As a generalist internal medicine doctor having both inpatient and outpatient practice, I sometimes try to appraise RCTs on oncology about diseases and treatments that relate to patients I see on practice.
But, since they (RCTs) are so many with so many new drugs, it's hard. I think it's the area where I found more difficult to critically appraise the literature. I get mostly stuck on Q2 (++) and Q5. Since I'm not in the field, I don't know from all the infinite publications and RCTs which is the best control arm at the moment. Also, I never know if should rely on surrogates to OS (most of the times I simply don't rely on them).
Do you have some tips to overcome this two main problems?
For Q5 I came to know with this article that you published that systematic review in 2018, which can help. But still, I'll always have to go to the table to look for it and in 5 years some things could have changed.
And for Q2? How can I know the best treatment at the time? A good and reliable source or guideline would be helpful. For guidelines, well, as a generalist, I sometimes have to rely on them. But when I go deeper in the subjects (depending on the society and theme) they're many times flawed...hard times as Dickens wrote!
If the trial doesn't have a control arm it's useless. If it doesn't have a true placebo group, it's useless. If it's control arm is the previous drug this one wants to replace, it is useless. If the trial cites only the RRR or relative risk reduction, it is virtually meaningless.
Then again, in this modern day and age, how do we know that the trial results aren't coming from some chat-gpt program? They feed in the data and like magic chat spits out results giving us a miraculous new cancer drug. I trust no drug trials after the ModRNA substances trial fiasco. But it's fun reading your articles.
Thank you for this insightful guide! Navigating cancer clinical trials can feel daunting, but your concise tips make it accessible. Understanding trial data empowers patients and caregivers to make informed decisions. A valuable resource for all seeking clarity in a complex landscape.
Almost all, maybe all, of the questions (1-9) can be algorithmically emulated.
But it is not all clear whether the "development of judgment" can be emulated. 🤷♂️ By what method shall we determine that "good judgment" has been developed, continues to develop, or has ceased developing.
Thank you for all the valuable tips.
As a generalist internal medicine doctor having both inpatient and outpatient practice, I sometimes try to appraise RCTs on oncology about diseases and treatments that relate to patients I see on practice.
But, since they (RCTs) are so many with so many new drugs, it's hard. I think it's the area where I found more difficult to critically appraise the literature. I get mostly stuck on Q2 (++) and Q5. Since I'm not in the field, I don't know from all the infinite publications and RCTs which is the best control arm at the moment. Also, I never know if should rely on surrogates to OS (most of the times I simply don't rely on them).
Do you have some tips to overcome this two main problems?
For Q5 I came to know with this article that you published that systematic review in 2018, which can help. But still, I'll always have to go to the table to look for it and in 5 years some things could have changed.
And for Q2? How can I know the best treatment at the time? A good and reliable source or guideline would be helpful. For guidelines, well, as a generalist, I sometimes have to rely on them. But when I go deeper in the subjects (depending on the society and theme) they're many times flawed...hard times as Dickens wrote!
If the trial doesn't have a control arm it's useless. If it doesn't have a true placebo group, it's useless. If it's control arm is the previous drug this one wants to replace, it is useless. If the trial cites only the RRR or relative risk reduction, it is virtually meaningless.
Then again, in this modern day and age, how do we know that the trial results aren't coming from some chat-gpt program? They feed in the data and like magic chat spits out results giving us a miraculous new cancer drug. I trust no drug trials after the ModRNA substances trial fiasco. But it's fun reading your articles.
Thank you for this insightful guide! Navigating cancer clinical trials can feel daunting, but your concise tips make it accessible. Understanding trial data empowers patients and caregivers to make informed decisions. A valuable resource for all seeking clarity in a complex landscape.
Oh thanks ! As my job is Heath Technology Assessment (HTA), I mean ... almost every thing to assess ... your explanations were a great value !
Oh thanks ! As my job is Heath Technology Assessment (HTA), I mean ... almost every thing to assess ... your explanations were a great value !
"You need to develop judgement."
Almost all, maybe all, of the questions (1-9) can be algorithmically emulated.
But it is not all clear whether the "development of judgment" can be emulated. 🤷♂️ By what method shall we determine that "good judgment" has been developed, continues to develop, or has ceased developing.