Investigating a framework to prioritize sources for updating the evidence base informing cancer symptom triage and management knowledge tools: a secondary data analysis

When a person receives a cancer diagnosis, the journey often involves managing a complex array of physical symptoms, from nausea and fatigue to pain and skin changes. For nurses and doctors, deciding how to respond to these symptoms requires up-to-date, reliable information. To help, researchers create "knowledge tools"—essentially trusted guides that synthesize the latest medical research into clear advice for daily practice. These guides tell healthcare workers when a symptom is mild enough to manage at home and when it requires immediate hospital attention. However, keeping these guides current is a massive undertaking. The medical world produces new studies at a staggering pace, and the people who maintain these guides must constantly search through thousands of new reports to find the few that actually change what they know. If they miss a crucial update, patients might suffer; if they spend too much time searching, the guides become outdated before they are even published. The challenge is finding a way to stay accurate without drowning in an ocean of data.

A team of researchers in Canada set out to solve this problem by examining how they update their own set of guides, known as the COSTaRS practice guides. These tools are used across the country to help nurses triage cancer symptoms over the phone, helping patients decide whether to stay home or go to the emergency room. The team wanted to know if they could make the process of updating these guides more efficient without losing any important information. They focused on four specific symptoms: diarrhea, constipation, fatigue, and mouth sores. In their most recent update, the team had to sift through a massive number of new documents. They found that the number of citations they needed to screen had grown from a few hundred in previous years to over 17,000 in 2024. This explosion of data was driven largely by a rapid increase in published "systematic reviews," which are studies that combine the results of many other studies to find a clear answer.

To test a new, faster approach, the researchers looked closely at the 59 new and existing sources they had used to update the four guides. They separated these sources into two main groups: clinical practice guidelines, which are comprehensive recommendations created by expert groups, and systematic reviews. The team then applied a strict set of rules to see if they could have arrived at the same conclusions by ignoring the massive database searches and focusing only on specific, high-quality sources. They asked three simple questions: Could they skip the database searches entirely? Could they ignore organizations that only produce one guideline and focus only on those that produce many? And could they ignore guidelines that did not meet a certain standard of quality?

The results showed that the team could have saved a tremendous amount of time without missing a single critical piece of evidence. They discovered that the systematic reviews they had found in the database searches did not offer any new information that wasn't already included in the clinical practice guidelines. In fact, every new recommendation found in a systematic review was already present in a guideline document. Furthermore, the team found that they could have skipped searching electronic databases entirely. By simply visiting the websites of known organizations that create these guidelines, they would have found almost all the necessary information. The few documents they found only in the database searches were either low-quality or duplicates of what they could have found by hand.

When the researchers applied their new prioritization framework, they realized they could have removed all 21 systematic reviews and seven specific guidelines from their list of sources. This would have left them with a much smaller, more manageable set of documents to review. The only things they would have missed were three very specific items: a recommendation to use acupuncture for constipation, a suggestion to check for mouth sores in patients with diarrhea, and a specific medication for a type of oral infection. These three items were minor exceptions in a sea of data. The study concluded that for these four symptoms, the most efficient path forward is to stop searching the vast electronic databases and instead focus on hand-searching the websites of reputable organizations that consistently produce high-quality guidelines.

This approach suggests that the medical community can reduce "research waste," which occurs when time and resources are spent on searching for information that does not actually add new value. By trusting the rigorous work of established guideline developers and skipping the redundant systematic reviews, the team demonstrated that it is possible to keep these life-saving guides current with far less effort. While this method worked perfectly for the four symptoms they tested, the researchers noted that it might need adjustment for rapidly changing fields, such as new cancer immunotherapies, where the landscape shifts too quickly to rely on established patterns. For now, however, the study offers a clear path to making the maintenance of medical knowledge tools more sustainable, ensuring that nurses and patients continue to receive the best possible care without the burden of an impossible search.