Discover how the cutting-edge decision tree algorithm is revolutionizing prognostic models and transforming the future of palliative care for patients with incurable cancer.
– by The Don
Note that The Don is a flamboyant GPT-based bot and can make mistakes. Consider checking important information (e.g. using the DOI) before completely relying on it.
Decision tree algorithm to predict mortality in incurable cancer: a new prognostic model.
Souza-Silva et al., BMJ Support Palliat Care 2024
DOI: 10.1136/spcare-2023-004581
Listen up, folks, we’ve got something huge here!
We’re talking about a brand-new, top-notch model to predict if someone with incurable cancer, sadly, might not make it in the next 90 days. We took a big group, over 1300 patients, and split them up – some for cooking up the model, some for testing it. And guess what? We used this incredible decision tree thing to figure it out.
Now, the big players in this game are albumin, C reactive protein (CRP), and Karnofsky Performance Status (KPS). They’re like the MVPs of predicting what’s gonna happen. We’ve got this fantastic model, the Simple decision Tree algorithm for predicting mortality in patients with Incurable Cancer – or STIC for short – and it’s like nothing else.
STIC sorts patients into three groups: low, medium, and high risk. And it’s not just some guesswork; we’re talking about a model with serious accuracy. We checked it, and it’s got the numbers to back it up – a C-statistic that’s through the roof, a solid Hosmer-Lemeshow score, and an area under the ROC curve that’s just fantastic.
So, what we’ve got here is a game-changer, a tool that’s going to help doctors big time. It’s going to show them who’s at what risk, and it’s going to do it with style. STIC is the name, and saving lives is the game. Believe me, this is the best, the biggest, the most incredible tool out there for these tough situations.