I’m currently sitting at National Institute of Health at a NCI workshop on hepatocellular cancer. I’m learning quite a lot, though I admit its like drinking from a firehose: HCC is a quite a serious disease, most patients diagnosed have a grim prognosis and while there are many different treatment modalities available, many will not provide long-term efficacy to most patients. There is a wide range of treatment modalities, including various surgical, radiology, and medical options, each of which have variable efficacy and challenging safety profiles. The treatments are being innovated fast-and-furious, and the HCC community is trying hard to maintain Level 1 (RCT) evidence to inform current practice, but many are challenged by having the research keep up with the innovations. I was struck by when listening to various presentations during the workshop: in a space where there are so many different treatments (which are used in various sequences or combinations) trying to improve survival for a serious disease and an urgent need to evaluate their comparative effectiveness of these alternatives, it seems an observational data network, like what we’ve built in OHDSI, can meaningfully support clinical practice by complementing the evidence being gathered by RCTs. It makes rational sense that RCTs in this space can only have dozens or perhaps a few hundred patients on any treatment arm, and its clear that the data demands for this type of oncology research is substantial. But there’s seems to be a wide range of unanswered questions that EHRs, registries, and claims could answer right away: questions on clinical characterization to summarize disease natural history and treatment utilization in current clinical practice; questions on patient-level prediction to identify which patients are at greatest risk of treatment toxicities or to respond to treatment; questions on population-level effect estimation to examine the comparative safety and effectiveness of alternative regimens.
To satisfy my own curiosity, I created this cohort definition (http://www.ohdsi.org/web/atlas/#/cohortdefinition/1769552) to allow me to identify how many patients I have within data I have access to, who have a first diagnosis of hepatocellular carcinoma with at least 2 years of medical history prior to first diagnosis. HCC is fairly rare, so I was surprised to see that I have patient records for >50,000 patients who satisfy this cohort definition across the databases I examined. Recognizing wholly the inadequacy of claims and EHR data, I’m excited by what would be possible to learn from such a large sample, given that this is 2 orders of magnitude larger population than what most HCC research seems to focus on.
My question to the community: is anyone out there interested in supporting the HCC community to better understand the disease and effects of the medical interventions to support these patients? If you have data, how many HCC patients do you have to learn from?
Assuming there is community interest, I hope we can leverage the OHDSI Oncology workgroup’s efforts, as was showcased at AMIA yesterday by @rimma, @mgurley, @rchen, @Christian_Reich, and others. It seems the HCC community would be a great place to realize the potential a true learning healthcare system.