SHARE CTD

In a traditional RCT, we recruit an intervention group and a control group simultaneously.

In External Controlled Trials, the control group is sourced externally from:
1️⃣ Real-World Data / Electronic Health Records.
2️⃣ Data from previous clinical trials (Historical Controls).
3️⃣ Patient registries.

Why skip the internal control?
✅ Ethical Concerns: In rare or terminal diseases, giving a placebo can be unethical if an intervention shows early promise.
✅ Feasibility: nearly impossible to find data in an extremely small population.
✅ Efficiency: speed up the development of life-saving therapies

Beware of BIAS = our biggest enemy!
Since there’s no randomisation, we face "Confounding by Time." Is the patient doing better because of the new drug, or because the "Standard of Care" in 2026 is better than the historical data from 2015?

The takeaways:
1. ECT requires even more rigorous data cleaning.
2. Data Quality is King: Garbage in, garbage out. If your external source is messy, your trial is invalid.

3. Regulatory Alignment: Always consult with FDA/EMA/local regulators early if you plan to use an ECT for drug registration.

The world of clinical trials is evolving from rigid to "Pragmatic & Adaptive." ECT proves that past data can save future lives.

Have you ever worked with External Controls or Synthetic Arms? Let’s discuss below! 👇

#PeerOnSky #ClinicalTrials #ExternalControlledTrials #RealWorldEvidence

Hi #ScienceSky people, back with #PeerOnSky series! After discussing reporting bias, let’s dive into a topic that’s currently reshaping regulatory landscapes and drug development: External Controlled Trials (ECT). Ever heard of "Synthetic Controls" or "Historical Controls"? Let’s break it down!

Reusing clinical trial data to consolidate and advance medical knowledge While data sharing holds great potential to maximize the value of research and reduce waste, these benefits can only be fully realized if shared data are also effectively reused. Yet, data reuse remai...

This paper is fully aligned with the themes of our @sharectd.bsky.social doctoral network featuring stellar PhD students (such as @kahin-tai.bsky.social and @giulia-varvar.bsky.social with whom we have published several nice papers on data sharing).
a) www.jclinepi.com/article/S089...

@kahin-tai.bsky.social's excellent talk (delivered as part of the LORIER Webinar Series on Reproducibility and Meta-Research, in partnership with @sharectd.bsky.social, ResToRes Research integrity in biomedical research, OSIRIS, the @reproductible-fr.bsky.social and Embrace) is now online.

Over the coming days, three independent teams (@sharectd.bsky.social PhD students + clinical & statistical experts) will each conduct their own IPD meta-analysis to answer the same research question.
👉 Can esketamine reduce suicidality?

Stay tuned... I’ll share updates during the week. And @sharectd.bsky.social website is here : www.sharectd.eu

How do we fix this?
✅ Preregistration is King: Stick to your original protocol.
✅ SAP Transparency: Publish your Statistical Analysis Plan before unblinding.
✅ Report Everything: If it was a primary outcome in your protocol, it MUST be in your paper, regardless of the p-value.

The message for us is clear: Negative results are not "failed" results.

When we delete non-significant data, we:
1. Distort systematic reviews/meta-analyses.
2. Waste resources on "new" studies that have actually failed before.
3. Betray the trust of the participants who volunteered.

But here's the kicker: The omission was significantly more likely if the results were not statistically significant (p > 0.05)

The interviews revealed that the reasons aren't always malicious. It's often: the "it's not interesting" excuse; lack of clinical importance (as perceived by the author); inconsistency between the protocol and the final analysis.

Smyth (2010) interviewed trialists and found a troubling pattern. ORB isn't just a myth; it's a systematic issue where researchers tend to report "good" results while burying non-significant ones.

The study found that about one-third of trials had at least one primary outcome changed or omitted. 🚩

Frequency and reasons for outcome reporting bias in clinical trials: interviews with trialists Objectives To provide information on the frequency and reasons for outcome reporting bias in clinical trials. Design Trial protocols were compared with subsequent publication(s) to identify any discr...

Long time no see, #ScienceSky people! 👋 After a short hiatus, we're reliving the #PeerOnSky series.

A "silent" issue in clinical trials: Outcome Reporting Bias (ORB). Let's revisit a classic but vital paper by Smyth et al. (2010) that gets into the heads of trialists. www.bmj.com/content/342/...

Meta-analysis of individual participant data: rationale, conduct, and reporting The use of individual participant data instead of aggregate data in meta-analyses has many potential advantages, both statistically and clinically. Richard D Riley and colleagues describe the rational...

#PeerOnSky Article 2! "Meta-analysis of individual participant data: rationale, conduct, and reporting" by Riley et al. (2010). IPD boosts power for subgroups and adjusts for confounders. Read: doi.org/10.1136/bmj.... What challenges do you face in IPD meta-analyses? #OpenScience #MetaAnalysis

A must read work from our network. 👍

🔬 #PeerOnSky starts! “Clinical Trial Participants’ Views of the Risks and Benefits of Data Sharing” by Mello et al. (2018). They found participants value data sharing for science, but worry about privacy breaches. A 2018 perspective still relevant today! Does this reflect current views? #DataEthics

🎉 Hello all! Welcome to #PeerOnSky! It stands as 'Peer discussion on the Sky'. We will dive into cutting-edge research, sparking discussion on BlueSky using the articles discussed within our network. We’ll kick off with a 2018 gem on clinical trial data sharing. #OpenScience #Research #JournalClub

a must read article for the week!

BBQ under the rain

class dynamics

Gottingen City tour!

Group presentation

We worked heavily on coding and biostats exercises, and balanced it out with 'rainy' BBQ evening, City tours, and German/Italian feasts. Datathon1 had it all! 😍Big thanks to the organisers and all participants! #hackathon #OpenScience #ClinicalResearch #biostatistics

🌧️ Just wrapped Datathon1 at UMC Göttingen, from 07 to 11 July! Part of SHARE-CTD, this in-person event brought doctoral students, PIs, and lecturers together for clinical trials, biostats, and data mgmt. Check the Vibes! #SHARECTD #Datathon #Research #biostatistics

The paper @mrcctu.bsky.social offers 8 principles: proactively share results, give participants a choice, make it timely & accessible, involve patients in planning, and more. It’s a call to honor participants’ roles in research. So important for trust! #PatientVoice #OpenScience What do you think?

Sharing clinical trial results with participants: important, expected and possible - Trials Participants in clinical trials should be pro-actively offered the results of trials in which they have participated. This should be done in a way that is accessible and understandable for all partici...

💬 Participants deserve to know! This Trials paper (doi.org/10.1186/s130...) pushes for sharing clinical trial results with participants—because their contributions matter. From a patient’s view, it’s about respect & transparency. Let’s dive in! #ClinicalTrials #Transparency #ShareCTD

We are optimistic about this momentum! What do you think—can these 6 steps transform data sharing in Germany or globally? Share your views or tag a colleague. @sharectd.bsky.social is here to discuss! #ResearchEthics #OpenAccess #ShareCTD #DataSharing

The paper highlights barriers: low sharing rates, GDPR uncertainty, & researcher liability. Solutions include integrating data sharing in ethics applications, mainstreaming consent, & creating data clearing offices. A step toward patient benefit! #ClinicalResearch #Transparency

🔬 New paper alert! BMC study (doi.org/10.1186/s128...) proposes 6 solutions target ethics, registries, & governance to tackles Germany’s clinical data sharing crisis. Only 2% of medical research shares data—time for change! Read on! #OpenScience #DataSharing #ShareCTD

What's your take on this, guys? @cburgwinkel.bsky.social @giulia-varvar.bsky.social @minoo-matbouriahi.bsky.social @obinwanne.bsky.social @gregpapapostolou.bsky.social

Huge thanks for the shoutout, @floriannaudet.bsky.social ! 📊 This Nature paper on anonymization in biomedical research is spot-on for our mission at SHARE-CTD. Balancing data sharing with privacy is key—any thoughts on best practices? @kahin-tai.bsky.social @jifanw.bsky.social @yazidoxx.bsky.social