Author, Cate North: As a breast cancer survivor since 2000 and a clinical trial participant since 2018, Cate North is grateful to be thriving. She founded Stage 4 Living to inspire, reassure and educate people about protecting their health and living with greater meaning and purpose. Learn more at stage4living.com.
“You’ve got cancer” is one of the scariest things a person can hear.
And once that door is opened, it leads to a passageway filled with more scary doors—surgery, radiation, chemotherapy, insurance, side effects, and so on.
From my experience as a breast cancer fighter and survivor, I can assure you that any worries you face will subside once you understand them and believe in your own resilience. And if cancer proves anything, it’s how resilient we humans can be.
What I want to focus on is a new concern that may be brewing for some cancer patients, which is the use of big data and artificial intelligence (AI) in healthcare. If you have cancer or are caring for someone with cancer, you may be wondering about data privacy and security. And if you are a minority or part of an underserved community, you may be seeing more stories in the news about bias within these new systems that could leave you out of treatment opportunities.
These are valid concerns, yet I believe that AI and big data hold great potential to bring treatment hope and improve the quality of life for most cancer patients. I am writing this to help you better understand these new technologies and how they can enhance your treatment options.
Big Data—Artificial Intelligence (AI)—Machine Learning
Data, AI, and machine learning are interrelated and already working behind the scenes in many now-common activities, like asking Siri or Alexa a question or finding something to binge-watch on Netflix.
In case you’re unfamiliar with these concepts, a simplified explanation is:
Big data is the aggregation of many data sets. Artificial intelligence is programming that can help machines (essentially computers and digital devices that are connected to a network) continuously learn and understand what all that data means. In short, AI aims to find the needle in the haystack, the diamonds in the dirt.
And when it comes to data, it adds up to a lot of hay and dirt! According to the World Economic Forum, by 2025, 463 exabytes of data will be created each day globally. What the heck is an exabyte, you ask? It’s the equivalent of 212,765,957 DVDs.
And that much is accumulating. Every. Single. Day.
It’s hard to fathom something nearly unfathomable, which is where AI is so vital. It can be used to help scientists and doctors develop new drugs and treatment plans. More importantly, it can help all of us as cancer patients to receive more effective and personalized care.
About data privacy, security, and bias
With so much data being generated, you would think there would be big data breaches happening all the time. That’s not the case, but of course a breach can be devastating, which is why we must never let our data guard down. Thankfully, many smart people work in cybersecurity and data is governed by many laws and regulations, especially patient data. In the United States we have protections under the HIPAA Privacy and Security Rules. As for clinical trials, this is how the FDA handles patient data:
“Patient/subject IDs, as well as any other unique patient identifier (e.g., Social Security number), and patient contact information will be redacted;”
In my own experience as a current clinical trial participant, I am “known” only as a subject ID—a random number that represents me and my treatment progress.
The last link in patient data privacy and security is the patients themselves. Every person bears responsibility for monitoring and protecting their own data and not sabotaging themselves by sharing passwords, using weak passwords, and failing to safeguard paperwork like insurance claim forms.
As for bias in AI algorithms, it’s true that much of the patient data from clinical trials and other sources have been dominated by people who are relatively wealthy, well-educated, and white, and that must change. The antidote is greater representation across all groups, including minorities and other underserved communities. The FDA recently held a Patient Engagement Advisory Committee to discuss and make recommendations on AI and machine learning in medical devices in regard to biases and transparency. The reported comments centered on:
“The importance of including diverse patients from different demographic groups as well as with different diseases; the importance of the human connection when learning difficult diagnoses; the need to relay the diagnostic accuracy of the technology; and the need to have adequate resources to place diagnoses in context with clearly conveyed actions.”
I am sharing my own experience and writing and speaking on this topic because I believe that every cancer patient should have equal access to clinical trials.
Making your own decision
When it comes to choosing to participate in a clinical trial and contribute to the body of cancer treatment data, every patient needs to make an informed decision based on their own comfort level. But I encourage you to consider this: Are you apprehensive about clinical trials because of privacy concerns, while at the same time uploading pictures of vacations and children to social media or providing your DNA to ancestry and genetic testing sites or banking online? Because any information-sharing practice can compromise privacy and security. Please don’t draw your line in a way that could limit your cancer treatment options. When doctors and patients share their treatment progress with other doctors and patients, patterns can be detected, better decisions can be made, and new treatments can be developed.
I am a participant and supporter of clinical trials. I was fortunate that my clinical trial option was vetted and presented to me by my oncologist, who works in a university hospital setting. Not every cancer patient is so fortunate, which why tools like TrialJectory are so valuable. TrialJectory empowers all cancer patients by easing the clinical trial research process and matching them only to the best trial options for their situation.
The value of cancer patient data grows exponentially when it can be aggregated, analyzed, and compared. That’s why I encourage everyone to understand AI and big data and not be afraid of them. After all, once you hear, “you’ve got cancer,” you will discover how much strength and courage you have.
Ultimately, you have the right to decide whether you want your data to be added to the mix of clinical trial data. You can always say no, but don’t deprive yourself of the benefits you and other cancer patients could gain if you said yes.