Emily Oster

2 minute read Emily Oster

Emily Oster

Ask Emily: How Do I Separate Fact From Fiction on Cancer Treatments?

From Quartz: Ask Emily: How Do I Separate Fact From Fiction on Cancer Treatments?

Emily Oster

2 minute read

Dear Emily,

My wife has a pretty common problem: cancer. While we’re very fortunate that her brand of the condition (not-yet-metastatic melanoma) hasn’t led to any life-threatening complications just yet, we’re trying to be vigilant on any life changes or treatment protocols that might help her stave off development of her cancer.

We’re both open to alternative forms of treatment beyond what’s we often hear of (surgery, radiation, chemotherapy). But it’s distressing to find so little good information on alternative therapies out there in the world and online. There has to be some way to filter out what hard data exists from the scams and the hearsay that’s out there. With your background separating medical fact from fiction, could you provide any advice on how we could best perform our own research? Are there any tools or resources you’d recommend to people looking to try and find alternative treatments, but who aren’t willing to completely compromise on science and data?

–Bryan

First, I’m very sorry to hear about your wife’s illness and very much hope that complications stay away.

The question you ask is a good one and relevant to virtually anyone who faces any medical issues. Even digging into research on standard therapies can be daunting, and the evidence can be surprisingly uninformative. Moreover, the internet is the obvious place to look for information–but there is no shortage of misinformation there.  But this doesn’t mean you cannot make it work for you.

The basic approach I recommend is to prioritize your research according to the studies that will provide the best-quality evidence. Usually, this means looking for evidence from trials that were randomized and controlled. Such studies enroll a group of people and randomly assign some of them to receive a treatment, then compare their results to a randomly assigned control group. These types of trials are most likely to lead to firm conclusions about the cause and effect of different factors.

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