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Call for collaborators / data partners on cardio-oncology study

Hi everyone,

I am looking for collaborators/data partners to work on a new study - to identify any suspected association between cardiotoxicity and anticancer treatments. The potential impact of any suspected associations will be explored in order to contribute to a benefit-risk balance between therapeutic gain and risk of cardiotoxicity, which can benefit cancer patients.

The study aims to investigate the frequencies of cardiotoxicity-related outcomes of interest following diagnosis index date in patients diagnosed with non-small cell lung cancer (NSCLC) and following start of anticancer treatments according to first therapy received; how different classes of drugs differ in their cardiotoxicity potentials in a selected type of cancer, i.e. NSCLC. Secondary objectives include describing the clinical characteristics of the overall cohort of patients with NSCLC at diagnosis date, describing different drugs’ combinations within first treatment of the overall cohort of patients with NSCLC at treatment date, describing the association between first treatment patterns (e.g. dose and duration) and cardiotoxicity-related outcome of interest, and identifying important risk factors for cardiotoxicity. Exploratory objectives include determining the associated healthcare cost from diagnosis date through till the end of follow-up period and the feasibility of determining the cost-effectiveness of different treatments included in the study.

I am searching for potential databases that can be used in this study. If you have any suggestions or experience with databases that would be suitable for this research question, I would be very interested in hearing from you!

Please reply here / DM me / contact me at stefanie.chanhy@gmail.com or h.chan7@herts.ac.uk.

Thank you in advance for your help!

Best wishes,

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Hi @StefanieChan , it’s great to see you raising this new study idea to the community. And since we’re in the midst of the Sisyphus Challenge (SOS Challenge – OHDSI), it’s great timing, as we’re walking step-by-step through how to conduct a network study. On week 1, @msuchard and @SCYou gave tutorials on how to initiate a study, including creating a Git repo and drafting your protocol so that others can review and determine their interest. Then last week, @clairblacketer @mvanzandt @sseager and @ljkaka showed how we can run database diagnostics to determine which data sources are potentially fit-for-use for a given question. These would be good next steps for you, and in particular, dbDiagnostics will help to clarify which sources have the required elements to potentially support exploration for specific anti-cancer treatments and specific cardiotoxic effects.

This week, we’re starting on the path of phenotype development and evaluation, which will be important to further solidify the definitions of the indication(s), exposures, and outcomes. I expect the tutorials this week by @aostropolets @agolozar @Christian_Reich and @Gowtham_Rao will be helpful for you in that regard.

I look forward to seeing your study move on the journey from idea to evidence!

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Hi @Patrick_Ryan , thank you so much for your advice!