Owen Yang
If I could only give one piece of advice on clinicians who plan to start a disease cohort. This would be my advice: think big.
(Graph: Chat GPT’s interpretation of ‘sheep on Mars’)
Think big
To elaborate, I would hope that you start your disease cohort not as a one-off effort, but with an ambition to scale up into a disease registry. A neuroblastoma registry. A dementia registry.
As a one-off cohort, as a clinician you would likely be in a mindset of recruiting a convenience sample. You would focus mainly on achieving a total number. You would focus on the fanciest and costly measure you have for your cohort, such as images, genetics, or some molecular markers. You would have a make-shift excel file with inappropriate free texts, which would be fine at a starting stage but would likely to continue towards the end of your project. You do not invest in infrastructure and your personnels. You would not waste your time investing in yourself, either, because it is just a one-off effort.
A registry
A registry would be a vision to record everyone with the disease, or everyone with the more specific condition of your interest, such as patients treated with a special medication. Although it is a small cohort that you are starting with, you are thinking about escalating into a proper disease registry in the next five or ten years.
With a vision of a disease registry, you would think about collaboration. Only with collaboration can you collect all children with neuroblastoma in a country, or even in the world. When you go to a meeting or conferences, you would sell your idea and find your comrades, instead of presenting the p values that could be a factor of randomness. You would pay attention to other people’s methods but not results, because they are relevant to your next wave of recruitment, collaboration, or analysis.
With a vision of a disease registry, you would think as a decision maker, about what outcomes we would like to achieve for these patients. For patients with dementia, what are the range of outcomes that are the most relevant as individuals, as a society, or as a healthcare providers. For these relevant outcomes, you would remember to collect information so obvious that missing them would seem strange, such as their socioeconomic status, their lifestyle, and their physical and social function. You would be surprised that people can ignore them when they are measuring functional MRI or molecular markers in the CSF. You would also pay attention to the policy changes that may affect the welfare of your patients, and be advocate for them.
You would also be a good reviewer. When you review an academic manuscript, you would appreciate the data that has been generated by hard-working researchers with a big heart. You would not over-emphasise on the technical advance or selective publication of positive results. Instead, you would know that a well-designed behavioural trial to improve physical activity in 100 adolescents could be as important as a drug trial to achieve a rare disease outcome with number needed to treat at 1 in 300. You could be the advocate for these people in a grant committee, when short term return of investment is being discussed as if it is a cutting-edge concept.
Everything starts small
It is inevitable that everything starts small, but you can start to tell who is on your side, and who is there for surviving their scientific career.
