j.cm...
@steventong.bsky.social #IDSky
Heat map of countries funding ID clinical trials and countries where ID clinical trials are conducted.
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Reposted by Sean Ong
josephmarcusid.medsky.social
Joseph Marcus @josephmarcusid.medsky.social · Jul 27
New post-hoc Camera-2 📷 post-hoc analysis out today regarding adherence to quality metrics in MRSA bacteremia.

Compared to similar non-trial population w/ MRSA bacteremia:
-No difference in 🪦, BUT
-non-trial had less following of quality metrics (see ⬇️)

#IDSky

jamanetwork.com/journals/jam...
Quality-of-Care Indicator Adherence and Mortality Outcomes in MRSA Bacteremia
This post hoc analysis of a randomized clinical trial investigates whether patient participation in clinical trials is associated with practitioner adherence to methicillin-resistant Staphylococcus au...
jamanetwork.com
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seanong.bsky.social
Sean Ong @seanong.bsky.social · Jul 18
This study was partly inspired after seeing a slide on @steventong.bsky.social's presentation about SAB trials at ESCMID 2024, after which we connected with the BACSARM and SAFO investigators to put this together. Conferences are a wonderful source of new project ideas and collaborations.
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seanong.bsky.social
Sean Ong @seanong.bsky.social · Jul 18
Glad to have the opportunity to collaborate with Spanish colleagues on this. We conducted a pooled Bayesian post-hoc analysis of the BACSARM and SAFO trials evaluating combination therapy with fosfomycin for SAB. The door may not be closed on adjunctive fosfomycin! Justifies need for more RCTs.
cidjournal.bsky.social
Clinical Infectious Diseases @cidjournal.bsky.social · Jul 17
Adjunctive Fosfomycin for the Treatment of Staphylococcus aureus Bacteremia: A Pooled Post-hoc Analysis of Individual Participant Data from Two Randomized Trials

✅ Just Accepted
#IDSky
Adjunctive Fosfomycin for the Treatment of Staphylococcus aureus Bacteremia: A Pooled Post-hoc Analysis of Individual Participant Data from Two Randomized Trials
The role of adjunctive fosfomycin in Staphylococcus aureus bacteremia (SAB) remains uncertain.
doi.org
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seanong.bsky.social
Sean Ong @seanong.bsky.social · Jun 26
This is a fantastic example of a Study Within A Trial (SWAT), incorporating research on RCT methods within a larger clinical trial. We are currently conducting a similar SWAT, SIMPLY-SNAP, which looks at the impact of simplified layered consent on recruitment to SNAP: doi.org/10.1136/bmjo...
Evaluating the impact of a SIMPlified LaYered consent process on recruitment of potential participants to the Staphylococcus aureus Network Adaptive Platform trial: study protocol for a multicentre pr...
Introduction Informed consent forms (ICFs) for randomised clinical trials (RCTs) can be onerous and lengthy. The process has the potential to overwhelm patients with information, leading them to miss ...
doi.org
seanong.bsky.social
Sean Ong @seanong.bsky.social · Jun 26
Thankful for another opportunity to write this editorial with @steventong.bsky.social in @jama.com: jamanetwork.com/journals/jam...

We discuss this trial, which evaluated the impact of different recruitment letter formats on RCT enrolment: jamanetwork.com/journals/jam...
Trials Within Trials—Optimizing the Delivery of RCTs
In the latest issue of JAMA, Johansen and colleagues1 report the results of a trial that investigated the impact of digital recruitment letter formats on recruitment to a larger clinical trial, the DA...
jamanetwork.com
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seanong.bsky.social
Sean Ong @seanong.bsky.social · Jun 16
8/ We tried to write this review in an approachable way for clinicians who may not be entirely comfortable with statistics. Hopefully it is useful to some folks.

In a follow-up paper, we applied the different methods described in illustrative post-hoc analyses of BALANCE and CAMERA2. Stay tuned!
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seanong.bsky.social
Sean Ong @seanong.bsky.social · Jun 16
7/ The nomenclature in the literature is inconsistent, and often mixes up outcomes, target parameters, and analytic methods. Confusingly, outcomes can be summarized using multiple different target parameters, which can be analyzed using multiple different methods. More than one way to skin a cat :)
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seanong.bsky.social
Sean Ong @seanong.bsky.social · Jun 16
6/ Importantly, we should look at whether odds are proportional (known as the PO assumption), or minimally that the direction of effect is consistent across all levels of the ordinal scale. As long as the effect is consistent (as opposed to discordant), the common OR is clinically interpretable.
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seanong.bsky.social
Sean Ong @seanong.bsky.social · Jun 16
5/ Parametric approaches can also be used for HCEs, commonly the proportional odds (PO) model. This estimates the common OR, interpreted as the odds a patient in one group has of being at least one step higher on the scale (i.e., having a better outcome) than a patient in the other group.
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seanong.bsky.social
Sean Ong @seanong.bsky.social · Jun 16
4/ This results in three summary numbers: total number of wins, losses, and ties. These numbers can be used to calculate different treatment effect estimates: win ratio, win odds, net treatment benefit, NNT, and probabilistic index. (Don't let the math scare you, it's simpler than it looks!)
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seanong.bsky.social
Sean Ong @seanong.bsky.social · Jun 16
3/ HCEs can also be analyzed using the generalized pairwise comparisons (GPC) method, where every patient in group 1 is compared to every patient in group 2 in all possible patient-pair combinations. A win is determined for each pair based on the hierarchical ordering of outcome components.
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seanong.bsky.social
Sean Ong @seanong.bsky.social · Jun 16
2/ Studies using DOOR are often analyzed using the Mann-Whitney U test, comparing distribution of ranks across groups. This estimates the probability that a randomly selected patient in group 1 has a better outcome to one in group 2 (AKA probabilistic index).

doi.org/10.1016/j.cm...
Redirecting
doi.org
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seanong.bsky.social
Sean Ong @seanong.bsky.social · Jun 16
1/ HCEs combine features of composite and ordinal outcomes: they combine multiple clinical events (composite), but are also hierarchical as they establish a rank order of clinical importance across the different component events. A common example in ID is the DOOR outcome, a specific type of HCE.
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seanong.bsky.social
Sean Ong @seanong.bsky.social · Jun 16
Our review on hierarchical composite endpoints (HCEs) has just been published in @cidjournal.bsky.social:
doi.org/10.1093/cid/...

We provide a conceptual overview of HCEs, explain the different associated target parameters and analytic methods.

@steventong.bsky.social @gurujosh.bsky.social
Making sense of hierarchical composite endpoints in randomized clinical trials – a primer for infectious disease clinicians and researchers
Hierarchical composite endpoints (HCEs) are increasingly being used in infectious diseases research. In this review aimed at educating the clinical reader,
doi.org
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Reposted by Sean Ong
germhuntermd.bsky.social
Ilan Schwartz @germhuntermd.bsky.social · Jun 13
Making sense of hierarchical composite endpoints in randomized clinical trials – a primer for infectious disease clinicians and researchers

@seanong.bsky.social @gurujosh.bsky.social @steventong.bsky.social and colleagues

Open Access #IDSky #MedSky

academic.oup.com/cid/advance-...
Venn diagram with one circle representing ordinal endpoints (eg WHO clinical progression score for COVID, modified Rankin scale, Glasgow outcome score, etc), another representing composite endpoints (eg time to death, treatment failure, or disease recurrence), and area of overlap (hierarchical composite endpoints, eg DOOR and extensions as seen in REMAP-CAP).
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seanong.bsky.social
Sean Ong @seanong.bsky.social · May 20
Honoured to be invited to write this commentary with @steventong.bsky.social, on an excellent target trial emulation study which showed that antibiotic use was not associated with improved outcomes in non-severe COVID-19.

jamanetwork.com/journals/jam...

#IDSky
Target Trial Emulation for Antibiotic Use in Acute COVID-19
This study by Pulia and colleagues1 reports results from a large population-based cohort using target trial emulation to examine the associations of antibiotic treatment with clinical outcomes in pati...
jamanetwork.com
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Reposted by Sean Ong
brxad.bsky.social
Bradley Langford @brxad.bsky.social · May 16
🆕 Evaluating BSI in Ontario we found #AMR was associated with a 10% ⬆️ risk of death equivalent to 1.2 deaths/100,000 people/year

These estimates are lower than those in previous literature, which may be due to robust adjustment for confounding

doi.org/10.1093/cid/...
@cidjournal.bsky.social
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Reposted by Sean Ong
cidjournal.bsky.social
Clinical Infectious Diseases @cidjournal.bsky.social · May 10
Evaluating Harms Associated With Prolonged Antibiotic Duration of Therapy in Community-Dwelling Older Adults: A Cohort Study Using Instrumental Variable Analysis

#IDSky
Evaluating Harms Associated With Prolonged Antibiotic Duration of Therapy in Community-Dwelling Older Adults: A Cohort Study Using Instrumental Variable Analysis
Shorter courses of antibiotic therapy are increasingly recommended to reduce antibiotic exposure. However, quantifying the real-world impact of duration of therapy is hindered by bias common in observational studies.
academic.oup.com
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Reposted by Sean Ong
germhuntermd.bsky.social
Ilan Schwartz @germhuntermd.bsky.social · May 9
Cefazolin vs Antistaphylococcal Penicillins for Treatment of Methicillin-Susceptible Staphylococcus aureus Bacteremia: A Systematic Review & Meta-Analysis

@connorprosty.bsky.social @seanong.bsky.social &c

Cefaz more effective, safer #idsky
www.clinicalmicrobiologyandinfection.com/article/S119... 🔓
Forest plot of 30 day all cause mortality which favors cefazolin (OR=0.73, 95%CI=0.62-0.85) Forest plot of discontinuation due to adverse effects which favors cefazolin (OR=0.13, 95%CI=0.06-0.27)
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seanong.bsky.social
Sean Ong @seanong.bsky.social · May 10
It's a reason some people might throw up to say the SNAP results don't apply to their setting... Because we only used (flu)cloxacillin in SNAP. So we did this SR/MA to try and address that.
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seanong.bsky.social
Sean Ong @seanong.bsky.social · May 7
But at the same time I recognize that every trial/study setting has a unique sociodemographic context, so there isn't a one-size-fits-all solution! And being overly prescriptive and mandating reporting may also be counterproductive. As with most things, a nuanced approach is best.
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