Shadowing Practice: Sequential, Multiple Assignment, Randomized Trial Designs With Dr Kidwell - Learn English Speaking with Video

Hello, and welcome to JAMA Evidence, our podcast series based on core issues in evidence -based medicine.

Today, we will be discussing sequential, multiple assignment, randomized trial designs.

I'm your host, Dr. Roger Lewis, statistical editor for JAMA and co -editor of the JAMA Guide to Statistics and Methods series.

I'm here with Dr. Kelly Kidwell.

Dr. Kidwell, thank you so much for joining us.

Can you go ahead and tell our listeners a little bit about yourself?

Sure.

Thank you so much for having me, Roger.

I'm Kelly Kidwell.

I'm a professor of biostatistics at the University of Michigan School of Public Health, and my expertise is in clinical trial design and analysis,

and in particular, the sequential multiple assignment randomized trials or SMART design.

Well, again, thank you so much for joining us.

So the name of this approach to a trial design is a bit daunting, so let's try to break it up a little bit.

So for each of those terms, can you go ahead and tell us what it means and then how we put it together in designing a clinical trial?

I completely agree with you that the vocabulary around smart design is quite daunting.

So what an excellent first question to start with.

So sequential is about a few things.

One is that we're interested in sequences of treatments.

And in this clinical trial design, we're going to have sequential randomization.

So those terms aren't next to each other, but that's really what's happening and defines this trial,

such that at least some group of participants will be randomized twice in sequence.

So usually there's some upfront randomization

and then a subsequent randomization for some group of participants based on their response to the initial treatment.

And so that multiple assignment comes into the fact that we'll have this sequential treatment assignment.

So individuals could be assigned to multiple treatments.

And this is all wrapped up in a clinical trial.

So we're going to use this SMART clinical trial tool to give us robust evidence for sequences of treatments

that adapt to individual responses or patient status.

So in contrast, in a traditional or a simpler clinical trial design.

We just randomize once, and then the patient either does well

or perhaps doesn't do so well on the treatment to which they are assigned.

And if they don't do well, we often have some sort of rescue therapy or they have to leave the trial.

So how is the experience of a patient or a participant different in a SMART design?

Right.

So in a general, standard, traditional randomized clinical trial, we're really looking at one point in time,

sort of this trial in a vacuum.

The SMART is going to say, let's look at that patient over the course of care.

So in a standard trial where you might stop collecting their data and treating them off trial if they didn't respond, we actually want to use that data.

And in fact, we might want to randomize the treatment to

which rescue therapy they're getting so that we can collect unbiased evidence

and use causal inference to better understand what the effect of that treatment is.

And not just that treatment, but the entire treatment sequence.

And so really for the patient,

it might not be too different than a standard trial because we're going to treat you over the course of your care.

But to the investigators, we're going to make sure that

that data is collected for our trial and there might be randomization for the treatment assignment that follows for that patient.

So, let's think a little bit about how we analyze or what we can learn from those two different approaches.

So in the first, we randomize at a single point in time, and if the patient doesn't do well,

they either drop out of the trial or we assign a rescue therapy.

Whereas in the SMART design, if they require a change in therapy, we actually randomize what we do.

So what's different about what we can learn from those two different approaches?

That's right.

Often in our standard clinical trial, in that one stage where the patient drops out or receives clinician or patient choice therapy,

we no longer make inference or have any decisions or really robust results about that subsequent treatment or their outcome.

Whereas in the SMART, by randomizing that individual and continuing to collect that data,

we will be able to have really robust evidence over the course of care, over the sequence of treatments

that could have adapted based on their response to allow us

to give these sequential guidelines to clinicians to treat the patient not just up front at one point in time,

but over time, and really tailor it to how they're doing, if they responded, if they adhered, if they engaged with that treatment.

So in a sense, this more closely follows what happens in actual clinical care,

where we make a series of treatment decisions based on the patient's prior response, but in this case, you're setting it up

so we can rigorously learn about what is the best next

thing to do based on what's happened to the patient so far.

Is that a fair summary?

Absolutely.

We are looking at a type of clinical trial that more closely mimics the way in which treatment is practiced.

And so that we can provide evidence for these treatment strategies

that adapt to individual's response or patient status in the way that we would actually treat them in practice.

Let's suppose that a SMART design is run and there's two points at which patients are randomized,

maybe the initial therapy and then after some defined period of follow -up.

What does the result look like in the publication that results,

and how can clinicians utilize the results of the SMART in guiding their own clinical care?

One of the amazing advantages of a SMART design is

that it can answer many questions as opposed to just what is the best treatment at one time.

We can think about what is the best treatment to begin with?

What is the best subsequent treatment for those who respond?

What is the best subsequent treatment for those who don't respond?

And then we can think about that entire sequence of, okay, so what do we start with?

How do we change?

When do we change?

For whom do we change and what treatment do we give them?

And so we can really get from SMARTS this sequence of treatments adapted to patient response.

Not only that, we can collect baseline information, so information up front at the start of the trial, and information about the patient and how they're doing with the treatment,

how they're adhering, how they're engaging, if they're having side effects,

and use that information to better tailor the treatment assignment to that individual so that after the trial, right, we have all this information.

And we can look at what are the best sequences of treatments for which particular individuals.

The fact that the SMART design more closely matches actual clinical care,

which the sequences of therapies we offer patients is informed by their responses to prior therapies is an obvious advantage.

But what are some of the limitations or challenges in either the implementation or the interpretation of a SMART clinical trial?

I think there are a few limitations and also just lack of knowledge of this design and its opportunities that it offers.

Some of the limitations are that individuals think, oh, now that we have multiple randomizations or multiple assignments in sequence,

this is now logistically infeasible, or you're going to lose more people if you have to consent multiple times.

So one thing is that we often just consent once at the beginning of the smart design.

and we may randomize multiple times.

Alternatively, you could randomize up front to that sequence that they may follow, whether they respond or do not respond.

So logistically, this doesn't have to be very difficult.

We also have lots of technology that helps us with complex trials, if you want to say that it's complex, although it's not.

Number two is that individuals are worried about bias coming into play from a smart design

because of these multiple randomizations and the subsequent randomization depending upon patient response or status.

100

This is not a concern because we do not compare these treatment pathways or you first get A,

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you respond and you continue versus you first get A, you do not respond and you switch to B.

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We're not going to compare those people.

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We know that they're different.

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One responded and one didn't, and we can have some issues if we do those comparisons.

105

We're looking at what we call adaptive interventions or dynamic treatment regimens that include that entire treatment sequence that's adapted.

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So start with A, and if you respond, continue.

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And if you don't, receive B.

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We're going to think about what are the effects of that entire sequence that's tailored to the response.

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Another misconception is that a SMART is an adaptive design.

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Usually a SMART is a fixed design, not an adaptive design, meaning

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that we're not going to use information from patients who have

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been through the trial to change the trial in some way for future patients.

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So we're not going to change randomization probabilities or eligibility criteria based on the information we've gained from the trial thus far.

114

What does happen in a SMART is that patients' treatment might change based on their own response.

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So there might be a within -person adaptation, but there's no between -person adaptation.

116

And so generally, these aren't adaptive designs.

117

Since we're trying to learn more from a clinical trial that's a smart design versus a traditional design

118

that just has a single point of randomization, it seems like we might need larger sample sizes to answer the additional questions.

119

What are the challenges, if any, with respect to sample size requirements for a smart design?

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If you see pictures of smart designs, they look a little bit intimidating because there's a fair amount of branching that occurs due to these sequential randomizations.

121

And often investigators are quite worried that we're going to require thousands of patients.

122

The thing is that to size a SMART is just like sizing any other trial.

123

And so it's really dependent on the primary aim, which can be similar to a standard one -stage trial and compare,

124

for example, the initial treatments.

125

Alternatively, the aim can be based on those embedded tailored sequences of treatments or the adaptive interventions.

126

And for those perhaps more patients may be required than a standard trial.

127

However, this really isn't an apples -to -apples comparison of a SMART design to a standard or traditional one -stage trial.

128

As I mentioned before, the questions

129

that we can answer in a SMART are much different and many more than we could with a standard design.

130

And so perhaps we may need more depending on the primary aim, but we're going to get a lot more information,

131

data, robust results, and more practical information that we can use after a smart design.

132

In your article, you discuss a study that was performed by Fortney et al that used a smart approach.

133

Can you tell us a little bit about what they did, what they found, and how they analyzed their data?

134

Sure.

135

So in this study, they had a design where individuals were sequentially randomized to better understand some effects of direct

136

and indirect telecare.

137

And what they did is they answered questions that are sort of more similar to one stage design.

138

So they said, okay, so what's the best first thing to start with?

139

And then subsequently, what do we do if individuals aren't responding well to that initial treatment or intervention.

140

So they haven't yet pieced together that full sequence.

141

It seems like that's subsequent analyses for this group in terms of figuring out,

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so what is the best overall sequences of treatment that can adapt to the individuals?

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While they answered those individually, what they could find when they move forward with the analysis of the adaptive intervention is

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that there might be interactions between the initial treatment

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and the subsequent treatment for

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which we can only really quantify in these types of SMART designs as opposed to individual randomized clinical trials.

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And so what they likely will subsequently do is look at

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that sequence of treatment over the course of the trial

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or those adaptive interventions to see if there are any interactions between the first step and the second step.

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I'm Roger Lewis, and I've been speaking with Professor Kelly Kidwell about sequential multiple assignment randomized trials.

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You can find a link to her article in this episode's description.

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This episode was produced by Daniel Musisi at the JAMA Network.

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To follow this and other JAMA Network podcasts, please visit us online at jamanetworkaudio .com.

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Thanks for listening.

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Bu dersin kelimeleri ve konuşma notları

Bu konuşma dersi “Sequential, Multiple Assignment, Randomized Trial Designs With Dr Kidwell” videosuna dayanıyor. En çok tekrarlanan kelimeler: treatment, trial, design, smart, patient. Bu videoda gölgeleme çalışması için 103 cümle ve 2153 kelime var. Konuşma bölümü 13:26 sürüyor. Konuşmacı dakikada yaklaşık 160 kelimeyle, günlük konuşmaya yakın doğal bir hızda konuşuyor. Kelimelerin %84’i İngilizcede en sık kullanılan 3.000 kelime arasında; geri kalanına başlamadan önce bakmakta fayda var. 103 cümlenin 18 tanesi soru; soru tonlaması ve kısa cevaplar için iyi bir alıştırma.

Bu videodaki önemli kelimeler

Videodan öğrenmeye değer 15 kelime, telaffuzu ve anlamıyla:

Kelime	Telaffuz	Anlam
subsequent sıfat	/ˈsʌbsɪkwənt/	takip eden, izleyen
adapt fiil	/əˈdæpt/	uydurmak, adapte etmek
collect fiil	/ˈkɑlɪkt/	katılmak, toplamak
intervention isim	/ɪntɚˈvɛnʃən/	müdahale
tailor isim	/ˈteɪlɚ/	terzi, dikici
rescue fiil	/ˈɹɛs.kjuː/	kurtarmak
compare fiil	/kəmˈpɛɚ/	karşılaştırmak, kıyaslamak
participant isim	/pɑːɹˈtɪsəpənt/	katılımcı, iştirakçı
consent fiil	/kənˈsɛnt/	gönül, rıza
subsequently zarf	/ˈsʌb.sɪ.kwənt.li/	akabinde, arkadan
podcast isim	/ˈpɑdˌkæst/	podcast
investigator isim	/ɪnˈvɛs.tɪˌɡeɪ̯.təː/	araştırıcı, araştırmacı
alternatively zarf	/ɔlˈtɝ.nə.tɪv.li/	alternativ olarak, ya da
occur fiil	/əˈkɜː/	olmak
summary isim	/ˈsʌm.ə.ɹi/	özet, fezleke

Duyacağınız deyimsel fiiller

Kelime	Anlam
figure out fiil	açığa çıkarmak

Tekrar etmeye değer cümleler

Videodan, günlük konuşmada yeniden kullanabileceğiniz kısa ve tam cümleler:

Let's try to break it up a little bit.
One is that we're interested in sequences of treatments.
We can think about what is the best treatment to begin with?
How do we change?
When do we change?

Bu videodaki dil bilgisi

Konuşmacının en çok kullandığı yapılar, videodaki sözcüklerin aynısıyla:

Yapı	Videoda
Edilgen yapı be + fiilin üçüncü hâli — kimin yaptığı değil, ne olduğu önemli	will be randomized · could be assigned · are assigned
İlgi cümlecikleri who / which + cümle — bir kişi ya da şey hakkında ek bilgi	those who respond · those who don · aim, which can

Dikkat edilecek telaffuzlar

Konuşmacı we're, they're, I'm gibi kısaltılmış biçimleri 44 kez kullanıyor. Bunları duyduğunuz gibi kısa söyleyin.

“sh” ve “zh” sesleri: intervention /ɪntɚˈvɛnʃən/, limitation /lɪmɪˈteɪʃən/, interaction /ˌɪn.təˈɹæk.ʃən/, adaptation /ˌæd.æpˈteɪ.ʃən/, contrast /kənˈt(ʃ)ɹæst/
Uzun kelimeler — vurguyu doğru yere koyun: intervention /ɪntɚˈvɛnʃən/, participant /pɑːɹˈtɪsəpənt/, limitation /lɪmɪˈteɪʃən/, interaction /ˌɪn.təˈɹæk.ʃən/, subsequently /ˈsʌb.sɪ.kwənt.li/

Türkçe konuşanların zorlandığı sesler:

/w/ — dudaklar yuvarlak, /v/ değil: sequence /ˈsiː.kwəns/, subsequent /ˈsʌbsɪkwənt/, whereas /(h)wɛɹˈæz/, subsequently /ˈsʌb.sɪ.kwənt.li/, requirement /ɹɪˈkwaɪɹmənt/
Kelime başındaki ünsüz kümesi — araya ünlü eklemeyin: whereas /(h)wɛɹˈæz/, practical /ˈpɹæk.tɪ.kəl/, statistical /stəˈtɪs.tɪ.kəl/, probability /ˌpɹɑ.bəˈbɪl.ə.ti/, clinician /klɪˈnɪʃən/
/æ/ — “e”den daha açık: adaptive /əˈdæp.tɪv/, adapt /əˈdæpt/, whereas /(h)wɛɹˈæz/, interaction /ˌɪn.təˈɹæk.ʃən/, podcast /ˈpɑdˌkæst/

Bu videoyla nasıl çalışılır

Videonun tamamını konuşmadan bir kez dinleyin ve bilmediğiniz kelimeleri not edin.
0,75× hızla başlayın, cümle cümle tekrar edin ve kolaylaşınca normal hıza dönün.
Kendinizi kaydedin ve orijinaliyle karşılaştırın; subsequent, adapt, collect gibi kelimelere özellikle dikkat edin.

Gölgeleme Tekniği Nedir?

Gölgeleme, başlangıçta profesyonel tercüman eğitimi için geliştirilen ve çok dilli Dr. Alexander Arguelles tarafından popüler hale getirilen, bilim destekli bir dil öğrenme tekniğidir. Yöntem basit ama güçlüdür: ana dili İngilizce olan bir sesi dinler ve hemen yüksek sesle tekrar edersiniz — konuşmacıyı 1-2 saniye gecikmeyle takip eden bir gölge gibi. Pasif dinleme veya dilbilgisi alıştırmalarının aksine, gölgeleme beyninizi ve ağız kaslarınızı gerçek konuşma kalıplarını eşzamanlı olarak işlemeye ve yeniden üretmeye zorlar. Araştırmalar, telaffuz doğruluğu, tonlama, ritim, bağlı konuşma, dinleme anlama ve konuşma akıcılığını önemli ölçüde geliştirdiğini göstermektedir — bu da onu IELTS Konuşma hazırlığı ve gerçek dünya İngilizce iletişimi için en etkili yöntemlerden biri yapar.

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Bu dersin kelimeleri ve konuşma notları

Bu videodaki önemli kelimeler

Duyacağınız deyimsel fiiller

Tekrar etmeye değer cümleler

Bu videodaki dil bilgisi

Dikkat edilecek telaffuzlar

Bu videoyla nasıl çalışılır

Gölgeleme Tekniği Nedir?